LI X B, WANG X, WANG R Y,et al.Research on remaining life estimation method considering change points and measurement errors[J].Journal of Henan Polytechnic University(Natural Science) ,2026,45(5):20-29.

doi:10.16186/j.cnki.1673-9787.2025050045

Received:2025/05/23

Revised:2025/08/20

Published:2026-07-24

Research on remaining life estimation method considering change points and measurement errors

Li Xiaobo1, Wang Xiang1, Wang Ruiyi2, Shen Qing2

1.College of Urban Rail Transit， Shanghai University of Engineering Science， Shanghai  201620， China；2.Shanghai Metro Electronic Technology Co.， Ltd.， Shanghai  200233， China

Abstract: Objectives In order to improve the prediction accuracy of the remaining service life of the product， a two-stage nonlinear Wiener process degradation model in which both change points and measurement errors were considered was proposed.  Methods Firstly， based on the statistical characteristics of degradation data for products of the same type，a change point detection algorithm was used to estimate the change points of the product offline based on statistical characteristics of degradation data for products of the same type. The maximum likelihood estimation method was used to solve the initial model parameters. Then，based on the change point position of the same type products， the threshold value of degradation angle criterion was determined to realize monitoring the change point of target products online. On this basis， the Kalman filtering algorithm was used to estimate the hidden state of the target product， and the model parameters were updated online. The expressions for the RUL probability density function and cumulative distribution function considering online updating of the model parameters were derived. Finally， the effectiveness and rationality of the proposed method were verified by comparing and analyzing the simulated degradation data and the experimental data on NASA electrolytic capacitor accelerated degradation， respectively.  Results Compared with the single-stage nonlinear Wiener process， the simulation data analysis results showed that the mean absolute error（MAE） of the proposed algorithm decreased by 1.558 9； Comparinged with the traditional two Wiener process models， the verification results of accelerated aging test data indicated that the mean square error of capacitor remaining life prediction using the proposed method have been improved by 524.473 3 and 112.759 1， respectively. Conclusions The research results have important reference values for remaining life study of products with different degradation patterns during different usage periods， especially suitable for situations where there was a significant difference in degradation characteristics between the early and late stages of product performance degradation.

Key words:remaining useful life prediction;two-stage nonlinear Wiener process;change point detection;measurement error