Volume 42 Issue 1
Jan.  2023
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ZHANG Jinbao, ZOU Tiangang, WANG Min, GUI Peng, GE Hongxia, WANG Cheng. Review on Remaining Useful Life Prediction of Rolling Bearing[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(1): 1-23. doi: 10.13433/j.cnki.1003-8728.20200489
Citation: ZHANG Jinbao, ZOU Tiangang, WANG Min, GUI Peng, GE Hongxia, WANG Cheng. Review on Remaining Useful Life Prediction of Rolling Bearing[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(1): 1-23. doi: 10.13433/j.cnki.1003-8728.20200489

Review on Remaining Useful Life Prediction of Rolling Bearing

doi: 10.13433/j.cnki.1003-8728.20200489
  • Received Date: 2020-11-26
  • Publish Date: 2023-01-25
  • Rolling bearing are a key component of rotating machinery, and remaining useful life prediction of them will be of great significance to production, maintenance and personal safety. Due to the complex and changeable working environment of the rolling bearing, there are fewer reference samples in the same working condition but more in different working conditions. Moreover, the samples have the characteristics of unbalanced, incomplete, no label and noise interference, which increases the difficulty of RUL prediction. With the advent of the era of big data and the development of artificial intelligence, rolling bearing RUL prediction methods have become more abundant. Therefore, based on the framework of prognosis and health management, the failure modes and fault data characteristics of the rolling bearing are stated, methods concerning fault feature extraction, dimension reduction and fusion, as well as the obtained performance degradation indicators are respectively classified and contrastive analysis are performed. Combining with the data driven algorithms, the prediction approach, model selection and evaluation criteria of rolling bearing RUL are sorted and compared. Finally, the future development trend of rolling bearing RUL prediction is prospected.
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