铸造机械加工中频感应电炉温度优化控制  

Medium Frequency Induction Furnace Temperature Optimal Control in Casting Machining

作　　者：康俊杰[1] 崔彦军[1] 王志强[1] 范巧云[1] 

机构地区：[1]河北省科学院应用数学研究所,河北石家庄050081

出　　处：《计算机仿真》2017年第3期194-198,共5页Computer Simulation

摘　　要：针对当前中频感应电炉温度控制精度不高,自动化控制程度低,采用BP神经网络PID控制方法对中频感应电炉的温度控制进行研究,解决了炉渣对温度采集过程中温度测量不准确及温度控制品质差的问题。在MATLAB环境下进行仿真验证,仿真结果表明,上述控制器较常规PID控制器对温度的控制效果显著,缩短调节时间,减小超调,有力地改善了中频感应电炉的动态响应过程,获得比较满意的控制结果,使得在冶炼行业整体发展萎靡,企业不愿再投入大量资金更新设备的情况下,达到企业满意的控制效果,并易被各个企业接受。In view of the current medium frequency induction furnace,the control accuracy is poor and the automation control degree is low.This paper adopted the PID control combined with BP neural network to research the temperature control of medium frequency induction electric furnace,and solved the problem of inaccurate temperature measurement for the slag.Modeling and simulation based on MATLAB were carried out,and the results show that this temperature controller is more effective than conventional PID controller.At the same time,this controller shortens the adjusting time and reduces the overshoot.Therefore,this algorithm can effectively improve the dynamic response process of the medium frequency induction furnace,and obtains satisfactory control result.

关 键 词：中频感应电炉 神经网络 温度控制 超调 

分 类 号：TK183[动力工程及工程热物理—热能工程]