Life Prediction Method of Electromagnetic Contactor Based on Fusion of Improved Particle Filter and Degradation Model

Abstract

Electromagnetic contactors are the key components of high-speed trains. A reasonable evaluation of the remaining life of the contactors can optimize the replacement cycle of the contactors and ensure the safe operation of the train. Aiming at the problem of remaining life prediction of contactors, a contactor life prediction method based on the fusion of improved particle filter algorithm and performance degradation model is proposed. Firstly, on the basis of analyzing the failure mechanism of the contactor and establishing its electromagnetic and dynamic simulation model, a performance degradation model based on overtravel time is established. Then design the contactor life test to obtain its full life cycle degradation data. Next, the adaptive genetic algorithm is used to optimize the resampling process of the particle filter algorithm. Finally, the optimal parameter values of the performance degradation model are obtained by the improved particle filter algorithm, and then the prediction of the remaining life of the contactor is realized. The prediction results show that the method can effectively predict the remaining life of the contactor, and the prediction accuracy meets the actual engineering needs, which provides an important reference for the operation and maintenance of the electromagnetic contactor for high-speed trains.