Tribological Condition Monitoring of Grease-Lubricated Rolling Element Bearings via The Development and Appraisal of Elemental Analysis Techniques
Paul Prendergast 20036082
Dissertation Submitted to The School of Engineering Waterford Institute of Technology
In Partial Fulfillment of the Requirements for the Degree of Master of Science in Innovative Technology Engineering
October, 2013
Abstract This dissertation presents works on the development of spectrographic multi-elemental analysis of grease lubricant based on rotating disc electrode atomic emission spectroscopy, the ultimate goal being condition monitoring of grease-lubricated rolling element bearings. Lubrication analysis provides the earliest indication of a systems’ health condition, allowing for advanced proactive failure prevention. Hence, lubrication analysis has become an integral part of condition monitoring programmes where proactive maintenance has benefits over predictive methods. The analysis of in-service oil lubrication is common place; on the other hand analysis of in-service grease lubricant is an extremely challenging task and is consequently largely underdeveloped. However, the requirement to determine the health of both the grease lubricant used and the equipment which it lubricates is becoming increasingly important, particularly for industrial sectors where unexpected failure has significant associated cost. The work focused on the development and appraisal of protocols that enable rotating disc electrode elemental analysis of grease lubricant using small volumes, and of lower cost than alternative methods. Based on the findings two application appraisals on industrial rolling bearing used in wind power generation and in rail transport were undertaken in order to investigate the influence of particle size and sampling location. 
Appraisal Study 1: Particle Size Influence - Conducted on wind turbine pitch bearings through a passive sampling approach.

Appraisal Study 2: Sample Location Influence - Conducted on rolling stock (rail vehicle) axle bearings through an active sampling approach.
The outcomes of the research undertaken point towards the potential of monitoring grease lubricant elemental conditions for the reduction of failure, validating the prospect for reducing potentially catastrophic bearing failures by improving failure prediction for grease-lubricated rolling element bearings.
ii
Acknowledgments The research presented was carried out in conjunction with Waterford Institute of Technology and T.E Laboratories, Carlow. I would like to express my sincere gratitude to all those who provided me the possibility to complete this research. Firstly, I would like to express my gratitude to T.E Laboratories, who enabled this research and provided me with the unique opportunity to embrace the world of tribology and for giving me the chance to study and work in a very challenging and knowledgeable industrial environment. In particular, I would like to thank Shane Moore for his advice and for sharing his experience and knowledge. I would like to express my appreciation to those companies that provided sampling material, access to equipment, and information: EcoPower Ltd., Iarnród Éireann (Irish Rail) and Spectro. Inc. A sincere thank you to my supervisor Dr. John O’Dwyer for his excellent guidance and wiliness to ensure throughout the project that everything was rolling! and for his initial encouragement to pursue this research topic and for initiating the process of collaboration with T.E Laboratories. To end I would like to thank my family and friends for their endless encouragement over the last year. A special thank you to Carol, for her support, interest she showed in my research and for her time proof reading.
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Declaration Tribological Condition Monitoring of Grease-Lubricated Rolling Element Bearings via The Development and Appraisal of Elemental Analysis Techniques Presented to: The School of Engineering Waterford Institute of Technology
This dissertation is submitted in partial fulfilment of the requirements for the Degree of Master of Science in Innovative Technology Engineering. It is entirely my own work and has not been submitted to any other college or higher institution, or for any other academic award in this college. Where use has been made of the work of others it has been fully acknowledged and fully referenced. Although every effort has been made to ensure the accuracy of the material contained in this dissertation, complete accuracy cannot be guaranteed. Neither the author, nor Waterford Institute of Technology or T.E. Laboratories accept any responsibility whatsoever for the loss or damage occasioned or claimed to have been occasioned, in part or in full, as a consequence of any person acting, or refraining from acting, as a result of a matter contained in this dissertation.
Signed:
___________________________ Paul Prendergast
Date: 1st October 2013. iv
Table of Contents Abstract ................................................................................................................... ii Acknowledgments ................................................................................................... iii Declaration ...................................................................................................................... iv Table of Contents ..................................................................................................... v List of Figures ................................................................................................................... ix List of Tables ................................................................................................................... xv 1.
Chapter 1. Introduction 1.1.
Introduction ....................................................................................................... 1
1.2. 1.3.
Primary Hypothesis ....................................................................................... 3 Problem Synopsis ............................................................................................... 4
1.3.1.
2.
Motives for the Research - In Summary ..................................................... 6
1.4.
Principal Aims and Objectives of the Research ................................................. 8
1.5.
Organisation of Dissertation .............................................................................. 9
Chapter 2. Grease as a Lubricant (Literature Review) 2.1.
Introduction ..................................................................................................... 12
2.2.
Comparisons of Grease versus Oil Lubrication ................................................ 12
2.3.
Grease Lubricant Definition ............................................................................. 14
2.4.
Grease Composition, Properties & Structure .................................................. 14
2.4.1.
Base Oil ..................................................................................................... 16
2.4.2.
Thickener .................................................................................................. 18
2.4.3.
Additives & Solid Filler .............................................................................. 21
2.4.4.
Grease Compatibility ................................................................................ 22
2.5.
Grease Lubrication Mechanism ....................................................................... 23
2.5.1. 2.6.
Phases in Grease Lubrication ................................................................... 25
Grease Life & Ageing ........................................................................................ 27 v
3.
2.6.1.
Grease Life ................................................................................................ 27
2.6.2.
Grease Ageing ........................................................................................... 28
2.7.
Impact of Contaminates in Lubricating Grease ............................................... 29
2.8.
Summary .......................................................................................................... 33
Chapter 3. Tribological Condition Monitoring of Grease Lubricants (Literature
Review) 3.1.
Introduction ..................................................................................................... 34
3.1.
Grease Condition Monitoring Overview .......................................................... 34
3.1.1. 3.2.
Grease Elemental Importance ......................................................................... 37
3.3.
Elemental Spectroscopy .................................................................................. 39
3.3.1.
Basic Operation of Atomic Emission Spectroscopy .................................. 40
3.3.2.
Atomic Emission Spectroscopy Comparison ............................................ 41
3.4.
Rotary Disc Electrode Atomic Emissions Spectroscopy ................................... 44
3.4.1.
Basic Operation of RDE-AES ..................................................................... 45
3.5.
RDE-AES Influencing Factors ............................................................................ 46
3.6.
Grease Elemental Analysis - Past Investigations Influence ............................. 48
3.7.
Sampling for Grease Analysis........................................................................... 52
3.7.1.
In-service Grease Sampling ...................................................................... 53
3.7.2.
Approaches for Grease Sampling ............................................................. 54
3.8. 4.
Grease Qualification Testing .................................................................... 37
Summary .......................................................................................................... 55
Chapter 4. Methodology for Grease Elemental Analysis by RDE-AES 4.1.
Introduction ..................................................................................................... 57
4.2.
Grease Elemental Analysis by RDE-AES Assessment ....................................... 57
4.3.
RDE-AES Protocol and Sample Preparation Methodology .............................. 60
4.3.1.
Protocol I - Blank Oil Dilution ................................................................... 61 vi
4.3.2.
Protocol II - Whole Grease Smear ............................................................ 62
4.3.3.
Protocol III - Solvent Dilution ................................................................... 63
4.3.4.
Protocol IV - Whole Grease Cup ............................................................... 64
4.4.
Data Analysis & Protocol Selection Criteria ..................................................... 64
4.4.1. 5.
Protocol Selection Criteria ........................................................................ 65
Chapter 5. Appraisal of Grease Elemental Analysis via the Development of RDE-
AES 5.1.
Introduction ..................................................................................................... 67
5.2.
Results of Appraisal of Grease Elemental Analyis by RDE-AES........................ 67
5.2.1.
Protocol-to-Protocol Elemental Comparison ........................................... 69
5.2.2.
Grease-to-Grease Elemental Comparison ................................................ 77
5.2.3.
Solvent Control Results ............................................................................ 78
5.3.
Discussion of Grease Elemental Analysis via the Development of RDE-AES ... 79
5.3.1. 5.4. 6.
Conclusion of Grease Elemental Analysis via the Development of RDE-AES .. 85
Chapter 6. Appraisal Study 1: Particle Size Influence 6.1.
Introduction ..................................................................................................... 86
6.2.
Comparative Grease Elemental Analysis Procedure, RDE-AES vs. ICP-MS...... 88
6.2.1.
ICP-MS Grease Elemental Analysis Procedure ......................................... 89
6.3.
Comparative Grease Elemental Analysis Results ............................................ 90
6.4.
Discussion & Validation of Particle Size Influence Investigation ..................... 94
6.4.1. 6.5. 7.
RDE-AES Grease Elemental Analysis Protocol Selection .......................... 82
Validation through Ferrographic Wear Particle Analysis ......................... 99
Conclusion of Appraisal Study 1 .................................................................... 115
Chapter 7. Appraisal Study 2: Sample Location Influence 7.1.
Introduction ................................................................................................... 117
7.1.1.
Detail of Bearings Appraisal Study 2 ...................................................... 119 vii
8.
7.2.
Analysis Procedure for Appraisal Study 2 ...................................................... 123
7.3.
Results of Investigation of Sample Location Influence .................................. 124
7.3.1.
Visual Inspection Findings ...................................................................... 125
7.3.2.
RDE-AES Grease Elemental Analysis Results .......................................... 129
7.4.
Discussion of Sample Location Influence Investigation ................................. 132
7.5.
Conclusion of Appraisal Study 2 .................................................................... 135
Chapter 8. Summary of Research & Recommendations for Future Work 8.1.
Introduction ................................................................................................... 137
8.2.
Summary of Works Completed...................................................................... 137
8.2.1.
Original Contributions of Research ........................................................ 141
8.3.
Review of the Limitations of Grease Elemental Analysis .............................. 142
8.4.
Recommendations for Future Work .............................................................. 143
References........................................................................................................... 146 Appendices .......................................................................................................... 151 A. Appendix A. Supplementary Information, on Grease Qualification Testing, Grease Compatibility and Grease Properties ........................................................................... 152 B.
Appendix B. Grease Solvent Investigation ............................................................ 156
C.
Appendix C. Grease Elemental Analysis by RDE-AES Results................................ 158
D. Appendix D. Ferrography ...................................................................................... 178
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List of Figures Figure 1-1: Illustration of Condition Monitoring Failure Detection Times ....................... 1 Figure 2-1: A typical schematic of the stribeck curve; the friction coefficient as a function of the lubrication parameter: ΡV/P referred to as the Hersey number. In this formula, Ρ is the fluid viscosity, V is the relative speed of the surfaces, and P is the load on the interface per unit bearing width [25] ............................................................................. 13 Figure 2-2: Typical Grease Composition ......................................................................... 15 Figure 2-3: Grease Structure Microphotograph Taken by Scanning Electron Microscope, at (A) a Lithium Grease with PTFE additives, at (B) a Bentonite Clay Grease. Adapted from [33] ......................................................................................................................... 16 Figure 2-4: Grease Categories ........................................................................................ 19 Figure 2-5: Phases in Grease Lubrication of Rolling Bearings. Adapted from [50] ........ 25 Figure 2-6: Influence of a contaminant on the pressure distribution in EHL line contact where u1 and u2 are the velocities of the surfaces [60] ................................................ 30 Figure 2-7: Illustration of Contaminate Type in Contact Zone [60] ............................... 31 Figure 3-1: Spectral Emission Lines of Iron [72] ............................................................. 40 Figure 3-2: Wear Particle Size Detection Stages [75] ..................................................... 43 Figure 3-3: Illustration of RDE-AES Operation. Adapted from [71] ................................ 45 Figure 3-4: Rotating Disc Electrode Spectroscopy [70] .................................................. 46 Figure 3-5: Active (Left) and Passive (Right) Grease Sampling Devices ......................... 53 Figure 3-6: Tube and Syringe Grease Sampling [87] ...................................................... 55 Figure 3-7: Grease Sampling from Seal [87] ................................................................... 55 Figure 4-1: RDE-AES Grease Analysis Protocols ............................................................. 57 Figure 4-2: Syringe for Grease Sample Preparation ....................................................... 60 Figure 4-3: Basic RDE-AES Configuration........................................................................ 60 Figure 4-4: Grease Samples Prepared in Disposable Specimen Cup .............................. 62 Figure 4-5: Protocol II (Whole Grease Smear) Prepared Disc Electrodes with Disposable Specimen Cup in Place.................................................................................................... 63 Figure 4-6: RDE-AES Flame Retarder for Low Flash Point Analysis for Protocol III ........ 63 Figure 5-1: Mean Plot of Elemental Data with 95% Confidence Interval - G1 ............... 69 Figure 5-2: Distribution of Data Iron-G1 ........................................................................ 70 ix
Figure 5-3: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G1 ......... 70 Figure 5-4: Means Comparison Chart Iron-G1 ............................................................... 70 Figure 5-5: Mean Plot of Elemental Data with 95% Confidence Interval – G2 .............. 71 Figure 5-6: Distribution of Data Iron-G2 ........................................................................ 72 Figure 5-7: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G2 ......... 72 Figure 5-8: Means Comparison Chart Iron-G2 ............................................................... 72 Figure 5-9: Mean Plot of Elemental Data with 95% Confidence Interval - G3 ............... 73 Figure 5-10: Distribution of Iron-G3 ............................................................................... 74 Figure 5-11: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G3 ....... 74 Figure 5-12: Means Comparison Chart Iron-G3 ............................................................. 74 Figure 5-13: Mean Plot of Elemental Data with 95% Confidence Interval – G4 ............ 75 Figure 5-14: Distribution of Data Iron-G4 ...................................................................... 76 Figure 5-15: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G4 ....... 76 Figure 5-16: Means Comparison Chart Iron-G4 ............................................................. 76 Figure 5-17: Grease-to-Grease Protocol Influence on Average Iron Recovery .............. 77 Figure 5-18: Grease-to-Grease Protocol Influence on Average Zinc Recovery .............. 77 Figure 5-19: Grease-to-Grease Protocol Influence on Average Sodium Iron Recovery. 78 Figure 6-1: Bellows-Type Grease Discharge Catcher on Bearing Discharge Port (Left). Extraction of Used Pitch Bearing Grease Sample from Bellows-Type Grease Discharge Catcher (Right) ................................................................................................................ 86 Figure 6-2: Location of Wind Turbine Pitch Bearings Shown with Nacelle Removed Adapted from [90] .......................................................................................................... 87 Figure 6-3: Image of a Pitch Bearing 3 Taken from Inside the Nacelle .......................... 87 Figure 6-4: Aqueous Grease Sample Solutions after Sulphated Ash Digestion ............. 90 Figure 6-5: RDE-AES vs. ICP-MS Comparison of Iron Elemental Analysis Result, a Wear Metal .............................................................................................................................. 93 Figure 6-6: RDE-AES vs. ICP-MS Comparison of Barium Elemental Analysis Result, a Stable Additive (Rust Inhibitor) ...................................................................................... 93 Figure 6-7: Ferrographic Blank Oil Dilution Preparations Indicating Colour Change as a Result of Particle Concentration Reduction Due to Serial Dilution. ............................. 101 Figure 6-8: Benign Rubbing, Dark Metallo- Oxides & Crystalline Particles (x200Mag.) ...................................................................................................................................... 103 x
Figure 6-9: Benign Rubbing, Dark Metallo-Oxides & Crystalline Particles Showing Iridescence (x200Mag. Cross Polarisation) .................................................................. 103 Figure 6-10: Severe Wear and Reworked Wear Particles & Benign Rubbing (x200Mag.) ...................................................................................................................................... 104 Figure 6-11: Severe Wear Reworked Wear Particle & Benign Rubbing (x500Mag.) After Heat Treatment ............................................................................................................ 104 Figure 6-12: Rolling Contact Fatigue Spall & Severe Wear (x200Mag.) ....................... 104 Figure 6-13: Rolling Contact Fatigue Spall (x500Mag.) ................................................ 105 Figure 6-14: Rolling Contact Fatigue Spall (x500Mag.) After Heat Treatment ............ 105 Figure 6-15: Severe Wear & Rolling Contact Fatigue Spalls (x200Mag.) ..................... 105 Figure 6-16: Severe Wear & Rolling Contact Fatigue Spalls (x500Mag.) ..................... 106 Figure 6-17: Severe Wear & Rolling Contact Fatigue Spalls (x500Mag.) After Heat Treatment ..................................................................................................................... 106 Figure 6-18: Fatigue Spall, Severe Wear & Benign Rubbing (x200Mag.) ..................... 107 Figure 6-19: Fatigue Spall, Severe Wear & Benign Rubbing (x200Mag.). After Heat Treatment ..................................................................................................................... 107 Figure 6-20: Fatigue Spall & Benign Rubbing (x500Mag.). After Heat Treatment ....... 108 Figure 6-21: Severe Wear & Heavy Benign Rubbing (x200Mag.). After Heat Treatment ...................................................................................................................................... 108 Figure 6-22: Severe Wear & Heavy Benign Rubbing (x500Mag.). After Heat Treatment ...................................................................................................................................... 108 Figure 6-23: Severe Wear & Dark Oxides (x200Mag.) .................................................. 110 Figure 6-24: Sliding Wear, Sever Wear and Dark Oxides (x200Mag.) .......................... 110 Figure 6-25: Sliding Wear, Indication Sliding striations (x500Mag.). After Heat Treatment ...................................................................................................................................... 110 Figure 6-26: Steel Alloy Severe Sliding Wear, Over Heated (x200Mag.) ...................... 111 Figure 6-27: Steel Alloy Severe Sliding Wear, Over Heated (x200Mag.). After Heat Treatment ..................................................................................................................... 111 Figure 6-28: Large Rolling Contact Fatigue Spall (x50Mag.) ......................................... 111 Figure 6-29: Large Rolling Contact Fatigue Spall, Top Right (x200Mag.) ..................... 112 Figure 6-30: Large Rolling Contact Fatigue Spall, Top Right (x200Mag.). After Heat Treatment ..................................................................................................................... 112 xi
Figure 6-31: Large Rolling Contact Fatigue Spall, Centre (x200Mag.) .......................... 112 Figure 6-32: Large Rolling Contact Fatigue Spall, Centre (x500Mag.) .......................... 113 Figure 6-33: Large Rolling Contact Fatigue Spall, Centre (x500Mag.). After Heat Treatment ..................................................................................................................... 113 Figure 6-34: Large Rolling Contact Fatigue Spall, Edge Crack (x200Mag.). After Heat Treatment ..................................................................................................................... 113 Figure 6-35: Deteriorated Re-worked Rolling Contact Fatigue Wear, Indication of Cast Iron (X200Mag.). After Heat Treatment ....................................................................... 114 Figure 6-36: Wear Particle Size Comparison of the Three Bearings (x200Mag.) ......... 114 Figure 7-1: AP Tapered Double Outer Ring Roller Bearing Components Adopted From [96]................................................................................................................................ 121 Figure 7-2: Five Sampling Points of Grease for Appraisal 2, Sample Location Influence (cross section view of bearing) ..................................................................................... 123 Figure 7-3: Bearing Outer Cup Condition, S1 (Left) and S2 (Right) .............................. 126 Figure 7-4: Visual Comparison of Grease from Outboard Seals of Bearing Assembly Note the visible levels grease degradation and variance in quantity of S1 in comparison to unused bearing grease of C2, C2 (Left) and S1 (Right) ............................................ 126 Figure 7-5: Cup Raceways Visual Inspection, S1 (Left) and S2 (Right) ......................... 126 Figure 7-6: Inboard Cone Assembly, S1 (Left) and S2 (Right)....................................... 127 Figure 7-7: Comparison of Control and Specimen Bearings, C1 (Left) and S1 (Right) . 127 Figure 7-8: Control Bearing C1, Inboard Cone Assembly ............................................. 127 Figure 7-9: Inboards Raceway Surface Damage to Unused Control Bearing, C1- Image to upper right taken at x10 Magnification of Surface Damage ........................................ 129 Figure 7-10: Comparative Distribution of Iron (Fe) in Grease for Bearings, S1 and S2 131 Figure 7-11: Comparative Distribution of Chromium (Cr) in Grease for Bearings, S1 and S2 .................................................................................................................................. 131 Figure 7-12: Comparative Distribution of Nickel (NI) in Grease for Bearings, S1 and S2 ...................................................................................................................................... 132 Figure B-1: Grease Solvent Testing............................................................................... 157 Figure C-1: Mean Plot of Elemental Data with 95% Confidence Interval - G1 ............. 159 Figure C-2: Distribution of Elemental Data - G1 ........................................................... 159 Figure C-3: Distribution of Data Iron-G1 ...................................................................... 160 xii
Figure C-4: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G1 ....... 160 Figure C-5: Means Comparison Chart Iron-G1 ............................................................. 160 Figure C-6: Distribution of Data Boron-G1 ................................................................... 161 Figure C-7: Mean Plot of Boron Elemental Data with 95% Confidence Interval-G1 .... 161 Figure C-8: Means Comparison Chart Boron-G1 .......................................................... 161 Figure C-9: Distribution of Data Phosphorus-G1 .......................................................... 162 Figure C-10: Mean Plot of Phosphorus Elemental Data with 95% Confidence Interval-G1 ...................................................................................................................................... 162 Figure C-11: Means Comparison Chart Phosphorus-G1............................................... 162 Figure C-12: Distribution of Data Zinc-G1 .................................................................... 163 Figure C-13: Mean Plot of Zinc Elemental Data with 95% Confidence Interval-G1 ..... 163 Figure C-14: Means Comparison Chart Zinc-G1 ........................................................... 163 Figure C-15: Mean Plot of Elemental Data with 95% Confidence Interval – G2 .......... 164 Figure C-16: Distribution of Elemental Data – G2 ........................................................ 164 Figure C-17: Distribution of Data Iron-G2 .................................................................... 165 Figure C-18: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G2 ..... 165 Figure C-19: Means Comparison Chart Iron-G2 ........................................................... 165 Figure C-20: Distribution of Data Calcium-G2 .............................................................. 166 Figure C-21: Mean Plot of Calcium Elemental Data with 95% Confidence Interval-G2 ...................................................................................................................................... 166 Figure C-22: Means Comparison Chart Calcium-G2 ..................................................... 166 Figure C-23: Distribution of Data Phosphorous-G2...................................................... 167 Figure C-24: Mean Plot of Phosphorus Elemental Data with 95% Confidence Interval-G2 ...................................................................................................................................... 167 Figure C-25: Means Comparison Chart Phosphorous-G2 ............................................ 167 Figure C-26: Distribution of Data Zinc-G2 .................................................................... 168 Figure C-27: Mean Plot of Zinc Elemental Data with 95% Confidence Interval-G2 ..... 168 Figure C-28: Means Comparison Chart Zinc-G2 ........................................................... 168 Figure C-29: Mean Plot of Elemental Data with 95% Confidence Interval - G3 ........... 169 Figure C-30: Distribution of Elemental Data – G3 ........................................................ 169 Figure C-31: Distribution of Iron-G3 ............................................................................. 170 Figure C-32: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G3 ..... 170 xiii
Figure C-33: Means Comparison Chart Iron-G3 ........................................................... 170 Figure C-34: Distribution of Sodium-G3 ....................................................................... 171 Figure C-35: Mean Plot of Sodium Elemental Data with 95% Confidence Interval-G3171 Figure C-36: Means Comparison Chart Sodium-G3 ..................................................... 171 Figure C-37: Distribution of Data Molydenum-G3 ....................................................... 172 Figure C-38: Mean Plot of Molybdenum Elemental Data with 95% Confidence IntervalG3.................................................................................................................................. 172 Figure C-39: Means Comparison Chart Molydenum-G3 .............................................. 172 Figure C-40: Distribution of Data Zinc-G3 .................................................................... 173 Figure C-41: Mean Plot of Zinc Elemental Data with 95% Confidence Interval-G3 ..... 173 Figure C-42: Means Comparison Chart Zinc-G3 ........................................................... 173 Figure C-43: Mean Plot of Elemental Data with 95% Confidence Interval - G4 ........... 174 Figure C-44: Distribution of Elemental Data – G4 ........................................................ 174 Figure C-45: Distribution of Data Iron-G4 .................................................................... 175 Figure C-46: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G4 ..... 175 Figure C-47: Means Comparison Chart Iron-G4 ........................................................... 175 Figure C-48: Distribution of Data Calcium-G4 .............................................................. 176 Figure C-49: Mean Plot of Calcium Elemental Data with 95% Confidence Interval-G4 ...................................................................................................................................... 176 Figure C-50: Means Comparison Chart Calcuim-G4 ..................................................... 176 Figure C-51: Distribution of Data Sodium-G4 ............................................................... 177 Figure C-52: Mean Plot of Sodium Elemental Data with 95% Confidence Interval-G4 ...................................................................................................................................... 177 Figure C-53: Means Comparison Chart Sodium-G4 ..................................................... 177 Figure D-1: Pitch Bearing 1 Ferrography Report Sheet ................................................ 178 Figure D-2: Pitch Bearing 2 Ferrography Report Sheet ................................................ 178 Figure D-3: Pitch Bearing 3 Ferrography Report Sheet ................................................ 179
xiv
List of Tables Table 2-1: American Petroleum Institute Base Oil Categories. Adopted from [37]. ...... 17 Table 2-2: NGLI Consistency Grades. Adapted from [42, 43] ......................................... 21 Table 2-3: Summary of Common Grease Additives ....................................................... 22 Table 3-1: Common Grease Condition Monitoring Analysis Methods .......................... 36 Table 3-2: Common Grease Elements and Potential Sources. Adopted from [16]........ 38 Table 3-3: Summary of RDE-AES Elemental Analysis in the Context of Grease Lubricant ........................................................................................................................................ 41 Table 3-4: Summary of ICP Elemental Analysis in the Context of Grease Lubricant ..... 41 Table 4-1: Grease Selection for RDE-AES Appraisal ....................................................... 59 Table 4-2: RDE-AES Parameters ..................................................................................... 61 Table 4-3: Summary of RDE-AES Appraisal Bounds ....................................................... 65 Table 4-4: Summary of Protocol Selection Criteria ........................................................ 66 Table 5-1: Protocol Designation ..................................................................................... 67 Table 5-2: Analysis of Variance for Iron - G1 .................................................................. 70 Table 5-3: Analysis of Variance for Iron – G2 ................................................................. 72 Table 5-4: Analysis of Variance for Iron – G3 ................................................................. 74 Table 5-5: Analysis of Variance for Iron – G4 ................................................................. 76 Table 5-6: Solvent Control Elemental Averages at 0 PPM and 100PPM Oil Standard ... 78 Table 5-7: RDE-AES Protocol Selection Considerations.................................................. 83 Table 6-1: Summary of RDE-AES and ICP-MS Particle Size Limitations .......................... 89 Table 6-2: ICP-MS Operation Parameters ...................................................................... 90 Table 6-3: RDE-AES Elemental Analysis Result, Pitch Bearing 1 ..................................... 92 Table 6-4: RDE-AES Elemental Analysis Result, Pitch Bearing 2 ..................................... 92 Table 6-5: RDE-AES Elemental Analysis Result, Pitch Bearing 3 ..................................... 92 Table 6-6: ICP-MS Elemental Analysis Result, Pitch Bearing 1 ....................................... 92 Table 6-7: ICP-MS Elemental Analysis Result, Pitch Bearing 2 ....................................... 92 Table 6-8: ICP-MS Elemental Analysis Result, Pitch Bearing 3 ....................................... 92 Table 6-9: RDE-AES vs. ICP-MS Relative Difference of Iron Elemental Analysis Results 93 Table 6-10: RDE-AES vs. ICP-MS Relative Difference of Barium Elemental Analysis Results ........................................................................................................................................ 94 xv
Table 6-11: Particle Concentration Classification used in Ferrographic Analysis ........ 102 Table 6-12: Particle Shape Classification used in Ferrographic Analysis ...................... 102 Table 7-1: Details of Axle Bearings in Appraisal 2 ........................................................ 120 Table 7-2: Summary of Visual Inspection of Specimen Bearings S1 and S2 ................. 125 Table 7-3: Bearing S1, Grease Elemental Distribution as a Function of Sample Location ...................................................................................................................................... 130 Table 7-4: Bearing S2, Grease Elemental Distribution as a Function of Sample Location ...................................................................................................................................... 130 Table 8-1: The Objectives of the Research were Establish as Follows ......................... 138 Table A-1: Grease Qualification .................................................................................... 152 Table A-2: Grease Compatibility Chart ......................................................................... 154 Table A-3: General Grease Properties. Adopted From [97] ......................................... 155 Table B-1: Solvents Solutions Used .............................................................................. 156 Table B-2: Grease Solvent Dilution Results .................................................................. 157 Table C-1: Analysis of Variance for Iron – G1 ............................................................... 160 Table C-2: Analysis of Variance for Boron – G1 ............................................................ 161 Table C-3: Analysis of Variance for Phosphorus – G1 .................................................. 162 Table C-4: Analysis of Variance for Zinc – G1 ............................................................... 163 Table C-5: Analysis of Variance for Iron – G2 ............................................................... 165 Table C-6: Analysis of Variance Calcium – G2 .............................................................. 166 Table C-7: Analysis of Variance for Phosphorous – G2 ................................................ 167 Table C-8: Analysis of Variance for Zinc – G2 ............................................................... 168 Table C-9: Analysis of Variance for Iron – G3 ............................................................... 170 Table C-10: Analysis of Variance for Sodium – G3 ....................................................... 171 Table C-11: Analysis of Variance for Molybdenum – G3 .............................................. 172 Table C-12: Analysis of Variance for Zinc – G3 ............................................................. 173 Table C-13: Analysis of Variance for Iron –G4 .............................................................. 175 Table C-14: Analysis of Variance for Calcium – G4 ....................................................... 176 Table C-15: Analysis of Variance for Sodium – G4 ....................................................... 177
xvi
1. Chapter 1. Introduction
1.1. Introduction The practice of condition-based maintenance has become a key strategy for all industries due to the industrial imperative to increase efficiency which has been aided by the technological improvements in detection methods and data analysis in addition to reduced cost of application. Condition-based maintenance is the contemporary way to achieve the requirements for enhanced productivity, cost reduction and improved operational safety. Condition-based maintenance offers superior performance for all critical equipment or components compared to other strategies: such as, run-to-failure maintenance and preventive maintenance. Condition-based maintenance strategies are commonly classified as being either predictive or proactive. Predictive maintenance is a process aimed at detecting a machine condition that will eventually lead to failure and then estimating the amount of time before failure occurs, whereas proactive maintenance involves aiming corrective action at failure root causes, not active failure symptoms and faults [1-4].
