X-ray transmission sorting of tungsten ore

Optimal sensor selection for sensor-based sorting based on automated mineralogy data

Sensor-based sorting has had a wide range of industrial use in automating and speeding up the process which requires substances or objects to be segregated from each other. The high demand for goods including raw materials, food, minerals, and waste recycling has increased the pressure for high-speed sorting. The first part of this paper presents a comprehensive theoretical and practical survey and comparison of current sorting methods relying on the use of the electromagnetic spectrum. Sorting methods are classified among other things, which portion of the EM spectrum is it, background noise rejection capacity, sample size limitations, sample chemistry limitations, sample surface cleanliness, spatial resolution capacity, spectral resolution, and feed rate limitations. The analysis focuses on color or visible light sorting, gamma-ray sorting, infra-red sorting, x-ray transmission-based sorting and x-ray fluorescence sorting, coupling the findings to the classification criteria outlined. We see a need to define a universal sorting scheme that will in general be applied to most sorting tasks. To do this, the final part of this paper re-looks at the x-ray transmission and x-ray fluorescence sorting scheme in line with the established limitations and proposes a dual x-ray transmission and fluorescence method to mitigate the challenge affecting the different schemes.

Sensor-Based Ore Sorting—A Review of Current Use of Electromagnetic Spectrum in Sorting

X-ray fluorescence and transmission have found common use in large-scale diamond sorting. These methods have progressed independently with each providing a solution for a specific range of particle size. Fluorescence is applicable for diamond sizes between 1.25 - 32 mm and is subject to self-absorption, while transmission has been used on diamond fractions between 10 mm - 100 mm. Transmission sorting suffers poor contrast at particle sizes below 10 mm. Parametric x-ray absorption fine structure models of fluorescence, with five describing features, and a transmission one with five parameters, are developed for both phenomena and simulated against literature for correctness. Furthermore, we define a new x-ray signature parameter by combining high-density ensemble data from both modes for a calibrated sample which we use as a benchmark in our sorting criteria. Finally, we construct random theoretical pure compounds and implore a fast noise rejecting Kolmogorov-Smirnov sorting algorithm to test random samples against the calibrated sample. For compounds that are closely related to the calibration sample, we obtained a percent similarity in the order of 98 %, while completely dissimilar theoretical compound similarity can be as low as 6 %

X-ray transmission sorting of tungsten ore

Citations

Optimal sensor selection for sensor-based sorting based on automated mineralogy data

Sensor-Based Ore Sorting—A Review of Current Use of Electromagnetic Spectrum in Sorting

A Fast and Noise Rejecting Kolmogorov-Smirnvo Sorting Algorithm in X-ray Diamond sorting

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