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| Industrial application of a ball mill optimization control system based on digital twin technique |
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Received:February 17, 2025
Revised:February 17, 2025
Accepted:February 18, 2025
Published Online:August 05, 2025
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| DOI： |
| KeyWord:Ball;Mill, Digital;twin, Optimal;control, Intelligence, Industrial;system |
| Author | Institution |
| ZHOU Yun |
Dexing copper mine,Jiangxi Copper Co Ltd,Shangrao |
| WANG Binjie |
BEIBU GULF UNIVERSITY,Qinzhou,;BGRIMM Technology Group |
| ZHANG Zhengfei |
Dexing copper mine,Jiangxi Copper Co Ltd,Shangrao |
| LIU Daoxi |
BGRIMM Technology Group |
| SONG Tao |
BGRIMM Technology Group |
| YANG Jiawei |
BGRIMM Technology Group |
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| Abstract: |
| After more than ten years of development, digital twin technology has gradually moved from the conceptual stage to the industrial development stage and has begun to see different industrial application cases in the mineral processing industry. In the closed-circuit grinding process of a domestic mineral processing plant, which consists of conventional ball mills and hydrocyclones, the raw ore is from different sites and the properties of the raw ore fluctuate greatly. The production process control is highly dependent on the on-site experience of the operators. To address these industrial issues, this paper, based on the general technical framework of "digital twin", introduces real-time production process data into the mechanism structure to establish a digital twin simulation model of the grinding process, achieving online prediction of key parameters in the grinding process. A set of optimization control methods for the grinding process is designed using expert system technique, including equipment safety control, process index control, and stable control of state parameters, to realize automatic adjustment of operation parameters in the grinding process. A C/S architecture is adopted to develop a digital twin industrial optimization control system for ball mills. This system has been successfully put into practice in the mineral processing plant, solving existing problems in production, realizing digitization of the grinding production process, data visualization, and intelligent operation. |
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