Condition-Based Maintenance for Traction Power Supply Equipment Based on Partially Observable Markov Decision Process

Actual condition-based maintenance for traction power supply equipment (TPSE) is almost based on completely observable equipment state. However, it is unpractical to accurately reveal the equipment state due to the inescapably uncertainty of state assessment. In order to optimize the maintenance of TPSE, a maintenance model based on partially observable Markov decision process is proposed in this paper. Firstly, the degradation process of the TPSE is described by a four-state Markov process, and the state residence time and its transition probability of the equipment are obtained by equaling fault times in the statistical period. Then, the imperfect maintenance is considered in this paper. And the failure risk of the TPSE after maintenance is quantified for optimizing both the economic cost and the reliability of maintenance strategy. Finally, the practical fault record data of 27.5 kV vacuum circuit breakers for a traction power supply system (TPSS) are used to verify the proposed model. The results show that the maintenance model can provide guidance on decision-making for the maintenance under uncertainty, and the determination of maintenance schemes to optimize both TPSE reliability and operational cost.

I. Introduction

Current maintenance mode of traction power supply equipment (TPSE) served in High-Speed Railway in China contains both periodic preventive maintenance (PPM) and corrective maintenance. Maintenance personnel conduct maintenance actions for equipment at regular intervals according to the plan. However, the flexibility and pertinence of the PPM for TPSE is unsatisfactory. And it has the problems of insufficient maintenance and excessive maintenance [1]. Therefore, there is an urgent need to improve the traditional maintenance mode of TPSE. The technologically advanced data collecting and fault diagnosis techniques have been explored for improving reliability prediction and maintenance decision making [2]–[5]. Condition-based maintenance (CBM) is a developed maintenance mode based on the state data obtained from preventive test and online monitoring. The CBM will flexibly and purposely formulate the maintenance scheme according to the state of the equipment, thereby reducing the waste of maintenance resources and solving the problems of insufficient maintenance and excessive maintenance [6]–[9]. For this reason, this paper applies CBM in the maintenance of TPSE to address the existing problems of the traditional maintenance mode. However, there are still some issues that need to be addressed when applying CBM.