Wavelet Neural Network Based Fault Diagnosis of Asynchronous Motor

摘要：

According to asynchronous motors complex fault characteristics, and the combination of wavelet transform technique, an improved wavelet neural network for fault diagnosis of asynchronous motor is proposed in this paper. Taking Wavelet transform technique as wavelet neural network(WNN) the input vector of picking up asynchronous motors the characteristic signal, and wavelet neural network algorithm is ptimized, The self-adaptive wavelet neural network algorithm about adjusting momentum vector alter-learning rate is proposed and given the momentum coefficient and alter-learning rate adjustment method. Through the actual testified results show that the method is effective and feasible, and has a better diagnostic accuracy, fast and generalized performances.

关键词： Asynchronous motor Wavelet neural network Fault diagnosis Wavelet transformation

作者: Bo Hu Wen-hua Tao Bo Cui Yi-tong Bai Xu Yin

作者单位: School of Information & Control Engineering,Liaoning Shihua University ,Fushun Liaoning Province 113001,China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3260-3263

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）