基于经验模态分解的轴承故障诊断

作者：王焱，朱善安 日期：2007-10-25/span> 浏览：4079 查看PDF文档

基于经验模态分解的轴承故障诊断

王焱，朱善安
（浙江大学 电气工程学院，浙江 杭州 310027）

摘要：简要介绍了轴承故障诊断的基本方法，通过对比共振解调法和经验模态分解法，证明了经验模态分解是一种适用于分析非线性、非平稳信号的方法。同时，通过实际例子验证了该方法可以用于有效地发现轴承故障，从而提高了诊断的准确性。
关键词：经验模态分解；故障诊断；非平稳；轴承
中图分类号：TH115文献标识码：A文章编号：1001-4551(2007)10-0077-03

Bearing fault diagnosis based on EMD
WANG Yan, ZHU Shanan
(College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)
Abstract: The basic methods of bearing fault diagnosis were introduced. The empirical mode decomposition method is applicable to analyze nonlinear and nonstationary signals in comparison with resonance demodulation methods, which is proved to be effective on fault diagnosis and can improve the accuracy of diagnosis.
Key words: empirical mode decomposition (EMD); fault diagnosis; nonstationary; bearing