Research on Mechanical Performance Degradation Modeling and Remaining Useful Life Prognosis Method of AC High-Voltage Circuit Breakers

Abstract

This article proposes a data-driven degradation modeling and remaining useful life prognosis method for ac high-voltage circuit breakers that addresses uncertainty in the degradation process. First, the Nadaraya–Watson method is used to reduce measurement error by smoothly estimating the closing-time dataset of high-voltage circuit breakers. Second, the functional principal component analysis (FPCA) is applied to extract the common degradation-trend component and deviation component from the smoothed data, to construct a degradation model. Finally, the model parameters are dynamically updated using Bayesian inference to predict the degradation trend and estimate the remaining useful life of high-voltage circuit breakers. Experimental results show that the proposed method offers timely identification of degradation trends and accurate estimation of remaining useful life. This not only enhances equipment reliability and reduces maintenance costs but also provides essential technical support for implementing intelligent operation and maintenance strategies for high-voltage circuit breakers, demonstrating strong engineering applicability and practical significance.