Figure 1-1: Illustration of Condition Monitoring Failure Detection Times
The application of condition-based maintenance in either a predictive or proactive regime, by methods such as; vibration and acoustic emission monitoring, thermography,
1
and tribology, enables better plant reliability, more accurate prediction of failures leading to fewer unplanned stoppages, reduced overall cost, and failure root cause identification. Bearing life calculations approaches are numerous due to fact that a number of proprietary approaches have evolved to predict bearing life, and these varying methods can provide significantly different predictions [5]. Bearing life in this work will take the following definition “length of time, or the number of revolutions, until a fatigue spall of a specific size develops. The spall size, regardless of the size of the bearing, is defined by an area 6 mm2�. As bearing life is defined by a material fatigue phenomenon, specific bearing life predications are impossible to precisely predict. Hence, the desire for condition monitoring of bearings and the determination of bearing rated life based on statistical distributions such as Weibull distribution for large populations of identical bearings. The most common method to describe bearing life assuming ideal conditions is L10 life, the life that 90% of a group of apparently identical bearings will complete or exceed a revolution cycle before the area of spalling reaches the defined 6 mm2 size criterion [5]. The focus of this research; which is the condition-based maintenance of grease-lubricated rolling element bearings, has traditionally been time-based in a preventative or planned maintenance approach. Taking the example of a grease-lubricated rolling element bearing having a L10 predicted life after 500,000 revolutions in a preventative time based replacement strategy would, result in 90% of the bearings replaced being in a completely acceptable condition. This conservative and expensive approach serves to illustrate the merits of adopting a condition-based maintenance strategy for grease-lubricated rotating machinery components. In other cases, condition-based maintenance of greaselubricated rotating machinery is normally only done in response to high bearing temperatures, noisiness, grease appearance, vibration signal analysis, and more recently through acoustic emission techniques. Taking the latter; vibration and acoustic emission techniques which are predominantly used in online applications for the detecting of bearing damage or faults [6, 7] can result in over or under greasing, depending on the periodicity of greasing, quantity added, operating conditions and run time of the machinery. Consequently, such methods often lead to costly failure as the condition of
2
the grease is not readily addressed. This may be unexpected as grease life is most often shorter than bearing life, and thus dominates service life [8]. Considering the situation before a fault has initiated, the main problems are determined by the grease lubrication situation within the rolling element bearing. Investigation by SKF Condition Monitoring [3] which classified the distribution of the causes of rolling element bearings failure before their calculated lifetime found that 84% of failures are a direct result of lubrication issues, such as contamination, starvation and ageing. The remaining 16% are maltreatment related issues such as misalignment, incorrect mounting, incorrect sizing, and vibration at stand still, causing fretting wear. Similar conclusions were drawn by VTT Technical Research [9] based on surveys carried out within industrial companies, concluding that the most prominent reason for bearing failures according to the survey was either; the lack of lubrication or lubricant failure. As such, the primary fault already exists in the bearing long before detection by traditional approaches. If a bearing is correctly sized, mounted correctly to correspond to the running and loading conditions, lubrication problems can be considered the earliest warning signal of the approach of failure. Intrinsically, tribological based condition monitoring of lubricants, including grease, enables the earliest possible identification of machine or component condition deterioration, refer to Figure 1-1. Based on the aforementioned the primary hypothesis of the research can be deduced. 1.2. Primary Hypothesis “ The condition assessment of used grease from a grease-lubricated rolling element bearing during its running indicates the earliest failure risks. The occurrence of contaminate debris is unavoidable, and the processes whereby these particles lead to fatigue and wear are known and if undetected lead to eventual component failure. By monitoring grease elemental conditions; the level of bearing wear, degradation and contamination can be assessed. Thus, the risk of premature failure of the bearing can be reduced while maximising lead time for predictive or proactive condition-based maintenance. �
3
1.3. Problem Synopsis The main role of grease in a rolling element bearing is to provide the rolling element ring contact with a lubricant to ensure a separation such that the bearing has a long life and low friction. Bearing life is increased as friction is reduced by the grease lubrication film separating the rolling elements from the bearing ring such that the roughness interactions are prevented [8]. Grease lubrication failures can lead to instantaneous or rapidly increasing damage of components, which as a result may ultimately culminate in breakdown and severe losses; the failure of a grease can therefore result in secondary costs far in excess of the value of the grease and the grease-lubricated component. Historically, tribological condition monitoring of in-service used grease has not been common practice even though the majority of installed bearings are grease-lubricated and have a substantial impact on the reliability of equipment. Key factors that have prevented tribological grease analysis include; requirement for large sample volumes, difficulties in obtaining a representative sample due to the non-uniform non-Newtonian flow of grease in the lubrication contact zones. However, recent progress in analytical techniques, has rendered the analyses of smaller samples to be more feasible. As illustrated by both Herguth [10] and Bots [11] along with the recent publication of standard sampling practice for obtaining used in-service samples of lubricating grease in ASTM D7718 [4] based on the works of Wurzbach [12-15], efforts to stream line in-service grease tribological condition monitoring it application has now gathered pace. It is now possible to analyse used grease samples of small volumes with confidence to allow tribological condition assessment. In traditional, tribological condition monitoring of oil lubricants, wear metals, additives and contaminant levels can indicate lubrication degradation and the condition of a machine or component of which it lubricates. The same is true of grease-lubricated systems; taking metallic elements as a prime illustration. With over a dozen metallic elements commonly present in greases; metallic elements can be present as: (i)
As additives for performance enhancements
(ii)
As a thickener component of the grease
4
(iii)
Or more importantly for grease condition monitoring present as: a. Contaminants b. or Wear metals
Determining the concentrations of elements presents in a grease can be a significant determining factor for the condition assessment of both the grease lubricant used, and equipment which it lubricates allowing ultimately for condition-based maintenance of grease lubricated components in both predictive, and proactive approaches. For lubricants, elemental concentration can be determined by elemental analysis through spectroscopy techniques split broadly between atomic absorption spectroscopy (AAS) and atomic emissions spectroscopy (AES). The latter, AES, has found more success in commercial tribological condition monitoring applications where both inductive coupled plasma (ICP) and rotary disc electrode (RDE) methods are most common, with particle size detection limits ranging from ~ 0.5 µm to 3 µm and ~ 3 µm to 10 µm respectively; each method having advantages and disadvantages. The size limitations of AES techniques can be addressed by analysis in conjunction with analytical ferrography, which has a particle size detection range from ~7 µm to 100 µm and is therefore a useful complementary technique to AES. Nevertheless, the wear detection methods outlined are not easily assimilated to grease due to its complex semi-solid matrix arrangement with a large range of consistency grades and significantly varied chemical composition; thus preventing straightforward analytical analysis by such methods. Consequently, there is a clear absence of research into in-service grease analysis for condition monitoring; including wear characterisation, lubricant degradation and contamination. This is despite the huge significance, that grease lubrication plays, and the vast range of testing procedures, used in manufacture; for qualification and performance testing of new grease, see Section 3.1.1, Chapter 3. Grease lubricants contain a vast amount of elemental information that may be applied to provide proactive detection on the earliest onset of failure due to wear, degradation or contamination. As a result, grease elemental analysis methods have been illustrated for instance by Fox [16] through ICP-AES were grease samples are brought to an aqueous solution by an acid decomposition process and earlier by Jones [17] through, an RDE-AES 5
blank oil dilution method. In addition, early grease ferrography studies have been reported by the U.S Naval Air Force [18] based on solvent preparation. Grease elemental analysis by ICP-AES as referred to was developed by Fox [16], and was standardised in 2006 and recently revised in 2012 in ASTM D7303 [19] as a standardised qualification test for unused grease. This method requires breaking down the grease structure by the use of an acid digestion processes prior to analysis, and as such the main disadvantage of this approach is the time required which renders the analysis very expensive and therefore restrictive when considering certain commercial applications for condition monitoring of used grease. Moreover issues with loss of volatile or reactive components of grease exists. Analytical methods for grease elemental analysis should enable the detection of all the elements likely to be encountered in typical applications e.g., wear metals, lubricant additives, thickeners and contaminants, with minimum sample preparation allowing for efficiencies. To address the problems with current methods and requirements mentioned above this research seeks to develop such a technique, based on RDE-AES elemental analysis of grease where limited published research on its application to grease currently exists. The development and appraisal of grease elemental analysis protocols through RDE-AES with minimised perpetration, represent a significant challenge, and if successful, would enable a number of important RDE-AES benefits to be realised for grease analysis. These benefits include, robustness, low analysis cost, faster throughputs and accuracy which may ultimately enable advanced failure prediction times for grease–lubricated rolling element bearings. 1.3.1. Motives for the Research - In Summary Elemental analysis of grease lubricants can yield excellent information permitting the determination of the condition of both the grease lubricant used, plus the equipment which it lubricates for condition-based monitoring strategies. The achievement of improved analytical efficiencies would permit increased application of grease condition monitoring, ultimately leading to increased productivity, cost reduction and operational safety for grease-lubricated components and therefore equipment; the goals of condition-based maintenance. 6
The application focus of this research is constrained to the concern of one grease lubrication application, grease-lubricated rolling element bearings. Yet, methods developed and accessed will hold applicability to various other areas of grease lubrication. The subsequent factors encapsulate the motives why research work must be carried out in the first place, and additionally to develop efficient elemental analysis of grease lubricants, and the rationale for research application constraints for grease-lubricated rolling element bearings: A. Rolling element bearings are the most widespread machine element after nuts and bolts [20]. Greases are the most common lubricants for rolling bearings, approximately 90% of all rolling bearings are lubricated with grease [10, 21].
B. Grease life is shorter than bearing life, and as a result it dominates service life. Additionally, as with bearing life grease life is not deterministic, there is no absolute value and thus it is given by statistical distribution based on empirical testing [20].
C. Research for root cause failure in grease-lubricated rolling element bearings has demonstrated that the majority of bearings failures before calculated fatigue lifetime, are a direct result of lubrication issues [3, 9].
D. The contaminants of the grease cannot be filtered away, in contrast with oil lubricated bearing applications, and thus grease lubricants retain a history of any contaminates, wear process etc. The accumulation of contaminants and wear metals in the vicinity of the contact zone, exacerbate the lubrication situation. Thus, effective monitoring can enable predictive or proactive condition-based maintenance.
E. On-line condition monitoring of the lubricating grease, although possible as shown in [22], can be very problematic and costly to carry out. This is because of
7
difficulties in obtaining representative grease samples from a fixed position where retrofitting presents the risk of negative influence on bearing life.
F. Grease lubricants contain a vast amount of elemental information that can be used to provide proactive detection, of the earliest onset of failure due to wear, degradation or contamination. This would include potential warning, if the recommended grease is being not being used; through comparison of metallic grease thickeners, or a comparison of the additive content between fresh and used grease [11].
G. Present standardised methods for elemental analysis of grease, ASTM D7303 [13] by ICP-AES are severely limited by preparation time, issues with loss of volatile or reactive elemental components of grease, low particle size range smaller than approximately 3 Âľm and limited elemental range when compared with RDE-AES. Moreover, is only applicable to new grease, as such no standard method of used grease elemental analysis exists currently.
1.4. Principal Aims and Objectives of the Research This study aims to develop and appraise tribological condition-based monitoring protocols for grease-lubricated components, with efficient elemental analysis based on RDE-AES principles. The core application focus of this research will be on the development of protocols for grease-lubricated rolling element bearings. The goal is to develop of RDEAES protocols that will consequently enable the long established benefits of RDE-AES of in-service oil, compared to alternative spectral analysis methods to be espoused to inservice used greases. The objectives of the present research are as follows: A. To study and develop efficient, protocol(s) for grease elemental analysis through, RDE-AES that enables the detection of elements likely to be encountered in typical applications, including wear metals, lubricant additives, thickeners and contaminants.
8
B. To determine the correlation between elemental analysis results and RDE-AES protocol(s) developed. Comparison of data and methods from different protocol(s) will illustrate the prospective disputes between protocol(s) established.
C. To examine the effects of particle size limitations on elemental analysis results, and as a consequence on the condition conclusions that may be drawn, in lubricating grease analysed through spectrographic analysis techniques, including that developed by RDE-AES.
D. To investigate the effects of sampling location on elemental analysis results, based on sampling locations within grease-lubricated rolling element bearings. Sampling will follow ASTM D7718 [4] sampling standard and RDE-AES protocol(s) deemed to be most applicable.
E. Inclusive validation and assessment of used grease RDE-AES elemental analysis protocol(s) developed based on the appraisal of data acquired, efficiency of data accusation,
and
appropriateness
for
commercial
applications,
and
accompaniment to additional tribological grease condition assessments methods.
1.5. Organisation of Dissertation This dissertation follows a chaptered framework with each chapter dealing with a different topic in relation to the project. Each chapter begins with a brief introduction to the subjects covered within. Similarly, each chapter ends with a summary or conclusion of the works presented in the chapter. The work presented in this dissertation are laid out as follows: • Chapter 1: The introduction presents the overview to the study, including relevant background by means of a primary hypothesis and problems synopsis. Likewise, the chapter specifies the motives for the need for the research and reasons for focusing on grease-lubricated rolling element bearings, as well as providing the dissertation organisation herein. 9
• Chapter 2: A literature review focused on grease as a lubricant; presents a convergence of current literature, with a focus on lubricant grease due to the significance in terms of the research. The chapter begins by providing an insight into grease; composition, properties, structure; lubrication mechanisms, life, ageing, degradation and reviews the impact of contaminates. The aim of the review is to provide the reader with an understanding of the background and the theory of lubricant grease in the context of research. • Chapter 3: A literature review concentrated on the tribological condition monitoring of grease lubricants by elemental means; the chapter is a grounded on understanding and underlying mechanism grease lubricant provided in Chapter 2. The focus of the review is on the exploration of the grease condition monitoring. As specified, in the beginning of this chapter the focus of the research is on the application of rotary disc electrode atomic emissions spectroscopy (RDE-AES) for grease condition monitoring through grease elemental analysis, and as such fundamentally forms the core of the review. The chapter identifies knowledge on its application together with research deficits which can be improved upon by the research proposed, where the worth to industry can be substantiated. The review concludes by highlighting the key influences on the proposed research and overviews current used grease sampling practice. • Chapter 4: Methodology for grease elemental analysis by RDE-AES; presents the research approach for the comparative appraisal of simultaneous multi elemental grease analysis, by RDE-AES through the four protocols. The chapter sets out the approach used for the appraisal, by outlining the data analysis approach and the selection criteria that will be used to discern which method is most applicable to condition monitoring of grease lubricants. • Chapter 5: The appraisal of grease elemental analysis by RDE-AES; presents, findings for the comparative appraisal of simultaneous multi element grease analysis by RDE-AES through the four protocols prescribed in Chapter 4. The chapter concludes with a discussion on the results and findings. The outcomes, knowledge and conclusions of which are subsequently applied to real condition monitoring applications, through application appraisal studies presented in the subsequent chapters. 10
• Chapter 6 and 7: Are dedicated to industrial application appraisal of grease elemental analysis by RDE-AES which is based on the findings of Chapter 5. The appraisal studies are set out as follows to investigate the influence of particle size and sampling location: - Chapter 6: Appraisal Study 1: Particle Size Influence, conducted on wind turbine pitch bearings through a passive sampling approach, where comparative elemental analysis findings are validated by ferrographic wear particle investigation.
- Chapter 7: Appraisal Study 2: Sample Location Influence, conducted on locomotive axle bearings through an active sample approach, where elemental analysis findings are correlated with a visual bearing inspection. Each appraisal study encompasses individual, analysis procedures, elemental analysis results, discussions and conclusions. • Chapter 8: A summary of research and recommendations for future work; is the final concluding chapter of the dissertation. The chapter classifies the main achievements of the research conducted, highlights the significance and contribution of the research, and recognises current limitations with appropriate recommendations being made for future work.
11
2. Chapter 2. Grease as a Lubricant (Literature Review)
2.1. Introduction The following chapter is a literature review of grease as a lubricant, the majority of which comprises of a substantial broad-spectrum examination of lubricant grease due to its significance in terms of the research. The objective is to deliver a review of the theory of grease lubricants in the context of, composition, lubrication mechanisms, life, ageing and degradation to provided background understanding for the research. The review ends with an exploration on the impact of contaminates in lubricating grease, before closing with a summary of the chapter that leads the reader onto the ensuing review chapter.
2.2. Comparisons of Grease versus Oil Lubrication Lubrication, whether it is with a lubricating grease or oil, the concentrations is on the same key principle: building an oil ďŹ lm between the two mating surfaces that move relative to each other, to separate the surfaces and prevent the surface asperities them from coming in contact. As previously classified with regards, to bearing life, in Chapter 1 by increased lubrication film separating the rolling elements increases life, as friction is reduced such that the roughness interactions of surface asperities are prevented. In general cases, of oil lubricated systems, lubrication film can be easily predetermined using a stribeck curve and classical Elasto-Hydrodynamic Lubrication (EHL) modelling [23]. A typical stribeck curve can be seen in Figure 2-1 which summarises the lubrication regimes by presenting the relationship between speed, load, oil viscosity, oil film thickness, and friction. Although presented originally by Kauzlarich and Greenwood [24] EHL modelling of grease lubrication, the predetermination is much more challenging [20] due to several functions playing a role. Although, the lubrication principles for greases and oils are alike, grease lubrication mechanisms is fundamentally more complex. This is reviewed in further detail in Section 2.5. The significant difference between the two, is the method by which the oil is supplied to the contact zone to provide a lubrication film. However, for a grease can only be 12
maintained if adequate oil can be provided; composition clarification and grease lubrication mechanism in Section 2.4 and 2.5 respectively will provide supplementary understanding of this statement.
Figure 2-1: A typical schematic of the stribeck curve; the friction coefficient as a function of the lubrication parameter: ΡV/P referred to as the Hersey number. In this formula, Ρ is the fluid viscosity, V is the relative speed of the surfaces, and P is the load on the interface per unit bearing width [25]
In short, lubrication oils often require multifaceted ancillary support equipment to condition, filter and deliver the oil to the contact zone, prevent leakage, and minimize contamination ingress. In comparison, lubricating grease delivers the oil via the thickener matrix and does not require axillary items listed. Grease lubricants are used in applications, whereby an oil lubricant would not provide sufficient protection, or could not be easily contained close to the point of application [26]. Grease is chosen as lubricant over oil for a variety of reasons; for additional illustration, it provides lower friction, is easily confined, provides sealing, and has a long lubricating life at low cost; grease can be expected to lubricate effectively over a wide range of conditions and for extended periods taking for example sealed for life bearings. The positive points made above are by no means exhaustive, but undoubtedly informative. General debate of grease versus oil is provided in more detail by Fitch [27]. To provide balance the key drawbacks are now emphasised. In grease-lubricated system, by and large, there is no flow in comparison to an oil lubrication system; therefore a number of drawbacks can be appreciated. Namely, as direct consequence of lack of grease flow, little to no cooling can be provided, leaving grease very susceptible to viscosity changes also 13
contaminates build up is common, as grease retains all contaminates unlike an oil. Furthermore, in contrast to oil as a result grease ageing becomes a bigger issue, which is reviewed in Section 2.6.
2.3. Grease Lubricant Definition Grease lubricant definitions vary slightly from source to source as can be appreciated in subsequently extracts. A grease can be defined as a solid to semi solid lubricant consisting of a dispersion of thickening agent in a lubricating fluid, Neale [28]. According to DIN 51825 [29], “lubricating greases are consistent lubricants which consist of mineral oils and/or synthetic oils as well as a thickener.” Grease is defined by ASTM D4175 [30] and National Lubrication Grease Institute (NGLI) [31] as “solid to semi solid product or dispersion of a thickening agent in a liquid lubricant. Other ingredients imparting special properties may also be included”. A more universal definition can be appreciated from the Society of Automotive Engineers (SAE International) [32], which define grease lubricants as “a thickener added to a lubricating oil to acquire the properties of a pseudoplastic solid capable of providing a local and stationary source of lubrication”
2.4. Grease Composition, Properties & Structure This section provides an overview focused on grease lubricants, which serve as a simple yet effective and convenient source of lubrication for a wide variety of applications, across a relatively large variety of operating environments. One of the main application of which is rolling element bearings as classified in Chapter 1, the application focus of this research. Consequently, modern greases vary extensively in terms of chemical composition, properties and structure to accommodate the large variety of applications. As an end result, the performance of grease lubricants greatly depends on the chemical composition and properties of the materials used in production. Understanding of such is crucial for the application of any condition based maintenance approach, including that proposed by the research. As can be inferred, from the definitions provided grease composition; comprises of three basic components that contribute to the multi-phase pseudo-plastic solid structure of lubricating grease; of a dispersive phase or a base oil and dispersed phase of thickener
14
and very commonly, in present greases, a additives or solid lubricants to enhance performance [33]. Typically grease component composition values ranges can be
Grease Composition
perceived in Figure 2-2.
Base oil (65 to 97 %) Thickener (3 to 35 %) Additives (up to 10 %) Solid Filler (up to 10 %)
Figure 2-2: Typical Grease Composition
As mentioned, it is primarily the base oil in the grease which provides the actual lubrication. Where the function of the thickener is to provide a physical matrix or structure to hold the base oil in a pseudo-plastic solid structure until operating conditions, such as load, shear and temperature, initiate viscoelastic flow in the grease. Under non stress conditions, the thickener holds the oil within its matrix, ready to be released to provide lubrication. To achieve this dispersive phase and dispersed phase matrix relationship, a careful balance of solubility between the base fluid and the thickener is required [34] which effects the grease properties. Which can be clarified by grease microstructure, according to Paszkowski [33] the mechanical durability and the stability of the microstructure of the thickener in a lubricating grease, determines the friction reduction, the protection of the lubricated surfaces, as well as the grease performance during the mechanical loading in the friction node. Which illustrates why the thickener defines the type of grease, which is reviewed further in Section 2.4.2. To return to detail on grease microstructure where additional detail can be seen in Paszkowski [33]. In reference to works cited by Lugt [8] and Paszkowski [33] the base oil is locked in the free spaces of the microstructure through the mechanical occlusion, the capillary phenomena as well as the molecular attraction, namely weak Van der Waals bonds between the 15
thickener and the polar components of the oil. Interactions in the dispersed phase between thickener molecules are dipole-dipole including hydrogen bonding or ionic and Van der Waals forces. The effectiveness of these forces depends on how these ďŹ bers contact each other, the thickener structure form cross-linked networks that give grease a consistency. The shape of the thickener particles and their surface topography can differ [33], resulting in different properties depending on the kind thickener used and the particles size. The thickener ďŹ bers can vary in length from about 1 to 100 Âľm and have a length to diameter ratio of 10 to 100. Scarlett [35] has shown this ratio correlates with the consistency of the grease for a given concentration of thickener. Illustration of grease structure comparison which can be seen in Figure 2-3.
(B)
(A)
Figure 2-3: Grease Structure Microphotograph Taken by Scanning Electron Microscope, at (A) a Lithium Grease with PTFE additives, at (B) a Bentonite Clay Grease. Adapted from [33]
In general terms, the grease thickeners matrix structure serves as a reservoir of lubricating base oil for future use, as well as a method to keep the oil in place in application, in addition to being one of the principle property determiners of grease. The ensuing sections will briefly detail grease composition in regards to components. Due to the diverse composition of grease lubricants the following section does not aim to address all subject matters, however substantial detail on the topics can be attained in Lugt [36] of which the following is in part refers to. 2.4.1. Base Oil A wide range of lubricant base oils are used in grease lubricants, as the base oil components of grease must offer a range of appropriate properties, in order to fulfil roles 16
in a wide range of applications. The most common base oils are mineral oils, that fall into three basic categories aromatic, naphthenic and paraffinic derived from the refining of crude oil and downstream petroleum raw materials. Of grease mineral base oils paraffinic oils are most commonly used, due to concerns about the carcinogenic aspects of the first two listed. The other major classes of grease base oils or synthetic oils, where the major difference between mineral oils is that synthetic oils have well defined molecular structures with well-defined molecular weight distribution, physical properties and chemical characterisation [36]. Similar to synthetic oil lubricants, greases with synthetic base oils may have possible advantages including, improved lubricity, oxidation stability and wider thermal operating range, with the major disadvantage being cost [1]. Polyalphaolefins and esters based synthetic oils represent the most common. Clarification between mineral and synthetic base oil is best seen by the American Petroleum Institute (API) base oil categories presented in Table 2-1. Where group I-III are classified as mineral oils and group IV and above as synthetic oils. Table 2-1: American Petroleum Institute Base Oil Categories. Adopted from [37].
Group Saturates
Sulphur Weight %
Viscosity Index
Process
I
< 90%
And / Or
> 0.03
80 - 119
Solvent Refined
II
> 90%
And
< 0.03
80 - 119
Hydro-Processed
II+
“> 90%”
And
< 0.03
100 - 119
Hydro-Cracked
III
> 90%
And
< 0.03
> 120
Severe HydroCracked
IV
Polyalphaolefins (PAOs) Group V – All other synthetics
17
Chemical Reaction
2.4.2. Thickener As previously, stated the grease thickener determines the primary properties of a grease, including consistency and oil bleed properties. As such, the grease thickener type is also used as the primary grease classifier; different categories as represented in Figure 2-4. There is large variety of grease thickeners used in grease lubricants widely defined between soap and non-soaps as per Figure 2-4. Cann [38] investigated the role of the grease thickeners in the lubrication process and concluded that; two different effects can be identified, indirect and direct. Respectively, indirect where the thickener influences oil release either through the oil retention properties and direct where the thickener augments the oil EHL film thickness. Grease thickener have been classified into three categories by Velykovsky cited by Ishchuk [39] based on their nature and interaction with the dispersion medium or base oil and thickening mechanism:
Polymorphic thickeners: whose interaction with the dispersion medium strengthens as they change over into high-temperature mesomorphic phases, i.e., thickeners that do not interact with oils at ordinary temperatures and colloidally disperse at elevated temperatures. Such thickeners include soaps.
Thickeners exhibiting no polymorphism: but melting at relatively low temperatures and forming homogeneous solutions with the dispersion medium at a temperature exceeding their melting temperature. These include solid hydrocarbons.
Non-dissolvable or heat-resistant organic and inorganic thickeners: not dissolving in the dispersion medium and not undergoing phase transformation with increasing temperature promoting their interaction with the dispersion medium. These include highly dispersible silica gels, carbon black, pigments, and clays.
18
Straight Li, Al, Ca, Na, Ba
Mixed Li, Al, Ca, Na, Ba
Soap
Complex Li, Al, Ca, Na, Ba Grease Thickner Clay Bentonite
Non-Soap
Polyurea
Others Silica Gels, Carbon Black, Pigments
Figure 2-4: Grease Categories
Of the grease categories listed in Figure 2-4 soap based are most common of which straight lithium soaps the most common at present. Soap based greases as shown in Figure 5 are split into three types of soap-based thickeners, straight or simple, mixed and complex. In general, there are two main processes used for producing lubricating grease; with the soap thickener, produced in situ within the lubricating fluid or base oil or with soap thickener or non-soap thickener added to the lubricating fluid or bass oil. Where saponification is the key process responsible, which can be simple resented through Acid + Base = Soap + Water [40]. Common acids include high molecular weight fatty acids: stearic and 12 hydroxy stearic acid; short chain complexing acids: tallow, azelaic and sebacic acid. Common bases as indicated in Figure 5 include lithium hydroxide, aluminium hydroxide, calcium hydroxide, sodium hydroxide, and barium hydroxide. Which are used to produce straight grease, such as lithium soap greases, calcium soap greases, sodium soap greases and aluminium soap grease etc. Where mixed thickeners can be formed by combinations for instance; one type of acid may be used with two different bases forming a mixed grease. According to Lugt [36] through the combination of a mixed grease, unfavourable qualities of straight soap can be compensated. The final soap grease category complex grease can be defined as soaps made by a conventional metallic soap in combination with a 19
complexing agent. In recent times, complex thickener-type greases are gaining popularity. They are being selected because of their high dropping points and excellent load-carrying abilities [41]. The most widely used grease is lithium complex soap grease, other example include calcium complex soap grease, sodium complex soap greases and aluminium complex soap grease. In brief, review of non-soap thickeners formed from either inorganic or organic thickeners where clay bentonite and inorganic thickener based and polyureas an organic grease are most common. Again greater detail can be found in [36]. The two other major classification means are firstly through NGLI grades; a numeric scale based on consistency of worked greases, which is based on ASTM D217 cone penetration or the distance in tenths of a millimetre, that a standard cone penetrates a sample of the grease under standard conditions at 25째C. NGLI grades, grease consistency ranges from 000 which is semi-liquid up to 6 which is a semi-solid. Refer to Table 2-2. NLGI grades 0, 1 and 2 are applied in highly loaded gear transmissions; grades 1 through 4 are often applied in rolling bearings where grade 2 is the most common. Secondly, the dropping point of a grease is the temperature at which the grease changes from semi-solid to a liquid. The dropping point establishes the maximum useable temperature of the grease, which is typically set at 50 째C to 100 째C below the experimentally determined dropping point. The dropping point indicates the upper temperature limit at which a grease retains its structure, not the maximum temperature at which a grease may be used [41].
20
Table 2-2: NGLI Consistency Grades. Adapted from [42, 43]
NGLI Grade
Usage
ASTM â&#x20AC;&#x201C; Worked Penetration
Consistency
000
445-475
Highly fluid to fluid
Softest grease. Just enough thickener to keep the oil from running out. Gear case lubricant.
00
400-430
Fluid
Gear case lubricant.
0
355-385
Semi-fluid
Low temperature in centralised lubrication systems.
Very soft
Needle and multiple row roller bearings. Low temperature operation in centralised lubrication systems.
1
310-340
2
265-295
Soft
Ball and roller bearings, moderately loaded and medium speed applications. Most common grease grade.
3
220-250
Relatively consistent
Wheel bearings, precision and high speed use.
4
175-208
Consistent
High speed, lightly loaded applications. Water-pump grease
130-160
Very consistent
Very stiff grease. Also used in highspeed applications. Rarely seen in modern equipment
Hard
Solid-type grease. Pillow-block lubrication. Rarely seen in modern equipment.
5
6
85-115
2.4.3. Additives & Solid Filler Additives are commonly added to grease lubricants for similar reasons as oil lubricant and play several enhancement roles in a lubricating grease performance as shown in Table 2-3. They primarily include enhancing the existing desirable properties, suppressing the 21
existing undesirable properties, and imparting new properties. The most common additive classes are anti-oxidants and rust inhibitors, extreme pressure, anti-wear, and friction-reducing agents. In addition, to these additives, solid fillers or boundary lubricants such as molybdenum disulfide or graphite may be suspended in the grease to reduce friction and wear without adverse chemical reactions to the metal surfaces during heavy loading and slow speeds. Polymers are another common ingredient in modern grease, providing manufacturers the ability to tailor finished grease performance characteristics. The incorporation of polymers can build base oil viscosity, and can provide enhanced film strength, tack, water resistance and reduced oil separation to the finished grease. Various additives and solid fillers are playing an ever increasing role in grease lubricating applications. Table 2-3: Summary of Common Grease Additives
Additive or Solid Filler Anti-oxidant
Function Retard oxidation of base stock for longer lubricant life Rust Inhibitor Protect ferrous surfaces from rusting Antiwear Provide wear protection during boundary lubrication Extreme Pressure Provide protection during high load and shock loading conditions Tackifiers/Polymers Enhance water resistance and metal adhesiveness Molybdenum Disulfide, Graphite, Zinc Solid lubricants providing protection and Oxide, Teflon, Polyethylene friction reduction under high load/sliding conditions at low speeds 2.4.4. Grease Compatibility The NGLI [44] defines grease incompatibility as: â&#x20AC;&#x153;Two lubricating grease when a mixture of the products shows physical properties of service performance which are markedly inferior to those of either of the grease before mixing. Performance or properties inferior to one of the products inferior to one of the products and superior to the other may be due to simple mixing and would not be considered as evidence of incompatibilityâ&#x20AC;?.
