On-line fault diagnosis model for locomotive traction inverter based on wavelet transform and support vector machine

Abstract A traction inverter is the power source for rail transit vehicles. An insulated-gate bipolar transistor (IGBT) is the primary component of a traction inverter. IGBT faults can cause serious problems in locomotive power supply systems. The disadvantage of traditional fault detection methods for IGBT modules is a lack of real-time processing and high efficiency. An on-line fault diagnosis method based on a wavelet transform and multi-classification support vector machine (multi-SVM) is proposed for IGBT faults. Wavelet decomposition is used to process fault current signals, and energy vectors are constructed. Multi-SVM is used to establish a fault recognition model. The validity of this method is verified by simulations with MATLAB/Simulink.