LAUSR

Abstract The performance of braking system strongly affects the safe operation of electric multiple unit (EMU). During the practical operation, it’s of great significance to detect incipient faults in braking system. Since the braking process is a typical non-Gaussian and multi-stage process, it’s difficult to detect these incipient faults. Particularly, the usually occurred overlap of normal and faulty samples during braking process makes the detection more difficult. In this paper, a novel method based on data domain description and variable control limit (VCL) is developed for detecting incipient faults in EMU braking system. The local reachability density (LRD) weighted support vector data description with negative samples (NSVDD) is introduced for offline modeling to get more accurate domain description, while the Gaussian kernel trick is utilized to obtain hypersphere with soft boundary. With the presence of sample overlap, the VCL strategy is adopted for online fault detection, which effectively reduces false alarm rate (FAR) and increases fault detection rate (FDR) simultaneously. A case study of three kinds of incipient faults in EMU braking system fully demonstrates the effectiveness of the proposed method.