Remaining Useful Life prediction of rolling bearings based on risk assessment and degradation state coefficient

Prediction of Remaining Useful Life (RUL) of bearings is very important for the condition-based maintenance of the rotating machinery. In order to predict the RUL more accurately, an approach of RUL prediction based on risk assessment and degradation state coefficient is proposed. The Mahalanobis Di...

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Bibliographic Details
Published in:ISA transactions 2022-10, Vol.129, p.413-428
Main Authors: Li, Qiang, Yan, Changfeng, Chen, Guangyi, Wang, Huibin, Li, Hongkun, Wu, Lixiao
Format: Article
Language:English
Subjects:
Degradation state coefficient
GA-SVR
Modified health indicator
Remaining useful life
Risk assessment
VMD-SVD
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Summary:Prediction of Remaining Useful Life (RUL) of bearings is very important for the condition-based maintenance of the rotating machinery. In order to predict the RUL more accurately, an approach of RUL prediction based on risk assessment and degradation state coefficient is proposed. The Mahalanobis Distance (MD) is calculated depending on the characteristics of vibration signals in the time domain and time–frequency domain. The features in the time–frequency domain are extracted by using Variational Mode Decomposition-Singular Value Decomposition (VMD-SVD). The monotonously increasing Health Indicator (HI) is obtained by using MD1-CUMSUM. The risk assessment is proposed to adaptively determine the thresholds of initial fault and failure, which is a trade-off between the false alarm rate and sensitivity. The RUL prediction of the testing bearing is completed based on the Genetic Algorithm-Support Vector Regression (GA-SVR) and Modified Health Indicator (MHI) with the degradation state coefficient. The proposed approach is verified by using two experimental vibration signal datasets. The results show that the proposed method has good capability to predict the RUL of rolling bearings. •The monotonously increasing HI is constructed by using MD1-CUMSUM based on the multi-domain features.•The risk assessment is proposed to adaptively determine the thresholds of initial fault and failure.•A degradation index MHI based on HI and degradation state coefficient γ is proposed.•The proposed approach is verified by other experimental vibration signal datasets.
ISSN:0019-0578
1879-2022
DOI:10.1016/j.isatra.2022.01.031