Fault Diagnosis in Medium Voltage Drive Based on Combination of Wavelet transform and Support Vector Machine

Abstract

Nowadays, Medium Voltage Drive (MVD) has been widely applied in the field of high-powered motor speed-regulation. These types of converter use a lot of insulated gate bipolar translators (IGBTs). So it is very important to find an effective way to diagnose IGBT open-circuit faults. This study describes a method of diagnosis for IGBT open-circuit faults in MVD whose topology is cell series of multi-level. This method combines wavelet transform (WT) and support vector machine (SVM). The wavelet transform is used to extract fault features and SVM is used to classify the fault states of a single power unit. Then, the trained SVM classifier is used to scan all power units of MVD sequentially. Results of simulation on the platform of MATLAB/Simulink show that this method has a good diagnosis capability. It can diagnose the IGBT open-circuit faults of the whole inverter system, and diagnosis accuracy is up to 96%. So, this method has a good application prospect.