变步长频率加权能量算子在轴承故障诊断中的应用

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摘要

通过包络解调可以提取调制信号中的周期成分来实现轴承故障的早期诊断与预警。但在进行包络解调时，需要解调信号必须为单调幅调频信号，且解调效果容易受到其他干扰信号的影响。频率加权能量算子较包络解调具有更高鲁棒性，但频率加权能量算子在离散化时使用的中点平均差分方法对中心频率较低的调制信号进行解调时鲁棒性较差。因此变步长频率加权能量算子通过改变步长参数来增强其在中心频率较低时的鲁棒性。通过分析与试验验证表明，变步长频率加权能量算子在整个频带都具有较好的解调效果。变步长频率加权能量算子可以在信号未经分解的前提下实现不同共振频带的解调，所以具有更强的工程应用价值。

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	刘泽潮
	林建辉
	丁建明
	吴文逸

关键词 ：滚动轴承故障诊断')" href="#">

滚动轴承故障诊断, 频率加权能量算子, 变步长差分

Abstract：Envelope demodulation can be used to extract periodic components in modulated signals to realize early diagnosis and warning of bearing faults,but the envelope demodulation requires that the signals to be demodulated must be Am-FM signals,and the demodulation effect is easily affected by other interference signals. The frequency weighted energy operator is more robust than the envelope demodulation. However,the frequency weighted energy operator used to demodulate modulated signals with lower central frequency is less robust when the middle point average difference method was applied in discretization. Here,the variable step frequency weighted energy operator (VFWEO) was proposed to enhance its robustness at lower central frequency by changing step parameters. Analysis and test verification showed that VFWEO has a better demodulation effect within the entire frequency band; VFWEO can be used to realize demodulation of different resonant frequency bands without decomposing signals,so it is more valuable in engineering application.

Key words： Rolling bearing fault diagnosis Frequency-weighted energy operator Vary step difference.

收稿日期: 2018-04-26 出版日期: 2019-03-28

引用本文:

刘泽潮,林建辉,丁建明, 吴文逸. 变步长频率加权能量算子在轴承故障诊断中的应用[J]. 振动与冲击, 2019, 38(7): 86-92.
LIU Zechao, LIN Jianhui, DING Jianming, WU Wenyi. Application of variable step frequency weighted energy operator in bearing fault diagnosis. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(7): 86-92.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2019/V38/I7/86

[1] Randall R B, Antoni J. Rolling element bearing diagnostics—A tutorial [J]. Mechanical Systems & Signal Processing, 2011,25(2):485-520.
[2] 丁康, 米林. 解调分析在故障诊断中应用的局限性问题[J]. 振动工程学报, 1997(1):13-20.
Ding Kang, Mi. Lin. Investigation on limitations for demodulation analysis application in failure diagnosis [J]. Journal of Vibration Engineering, 1997(1):13-20.
[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(09):93-96.
ZHANG Jiafan, YI Qiwei, Li Ji. Complex Analytic wavelet transform and vibration signals envelope-demodulation analysis [J]. Journal of vibration and shock, 2010(09):93-96.

[4] 胡晓依, 何庆复, 王华胜, 等. 基于STFT的振动信号解调方法及其在轴承故障检测中的应用[J]. 振动与冲击, 2008(02):82-86.
Hu Xiaoyi, He qingfu, Wang Huasheng. Vibration signal demodulation method based on STFT and its application in rolling bearing fault detections [J].Journal of vibration and shock, 2008(02):82-86.
[5] 胡异丁, 任伟新, 杨栋, 等. 基于希尔伯特变换的非平稳调幅信号解调[J]. 振动与冲击, 2013(10):181-183.
Hu Yiding, Ren Weixin, Yang Dong. Demodulation of non-stationary amplitude modulated signal based on Hilbert transform [J]. Journal of vibration and shock, 2013(10):181-183.
[6] 夏均忠, 赵磊, 白云川, 等. 基于Teager能量算子和ZFFT的滚动轴承故障特征提取[J]. 振动与冲击, 2017(11):106-110.
Xia Junzhong, Zhao Lei, Bai Yunchuan. Fault feature extraction of rolling element bearing based on Teager energy operator and ZFFT [J].Journal of vibration and shock, 2017(11):106-110.
[7] Wu K, Zhang D, Lu G, et al. GMAT: Glottal closure instants detection based on the Multiresolution Absolute Teager-Kaiser energy operator[J]. Digital Signal Processing, 2017,69.
[8] 杨青乐, 梅检民, 肖静, 等. Teager能量算子增强倒阶次谱提取轴承微弱故障特征[J]. 振动与冲击, 2015(06):1-5.
Yang Qingle, Mei Jianmin, Xiao Jing. Weak fault feature extraction for bearing based on order cepstrum enhanced by teager energy operator [J].Journal of vibration and shock, 2015(06):1-5.
[9] 王天金, 冯志鹏, 郝如江, 等. 基于Teager能量算子的滚动轴承故障诊断研究[J]. 振动与冲击, 2012,31(2):1-5, 85.
Wang Tianjin, Feng Zhipeng, Hao Rujiang. Fault diagnosis of rolling element bearings based on teager energy operator [J]. Journal of vibration and shock, 2012,31(2):1-5, 85.
[10] 马增强, 李亚超, 刘政, 等. 基于变分模态分解和Teager能量算子的滚动轴承故障特征提取[J]. 振动与冲击, 2016(13):134-139.
Ma Zengqiang, Li Yachao, Liu Zheng. Rolling bearing fault feature extraction based on variational mode decomposition and Teager energy operator [J].Journal of vibration and shock, 2016(13):134-139.
[11] O'Toole J M, Temko A, Stevenson N. Assessing instantaneous energy in the EEG: A non-negative, frequency-weighted energy operator.: Engineering in Medicine and Biology Society, 2014[C].
[12] Smith W A, Randall R B. Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study[J]. Mechanical Systems & Signal Processing, 2015,64-65:100-131.
[13] Gilles J E R F, Heal K. A parameterless scale-space approach to find meaningful modes in histograms u2014 Application to image and spectrum segmentation[J]. International Journal of Wavelets Multiresolution & Information Processing, 2014,12(06):1450044.
[14] Gilles J. Empirical Wavelet Transform[J]. IEEE Transactions on Signal Processing, 2013,61(16):3999-4010.