基于智能技术的温度测量系统的设计

钢水温度是炼钢过程的重要控制指标。目前由于钢水温度过高和钢液、钢渣对测温枪的腐蚀,现有的测量温度的方法无法得到钢水温度的连续变化的信息。针对这种情况,介绍了基于智能技术的钢水温度的软测量方法。应用人工神经元网络BP算法对钢水温度进行初步预报,再根据专家系统知识对一些特殊的情况进行修正,从而获得良好的效果。运行结果表明:采用该测量方法,钢水温度预报的适应性和准确性都得到了显著提高,并且该方法在安全性、操作控制及经济效益等方面具有很大的优越性,具有广阔的发展前景。

Design of Temperature Measurement System Based on Intelligent Technology

The molten steel temperature is an important processing target for steel-making.Because of high temperature and strong erosion from steel and slag at present,the continuous steel temperature information can not be obtained by existing measurement method.In view of this kind of situation,The soft measuring technique of the molten steel temperature based on the intelligent technology is introduced.The artificial neural network model is used to predict the initial temperature trend,and then an expert system is used to compensate the error caused in special conditions.The movement result indicated that the adaptation and accuracy of the steel temperature prediction have been improved,and the measure has the advantages of soft measurement method in safety,operation control and economy benefit,which demonstrates the system possesses a very extensive protect.