现代制造工程Issue(7)：127-131,5.
小波包和改进 Elm an 神经网络相融合的异步电动机滚动轴承的故障诊断
Fault diagnosis of asynchronous motor rolling bearing based on synergetic wavelet packet and Elman neural network
摘要
Abstract
As for the limitations of the single signal processing method is not easy to accurately diagnose fault of asynchronous mo -tor rolling bearing ,the diagnosis method of the wavelet packet and improved Elman neural network are fused is proposed .The ac-quisition data of four different fault signals are denoised ,decomposed and reconstructed using the wavelet packet ,the energy char-acteristics of different fault types is extracted in effect .By introducing the βof a feedback factor build neural network of improved Elman.Experimental results show that both of improved and unimproved Elman neural network can realize the fault diagnosis of a -synchronous motor rolling bearing ,but as for the diagnosis time and accuracy ,the latter is better than the former in the diagnostic efficiency and accuracy .关键词
小波包/改进Elman神经网络/滚动轴承/故障诊断Key words
wavelet packet/improved Elman neural network/rolling bearing/fault diagnosis分类
信息技术与安全科学引用本文复制引用
黄丽霞,肖顺根,宋萌萌..小波包和改进 Elm an 神经网络相融合的异步电动机滚动轴承的故障诊断[J].现代制造工程,2014,(7):127-131,5.基金项目
宁德市科技计划项目（20110112）；宁德师范学院服务海西建设项目（2012H408）；宁德师范学院专项课题项目 （）
