Multiband Envelope Spectra Extraction for Fault Diagnosis of Rolling Element Bearings
1
State Key Lab of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
2
School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
3
Department of Power Engineering, Naval University of Engineering, Wuhan 430033, China
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(5), 1466; https://doi.org/10.3390/s18051466
Received: 27 March 2018
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Revised: 2 May 2018
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Accepted: 5 May 2018
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Published: 8 May 2018
(This article belongs to the Section Physical Sensors)
Bearing fault features are presented as repetitive transient impulses in vibration signals. Narrowband demodulation methods have been widely used to extract the repetitive transients in bearing fault diagnosis, for which the key factor is to accurately locate the optimal band. A multitude of criteria have been constructed to determine the optimal frequency band for demodulation. However, these criteria can only describe the strength of transient impulses, and cannot differentiate fault-related impulses and interference impulses that are cyclically generated in the signals. Additionally, these criteria are easily affected by the independent transitions and background noise in industrial locales. Therefore, the large values of the criteria may not appear in the optimal frequency band. To overcome these problems, a new method, referred to as multiband envelope spectra extraction (MESE), is proposed in this paper, which can extract all repetitive transient features in the signals. The novelty of MESE lies in the following aspects: (1) it can fuse envelope spectra at multiple narrow bands. The potential bands are selected based on Jarque-Bera statistics of narrowband envelope spectra; and (2) fast independent component analysis (fastICA) is introduced to extract the independent source spectra, which are fault- or interference-related. The multi-band strategy will preserve all impulse features and make the method more robust. Meanwhile, as a blind source separation technique, the fastICA can suppress some in-band noise and make the diagnosis more accurate. Several simulated and experimental signals are used to validate the efficiency of the proposed method. The results show that MESE is effective for enhanced fault diagnosis of rolling element bearings. Bearing faults can be detected even in a harsh environment.
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Keywords:
narrowband amplitude demodulation; Jarque-Bera statistic; rolling element bearing; blind source separation; fault diagnosis
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MDPI and ACS Style
Duan, J.; Shi, T.; Zhou, H.; Xuan, J.; Zhang, Y. Multiband Envelope Spectra Extraction for Fault Diagnosis of Rolling Element Bearings. Sensors 2018, 18, 1466. https://doi.org/10.3390/s18051466
AMA Style
Duan J, Shi T, Zhou H, Xuan J, Zhang Y. Multiband Envelope Spectra Extraction for Fault Diagnosis of Rolling Element Bearings. Sensors. 2018; 18(5):1466. https://doi.org/10.3390/s18051466
Chicago/Turabian StyleDuan, Jie, Tielin Shi, Hongdi Zhou, Jianping Xuan, and Yongxiang Zhang. 2018. "Multiband Envelope Spectra Extraction for Fault Diagnosis of Rolling Element Bearings" Sensors 18, no. 5: 1466. https://doi.org/10.3390/s18051466
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