摘要:
基于传统控制方法的重介质选煤过程自动控制存在能耗高、灰分含量波动大等问题，而先进控制能够改善过程动态性能，使系统运行接近最优状态。首先介绍了重介质选煤工艺流程，分析了重介质选煤过程的多时间尺度、多速率特性，并基于重介质选煤过程强非线性、多变量耦合、时变性、多干扰等因素，分析了重介质选煤过程先进控制在数学建模、运行指标跟踪控制、稳定性、关键参量精确感知等方面的难点；然后从重介质选煤过程建模、重介质悬浮液密度控制、精煤灰分控制等方面，综述了重介质选煤过程先进控制的研究进展；最后展望了重介质选煤过程先进控制未来的研究方向：基于大数据的重介质选煤可视化平台建设,面向重介质选煤过程的知识和数据混合驱动的智能优化与控制,产品质量与效率预测方法研究,重介质选煤虚拟实验平台搭建。
Abstract:
Automatic control of dense medium coal separation process based on traditional control methods has problems of high energy consumption, large fluctuation of ash content and so on, while advanced control can improve dynamic performances of the process and make the system run close to the optimal state. Firstly, dense medium coal separation technology is introduced with characteristics analysis of multi-time scales and multi-rate. Based on factor analysis of strong nonlinearity, multi-variable coupling, time variant and multi-interference in dense medium coal separation process, difficulties of advanced control of dense medium coal separation process are analyzed, which are about mathematical modeling, tracking control of operation indexes, stability and accurate perception of key parameters. Secondly, research progresses of advanced control of dense medium coal separation process are summarized in terms of process modeling, density control of dense medium suspension and ash content control of clean coal. Finally, prospects about future research directions of advanced control of dense medium coal separation process are made, which involve visualization platform construction of dense medium coal separation based on big data, prior knowledge and data hybrid driven intelligent optimization and control orienting dense medium coal separation process, research on prediction methods of product quality and efficiency, and virtual experimental platform construction of dense medium coal separation.
百度学术
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