22
Mixing of incompatible greases can cause significant changes in lubrication performance and can lead to failure of the grease lubricant, and ultimately the grease-lubricated system. Generally the mixing of incompatible grease results in consistency of the grease or NGLI grade as classified in Section 2.4.2 altering from the normal state. Consistency changes, can result in loss of consistency, thinning of the grease or hardening of the grease lubricant both situation can cause serious issues. Mixing of incompatible grease may also affect the dropping point of the grease and or oil bleed rate, the significance of oil bleed in terms of grease lubrication mechanism is outlined in the following section. See Table 0-2, in Appendix A for a general grease compatibility chart. Additionally, Table 0-3, Appendix A provides an overview of general grease properties broken down by categories.
2.5. Grease Lubrication Mechanism As introduced, in Section 2.2, compared to oil lubrication mechanism; grease lubrication mechanism is far more complex; the grease lubrication mechanism is altered for different, speeds, temperatures and even bearing types. Despite the overwhelming importance of this subject, very little is known about the mechanisms of grease lubrication according to Cann [45]. Regardless it is definite that grease provides lubrication for components including rolling bearings that is sufficient to prevent continuous contact surface asperities causing server friction and wear. However, there is no consensus on the lubrication mechanisms in grease lubrication [8]. As categorised earlier, EHL modelling of grease lubrication for the predetermination of lubrication film thickness is much more challenging. Generally it is understood that the lubrication film thickness changes over time within a grease-lubricated system, which results in a limited time in which a grease lubricant can provide adequate lubrication, termed grease life. As such, grease life plays an imperative role in grease lubrication mechanism and in-turn relates to condition maintenance approach proposed as revealed in Chapter 1; grease life is shorter than bearing life. Grease life is reviewed further in Section 2.6 where factors effecting grease life are presented. Considering the interactions between the base oil and thickener determines the main properties, including flow or rheology, of the grease thus
23
lubrication performance, it is comprehensible to accept the inconclusiveness of the literature on grease lubrication mechanisms. There is clear distinctions between conclusions drawn on grease lubrications mechanism where for instance Lansdown and Gupta [46] concluded that it is the whole grease that is responsible, not just the base oil bled from the thickener structure. Whereas suggestions that base oil alone provides lubrication after initial grease film is removed due to rotation, is shown by Hurley [47]. Cann [48] in review of starved grease lubrication of rolling contacts a commonly accepted operation mode, in which a grease bearings operate under starved EHL regime where there is a limited supply of base oil lubricant to the contact zone found the following: the degree of starvation increases with increasing rolling speed, base oil viscosity and thickener content but decreases at higher temperatures. In many cases an increase in absolute film thickness is obtained when moving from high viscosity base oil to a low one, this result is the reverse of normally accepted EHL rules. Taking the fully flooded film thickness as a guide to lubrication performance is therefore not valid, as grease film thickness in the starved regime is determined by local replenishment rather than bulk rheological properties. Rheological greases, are a categorised as fall a non-Newtonian fluids. Greases that exhibit shearinduced thinning are referred to as thixotropic greases, and those that exhibit shearinduced thickening are referred to as rheopectic greases [49]. As with all, viscoelastic flow non-Newtonian fluids responses are time dependent. As grease may be both thixotropic and rheopectic. As a simple example, thixotropic or shear thinning greases begin to thin under a given stress alternatively a rheopectic or shear thickening greases will begin to harden under stress the same given stress; result in two infinitely different lubrication mechanisms. On the other hand, the most extensively used lubrication mechanism to describe grease lubrication is that the grease acts as an oil reservoir where the oil is slowly released into the contact zone to provide lubrication. Which would indicate that in the case of grease lubrication that there may be more than one lubrication mechanism. An assertion backed up by Lugt [8] â&#x20AC;&#x153;The various hypotheses on the mechanisms of grease lubrication, all based on observations/measurements,
24
indicate that there may be no unique mechanism”. The subsequent section outlines the commonly assumed phases in grease-lubricated rolling bearings. 2.5.1. Phases in Grease Lubrication Grease lubrication can roughly be broken into two phases in rolling bearings; the churning phase and the bleeding phase.
Churning Phase
Bleeding Phase Servere Film Breakdown
•Reservior formation •Film Thickness: Fully Flooded
•Reservior consumed •Film Thickness: Starved EHL, ocassional film breakdown and replenishment
Figure 2-5: Phases in Grease Lubrication of Rolling Bearings. Adapted from [50]
During the initial, churning grease flow is governed by the internal design of the bearing, the design of the housing and the rheological properties of the grease [50]. For the duration of the churning phase, grease in the contact zone is continuously being compressed and mechanically worked, where forced grease movement occurs. The churning phase commences immediately after starting the bearing with fresh grease and typically takes a few hours to 24 Hrs. to complete [50]. This phase is associated with relative high levels of friction torque, and heat production as shown in ROF+ grease life test studies [51]. At the end of this phase the majority of the volume is pushed to the side of the bearing where the second phase, bleeding of grease lubrication begins. During the bleeding phase, as indicated in Figure 2-5 the reservoir of grease formed at the end of the churning phase is consumed through an oil bleeding process. Oil bleeding from grease is an essential process and is critical to grease lubrication. Grease oil bleed mechanism has been investigated from a thin-film perspective by [52] where operation under a starved EHL regime was explored. Under starved EHL grease lubrication conditions where the lubrication film thickness drops to a fraction of the full EHL value, the effects of ageing can be accelerated, as the grease cannot supply enough oil bleed to allow for full EHL lubrication. As specified, in Section 2.4.2 oil bleed properties are mainly 25
contributed to thickener structure and interactions between the lubrication fluid, including base oil viscosity and additives incorporate. In the bleeding phase, server lubrication film break downs are common in grease lubricants as a result of; the degradations in properties of grease over time, by both physical and chemical means. When grease oil bleed occurs, oil that is released into the bearing contact zone is gradually broken down by oxidation, lost by evaporation, or leakage. To add further complexity to grease lubrication, degradation analysis has shown that the condition of the grease varies depending on the distribution within the bearing [53, 54]. These studies found and drew a number of conclusions, including the following:
Grease degradation, is dependent on the location and hence local conditions.
Grease lubricant remaining in the cage pocket region was heavily degraded and contained very little thickener, grease lubricant remaining on the inner raceway surface was predominately base oil with minute levels of thickener, grease lubricant on the seals contained different amounts of thickener depending on the seal position.
Oxidation and evaporation of base oil occurs during normal operation throughout the bearing.
After the initial running-in or churning phase the “active” lubricant is heavily degraded grease, containing oxidized from the base oil and the thickener of the grease.
Lugt [8], in a review on grease lubrication in rolling bearing highlights, adds more intricacy to grease lubrication phases and mechanisms. In the review he recognises that greaselubricated bearings show a natural “self-healing” mechanism. Where starved EHL lubrication film break down results, aids in replenishment of grease to the lubrication zone of the bearing race ways. Which is instigated as the lubrication film breakdowns produces metal-to-metal contact, which creates local heat and consequently causes the release of non-degraded base oil to lubrication zone to enable longer bearing lubrication.
26
2.6. Grease Life & Ageing Grease life can loosely be defined as the time during which the grease can ensure the (re)formation of a low shear separation layer, between the rolling element and the raceway surfaces [55]. In other words, the time where a grease lubricant can provide sufficient lubrication through the associated grease lubrication mechanisms; as pointed out in Section 2.5 there may be more than one lubrication mechanism involved. The following sections however, are composed assuming a single lubrication mechanism; that a grease-lubricated rolling bearing operates under starved EHL regimes, as presented briefly in Section 2.5.1. Starved EHL regime research has shown that lubrication film thickness can be 35 â&#x20AC;&#x201C; 70% of what would be achieved from oil of the same grade and viscosity once placed in a grease thickener matrix [56, 57]. Reference [56, 57] address in more detail the effects of breakdown of the grease structure and of starvation conditions on the film thickness. Basically, a grease-lubricated bearing cannot function effectively unless the grease lubricant is within the grease life, and can supply bleed oil to meet the demand. As the grease in contact zones is degraded or aged. Grease life is influenced by various factors for instance; will depend on the selection of grease, type of bearing, contaminates, working conditions and environmental amongst others for rolling bearing lubrication the application focus of the research. 2.6.1. Grease Life Grease life cannot be accurately measured or predicted as numerous factors, for instance speed, load, operation environment, type of bearing, rate of lubrication, contaminants, etc. influence grease life. Current grease life models have been developed mainly by the bearing manufacturers such as SKF, Timken. Where calculations on grease life are established through empirical models based on the tests conducted on systems such as R0F, ROF+, R2F, FE8 or FE9. It is generally accepted that grease life follows the Weibull probability density distribution and therefore a sufďŹ ciently large number of bearings need to be tested [51]. The reliability of grease-lubricated bearings is also reviewed in in the previous reference. It is clear from the literature reviewed the scientiďŹ c developments are still very limited and there is still much to be done for the development of a true 27
physical grease life model; currently, all published grease life models are empirically based on grease life testing systems such as those listed previously. 2.6.2. Grease Ageing Grease ageing is the process by which grease life is reduced, and can be caused and or accelerated by several factors. Cann [54] cites Carré et al. (1983) as providing the most comprehensive analysis of grease degradation changes in bearing tests, and draws the following conclusion from this and other studies: Grease undergoes both chemical and physical deterioration during use. Chemical changes include:
Loss of antioxidant due to the oxidation reactions rather than evaporation
Increase in acidity (after depletion of the antioxidant)
Formation of oxidized hydrocarbon species leading to the formation of acidic and/or high viscosity products
Loss of carboxyl bands of soap thickener
Physical deterioration includes:
Increase in bleeding rate and oil leakage
Destruction of the thickener structure, either due to working or the chemical breakdown
Loss of the base oil due to evaporation or loss of volatile oxidation products.
In brief, grease ageing can be classified into mechanical aging and chemical. Where respectively mechanical aging can be summed up by; base oil separation, base oil evaporation and weakening or destruction of the thickener structure, and chemical aging simply by; oxidation. According to Ito et al. [58] physical or mechanical deterioration is predominate at low temperatures and high speed and chemical deterioration is predominate at higher temperatures and low speeds. From general literature it is accepted that the two grease aging mechanisms typically ensue simultaneously, and bare influence upon each other. The dominating factors for the grease aging, are speed and temperature of operation, as can be inferred for the statement from Ito et al. However, 28
as indicated in the opening of this section grease life is influenced by numerous factors including one of which is contaminates. The role of contaminates in grease life and grease aging is of major concern, primarily due to the fact that grease contaminates influence temperature one of the primary grease life influencers. Through increased friction as a result of a number of mechanisms, where lubricating film thickness can be reduced due to viscosity decrease, due to temperature or incompatible grease contamination etc. The effect of contaminates in lubricating grease is looked at in further detail in Section 2.7 which directly follows. Due to its direct relationship to the research proposed. The ageing or degradation of grease within a grease-lubricated system is not uniform as already underlined through reference to Canns work[53, 54]. Whereby, it has shown that the condition of the grease varies depending on the distribution within the bearing. This observation was made much earlier by Milne et al. [59] in work on the observation on the movement and structure of grease in roller bearings. Here it was shown that only a small amount of grease in contact zones between the rollers and bearing race, acted in providing lubrication to the system. The remaining grease held in bearing underwent relatively no ageing or degradation. Evidently this led Milne et al. [59] to the conclusion that in a properly operating grease-lubricated bearing only a small amount of the grease becomes aged or degraded while the majority of grease remains in a practically unused condition. Fundamentally, the role of the bulk of the grease in a system is to keep the small amount of active grease in place, and to replenish it via oil bleeding. As active grease oil is aged and degraded, the other valuable function it plays is to prevent contaminants from entering the contact zones.
2.7. Impact of Contaminates in Lubricating Grease As stressed in the previous section the role of contaminates in grease life and grease aging is major of upmost interest. Contamination is detrimental to grease lubricating qualities, and can cause serious bearing damage if undetected. The presence of contaminates within a grease-lubricated system progressively increases, as more wear contaminates are generated in the contact zones, as little movement occurs in grease to remove them. Abrasive contaminate wear particles in a grease-lubricated system may be more harmful than an identical particles in an oil lubricated system. As with grease lubrication little 29
opportunity, exists for particles to be removed, in contrast to oil where filtration or settling of the particle may occur. Illustration of the effect of a solid contaminant in a lubricant on the pressure distribution in EHL line contact is shown in Figure 2-6. As can be seen, contaminant smaller than the lubrication film thickness, lead to high pressure peaks, which travel through the contact zone. These pressure peaks cause additional fatigue-stress in the rolling elements and the raceways, which reduces the lifetime of the rolling bearing.
Figure 2-6: Influence of a contaminant on the pressure distribution in EHL line contact where u1 and u2 are the velocities of the surfaces [60]
Grease contamination can broadly be categorised into two: ingested and generated. Such contamination may be present in grease from a number of sources, due to the ingression of water, through the introduction of incompatible grease or other solid particles including dirt. The focus of this review is on solid contaminates within grease-lubricated systems. As stated, contaminates may be generated, through the production of wear particles. During normal operation there will be a level of wear due to normal operation, thus contamination is unavoidable. In a study by Dywer-Joyce et al [60] on the effects of solid contaminate and debris particles in lubricated bearing performance, it was suggested that there are three mechanism for the deformation of solid contaminates based on particle type, once they enter the contact zone. The three mechanism are as follows: for ductile particles will deform plastically resulting in either plastic or elastic deformation of the contact services as shown in Figure 2-7, A. Ceramic particles will fracture, resulting in smaller particles where size is dependent on fracture position in the contact zone as shown in Figure 2-7, 30
B & C. Small ceramic particles that go unchanged cause plastic deformation in contact zone as illustrated in Figure 2-7, D.
Figure 2-7: Illustration of Contaminate Type in Contact Zone [60]
As seen, in Figure 2-7 the influence of small hard ceramic particles, which include commonly ingested contaminates such as dirt, sand and other environmental particles may have a greater impact then ductile particles such as wear metals. The presence of solid contaminates when considered in terms of grease lubrication mechanisms and lubrication film behaviour as outlined previously, the impact of contaminates in lubricating grease is significant. The potential greater impact of solid contaminates on grease-lubricated systems which cause increasing levels of damage, as opposed to oil lubricated systems is clear. As stated in the opening of this section; the flowing or flushing action of an oil lubricant, aids in the removal of potentially harmful solid particles from the lubricant contact or load zones surfaces. Hence, grease-lubricated systems are more prone to the entrapment of contaminate debris particles in lubricant contact or load zones surface, resulting in surface damage and shortened component life. The damage that results, can lead to contact fatigue and increased wear, thus leading premature failure of the components part or the entire machine. In terms of the application of this research for rolling bearing, the most prevalently failure is caused by rolling contact fatigue which can be induced by the presence of contaminates as shown in Figure 2-6 earlier. Dwyer-Joyce [61] on the life cycle of a debris particle states that debris particles exist in most lubrication systems. Contaminate particles can come 31
from a number of sources including: the surrounding environment, poor lubrication practices they can also be generated within the machine components. The latter of which can bare more interest for grease-lubricated systems as presented in Section 2.2 grease lubrication minimises contamination ingress. During machine operations and indeed grease-lubricated rolling bearing operation, wear metal debris particles are generated by rubbing motion of mechanical component parts, which are either generated by normal benign wear or abnormal wear modes. The creation of wear metal debris particles particularly from abnormal wear modes are normally responsible for the early failure of tribological machine elements including grease-lubricated rolling bearings. Moreover, the initial damage caused by wear metal debris contaminate particles within a system can, result in the generation of further wear debris, often higher than original failure quantities [61]. Contaminate particle within grease lubrication have a knock-on effect particularly wear metal debris in the area where is generated. Yet, unlike oil lubricated systems the generated wear does not bare significant impact on other elements of a lubrication system. Likewise, Kahlman [62], classifies that the presence of hard contaminants in lubricated rolling bearings is a major cause of premature failure, for example by fatigue or by abrasive wear of rolling elements, races or cages, but notes the importance of both bearing metallurgy and contaminate composition on the resulting failure mechanism and wear mode. Which in effect, results in two mechanisms where the variance between two and three body abrasion caused by contaminates which is review in detail in [63]. In two body abrasion the contaminate particle maybe imbedded and remain stuck, in one surface while it wears or scratches the other. Contaminates in grease-lubricated systems dramatically reduce condition, and instigate a number of abnormal wear modes dependent on a number of factors. Displayed, earlier in Figure 2-7 particle type has an impact on; particles can be deformed or fractured by passage through the contact zone, but particle size also has an impact. Particle of less than 10 Âľm can be considered most damaging for oil lubricated systems, as the larger particles will settle out, be filtered out or be fractured or deformed into particles of less than 10 Âľm [1]. However, the same is not true of grease lubrication, as 32
large particles will not settle out or be filtered. Though, smaller contaminate particles of less than 10 Âľm can enter the load zones between bearing surfaces creating points of high stress again as shown in Figure 2-6 that lead to eventual spalling and early fatigue failure. Solid particle contamination has a detrimental impact on grease lubricating qualities and can cause serious damage if gone undetected, contamination that reaches or that are generated in the contact zones will remain trapped and will continually wear on the surfaces due little migration with grease. Thus, the monitoring of solid contaminates in grease, and taking action accordingly to mitigate can improve life and prevent failure.
2.8. Summary In summation, as can be grasped for the topics reviewed in this chapter grease lubrication is a highly complex area. The multi-phase, non-Newtonian, multi-composition and as a result multi-property nature of the essential lubricant, causes decisive principle conclusions to be limited. As opposed to the relatively well classified knowledge of oil lubricants; grease lubricant knowledge although quite extensive is diminutive in comparison giving the importance of grease lubricates today and into the future. The risk of unequivocal assumption of theories or mechanisms transfer between oil lubricant research and grease lubricants, can undoubtedly be seen as problematic, with grease life and aging as an example. On the other hand, the presence of contaminate debris is inevitable, and the processes whereby these particles lead to fatigue and wear are defined. Which if gone undetected lead to eventual component failure. It is this assertion that needs to be considered in conjunction with grease condition monitoring, which is focally reviewed in the ensuing chapter.
33
3. Chapter 3. Tribological Condition Monitoring of Grease Lubricants (Literature Review)
3.1. Introduction The following literature review, is a continuance of the imperative prior review chapter, on which this chapterâ&#x20AC;&#x2122;s supports are built. The focus of the review is on the exploration of the grease condition monitoring. As specified, in Chapter 1 the focus of the research is on the application of rotary disc electrode atomic emissions spectroscopy (RDE-AES) for grease condition monitoring, through grease elemental analysis, as such forms the core focus of the review. The chapter intends to identify knowledge on its application and research deficits which can be improved upon, by the research proposed, where the worth to industry can be substantiate. The review closes by highlighting the key influences on the proposed research before providing a summary.
3.1. Grease Condition Monitoring Overview The analysis of in-service used grease, has not become a valuable diagnostic tool for tribological condition monitoring applications in a similar sense to oil lubricants. From the literature reviewed, it was clearly established that grease analysis can provide extremely useful information. In the majority of published cases, grease analysis was initially performed only after failure for root cause analysis, but trend analysis of used grease samples have shown that failure in grease-lubricated systems can be recognised in advance. Although, as can be appreciated from Chapter 2 the analysis of in-service used grease lubricants is intrinsically more complex than that of oil. Oil conditioning monitoring has become an indispensable part of many condition-based maintenance approaches across numerous industry sectors, with numerous well defined standard oil analysis test being long established [64]. However, on the whole the same is not true of grease lubricants. Due to a number of key factors that include; large sample volumes needed, difficulties in obtaining a 34
representative sample, due to the non-uniform non-Newtonian flow of grease lubrication in the lubrication contact zones, and the vast array of grease types with varied multiphase multi-component composition. These have historically, resulted in tribological condition monitoring, of in-service used grease not becoming common practice; even though the large majority of installed bearings are grease-lubricated and have a substantial impact on the reliability of the equipment. In contrast, to the quite extensive array of grease qualification tests which are identified in Section 3.1.1; in most cases require grease samples in the range of 50 grams for analysis. As a consequence, are not amenable for used grease analysis due to the relatively small amount of grease lubricant used in most applications. Moreover, the strength of information to be obtained in relation to condition monitoring from most qualification tests are of limited benefit. Consequently, grease qualification test are only carried out for grease manufacture, quality control and by bearing manufactures to empirically interpolate predicted life times and re-lubrication intervals as highlighted in Chapter 2. As a consequence, of the growing requisite for condition monitoring of grease-lubricated components in particular industries. Along with the progression in analytical process as presented by Herguth [10] the analysis of used grease for condition monitoring purposes can now be conducted with small sample as low as milligrams. Nonetheless, there are only a small number of laboratories in the world that specialise in the analysis of used grease using small sample sizes [11]. Furthermore, recent publication of sampling standard practice for obtaining in-service samples of lubricating grease in ASTM D7718 [4] based on the works of Wurzbach [12-15] efforts to stream line in-service grease tribological condition monitoring. It is now possible to analyses in-service grease of small volumes with confidence to allow tribological condition assessment. Despite this, a limited range of published literature exists on used grease condition monitoring, of those reviewed [11, 65] are most discerning. The review by Turner [11, 65] presents various techniques which are employed for grease condition monitoring identifying their significances. Additionally, a range of low cost methods grease condition monitoring methods are presented in [66] including a simplified grease consistency test which showed correlation against standard cone penetrometer consistency test result. A simple contamination and wear debris assessment method based on surface scratch 35
characteristic was also provided. Other simple field based grease condition test methods can be seen in the SKF grease test kit [67]. A non-exhaustive list of the most common commercial used grease analysis methods can be found in Table 3-1. Table 3-1: Common Grease Condition Monitoring Analysis Methods Detection Property
X X
X
X
X X X
X
X X
N/A
X
ASTM D5707/5706 ASTM D2596, ASTM D2266 ASTM D2265 N/A D6304 Adapted
X X X X
N/A N/A N/A ASTM D7303 N/A N/A ASTM D1403 N/A ASTM D5483
X X
X
Standard
Other
Consistency
Additive Degradation
X
Four Ball Dropping Point Bleeding Out Characteristics Karl-Fischer Titration
Oxidation
Water
Appearance Crackle Test Fourier Transform Infrared Analysis ICP Elemental Analysis Indication for wear and contaminates by sulphated ash Ferrography / Ferrous Density Cone Penetration (½- or Ÿ-scale) Grease Rheometry Differential Scanning Calorimetry (DSC) Remaining Antioxidant by Linear Sweep Voltammetry (RULER) SRV (EP)
Solid Contaminates
Analysis Method
As classified, the research is aimed, primarily on the development of grease elemental analysis via, rotary disc electrode atomic emissions spectroscopy for grease condition monitoring. In traditional, RDE-AES condition monitoring of oil lubricants, hydraulic fluids elemental analysis permits the detection of wear metals, additives and contaminates The same is not true of grease lubricants systems, as illustrated by example in Chapter 1. The elemental determination of the concentration, of wear metals, additives and 36
contaminates can be a significant determining factor for the condition assessment of both the grease lubricant used, and the equipment which it lubricates. Allowing ultimately for the condition-based maintenance of grease in both predictive and proactive approaches. The significance of information that can be obtained from grease elemental analysis is presented subsequently in Section 3.2. Grease condition monitoring has numerous applications, across wide ranging components and systems, including that of the application focus of this research greaselubricated rolling bearings. The application of grease condition monitoring can have significant cost benefits in numerous industries, including power generation; wind power, motor operated values, transport; rail and manufacture; robotic joints to provide illustration. 3.1.1. Grease Qualification Testing Grease qualification testing can be divided into three area; functional testing, grease property testing and life testing. Table 0-1 in Appendix A present a representation of the numerous current qualification test protocols used today.
3.2. Grease Elemental Importance Elemental analysis results from used greases can provide critical information regarding wear rates, contamination, additive depletion, and possibly provide indication of thickener type and deterioration. Bots [68] concludes different situations and influencing factors for wear, contamination and grease condition have displayed multifaceted coherences between the grease analysis results and their practical meaning. This leads to the conclusion that by observing and interpreting these factors with expert knowledge; condition-based proactive maintenance strategies can be applied to grease-lubricated components. Similar conclusion are drawn by of Wurzbach in [12, 14, 15]. Grease lubricants contain a vast array of potential elemental information that can be used to interpret lubricant and component conditions, through wear metal, contamination and additives elemental detection. Table 3-2 provides a summary of common elements to found and potential source. 37
Table 3-2: Common Grease Elements and Potential Sources. Adopted from [16] Element
Potential Sources
Range
Aluminium, Al
Clay or other thickener
<20 to 3000 PPM
Antimony, Sb Extreme pressure additive Boron, B Complexing additive for thickener Barium, Ba Rust inhibitor Bismuth, Bi Extreme pressure additive Cadmium, Cd Wear metal, contaminant Calcium, Ca Thickener and extreme pressure additive Chromium, Cr Wear metal, contaminant Copper, Cu Wear metal, contaminant Iron, Fe Wear metal, clay thickener Lead, Pb Extreme pressure additive Lithium, Li Thickener Magnesium, Mg Clay thickener minor element Manganese, Mn Clay thickener minor element Molybdenum, Mo Molybdenum disulfide / extreme pressure additive Nickel, Ni Phosphorous, P Sulfur, S Silicon, Si Tin, Sn Zinc, Zn
Wear metal Additives such as zinc dithiophosphate (ZDDP) Additives such as ZDDP Contaminant (dirt), clay thickener trace element Contaminant Additives such as ZDDP
<20 to 1000 PPM <20 to 1000 PPM <20 to 1000 PPM <10 to 1000 PPM Trace to 1000 PPM <20 to 3000 PPM Trace to 1000 PPM Trace to 1000 PPM <10 to 5000 PPM <20 to 1000 PPM <20 to 3000 PPM Trace to 100 PPM Trace to 100 PPM <20 to 3000 PPM Trace <20 to 1000 PPM <20 to 1000 PPM <10 to 1000 PPM Trace to 100 PPM <20 to 1000 PPM
As, can be noted in Table 3-2 common grease elements may potentially come from several sources, as shown with the case of aluminium. As indicated, in Section 2.4 aluminium was defined as a common soap thickener. However aluminium may present as both an environmental contaminate and a wear metal dependent on the application of the grease lubricant. Grease element importance, may be shown by considering the comparison with an oil lubricated system; as the wear particles are formed, or solid contaminates enter they are carried by the oil lubricant to other mechanisms where they then can be grinded, deformed, or the particles can settle in sumps or be caught in filtration systems. As a result, the final quantity and size distribution of the wear particles remaining in the oil for elemental analysis is greatly influenced; leaving just a snap shot of recent particles. In contrast, very little particle settling or movement occurs within grease, after the initial churning phase as recognised in Section 2.5.1, Chapter 2. In a grease-lubricated system 38
wear particles or solid contaminates accumulate and are not removed without regreasing so can provide an entire wear history a component. In essence, since grease lubricant properties often change drastically during operation through, lubrication film thickness changes as highlighted in Section 2.5, Chapter 2, the potential incidence for wear is increased. However, the solid contamination and wear information is concentrated within a relatively small volume thatâ&#x20AC;&#x2122;s not affected by filtration or diluted by an oil reservoir, grease elemental analysis can be a very attractive condition-monitoring tool. Elemental analysis may be performed by a number of spectrographic analysis techniques which is reviewed in Section 3.3. Elemental wear metal in grease, include iron, chromium, tin, copper, lead, nickel, aluminium, molybdenum and zinc. For the chosen application focus of the study greaselubricated rolling bearings, wear metals of particular interest for diagnosing a bearing or grease condition is the amount of iron and chromium. Which may present as wear from the bearing material. Non-ferrous materials like copper, lead and tin indicate corrosive or abrasive wear from the bearing cage [1]. The likely reason for the presence of increased wear metals in a grease lubricant can be determined by additional testing means or by means of interpreting additional elemental information, which may be present due to grease contaminates.
3.3. Elemental Spectroscopy Spectrographic analysis of which, there are varied techniques allows for the rapid accurate measurement of the common elemental materials found in lubricants. As, such spectrographic analyses are used in both oil analysis and wear debris analysis for condition monitoring [69]. The reference provided reviews the history in detail in the context of condition monitoring applications. Today spectrographic analysis techniques are primarily conducted on lubricant oils, hydraulic oils, dielectric oils and to a lesser extent grease to determine their condition. In an effort to avoid failure, improve quality control, to reduce inventories of oils and for determining the most cost efficient intervals for maintenance. Spectrographic analysis forms part of most if not all standard oil analysis test carried out [64]. 39
As specified previously in Chapter 1, the techniques of interest in this research are atomic emissions spectroscopy, of which the application of rotary disc electrode atomic emissions spectroscopy (RDE-AES) to used grease for condition monitoring is proposed. General AES operation principle is outlined in Section 3.3.1. Of AES techniques used in commercial lubricant analysis the, RDE-AES, is one of the most common, the other inductively coupled plasma, a comparison of methods is provided in Section 3.3.2. 3.3.1. Basic Operation of Atomic Emission Spectroscopy Atomic emission spectrometry (AES) is a method for detecting and quantifying the presence of elements in a given material. AES exploits the fact that every element has a unique atomic structure, which when subjected to additional energy, emit light of specific wavelengths [70]. In AES application to lubricant analysis, individual atoms within the sample, for example taking elements from Table 3-2; iron atoms from wear debris, zinc atoms from a zinc dialkyldithiophosphates (ZDDP) additive molecule, or silicon from silica contamination, can be excited using a high-energy source. The atoms absorb energy from the excitation source and are transformed to a high-energy electronic state. Due to the laws of quantum physics, atoms do not like being in these excited states and rapidly lose the energy they have gained, mainly by emitting light energy. The energy of light emitted, which is inversely proportional to the wavelength, is dependent on the electronic structure of the atom, and is thus different for each type of atom [71]. Thereby, by measuring the amount of light emitted at the characteristic emission wavelength for atoms listed, the concentration of each atom can be determined, through the spectral lines produced, once passed through a prism or grating. An example of the spectral lines emitted by iron can be seen in Figure 3-1.
