Classification of rotor fault in induction machine using Artificial Neural Networks

In this paper, we have developed a feedforward neural networks to detect and to diagnosis rotor fault on induction motors using stator currents. In the first step, causes and effects of rotor fault have been studied, particularly, the number of broken bars has been considered. Then, in the second step, the number of broken rotor bars has been localized by Artificial Neural Networks (ANN), using the Fast Fourier Transform. Simulation results show that the Neural Network proposed approach presents a good tools for the diagnostic of induction machines.