Enhanced bearing fault diagnosis using integral envelope spectrum from spectral coherence normalized with feature energy

被引:33
作者
Chen, Bingyan [1 ]
Cheng, Yao [1 ]
Zhang, Weihua [1 ]
Gu, Fengshou [2 ]
机构
[1] Southwest Jiaotong Univ, State Key Lab Tract Power, 111 First Sect,North Second Ring Rd, Chengdu 610031, Peoples R China
[2] Univ Huddersfield, Ctr Efficiency & Performance Engn, Huddersfield HD1 3DH, W Yorkshire, England
关键词
Weighted combined envelope spectrum; Improved envelope spectrum; IESFOgram; Spectral coherence; Bearing diagnostics; FAST COMPUTATION; BAND; DEMODULATION; KURTOSIS;
D O I
10.1016/j.measurement.2021.110448
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Enhanced envelope spectrum (EES) and improved envelope spectrum (IES) generated from spectral coherence (SCoh) are proven to be more robust fault detection tools than squared envelope spectrum (SES). However, EES cannot effectively detect the fault-induced components under strong interference noise and IES can only capture the information of a fault-sensitive resonance spectral frequency band. To overcome these problems, weighted combined envelope spectrum (WCES) from SCoh is proposed as a novel fault detector. WCES integrates the fault components distributed in multiple resonance frequency bands using normalized feature energy and removes the envelope spectrum slices with less fault information to exclude disturbance noises. The performance of WCES is validated using simulations and experiments and compared with the advanced envelope spectra. The results demonstrate that WCES can effectively detect bearing faults under strong interference noise and multiple resonances compared with the SES, EES and IES, and has potential application value in bearing diagnostics.
引用
收藏
页数:19
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共 41 条
[1]   Order-frequency analysis of machine signals [J].
Abboud, D. ;
Antoni, J. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 87 :229-258
[2]   Cyclic spectral analysis of rolling-element bearing signals: Facts and fictions [J].
Antoni, J. .
JOURNAL OF SOUND AND VIBRATION, 2007, 304 (3-5) :497-529
[3]   Fast computation of the kurtogram for the detection of transient faults [J].
Antoni, Jerome .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (01) :108-124
[4]   Fast computation of the spectral correlation [J].
Antoni, Jerome ;
Xin, Ge ;
Hamzaoui, Nacer .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 92 :248-277
[5]   The infogram: Entropic evidence of the signature of repetitive transients [J].
Antoni, Jerome .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2016, 74 :73-94
[6]   A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram [J].
Barszcz, Tomasz ;
Jablonski, Adam .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2011, 25 (01) :431-451
[7]   The relationship between kurtosis- and envelope-based indexes for the diagnostic of rolling element bearings [J].
Borghesani, P. ;
Pennacchi, P. ;
Chatterton, S. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2014, 43 (1-2) :25-43
[8]   A joint resonance frequency estimation and in-band noise reduction method for enhancing the detectability of bearing fault signals [J].
Bozchalooi, I. Soltani ;
Liang, Ming .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2008, 22 (04) :915-933
[9]   A performance enhanced time-varying morphological filtering method for bearing fault diagnosis [J].
Chen, Bingyan ;
Song, Dongli ;
Zhang, Weihua ;
Cheng, Yao ;
Wang, Zhiwei .
MEASUREMENT, 2021, 176
[10]   Informative frequency band selection in the presence of non-Gaussian noise - a novel approach based on the conditional variance statistic with application to bearing fault diagnosis [J].
Hebda-Sobkowicz, Justyna ;
Zimroz, Radoslaw ;
Pitera, Marcin ;
Wylomanska, Agnieszka .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2020, 145