A Wavelet and Neural Networks Based on Fault Diagnosis for HAGC System of Strip Rolling Mill  

作　　者：LI Guo you DONG Min 

机构地区：[1]Key Laboratory of InduslriaI Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, Hebei, China [2]College of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China

出　　处：《Journal of Iron and Steel Research International》2011年第1期31-35,共5页

基　　金：Item Sponsored by National Natural Science Foundation of China(50375135);Provincial Natural Science Foundation of Hebei Province of China(E2005000323)

摘　　要：The fault diagnosis of HAGC （Hydraulic Gauge Control） system of strip rolling mill is researched. Taking the advantage of the accompanying characteristics of the closed loop control system, rolling force forecasting model is built based on neural networks. The comparison results of the prediction and the actual signal are taken as residual signals. Wavelet transform is used to obtain the components of high and low frequency of the residual signal. Wave let decomposition results make fault feature clear and time-domain positioning accurately. Fault numerical criterion is established through Lipschitz exponent. By analyzing the varied fault features which correspond to varied fault rea sons, the fault diagnosis of HAGC system is implemented successfully.The fault diagnosis of HAGC （Hydraulic Gauge Control） system of strip rolling mill is researched. Taking the advantage of the accompanying characteristics of the closed loop control system, rolling force forecasting model is built based on neural networks. The comparison results of the prediction and the actual signal are taken as residual signals. Wavelet transform is used to obtain the components of high and low frequency of the residual signal. Wave let decomposition results make fault feature clear and time-domain positioning accurately. Fault numerical criterion is established through Lipschitz exponent. By analyzing the varied fault features which correspond to varied fault rea sons, the fault diagnosis of HAGC system is implemented successfully.

关 键 词：HAGC fault diagnosis neural network wavelet transform 

分 类 号：TG333.72[金属学及工艺—金属压力加工] TP18[自动化与计算机技术—控制理论与控制工程]