Artificial Neural Network-based fault diagnostics of an electric motor using vibration monitoring

In this study, a motor condition diagnostic was achieved through the implementation of an Artificial Neural Network (ANN), successfully applying into a predictive maintenance system. Electrical motors were monitored to obtain data to train the ANN. Out of these monitoring, vibration signatures were used as the input layer, and the motor condition was used as the expert training information. The main objective was to apply neural networks to a condition based predictive maintenance in order to detect the type of system's failure. As a result, the expert system can be utilized to decrease the possible failures in operating system and increase the availability and effectiveness of a system.