DETECTION AND CLASSIFICATION OF FAULTS IN INDUCTION MOTOR USING WAVELET AND FUZZY CONTROLLER

Electrical Engineering

Computer simulation of electric motor operation is particularly useful for gaining an insight into their dynamic behavior and electro-mechanical interaction. A suitable model enables motor faults to be simulated and the change in corresponding parameters to be predicted without physical experimentation. This proposed approach presents both a theoretical and experimental analysis of asymmetric stator winding and rotor faults in induction machines. A three-phase induction motor was simulated and operated under normal healthy operation, with phase to phase winding fault, phase to ground winding fault and short circuit winding fault and with voltage imbalances between phases of supply. The results illustrate good agreement between both simulated and experimental results. For analysis of fault condition conventional method of Fast Fourier transform are first employ and test for different winding fault conditions. Then fuzzy logic controller based on fuzzy rule base design for analysis of stator winding faults. From both the conditions it clear that the FFT analysis only calibrate total harmonics distortion (THD) of faulted voltage and current signal of three phase induction motor input side (stator side). While fuzzy logic controller directly analyzed the type of the fault on induction motor stator winding. Then finally, the results of fuzzy logic controller compare with signal process method as wavelet transform and Fast fourier transform analysis method. Motor model and fault analysis system design in MATLAB 2015 Simulink software. Using this software, motor parameter analysis, fault cases analyzed.

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