Diagnosing of Bearing Faults in Induction Motor by Adopting DWT-Based Artificial Neural Network (ANN)

Abstract

This paper introduces technology for detecting bearing damage to the 3-phase induction machine that is divided into two stages. In the first stage, the stator current signal (iq) is decomposed by adopting (DWT) and extract RMS values of the current signal (iq). The second stage is to enter the external RMS values of the stator current signal (iq) into the trained artificial neural network to detect these defects. With this mechanism, One can protect the induction motor from damage. This is done by using a simulation program simulink/MATLAB2019. The computed results show that better performance can be achieved using such a technique.