Compound Fault Diagnosis Method Guided by Variational Mode Decomposition for Wheelsets and Bearings
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摘要:
针对列车轮对轴承系统复合故障难以辨识与诊断问题，提出一种变分模态分解（variational mode decomposition， VMD）引导的多故障特征提取匹配方法. 首先，为避免预定义模式数在运行过程中对先验知识依赖从而对诊断结果造成影响，对原始轴箱振动数据进行逐阶VMD分解，模式数为2～
N ；其次，对VMD分解获取的本征模态函数（VMD intrinsic mode functions， VIMF）进行相关峭度计算，提取相关峭度最大的VIMF；然后，将相关峭度最大的VIMF进行平方包络分析，提取故障特征频率；最后，将所提方法与快速峭度谱、相关峭度谱方法进行对比. 仿真信号和试验数据分析表明：所提方法完全规避了VMD模型中关键参数K 的选择问题，可以准确、有效地分别提取出轮对和轴承的故障特征；与快速谱峭度与相关谱峭度方法相比，获取的故障特征谐波分量在数量和信噪比上均具有明显优势.Abstract:A multi-fault feature extraction and matching method guided by variational mode decomposition (VMD) was proposed to address the difficulty in identifying and diagnosing composite faults in train wheelset bearing systems. Firstly, in order to avoid the pre-defined mode number relying on prior knowledge during operation and thus affecting the diagnosis results, the original axle-box vibration data are directly decomposed by VMD step by step, and the number of modes is 2–
N . Secondly, the VMD intrinsic mode functions (VIMF) obtained by VMD are calculated to extract the VIMF with the largest correlation kurtosis; then, the determined VIMF is analyzed by square envelope analysis to extract the fault feature frequency. Finally, the proposed method is compared with the fast spectral Kurtogram method and the correlation Kurtogram method. The analysis of simulation signals and experimental data shows that the proposed method can completely avoids the problem of selecting the key parameterK in the VMD model, and can accurately and effectively extract the fault characteristics of wheelsets and bearings, respectively. Compared with the fast spectral Kurtogram method and the correlation Kurtogram method the proposed method can diagnose compound faults effectively, and the obtained fault feature harmonic components are more advantageous in quantity and signal-to-noise ratio. -
图 3 仿真信号轴承外圈故障的VMD引导的相关峭度谱
Figure 3. VMD-guided correlation kurtosis spectrum of bearing outer-race fault for simulation signal
图 4 仿真信号轴承外圈故障VIMF平方包络谱
Figure 4. VIMF square envelope spectrum of bearing outer-race fault for simulation signal
图 5 仿真信号轮对踏面缺陷的VMD引导的相关峭度谱
Figure 5. VMD-guided correlation kurtosis spectrum of wheelset tread defect for simulation signal
图 6 仿真信号轮对踏面缺陷VIMF平方包络谱
Figure 6. VIMF square envelope spectrum of wheelset tread defect for simulation signal
图 8 仿真信号快速峭度谱最大峭度分量平方包络谱
Figure 8. Square envelope spectrum of sub-signal with maximum kurtosis for simulation signal
图 9 仿真信号轴承外圈故障的相关峭度谱
Figure 9. Correlation kurtosis spectrum of bearing outer-race fault for simulation signal
图 10 仿真信号轴承外圈故障最大相关峭度分量平方包络谱
Figure 10. Square envelope spectrum of the sub-signal with maximum correlation kurtosis of bearing outer-race fault for simulation signal
图 11 仿真信号轮对踏面缺陷的相关峭度谱
Figure 11. Correlation kurtosis spectrum of wheelset tread defect for simulation signal
图 12 仿真信号轮对踏面缺陷最大相关峭度分量平方包络谱
Figure 12. Square envelope spectrum of the sub-signal with maximum fast kurtosis of wheelset tread defect for simulation signal
图 16 试验信号轴承外圈故障的VMD引导相关峭度谱
Figure 16. VMD-guided correlation kurtosis of bearing outer-race fault for measured signal
图 17 试验信号轴承外圈故障VIMF波形及其平方包络谱
Figure 17. VIMF waveform and its square envelope spectrum of bearing outer-race fault for measured signal
图 18 试验信号轮对踏面缺陷的VMD引导相关峭度谱
Figure 18. VDM-guided correlation kurtosis spectrum of wheelset tread defect for measured signal
图 19 试验信号轮对踏面缺陷VIMF波形及其平方包络谱
Figure 19. VIMF waveform and its square envelope spectrum of wheelset tread defect for measured signal
图 21 试验信号最大峭度分量平方包络谱
Figure 21. Square envelope spectrum of the sub-signal with maximum kurtosis for measured signal
图 22 试验轴承外圈故障的相关峭度谱
Figure 22. Correlation kurtosis of bearing outer-race fault for measured signal
图 23 试验信号轴承外圈故障最大相关峭度分量平方包络谱
Figure 23. Square envelope spectrum of sub-signal with maximum fast kurtosis of bearing outer-race fault for measured signal
图 24 试验信号轮对踏面缺陷的相关峭度谱
Figure 24. Correlation kurtosis spectrum of wheelset tread defect for measured signal
图 25 试验信号轮对踏面缺陷最大相关峭度分量平方包络谱
Figure 25. Square envelope spectrum of the sub-signal with maximum fast kurtosis of wheelset tread defect formeasured signal
表 1 仿真信号参数设置
Table 1. Parameter description of simulation signals
类型 振幅 结构阻尼系数 激振 周期 随机系数 轴承 1 1000 3500 1/83.3 0.01Tb 轮对故障 8 2000 1000 1/10.29 0.01Tw 随机冲击响应 10 1000 2000 
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