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Research on soft sensor method of copper concentrate grade based on NNG-LSSVM |
Received:May 22, 2020 Revised:May 27, 2020 |
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DOI:doi:10.3969/j.issn.1671-9492.2021.03.015 |
KeyWord:LSSVM; NNG; copper mine flotation; soft sensor; copper concentrate grade |
Author | Institution |
wuhao |
Qilu University of Technology |
panbingqing |
Qilu University of Technology |
yanghuilin |
Qilu University of Technology |
sunkai |
Qilu University of Technology |
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Abstract: |
Abstract: Flotation technology is the most primary method of beneficiation of copper mines and has been widely used. In the flotation process, the grade of copper concentrate determines the quality of the final product, therefore it’s a key variable in the entire process. Nevertheless, in the actual production, the measurement of this parameter takes a long time, making it difficult to measure in real time online. The paper proposes a soft-sensing method based on non-negative garrote and least squares support vector machine, and uses the actual production data provided by the DCS system to predict and model this variable. The simulation results show that the researched soft-sensing method can accurately predict the change of copper concentrate grade, and can well realize the real-time prediction and estimation of concentrate grade, and the accuracy of model obviously superiors to other soft-sensing methods. |
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