Figure 3-1: Spectral Emission Lines of Iron [72]
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3.3.2. Atomic Emission Spectroscopy Comparison Although, there are a variety of methods of atomic emission spectroscopy with RDE-AES the focus of research, this section provides comparison to the most common alternative spectrographic technique inductive coupled plasma (ICP) used in lubricant analysis; moreover, it provides rationale for focus. The clearest distinction between the two is the method of spectral excitation, once the elements are excited the spectrographic technique essentially follow the same process as outlined in Section 3.3.1. Still it remains, the variance in the excitation method has a significant impact on the capabilities and benefits of each respectively. The main advantages and disadvantages of the two respective techniques are summarised in Table 3-3 and Table 3-4. Table 3-3: Summary of RDE-AES Elemental Analysis in the Context of Grease Lubricant
Advantages
Disadvantages
- simple to operation - sample preparation may be minimised - robustness no major requirement for operation bar power supply - does not require cooling water or gases - particle size detection > 10 µm - simultaneous measurement of elements - lower cost, specialised to lubricants analysis
- blind to particles > 10 µm - no standard method for grease analysis - grease consistency effect may be greater - not currently able to detect lithium
Table 3-4: Summary of ICP Elemental Analysis in the Context of Grease Lubricant
Advantages
Disadvantages
- high performance at low elemental level limited grease consistency (matrix) effect due to preparation requirements
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- requires laboratory environment - requires process gas (argon) and internal calibration standards - requires extensive sample preparation for grease - inefficient for particles > 2 µm - blind to particles > 3 µm - standard method only for qualification testing - high cost, multipurpose
In an ICP analysis the lubricant sample is nebulised, for injected into a high-temperature argon plasma, where the atoms are vaporised and excited [71]. Where as in RDE-AES, a large electric potential is built up between the graphite electrodes, one of which is coated in a lubricant refer to Section 3.4.1 for more detail. Once the charge voltage has been reached, an electrical arc discharges creating a high temperature. Which vaporises a portion of the lubricant creating a plasma [70], where spectral light emission can be captured and analysed. Further, the significance of the difference in the method of excitation results in varied particle size detection limits and precision. The effect of which was reviewed by Anderson et al [73] for application to coolant analysis. Where it was stated that the ICP-AES techniques measures only the most finely divided material; the material cannot be in the form of large particles. This is because of the sample introduction and excitation method outlined where the requirement to nebulise the sample exists. RDE-AES methods have the ability to detect larger particles, based on their method of excitation. The general range limits are given as: approximately 0.5 µm - 2 µm for ICP and approximately 2 µm - 8 µm for RDE-AES, which assumes standard operation, but it should also be noted that the range will be effected by the particular element in question, and in the case of metals; the amount of surface oxidation on the surface. With results of elemental results of the ICP being accurate to approximately 0.1 PPM, in contrast the results RDE-AES methods are accurate to approximately 1 or 2 PPM. Both methods have varying capabilities and benefits as stated in the opening. Despite this fact, in general this of no concern, once the variation is appreciated; for the purposes of trending data of wear metals or contaminates. However, the elemental data from samples analysed by ICP and RDE-AES instruments typically will not correlate [71] which is particularly prevalent if larger wear particles are present. Lukas and Anderson [74] qualify the ability to measure larger wear particles presumes that they are present in small quantities and that the larger particles are actually excited. They state that for a typical 1 ml oil sample, less than 50% is subjected to analysis with the RDE-AES methods, and only a few percent for the ICP methods. Therefore, if there are only a limited number of larger particles the chances of detection is limited. Although, the likelihood is higher for RDE-AES due to both; greater particle size detection limits and superior percentage of sample analysed. 42
The particle size detection limits of both AES methods can in essence make them "blind" to particles that are over, a certain size. For RDE-AES, the focus of this research it is stated that the detection limits are approximately 2 µm - 8 µm. However, is considered "blind" of particles greater than 10 µm. The simple reason for this even with extremely high arc discharge voltages and temperatures, for full spectral light emissions the particles must be completely excited or vaporised to form a plasma. Because the excitation process occurs over a fractions of second the energy requirements to completely burn or vaporise a large metal particle is restricted. Additional, influencing factors identified with regards RDE-AES of grease can be seen in Section 3.5. Due to the particle size limitation of AES and the fact that, normal RDE-AES stereographic elemental analysis is limited to particle size of 10 µm or less, it is common for secondary test to supplement the results. For example techniques such as: particle quantification, laser net fines to analytical ferrography, a suggested selection process for secondary detections methods can be seen in Figure 3-2.
Figure 3-2: Wear Particle Size Detection Stages [75]
The secondary process of analytical ferrography, whereby the microscopic inspection of wear particles, by pattern, size, morphology, and composition can identify failure modes within a lubricated system. Analytical ferrography is among the most powerful diagnostic 43
tools in tribological lubricant analysis, with its applications to oil lubricants most wellknown. Analytical ferrography presents as a very attractive secondary method for grease lubricants due to its qualitative nature, as representative sampling may pose issues.
3.4.Rotary Disc Electrode Atomic Emissions Spectroscopy The RDE-AES technique as applied to, used oil analysis, is a long established and widely practiced technique. It is considered the standard analytical method for the majority of oil analysis laboratories [76]. In the RDE-AES technique, an electrical source is used to impart the energy required to excite the atoms. Excitation in the sample, produces spectral light for the determination of the element as described in Section 3.3.1, is generated by an electric arc between two electrodes. ASTM D6595 [77] is the standard test method for determination of wear metals and contaminants in used lubricating oils or used hydraulic fluids by rotating disc electrode. However, no such standards exists for grease lubricant analysis to date. The RDE-AES method of analysis has been in existence for over 30 years; the developments and functional enhancements in RDE-AES used oil analysis spectrometers are outlined in [76]. The most notable of which beside the change from photomultipliers to solid state charged couple devices (CCD) for the capture spectral emissions, is the development of the additional process of rotrode filter spectroscopy (RFS) technique which makes use of the fact that the graphite disc electrodes used in RDE-AES are porous [74]. The RFS technique allows for the detection of larger particle size and has been shown in applications to provide additional information, about larger wear particles which is outlined in [74, 76, 78]. The RFS is a filtering process, as the name employs, in which a RFS graphite electrode captures the larger particles in a lubricant for instance oil, assisted by a vacuum. Residual oil is removed by a solvent and is allowed to dry. The larger particles are left on the outer circumference of the disc electrode, so they can vaporised allowing for detection. Detection of larger particle is made possible as more energy is available, as the oil within the sample does not need to be excited. The RFS method is most commonly, used as a comparative method for RDE-AES, by increasing the size limitations as outlined in Section 3.3.2 and as shown in Figure 3-2 may be used as an indication method for further analysis. 44
3.4.1. Basic Operation of RDE-AES Figure 3-3 illustrates the workings of a rotating disc electrode elemental analysis procedure, and provides an example of actual operation. As can be seen, a gap exists between a rotating graphite disc electrode and the stationary rod electrode. During operation a disc electrode is placed on the end of the rotation shaft. In the case of oil analysis the rotating of the disc electrode draws a continuous sample of oil between the electrode gap. A large electric potential is set up between a disc and rod electrode with the sample passing through the gap between them. An electric charge stored by a capacitor is discharged across this gap, subsequently creating a high temperature electric arc, which vaporises a portion of the sample forming a plasma. Causing the sample to be excited again as described in Section 3.3.2. The light emitted by the excited atoms is collected and focused onto the slits of the spectrometer as displayed by Figure 3-4.
Figure 3-3: Illustration of RDE-AES Operation. Adapted from [71]
The light given off as a result of this vaporisation encompasses, the light emissions of all the elements present in the sample. The light emissions are separated into individual wavelengths by a diffraction grating as shown Figure 3-4, which splits light of different wavelength into discrete wavelengths, based on their angle of diffraction [4]. The light intensity at each angle, typically referred to as a channel, is measured using a light-
45
sensitive photodiode CCD arrangement and the resultant voltage signal is converted to a concentration in PPM based on a simple calibration procedure [70].
Figure 3-4: Rotating Disc Electrode Spectroscopy [70]
3.5. RDE-AES Influencing Factors As, with all AES detection methods RDE-AES has a number of factors that influence the result obtained. The most commonly known influencing factor, is that of particle size which was highlighted in Section 3.3.2. The following section highlights additional contributory factors and aims to relate the context for the proposed use of RDE-AES for used grease elemental analysis for condition monitoring purposes. Lukas and Anderson [74] reference Rhine et al. in review of approaches to allow for the quantification of large wear particles in used lubricating oils; summarise the most important influencing factors for particle detection in AES techniques including RDE-AES based on works conducted by Naval Air Engineering Center. The following are the parameters of most relevance as discerned by the review for the application of RDE-AES to grease elemental analysis: ď&#x201A;ˇ
Representative samples; as with all methods of lubricant analysis. Is a major issue in the context of grease analysis as reviewed in this chapter. Obtaining a representative can be more complex due the rheological properties and mechanisms of grease lubrication.
46
Excitation parameters; the type of excitation influences the particle size detection capabilities of spectrometric techniques. Lukas and Anderson [74], state for RDEAES, an arc source has better efficiency for certain elements, but for others a spark source is preferred. The effect of excitation parameters, in terms of effect of exposure time and spark intensity for RDE-AES detection was shown by Saba [79] a co-author in works referenced by Lukas and Anderson. Undoubtedly, excitation parameters will have a significant influence on grease analysis.
Another parameter highlighted was oil viscosity, which will have a major and possibly larger influence on grease sample as shown in Section 2.4.1 in Table 2-2, the large consistency variation in grease NGLI grades. It is pointed out for RDEAES, the viscosity of the oil has an effect on the quantity of the sample reaching the analytical gap for excitation and thus the quantity of wear particles carried with it for excitation. Which is further influenced by the porosity of the graphite disk electrode. Saba [79] investigated the effect of coating electrodes or the surface density effect on emission signal concluding that paraffin wax showed the most promising result for RDE-AES.
Lubricant composition has also been shown to effect the efficiency of the RDEAES technique. Where for example variance exists between hydrocarbon oils and ester oils. This factor is presumed to have the same implication for base oil composition of grease, but may also be effected by various thickener compositions as reviewed in Section 2.4.2 of Chapter 2.
The factor of note, as specified in the opening is particle size, which has an effect on results and presents as a limitation when large particles are concerned. In addition, research has shown the morphology of wear particle will also have an effect on results obtained. The example provided in [17] is the comparison of rubbing wear particles and spherical wear particles. If both types are described by their major dimension, spherical particles of the same dimension as rubbing wear particles will be more difficult to excite, thus will emit less spectral light which results in lower detection rates.
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3.6. Grease Elemental Analysis - Past Investigations Influence Currently used grease elemental analysis is being offered commercially by a relatively small number of labs and by some grease manufacture as a condition monitoring tool examples include: Herguth Laboratories and MRG Laboratories, United States. OelCheck, GmbH. Germany FocusLab Laboratories, Ltd. Bangkok, Lubricant Quality Scan, England, Naias Labs, Greece and Kl端ber, Lubrication, Germany. Influence of past research and current practice is an important aspect to the research, although research specifically related to the focus application is limited as presented in the extensive focus review. Whereby in large the knowledge presented was acquired from investigation into oil elemental analysis. Past published research, in respects to the application of grease elemental analysis is sparse, that of which was reviewed is presented herein. Jones [17] through, a RDE-AES method, investigated the suitability of grease elemental analysis for condition monitoring, based on a case study conducted on a grease-lubricated taper roller thrust bearings which were used in working a mill. The research proposed a low cost method with minimum sample preparation for the detection of elements likely to be encountered in typical grease lubrication applications. The abridged sampling and elemental analysis technique pursued in the study are as follows: Grease sampling in the study was achieved by the use of nylon tubing attached to a 'Vampire' sampling gun inserted into the loaded region of the bearing. The 'Vampire' sampling gun was used to extract six centimetres of grease, for elemental analysis of the used bearing grease. Similar sampling procedures are now covered in ASTM D7718 [4]. The grease samples collected were prepared by forcing a weighed amount of grease from the nylon tube into a beaker. The next step was the addition of blank oil at three-times the weight of the used grease sample. Which as stated underwent exhaustive mixing to form a semi-liquid sample suitable for analysis. Spectrographic elemental analysis was conducted by means of RDE-AES, by adding the prepared grease into a specimen cup for analysis. Following the procedures as outlined in Section 3.4.1, whereby the pre-sparking ensured an even coating of the graphite disc electrode prior to analysis. Based on the case study, Jones concluded that the method developed using existing spectrographic RDE48
AES equipment was suitable for monitoring grease-lubricated bearings. As during the study, areas of excessive wear had been highlighted within the bearings involved the study. In contrast, other grease elemental analysis procedures based on RDE-AES have been presented, for instance by OelCheck, Germany where Bots [11] presents their method of grease elemental analysis by a whole grease smearing technique. In which a small quantity in the region of 0.3 grams of grease is distributed or smeared over the outer radius of a RDE-AES graphite disc electrode. Where the grease sample can undergo spectrographic RDE-AES analysis. The merits from a practical and commercial sense for such a technique is clear; sample preparation is significantly minimised even in contrast to the method proposed by Jones. Moreover, the appeal of low sample volumes is apparent as in the majority of applications, the volumes of grease lubricant in a system can be relatively low. Correspondingly, a similar procedures are presented in [70] for grease elemental analysis as an option when grease samples are two stiff. It is recommended to smear the stiff grease, that with a high NGLI grade grease around the outside circumference of the graphite disc electrode. This then can be placed in position for RDE-AES analysis accompanied by a sample holder as can be seen in Figure 4-3 filled with a standard blank base oil of 0 PPM oil allowing for elemental analysis. An alternative recommendation provided by [70] for stiff greases is the application of heat to reduce consistency prior to RDE-AES elemental analysis, if the grease sample cannot be ran straight from a specimen cup. Other grease elemental analysis techniques make use of solvents, to breakdown the structure of the grease to allow for analysis. The basis for the solvents used in such arrangements originate for early grease ferrography studies that were conducted by the U.S Naval Air Force [18, 80] based on solvent preparation to allow for wear characterisation of grease samples taken from critical applications such as swash plates of helicopters. The studies conducted, on nine unused grease of various thickener types, and variation in base oils from mineral to synthetic; found that of the three solvents explored that a 49
blend of toluene (toluol) and hexane was found to be most effective. Including the most common type of grease thickener lithium, the solvent used was a composition of 30% toluene and 70% hexane to create an aromatic, aliphatic essentially non-polar blend [81]. The previous reference [81] to the Wear Particle Atlas provides more detail on the application of ferrography and solvation in regards to grease-lubricated systems. The study draws a number of important recommendations and conclusions including; that ferrograms produced from grease are of a quality which is comparable to those made with oil. Nonetheless, although satisfactory result may be drawn, the examination is as not straightforward as oil. The two main reasons are firstly, the uneven distribution of wear particles in grease and secondly physical configuration of certain bearing may inhibit sampling of grease lubricant wear or present. The previous statement can without difficulty be agreed upon, as presented previously in Section 2.6, Chapter 2, a large proportion of grease within a grease-lubricated system may remain in a fundamentally unused state. There have been other replications studies of the solvent degradation of grease for ferrography, such as that presented by Dalley [82]. Who provided technical advice for revision to the Wear Particle Atlas. The seminar paper by Dalley duplicates the solvents used in the U.S Naval Air Force grease ferrography studies on range of grease and concludes that no universal solvent could be found. The application of solvent degradation procedure for RDE-AES spectrographic elemental of grease is maintained by Wurzbach [12, 14, 15]. Where he classifies that a grease sample is weighed out to glass vial, where it is diluted and dissolved with a filtered mixture of grease solvent, which allows for RDE-AES elemental analysis of grease. The other common alternative for grease elemental analysis is by ICP (inductively coupled plasma), which requires very different preparation compared to RDE-AES. As stated previously the grease solution must be brought to an aqueous solution by an acid digestion to allow nebulisation. The acid digestion process required for grease can take upwards of approximately two hours. For instance the sulphated ash digestion process, may take up to three hours. General comparison of both methods was given in Section 3.3.2. The most significant research on grease ICP elemental analysis originates from research conducted by Fox [16]. On which the effects of four different unused grease 50
acids digestion process were compared to allow for ICP elemental analysis. Fox made the conclusion that of the four acid digestion procedures tested, each had advantages and disadvantages. In deduction, Fox has stated that closed-vessel microwave digestion provided the most advantages primarily due to the fact; volatile element losses were reduced, as the process is closed to the atmosphere. The findings from this research, resulted in the publication of ASTM D7303 [19] in 2006. It was recently revised in 2012, as a standardised qualification test for unused grease elemental analysis. ASTM D7303 [19] was published prior to an inter laboratory study on which two methods investigated by Fox where accessed. The results and procedure used in the inter laboratory study are found in ASTM Research Report RR: D02-1608 [83]. The ASTM D7303 [19] standard method for determining metals in lubricating grease by ICP-AES covers the determination of a number of metals such as aluminium, antimony, barium, calcium, iron, lithium, phosphorus, magnesium, molybdenum, silicon, sodium, and zinc in unused lubricating greases. The important factor to note is that this standard for grease elemental analysis only holds full applicability to unused greases. Comparable to RDE-AES methods of elemental analysis of used grease, no standards exist and laboratories that undertake such testing use adoptions of standard practice for single phase liquids lubricants such as oil or hydraulic fluid. Although, there are distinct methods that can enable elemental analysis of used grease, including through RDE-AES, as shown in this section there are no standard test method that all laboratories can adhere to. Additionally, there has been little investigation into the effects or comparisons of the various methods that can be adopted and the effect on the results that can be obtained, for condition monitoring purposes as a consequence. Where the appraisal of data obtained from the method can illustrate the prospective disputes between the methods of RDE-AES grease analysis. Furthermore, the effect of sampling location and sampling method on used grease elemental analysis within greaselubricated systems, including that of grease-lubricated rolling bearings, holds significant merit for investigation.
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3.7. Sampling for Grease Analysis As with all, valid tribological condition monitoring approaches, sampling is one of the most important areas that alters the effectiveness of the approach; simply if a sample does not represent an accurate condition of the lubricant, and component at the time of sampling, the reliability of both the test results and their interpretation is affected. Representative sampling of grease is one of the most important and potentially challenging aspects for grease condition assessment through the application of elemental analysis. One of the principal concerns is the capability of obtaining a representative sample of the degradation within the grease for example wear metals and/or contamination. Therefore, the delineation of an appropriate sampling protocol for obtaining a representative sample of grease from lubricated components is essentials, in this case grease-lubricated rolling element bearings. Obtaining a representative sample from grease-lubricated components is far more complex than for oil lubricated systems; as classified throughout, due to the rheological properties of greases, which is further complicated by the fact that dependent on sample location the results obtained may vary significantly. As a case in point, an uncomplicated comparison; with reference to, Section 2.6.2, Chapter 2, if a grease sample is taken from a bearing wear track, it will be highly degraded and hypothetically have a high concentration of wear metals. In comparison, if the sample is taken from the same bearing, but from an inactive lubricant space, the sample will have underwent little or no degradation and elementally will not be considerably different from a new, or unused grease sample. Whereby the results of latter scenarios are of little benefit as the grease sample is not representative. The fact that lubricant grease do not mix or flow in the same way as oil does in similar mechanical system has benefits for condition monitoring applications, as such retains a history of any contaminates, wear process etc. The accumulation of contaminants and wear metals in the vicinity of the contact zone, make the lubrication situation worsen. Thus, effective monitoring can enable predictive or proactive condition-based maintenance. In basic terms, put ingenuously the analytical procedure for element analysis of lubricants, including grease for the purposes of condition monitoring is quite clear-cut. 52
Where by the initial phase consists of first analysing a sample, in a new or unused condition. Followed by analysing the used grease sample using an appropriate protocol where comparison of data can indicate abnormal wear as an increase in the readings for iron, chromium or copper dependent of metallurgy of component, changes in additives such as boron or other additives can also indicate issues in the used grease or component. The potential issues, concerns and indeed limitations attributed to grease sampling for the purposes of grease condition monitoring, through the research focus of elemental analysis of grease by RDE-AES; are addressed by ASTM D7718 â&#x20AC;&#x201C; 11 [84] guidelines which are abridged in subsequent Sections 3.7.1 and 3.7.2 in conjunction with supplementary grease sampling recommendations and considerations in the latter. 3.7.1. In-service Grease Sampling ASTM D7718 - 11 [84], the internationally recognised standard practice guideline for obtaining in-service samples of lubricating grease. The standard includes guideline methods for obtaining a reliable in-service lubricating grease sample from the various grease-lubricated components including motor-operated valves, gearboxes, pillow-block bearings, electric motors, bearing, exposed bearings, open gears, and failed greaselubricated components. The standard characterises, the proper precautions and steps, tools and methods, to consistently obtain and submit grease samples for analysis. It promotes use of the sampling devices, including both active and passive device arrangement named the grease thief (I & II), shown in Figure 3-5 but along with other arrangements including, tubing and syringe methods presented and states, that various configurations and styles of active grease-sampling devices are possible.
Figure 3-5: Active (Left) and Passive (Right) Grease Sampling Devices
It should be noted that the standard is only meant as a guideline to aid best practice and is not letter by letter pertinent to all grease lubricant sampling scenarios. The standard also indicates that in some cases, it may be necessary to take more than one sample from 53
a piece of equipment to obtain more reliable results; due to load sectors and grease lubricant properties. As highlighted by Shorten [85] through the example of large slew bearings which may never fully rotate in certain applications due to placement. The possibility of obtaining non-representative samples is amplified due to the percentage increase of non-load zones or dead space referred to in Section 3.2. For that reason, to maintain confidence in the condition of the bearing race and rollers, the loaded sectors must be considered and samples taken from more than one point. Shorten [85] outlines general recommendations for sample numbers for conventional slewing bearings of less than four meters in diameter; where convention and best practices dictate that four sectors are sampled. Larger bearings of greater than four meters in diameter can require more samples depending on the size and degree of movement, it is stated some applications may require up to twelve sampling points due to the low relative movement and load configuration. These sample numbers are high and may be even higher in more complex bearing arrangement, but by obtaining representative sample across bearing sectors, it provides the opportunity for the analysis conducted via elemental analysis to create an entire condition representation of the grease-lubricated bearings. In most cases there are three broad approaches to obtain in-service grease for condition monitoring purposes, including that of elemental analysis [86]. Which are summarised as follows: 3.7.2. Approaches for Grease Sampling 1. By partial disassembly; such as by removing the bearing shield (cover) or, screw plugs filler plugs or lifting bearing seals; all can be suitable if bearing is "filled for life" Illustrations of which can be seen in Figure 3-6 and Figure 3-7.
2. By sampling the grease using a probe device such as grease thief (I) or syringe tubing methods outlined ASTM D7718 - 11 [84], see Figure 3-5 and Figure 3-6. Both approaches No. 1 and No. 2 may require multiple sample points as briefly defined in Section 3.7.1.
3. By collecting grease discharge, in a passive sampling process. Passive sampling is achieved, by use of a passive grease-sampling device to collect a sample of inservice lubricating grease from a purge path. Grease discharge is the grease that 54
is purge or extruded from exhaust ports, seals and other openings during relubrication or machine operation. Grease discharge traps are used to prevent sample commination, examples of devices include the grease thief (II) and bellows-type grease discharge traps. Sampling approach number three has largely been dismissed according to Fitch [86] due to ignorance; whereby the condition and state of grease discharge relates both to the state of lubrication and the health of the machine.
Figure 3-6: Tube and Syringe Grease Sampling [87]
Figure 3-7: Grease Sampling from Seal [87]
3.8. Summary Although grease analysis, for condition monitoring purposes, has only of late become significant, it holds many opportunities for increased applications of tribological condition-based monitoring for increased machine reliability on an international level. Even though, grease elemental analysis can be considered potentially more problematical than lubricant oil analysis because of grease composition and lubrication mechanisms are more complex. Grease elemental analysis can be an excellent analysis technique, for condition monitoring where grease elemental importance was reviewed in Section 3.2. Whereby, RDE-AES principles, the focus of this research is one technique that if
55
developed further can be used for cost-saving and increased reliability, across numerous industrial sectors. Consequently, the chapter in Section 3.6 identified key knowledge deficits including; the need for assessment of the consequence of the RDE-AES protocol pursued, in terms of effect on the elemental results for condition monitoring purposes. The methodology set out to address this is present subsequently in Chapter 4. The analysis appraisal of which will be presented in Chapter 5, where conclusions will not only be drawn on the efficacy but also the practical applicability for condition monitoring purposes. In addition, the chapter also highlighted a number of influencing factors that hold significant merit for investigation including; particle size influence and the effect of sampling location on used grease elemental analysis. These expects of grease elemental analysis are explored respectively in Chapter 6 and Chapter 7 through application appraisal studies conducted on grease-lubricated rolling element bearings in industrial applications.
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4. Chapter 4. Methodology for Grease Elemental Analysis by RDEAES
4.1. Introduction The following chapter presents the research approach for the comparative appraisal of simultaneous multi-elemental grease analysis, by RDE-AES through the protocols prescribed in Section 4.3 of this chapter. The experimental RDE-AES grease elemental analysis protocols to be explored will focus on four RDE-AES approaches where a
Simultaneous multi element analysis of used grease
categorical split between whole grease, and dilution methods can be seen in Figure 4-1. Whole Grease â&#x20AC;&#x201C; Cup
Direct
Whole Grease â&#x20AC;&#x201C; Smear Solvent Dilution
Indirect Blank Oil Dilution
Figure 4-1: RDE-AES Grease Analysis Protocols
The chapter sets out the approach used for the appraisal of the RDE-AES techniques that can enable grease elemental analysis. The chapter ends by outlining the data analysis approach and the selection criteria that will be used to discern which method is most applicable to condition monitoring of grease lubricants.
4.2. Grease Elemental Analysis by RDE-AES Assessment The application of simultaneous multi-elemental analysis to grease by RDE-AES presents a number of additional difficulties as opposed to similar approaches on lubricant fluids such as oil. The first concern is the capacity of obtaining a representative sample of the degradation within the grease, for example wear metals and/or contamination, and this primary issue is addressed in, Chapter 6 and 7 through two industrial application appraisal studies. The second complication, which is, the focus of this chapter, is the physical issue of getting the grease sample into the analytical gap for excitation and consequent 57
elemental determination by RDE-AES principles. The approach, most appropriate depends greatly on the physical properties, particularly the consistency of the grease sample, the result of which has consequences for the protocol to be pursued. The four protocols for the purpose of the investigation of the aforementioned challenges is provided in Section 4.3. In normal RDE-AES elemental analysis of oil, as indicated in Figure 3-3, Chapter 3, a graphite disc is pressed onto the end of a shaft which rotates in turn causing the electrode disc to rotate. In the normal use of RDE-AES for lubricant oil; a quantity of oil, approximately 2 ml, is placed in a specimen cup and positioned so that the bottom of the rotating disc passes through the oil as it rotates. An analytical gap is formed between the top of the rotating graphite disc and the tip of the graphite rod electrode. An electric discharge across the gap vaporises the oil which has adhered to the rotating disc. The spectral light emitted contains characteristic wavelengths of the elements present in the oil sample. The internal spectrometer optics capture and splits the emitted light into discrete wavelengths and electronics quantify these wavelengths and simultaneously report the elements in part per million (PPM). It is the issue of adherence to the surface, of the carbon disc that causes impediments for grease analysis due to the semi-solid consistency of grease. With further regard to grease consistency or more readily categorised by NGLI grade, taking the following comparison a grease of an NGLI grade of 00 as opposed to a grease of grade 6, where grade one (grade 00) is comparatively like a thickened oil or semi-fluid and the other (grade 6) soap like in consistency or a semi-solid will consequently require different approaches to enable the sample to enter the analytical gap between the graphite disc electrode and graphite rod electrode. This essential requirement effectively means that a number of protocols are required to enable elemental analysis across all grades, and indeed sample volume. The protocols of concern in this study can be depicted Figure 4-1. Considering the whole grease cup method and ignoring sample volumes, if the grease has a high NGLI grade this method will not be amenable to elemental analysis. For instance the grease will not enter the analytical gap for excitation as it will be too viscous for the 58
rotating graphite disc electrode to draw up, or alternatively the sample cup will be picked up during rotation. Thus, an alternative protocol will be required to allow for elemental analysis of the grease, such as those listed in Figure 4-1. The intention of this study is to perform a repeatability study, in order to determine the correlation between the grease elemental analyses results obtained from the four RDE-AES protocols, across the most common categories of lubricant grease found in rolling element bearing applications with the comparison of data encompassing repeatability or variation, recovery and additional protocol criteria of concern as given in Section 4.4.1. These parameters will illustrate the potential advantages and limitations between the protocols investigated. The ultimate goal is for simultaneous multi-elemental analysis of grease through RDE-AES for condition monitoring that can permit the detection of elements likely to be encountered in typical applications, including wear metals, lubricant additives, thickeners and contaminants. In order to be conducted precisely, and because the composition of lubricant greases are so varied as shown in Chapter 2, the study encompassed four greases. The selection was based on the most common grease type by thickener classification, encompassing the two main classes of grease; soap and non-soap grease. The grease selection used in the study can be seen in Table 4-1. Table 4-1: Grease Selection for RDE-AES Appraisal
Lithium
G4
Bentonite Clay
Highly refined mineral oil
Mineral Oil
59
2
Soap
2
0/00
NonSoap
Mallueas
G3
Soap
Rockman
oil
Starplex
Complex
Renolit
Highly refined mineral
2
Product
Lithium- Calcium
Soap
OHG
oil
Grade
MP2
G2
Highly refined mineral
NGLI
EP 2
Lithium-Complex
Class
LX EP 2
G1
Base Oil
Name
Thickener
Red
ID
4.3. RDE-AES Protocol and Sample Preparation Methodology For each of the grease samples listed in Table 4-1, all samples underwent the same preparation, which involved ensuring the grease sample was homogenised through mixing thoroughly before being held in a 20 ml syringe for delivery during testing, as show in Figure 4-2. The study was conducted on a Spectoil M oil and fuel analysis spectrometer from Spectro Incorporated. The basic RDE-AES set-up configuration can be seen in Figure 4-3, with the sample stand raised.
