基于自适应小波网络的汽轮发电机组振动故障诊断方法的研究  

Study of Method on Adaptive Wavelets Network for Vibration Fault Diagnosis of Steam Turbine-Generation Set

作　　者：李化[1] 孙才新[1] 胡雪松[1] 岳刚 唐能凡 王肯 

机构地区：[1]重庆大学电气工程学院,400044 [2]重庆发电厂

出　　处：《电工技术学报》2000年第3期57-60,共4页Transactions of China Electrotechnical Society

摘　　要：基于自适应小波网络理论，构造了一个应用于汽轮发电机组振动故障诊断与识别的自适应小波网络分类器。仿真结果表明，该方法具有良好的诊断性能，且收敛速度快，是一种有效的诊断方法。同时对该网络的分类性能进行了分析，得出了一些具有实际价值的结论。An adaptive wavelet network classifier for vibration fault diagnosis of steam turbinegeneration is proposed based on theory of adaptive wavelet neteoth (AWN). The results of simulation showtha this method has better diagnostic, faster speed of learning properties and it is an efficient method. Andthen som important related elements which affect the classified performance of AWN are analyzed, conclusionswhich are of great importance in real application are obtained.

关 键 词：自适应小波网络 汽轮发电机组 故障诊断 振动 

分 类 号：TM311.071[电气工程—电机]