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盲VMD-Cepstral在轴承故障诊断中的应用
引用本文:柏林,唐智,徐冠基.盲VMD-Cepstral在轴承故障诊断中的应用[J].振动.测试与诊断,2018,38(3):597-602.
作者姓名:柏林  唐智  徐冠基
作者单位:重庆大学机械传动国家重点实验室
基金项目:国家自然科学基金资助项目 (51475052,51675064);中央高校基本科研业务费资助项目(106112016CDJZR115502)
摘    要:针对滚动轴承早期故障诊断困难的问题,从经验模态分解(empirical mode decomposition,简称EMD)以及包络谱出发,为解决EMD抗噪效果较差、具有端点效应等局限性,提出了盲变分模态分解(variational modal decomposition,简称VMD)-主成分分析(principal component analysis,简称PCA)-包络谱熵结合倒谱包络的轴承故障诊断方法。首先,对滚动轴承的振动信号进行了变分模态分解;其次,对分解得到的分量进行PCA去相关处理;然后,对分量计算包络谱熵,选择熵值小于其平均值的分量进行信号重构;最后,对重构的信号进行倒谱包络分析。实验结果表明,该方法能有效地提取出滚动轴承的故障频率,从而判断出滚动轴承的损伤位置,并且具有良好的抗噪能力。

关 键 词:变分模态分解    主成分分析    包络谱熵  倒谱包络

Bearing Fault Diagnosis Based on Variational Modal Decomposition Combined with Envelope of Spectrum
BO Lin,TANG Zhi,XU Guanji.Bearing Fault Diagnosis Based on Variational Modal Decomposition Combined with Envelope of Spectrum[J].Journal of Vibration,Measurement & Diagnosis,2018,38(3):597-602.
Authors:BO Lin  TANG Zhi  XU Guanji
Affiliation:(The State Key Laboratory of Mechanical Transmission, Chongqing University Chongqing, 400044, China)
Abstract:Aiming at the problem of early fault diagnosis of rolling bearing, it is pointed out that the empirical mode decomposition (EMD) has poor anti-noise effect and the limitation of end effect. Variational modal decomposition (VMD), principal component analysis (PCA) and entropy bearing fault diagnosis are put forward based on cepstral envelope. Firstly, it takes VMD to decompose the bearing vibration signal of rolling; secondly, the components are handled by PCA. Then, it computes the entropy of the components and choses whose entropy of components is less than the average to reconstruct. Finally, the reconstructed signal is analyzed by cepstral envelope. Experimental results show that the method can effectively extract the rolling bearing fault frequencies, and judge damage position of the rolling bearing, it has a good anti-noise ability.
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