Fault diagnosis for rolling bearing of Urban Trnsit trains based on EMD and envelope spectrum
-
摘要: 为了准确识别城轨列车滚动轴承故障类型，研究了一种基于经验模态分解（EMD，Empirical Mode Decomposition）和包络分析的滚动轴承故障诊断方法。对滚动轴承的振动信号进行EMD分解，得到若干个本征模态函数（IMF，Intrinsic Mode Function）之和，对包含主要信息成分的IMF分量作包络分析，根据包络谱的故障特征频率判断滚动轴承故障类型。实验结果表明，该方法能够准确有效地识别城轨列车滚动轴承的故障类型。Abstract: Aiming at the problem of fault diagnosis for rolling bearing of Urban Transit trains, a method combined empirical mode decomposition (EMD) with envelope spectrum was researched on the basis of roller bearing vibration signals. Rolling bearing vibration signals were decomposed into a finite number of intrinsic mode functions(IMFs) by using EMD. Envelope spectrum was used to calculate some IMFs including the main information. Fault pattern was determined by contrast with characteristic defect frequencies of rolling bearing. The experiment result indicated that the fault pattern of rolling bearing could be identified effectively by the researched method.
-
Key words:
- rolling bearing /
- fault diagnosis /
- EMD /
- envelope spectrum
-
[1] Djebala A, Babouri M K, Ouelaa N. Rolling bearing fault detection using a hybrid method based on Empirical Mode Decomposition and optimized wavelet multi-resolution analysis[J]. The International Journal of Advanced Manufacturing Technology, 2015, 79(9-12): 2093-2105. [2] Žvokelj M, Zupan S, Prebil I. EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis[J].Journal of Sound and Vibration, 2016(370): 394-423. [3] Golafshan R, Sanliturk K Y. SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults[J]. Mechanical Systems and Signal Processing, 2016(70): 36-50. [4] 何广坚，邢宗义，左 成，等 . 基于 EMD 与 SVM 的城轨列车滚动轴承故障诊断方法研究 [J]. 铁路计算机应用，2015，24（8）：1-4，15. [5] 潘丽莎，陈 皓，秦 勇，等 . 基于小波包和 RBF 神经网络的轨道车辆滚动轴承故障诊断 [J]. 铁路计算机应用，2012，21（7）：8-11. [6] HUANG N E, SHEN Z, LONG S R. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Nonstationary Time Series Analysis[J]. The Royal Society A: Mathematical, Physical & Engineering Sciences, 1998(3): 903-995. [7] 王 婷 . EMD 算法研究及其在信号去噪中的应用 [D]. 哈尔滨 ：哈尔滨工程大学，2010. [8] 李 智，陈祥初，刘政波 . 包络分析及其在设备故障诊断中的应用 [J]. 测试技术学报，2002（2）：92-95. [9] Feng G J, Gu J, Zhen D, et al. Implementation of envelope analysis on a wireless condition monitoring system for bearing fault diagnosis[J]. International Journal of Automation and Computing, 2015, 12(1): 14-24. [10] 刘建强，赵治博，章国平，等 . 地铁车辆转向架轴承故障诊断方法研究 [J]. 铁道学报，2015（1）：30-36.
点击查看大图
下载:
