Journal
JOURNAL OF SOUND AND VIBRATION
Volume 523, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jsv.2022.116746
Keywords
Spectral coherence; Improved envelope spectrum; Candidate fault frequencies; Frequency band selection; Bearing fault diagnosis
Categories
Funding
- independent project of State Key Laboratory of Traction Power [2021TPL-T11, 2020TPL-T08]
- Fundamental Research Funds for the Central Universities [2682021CG003, 2682021CX090]
- Scientific Research Project of Tianjin Education Commission [2019KJ128]
- Scientific Research Projects of China State Railway Group Co., Ltd. [J2020J006]
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This study proposes a method based on spectral coherence to identify bearing faults. By displaying the energy flow of vibration signal in a two-dimensional plane, the periodic faults of the bearings can be accurately identified. To address the interference and noise issues, an adaptive method is introduced to determine the informative spectral frequency band.
Early fault identification of the rolling element bearings remains difficult because the repetitive transient signature generated via localized incipient damage is easily submerged by various interference components and strong noise. Spectral coherence (SCoh) is a breakthrough approach for revealing the second-order cyclostationary of bearing faults by displaying the energy flow of vibration signal jointly in a two-dimensional plane comprising the resonance frequency and bearing fault frequency. Considering the non-uniformity of fault information distribution in the whole spectral frequency band, the enhanced envelope spectrum (EES) obtained by integrating over the full spectral frequency band is vulnerable to strong background noise. Thus, how to identify an informative spectral frequency band for constructing a diagnostic improved envelope spectrum (IES) is crucial to accurately identify bearing faults. To address this issue, a feature-adaptive method called IES via Candidate Fault Frequency Optimization-gram (IESCFFOgram) is proposed to determine the informative spectral frequency band from SCoh for bearing fault diagnosis. The innovation of this method is to fully excavate the fault information hidden in the SCoh and adaptively determine the informative spectral frequency band according to the identified candidate fault frequencies. The proposed method is tested and validated on simulated signals, vibration datasets obtained from artificial fault bearing experiments, and accelerated bearing degradation tests. In addition, comparisons with state-of-the-art methods have been conducted to highlight the superiority of the proposed methodology.
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