基于复包络谱的滚动轴承故障特征提取方法研究

摘要
图/表
参考文献(18)
相关文章 (15)

全文: PDF (2988 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要提出一种基于复包络谱的滚动轴承故障特征提取方法。采用正交采样技术获取滚动轴承同一支撑处互相垂直方向上的振动信号，并将其组成一个复数信号；运用二元经验模态分解（bivariate empirical mode decomposition，BEMD）将复数信号分解成若干复固有模态函数(complex intrinsic mode function, CIMF)之和，应用Hilbert变换解调出CIMFs的实部和虚部包络信号，将实部和虚部的包络信号组成复数形式的包络信号，并用复傅里叶变换求其频谱。依据复数形式的包络信号的傅里叶谱提取滚动轴承的复合故障特征频率，并与全矢谱做了对比分析。复合故障试验案例证明了该方法的可有性和有效性；XJTU-SY 滚动轴承数据集的复合故障分析进一步验证了该方法提取的故障特征更为全面。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	黄传金1
	宋海军1
	秦娜2
	雷文平3
	孙熙庆1
	柴鹏1

关键词 ：复傅里叶变换, 复包络信号, 复固有模态函数, 故障特征提取, 滚动轴承

Abstract：A fault feature extraction method of rolling bearings based on complex envelope spectrum was proposed.Firstly, the vibration signals at the same support of rolling bearings were obtained by orthogonal sampling technology, and they were composed into a complex signal.Secondly, the complex signal was decomposed into the sum of several complex intrinsic mode functions (CIMF) by using the bivariate empirical mode decomposition (BEMD).The envelope signals of real part and virtual part of CIMFs were demodulated by the Hilbert transform.The envelope signals of real part and virtual part were composed of complex envelope signals, and the spectrum was calculated by the complex Fourier transform.According to the characteristics of the complex signal Fourier transform, which can enhance the characteristic amplitude and synthesize the characteristic frequency, the fault characteristic frequency of rolling bearing was extracted according to the complex envelope signal Fourier spectrum.According to the Fourier spectrum of the complex envelope signal, the fault characteristic frequency of rolling bearing was extracted and compared with the full vector spectrum.A composite fault test case proved the feasibility and effectiveness of this method; the composite fault analysis of XJTU-SY rolling bearing data set further proved that the fault features extracted by this method are more comprehensive.

Key words： complex Fourier transform complex envelope signal complex intrinsic mode functions Fault feature extraction

收稿日期: 2020-01-02 出版日期: 2021-06-28

引用本文:

黄传金1，宋海军1，秦娜2，雷文平3，孙熙庆1，柴鹏1. 基于复包络谱的滚动轴承故障特征提取方法研究[J]. 振动与冲击, 2021, 40(12): 189-195.
HUANG Chuanjin1,SONG Haijun1,QIN Na2,LEI Wenping3,SUN Xiqing1,CHAI Peng1. Fault feature extraction of rolling bearings based on complex envelope spectrum. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(12): 189-195.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2021/V40/I12/189

［1］胡爱军，赵军，孙尚飞，等．基于谱峭度和最大相关峭度解卷积的滚动轴承复合故障特征分离方法［J］．振动与冲击，2019，38(4)：158-164
HU Aijun, ZHAO Jun, SUN Shangfei, et al.A compound fault features separation method of rolling bearing based on spectral kurtosis combined with maximum correlated kurtosis deconvolution［J］.Journal of Vibration and Shock,2019，38(4):158-164.

［2］LIU Haiyang, HUANG Weiguo, WANG Shibin, et al.Adaptive spectral kurtosis filtering based on Morlet wavelet and its application for signal transients detection［J］.Signal Processing, 2014, 96: 118-124.

［3］丁康，黄志东，林慧斌．一种谱峭度和 Morlet小波的滚动轴承微弱故障诊断方法［J］．振动工程学报，2014，27(1)：129-135．
DING Kang, HUANG Zhidong, LIN Huibin.A weak fault diagnosis method for rolling element bearings based on Morlet wavelet and spectral kurtosis［J］.Journal of Vibration Engineering, 2004, 27(1):129-135.

