Artificial Neural Networks Eccentricity Fault Detection of Induction Motor

This paper deals with eccentricity fault detection in a induction motor via artificial neural networks. Discriminative features are extracted from magnitude-frequency plot of line current spectra at characteristic frequencies. Based on this data, training and test sets for used artificial neural networks are made. Feedforward and radial basis function neural networks are used for tasks of rotor condition classification. Well trained artificial neural networks are capable to successfully classify rotor condition at medium and full shaft load for choosen features. Simple structure and implementation made them suitably for practical usage.