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现代矿业 ›› 2026, Vol. 42 ›› Issue (02): 244-249.

• 实用技术 • 上一篇    下一篇

某矿山磨矿过程智能优化控制技术研究及应用

彭 力 王小候 矣建林   

  1. 云南锡业股份有限公司大屯锡矿
  • 出版日期:2026-02-25 发布日期:2026-03-19

Research and Application of Intelligent Optimization Control Technology for Grinding Process in a Mine

  1. Datun Tin Mine,Yunnan Tin Industry Co.,Ltd.
  • Online:2026-02-25 Published:2026-03-19

摘要: 磨矿作为矿物加工的关键环节,其运行稳定性直接影响后续浮选作业的回收率与精 矿品位。针对某矿山 4 000 t/d 磨矿分级生产线存在的给矿波动大、设备效率低、能耗高等问题,开 展了磨矿过程智能优化控制技术的应用研究。通过构建“感知-决策-执行”三层闭环智能控制 系统,集成给料智能控制、磨机智能调控、分级智能管理与监控统计四大功能模块,并结合块度分 析、振动监测、浓度与粒度在线检测等硬件系统,实现了磨矿全流程的实时监测与自适应调控。系 统投运后,关键工艺参数稳定性显著提升:给矿量波动控制在±10 t/h 以内,半自磨浓度稳定在 62%±1%,浮选给矿粒度合格率提升至 90% 以上,半自磨比功耗由 5.45 kW·h/t 降至 5.33 kW·h/t,年 节电量约 15.84 万 kW·h。研究表明,该智能优化控制系统有效提升了磨矿流程的稳定性、设备利 用率和能源效率,为类似矿山磨矿流程的安全高效运行与智能化升级提供了可行的技术路径。

关键词: 磨矿, 智能控制, 浓度, 粒度 DCS

Abstract: As a key step in mineral processing,the operational stability of grinding directly affects the recovery rate and concentrate grade of subsequent flotation operations. In response to issues such as sig⁃ nificant fluctuations in ore feed,low equipment efficiency,and high energy consumption in a 4 000 t/ d grinding-classification production line in a mine,applied research on intelligent optimization control tech⁃ nology for the grinding process was conducted. By establishing a three-layer closed-loop intelligent control system of "perception-decision-execution",integrating four functional modules—intelligent feed control, intelligent mill regulation,intelligent classification management,and monitoring statistics—and combin⁃ ing hardware systems such as particle size analysis,vibration monitoring,and online detection of density and particle size,real-time monitoring and adaptive control of the entire grinding process were achieved. After the system was put into operation,the stability of key process parameters significantly improved. Ore feed fluctuations were controlled within ±10 t/h,the SAG mill density stabilized at 62%±1%,the qualified rate of flotation feed particle size increased to over 90%,and the specific power consumption of the SAG mill decreased from 5.45 kW·h/t to 5.33 kW·h/t,resulting in an annual electricity saving of approximately 158 400 kW·h. The study demonstrates that this intelligent optimization control system effectively enhanc⁃ es the stability,equipment utilization rate,and energy efficiency of the grinding process,providing a feasi⁃ ble technical pathway for the safe,efficient operation,and intelligent upgrading of similar mining grinding processes.

Key words: grinding, intelligent control, concentration, particle size, DCS