Fuzzy Neural Network based On-line Stator Winding Turn Fault Detection for Induction Motors

A fuzzy neural network based on-line turn fault detection approach for induction motors is proposed in this paper. B-spline membership fuzzy neural network is employed to detect turn fault, since the selection of the weighting factors, the knot positions and the control points of the B-spline membership fuzzy-neural networks is crucial to obtaining good approximation for complex nonlinear systems, a genetic algorithm with an efficient search strategy is developed to optimize network parameters. Based on it, Experiments are carried out on a special rewound laboratory induction motor, the results show fuzzy neural network based diagnosis model determines the shorted turns exactly, and is more effective than the parameters estimation method under the condition of detecting a slowly developing turn fault.