基于奇异值分解和变分模态分解的轴承故障特征提取

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振动与冲击 ›› 2016, Vol. 35 ›› Issue (22) : 183-188.

论文

赵洪山 1，郭双伟 1，高夺 1

作者信息 +

Singular Value Decomposition and Variational Modal Decomposition Based Fault Feature Extraction of Bearing Fault

Zhao Hongshan 1 Guoshuangwei 1 Gaoduo 1

Author information +

文章历史 +

摘要

为了有效提取轴承故障，提出了基于变分模态分解和奇异值分解降噪的故障特征提取方法。通过对故障信号进行变分模态分解，获得其本征模态函数。基于峭度指标，选择包含故障信息的本征模态函数进行信号重构。利用奇异值分解降噪技术对重构信号进行处理，提高信噪比。最后对降噪信号进行包络解调提取故障特征频率。与常见的故障特征提取方法相比，该方法能有效辨别滚动轴承的典型故障，突出故障特征，提高滚动轴承的故障诊断效果。

Abstract

In order to extract fault features of rolling bearing effectively, a method which is based on variational mode decomposition and singular value decomposition was proposed. The Intrinsic Mode Function (IMF) is obtained by variational mode decomposition. The IMF containing fault information was selected to reconstructed based on the kurtosis. Singular value decomposition was used to reduce noise and increase signal-to-noise. Then the fault feature was extracted by envelope spectrum analysis. Compared with common fault feature extraction method, the proposed method can distinguish typical faults , highlight fault features and improve the diagnostic effect.

导出引用

赵洪山 1，郭双伟 1，高夺 1. 基于奇异值分解和变分模态分解的轴承故障特征提取[J]. 振动与冲击, 2016, 35(22): 183-188

Zhao Hongshan 1 Guoshuangwei 1 Gaoduo 1 . Singular Value Decomposition and Variational Modal Decomposition Based Fault Feature Extraction of Bearing Fault[J]. Journal of Vibration and Shock, 2016, 35(22): 183-188

参考文献

[1] 陈雪峰，李继猛，程航，等. 风力发电机状态监测和故障诊断技术的研究与进展[J].机械工程学报,2011，47(9)：45-52．
CHEN Xue-fen，LI Ji-meng，CHENG Hang， et al．Research and application of condition monitoring and fault diagnosis technology in wind turbines [J]．Power System Technology，2011，47(9)：18-22．
[2] 周智，朱永生，张优云，等. 基于EEMD和共振解调的滚动轴承自适应故障诊断[J]. 振动与冲击,2013，32(2)：76-80.
ZHOU Zhi，ZHU Yong-sheng，ZHANG You-yun，et al．Adaptive fault diagnosis of rolling bearings based on EEMD and demodulated resonance [J]．Journal of Vibration and Shock，2013，32(2)：76-80．
[3] 张家凡，易启伟，李季．复解析小波变换与振动信号包络解调分析[J]. 振动与冲击,2010，29(9)：93-96.
ZHANG Jia-fan，YI Qi-wei，LI Ji．Complex analytic wavelet transform and vibration signals envelope-demodulation analysis[J]．Journal of Vibration and Shock，2010，29(9)：93-96．
[4] 王新晴,马瑞恒,王耀华,等. 基于一种新的时频分布的机械故障诊断[J]。机械工程学报,2003,39(7):150-153．
WANG Xin-qing，MA Rui-huan，WANG Yao-hua，Yan Jun，Cai Ligen，Wang Yang，et al．Mechanical fault diagnosis based on a new time-frequency distribution [J]．Power System Technology，2003，39(7)：150-153．
[5] 马瑞恒，王新晴. 基于一种新的时频分布的机械故障诊断[J]. 振动与冲击,2003，22(3)：70-72.
MA Rui-huan，WANG Xin-qing．Mechanical fault diagnosis based on a new time-frequency distribution [J]．Power System Technology，2003，22(3)：70-72．
[6] Huang NE，Shen Z，Long SR，et al．The empirical mode decomposition and the Hilbert spectrum for non liner and non-stationary time series analysis[J]. Proceedings of the Royal Society ，1998(454):903-993.
[7] 朱文龙，周建中，肖剑，等. 独立分量分析–经验模态分解特征提取在水电机组振动信号中的应用[J]. 中国电机工程学报，2013，33(29)：95-101．
ZHU Wen-long，ZHOU Jian-zhong，XIAO Jian， et al．An ICA-EMD feature extraction method and its application to vibration signals of hydroelectric generating units [J]．Proceedings of the CSEE，2013，33(29)：95-101．
[8] 杨江天，赵明元. 改进双谱和经验模态分解在牵引电机轴承故障诊断中的应用[J]. 中国电机工程学报，2012，32(18)：116-122．
YANG Jiang-tian，ZHAO Ming-yuan， et al．Fault diagnosis of traction motor bearings using modified bispectrum and empirical mode Decomposition [J]．Proceedings of the CSEE，2012，32(18)：116-122．
[9] Wu ZH，Huang NE. Ensemble empirical mode decomposition：a noise assisted data analysis method [J]．Advances in Adaptive Data Analysis，2009，1(1)：1-41．
[10] Rilling G，Flandrin P．On the influence of sampling on the empirical mode decomposition[C]//Proceedings of IEEE Conference on Acoustics，Speech and Signal Processing，Toulouse，France，2006．
[11] Dragomiretskiy K,Zosso D．Variational mode decomposition[J]．IEEE Tran on Signal Processing，2014，62(3)：531-544．
[12] 王建国，李健，万旭东. 基于奇异值分解和局域均值分解的滚动轴承故障特征提取方法[J].机械工程学报,2015，51(3)：104-110．
WANG Jian-guo，LI Jian，WAN Xu-dong．Fault feature extraction method of rolling bearings based on singular value decomposition and local mean decomposition [J]．Power System Technology，2015，51(3)：104-110．
[13] 汤宝平,蒋永华,张详春. 基于形态奇异值分解和经验模态分解的滚动轴承故障特征提取方法[J]. 机械工程学报,2010，46(5)：37-42.
TANG Bao-ping，JIANG Yong-hua，ZHANG Xiang-chun．Feature extraction method of rolling bearing fault based on singular value decomposition-morphology filter and empirical mode decomposition，2010，46(5)：37-42．
[14] 赵学智,叶邦彦,陈统坚. 奇异值差分谱理论及其在车床主轴箱故障诊断中的应用[J]. 机械工程学报,2010，46(1)，100-108.．
ZHAO Xue-zhi，YE Bang-yan，CHEN Tong-jian．Difference spectrum theory of singular value and its application to the fault diagnosis of Headstock of Lathe，2010，46(1)：100-108．
[15] 苏文胜，王奉涛，张志新，等．EMD 降噪和谱峭度法在滚动轴承早期故障诊断中的应用[J]．振动与冲击，2010，29(3)：18-21
SU Wen-sheng，WANG Feng-tao，ZHANG Zhi-xin，et al．Application of EMD denoising and spectral kurtosis in early fault diagnosis of rolling element bearings [J]．Journal of Vibration and Shock，2010，29(3)：18-21．
[16] 胡爱军，马万里，唐贵基．基于集成经验模态分解和峭度准则的滚动轴承故障特征提取方[J]．中国电机工程学报，2012，32(11)：106-111．
HU Ai-jun，MA Wan-li，TANG Gui-ji．An ICA-EMD feature extraction method and its application to vibration signals of hydroelectric generating units [J]．Proceedings of the CSEE，2012，32(11)：106-111．