一种基于规则推理的电熔镁炉智能控制系统

传统的电熔镁炉熔炼过程人工控制方法存在生产过程中能源消耗大、产品品位低、工人劳动强度高等不足.针对上述情况,提出了利用工业现场人工操作经验总结出的控制规则与相关控制理论相结合对电熔镁炉熔炼过程进行自动控制的方法,并使用该方法设计了一种基于规则推理的电熔镁炉智能控制系统,包括电流预设定模型、电流偏差阈值自学习模型和电流平衡调节补偿模型等协调控制电动机.该系统成功应用于国内某电熔镁砂厂,取得了良好的应用效果.

Intelligent Control System of Fused Magnesia Production via Rule-Based Reasoning

Traditional manual process control of electric furnace smelting of magnesia has such disadvantages as high energy consumtion, poor-quality products and high labor intensity. To solve those problems, an auto-control method was proposed for the smelting process through combining the control rules which were summed up from operational experience acquired in monual control process with relevant control theory. Then, based on this method and rule-based reasoning, an intelligent control system was designed for the electric furnace smelting of magnesia, involving some models developed for current presetting, regulation/compensation for current unbalance and self-learning of current deviation threshold, as well as the recognizer of working conditions and electrode lifting controller. The intelligent control system has been introduced in a domestic magnesia smeltery with successful results obtained in application.