REWO-SORT Sensor Fusion for Enhanced Ore Sorting: a Project Overview

Among the numerous challenges recently confronting the mining industry is the need to process ore with successively lower grades due to the continuous depletion of high-grade deposits. This increases the consumption of energy and water and, thus, the operational costs at a mine site. Multimodal sort...

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Hauptverfasser: Firsching, Markus, Bauer, Christine, Wagner, Rebecca, Ennen, Alexander, Ahsan, Amit, Kampmann, Tobias Christoph, Tiu, Glacialle, Valencia, Alvaro, Casali, Aldo, Montes Atenas, Gonzalo
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Sprache:eng
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Zusammenfassung:Among the numerous challenges recently confronting the mining industry is the need to process ore with successively lower grades due to the continuous depletion of high-grade deposits. This increases the consumption of energy and water and, thus, the operational costs at a mine site. Multimodal sorting represents a promising technique to achieve pre-concentration of valuable minerals already at an early stage in the metallurgical process.In the ERA-MIN2 project “Reduction of Energy and Water Consumption of Mining Operations by Fusion of Sorting Technologies LIBS and ME-XRT” (REWO-SORT), a fusion technology including laser-induced breakdown spectroscopy (LIBS) and multi energy X-ray transmission (ME-XRT) is being developed by a multidisciplinary expert consortium. The project aims at classifying crushed mineral particles on a conveyor belt with the aid of deep learning technologies. In addition, the operating conditions to work with high throughput while keeping a particle monolayer on the conveyor belt have been identified. The latter objective is addressed using discrete element method (DEM) simulations. Parameter calibrations were experimentally obtained using a copper sulfide ore from the Rafaela mining company (Chile). The combination of LIBS and ME-XRT is promising, as they complement each other regarding analytical and particle selection capabilities: LIBS can provide an elemental analysis of the sample surface, while ME-XRT produces volumetric data with lower accuracy. Both sensors will be combined to extrapolate accurate and representative volumetric data, thereby securing an optimal particle selection at high throughputs. First measurements and analyses of ore samples using LIBS and ME-XRT, as well as their correlation with the Cu concentration obtained by reference lab analysis will be presented and discussed. Preliminary DEM studies indicate the existence of a threshold of conveyor belt surface area covered with particles of around 85%. Above this value the particle monolayer cannot be maintained, imposing another restriction for the speed of sensor analysis.