摘要
针对齿轮的故障诊断 ,提出了一种基于小波特征提取和BP神经网络的诊断系统 ,利用小波分解后各频段能量的分布作为特征向量输入神经网络。试验表明该方法能准确地诊断出齿轮的故障 。
Aimed at the gear fault diagnosis, a diagnosis system which based on the wavelet for picking up character and BP neural network are proposed, the energy distributing of each frequency segment which is decomposed by wavelet are treated as the eigenvector and input the NN. The testing result indicates that this method can accurately diagnose the fault of gear and has extensive application foreground.
出处
《煤矿机械》
北大核心
2004年第7期126-128,共3页
Coal Mine Machinery
关键词
小波变换
神经网络
故障诊断
wavelet transform
neural network
fault diagnosis
