阳极焙烧中温度的软测量  

Temperature soft sensor method in anode baking

作　　者：张耿[1] 苗丽[1] 孙振伟[1] 

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050

出　　处：《微计算机信息》2008年第4期292-293,共2页Control & Automation

基　　金：国家科技攻关计划项目(2002BA901A28);甘肃省省长基金(GS015-A52-012)资助项目

摘　　要：本文利用模糊聚类的神经网络方法,采用数据分组训练、自动确定模糊分类线、在线测量时分类中心自适应修正,降低了计算量,提高了温度精度,将该算法用于阳极焙烧中温度预报的仿真,仿真实验以已有的焙烧炉温度场模型为基础,仿真结果表明该方法能够解决阳极焙烧温度难以在线测量的问题。A neural network soft sensor modeling method based on fuzzy clustering is used. The training data set is separated into several clusters with different centers, the number of fuzzy cluster is decided automatically, and the clustering centers are modified using an adaptive fuzzy clustering algorithm in the online stage. This method can reduce the calculation remarkably and has good temperature prediction accuracy. The proposed method has been applied to the temperature estimation in an anode baking. Simulati...

关 键 词：软测量 神经网络 模糊聚类 阳极焙烧 温度控制 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]