Abstract
ABSTRACTThe safety and reliability of traction power supply systems (TPSSs) have aroused concern for the long-term development of high-speed railway (HSR) in China. To improve the current TPSS maintenance situation, it is essential to manage and make full use of the abundant data from on-line sensors and off-line tests for fault detection and prediction. This paper proposes a novel framework using prognostics and health management and active maintenance (PHM-AM) technology for TPSS maintenance. The hardware components and software modules needed to implement the proposed PHM-AM framework are described in details. Subsequently, several methodologies are employed to address the issues of data management, utilization, and maintenance in TPSSs. Finally, the implementation of the PHM-AM system is illustrated through three case studies and a preliminary software interface. These examples help to bridge the gap between theoretical modelling and the practical application of fault detection, health diagnosis, and maintenance decision-making methods in TPSSs.
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