Analysis of Total Harmonic Distortion and implementation of Inverter Fault Diagnosis using Artificial Neural Network

Abstract

As power electronics devices dependability is very significant to guarantee Multi Level Inverter (MLI) systems stable functioning, it is imperative to identify and position faults as promptly as possible. Due to the fault occurrences, the Total Harmonic Distortion (THD) on the system gets a hit. In this perspective, to improve fault diagnosis accuracy and efficient working of a Cascaded Multi level Inverter System (CHMLIS), a quick and accurate fault diagnosis strategy with an optimized training algorithm using Artificial Neural Network (ANN) is presented. Also, Total Harmonic Distortion (THD) is analyzed for each switch Fault simulated using MATLAB/Simulink and the results are presented. Results shows the efficacy of Algorithm in identifying the fault. The auxiliary cell is replaced while the fault occurs in the main cell thus making the uninterrupted working of the Multi-Level Inverter (MLI) in the Induction Motor Drive (IMD).