智能磨矿系统半自磨机控制关键参数研究
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中国恩菲工程技术有限公司, 北京 100038

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何荣权(1980—),男,湖南道县人,硕士,正高级工程师,主要从事选矿工程咨询、设计、项目管理及科研工作。

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TD921+.4

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Research on the Key Control Parameters of Intelligent Grinding System
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    摘要:

    以某选矿厂半自磨工艺智能磨矿系统生产实践为基础,总结分析了智能磨矿系统半自磨机重要控制参数的影响和运行情况。通过分析生产实践数据发现,智能磨矿系统的关键控制参数为半自磨机转速、给矿粒度、半自磨机磨矿浓度。半自磨机转速对智能磨矿系统的控制最敏感,调节效果最显著,可快速调整磨矿系统运行状态;给矿粒度次之,能起到短时调节作用;半自磨机磨矿浓度敏感性最弱,可实现微调。通过上述关键参数的协同控制,能实现磨矿系统处理能力最大化,产品粒度可调可控。

    Abstract:

    Based on the production practice of intelligent grinding system of semi-automatic grinding process in a concentrator, the effect of important control parameters and operation conditions of semi-autogenous mill of intelligent grinding system were summarized and analyzed. Through the analysis of production practice data, it is found that the key control parameters of the intelligent grinding system are semi-autogenous mill speed, feeding size and grinding concentration. The speed of semi-autogenous mill is the most sensitive parameter to the control of intelligent grinding system, and the regulation effect is the most significant. It can quickly adjust the operation state of grinding system. The feeding particle size takes the second place, which can play a short-term adjustment role;the grinding concentration has the weakest sensitivity and can achieve fine adjustment. Through the collaborative control of the above key parameters, the processing capacity of the grinding system can be maximized, and the product size can be adjusted and controlled.

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何荣权,尤腾胜,邓朝安.智能磨矿系统半自磨机控制关键参数研究[J].绿色矿冶,2023,39(1):17-20.

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  • 收稿日期:2022-12-20
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  • 在线发布日期: 2025-11-17
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