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Sensor-based sorting for potash operations By Rebecca Gotto and Lucinda Wood, Saskatchewan Research Council The solution A new test performed by the Saskatchewan Research Council (SRC) that combines high-resolution X-ray micro Computer Tomography (CT) with QEMScan has the ability to gather not only information about the amenability of ore to XRT sorting, but to obtain valuable information about mineralogy and optimum sensing parameters that can streamline metallurgical test work programs. To complete the test, SRC’s team conducts 3D CT scanning on potash samples to obtain volumetric information of individual mineral phases. QEMScan is then used to calibrate the greyscale values of the 3D volume, which reflects different

SRC’s Industrial CT Scanner. PHOTO PROVIDED BY SRC.




atomic numbers of minerals in the potash sample.


through particles, not just their sur-

ing increasingly prevalent for min-

faces, to generate images of varying

This test also provides information

ing operations as a method to re-

greyscale that indicate mineralogical

relating to grain size and associated

move waste or to upgrade ore prior

differences within the particle and

X-ray attenuation coefficients, de-

to downstream hydrometallurgical

then mechanically separate them.

sired mineral presence, and infor-

ing has the potential to upgrade

A popular test currently used to

erals and clays used to later assist

feed prior to milling and hydromet-

evaluate the amenability of the ore

with developing sorting algorithms.

allurgical processes, thereby reduc-

to X-ray sorting is to simply pass

This ensures that industry can get a

ing plant footprints, tailings storage

the particles through an industrial

quick and accurate understanding of

facilities, and energy consumption.

sorter and obtain grey-scale images

whether sorting is the right technol-

However, potash projects and opera-

based on default imaging param-

ogy for their needs and have the op-

tions need to know if this technology

eters. This test provides information

timum parameters to proceed with

is appropriate, and what its optimal

on the presence of mineralogical

their metallurgical test work. This

parameters are.

differences, but it does not provide

also results in streamlined metallur-

an understanding of the actual min-

gical test work as the range of pa-

processing. Sensor-based ore sort-

The problem

eralogical composition of the ore. It

mation relating to associated min-

rameters to be tested have already been optimized beforehand.

Of all the ore sorting technologies

also does not necessarily pick up all

available, X-ray transmission (XRT)

the differences owing to its default

Industrial CT systems offer great

sorters are one of the most com-

imaging parameters, especially for

versatility and many advantages in

mon choices. That is because XRT

lesser known commodities or com-

analyzing large or dense materials,

sorters pass high-intensity X-rays

plex ores.

such as mineral containing potash,

58 PotashWorks 2021

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PotashWorks 2021  

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