A review of intelligent ore sorting technology and equipment development
Xianping Luo, Kunzhong He, Yan Zhang, Pengyu He, Yongbing Zhang. A review of intelligent ore sorting technology and equipment development, Int. J. Miner. Metall. Mater., 29 (2022), No. 9, p. 1647-1655.
intelligent ore sorting technology; sorting equipment; separation efficiency; online element rapid analysis technology
Under the background of increasingly scarce ore worldwide and increasingly fierce market competition, developing the mining industry could be strongly restricted. Intelligent ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings production. However, long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology, equipment sorting actuator, and information processing algorithm. The high precision, strong anti-interference capability, and high speed of these factors guarantee the separation efficiency of intelligent ore sorting equipment. Color ore sorter, X-ray ore transmission sorter, dual-energy X-ray transmission ore sorter, X-ray fluorescence ore sorter, and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting efficiency. With the continuous improvement of mine automation level, the application of online element rapid analysis technology with high speed, high precision, and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the future. Laser-induced breakdown spectroscopy, transient γ neutron activation analysis, online Fourier transform infrared spectroscopy, and nuclear magnetic resonance techniques will promote the development of ore sorting equipment. In addition, the improvement and joint application of additional high-speed and high-precision operation algorithms (such as peak area, principal component analysis, artificial neural network, partial least squares, and Monte Carlo library least squares methods) are an essential part of the development of intelligent ore sorting equipment in the future.
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