Parameter estimation for electric motor condition monitoring

This paper presents parameter identification technique to quantify the faults in motor condition monitoring. Genetic Algorithm (GA) has been used as a key technique to estimate the motor parameters. The zero-sequence voltage equation for the stator has been used as a model to estimate motor stator parameters - the stator resistance and the stator leakage inductance. The comparison of the parameter estimation by the earlier Recursive Least Square (RLS) method and the proposed GA technique has been discussed. The GA technique shows better accuracy in the estimation. The estimation has been tested on both simulations and a real test motor.