Abstract

The speed and localization information of the high-speed trains are essential and significant for train control systems. The occurrence of faults in SDUs (Speed Distance Units) will affect the accuracy and effectiveness of location reports to ensure the operation safety of high-speed trains. The fault detection and diagnosis method for SDUs are focused in this paper. By using the on-board GPS (Global Positioning System) measurements, we propose a parallel-filtering-based architecture for detecting the faults in odometers that use the pulse-counting information to estimate the speed and travelling distance of the trains. According to the characteristics of different fault modes, including the hard fault, soft fault and implicated fault, a rule-based fault diagnosis approach is proposed to identify the detected fault and take suggested maintenance measures, where a conservative determination strategy for utilizing the results of the two filters is demonstrated to decrease the missed detection probability. The field operation data from the high-speed train is employed to build the simulation scenarios. The simulation results demonstrate the performance of the proposed method and illustrate its potentials in real-time fault diagnosis and maintenance for speed distance units.

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