Real-Time Quantitative Mineral Analysis (QMA) using Artificial Intelligence (AI) Enabled LIBS Sensor for Bulk Ore Sorting on Mining Conveyors

D. Gagnon, Francis Vanier, J. Haddad, Elton Soares de Lima Filho, Antoine Hamel, C. Padioleau, Francis Boismenu, André Beauchesne, P. Bouchard, Tony Vaillancourt, M. Sabsabi, Alain Blouin, A. Plugatyr, A. Harhira
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Abstract

Crushing and grinding rocks are energy-intensive. This paper shown the development pathway and the performances of an unprecedented sensor dedicated to run-of-mine ore characterization for bulk sorting to reduce the amount of waste rocks processed.
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实时定量矿物分析(QMA)使用人工智能(AI)支持的LIBS传感器在采矿输送机上进行散装矿石分选
破碎和研磨岩石是能源密集型的。本文展示了一种前所未有的用于散装分选的原矿特征传感器的发展路径和性能,以减少废石的处理量。
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