Incipient Fault Diagnosis of IGBT Drive Circuit Based on EWT-ResNet

Abstract

The operation of the Insulated Gate Bipolar Transistor (IGBT) is closely related to the operating state of the drive circuit. Based on the theory of analog circuit fault diagnosis, this paper proposed an incipient fault diagnosis method combing Empirical Wavelet Transform (EWT) and Residual Network (ResNet) for IGBT drive circuit which has an EXB-841 driver module as the core. Firstly, the drive circuit was divided into the driving function (DF) part and the short-circuit protection (SP) part according to its working principle and basic structure. And the sensitivity analysis was performed on all the main components in both sections to select the test objects. Secondly, the circuit signals were obtained by fault injection and Monte Carlo analysis and then decomposed by improved EWT based on Scale Space (SS) to construct the datasets. Finally, based on the structure of ResNet18, 1D-ResNet was established and trained on the collected datasets to achieve deep feature extraction and fault classification. Simulation results show that the incipient fault diagnosis accuracy of DF part and SP part is 99.55% and 97.55% respectively.