Luo, Danoczi, Nakutnyy
Presented at the Preconcentration Digital Conference November 2020
Sensor-based sorting methods to remove waste or for upgrading ore prior to downstream metallurgical processing is becoming more prevalent for mining operations. X-ray transmission (XRT) sorters are a popular choice for mineral processing plants since they can sort a wide variety of minerals. XRT sorters pass high intensity X-rays through particles to generate images of varying greyscale, based on their effective atomic density. The ore sorter then mechanically separates the particles using algorithms based on the images.
A popular test currently used to evaluate the amenability of the ore to XRT sorting is to pass the particles through the sorter and obtain the greyscale images showing mineralogical differences. This test provides information on the mineralogical heterogeneity between ore particles for their separation. However, it does not provide an understanding of the actual mineralogical composition of the ore or information pertaining to which other minerals may respond in a similar manner, nor does it provide liberation information.
This paper describes a test that combines high resolution X-ray micro Computer Tomography (CT) combined with QEMScan to obtain information about amenability of ore to XRT sorting and to obtain valuable information that can streamline metallurgical testwork programs. This test also provides information relating to particle thickness and associated X-ray attenuation coefficients, desired mineral presence and mineralogical information relating to associated minerals and clays to assist with developing sorting algorithms. Combining the CT and QEMScan can address many limitations of the current method to determine whether XRT sorting technology is appropriate for particular ores. Mineralogy information from QEMScan can identify incidences of; mineral encapsulation, problematic clays, detrimental minerals as well as calibrate the greyscale values of CT data. Additional 3D CT imaging carried out on cores provides spatial information of the minerals within the ore and mineral grades.
P Luo1, J E Danoczi2 and P Nakutnyy3
The authors appreciate the permission granted from the Saskatchewan Research Council for publishing the paper
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