Abstract
Air brake system (ABS) plays a vital role in the safe operation of high-speed trains (HSTs). In order to ensure the reliability of the ABS, fault diagnosis becomes significant. The conventional inter-variable variance (IVV) method is first briefly revisited, and its defects are pointed out; accordingly, an improved index called exter-variable variance (EVV) is proposed, which overcomes the shortcomings of the IVV index. Specifically, the mean value of the calculation for EVV is reformed for enhanced fault detection, and afterward, a new fault pattern recognition method is designed for fault classification. The methodology is detailed by theoretical derivation and analysis. Finally, simulation experiments verify the method’s effectiveness on a fault injection platform, which can simulate the injection of five common fault types occurring within the ABS.
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