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Remaining useful life prediction of equipment considering dynamic thresholds under the influence of maintenance
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Lanzhou University of Technology, China
Submission date: 2023-09-13
Final revision date: 2023-10-07
Acceptance date: 2023-11-06
Online publication date: 2023-11-08
Publication date: 2023-11-08
Corresponding author
Li'na Ren   

Lanzhou University of Technology, China
  • To predict RUL by considering dynamic thresholds.
  • A multi-stage maintenance-impact degradation model is established.
  • The parameters are estimated using the MLE and Bayesian formula.
  • The proposed approach can enhance the precision of RUL prediction.
A novel approach for predicting remaining useful life (RUL) is proposed for situations where maintenance threshold and failure threshold exhibit dynamic behavior due to uncertainties in degradation and the influence of detection strategies during maintenance processes. The approach introduces maintenance threshold error to establish a multi-stage maintenance-impact degradation model with dynamic maintenance threshold based on the Wiener process. This model considers the impact of maintenance on degradation rate, amount, and path. Moreover, by using the first hitting time (FHT) and introducing failure threshold error to reflect the dynamic behavior of the failure threshold, the formula for predicting equipment RUL is derived. The model parameters are estimated using both the maximum likelihood estimation (MLE) approach and Bayesian formula. The proposed approach was validated with simulation data and gyroscope degradation data, and the results demonstrate its ability to effectively enhance the precision of equipment RUL prediction.