Figure 4-2: Syringe for Grease Sample Preparation
Figure 4-3: Basic RDE-AES Configuration
60
All RDE-AES parameters such as pre-burn time, exposure time, electrode gap setting, spark intensity and the extracted air gas flow were held constant. A summary of the instrument configuration used for this study is given in Table 4-2. Table 4-2: RDE-AES Parameters Pre-burn Exposure Electrode Gap Extracted Gas Flow (Air)
5 Seconds 30 Seconds 2.286 mm 4 LPM
In order to reduce possible inconsistency induced by disc porosity or trace elements the study used carbon disc from the same manufactured lot number. Each of the grease samples were ran five times over two trials, and by one appraiser for a total of ten measurements per sample for each of the four protocols, with each trial being run in the shortest possible time span. Prior to undergoing testing the Spectoil M was fully calibrated and standard checks were ran at 0 PPM, 100 PPM and 900 PPM, to ensure correct measurements would be obtained. Before the recording of subsequent trial results for each grease and protocol, an additional standards check was run in order to ensure the system remained within calibration limits. Testing was conducted under adapted ASTM D6728 - 11 [88] guidelines and Spectroil M operation guidelines. Once the sample was prepared, it was stored for the shortest possible period in a protective bell jar until undergoing elemental analysis to prevent the risk of atmospheric contamination. Full details of each of the four preparation protocols are detailed in the following sections. 4.3.1. Protocol I - Blank Oil Dilution a. A weighed amount of grease is forced from the 20 ml syringe into a specimen cup, where weight was recorded; target weight 30 g Âą 2 g. b. The equivalent weight of a standard blank oil of 0 PPM (1:2 dilution) at tolerance of Âą 0.2 g. A minimum of 1 g of grease is required for a single specimen preparation. c. The oil diluted sample is thoroughly mixed with non-metallic spatula, which results in a semi-fluid sample suitable for analysis.
61
d. An RDE-AES disposable specimen cup is filled over the brim by forcing grease through a 20 ml syringe, ensuring that no air is trapped in the grease test sample prepared, see Figure 4-4. e. The prepared disposable specimen cup undergoes RDE-AES spectral analysis covered by parameters outlined, where pre-burn of five seconds ensures an even coating of the graphite disc electrode, prior to analysis.
Figure 4-4: Grease Samples Prepared in Disposable Specimen Cup
4.3.2. Protocol II - Whole Grease Smear a. The grease sample is prepared as per Protocol I resulting in test grease filled disposable specimen cup. b. A graphite disc electrode is position onto a holding device, using a lens tissue to prevent contaminant to the surface. c. The grease from the prepared disposable specimen cup is distributed uniformly over the outer circumference of the graphite disc electrode to achieve a target weight of 0.25 g Âą 5 g. A disposable specimen cup was used as a shield in order to prevent contamination or cross contamination of the greases, see Figure 4-5. d. The grease smeared graphite disc electrode is loaded from the holding device, onto, a disc electrode shaft with an application aid, to ensure the smeared grease remains untouched. e. The prepared grease smear the grease graphite disc electrode underwent RDEAES spectral analysis under parameter outlined, with the addition of a disposable specimen cup filled with a 0 PPM standard blank oil 75 cSt (75x10-6 m2/s) kinematic viscosity.
62
Figure 4-5: Protocol II (Whole Grease Smear) Prepared Disc Electrodes with Disposable Specimen Cup in Place
4.3.3. Protocol III - Solvent Dilution a. A weighed amount of grease is forced from the 20 ml syringe into a glass scintillation vial, where weight was recorded. b. A solvent mix of 70% toluene and 30% n-hexane at a dilution of 1:2 is added to vial. The solvent mixture selection was based on a solvent study conducted, additional information on the grease solvent dilution findings can be found in Appendix B. A minimum of 1 g of grease is required for a single specimen preparation. c. The vial cap is placed securely on the scintillation vial, where it is then shaken to ensure full dilution, further dissolution of the sample is achieved using an ultrasonic bath for two minutes. d. The dissolved liquefied grease sample is then analyse by RDE-AES, where sample is placed in a disposable specimen cup and flame retarder cover is put in position, as shown in Figure 4-6 due to the low flash point of the solvents involved.
Figure 4-6: RDE-AES Flame Retarder for Low Flash Point Analysis for Protocol III
63
4.3.4. Protocol IV - Whole Grease Cup a. An RDE-AES disposable specimen cup is filled as per Protocol I. b. Excess grease is removed, employing an additional disposable specimen cup, leaving a level consistent amount of grease for analysis. c. The prepared disposable specimen cup undergoes RDE-AES spectral analysis, under the parameters outlined, where a pre-burn of five seconds ensures an even coating of the graphite disc, prior to analysis.
4.4. Data Analysis & Protocol Selection Criteria The RDE-AES multi-elemental procedure acquired data for twenty-three elements for each grease trial, including iron, chromium, lead, copper, tin, aluminium, nickel, silver, silicon, boron, sodium, magnesium, calcium, barium, phosphorus, molybdenum, titanium, zinc, vanadium, manganese, cadium, hydrogen and carbon. All of the elemental data extracted from RDE-AES protocol tests are in PPM (parts per million), and where necessary the required dilution factors are incorporated into the results provided. As previously indicated, the main variable of concern for the research appraisal is the protocol repeatability or variation in the results obtained with respect to the four RDEAES protocols employed. Repeatability is defined as the variability between the test results, acquired by a single appraiser and/or instrument on the same or replicate item and under the same conditions [89]. The analysis of variance is used to analyse the differences between the means, and the associated protocols of this appraisal. In this context is should be emphasised, that twenty-three elements were analysed for each RDE-AES protocol, the majority of which present in the samples were of little or no significance. Hence, only designated elements will be statistically analysed based their significance for the grease involved. Iron is used throughout all evaluations to form a comparator across all four greases. Elemental iron will be present in the new greases used in the study as a result of the manufacturing process, since final filtration to remove iron after blending is not feasible. As specified, each of the four grease samples G1 to G4 listed in Table 4-1, where analysed five times over two trials by one appraiser for a total of ten repeat analyses per sample,
64
for each of the four protocols. Table 4-3 provides a summary of RDE-AES appraisal bounds and total sample size involved. Table 4-3: Summary of RDE-AES Appraisal Bounds
Grease
G1
G2
G3
G4
Protocol No.
Protocol I Protocol II Protocol III Protocol IV Protocol I Protocol II Protocol III Protocol IV Protocol I Protocol II Protocol III Protocol IV Protocol I Protocol II Protocol III Protocol IV
Trial Size
No. of Trails
Sample Size
No. of Protocols
SubTotal Sample Size
5
10
40
5
10
40
2
4
5
10
40
5
10
40
Total Sample Size
No. of Elements
No. of Measurements
160
23
3,680
The aim of the analysis is to determine the variation in the mean elemental result as a consequence of both the selected protocol and grease type. 4.4.1. Protocol Selection Criteria The selection criteria for the most suitable protocol or protocols for grease elemental analysis by RDE-AES is multifaceted, as the application of the protocol to condition monitoring must be considered in the selection process. Therefore the key section criteria for an elemental condition monitoring protocol needs to emphasised. When analysing elemental analysis data for lubricants and machine components for condition monitoring purposes, it is essential to not only look at the absolute elemental value for the element of concern, but rather the trend in elemental analysis data over a given period. When trend or percentages change in elemental analysis data or in other words, the change in elemental concentrations over repeated analyses is used for the identification of lubricant or component issues. The most important parameter for 65
successful identification of such trends is the reliability of elemental data acquired. Hence, â&#x20AC;&#x2DC;Reliability of Dataâ&#x20AC;&#x2122; will form a central selection criterion for the appraisal that follows in Chapter 5. In other to achieve a measure of the repeatability of the four protocols the variance in mean result will provide direction. This is not only important for the trending reasons outlined above but as wear rates will be different for different grease-lubricated rolling element bearing depending on a number of parameters including; design and even manufacturing variation between identical designs, grease type, age, usage, and operation condition, and accordingly elemental recovery is also important, i.e., the protocolâ&#x20AC;&#x2122;s ability to detect an element at a level of significance. The previous paragraphs do not highlight all the selection criteria required when considering the application of grease elemental analysis for condition monitoring of bearings, particularly when commercial implication are considered. For illustration, grease sample volume requirements will also be a major deciding factor. As the volume of lubricant grease within a bearing can be relatively low generally the majority of the limited free volume within a bearing is not fully packed with a lubricant grease. Therefore the lower the sample volume required for elemental determination, the more desirable the protocol. The final important selection criterion is the cost of analysis. Notwithstanding the fact that the cost of an unanticipated grease lubricant failure, far and above outweighs the costs of either the lubricant used or indeed the component which it lubricates, the cost to determine such is a concern for widespread commercial industrial applications. Consequently, factors such as time cost required, which must include the preparatory and analysis time associated with the protocol in addition the cost of consumables, must be considered along with the potentially hazardous nature of those consumables required to enable grease analysis. Table 4-4 provides a summary of the protocol selection criteria. Table 4-4: Summary of Protocol Selection Criteria
Parameter Repeatability Sample volume
Classification Minimum variance in mean elemental result is desired.
Cost of analysis
Preparation and analysis time, consumables, and cost associated with potential protocol hazards.
Smaller volumes are more favourable.
66
5. Chapter 5. Appraisal of Grease Elemental Analysis via the Development of RDE-AES
5.1. Introduction The following chapter presents findings for the comparative appraisal of simultaneous multi-elemental grease analysis by RDE-AES through the protocols prescribed in Section 4.3, Chapter 4. The chapter concludes with a discussion of the results and findings, on which the outcomes, knowledge and conclusions are applied to genuine condition monitoring scenarios, through condition monitoring application appraisal studies presented in the Chapter 6 and 7.
5.2. Results of Appraisal of Grease Elemental Analyis by RDE-AES As emphasised in Section 4.4, the results of appraisal of grease elemental analysis by RDEAES, will concentrate on designated elements, based on their significance for the grease involved. Iron is used throughout all evaluations to form a comparator. This section provides the consolidated results based on analysis conducted on the data obtained. Table 5-1 provides an outline of the four protocols involved, together with the designations used to presentation of results. Specifications with regard to the greases selected for the RDE-AES appraisal is found in Table 4-1, Chapter 4. Table 5-1: Protocol Designation
Protocol No.
Method
Designation
I
Blank Oil Dilution
Blank Oil
II
Whole Grease Smear
Smear
III
Solvent Dilution
Solvent
IV
Whole Grease Cup
Whole
The result are laid out for each of the four appraisal greases G1 to G4 in turn, where protocol-to-protocol comparison is given for all elements of interest by way of a mean value plot of elemental data with 95% confidence interval, based on the results from a sample size of ten repeat test. By considering the magnitude of variance in elemental 67
results on a protocol-to-protocol basis, it can be determined if the variance in results would have practical implications for the implementation of RDE-AES to condition monitoring applications of grease lubricants. Elemental iron findings throughout the RDE-AES spectral analysis appraisal for each grease is given in greater detail to facilitate appraisal. As of the twenty-three elements measured, iron is the only element that was present in all greases at a level of significance. Following on from the protocol-to-protocol comparison of designated elements, greaseto-grease comparison taking account of the protocols is also provided. The results are laid out as follows: Protocol-to-Protocol Elemental Comparison, Section 5.2.1
G1 - Mean value plots of elemental data, of iron, phosphorus, boron and zinc. - Analysis of variance for Iron.
G2 - Mean value plots of elemental data, of iron, phosphorus, calcium and zinc. - Analysis of variance for Iron.
G3 - Mean value plots of elemental data, of iron, molybdenum, sodium and zinc. - Analysis of variance for Iron.
G4 - Mean value plots of elemental data, of iron, calcium and sodium. - Analysis of variance for Iron.
Note: Appendix C, pp. 158-177, provides additional results for all elements statistically appraised which are not included in the following sections. Grease-to-Grease Elemental Comparison, Section 5.2.2
Grease-to-Grease Protocol Influence on Average Iron Recovery
Grease-to-Grease Protocol Influence on Average Zinc Recovery
Grease-to-Grease Protocol Influence on Average Sodium Recovery
Solvent Control Elemental Averages at 0 PPM and 100PPM Oil Standard, Section 5.2.3
68
The studies sample size was significant enough to detect variation in the mean result with an accepted alpha level of 0.05. Consequently, leaving only a 5% chance of finding an effect that does not really exist within the data thus enabling confident comparison of simultaneous multi-elemental analysis of grease by RDE-AES. 5.2.1. Protocol-to-Protocol Elemental Comparison G1: Lithium-Complex Grease
Figure 5-1: Mean Plot of Elemental Data with 95% Confidence Interval - G1
69
Table 5-2: Analysis of Variance for Iron - G1
Figure 5-2: Distribution of Data Iron-G1
Figure 5-3: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G1
Figure 5-4: Means Comparison Chart Iron-G1
70
G2: Lithium-Calcium Complex Grease
Figure 5-5: Mean Plot of Elemental Data with 95% Confidence Interval â&#x20AC;&#x201C; G2
71
Table 5-3: Analysis of Variance for Iron â&#x20AC;&#x201C; G2
Figure 5-6: Distribution of Data Iron-G2
Figure 5-7: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G2
Figure 5-8: Means Comparison Chart Iron-G2
72
G3: Lithium Grease
Figure 5-9: Mean Plot of Elemental Data with 95% Confidence Interval - G3
73
Table 5-4: Analysis of Variance for Iron â&#x20AC;&#x201C; G3
Figure 5-10: Distribution of Iron-G3
Figure 5-11: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G3
Figure 5-12: Means Comparison Chart Iron-G3
74
G4: Bentonite Clay Grease
Figure 5-13: Mean Plot of Elemental Data with 95% Confidence Interval â&#x20AC;&#x201C; G4
75
Table 5-5: Analysis of Variance for Iron â&#x20AC;&#x201C; G4
Figure 5-14: Distribution of Data Iron-G4
Figure 5-15: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G4
Figure 5-16: Means Comparison Chart Iron-G4
76
5.2.2. Grease-to-Grease Elemental Comparison
Figure 5-17: Grease-to-Grease Protocol Influence on Average Iron Recovery
Figure 5-18: Grease-to-Grease Protocol Influence on Average Zinc Recovery
77
Figure 5-19: Grease-to-Grease Protocol Influence on Average Sodium Iron Recovery
5.2.3. Solvent Control Results Table 5-6: Solvent Control Elemental Averages at 0 PPM and 100PPM Oil Standard Average Average 0 PPM 100 PPM 0 PPM 100 PPM Iron 0 97 Magnesium 0 99 Chromium 0 90 Calcium 0 96 Lead 0 94 Barium 0 105 Copper 0 102 Phosphorus 0 108 Tin 0 92 Zinc 0 95 Aluminium 0 102 Molybdenum 0 95 Nickel 0 95 Titanium 0 95 Silver 0 99 Vanadium <1 102 Silicon 29 130 Manganese <1 106 Boron 0 96 Cadium 0 103 Sodium 30 125
78
5.3. Discussion of Grease Elemental Analysis via the Development of RDE-AES The overall inference from the results demonstrates the feasibility of obtaining relatively satisfactory elemental results for all RDE-AES protocols involved in the appraisal for the greases involved, albeit with varying degrees of confidence and levels of elemental recovery. When the analysis of variance results attained are compared for the four preparation protocols outlined, it is evident that distinct relative differences are present between the four methods. Furthermore, the difference or variance in results between means for the methods, greases and elements encompassed can be acknowledged to be statistically significant. This can be concluded at a 0.05 level of significance which correlates with the alpha value used during analysis, leaving only a 5% chance of finding an effect that does not really exist within the data. However, this statistical significance does not automatically imply practical significance to the result obtained, and this issue will be discussed later. The level and significance in variance of the mean result as a function of the preparation protocols is made visible by the means comparison charts, where intervals that do not overlap indicate means that differ from each other as shown in Figure 5-4, Figure 5-8, Figure 5-12, Figure 5-16 and through inspection of data in Table 5-2 to Table 5-5 with additional elements provided in Appendix C. As expected the amount of variation of smallest proportion is present between the oil dilution and whole grease methods, across the widest range of greases and elements involved in the study. Through the consideration of the size of differences in means for the elements of each grease sample it can be concluded that the variation in elements encompassed can be recognised to hold practical implications that are statistically significant for comparison purposes. The explanation for the variations and differences originates in the protocolâ&#x20AC;&#x2122;s preparatory requirements to enable analysis due to the grease structure. Undoubtable this bares an impact on the results obtained with the strongest indication of this being illustrated in the elemental results attained through the use of a solvent dilution preparation protocol. The dilution effect is not as dominant with the blank oil dilution as it holds a kinematic 79
viscosity of 75 cSt (75x10-6 m2/s). Protocol III, the solvent dilution procedures for grease G1-G3 exhibited a significant increase in elemental recovery in contrast to grease G4, where a significant decline in this increasing effect of elemental recovery was identified for all elements tested (apart from sodium) the cause for this is explained by the elemental constituents of the solvent solution used which is discussed later. The rationale and justification for this effect is due to the influence of grease sample consistency on RDE-AES elemental recovery as pointed towards in Section 3.5, Chapter 3. The analysis of variance conducted permitted for the delineation of both the positive and negative effect of grease consistency alteration of the test samples, as shown in Figure 5-17 to Figure 5-19. The positive effect of greater recovery due to the decrease in consistency can be seen in greases G1-G3. Samples G1-G3 began with an NGLI grade of 2, as given in Table 4-1, Chapter 4. Thus the addition of the solvent reduces the consistency of the grease significantly, which in turn, had the effect of increasing the volume of the sample reaching the analytical gap and thus the quantity of elements carried within the grease for excitation. Correspondingly, the negative effect of Protocol III and the specific solvent when used for grease G4 which began with a low NGLI grade of 0/00, the addition of the solvent reduces the consistency of the grease significantly which in turn had the effect of decreasing the quantity of the sample reaching the analytical gap and thus the quantity of elements carried with it for excitation. The positive effect of increase the viscosity is also seen in G4 where the additional of the blank oil acts to thicken or increase the consistency of the low NGLI grade grease. However, the results show a limited contradiction to this assumption in grease G4 with increased sodium recovery for solvent dilution preparation; the reason for this is explained when results in Table 5-6, are taken into consideration. Of the elemental solvent dilution control, the solvent mixture used in the study contained a level of elemental sodium as a result of the manufacturing process. For oil lubricants, the influence of viscosity on RDE-AES results as stated in Section 3.5, Chapter 3, has been carried out for example by Saba [79], demonstrating significant correlation between elemental results and the viscosity of test oil sample involved. Correspondingly the findings of the research conducted would strongly point towards 80
similar correlations when considering the influence of grease consistency on the results obtained by RDE-AES protocols appraised. Moreover, it can be suggested that there may be an ideal consistency level that would serve to optimise elemental recovery in a grease sample if the consistency could be controlled precisely during the excitation process. The volume reaching the analytical gap for excitation, and consequent elemental determination by RDE-AES is governed by the physical constraints that the protocols appraised in this study are trying to overcome. Alternative influencing factors were also referred to in Section 3.5, Chapter 3, including: sampling, excitation parameters, porosity of the graphite disk electrode, lubricant composition, and particle size and morphology. It can be strongly assumed that the first three parameters listed played a negligible impact on the results obtained as all these were kept constant throughout the appraisal for each of the four protocols. Lubricant composition, and to a lesser extent particle size and morphology are deemed to play a greater influence on results obtained in contrast to the three parameters that could be, and, were kept constant throughout. Composition effects on results, are specifically interesting as it has been shown in other studies that lubricant composition has an effect on the efficiency of RDE-AES elemental analysis. For example where the variance between hydrocarbon and ester-based lubricant oils exists, this effect can be accepted to have similar or greater implications for grease composition including base oil and thickener composition and even the underlying physical structure of the grease may impact on the results. The aforementioned composition influence of grease are highly likely to result in more energy being required to break down the grease structure for excitation, thus influencing elemental results that can be achieved. This may suggest potential benefits of a process that would remove the base oil components and soluble elements from insoluble elements. Such an approach may be an attractive option for quantitatively identifying ferrous and nonferrous wear, and contaminant in grease-lubricated systems. As noted in Chapter 3, rotrode filter spectroscopy (RFS) has been used as a secondary screening test for coarse ferrous and
81
nonferrous wear and contaminant particles in oil by removing insoluble components and oil [78]. An additional, area to consider in this discussion on the appraisal of grease elemental analysis by RDE-AES is that particular elements are more difficult to accurately measure through RDE-AES and other spectrographic techniques, this being due to the different properties of the elements with regards to excitation and consequent spectral emission determination. For instance elements such as zinc or phosphorous are more difficult to accurately measure than stable elements, for example wear metals such as iron or copper. Therefore, a larger variance in the mean result may be acceptable for condition monitoring purposes of certain elements, found in lubricant grease. This leads to the argument that although significant variations exist between the four protocols appraised, the practical significance when taking each protocol on its own is of diminutive concern; as lubricant condition monitoring judgements through elemental analysis is characteristically conducted on a trend or percentage change based procedures, with warning limits set appropriately to enable preventive action. 5.3.1. RDE-AES Grease Elemental Analysis Protocol Selection In view of the previous paragraph, results and indeed selection criteria set out in Section 4.4.1, Chapter 4. There are a number of parameters when considering a technique for a selection for use as a condition monitoring tool. For the four protocols outlined and their application to elemental condition monitoring of grease-lubricated rolling element bearings the selection of the most appropriate method depends on the information required. Where appropriate trade-offs must be made to allow selection which include analysis time including preparation, the competency or confidence in result based in repeatability, elemental recovery, expense, potential hazards, and importantly sample volume requirements. Table 5-7 provides a summary of consideration with respect to the strength and limits of the four perspective protocols. With regards to the RDE-AES protocols appraised via the review of the variance present in the results obtained and considering the possible trade-offs. The results would indicate that the Protocol II (whole grease smear) provides the greatest potential for grease elemental analysis by RDE-AES for condition monitoring purposes. 82
Table 5-7: RDE-AES Protocol Selection Considerations Protocol No.
Strengths
Requires 0 PPM Blank Oil Dilution effects need to accounted for in analysis
Smallest sample volume >0.3 g Greatest possibility for additional analysis with remaining sample Simple preparation Lowest relative variance in mean result No additional nonstandard consumable No dilution effects Highest recovery for high NGLI grade greases i.e. positive consistency effect for high NGLI grade greases May be necessary for very high NGLI grade greases
Requires 0 PPM Blank Oil
Hazardous solvents required Solvent contamination presented as issue may require added filtration step Negative consistency reduced Need for flame retarder (additional time) Dilution effects need to accounted for in analysis Reducing sample volume through increasing dilution factor likely to have negative effect Largest Sample Volume ~2 g Not Suitable for high NGLI grade grease Only suitable for a small range of NGLI grade grease i.e. NGLI ~ ≥2
Smear
II
Positive consistency effects for both low and high NGLI grades Sample volume <1 g Possibility to reduce sample volume through higher dilution factor
Blank Oil
I
Limits
III
No preparation No additional consumables No dilution effects
IV
83
Whole
Solvent
This can be affirmed based on the small subset of greases in the RDE-AES appraisal presented; Protocol II the whole grease smear protocol showed significantly less deviation over the greases and elements tested. Moreover, the protocol requires no hazardous substances such as solvents. It requires the smallest volume of sample, additionally preparation time before analysis is kept to a minimum, and further opportunities for enhancement and refinement exist. The findings presented would suggest for commercially feasible grease lubricant condition monitoring through elemental analysis based on RDE-AES principles, certain preparation procedures may be more suitable for specific situations. Yet the author considers that Protocol II holds the greatest potential, based on the results. Which could be enhanced upon further development, in the form of increased RDE-AES performance for grease analysis including; elemental sensitivity, the removal for the requirement for bank oil due to temperature at analytical gap and the major elemental limitation of not having the ability to detect lithium using the current configuration. Lithium as stated in Section 2.4.2, Chapter 2 is the most common grease thickener at present. Further investigation including an inter-laboratory study is warranted. An international standard could be developed for grease condition monitoring through RDE-AES protocols, in a similar fashion to that widely recognised for oil lubricants and for new greases for qualification purposes. This would have a major impact for all industries that rely on grease-lubricated equipment, including grease-lubricated rolling element bearings in industries where unpredicted failure of such components can have major economic and even safety consequences, particularly in the power generation, transport and manufacturing industries. This is particularly true, where alternative means of condition monitoring provide reduced lead times for failures prevention, or alternatives such as vibration or thermal analysis on relatively slow moving parts, would require extremely complex computations to detect or identify the onset of an issues. Furthermore, the findings presented in this chapter can address the motives of why research work was carried out, in order to develop and investigate elemental analysis of grease lubricants for condition monitoring purposes as detailed in Section 1.3.1, Chapter 1 â&#x20AC;&#x2DC;Motives for the Researchâ&#x20AC;&#x2122;. 84
5.4. Conclusion of Grease Elemental Analysis via the Development of RDE-AES In conclusion, the appraisal presented within this chapter of grease elemental analysis by RDE-AES using existing spectrographic equipment designed primarily for oil analysis, has been demonstrated to be feasible and thus in principle useful as a tool to evaluate greaselubricated equipment condition. Even though grease elemental analysis has not emerged as a central condition monitoring tool in the same manner as oil elemental analysis has even though both lubricants types are essential for the operation of equipment. This can be attributed to the additional difficulties of the physical issues of getting the grease sample into the analytical gap for excitation and consequent elemental determination as outlined in Section 4.2, Chapter 4 and industrial tendency to pursue more complex but possibly less effective alternatives. RDE-AES preparation procedures designed to address such challenges have been tested and compared. The significant variance in mean values which is shown to be dependent on preparation protocol, where random error alone can be discounted from the appraisal conducted. However, the precise factors that govern this has not been established definitively. Granted, possible reasons where alluded to or suggested in the discussion in Section 5.2, where sample consistency, elemental particle properties size, shape and density can be assumed to be underlying factors which influence the results. Further investigation would be required to identify the precise underlying factors. Nonetheless, the appraisal of the relatively small but select subset of greases in the RDEAES appraisal presented in this chapter, has enabled the confident selection of a suitable protocol for application appraisal studies which are presented in the subsequent chapter. In short, Protocol II the whole grease smear method was identified as the most promising option for the completion of accompanying appraisals studies of the application of RDEAES grease elemental analysis to condition monitoring of grease-lubricated rolling element bearing.
85
6. Chapter 6. Appraisal Study 1: Particle Size Influence
6.1. Introduction The following section presents, an overview to an appraisal study of particle size influence of used grease elemental analysis, through rotating disc electrode atomic emission spectroscopy (RDE-AES) and inductively coupled plasma mass spectroscopy (ICP-MS). Where respectively RDE-AES was conducted via, Protocol II the whole grease smear method, and ICP-MS, through an aqueous solution, processed by a sulphated ash digestion, the procedure followed is outlined in Section 6.2. The used grease samples for the comparative particle size limitations assessment of grease elemental analysis, were acquired from grease-lubricated wind turbine bearings. The used grease samples were obtained using approach No. 3 outlined in Section 3.7.2, Chapter 3; a passive collection method was employed, following ASTM D7718 - 11 [84] protocols and the use of a bellows-type grease discharge trap. The grease sampling approach adopted can be seen in Figure 6-1.
Figure 6-1: Bellows-Type Grease Discharge Catcher on Bearing Discharge Port (Left). Extraction of Used Pitch Bearing Grease Sample from Bellows-Type Grease Discharge Catcher (Right)
Samples were provided courtesy of EcoPower Ltd, and taken from a Vestas V52 3 blade horizontal axis wind turbine with a rotor diameter of 52m; turbine No. 20 of Raheen Barr Wind Farm Co. Mayo such a turbine would has a rotational operational interval of 14 rpm to 31.4 rpm. The used grease samples were acquired from each of the three Rollix balls without gear pitch bearings, referred to hereafter as Pitch Bearing 1, 2 and 3. Figure 6-2 below provides an illustration of the location of pitch bearings, which are used to provide
86
support for control adjustments of the blades to optimise speed for power generation in a wind turbine. Figure 6-3 taken from inside the nacelle of turbine No.20, Raheen Barr Wind Farm showing Pitch Bearing 3.
Location of wind turbine pitch bearings. Pitch bearings provide support for control adjustments of the blades to optimise speed for power generation.
blade to optimize speed
Figure 6-2: Location of Wind Turbine Pitch Bearings Shown with Nacelle Removed Adapted from [90]
Figure 6-3: Image of a Pitch Bearing 3 Taken from Inside the Nacelle
The opportunity for sampling where an anticipated occasion of severe bearing wear occurred, on the Vestas wind turbine in question, as a result of it undergoing a known damage condition which resulted in a complete grease purge for the system. Therefore, the grease samples from the three Rollix balls without gear pitch bearings of the Vestas wind turbine were acquired post a damage condition, were one blade of the turbine had been damaged by a lighting strike to the blade tip. This subsequently resulted in blade tip damage, which causes increase levels of wear particle generation due to additional stress 87
on the pitch bearing supporting the damaged blade in question. Such circumstances would be expected to result in highly accelerated wear including increased primary wear such as fretting at standstill and secondary wear such as fatigue spalling of the bearing surfaces. The Rollix balls without gear pitch bearings in question were originally manufactured in 2002 and have been in operation since August of that year. Such bearings are extremely common in wind turbine applications, and are found in 50% of the wind turbines in the world [91]. The aim of the appraisal study is to comparatively investigate, spectrographic elemental analysis with regards to particle size influence and limitations for the purpose of condition monitoring of grease-lubricated rolling element bearings, via the methods to be presented.
6.2. Comparative Grease Elemental Analysis Procedure, RDE-AES vs. ICP-MS For the most part the grease sample of interest, for monitoring bearing and lubricant performance is the small portion of the grease doing the work at the contact interfaces, in the load zone of the bearing. As indicated in Section 3.2, Chapter 3, the area closest to the working zone will have the most evidence of wear, contamination and degradation and in general will be the most representative. Although, in most cases including this appraisal it is unachievable to obtain a grease sample located directly in the contact interface without bearing disassembly. In this study representative sampling was achieved, through a passive sampling approach adhering to ASTM D7718 - 11 [84] as reviewed in Section 3.7, Chapter 3. Once the three samples were obtained through the passive approach, the initial procedure was to ensure all samples were fully homogeneous and this was achieved by meticulously mixing the entire grease discharge from each bearing prior to elemental analysis. The comparative elemental analysis preformed, was conducted using both RDE-AES by means of the whole grease smear method which was outlined in Protocol II in Chapter 4 and, ICP-MS by using a sulphated ash digestion procedure to process attain an aqueous solution of the grease sample to allow for analysis. Full detail of the ICP-MS procedure followed is given in Section 6.2.1. 88
For each of the three grease samples obtained from the three bearings, Pitch Bearing 1, 2 and 3, three sample preparations were prepared for each and subsequent spectrographic analysis by both RDE-AES and ICP-MS. This was done to in order draw full validation and confirmation of the results and conclusions obtained from the spectrographic elemental analysis of the grease. As classified, in Section 3.3.2, Chapter 3 elemental analysis has distinct particle size limitations, which in essence make them "blind" to particles that are over a specific size range. Where respectively for RDE-AES the maximum detection limits are approximately 8 µm and are considered "blind" to particles greater than 10 µm; for ICP-MS maximum particle size limitations are lower, at approximately 2 µm for ICP-MS and are considered "blind" to particles greater than 3 µm. Each method has additional limitations and benefits as highlighted in Section 3.3.2, Chapter 3. However, herein, Table 6-1 provides summarised particle size limitations for the two methods. Table 6-1: Summary of RDE-AES and ICP-MS Particle Size Limitations
RDE-AES Particle Size Limitations
- Efficient limit 8 µm - Blind above 10 µm
ICP-MS - Efficient limit 2 µm - Blind above 3 µm
To overcome these particle size limitations a wear particle analysis study will be conducted by performing analytical ferrography of the samples obtained for the three pitch bearings. The analytical ferrography study aims to validate finding of the comparative elemental analysis study. Analytical ferrography will also be used to determine and identify the size distribution and more importantly the morphology of wear particles generated of the associated wear regime. Through the application of a secondary process in this case a wear particle analysis by analytical ferrography a greater delineation of the wear condition can be asserted for this appraisal study. 6.2.1. ICP-MS Grease Elemental Analysis Procedure To obtain an aqueous solution suitable for grease elemental analysis by ICP-MS, the process followed similar procedures as would for sulphated ash digestion of other
89
substances, in accordance with ASTM D7303 [19] guidelines for grease qualification testing of elements by ICP-AES. The abridged procedure used in the study was as follows: Approximately, 1 g ± 0.1 g of grease was weighted into a 50 ml porcelain crucible to allow for the high temperatures required. The grease sample was then charred on a hot plate until reduced to approximately 0.5 g. After cooling, 2 ml of sulphuric acid was added to the residue and heated until the fumes cease to develop. The charred sample was placed in a muffle furnace at approximately 525 °C ± 5 °C until the black colour was gone and the grease sample was fully digested. The ashing process was set to 2 hours but the process was repeated on samples to ensure complete digestion. Once removed from the muffle furnace and allowed to cool, 5 ml of nitric acid was added and the sample was re-heated to dissolve remaining solids. The solution was brought to initial dilution volume of 50 ml in a volumetric flask with deionized water, the initial solutions before subsequent dilution and filtration can be seen Figure 6-4. The grease sample could then be analysed by ICP-MS following internal practice and ASTM D7303 guidelines with operation conditions, as per Table 6-2.