［4］YU Dejie, CHENG Junsheng, YANG Yu.Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings［J］.Mechanical Systems and Signal Processing, 2005, 19(2): 259-270.

［5］LIU Huanhuan, HAN Minghong.A fault diagnosis method based on local mean decomposition and multi-scale entropy for roller bearings［J］.Mechanism and Machine Theory, 2014, 75: 67-78.

［6］WANG Hongchao, CHEN Jin, DONG Guangming.Feature extraction of rolling bearing’s early weak fault based on EEMD and tunable Q-factor wavelet transform［J］.Mechanical Systems and Signal Processing, 2014, 48: 103-119.

［7］ZHENG Jinde, CHENG Junsheng, YANG Yu.A rolling bearing fault diagnosis approach based on LCD and fuzzy entropy［J］.Mechanism and Machine Theory, 2013, 70: 441-453.

［8］CHEN Zhuyun, LI Weihua.Multisensor feature fusion for bearing fault diagnosis using sparse autoencoder and deep belief network［J］.IEEE Transactions on Instrumentation and Measurement, 2017, 66(7): 1693-1702.

［9］程军圣，张亢，杨宇．局部均值分解方法及其在滚动轴承故障诊断中的应用［J］．中国机械工程，2009，20(22)：2710-2716.
CHENG Junsheng, ZHANG Kang, YANG Yu.Local mean decomposition method and its application to roller bearing fault diagnosis［J］.China Mechanical Engineering, 2009,20(22): 2710-2716.

［10］GOLDMAN P, AGNES M, Application of full spectrum to rotating machinery diagnostics［J］.Orbit, First Quarter, 1999: 17-21.

［11］QU L, LIU X, PEYRONNE G, et al.The holospectrum: A new method for rotor surveillance and diagnosis［J］.Mechanical Systems & Signal Processing, 2003(3): 255-267.

［12］韩捷，石来德．全矢谱技术及工程应用［M］.北京：机械工业出版社，2008.

［13］巩晓赟．基于全矢谱的非平稳故障诊断关键技术研究［D］．郑州：郑州大学，2013

［14］黄传金，邬向伟，曹文思，等．基于 LMD 的全矢包络技术及其在 TRT 振动故障诊断中的应用［J］．电力自动化设备，2015，35(2)：168-174.
HUANG Chuanjin, WU Xiangwei, CAO Wensi, et al.LMD-based full vector envelope technique and its application in TRT vibration fault diagnosis［J］.Electric Power Automation Equipment,2015,35(2):168-174

［15］ZHAO X M, PATEL T H, ZUO M J.Multivariate EMD and full spectrum based condition monitoring for rotating machinery［J］.Mechanical Systems and Signal Processing, 2012(27): 712-728

［16］黄传金，宋海军，秦娜．BEMD全矢包络谱及其在TRT故障诊断中的应用［J］．电力自动化设备，2018，38(1)：184-192
HUANG Chuanjin, SONG Haijun, QIN Na.Full envelope spectrum based on BEMD and its applications in TRT fault diagnosis［J］.Electric Power Automation Equipment, 2018,38(1):184-192.

［17］黄传金，孟雅俊，雷文平，等．复局部均值分解全矢包络技术及其在转子故障特征提取中的应用［J］．机械工程学报，2016，52(7)：69-78.
HUANG Chuanjin, MENG Yajun, LEI Wenping, et al.Full vector envelope technique based on complex local mean decomposition and its application in fault feature extraction for rotor system［J］.Journal of Mechanical Engineering, 2016, 52(7):69-78.

［18］WANG Biao, LEI Yaguo, LI Naipeng, et al.A hybrid prognostics approach for estimating remaining useful life of rolling element bearings［J］.IEEE Transactions on Reliability, 2018: 1-12.