磨矿过程动态多目标优化方法研究及应用

磨矿过程是选前准备最后一道工序，其目的是使矿石中的有用矿物和脉石矿物或不同的有用矿物实现单体解离或者使物料的粒度满足选别作业的要求。磨矿过程的主要控制目标保证磨矿产物浓度、粒度合格，满足下一段磨矿或选别作业对此段磨矿粒度的要求，在此基础上尽可能提升处理量；同时也要保证设备安全及能耗合理。所以，磨矿过程优化控制是一个典型的多目标优化问题，针对磨矿生产过程存在多个目标问题进行研究，提出一种基于参考向量的磨矿过程动态多目标进化优化方法，首先，采用经验知识的专家系统作为参考向量，嵌入到NSGA-Ⅱ算法上，实现优化决策。然后，针对磨矿过程特点，建立生产指标正常的经验数学模型，解决目标函数难以建立的问题。针对周期改变或随机变化的实际生产工况，设计面向工艺的环境观测器，能够及时发现当前环境的变化，并合理给出新环境下磨矿过程的优化决策，实现磨矿过程多目标优化，即在磨矿产品合格前提下最大化处理量、能耗最合理。最后，设计开发控制器，在某半自磨磨矿过程成功应用，实现了磨矿产品指标的稳定、处理量的稳定以及磨矿电单耗的降低。

Research and application of dynamic multi-objective optimization method in grinding process

The grinding process is the last process of preparation before beneficiation. Its purpose is to separate the useful minerals in ore from gangue minerals or different useful minerals, or to make the particle size of materials meet the requirements of beneficiation. The main control objective of the grinding process is to ensure that the concentration and particle size of grinding products are qualified and meet the requirements of the grinding particle size of the next grinding or beneficiation operation. On this basis, the processing capacity should be increased as much as possible; At the same time, equipment safety and reasonable energy consumption shall be ensured. Therefore, the optimization control of grinding process is a typical multi-objective optimization problem. This paper studies the multi-objective problem in grinding process, a dynamic multi-objective evolutionary optimization method for grinding process based on reference vector is proposed, which can detect the change of current environment in time according to the actual production conditions with periodic change or random change, the optimization decision of grinding process under new environment is given to realize multi-objective optimization of grinding process, that is, the maximum processing capacity and the most reasonable energy consumption under the condition of qualified grinding products.