Figure 6-4: Aqueous Grease Sample Solutions after Sulphated Ash Digestion Table 6-2: ICP-MS Operation Parameters
Forward Power Coolant Gas, Argon Auxiliary Gas, Argon Nebuliser Gas, Argon Sample uptake rate
1150W 12 L / min 0.5 L / min 0.7 L / min 1 mL / min
6.3. Comparative Grease Elemental Analysis Results The results and discussions to ensue present the spectrographic elemental analysis findings from the comparative grease elemental analysis assessment conducted on the aforementioned wind turbine rolling bearings. All elemental results are expressed in parts 90
per million (PPM); based on normalisation of PPM results returned on test equipment involved, of grease weight used, and the dilution factor if applicable. The results present the average elemental concentration of both the RDE-AES and ICP-MS methods, based on the result from three separate preparations, conducted under the same conditions as detailed in Section 6.2. After the comparative elemental results are presented they are discussed in Section 6.4 where the ferrographic analysis diagnosis is provided in Section 6.4.1. It should be noted that the elements comparison range in the study was constrained by the limitation of the ICP-MS due to requirements for internal elemental standards to enable testing which were not available. However, it should be emphasised that this appraisal study was primarily concerned with the wear metal contaminates present and what they indicate in respect to the condition assessment judgements of the wind turbine pitch bearings, plus the influence of particle size on elemental results, post a known damage condition i.e., lighting strike in this case to blade number 3, which correlates with Pitch Bearing 3 in this appraisal for both RDE-AES and ICP-MS elemental analysis. The elemental results obtained by both methods are given in Table 6-3 to Table 6-8 in which both wear metals; iron, copper, tin and additives; barium, zinc and manganese were present in the grease discharge from the Rollix pitch bearings. More detailed results for the most important wear metal element for this appraisal; iron, are provided in Figure 6-5 and Table 6-9, with the elemental comparison of the additive barium, given in Figure 6-6 and Table 6-10. Barium was chosen to act as comparator for the iron wear metal results presented because elementally in this case barium sulfonate (NaSul) is relatively stable and would not be lost through the volatile process of sulphated ash digestion required for ICP-MS analysis. Barium sulfonate, which is used as an additive in grease for its rust inhibiting properties, would offer a component that would not be affected by significant variations in particle size in contrast to iron wear particles, and is within particle size limitations for both elemental comparison methods of the appraisal.
91
Table 6-3: RDE-AES Elemental Analysis Result, Pitch Bearing 1 Iron Chromium Copper Tin Barium Zinc Manganese Mean 554.8 179.4 26.6 64.5 13.5 287.5 203.5 Max 591.8 193.4 30.9 74 14.1 300.9 214.5 Min 461.8 146.8 21.4 63 8.4 246.4 172.7 Average 536.1 173.2 26.3 67.2 12 278.3 196.9 Table 6-4: RDE-AES Elemental Analysis Result, Pitch Bearing 2 Iron Chromium Copper Tin Barium Zinc Manganese Mean 476.1 92.7 50.5 49.3 14.0 84.9 204.3 Max 700.2 100.0 54.6 51.7 14.6 85.9 218.2 Min 464.0 91.5 49.8 46.7 12.7 82.6 201.1 Average 546.8 94.7 51.6 49.2 13.7 84.5 207.9 Table 6-5: RDE-AES Elemental Analysis Result, Pitch Bearing 3 Iron Chromium Copper Tin Barium Zinc Manganese Mean 3142.0 133.2 25.1 69 11.7 169.3 169.3 Max 3389.0 133.2 27.9 81.3 12.0 170.3 171.6 Min 3018.0 113.3 21.9 69 10.4 156.4 146.7 Average 3183.0 126.2 24.9 74.5 11.3 165.3 162.5 Table 6-6: ICP-MS Elemental Analysis Result, Pitch Bearing 1 Iron Chromium Copper Tin Barium Zinc Manganese Mean 33484.7 248.3 33.4 0.3 9.6 229.4 399.3 Max 46825.5 354.6 35.3 0.6 12.0 233.9 429.8 Min 28472.8 206.3 31.0 0.1 9.5 209.3 316.9 Average 36261.0 269.7 33.2 0.3 10.4 224.2 405.0 Table 6-7: ICP-MS Elemental Analysis Result, Pitch Bearing 2 Iron Chromium Copper Tin Barium Zinc Manganese Mean 41847.3 59.5 45.2 3.7 11.2 176.6 316.9 Max 45496.9 66.8 46.4 5.3 12.1 185.8 431.2 Min 26820.5 40.1 39.1 2.2 9.4 154.6 316.9 Average 38156.9 175.6 37.2 1.6 10.6 194.8 391.0 Table 6-8: ICP-MS Elemental Analysis Result, Pitch Bearing 3 Iron Chromium Copper Tin Barium Zinc Manganese Mean 6052 45.6 38.2 1.1 9.1 196.5 141.7 Max 11197.7 89.6 41.7 1.4 9.8 196.5 147.9 Min 5131.3 37.4 31.8 1.0 8.7 137.0 133.0 Average 7460.3 57.6 37.2 1.2 9.2 176.7 140.9
92
100000.0
Rollix Pitch Bearing 1
Rollix Pitch Bearing 2
7460.34
Rollix Pitch Bearing 2
38054.90
Rollix Pitch Bearing 1
10.0
36260.97
546.78
100.0
3183.00
1000.0
536.13
Iron, PPM
10000.0
1.0 Rollix Pitch Bearing 3
RDE-AES Smear
Rollix Pitch Bearing 3
ICP-MS
Figure 6-5: RDE-AES vs. ICP-MS Comparison of Iron Elemental Analysis Result, a Wear Metal Table 6-9: RDE-AES vs. ICP-MS Relative Difference of Iron Elemental Analysis Results
Pitch Bearing 1 Pitch Bearing 2 Pitch Bearing 3 Average
RDE-AES ICP-MS Relative Difference 536.13 36260.97 194% 546.78 38054.90 194% 3183.00 7460.34 80% 1421.97 27258.74
13.74
11.34
10.39
10.91
9.24
10.0
12.01
Barium, PPM
100.0
Rollix Pitch Bearing 1
Rollix Pitch Bearing 2
Rollix Pitch Bearing 3
Rollix Pitch Bearing 1
Rollix Pitch Bearing 2
Rollix Pitch Bearing 3
1.0
RDE-AES Smear
ICP-MS
Figure 6-6: RDE-AES vs. ICP-MS Comparison of Barium Elemental Analysis Result, a Stable Additive (Rust Inhibitor)
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Table 6-10: RDE-AES vs. ICP-MS Relative Difference of Barium Elemental Analysis Results RDE-AES ICP-MS Relative Difference Pitch Bearing 1 12.01 10.39 14% Pitch Bearing 2 13.74 10.91 23% Pitch Bearing 3 11.34 9.24 20% Average 12.36 10.18
6.4. Discussion & Validation of Particle Size Influence Investigation A feature of grease analysis, as opposed to oil analysis, is that contaminants and wear debris are not uniformly distributed throughout the lubricant, and as stated previously, particle levels will tend to be substantially higher. This may lead to samples with variances in additive, wear debris and contamination content. The apparent difficulty for grease analysis is the integrity of the sample; the grease sample must be as representative as possible to the actual condition of the system in question. In this appraisal study, this issue was allied through the analysis of the entire grease discharge of the Rollix pitch bearings in question in adherence to ASTM D7718 - 11 [84]. The discussion which follows focuses on the comparative spectral elemental analysis of grease with regards to particle size limitations, in advance to the presentation of the wear particle analysis validation conducted by analytical ferrography which is provided in Section 6.4.1. Findings are discussed in conjunction for validation, and to provide greater detail of the wear process within the wind turbines pitch bearings. As noted, in the opening of Section 6.3 the range of elements that could be compared by both RDE-AES and ICP-MS was considerably reduced due to the limitations of the ICP-MS test requirements. An internal standard is required to enable ICP-MS test results due to machine operation the lack of which reduced the range of elements available for comparison. As defined in Chapter 5, RDE-AES allows for the simultaneous detection of up to twenty-three elements. In this incidence the range of elements available for comparison in this appraisal was reduced to a range of eleven elements due to the aforementioned restrictions. However included elemental groups of primary interest; which included all key wear metals. As specified previously, elemental analysis of a grease can permit the determination of the condition of both the grease lubricant used and the equipment which it is lubricates. In this appraisal, the primary objective was the 94
investigation of the influence of particle size on the elemental analysis results obtained from the methods involved, and it is this which is the focus of the ensuing discussion. The findings from the comparative elemental analysis appraisal conducted have been provided in Sections 6.3 where strong confidence in the findings was achieved based on the validation conducted. Considering the comparison of additive elemental results of a stable element, which would naturally have a relatively constant particle size distribution and be within the particle size limits of both methods respectively. To this end barium was chosen, a common additive rust inhibitor as a stable comparator for such reasons. The comparative results of which were outlined in Figure 6-6 and Table 6-10. The relative difference of barium for both methods indicate no major significance, at maximum showing a 23% relative difference which can be accounted for by the high dilution requirements and impact as a result of the volatile ICP-MS preparation process these issues are discussed in greater detail later. However, in comparison of iron wear metal results of both methods it is clear that an issue with undeviating comparison exists, where disparities between elemental averages can be seen to be orders of magnitude in difference, this is strikingly illustrated by irons widely contradictory comparative results as shown in Figure 6-5. By and large, the relationship appears to be linear, for iron with average elemental results of Pitch Bearing 1 and 2 both appearing to be relatively constant which each other, for both RDE-AES and ICP-MS results. When iron wear results of each method are compared to each other a significant disparity in comparison with relative difference of 194% for both Pitch Bearing 1 and 2 exists. On the other hand, the relative differences of Pitch Bearing 3 between RDE-AES and ICP-MS indicates a seemingly more amenably closer result in comparison, with a relative difference of 80%. Leading to the conclusion that a significant difference is present in elemental result for iron a key wear metal when comparing RDE-AES and ICP-MS results. The reason for this can be clarified as follows; of the spectral elemental analysis methods compared in the appraisal study, both have elemental detection particle size limitations, which were summarised in earlier in Table 6-1. Both RDE-AES and ICP-MS instruments 95
suffer from size limitation effects with the particle size limitations of ICP-MS at 2 Âľm, being more severe than for RDE-AES at 8 Âľm. The research conducted accredited such restriction to the need for the sample and particles to be nebulised for excitation, where the requirement to pre-filter to prevent nebuliser blockage was present. The issue can be anticipated to be somewhat reduced as the grease tested by ICP-MS underwent a sulphated ash digestion process, prior to sample dilution, in essence dissolving or breaking down a percentage of the lager wear particles in the bearing grease. The significance of particle size limitations even after acid digestion can still strongly be seen in the comparative results shown in Figure 6-5. Whereby the RDE-AES and ICP-MS average element results effectively contradict each other. As case in point, if the results from either method were taken individually they would lead to a different bearing condition diagnosis being made for condition monitoring purposes therefore results are in total contradiction. The results of the RDE-AES grease elemental analysis method provided a clear indication that Pitch Bearing 3 as given in Figure 6-5, exemplifies a significantly poorer state of bearing condition or health with increased levels of wear deterioration depicted by the high levels of iron present as opposed to Pitch Bearings 1 or 2. Results derived credibly allow the inference that Pitch Bearing 3 is undergoing an increased level of wear-out, even without historical trend data for comparison being available. With RDE-AES iron wear levels of 3,183.00 PPM distinguished from the average wear for all three pitch bearings of 1421.97 PPM, Table 6-9. In this appraisal of three pitch bearings from the same wind turbine, progressive failure indications can be determined from the elemental assessment of grease without the requirement for previous trend data, in this instance due to the fact that the three pitch bearings have effectively operated under identical operating conditions. The findings from the RDE-AES grease elemental analysis through Protocol II, the whole grease smear method, fully correlate with the known damage condition of blade number 3. As evident from Figure 6-5 and Table 6-9, a significant conflict in the indicated condition can be seen in the results presented comparatively for RDE-AES and ICP-MS. Taking the averages iron wear of ICP-MS alone result would indicate that both Pitch Bearing 1 and 2 96
were in approximately the same condition of deterioration, were as Pitch Bearing 3 which was known to have undergone a known damaged condition presents the least advanced deterioration. The elucidation of this conflict in ICP-MS results can once again be accredited to the severe elemental particle size limitation of the ICP-MS and the higher particle size detection limit range of the RDE-AES method. Simply put the reason for this conflict is that the ICP-MS method was effectively blind to a greater number of large wear particles than the RDE-AES method. Which for ICP-MS can be considered to be particles greater than 2 µm, with the presence of particles of 3 µm or greater simply not being detected. The results show that the severe particle size limitation of ICP-MS were present even after sulphated ash digestion, which in theory should facilitates a greater recovery of large particles for the ICP-MS method, as the volatile process should in aid in the breaking down of larger particle to level that that they should become within range. It is reasoned that the levels of recovery of larger wear particles which remained present in the aqueous solution after the grease ashing process, had been filtrated out before nebulisation or may not have been excited fully in the plasma flame in the excitation process, leading to the significantly reduced detection levels of iron wear particles as illustrated in the results. In contrast, elemental analysis by RDE-AES has a considerably greater recovery level for larger particles present notwithstanding the particle size limitations of its own, which are generally deemed to be particles greater than 8 µm with the presence of particles of 10 µm or greater simply not being detected. Therefore the particle size limitations underline the reason for the significant contradiction in comparative elemental analysis results and highlights the significant influence of particle size for condition monitoring of greaselubricated bearings. The discussion will now draw attention to other clarifications concerning the divergence in the comparative elemental results that have not been addressed thus far. The most obvious reason as pointed out previously is the different preparatory requirements for RDE-AES and ICP-MS that enable analysis, which required due to lubricant greases semisolid structure. Again the strongest illustration of this is seen in the, ICP-MS sulphated ash procedure although yielding a significantly higher recovery particle size limitations and 97
relatively unstable elements negate this benefit and thus yield higher deviation within results even when variance caused by sampling may be assumed to be eliminated. The simple explanation is due to the volatilisation in the ICP-MS digestion process required with temperatures of over 525 째C, and the use of sulphuric acid to aid the process, issues of loss of less stable elements is clear. This effect is not as prevalent in results presented thus fare. Since common volatile additives such as phosphorus could not be compared due ICP-MS limitations, whereas relatively stable metallic elements were compared. However, the significance of elemental loss for ICP-MS in contrast to RDE-AES can be best seen best in the comparison of results for tin using the two methods; Table 6-3 to Table 6-8. The levels of tin present due to its volatility and instability result in a significant elemental recovery loss by ICP-MS where recovery levels show significant drop for each bearing respectively, in comparison to RDE-AES results; from 67.2 PPM to 0.3 PPM, 49.2 PPM to 1.6 PPM, 74.5 PPM to 1.2 PPM. As referred to in the opening paragraphs another potential issue of note is the high dilutions required for grease elemental analysis by ICP-MS in itself may affect the validity of results particularly in terms of repeatability which can be seen in the variance of the ICP-MS results obtained. High dilution was required simply because of the high iron levels to stay within the detection limits of ICP-MS, the pitch bearing grease samples required incredibly high dilutions of up to 1:50,000 to remain within the calibration curve limits of the ICP-MS instrument used. Therefore, if a small quantity of sample is lost during the preparation, or is in advertently added, the results obtained would contain a significant discrepancies in contrast to an occasion were the ideal volumes were achieved. In addition, to the aforementioned issues regarding the high dilutions requirements, it was noted that the ICP-MS sulphated ash digestion procedure showed a high propensity to spatter during hot plate reduction which would potentially result in the ejection of grease analyte from the container. On one occasion, sample ignition resulted in the sample becoming void, which resulted in a repetition of the preparatory steps required.
98
To conclude before the presentation of the finding of the ferrographic wear particle analysis, sets aside this discussion. It should also be emphasised the that issues raised above could not be attributed to ICP-MS calibration issues as calibration standards were within tolerances at the time of testing; similar calibration were also performed on RDEAES test equipment pre and post testing, as per laboratory accreditation procedures. 6.4.1. Validation through Ferrographic Wear Particle Analysis Analytical ferrography was chosen for this appraisal to provide an in-depth insight into the wear particles generated and to validate findings of the primary comparative elemental analysis study. To begin the initial analytical ferrography appraisal followed, preparation strategies based on a solvent dilution method established by work conducted on wear characterisation of grease samples taken from critical applications, which were conducted by the US Naval Air Force [18, 80] as referred to in Section 3.3.2, Chapter 3. However, after a series of unsuccessful and partially successful ferrogram preparations using such methods, at various dilutions and variations; such a method was deemed to be unsuitable for the grease samples in questions. Due to the inability to obtain, ferrograms deemed to be both representative of the wear and decipherable. The issue was primarily attributed to the extremely heavy build-up of grease thickener residue on the ferrogram slide after solvent washing and fixing. Furthermore, of the partially successful ferrograms prepared, the wear distribution appeared to be inappropriate for the rolling element bearings of the appraisal. This issue was associated with the low viscosity grease solutions which resulted as a consequence of the solvent dilution process. The prepared grease samples were noted to flow too vigorously over the ferrograms, and did not have enough viscosity to keep the grease thickener residue suspended. The issue of suspension was also attributed to the low recovery of large ferrous wear particles due to quick settling of particle to the bottom of the sample containers in the low viscosity solution. During the initial ferrography appraisal, the issue of low viscosity was attempted to be addressed through the addition of standard blank oil of 75 cSt (75x10-6 m2/s) kinematic viscosity, as an additional dilution substance but to no significant advantage. 99
Subsequently, an alternative preparation approach was required in order to obtain ferrograms, so as to allow for the analytical ferrographic validation of the elemental result. What follows is the condensed preparation procedure that resulted in the attainment of ferrograms, deemed to be both representative of the wear, and comprehensible. A weighted 1.5 g ± 0.1 g portion of grease, was added to a glass vial, which was initially diluted with the addition of 30 g of a dilatant. 1 g ± 0.1 g of solvent solution consisting of 70% toluene and 30% hexane was added to facilitate initial breakdown of grease structure. Whereby sample was vigorously shaken. The remainder of the dilatant weight was achieved through the addition of a standard blank oil with a kinematic viscosity of 75 cSt (75x10-6 m2/s). Once again the sample was vigorously shaken aided by the use of ultrasonic bath to ensure arbitrary particle distribution and breakdown of the thickener structure. The result of the preparation was 20:1 solution which was measured to have a viscosity range of 95 ± 5 cSt at 40 °C for the three grease samples. A viscosity amenable to a heavy oil that would ensure particle or grease thickener residue present would not settle out as quickly, as with the solvent dilution approach initially perused. What is more, of the subsequent dilutions that would be required to reduce particle concentration, which were achieved through the use of a 75 cSt standard blank oil, essentially ensured that viscosity could not drop below 75 cSt. Particle levels including wear and potentially contaminates in grease-lubricated systems are substantially higher than that of oil lubricated systems because the particles generated are not removed through filtration and cannot settle out, as classified previously in Section 2.2, Chapter 2. Thus, high levels of dilution were required to obtain ferrograms on which the number of particles was low enough so that the subsequent microscopic examination was not impractical due to piling of particles at entry regions of the ferrograms. Hence, a serial dilution process was conducted on the 20:1 solution prepared on which ferrograms where prepared and reviewed to access if the samples would prove to be satisfactory for analytical purposes.
100
Of the serial dilutions conducted on a volume-to-volume basis, a 100:1 dilution was found to provide the most satisfactory results. This in effect meant that the final dilution considered to provide enough clarity for subsequent ferrographic analysis was a 2,000:1 dilution. Figure 6-7 represents the ferrographic blank oil dilution preparation process where the effect of reducing particle quantity by dilution can visually be recognised by way of the colour change present in the samples.
Figure 6-7: Ferrographic Blank Oil Dilution Preparations Indicating Colour Change as a Result of Particle Concentration Reduction Due to Serial Dilution.
The importance of the requirement for a 2,000:1 dilution in regards to the complexity of ferrographic diagnosis of grease should be acknowledged. For example taking a simple reporting practice of classifying levels of specific wear particle type based on percentage coverage on the ferrogram slide, through the inclusion of dilution factors of such high proportions, there can be a tendency to misclassify wear levels. The primary objective of the analytical ferrography validation appraisal is to compare wear particle size and morphology of the wear within the grease samples, and consequently the concentration although significant is of secondary concern. The particle concentration classification and particle classification used in the ferrographic are given in Table 6-11 and Table 6-12. The sub-sections which follow relays in brief the ferrographic diagnosis results from the wear particle analysis conducted for each the three Rollix pitch bearing. Each section provides a selection of associated images. The supplementary ferrogram analysis report sheets are provided in Appendix D.
101
Table 6-11: Particle Concentration Classification used in Ferrographic Analysis
Classification Few Moderate Heavy None
Area Percentage Cover 1-5% 5-25% > 25% < 1%
Table 6-12: Particle Shape Classification used in Ferrographic Analysis
Particle Type
Size (Major Dimension)
Benign (Rubbing) Wear Particles
< 5 µm
Abrasive Wear Particles Severe Wear Particle Chunks Rework (Laminar) Particles 6.4.1.1.
Shape Factor (MajorMinor Dimension Any shape except curved or curled
> 15 µm > 5 µm
Long thin, curled or curved > 5:1 but < 30:1 < 5:1
> 15 µm
> 30:1
Any Size
Pitch Bearing 1 Ferrographic Diagnosis Result
There is a moderate amount of benign rubbing wear present, which was found to be mainly composed of low alloy steel, after heat treatmet at 330 °C for 90 s. This can be seen by the presence of blue temper colours after heat treatment, compare Figure 6-10 with Figure 6-11. There is a moderate amount of severe wear present, which was composed mainly of rolling contact fatigue spalls with signs of laiminar rework and surface pititng. This can be associated with a progressives stage in the failure mode associated with the rolling element bearing contact fatigue failure. The wear was found to be mainly composed of low alloy steel after heat treatmet. However, major diemension of the wear particles are below a 100 µm with few instance of greater than 100 µm, at very low volumes. There is presence of non-metailic contaminate in the form of crystaline silica particles which can be seen iridesce under cross polarisation illumation potrayed in Figure 6-9. A few to moderate amounts of dark metallo-oxides are present. These dark metallo-oxides 102
are partially oxidized wear particles which indicate overheating; but presence of such within a grease-lubricated rolling element bearing at such volumes, would appear relatively normal, as they would be produced as grease lubrication occurs under starved EHL conditions see Figure 6-8.
Figure 6-8: Benign Rubbing, Dark Metallo- Oxides & Crystalline Particles (x200Mag.)
Figure 6-9: Benign Rubbing, Dark Metallo-Oxides & Crystalline Particles Showing Iridescence (x200Mag. Cross Polarisation)
103
Figure 6-10: Severe Wear and Reworked Wear Particles & Benign Rubbing (x200Mag.)
Figure 6-11: Severe Wear Reworked Wear Particle & Benign Rubbing (x500Mag.) After Heat Treatment
Figure 6-12: Rolling Contact Fatigue Spall & Severe Wear (x200Mag.)
104
Figure 6-13: Rolling Contact Fatigue Spall (x500Mag.)
Figure 6-14: Rolling Contact Fatigue Spall (x500Mag.) After Heat Treatment
Figure 6-15: Severe Wear & Rolling Contact Fatigue Spalls (x200Mag.)
105
Figure 6-16: Severe Wear & Rolling Contact Fatigue Spalls (x500Mag.)
Figure 6-17: Severe Wear & Rolling Contact Fatigue Spalls (x500Mag.) After Heat Treatment
6.4.1.2.
Pitch Bearing 2 Ferrographic Diagnosis Result
There is a heavy to moderate amount of benign rubbing wear present, which was confirmed to be composed mainly of low alloy steel after heat treatment as outlined previously, which was in agreement with previous bearing diagnosis. There is a moderate amount of severe wear present, composed mainly of rolling contact fatigue spall, possible of occlusion origin which is indicated by wear particle profile detail, in Figure 6-20. There are few signs of laminar reworking indicating that fatigue spalls have not undergone over-rolling in the contact zones. Severe wear particles were found to be mainly composed of low alloy steel after heat treatment; and would appear to be in an earlier stage of the wear regime associated with rolling element bearing failure than that observed for Pitch Bearing 1. Major dimension of severe wear particles are below 50 Âľm 106
with few instances of greater than 50 Âľm. A few dark metallo-oxides are present, again a product of overheating due to insufficient lubrication; lubrication film breakdown within the bearing at some point.
Figure 6-18: Fatigue Spall, Severe Wear & Benign Rubbing (x200Mag.)
Figure 6-19: Fatigue Spall, Severe Wear & Benign Rubbing (x200Mag.). After Heat Treatment
107
Figure 6-20: Fatigue Spall & Benign Rubbing (x500Mag.). After Heat Treatment
Figure 6-21: Severe Wear & Heavy Benign Rubbing (x200Mag.). After Heat Treatment
Figure 6-22: Severe Wear & Heavy Benign Rubbing (x500Mag.). After Heat Treatment
108
6.4.1.3.
Pitch Bearing 3 Ferrographic Diagnosis Result
There is few to moderate amount of benign rubbing wear present, which was confirmed to be mainly composed of low alloy steel after heat treatment. This was in agreement with the two previous bearing diagnoses. There is a heavy amount of severe wear present composed mainly of large rolling contact fatigue spalls that have underwent reworking. In addition, other abnormal wear regimes are present with both severe sliding wear regimes with indications of overheating present see Figure 6-24 to Figure 6-27. The severe wear regime in comparison to Pitch Bearing 1 and 2 is at significantly more progressive stage, in the wear regime associated with rolling element bearing failure; due to presence of additional abnormal wear regimes and size distribution and morphology of wear particles present. Wear particles present are of a substantially larger size with major dimensions of highly advanced severe wear greater than 100 Âľm with instance of wear particle greater than 1826 Âľm or 1.826 mm. This indicates that the rolling contact fatigue spalling of the surface is at significantly more progressive stage. On heat treatment severe wear appears to be predominantly low alloy steel. However, temper colours, are restricted due to size of wear particle as seen in a number of wear particle images including Figure 6-22, Figure 6-30, Figure 6-33 and Figure 6-34. Furthermore, there is a presence of deteriorated re-worked rolling contact fatigue wear particles, with indications of cast iron upon heat treatment as seen in Figure 6-35. The presence of cast iron in the sample is indicative of severe rolling contact fatigue of bearing surface and subsequent exposure of the material underneath. Wear appears to be at a significantly increased level in comparison to Pitch Bearing 1 and 2 of the same system which appear to be at a relatively similar condition at this instance. The wear regime associated with rolling element bearing fatigue failure in Pitch Bearing 3 is more progressed, due to the large wear particle size and morphology of particles present.
109
Figure 6-23: Severe Wear & Dark Oxides (x200Mag.)
Figure 6-24: Sliding Wear, Sever Wear and Dark Oxides (x200Mag.)
Figure 6-25: Sliding Wear, Indication Sliding striations (x500Mag.). After Heat Treatment
110
Figure 6-26: Steel Alloy Severe Sliding Wear, Over Heated (x200Mag.)
Figure 6-27: Steel Alloy Severe Sliding Wear, Over Heated (x200Mag.). After Heat Treatment
Figure 6-28: Large Rolling Contact Fatigue Spall (x50Mag.)
111
Figure 6-29: Large Rolling Contact Fatigue Spall, Top Right (x200Mag.)
Figure 6-30: Large Rolling Contact Fatigue Spall, Top Right (x200Mag.). After Heat Treatment
Figure 6-31: Large Rolling Contact Fatigue Spall, Centre (x200Mag.)
112
Figure 6-32: Large Rolling Contact Fatigue Spall, Centre (x500Mag.)
Figure 6-33: Large Rolling Contact Fatigue Spall, Centre (x500Mag.). After Heat Treatment
Figure 6-34: Large Rolling Contact Fatigue Spall, Edge Crack (x200Mag.). After Heat Treatment
113
Figure 6-35: Deteriorated Re-worked Rolling Contact Fatigue Wear, Indication of Cast Iron (X200Mag.). After Heat Treatment
6.4.1.4.
Ferrographic Wear Particle Analysis Implications
The result of the ferrographic diagnosis of the three pitch bearings in short determined that the level of wear in Pitch Bearing 3 appeared to be at a significantly increased level in comparison to Pitch Bearing 1 and 2 of the same system. Pitch Bearing 1 and 2 appear to be at a relatively similar condition at this instance. An illustrative, comparison of the general findings of the ferrographic diagnosis can be seen in Figure 6-36. Which illustrates clearly that the wear regime associated with rolling element bearing fatigue failure in pitch bearing 3 is more progressed, due to wear particle size and morphology present.
Pitch Bearing 1
Pitch Bearing 2
Pitch Bearing 3
Figure 6-36: Wear Particle Size Comparison of the Three Bearings (x200Mag.)
