矿山生产过程时变计算实验及精准执行方法
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1. 榆林学院 信息工程学院,陕西 榆林 719000;2. 洛阳栾川钼业集团股份有限公司 博士后工作站, 河南 栾川 471500;3. 西安建筑科技大学 资源工程学院,西安 710055

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E-mail: fanston@126.com.

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TD80

基金项目:

国家自然科学基金项目(51864046);中国博士后科学基金项目(2019M662505);榆林市科技计划项目(CXY-2020-007-02);榆林市高新区科技计划项目(CXY-2020-37).


Time varying computation experiment and precise control method for mine production process
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Affiliation:

1. School of Information Engineering,Yulin University,Yulin 719000,China;2. Postdoctoral Workstation,Luoyang Luanchuan Molydbenum Industry Group Inc.,Luanchuan 471500,China;3. School of Resources Engineering,Xián University of Architecture and Technology,Xián 710055,China

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    摘要:

    在复杂多变的矿山开采环境下,计划难以执行等问题较为突出,如计划方案不可行、工序流程欠合理,且突发事件频繁,该问题已成为长期以来矿山企业面临的关键困难之一.为此,提出“先时变计算实验再精准过程执行”的智能开采新范式.首先,根据基本需求初始化生产计划方案;其次,对计划方案进行时变计算实验,即借助多代理方法构建基于计算机的人工系统,利用各简单代理自主推演和互动涌现进行计算实验或试验,评估方案的合理性和可靠性,预测生产现场人员、设备、环境的属性状态和整体系统的经济、空间及安全状态,根据实验结果调整方案后再次实验,直到具有稳定的实验结果为止;最后,以优化后的最优方案和工序流程进行现场执行,同时对执行过程进行实时感知、分析及纠正,实现按计划控制.在物联网数据驱动下,这种低成本、高效率、零风险和快速的事前预演手段及精准过程控制方法,对于辅助计划制定及安全高效生产意义重大.

    Abstract:

    In the complex mining environment, it is difficult to implement the plan, for example, the production plan is not feasible or the process flow is not reasonable, and the unexpected events occur frequently, which is one of the key difficulties faced by mining enterprises for a long time. Therefore, a new intelligent mining paradigm of “first virtual experiment then precise implementation” is proposed. Firstly, the production plan is initialized according to the basic needs. Then, the time-varying computation experiment is carried out, which is to build a computer-based artificial system with a multi-agent method. The computing experiments are carried out with the independent deduction of each simple agent and the emergence of multi-agent interaction based on subscription awareness, so as to evaluate the rationality and reliability of the scheme. According to the experimental results, the scheme is adjusted and the experiments are carried out again until the expected results are stable. Finally, the optimized scheme and process flow are used for on-site execution. At the same time, the real-time perception, simulation and correction of the execution process are carried out to achieve the planned control. Driven by the Internet of things data, this low-cost, high-efficiency, zero risk and fast-speed preview method and precise process control method are of great significance for planning and safe-efficient production.

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引用本文

冯治东,井石滚.矿山生产过程时变计算实验及精准执行方法[J].控制与决策,2022,37(5):1241-1250

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  • 在线发布日期: 2022-03-30
  • 出版日期: 2022-05-20
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