Application of Improved EWT Method in Bearing Fault Diagnosis of High-speed Train

Yuting LIU; Jianhui LIN

doi:10.13890/j.issn.1000-128x.2020.04.010

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Application of Improved EWT Method in Bearing Fault Diagnosis of High-speed Train

Test & Detection Technology | 更新时间：2021-12-10

- Application of Improved EWT Method in Bearing Fault Diagnosis of High-speed Train
- Electric Drive for Locomotives Issue 4, Pages: 47-53(2020)
- 作者机构：
  
  1.西南交通大学　牵引动力国家重点实验室，四川　成都　610031
- 作者简介：
- 基金信息：
- DOI：10.13890/j.issn.1000-128x.2020.04.010
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Yuting LIU, Jianhui LIN. Application of Improved EWT Method in Bearing Fault Diagnosis of High-speed Train. [J]. Electric Drive for Locomotives (4):47-53(2020)
DOI：

Yuting LIU, Jianhui LIN. Application of Improved EWT Method in Bearing Fault Diagnosis of High-speed Train. [J]. Electric Drive for Locomotives (4):47-53(2020) DOI： 10.13890/j.issn.1000-128x.2020.04.010.

摘要

高速列车轴承的故障特征提取较为困难，针对这一问题，在经验小波变换（Empirical Wavelet Transform，EWT）的基础上，提出了一种基于频谱趋势与频带合并的改进EWT方法，并将其应用于高速列车轴承的故障诊断。该方法首先利用经验模态分解，根据IMF分量判断准则，提取故障信号的频谱趋势，从而得到初始的频谱分界点；然后计算各初始频带的故障信息判断指标，得到自适应阈值，判断初始频带的有效性，通过对无效频带的合并完成频谱的重新划分；最后进行经验小波变换，将各频带通过正交滤波器组，对得到的各分量信号进行Hilbert变换，得到轴承的故障特征频率。通过仿真和试验验证，改进后的EWT方法可以准确地提取出轴承故障特征频率的基频和倍频成分，有效地确定轴承故障。

Abstract

It is difficult to extract fault features of axle box bearings of high-speed train. To solve this problem, an improved empirical wavelet transform based on spectrum trend and frequency band combination was proposed and applied to the fault diagnosis of high-speed train bearings. Firstly, by using empirical mode decomposition, the spectrum trend of the fault signal according to the IMF component judgment criterion was extracted, and the initial spectrum boundary point was obtained. Then, the fault information judgment index of each initial frequency band was calculated, and the adaptive threshold was obtained to determine the initial frequency band, the validity of the spectrum was re-divided by combining the invalid frequency bands. Finally, the empirical wavelet transform was carried out to pass each frequency band through the orthogonal filter bank, and the obtained component signals were subjected to Hilbert transform to obtain the fault characteristic frequency of the bearing. Through simulation and experimental verification, the improved EWT method could accurately extract the fundamental frequency and frequency doubling component of the bearing fault characteristic frequency, and effectively determine the bearing fault.

关键词

高速列车经验小波变换频谱趋势Hilbert变换故障诊断滚动轴承仿真

Keywords

high-speed trainEWTspectrum envelopeHilbert transformfault diagnosisrolling bearingsimulation

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