基于数据驱动的重介质选煤过程自适应优化研究

Study on Dense Medium Coal Preparation Process Based on Data Driven and Adaptive Optimization

重介质选煤过程时变性巨大,非线性强,干扰因素多,不考虑实际因素影响的控制系统难以满足使用需求。通过了解重介质选煤过程的工艺流程,对重介质选煤过程的动态特性进行分析,并将悬浮液密度以及灰分作为优化目标,阐述了基于数据驱动的自适应优化方法在重介质选煤过程中的应用原理。仿真结果显示,基于数据驱动的选煤自适应优化方法可以较好地实现对悬浮液密度以及灰分的跟踪,可满足使用需求。

The heavy medium coal preparation process has huge time variation,strong nonlinearity and many interference factors.The control system that does not consider the influence of actual factors is difficult to meet the demand.The dynamic characteristics of the dense medium coal preparation process is analyzed by understanding the process flow of the dense medium coal preparation process,and the suspension density and ash content are taken as the optimization objectives,and expounds the application principle of the data driven adaptive optimization method in the dense medium coal preparation process.The simulation results show that the coal preparation adaptive optimization method based on data-driven can better achieve the tracking of suspension density and ash content,which can meet the use requirements.