Hall Effect Sensor and Artificial Neural Networks Applied on Diagnosis of Broken Rotor Bars in Large Induction Motors

This paper presents the use of the neural networks techniques in order to help on diagnosis of broken bars in large induction motors in real time. The obtained signal of the Hall effect sensor is applied in an artifical neural network to identify a fault and to estimate the number of broken bars. Simulation results are presented from the model implemented in the SIMULINK/MATLAB tool.