摘要
分析了基于径向基神经网络的故障诊断方法和原理,采用小波包分析对其建立频域能量特征向量,利用径向基函数神经网络完成滚动轴承故障模式的识别。试验结果表明,系统不仅能够检测到轴承故障,而且能够比较准确地识别轴承的内、外圈故障模式,可以满足工程中的需要。
The method and the theory of fault diagnosis based on the radial basis function neural network are studied. The feature vectors are established by means of wavelet packet, and then recognition of fault pattern of rolling bearing was presented using radial basis function neural network. The experimental result shows that the system can not only detect the fault of bearing but also can recognize inner or outer rings fault pattern correctly. The results are of great significance for engineering application.
出处
《轴承》
北大核心
2009年第11期35-38,共4页
Bearing
基金
湖北省襄樊市科技孵化与引导计划项目(襄科计[2008]11号/2008GG1C42)
关键词
滚动轴承
故障诊断
小波神经网络
径向基函数
rolling bearing
fault diagnosis
wavelet neural networks
radial basis function
