Diagnosis of stator winding turn to turn fault of induction motor using space vector pattern based on neural network

In this paper, first space vector model of symmetrical induction motor is extended to asymmetrical structure due to stator turn to turn fault. Then a novel scheme in order to diagnosis of this fault is proposed where a neural network with space vector pattern has used. In this scheme, new indexes using space vector properties of stator voltage and current, is defined that oscillation of this indexes is due to unbalancing of stator voltage and current. This scheme using suitable learning of neural network is able to recognize stator winding turn-fault regardless admissible unbalancing of the input voltage, balanced variation of three phase voltage, and admissible variation of load torque. Simulations were performed in Matlab/Simulink environment to validate the proposed method.