基于局部均值分解的滚动轴承故障诊断新方法

doi:10.3969/j.issn.1000-1158.2014.01.15

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摘要针对滚动轴承振动信号的非平稳特性和调制特点，提出了一种基于Wigner-Ville谱熵的特征提取新方法：运用局部均值分解算法将轴承振动信号分解为若干个乘积函数，并基于Wigner-Ville分布描述主要乘积函数分量的时频能量特征。在此基础上，结合Shannon熵构造一种新的特征提取指标—Wigner-Ville谱熵，并将其构成的特征向量输入到最小二乘支持向量机，实现了轴承不同工作状态和故障程度的自动分类与诊断。仿真和实例分析证明了方法的有效性。

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	谢平
	杨玉昕
	江国乾
	李小俚
	李兴林

关键词 ：计量学, 故障诊断, 局部均值分解, 滚动轴承, 非平稳振动信号, 调制信号

Abstract：Targeting the characteristics of non-stationary and modulating of vibration signals for roller bearings, a new method for feature extraction based on Wigner-Ville spectral entropy is proposed. Firstly, the vibration signals are decomposed by the algorithm of local mean decomposition into several product functions. Secondly, the Wigner-Ville distribution of the principal components to obtain the time-frequency energy distributions is calculated, and Shannon entropy is introduced to construct a new index for feature extraction named Wigner-Ville spectral entropy. Finally, the feature vectors based on Wigner-Ville spectral entropy were input to least squares support vector machine, in order to automatically classify and diagnose the faults and damage degree of roller bearings. Simulation and experiments demonstrate the effectiveness and intelligence of the proposed method.

Key words： Metrology; Fault diagnosis; Local mean decomposition; Roller bearings Non-stationary vibration signal; Modulating signa

基金资助:河北省自然科学基金(F2011203149)

作者简介: 谢平(1972- )，女，黑龙江齐齐哈尔人，燕山大学教授，博士生导师，研究方向为复杂系统理论、智能信号处理等。pingx@ysu.edu.cn

引用本文:

谢平，杨玉昕，江国乾,李小俚，李兴林. 基于局部均值分解的滚动轴承故障诊断新方法[J]. 计量学报, 2014, 35(1): 73-77.
XIE Ping，YANG Yu-xin，JIANG Guo-qian,LI Xiao-li，LI Xing-lin. A New Fault Diagnosis Method Based on Local Mean Decomposition for Roller Bearings. Acta Metrologica Sinica, 2014, 35(1): 73-77.

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http://jlxb.china-csm.org:81/Jwk_jlxb/CN/10.3969/j.issn.1000-1158.2014.01.15 或 http://jlxb.china-csm.org:81/Jwk_jlxb/CN/Y2014/V35/I1/73