Multiple Fuzzy Diagnosis for Voltage Source Inverter Open Circuit Fault in Torque Direct Control Induction Motor Drive

Abstract

This article aims to examine the possibility of fault detection and diagnosis in an induction motor powering a three-phase inverter using artificial intelligence (AI) techniques. Due to the weakness of the switches contained in a three phase inverter. Early detection of these fault switches that may occur in the inverter will be very important in order to find a way to allow us to control the operation and the protective action to avoid regular failures. We present the simulation results of a fault diagnosis system using an artificial intelligence technique with direct torque control (FDTC) of fuzzy logic of the induction motor. In this article, we provide a detailed explanation of the multiple open circuit switching faults in the inverter with a simple feature extraction technique to investigate the possibility of detecting and diagnosing these faults. The search and identification of faulty switches is recognized in limited current periods. Classification performance for multiple defects is improved by the use of a fuzzy logic detection approach.