The wear particle analysis study conducted using analytical ferrography shows a relationship between the results found elementally by RDE-AES and by ICP-MS for Pitch Bearing 1 and 2 and provides validation of the reason for the contrast in results of Pitch 114
Bearing 3. The result provide strong validation that the wear regime associated with rolling element bearing fatigue failure in Pitch Bearing 3 is more progressed, due to the large wear particle size and morphology of wear particles present. Consequentially, validates the particle size limitation conclusion that were formed based on the results obtained from comparative elemental analysis.
6.5. Conclusion of Appraisal Study 1 The result of the appraisal study demonstrate the feasibility of obtaining agreeable condition diagnosis of grease-lubricated system elementally through RDE-AES and a passive sampling approach of grease discharge of wind turbine pitch bearings, in real situations. Where the employment of secondary methods of condition analysis can provide further detail on the wear regime present and severity of such. Which in this appraisal study was provided by the employment of analytical ferrography as a secondary validation process. The RDE-AES method in the appraisal, has showed a superior elemental range to that of ICP-MS, the RDE-AES result identified no potential volatility issues, preparatory time was akin to that of oil. Moreover the RDE-AES methods higher particle size limitations of around 8 Âľm allowed for accurate determination of the bearing condition, clearly permitting for the identification of the pitch bearing that was in the most deteriorated condition i.e., Pitch Bearing 3 which was associated with blade 3 which was known to have undergone a damage condition. The net conclusion to be drawn from Appraisal Study 1 is that although ICP-MS can offers superior resolution to detect low levels of elements present, it is has significant limitations including element range, volatility, protracted preparatory time requirement and more severe particle size limitations only having detection of particles smaller than approximately 2 Âľm and blind to those larger 3 Âľm. Thus it can be clearly reasoned that the RDE-AES presents more significant opportunities for the application of used grease elemental analysis for condition monitoring purposes. The befits of RDE-AES grease elemental was made particularly evident in this appraisal of wind turbine pitch bearings where the presence of severe wear which is of serious 115
concern due to potential impact of damage as result of severe wear modes. Fatigue spalling, severe sliding wear, and other severe wear regimes, including abrasive wear which was found to be present in the wear particle study conducted. These larger particles would simply go undetected by ICP-MS elemental analysis which would potentially lead to scenarios where misdiagnosis would be of concern. Appraisal Study 1 has demonstrated the viability of obtaining condition diagnosis from grease-lubricated system elementally through RDE-AES and a passive sampling approach of grease discharge. This confirms that grease discharge from bearings in the appraisal study is fundamentally representative of the overall grease condition as it exists within the bearing. As the grease is discharged from a bearing it carries a historical account of the bearingâ&#x20AC;&#x2122;s wear within. This includes debris from the bearing, contaminants the bearing was exposed to and degradation by products from the grease. Thus, the state of the discharge analysed by RDE-AES can correlate to the state of lubrication and ultimately the condition of the bearing.
116
7. Chapter 7. Appraisal Study 2: Sample Location Influence
7.1. Introduction The following appraisal study focuses on the influence of sampling location, on the results obtained from used grease elemental analysis through RDE-AES. Based on the conclusions drawn from the appraisal of grease elemental analysis by RDE-AES, presented in Section 4.3.2, Chapter 4, Protocol II the whole grease smear method was chosen this appraisal on the effect of sample location. With the relatively low variance and small grease sample volumes required being a significant deciding factors in terms of this appraisal, as it was for Appraisal Study 1. The study was conducted on rolling stock (rail vehicle) axle bearings through an active sample approach, where elemental analysis findings are correlated with visual bearing inspection. The bearings involved in the appraisal are tapered double outer roller axle journal bearings, manufactured by Timken known in short as AP bearings or All-Purpose (AP) railroad bearings. There are numerous heavy duty applications for such bearings and the remanufacture or requalification of the bearing type in question is common practice, including for that of the application appraisal focus; railway vehicles (rolling stock) and they are a key component of wheelset assemblies for both freight and passenger rolling stock across a wide number of vehicle classes. In rolling stock applications such bearings are mounted to the axle journal inside an axlebox structure that houses the journal bearing allowing it to support the necessary loads. The bearings in the appraisal study were provided courtesy of Irish Rail, from the electrical multiple unit (EMU) fleet best known as the DART, further detail is provided in Section 7.1.1 As stated, such bearing design are used on both freight and passenger rolling stock and as such are used extensively within Irish Rail and by other rail providers on a number of rolling stock classes. As can be expected, there are sporadic historic failure investigation accounts of bearing failures with the rail industry. One recent example was a significant investigation undertaken by the Railway Accident Investigation Unit of Ireland (RAUI) post a journal bearing failure in October, 2011 on a locomotives 201 class or diesel multiple units (DMU), details of which are outlined in RAIU Investigation Report 2012-R003 [92]. 117
The potential significance of failure of these bearings can be appreciated as such failures contribute to the train defect category according to Irish Rails Network Wide Risk Model [92] as having the potential for catastrophic axlebox failure which can lead to derailment of a train. Additional, bearing faults have occurred both prior and post the bearing failure of October 2011 within the Irish Rail fleet. A significant, example of bearing failure which resulted in derailment due to a burnt off axle journal bearing occurred in January 2008, on class 2700 freight wagon [92]. Correspondingly, similar journal bearing failures of AP bearings have occurred in other rail fleets worldwide, for example, VIA Rail Incorporated of Canada, reported a similar incident in 2012 in report R11T0034 [93] (Timken manufactured) and the Australian Transport Safety Bureau in 2010 which resulted in a derailment as recounted in report RO-2010-001 [94] (SKF manufactured). To avoid such high risk failures, there are a number of methods that are employed to mitigated the risk of potential catastrophic axle bearing failure; firstly by routine maintenance and inspection and secondly the monitoring of the temperatures of the axleboxes while in service. There are a number of methods for the monitoring of axleboxes while in service including the use of simple temperature sensitive devices that can release a smoke or odour at specified temperatures. As well as more sophisticated online trackside detectors such as acoustic bearing detector’s (ABD’s) and hot axlebox detectors (HBD's) which transmits an alerts signal based on identified failure condition thresholds. ABD’s monitor roller bearings acoustic emissions as they pass by specific track points to identify potential bearing defects prior to failure, and HBD’s which monitor the outside temperatures of the axle box and bearing through infra-red as they pass by specific track points, again identify potential bearing defects prior to failure. Referring to both the abovementioned lists of previous failures reports and Chapter 1, Section 1.1 (Figure 1-1), such methods are not completely reliable and are heavily influenced by environmental factors, and again as illustrated in Figure 1-1 they result in a reduced lead time to failure compared to lubricant condition monitoring. This appraisal considers that grease lubricant sampling of the axle bearings may be used as a means to enable early indication of possible failure, or as a screening procedure post 118
specified mileage limits for improved failure prevention by extending warning times and thus enhancing safety and reducing cost. However, in order to be considered to be a feasible solution, the movement of wear particles in a grease-lubricated bearing under normal running conditions must be fully evaluated, and hence the focus of this appraisal â&#x20AC;&#x153;Sampling Location Influenceâ&#x20AC;?. The majority of wear particles generated in the greaselubricated bearing will be restricted to the region where the active grease is located i.e., the load zone of the bearing. As outlined in Section 3.2, Chapter 3, an intricate problem in elementally monitoring grease-lubricated components is that the measurement of the concentration of an elements in the inactive grease which is in the majority, may provide little information regarding the wear and bearing condition; the concentration of wear particles is nonuniform throughout the grease and varies with the sample location. Thus, as the aim of this appraisal is to investigate sample location influence on condition monitoring deductions of used grease elemental analysis, following guidelines as per ASTM D7718 - 11 [84]. It should be noted that this appraisal is primarily concerned with sampling effect on elemental results for condition monitoring of the bearings involved through RDE-AES, not the larger issue of unanticipated axle journal bearing failure among rolling stock. However, the appraisal may direct possible applicability to such scenarios depending on the findings. 7.1.1. Detail of Bearings Appraisal Study 2 The appraisal study involved four axle journal bearings, with two acting as controls so that an elemental base line could be determined, and the remaining two acting as the primary test specimens all bearings used where Timken AP double tapered roller bearings (Part No. HM127442). Summary detail of the four axle bearing involved in the appraisal is given in Table 7-1. The control bearings used were of the same specifications, however they had been requalified at different times and had been placed in storage waiting for use when an overhaul was required. All four bearings where lubricated with Shell Alvania 2760B grease. This is a lithium grease with a mineral base oil, a NGLI Grade of 2.5, designed for
119
European axlebox applications where extended service intervals are required in order to reduce maintenance costs. Table 7-1: Details of Axle Bearings in Appraisal 2
Bogie
No.
Axle No.
Type
Vehicle
Bearing
No.
Designation
Involvement
Requalified
C1
2007
N/A
N/A
N/A
HM127442 C2
Control Requalified 2012
S1
Mileage of
M59
753-TL
8534
HM127442 S2
Condition
88,0433 km
Specimen
Hereafter, the bearings are abbreviated as per designation provided.
Requalification dates respectively where 2007 for bearing C1 and 2012 for bearing C2, and their inclusion in the study was primarily to obtain a truly representative base line of elemental grease. Since the pre-lubrication process can have an effect on the elemental results obtained for a new grease, therefore grease as manufactured was not tested. Further detail on bearing requalification and life is provided in Section 7.1.1.1. The specimen bearings S1 and S2 that acted as the primary specimens had previously been part of a boige assembly, associated with EMU unit 8543. Unit 8534 is 8500 class EMU used by Irish rail on the DART network. The class 8500 EMUâ&#x20AC;&#x2122;s are 20.9 m long, have a mass of 108,000 kg and a maximum speed of 100 km/h [95]. They are fitted with two bogies, each with two wheelsets on each bogie; a wheelset consist of two wheels, which are pressed onto an axle wheel seat, and two Timken AP bearing assemblies pressed onto the axle journals which are held within an axlebox as mention in the introduction in Section 7.1. The specimen bearings in the appraisal were from bogie number M59, associated with axle number 753-TL a powered axle and gearbox number 4051749-0020-044 which had 120
operated for 88,0433 km since the bearing was fitted and were removed during a standard overhaul. Technical information in previous paragraphs was provided courtesy of Irish Rail [95]. As stated, the specimen bearings are associated with gearbox number 4051749-0020-044, which had undergone routine tribological machine care monitoring at TelLabs since November 2011, including three ferrographic investigations since April 2013, during which periods no abnormal wear was detected. As this appraisal is concerned with sample location influence on elemental analysis result, the bearing assembly is important. The appraisal bearing assembly is shown in an exploded view in Figure 7-1; consisting of an outer cup which houses two tapered roller cone assemblies separated by a spacer which maintains the gap between the cones (Note the indication of inboard and outboard side of the bearing).
Outboard
Inboard
Figure 7-1: AP Tapered Double Outer Ring Roller Bearing Components Adopted From [96]
Side
Each cone assembly consists of a raceway, rolling elements and a cage. In general, as with all bearings the cup, rolling elements and cones are case hardened with precision finishes to ensure closely matched mating surfaces, with the cage acting essentially as a spacer that retains the rolling elements in place within the cone assembly cold formed from a single sheet of low carbon malleable steel, according to Timken [96]. The remaining components include the inboard and outboard seals, seal wear rings, a backing ring and an end cap. The end cap, secures the press fitted bearing in place on the axle, however bearing end caps are not involved in the appraisal due the mounting configuration of the 8500 class. The generic bearing design shown in Figure 7-1 is a rail industry standard and little design variation exist between different manufactures and 121
are considered self-contained, as they come pre-assembled and pre-lubricated and are extensively requalified to extend usage life. 7.1.1.1.
Bearing Requalification
According to the Timken standards [96], roller bearing components can be used indefinitely, provided they meet reconditioning criteria. However in practice, in true application environments such as that of the appraisal bearings and their components have a finite life, which is defined by fatigue. Predictions of bearing laboratory fatigue life, otherwise known as L10 life, are accurate in a controlled situation and the cause of laboratory failure is always material fatigue as referred to in Section 1.1, Chapter 1, for a given population of identical bearings, 90% will meet or exceed their predicted life, and 10% will fail before reaching it. And as such, if using L10 life on the bearing of the appraisal for overhauling times 90% of the bearings removed will statistically be fine. Hence, requalification of the bearings is standard practice to reduce cost and wastage associated with L10 life predictions. The requalification process involves stripping, cleaning, a visual inspection, measurement, reassembly, and re-greasing before the bearing can be refitted to a wheelset and returned to service [94], more often than not on different rolling stock applications. Reconditioned roller bearings account for the majority of roller bearings in service today, this is true also in the Irish Rail fleet [95]. At Irish Rail [95], during a wheelset assembly new roller bearings are only matched with new roller bearings. When reconditioned roller bearings are used, these are matched with reconditioned roller bearings made by and reconditioned by the same company. Remarkably, no records are kept with the cumulative distance for each bearing, nor is the total service age or previous history of the reason for bearing removal from service, considered during the requalification process. This is particularly, unusual as fatigue spalled bearing surfaces if within limits specified can pass qualification measurements once the bearing surface spalls are blended out as part of the requalification procedures. Bearings can be requalified and returned to service several times, more often than not, bearings will continue to be requalified until they are unable to be reused after failing the requalification process.
122
7.2. Analysis Procedure for Appraisal Study 2 The four bearings in the appraisal underwent the same sampling procedures, the grease samples from control bearings C1 and C2 were used to form a representative elemental base line. Specimen bearings S1 and S2 were inspected post removal from the axle as detailed in Section 7.1.1 during a scheduled overhaul of the boige. Appraisal bearings were dissembled so as to allow grease samples to be taken from not only the seals but also from the internal regions of the bearing. Disassembly also enabled the possible visual identification of possible wear scars, fatigue spalls or other wear damage on bearing raceways or other components. Findings in respects of pre and post axle bearing removal and subsequent visual inspection upon bearing disassembly is specified in Section 7.3.1. Once dissembled, the major portion of the grease was then extracted from the five locations (Figure 7-2) in each bearing if sample volumes permitted. This was achieved using a small non-metallic spatula following ASTM D7718 - 11 [84] procedures, for sampling from failed grease-lubricated components, although in all instances the bearings had not failed. As indicated in Figure 7-2 the five sample locations in the study included the outboard seal, outboard cage and rolling elements, spacer void, inboard cage and rolling elements and inboard seal.
Outboard Cage & Rolling Elements Outboard Seal
Inboard Cage & Rolling Elements
Spacer Void
Inboard Seal
Figure 7-2: Five Sampling Points of Grease for Appraisal 2, Sample Location Influence (cross section view of bearing)
The five major portions taken from each bearing was placed in separate sealed specimen cups for testing. The resulting grease samples obtained from the different bearing locations underwent thorough RDE-AES elemental analysis through Protocol II the whole 123
grease smear method as outlined in Chapter 4. The five sampling locations were studied to determine the sensitivity to the actual wear of the specimen bearings S1 and S2 through elemental analysis of the grease sample based on location effects. Results of the elemental analysis will provide an insight as to whether the sample location can support the generation of a representative view of the wear generation and bearing condition. Section 7.3.2 provided the results of the grease elemental analysis based on the five bearing sample locations. The quantity of grease removed in addition provides illustration of the actual amount of grease present at the time of sampling, due to initial grease migration and churning upon run-in of the bearing. This will serve as an indicator as to which areas of the bearing can provide sufficient amounts of grease for tangible field sampling provided that the results of appraisal suggest the feasibility of obtaining representative samples from locations of easily accessible.
7.3. Results of Investigation of Sample Location Influence The following sections present the results of the investigation. The findings from the visual inspection of bearings, S1 and S2, is provided in summarised in Table 7-2 in Section 7.3.1 which is followed by a brief review of visual inspection findings. Section 7.3.2 provides the result of the RDE-AES elemental analysis conducted on the grease samples acquired from the five locations. The elemental results will present the average elemental concentration based on the result obtained from the five grease samples taken from the five separate locations within each of the specimen bearings, S1 and S2. Comparison to base line grease elemental concentration of an unused bearing grease as applied to an axle bearing is provide from result obtained from the inclusive average elemental results taken across both control bearings, C1 and C2. Note: Two separate RDE-AES elemental measurement were taken for each of the five grease sample locations following Protocol II the whole grease smear method to form averaged elemental results. All result are expressed in parts per million (PPM).
124
7.3.1. Visual Inspection Findings Table 7-2: Summary of Visual Inspection of Specimen Bearings S1 and S2
S1
S2
Figure
Pre bearing disassembly condition (Visual assessment) Bearing Slight fretting wear on cup
Fretting wear on cup
Grease No signs of leakage
No signs of leakage
Figure 7-3 -
Condition Corrosion Very little
On exterior of cup
Figure 7-3
Post bearing disassembly condition (Visual Assessment) Grease Sufficient quantity but
Sufficient quantity but
degraded
Figure 7-4
degraded
Outboard seal Good Condition
Good Condition
-
Outboard cone Good Condition
OK/Good Condition
-
Outboard cage Satisfactory
Good Condition
-
Good Condition
-
Outboard Good Condition rollers Outboard race Good Condition1
Good Condition1
Spacer Not bad, but signs of
Figure 7-5
Good Condition
-
Ok Condition
-
fretting Inboard seal Ok Condition Inboard cone Satisfactory
Satisfactory
Figure 7-6
Inboard cage Good Condition
Satisfactory
Figure 7-6
Signs of over heating
Figure 7-6
Ok indication of over
Figure 7-5
Inboard rollers Ok Condition Inboard race Ok/Good Condition1
heating1
1
Cup raceway only inspected, cone raceway not inspected.
125
Outboard Side Fretting Marks
Fretting Marks
Inboard Side
Corrosion
Figure 7-3: Bearing Outer Cup Condition, S1 (Left) and S2 (Right)
Figure 7-4: Visual Comparison of Grease from Outboard Seals of Bearing Assembly - Note the visible levels grease degradation and variance in quantity of S1 in comparison to unused bearing grease of C2, C2 (Left) and S1 (Right)
S1
Inboard Side
Outboard Side
S2
Indication of overheating on inboard cup raceway Figure 7-5: Cup Raceways Visual Inspection, S1 (Left) and S2 (Right)
126
Signs of overheating on inboard rollers
Figure 7-6: Inboard Cone Assembly, S1 (Left) and S2 (Right)
Figure 7-7: Comparison of Control and Specimen Bearings, C1 (Left) and S1 (Right)
Figure 7-8: Control Bearing C1, Inboard Cone Assembly
7.3.1.1.
Overview of Visual Inspection Findings
Upon overhaul, and removal of the specimen bearings S1 and S2, no issues of concern were identified with the bearings from the bogie or their fittings. The axlebox was visually examined, there were no signs of grease loss, overheating or abnormal wear or witness marks that would indicate abnormal contact between the bearing and the axlebox or bearing and axle journal. In addition, the condition of the wheels on the associated wheelset, had no abnormal wear signs such as wheel flats outside Irish Rails acceptable 127
tolerances. As specified in the in Section 7.1.1 the gear box associated with the axle and thus the bearings had shown no instances of abnormal based on historical analysis conducted on the unitâ&#x20AC;&#x2122;s gearbox at TelLabs. Both specimen bearings S1 and S2 on disassembly showed no evidence of insufficient lubricant as volumes of grease lubricant present was significant. On initial lubrication Timken apply 230 +/-15 g of grease and specify that on overhaul a minimum amount of 124 g should be present [96]. The amount of grease remaining in bearings was measured during the study and found to be in excess of 150 g, for both S1 and S2 based on total weight of grease samples obtained during inspection. In general visual comparison of the grease, it is evident that the grease had underwent a level of degradation due to oxidation, as it had turned from light brown to dark brown/black as shown in Figure 7-4, (unused control grease from control bearings, C2 and used greases from specimen bearings, S1). The visual inspection also note the high variance in grease quantity available for sampling. Figure 7-4 visual illustrates this; a small quantity of grease was obtained from the outboard seal of the unused requalified bearing, C2, whereas a significantly larger quantity was obtained from the outboard seal of the used specimen bearing, S1. This variance is explained, as once a bearing is run the grease within, migrates to the outer extremes, due to centrifugal force caused by rotation of the bearing. Visual inspection, of the outboard and inboard cup raceways of the disassembled specimen bearings S1 and S2 revealed that bearing could be deemed to be operational and had underwent normal wear during usage. The only visual indication of abnormal wear was seen on the inboard cup raceway of bearing S2, Figure 7-5. Corresponding signs of overheating were visually present on the inboard rollers of bearing S2, Figure 7-6, suggesting insufficient lubrication or over loading at some point. The specimen bearings components were found to be in a serviceable condition, and within specification exhibiting no evidence of fatigue, fretting or other abnormal wear modes apart from the signs of overheating at some point on the inboard side of bearing S2.
128
Amusingly the only visual incident of severe bearing damage was found on the inboard raceway of control bearing C1, which had been requalified and had been stored since 2007 at Irish Rail. Figure 7-9 illustrates the surface damage to the raceway found upon inspection. Possible cause included: transport or handling damage. Alternatively, it may be explained due to the fact the bearing was requalified. As remarked upon in Section 7.1.1.1, a fatigue spalled bearing surfaces if within limits specified can pass qualification measurements once the bearing surface spalls are blended out as part of the requalification procedures.
Figure 7-9: Inboards Raceway Surface Damage to Unused Control Bearing, C1- Image to upper right taken at x10 Magnification of Surface Damage
7.3.2. RDE-AES Grease Elemental Analysis Results During visual inspection of the bearings grease samples were taken from the five locations as outlined in Figure 7-2 from each specimen bearing, S1 and S2. Table 7-3 and Table 7-4 provide the grease elemental distribution result obtain based on sample location influence, for bearing S1 and S2 respectively. To provide comparison base line the inclusive average elemental distribution results taken across both control bearings, C1 and C2 is provided. The comparative distribution of key wear metals including iron, chromium and nickel across the five sample locations in bearings S1 and S2 is provided in Figure 7-10, Figure 7-11 and Figure 7-12
129
Table 7-3: Bearing S1, Grease Elemental Distribution as a Function of Sample Location Location
Fe
Pb
Cu
Al
Cr
Ni
Outboard Seal
748.5
3.9
78.0
8.9
10.0
Outboard Cage & Rolling Elements
608.6
8.0
67.2
7.7
Spacer Void
1234.5
5.2
68.6
Inboard Cage & Rolling Elements
962.4
8.0
Inboard Seal
1522.0
Unused Grease
3.4
Mo
Mg
Zn
Ca
3.51 19.3 1657.5
53.2
5.7
319.6
292.1
9.6
3.11 15.2 1364.5
48.5
6.2
297.7
287.6
11.6
16.4
5.41 19.8 1619.5
68.8
7.2
398.9
352.8
82.7
9.7
12.5
4.26 19.7 1330.5
51.9
9.4
324.0
293.5
4.4
78.3
12.6
18.4
6.16 21.9 1512.5
85.8
5.4
407.5
283.9
<1
<1
1.5
<1
68.9
7.0
354.5
293.9
<1
Si
<1
Na
1450.7
(C1 & C2)
Table 7-4: Bearing S2, Grease Elemental Distribution as a Function of Sample Location Location
Fe
Pb
Cu
Al
Cr
Outboard Seal
782.0
3.3
46.8
8.6
9.7
Outboard Cage & Rolling Elements
858.9
8.5
82.6
9.9
Spacer Void
994.1
4.0
60.4
Inboard Cage & Rolling Elements
1573.0
8.4
Inboard Seal
1918.0
3.4
Unused Grease
Ni
Mo
Mg
Zn
Ca
3.11 17.5 1552.5
56.5
4.6
340.6
300.0
12.2
3.69 20.4 1483.5
65.0
8.1
386.7
334.7
9.9
12.6
3.68 15.6 1958.5
58.8
5.1
385.1
346.2
100.4
14.8
17.9
5.29 39.3 1221.5
86.3
13.0
423.4
355.8
5.1
103.3
15.6
22.3
6.93 23.2 1495.0 114.1
5.6
457.9
331.9
<1
<1
1.5
<1
7.0
354.5
293.9
<1
(C1 & C2)
130
Si
<1
Na
1450.7
68.9
2000.0
782.0
748.5
858.9
608.6
994.1
500.0
1234.5
962.4
1573.0
1918.0
1000.0
1522.0
Iron, PMM
1500.0
0.0 Inboard Seal
Inboard Cage & Rolling Elements Bearing S1
Spacer Void
Bearing S2
Outboard Cage & Outboard Seal Rolling Elements Average
Figure 7-10: Comparative Distribution of Iron (Fe) in Grease for Bearings, S1 and S2
25.0
9.7
10.0
12.2
9.6
12.6
5.0
16.4
17.9 12.5
10.0
22.3
15.0
18.4
Chromium, PPM
20.0
0.0 Inboard Seal
Inboard Cage & Rolling Elements Bearing S1
Spacer Void Bearing S2
Outboard Cage & Rolling Elements
Outboard Seal
Average
Figure 7-11: Comparative Distribution of Chromium (Cr) in Grease for Bearings, S1 and S2
131
8.0
3.1
3.5
3.5
3.7
2.0
3.7
5.4
4.3
5.3
6.9
4.0
6.2
Nickel, PPM
6.0
0.0 Inboard Seal
Inboard Cage & Rolling Elements Bearing S1
Spacer Void
Outboard Cage & Rolling Elements
Bearing S2
Average
Outboard Seal
Figure 7-12: Comparative Distribution of Nickel (NI) in Grease for Bearings, S1 and S2
Note: that average result in previous figures, indicates average elemental result of both bearings combined.
7.4. Discussion of Sample Location Influence Investigation When the elemental analysis results from the five used grease samples as a function of location within the bearing assemblies are compared with the new grease sample as shown in Table 7-3 and Table 7-4. Result would indicated in both instances that the bearings were wearing normally, and at a relatively light rate of wear over the duration of operation. This can be a stated although wear metal rates appear to be high, notably the raised Fe (iron) levels; in consideration to similar oil lubricated systems. However, the elemental concentration does not appear exceedingly high when considering that lubricant grease retains hundreds to thousands times more wear particles, as they are not removed once generated. This statement can be corroborated by the findings with regards to the high dilutions required in Appraisal Study 1. Moreover, based on the level of wear particularly that of ferrous present in comparison to the baseline obtained from the control bearings, in addition to the strong finding of the visual inspection, it can be deemed that the bearings underwent normal wear in operation and presented in a reasonable condition after 88,0433 km of usage. 132
To restate, the main objective of this appraisal, was to investigate the influence, if any of sampling location on elemental result for condition monitoring of grease-lubricated equipment through RDE-AES elemental analysis. Through the comparison of results obtained from the samples taken from the five different locations within the axle journal bearings, it is evident that the elemental results vary as a function of location, Table 7-3 and Table 7-4. For instance the results for the inboard regions of the bearing assembly illustrate increased wear rates, with the inboard cage and inboard seal regions indicating higher wear rates than their outboard counterparts, Figure 7-10, Figure 7-11 and Figure 7-12 provides the clearest illustration of location effects. The variance in locational bearing wear can be attributed to imbalanced loading, although the bogies are designed to distribution carriage weight evenly through the centre of the bearings for radial loads. Additional imbalanced thrust loads are created between the bearings and the axle journal seat, during cornering consequently thrust loading cannot be experienced to the same degree on the outboard side of the bearing. Comparing elemental iron results of the inboard seal to spacer void sample locations for bearings S1 and S2 a, 19% and a 48% differential exits respectively. Similar differentials across, all other wear metals present in the elemental findings. The imbalanced wear distribution in the bearings can further be recognised by considering key wear metals across location in the bearing analysed which is graphically presented in Figure 7-10, Figure 7-11 and Figure 7-12 for iron, chromium and nickel wear metals respectively. Overall these result would point toward substantial differential wear levels in the bearing based on elemental analysis findings of locations involved in the study; at the sampling time based on the duration of bearings running distance on the axle and boige involved in the appraisal. This may suggest the prerequisite to carry out a closer study looking at reasons for increased levels of inboard bearing wear and investigating the tendency of wear particles to migrate from load zones in the bearing outward from the interior load zone locations of the bearing to seal areas or spacer voids as was found to be the case in this study. The elemental results obtained from the bearings under consideration would suggest that sampling from bearing seal locations may provide an appropriate insight for condition 133
assessment purposes regarding the wear state of the bearing. It was found in the study that such locations not only provided adequate amounts of grease for testing but noted to be more easily accessible for potential field sampling. Remarkably, by contrast assessment to a region of the bearing that would have been expected to provide the most accurate condition assessment, the outer raceway of the bearing cup was found to have an insignificant amounts of grease for analysis, therefore it could not be elementally analysed. The implication of the results serve to lay emphasis on the critical nature of the sampling process on the results obtained, and that it is imperative to recognise that sample location will have an noteworthy impact on condition monitoring conclusions that may be drawn from elemental analysis results of grease-lubricated rolling element bearings. Although the appraisal concentrated on one specific bearing type, double tapered outer roller bearings the findings would suggest that similar results would be found on different configuration of grease-lubricated rolling element bearing. As a consequence, it needs to be pointed that the variance in elemental wear results based on location will alter relative severity depending upon the internal design of the bearing and duration of operation; both supporting varying degrees of wear particle migration and indeed bearing wear. Therefore it is suggested that in order assess the feasibility of the application of grease elemental analysis for reliable condition monitoring, it would be necessary to remove and dismantle a number of similar components in order to obtain an entire wear profile or picture of the component whereby samples would be taken from critical areas of wear, for example the load zones in approach similar to that used in this appraisal. Hence, with an understanding of the levels of wear across a small sample of the component in question as gleamed from the result in this appraisal an analyst would be better placed to interpret the result based on known information regarding the initial findings of the entire wear level profile in the component, thereby enabling the formation of substantiated judgement from more accessible regions of a grease-lubricated component. In summary, it should be appreciated that the applicability of RDE-AES elemental analysis to the condition monitoring of grease-lubricated components including rolling element 134
bearings; is critically reliant on the prospect of obtaining representative samples of grease for subsequent elemental analysis.
