Fault Diagnosis of Three-Phase PWM Inverters Using Wavelet and SVM

In this paper, a diagnosis method for switch open-circuit faults in three-phase PWM inverters is proposed, which employs support vector machine (SVM) as classifying method. At first, a discrete wavelet transform (DWT) is used to detect a discontinuity of currents due to the fault, and then the features for fault diagnosis are extracted. Next, these features are employed as inputs for the SVM training. After training, the SVM produces an optimized boundary which is used identifying the fault. Finally, the fault classification is performed online with instantaneous features. The experimental results have verified the validity of the proposed estimation algorithm.