INTER-TURN FAULT DETECTION IN INDUCTION MOTOR USING STATOR CURRENT WAVELET DECOMPOSITION

ABSTRACT A new method for the early detection of inter-turn faults in an induction motor is proposed in this paper. Simulation and experimental results shows that the proposed method works perfectly even under the dynamic load conditions of the induction motor. Reference frame transformation theory forms the backbone of the modeling of inter-turn fault of induction motor. The fault model has been prepared based on the synchronous reference frame. Mathematical model thus developed is then simulated using MATLAB/ SIMULINK®. Stator current signal were acquired using hall-effect sensor and NI Labview, which is further processed using Matlab software to obtain their wavelet coefficients up to 6 th level of decomposition. Statistical features of these wavelet coefficients were then extracted, analysed and it clearly indicates the interquartile range as a feature. A unique characteristic of the interquartile range of the 6 th level detailed wavelet coefficient obtained from the stator current is identified as a doable feature for the detection of inter-turn fault. Even the transient changes occurred in the stator current signal can be identified using this method, which is its advantage over the conventional signal processing techniques. A laboratory set up was made with the inter-turn fault intentionally introduced in the stator winding of the induction motor to verify the proposed method. The interquartile range of the 6 th level detailed wavelet coefficient of the stator current varies as the fault is developed in the motor, in the case of experimental data as well. It is observed that the results obtained from this experimental setup closely matches with the simulation results, which confirms the compatibility of the feature and correctness of the model