7.5. Conclusion of Appraisal Study 2 In conclusion, the comparison of elemental analysis results of the grease samples taken from the five different bearing locations, served to highlight the critical nature of sampling on the results obtained and the influence of sample location on bearing condition assessment as consequence. Equally import the findings of the grease elemental analysis demonstrated strong correlation to visual bearing inspection is possible through elemental analysis of the bearing grease. Additionally, the elemental results demonstrate the potential feasibility of obtaining satisfactory results from the outer regions of the bearing seals, based on the findings of the bearings considered in the study. On the other hand, the appraisal needs to note that the elemental examination of grease-lubricated bearings is not, straightforward. Firstly, the distribution of wear particles within the grease in a bearing is uneven; as shown by the results obtained. This may lead to grease samples with significant variances in results leading to potential misdiagnosis based on perceived condition. Therefore there is resolute justification for the practice of sampling multiple points of a bearing, dependent of bearing size and load zones configuration. Furthermore, it should be highlighted that the physical configuration constraints of some bearings may preclude the extraction of grease without the need for dismantling the bearing, thus rendering the application for condition monitoring almost impossible without minor alterations, or in other cases sampling via the use of a passive sampling approach of grease discharge as was shown to provide accurate condition assessments in Appraisal Study 1. The foremost difficulty with grease analysis can simply be concluded to be the integrity of the sample that can be attained; is the sample truly representative of the condition of the lubricant and the component which it lubricates? As discussed the answer to this may need to be ascertained through the dismantling of a number of bearings from a system, thereby enabling comparison of samples taken from various locations and thus 135
permitting for the discernment of the probable wear profile from more readily attainably locations, if an active sample approach is chosen. As a direct implication, there will be several situations where condition monitoring using grease elemental analysis for rolling element bearings may be precluded by sampling difficulties. Still, in systems where sampling that is representative of condition can be easily carried out, the benefits of having significantly increased machine condition failure detection times of up to several months in comparison to predictive methods such as acoustic emissions or vibration monitoring of a number of weeks as shown in Figure 1-1 in Chapter 1 is clearly self-evident. Consequently, by monitoring grease elemental conditions the level of bearing wear, degradation and contamination can be assessed. Thus, the risk of premature failure of a bearing can be reduced while simultaneously maximising lead time for predictive or proactive condition-based maintenance to be optimised, and thus offering the potential for significant cost savings.
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8. Chapter 8. Summary of Research & Recommendations for Future Work
8.1. Introduction This chapter brings the research work to a close. The chapter classifies the main achievements of the research conducted, highlights the significance and contribution of the research, and recognises current limitations with appropriate recommendations being made for future work. Detailed discussions and conclusions for each of the research elements have been provided comprehensively in the respective Chapters 5 - 7 of the dissertation. Hence herein the concluding chapter summarises what has been achieved by the research.
8.2. Summary of Works Completed The results and findings presented in this dissertation represent a significant and useful contribution to the enablement and justification for the use of grease elemental analysis for the purposes of tribological condition monitoring of grease-lubricated rolling element bearings, with the potential for application in numerous industries. As articulated in Chapter 1, the primary hypothesis was as follows: â&#x20AC;&#x153; The condition assessment of used grease from a grease-lubricated rolling element bearing during its running indicates the earliest failure risks. The occurrence of contaminate debris is unavoidable, and the processes whereby these particles lead to fatigue and wear are known and if undetected lead to eventual component failure. By monitoring grease elemental conditions; the level of bearing wear, degradation and contamination can be assessed. Thus, the risk of premature failure of the bearing can be reduced while maximising lead time for predictive or proactive condition-based maintenance. â&#x20AC;? The project enabled a quantitative and qualitative exploration of the development of condition monitoring of grease-lubricated rolling element bearings as set out by the
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research objectives in Section 1.4. Chapter 1, Table 8-1, provides a summary of establishment of objectives achieved. Table 8-1: The Objectives of the Research were Establish as Follows
Objective A established over Chapter 4 and Chapter 5 A. To study and develop efficient, protocol(s) for grease elemental analysis through, RDE-AES that enables the detection of elements likely to be encountered in typical applications, including wear metals, lubricant additives, thickeners and contaminants. Objective B established in Chapter 5 B. To determine the correlation between elemental analysis results and RDE-AES protocol(s) developed. Comparison of data and methods from different protocols will illustrate the prospective disputes between protocol(s) established. Objective C established in Chapter 6 C. To examine the effects of particle size limitations on elemental analysis results, and as a consequence on the condition conclusions that may be drawn, in lubricating grease analysed through spectrographic analysis techniques, including that developed by RDE-AES. Objective D established in Chapter 7 D. To investigate the effects of sampling location on elemental analysis results, based on sampling locations within grease-lubricated rolling element bearings. Sampling will follow ASTM D7718 [4] sampling standard and RDE-AES protocol(s) deemed to be most applicable. Objective E established over Chapters 5, Chapter 6 and Chapter 7 E. Inclusive validation and assessment of used grease RDE-AES elemental analysis protocol(s) developed based on the appraisal of data acquired, efficiency of data accusation, and appropriateness for commercial applications, and accompaniment to additional tribological grease condition assessments methods. In order to explore the primary hypothesis, both controlled experimental and real application appraisal studies where covered by the research in approximate equal proportions. The combination of both controlled theoretical works from the laboratorybased protocol development, and subsequent analysis of methodologies for the simultaneous multi-elemental analysis of grease through RDE-AES principles, were presented in Chapters 4 and 5.
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Consequently the research and the industrial application-focused appraisals presented in Chapters 6 and 7 were informed by knowledge established from the grease elemental analysis protocol assessed in Chapter 5. Findings and conclusions in Chapter 5 were drawn based on results obtained from the four protocols in conjunction with consideration of protocol selection criteria which identified Protocol II (the whole grease smear method) as the most promising for practical reliable condition monitoring. The influence of both particle size and sampling location on RDE-AES grease elemental analysis for condition monitoring as determined from industrial application appraisals, may be summarised as follows:
Appraisal Study 1: Particle Size Influence. This appraisal investigated particle size influence and limitations of spectrographic grease elemental analysis using samples acquired from wind turbine pitch bearings through a passive sampling approach, the wind turbine in question having undergone a failure condition induced by high current discharge as a result of a lightning strike to a single blade. RDE-AES and ICP-MS elemental grease analysis results were comparatively apprised, in order to illustrate the importance of particle size limitations on condition monitoring. The findings of this ‘particle size influence’ study were validated through a comprehensive ferrographic wear particle analysis. The comprehensive appraisal concluded that RDE-AES holds more practical potential for the widespread application of grease elemental analysis, for proactive condition monitoring of grease-lubricated systems due to higher particle size limits and indeed minimal preparatory requirements. The appraisal also noted the merits of the application of differential methods for elemental analysis of lubricants, including that of grease, whereby particle size limitations can be leveraged for the determination of more severe wear scenarios thereby preventing potential misdiagnosis by what is essentially a double check of elemental findings.
Appraisal Study 2: Sampling Location Influence. This appraisal examined the influence of sampling locations on wear condition assessment, based on critical locations within rolling stock axle journal bearings by RDE-AES, the objective being 139
to establish the practically or otherwise of grease elemental analysis to enhance failure prediction. This was undertaken as current detection methods are not entirely robust and such bearing failures have the potential for catastrophic axlebox failures which can lead to derailment of a train. Grease samples were acquired through use of an active sampling approach post bearing removal during a scheduled bogie overhaul to enable the establishment of an elemental wear profile across the entire bearing assembly. The appraisal served to highlight the critical nature of the sampling process, including location, on the results obtained, and that elemental results can show strong correlation to visual inspection. Furthermore, the appraisal endorsed the need for selected dismantling of greaselubricated bearings in order to obtain a comprehensive wear profile, so as to enable confident interpretation of results based on more easily accessed regions within a bearing for condition monitoring purposes. The final inference from the appraisal was that there may be several situations where condition monitoring methods of grease-lubricated rolling element bearings is precluded but in situations where representative sampling can be obtained reliably, and with relative ease, the benefits of having significantly increased machine condition failure detection times over traditional methods are self-evident. In synopsis, diverse situations and influencing factors for wear, contamination and grease condition can in-turn show elemental machine condition coherences with a reasonably low level of complexity between the grease analysis results and their real-world consequence as demonstrated through the appraisal studies conducted. This leads the author to the conclusion that observing and interpreting these elemental factors coupled with detailed knowledge of the system in question can enable proactive maintenance strategies to be applied in an efficient manner through the RDE-AES protocols of which the whole grease smear method (Protocol II) is of most promise, and provides the potential for enabling the earliest possible detection of the onset of failure. Improved tribological condition monitoring protocols for grease elemental analysis have diverse and far-reaching applications and implications to components operation, reliability and ultimately costs.
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8.2.1. Original Contributions of Research The following summarises the original contributions, determinations and/or recommendations which are deemed to be the most significant. A. The development of protocols for spectrographic simultaneous multi-elemental analysis of grease lubricant based on rotating disc electrode atomic emission spectroscopy, in combination with the associated preliminary statistical investigation and appraisal of results attained.
B. The determination that Protocol II the whole grease smear RDE-AES grease elemental analysis method is of most potential; with minimal preparation needs, which consumes small volumes of less than 0.3 g, and has no requirement for nonstandard or hazardous consumables. This method was shown to be most accurate across the elemental range involved and was demonstrated to be effective in distinguishing bearing conditions, and provided accurate representation of true bearing condition, based on the appraisal studies conducted on real applications.
C. Verification of the influence of particle size influence, for spectral elemental analysis condition determination of grease lubricants through the comparative appraisal of both RDE-AES and ICP-MS was established.
D. Validation of C by means of a comprehensive wear particle analysis, scrutinised by the application of analytical ferrography, for which an unconventional blank oil based dilution process was used to create ferrograms deemed to be both representative of the wear and decipherable. The wear particle analysis centred on wear generated during the operational use of three wind turbine pitch bearings, one of which had undergone a known failure condition.
E. Substantiation of the influence of sampling location effects on the condition monitoring deductions, this being based on grease elemental analysis from demanding rolling element bearing applications.
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F. Establishment of a preliminary wear profile for axel journal bearings as referred to in E, for rolling stock applications, with the critical nature of the sampling process, including location, being demonstrated.
G. Conclusion F resulted in endorsement of the need for selected dismantling of grease-lubricated bearings in order to obtain a reliable and truly representative wear profile, thereby enabling more accurate condition assessments based on sampling locations of easy access.
H. Confirmation of prospective feasibility and suitability of grease elemental analysis through the RDE-AES protocols developed based on both passive and active sampling approaches. This was established from the data acquired from appraisal studies conducted in a field environment, and directed for the predictive or proactive condition monitoring of grease-lubricated rolling element bearings in highly critical applications.
8.3.
Review of the Limitations of Grease Elemental Analysis
The following reviews the limitations of grease elemental analysis that were recognised in the course of this research: A. Sampling difficulties: The applicability of grease elemental analysis for condition monitoring of grease-lubricated rolling element bearings is critically limited on the possibility of obtaining representative samples.
B. Complexity of grease analysis interpretation: Condition monitoring conclusions that may be drawn from grease elemental analysis are not straightforward. Elements that can be detected can originate from multiply sources e.g., molybdenum and zinc found in a lubricating grease sample could originate from the both wear metal creation or be present as additives.
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C. RDE-AES elemental range limitations: The inability of RDE-AES in current configurations to detect lithium, the most common thickener element currently used in grease, severely hampers its application to detecting a common root cause of failure initiated by the mixing of incompatible greases.
D. Particle size limitations: The maximum 10 Âľm limit of RDE-AES elemental analysis promotes the potential for critical failures to go undetected and the underestimation of criticality level.
E. Combination of information: Whilst grease elemental analysis alone although it provides an extremely valuable insight into grease-lubricated rolling element bearing condition, it is the combination of the information that can be ascertained by condition monitoring test including grease elemental analysis that can lead to comprehensive failure prevention.
F. Rapid failure rate: Since both bearing material fatigue failure and grease lubricant failure are not deterministic, there is a possibility that some types of failures may occur so suddenly that grease elemental analysis performed at any practical frequency might not provide an advanced failure warnings. Notwithstanding the above limitations, the potential benefits of improved failure predictions and consequently downtime reductions of grease-lubricated rolling element bearings through advance diagnosis made possible via grease lubricant analysis are immense, particularly for critical, high-performance and demanding applications
8.4.
Recommendations for Future Work
Although a number of significant research outcomes and original contributions have been attained through the research conducted, there are additional considerations that have not been addressed by this, or current research. The following highlights key recommendations for future work that would be expected to provide important insights. The recommendations proposed for future work are as follows:
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A. The undertaking of controlled experimental bench testing on a suitable test rig in order to acquire controlled grease samples as a function of key parameters including rotational speed, loading, run time, cyclic loading and temperature thereby enabling a complete profile of bearing condition, and more reliable life predictions based on elemental grease analysis. In addition, common failure scenarios could be induced and monitored, such as, severe lubrication conditions like starvation, over-packing, incompatibility or specific solid or fluid contaminates scenarios, these providing an insight into the consistency of elemental data over bearing operational life. Significantly this would enable robust correlation between dominant failure modes and root-causes to be deduced by elemental data.
B. The study of bearing condition established on elemental data over extended periods would provide comparable research benefits as per recommendation A. At the time was not possible to be undertaken by this research. Due to time constraints, this was beyond the scope of this project. The information and knowledge to be gained from a prolonged study, particularly on highly critical applications over an extended period would broaden the knowledge and understanding of wear profiles and failure mechanisms of real applications. The findings would have immense benefit to the industry or application involved, including not only the end users but also the equipment designer and equipment manufacturers.
C. The further investigation of underlying factors that impact elemental recovery through RDE-AES is recommended. As outlined in the discussion in Section 5.2, Chapter 5, grease consistency, elemental particle properties, and physical particle properties including size, shape and density can be assumed to be the underlying factors which influence the results. The precise consequences or relationships was not explored in this study. Therefore further investigation is merited because the resultant more in-depth understanding would be expected to enable improvemed elemental data consistency.
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D. There is quite a limited knowledge of the effect of sampling on grease condition assessment, including that of elemental analysis. Whilst this research has addressed key aspects pertaining to the influence of particle size and sampling location through both passive and active sampling approaches, important questions remain unanswered e.g., Can a single or mixed active sample truly reflect the condition of the bearing over its entire life? Does dilution and the corruption of evidence as a result of a passive sample approach effect the condition assessment of a bearing? Which approach has the most legitimacy? Is it application specific?
E. The increase of the RDE-AES elemental range is strongly recommended. The inability of RDE-AES test equipment to detect lithium, the most common thickener element currently used in grease is a severe limitation which hampers the detection of a common failure caused by the mixing of incompatible greases. The increased capability would also be of benefit to RDE-AES oil and fuel analysis enabling the detection of lithium grease contamination. Significantly, RDE test equipment producers, Spectro Inc, are actively exploring this capability.
F. No standardised method for used grease elemental analysis currently exits. Therefore there is a distinct need for the development of an international standard in this arena. In order to achieve such an accepted standard, further investigation most notably the development of a code of practice via an interlaboratory study is required. Additionally, the development of a standard elemental reference grease, akin to those available for oil, would be highly recommended to enable enhanced credibility and certainty of results. These measures would rapidly allow for widespread industrial recognition of the use of RDE-AES grease elemental analysis as a technique for condition monitoring of critical grease-lubricated components.
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Turner, D., Used Grease Analysis Tests and Their Significance, in NLGI Conference. 2012. Raadnui, S., Low-cost Used Grease Analysis for Rolling Element Bearings. Practicing Oil Analysis, 2004. November. SKF Group. SKF Grease Test Kit TKGT 1. [cited 2013 2/05]; Available from: http://www.skf.com/binary/12-35956/MP5366E.pdf. Bots, S., Grease Analysis: Early Warning System for Failures and Proactive Maintenance Tool. Machinery Lubrication, 2013(February). Lukas, M. and R. Yurko, Current Technology in Oil Analysis Spectrometers and What We May Expect in the Future. 1996, DTIC Document. Spectro Inc, Overview and Systems Descriptions. Spectroil M. 2009. Version 3.4. Noria Corporation, Elemental Analysis. Practicing Oil Analysis, 2002 (January). Kramida, A., et al. NIST Atomic Spectra Database (ver. 5.0) [Online] 2012 [cited 2013 13, June]; National Institute of Standards and Technology, Gaithersburg, MD:[Available from: http://physics.nist.gov/asd. Anderson, D.P., M. Lukas, and B.K. Lynch, Diesel Engine Coolant Analysis, New Application for Established Instrumentation. 1998, DTIC Document. Lukas, M. and D. Anderson, Analytical Tools to Detect and Quantify Large Wear Particles in Used Lubricating Oil. Spectro Inc., MA, 2003. Johnson, M., Wear Debris Measurement. Tribology and Lubrication Technology (STLE), 2011(May): p. 27-34. Lukas, M., D.P. Anderson, and R.J. Yurko. New Development and Functional Enhancements in RDE Used Oil Analysis Spectrometers. in 1998 International Oil Analysis Conference. 1999. ASTM International, ASTM D6595 - 00: Standard Test Method for Determination of Wear Metals and Contaminants in Used Lubricating Oils or Used Hydraulic Fluids by Rotating Disc Electrode Atomic Emission Spectrometry. 2011. Anderson, D.P., et al., Rotrode filter spectroscopy: A method for multi-elemental analysis of particles in used lubricating oil. Lubrication Engineering, 1999. 55(10): p. 32-40. Saba, C.S., Improving the wear metal detection of spectrometric oil analysis. Lubrication Engineering, 1990. 46: p. 310-7. Bowen, E., J. Bowen, and D. Anderson. Application of Ferrography to grease lubricated systems. in 46th Annual Meeting NLGI. 1978. Anderson, D.P., Wear Particle Atlas. Revised. 1982, Naval Air Engineering Center. Dalley, R.J., An overview of ferrography and its use in maintenance. Predictive Maintenance Seminar. , 1991(Particle Analysis Division of Predict). ASTM International, Research Report RR: D02-1608 2006. ASTM International, ASTM D7718 â&#x20AC;&#x201C; 11: Standard Practice for Obtaining In-Service Samples of Lubricating Grease. 2011. Shorten, D., Used Grease Analysis Integrated into Critical Equipment Inspection Deferral Programs. Machinery Lubrication, 2001. March. Fitch, J., Why You Should Inspect Bearing Grease Discharge. Machinery Lubrication, 2012. October. ThyssenKrupp Rothe Erde GmbH. Grease sampling set. 2013 [cited 2013 25, June]; Available from: http://www.thyssenkrupp-rotheerde.com/Gb/.
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150
Appendices The appendices of the report contains four sections. The first section, Appendix A; provides a supplementary information that did not make it into the main body, but does merit inclusion in the appendices. The second section Appendix B; provides detail of the grease solvent study conducted. The third section Appendix C; contains complete statistical results based on works as referred to in Chapter 5. The fourth section Appendix D; of the report contains original ferrography report sheets used during ferrographic validation.
151
Appendix A. Supplementary Information, on Grease Qualification Testing, Grease Compatibility and Grease Properties
Table 0-1: Grease Qualification
Test
Governing Standards
Accelerated wheel bearing grease
ASTM D4290
leakage Acid & base number, colorimetric
ASTM D974
Acid & base number, potentiometric
ASTM D664
Apparent viscosity
ASTM D1092
Bearing rust test
ASTM D1743/5969
Copper corrosion
ASTM D4048/IP 112
Cone penetration
ASTM D217/ISO 2137
Contact (grease maker) CVJ efficiency rig Dropping point
ASTM D2265
Elemental Analysis ICP
ASTM D7303
EMCOR dynamic rust test
IP220/ISO 11007
Evaporation loss
IP183
FAG FE8
DIN51819T2
Four ball wear
ASTM D2266
Four ball EP
ASTM D2596
Elastomer compatibility
ASTM D4289/D471
Fretting wear
ASTM D4170
FZG gear low speed high speed
ISO 14735.03/ASTM D5182
Low temperature torque
ASTM D1478
Life performance automotive wheel
ASTM D3527
bearing Oil Separation
ASTM D6184/IP121
Oil separation during storage
D1742 152
Oxidation stability, bomb method
ASTM D942
PDSC oxidation induction time
ASTM D5483
Rheometer Roll stability
ASTM D1831
Rolling bearing grease performance
IP168
Salt fog corrosion
B117
SRV
ASTM D5707/5706
Timken EP
ASTM D2509
Water in petroleum products
ASTM D95/ISO 3733
Water spray-off
ASTM D4049
Water washout
ASTM D1264/ISO 11009
Wheel bearings low temp torque
ASTM D4693
Water resistance
DIN 51807 part 1
153
Table 0-2: Grease Compatibility Chart
Calcium 12 Hydroxy
Calcium Complex
Calcium Sulfonate
Lithium Stearate
Lithium 12 Hydroxy
Lithium Complex
Polyurea
Silica Gel
Sodium Soap
I
Calcium Stearate
I
Bentonite (Clay)
Barium Complex Bentonite (Clay) Calcium Stearate Calcium 12 Hydroxy Calcium Complex Calcium Sulfonate Lithium Stearate Lithium 12 Hydroxy Lithium Complex Polyurea
Barium Complex
n/ a I
Barium Soap
Aluminium Complex Aluminium Complex Barium Soap
I
I
I
I
C
I
B
I
I
C
I
C
B
n/ a
I
I n/ a I
B
B
B
B
I
I
C
I
C
I
I
I
I
C
C
I
I
I
I
I
I
C
I
C
C
B
C
I
B
B
C
C
C
I
I
I
I
C
B
B
I
I
n/ a C
C
C
C
n/ a C
B
I
I
C
I
B
I
C
C
I
C
I
C
I
n/ a I
I
C
I
B
I
I
I
B
B
C
I
C
B
n/ a I
I
B
I
I
C
C
I
n/ a B
I
I
B
C
I
B
n/ a C
I
I
C
C
C
C
C
n/ a C
I
I
I
I
B
I
I
I
C
I
B
C
C
I
I
I
I
I
B
I
Silica Gel
C
C
Sodium Soap
B
I
I
154
I I
I
C
I
C
n/ a B
I
C
n/ a
I
I n/ a I
I n/ a
Table 0-3: General Grease Properties. Adopted From [97] Grease type
Petroleum-oil greases Drop point °C 1
Maximum application temperature, °C
Polyethylsiloxane greases
Hydrolytic (water) stability
Antiwear and antiseizure properties
Maximum application temperature, °C
Hydrolytic (water) stability
Antiwear and antiseizure properties
Soap greases Sodium Lithium Lithium complex Hydrated calcium Anhydrous calcium
130160 175205 250 70-85 130140
100-110
Poor
Satisfactory
110-115
Poor
Low
110-125
Good
Satisfactory
120-130
Good
Low
150-160
Good
High
160-170
Good
Satisfactory
60-70
High
Good
—
—
—
100-110
High
Good
—
—
Calcium complex
230
140-150
Satisfactory (absorb water and compact)
High
Aluminium
95-120
65-70
High
Good
Aluminium complex
250
150-160
High
High
— 160-170
Satisfactory (absorb water and compact) —
Good
160-170
High
Good
—
—
Inorganic greases Silica gel
Absent
130-170
Good
Moderate
160-170
Good
Poor
Bentonite
Absent
120-150
Good
Satisfactory
130-150
Good
Poor
High
300-350 2
High
Good
Organic greases Carbon black Polymeric (fluorinated hydrocarbons) Pigment Polyurea
Absent
Absent 250
160-200
High
80-150
Satisfactory
Good
140-160
Satisfactory
Good
160-200 150-200
Good Good
High Good
250-3002 200-2302
Good Good
Good Satisfactory
50-65
High
Satisfactory
Hydrocarbon greases 50-70
50-60
High
Good
155
A. Appendix B. Grease Solvent Investigation Grease Solvent Dilution Findings Overview Four greases used were as follows: (A) LOCOLUB TMGG 516 a lithium soap thickener, mineral base oil, barium rust inhibitor and NGLI grade of 3. (B) SILKOLENE 783/L a silicone clay thickener, mineral base oil, and NGLI grade of 5. (C) RENOLIT LX EP 2 a complex lithium soap, synthetic base oil, with a ZDDP (zinc dithiophosphate) EP (extreme pressure) additive package and NGLI grade of 2. (D) Mallues Grease, a bentonite clay thickener mineral base oil, graphite EP (extreme pressure) additive package and NGLI grade of 0/00. The solvents solution mix percentage can be seen in Table A-1. Table A-1: Solvents Solutions Used Solvent
Mix %
Solvent 1
Toluene, Isopropanol
50% - 50%
Solvent 2
Toluene, Methyl ethyl ketone, Isopropanol
33% - 33% - 34%
Solvent 3
Toluene, Hexane
30% - 70%
Solvent 4
Toluene, Hexane
50% - 50%
Solvent 5
Toluene, Hexane
70% - 30%
Grease Solvent Dilution Results Two studies were performed on the solvent preparation method using the greases A, B, C and D in an unused condition and solvents 1-5 as specified in Table A-2. Results presented are based on mean dissolution (Rounded to whole numbers) were full dissolution was not achieved after 60 seconds in ultrasonic bath solvent dissolution was deemed incomplete and was discounted.
156
Figure A-1: Grease Solvent Testing Table A-2: Grease Solvent Dilution Results
Mean Dissolution Time Grease A
Grease B
Grease C
Grease D
Solvent 1
Incomplete
28 s
Incomplete
35 s
Solvent 2
Incomplete
33 s
Incomplete
16 s
Solvent 3
10 s
22 s
14 s
4s
Solvent 4
4s
30 s
8s
2s
Solvent 5
3s
26 s
5s
6s
In order to dissolve the greases, a study was undertaken to evaluate various solvent combinations the result of which are presented in Table A-2. Due to the various thickeners and additives used in the composition of greases, a single, general solvent could not be deemed established at this point. However, solvents 3-5, composed of toluene and hexane solutions of various compositions, appeared to be the most universal
solvent, as the solvating action was applicable over the selection of greases used in the study, including lithium soap greases. In contrast, with regards solvent 1 which was composed of 50% toluene and 50% isopropanol solution, this solvent was found to be ineffective with lithium soap greases. Similarly solvent 2 which was composed of 33% toluene, 33% methyl ethyl ketone and 34% isopropanol, showed a somewhat similar effect as solvent 1 on lithium soap grease. Therefore, solvents based on toluene and hexane mixture will be chosen for the future analysis in research study.
157
B. Appendix C. Grease Elemental Analysis by RDE-AES Results
158
G1: Lithium-Complex Grease
Figure B-1: Mean Plot of Elemental Data with 95% Confidence Interval - G1
Figure B-2: Distribution of Elemental Data - G1
159
Table B-1: Analysis of Variance for Iron â&#x20AC;&#x201C; G1
Figure B-3: Distribution of Data Iron-G1
Figure B-4: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G1
Figure B-5: Means Comparison Chart Iron-G1
160
Table B-2: Analysis of Variance for Boron â&#x20AC;&#x201C; G1
Figure B-6: Distribution of Data Boron-G1
Figure B-8: Means Comparison Chart Boron-G1
Figure B-7: Mean Plot of Boron Elemental Data with 95% Confidence Interval-G1
161
Table B-3: Analysis of Variance for Phosphorus â&#x20AC;&#x201C; G1
Figure B-9: Distribution of Data Phosphorus-G1
Figure B-10: Mean Plot of Phosphorus Elemental Data with 95% Confidence Interval-G1 Figure B-11: Means Comparison Chart Phosphorus-G1
162
Table B-4: Analysis of Variance for Zinc â&#x20AC;&#x201C; G1
Figure B-12: Distribution of Data Zinc-G1
Figure B-14: Means Comparison Chart Zinc-G1
163
Figure B-13: Mean Plot of Zinc Elemental Data with 95% Confidence Interval-G1
G2: Lithium-Calcium Complex Grease
Figure B-15: Mean Plot of Elemental Data with 95% Confidence Interval â&#x20AC;&#x201C; G2
Figure B-16: Distribution of Elemental Data â&#x20AC;&#x201C; G2
164
Table B-5: Analysis of Variance for Iron â&#x20AC;&#x201C; G2
Figure B-17: Distribution of Data Iron-G2
Figure B-19: Means Comparison Chart Iron-G2
165
Figure B-18: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G2
Table B-6: Analysis of Variance Calcium â&#x20AC;&#x201C; G2
Figure B-20: Distribution of Data Calcium-G2
Figure B-21: Mean Plot of Calcium Elemental Data with 95% Confidence Interval-G2 Figure B-22: Means Comparison Chart Calcium-G2
166
Table B-7: Analysis of Variance for Phosphorous â&#x20AC;&#x201C; G2
Figure B-23: Distribution of Data Phosphorous-G2
Figure B-24: Mean Plot of Phosphorus Figure B-25: Means Comparison Chart Phosphorous-G2 Elemental Data with 95% Confidence IntervalG2
167
Table B-8: Analysis of Variance for Zinc â&#x20AC;&#x201C; G2
Figure B-26: Distribution of Data Zinc-G2
Figure B-28: Means Comparison Chart Zinc-G2
168
Figure B-27: Mean Plot of Zinc Elemental Data with 95% Confidence Interval-G2
G3: Lithium Grease
Figure B-29: Mean Plot of Elemental Data with 95% Confidence Interval - G3
Figure B-30: Distribution of Elemental Data â&#x20AC;&#x201C; G3
169
Table B-9: Analysis of Variance for Iron â&#x20AC;&#x201C; G3
Figure B-31: Distribution of Iron-G3
Figure B-33: Means Comparison Chart Iron-G3
170
Figure B-32: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G3
Table B-10: Analysis of Variance for Sodium â&#x20AC;&#x201C; G3
Figure B-34: Distribution of Sodium-G3
Figure B-36: Means Comparison Chart Sodium-G3
171
Figure B-35: Mean Plot of Sodium Elemental Data with 95% Confidence Interval-G3
Table B-11: Analysis of Variance for Molybdenum â&#x20AC;&#x201C; G3
Figure B-37: Distribution of Data Molydenum-G3
Figure B-39: Means Comparison Chart Molydenum-G3
172
Figure B-38: Mean Plot of Molybdenum Elemental Data with 95% Confidence IntervalG3
Table B-12: Analysis of Variance for Zinc â&#x20AC;&#x201C; G3
Figure B-40: Distribution of Data Zinc-G3
Figure B-42: Means Comparison Chart Zinc-G3
173
Figure B-41: Mean Plot of Zinc Elemental Data with 95% Confidence Interval-G3
G4: Bentonite Clay Grease
Figure B-43: Mean Plot of Elemental Data with 95% Confidence Interval - G4
Figure B-44: Distribution of Elemental Data â&#x20AC;&#x201C; G4
174
Table B-13: Analysis of Variance for Iron â&#x20AC;&#x201C;G4
Figure B-45: Distribution of Data Iron-G4
Figure B-47: Means Comparison Chart Iron-G4
175
Figure B-46: Mean Plot of Iron Elemental Data with 95% Confidence Interval-G4
Table B-14: Analysis of Variance for Calcium â&#x20AC;&#x201C; G4
Figure B-48: Distribution of Data Calcium-G4
Figure B-50: Means Comparison Chart Calcuim-G4
176
Figure B-49: Mean Plot of Calcium Elemental Data with 95% Confidence Interval-G4
Table B-15: Analysis of Variance for Sodium â&#x20AC;&#x201C; G4
Figure B-51: Distribution of Data Sodium-G4
Figure B-53: Means Comparison Chart Sodium-G4 Figure B-52: Mean Plot of Sodium Elemental Data with 95% Confidence Interval-G4
177
C. Appendix D. Ferrography
Figure C-1: Pitch Bearing 1 Ferrography Report Sheet
Figure C-2: Pitch Bearing 2 Ferrography Report Sheet
178
Figure C-3: Pitch Bearing 3 Ferrography Report Sheet
179