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现代矿业 ›› 2025, Vol. 41 ›› Issue (10): 217-222,227.

• 实用技术 • 上一篇    下一篇

球磨机数字孪生监测系统开发及应用

张正飞1 王雪峰1 俞进发1 黄金武1 王彬杰1 宋 涛2 刘道喜2   

  1. 1. 江西铜业股份有限公司德兴铜矿;2. 矿冶科技集团有限公司
  • 出版日期:2025-10-25 发布日期:2025-12-08

Development and Application of Digital Twin Monitoring System for Ball Mill

  1. 1. Dexing Copper Mine,Jiangxi Copper Co. Ltd.;2. BGRIMM Technology Group
  • Online:2025-10-25 Published:2025-12-08

摘要: 德兴铜矿大山选矿厂矿石性质波动频繁,人工操作无法有效识别工况变化,导致磨 矿过程波动大,生产控制难度大。针对现场磨矿过程中关键参数难以直接测量、传统仿真系统缺 乏动态实时数据支撑等问题,通过建模仿真和数字孪生技术,开发了一套球磨机数字孪生监测系 统。系统可以进行球磨机运动轨迹机理模型研究分析,开展动态轨迹研究,结合磨矿过程生产实 际,选择自组织映射神经网络(SOM)的筒体内部混合充填率分类方法,实现混合充填率这一动态 参数分类识别,进而实现钢球运动轨迹动态计算,最后,设计开发球磨机数字孪生监控系统,实现 球磨机三维模型建模及驱动,工艺流程仿真以及过程数据监控。工业应用结果表明,系统能够有 效识别混合充填率状态,提升磨矿产品粒度预测精度,为球磨机的智能化运行与优化控制提供了 可靠的技术支撑。

关键词: 球磨机, 数字孪生, SOM, 三维可视化

Abstract: The ore properties of Dashan Concentrator of Dexing Copper Mine fluctuate frequently,and manual operation cannot effectively identify the changes of working conditions,resulting in large fluctua⁃ tions in the grinding process and difficult production control. Aiming at the problems that the key parameters in the field grinding process are difficult to measure directly and the traditional simulation system lacks dy⁃ namic real-time data support,a set of digital twin monitoring system for ball mill is developed through mod⁃ eling simulation and digital twin technology. The system can carry out research and analysis on the mecha⁃ nism model of ball mill motion trajectory and carry out dynamic trajectory research. Combined with the actu⁃ al production of grinding process,the self-organizing mapping neural network (SOM) classification method of mixed filling rate inside the cylinder is selected to realize the dynamic parameter classification and recog⁃ nition of mixed filling rate,so as to realize the dynamic calculation of steel ball motion trajectory. Finally, the digital twin monitoring system of ball mill is designed and developed to realize the three-dimensional model modeling and driving of ball mill,process flow simulation and process data monitoring. The industrial application results show that the system can effectively identify the state of mixed filling rate,improve the prediction accuracy of particle size of grinding products,and provide reliable technical support for the intel⁃ ligent operation and optimal control of ball mill.

Key words: ball mill, digital twin, SOM, 3D visualization