基于小波极限学习机的分解炉温控系统建模  

Wavelet Elm Model of Temperature Control System For Decompsing Furnace

作　　者：董燕[1] 牛鑫[2] 朱永胜[1] 毕浩洋[3] 

机构地区：[1]中原工学院,郑州450007 [2]济源职业技术学院,河南济源459000 [3]郑州大学,郑州450001

出　　处：《中原工学院学报》2013年第2期1-4,13,共5页Journal of Zhongyuan University of Technology

基　　金：国家自然科学基金项目(61071175)

摘　　要：在新型干法水泥生产过程中,分解炉温度是一个非常重要的控制对象.由于分解炉出口温度与其影响因素不是简单的线性或者非线性关系,使得传统的建模方法精度较低.本文提出一种基于小波极限学习机的方法,通过对已有的大量数据进行训练、测试,实现对水泥窑分解炉温度的建模.实验结果表明,该方法泛化性能好、学习速度快、模型精度高,具有一定的实践指导意义.In new dry cement production process, the decomposing furnace temperature is a very important control object. Due to the decomposing furnace outlet temperature and its influencing factors is a not simple linear or non-linear relationship, the traditional modeling methods have low accuracy. This paper presents a method based on wavelet Extreme Learning Machine to realize modeling of temperature control system for decomposing furnace through training and testing by existing large amounts of data. The experimental results show that this method has better generalization performance, faster learning speed and high model accuracy, which have a certain practical significance.

关 键 词：分解炉 小波极限学习机 建模 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]