摘要
采用能量分布特征提取方法和优化 BP算法 ,提出了一种基于小波变换和 BP神经网络的故障诊断系统。利用该系统对汽车变速箱三挡齿轮磨损程度进行估计 ,诊断结果与实际完全吻合 ,表明该小波神经网络故障诊断系统的有效性。由于小波分析特别适用于非平稳信号的处理 。
Vibration signals of a machine are proved to be non stationary ones. They usually carry the dynamic information of a machine and are very useful for fault diagnosis. The wavelet analysis is especially suitable for a non stationary signal processing and the artificial neural network is a very good tool for signal identification. In this paper, a new efficient fault diagnosis system based on the wavelet transform and the artificial neural networks was presented, the theoretical background of wavelet transform was given, and a much better BP algorithm based on the traditional BP algorithm was introduced. Accordingly, a new wavelet neural networks fault diagnosis system was developed. The proposed fault diagnosis system was tested on a gear wear estimation of gearbox. The results showed that the developed system was effective.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2002年第1期73-76,共4页
Transactions of the Chinese Society for Agricultural Machinery
基金
机械工业技术发展基金资助项目 (项目编号 :97JA0 10 4)
