Fuzzy Logic Based Condition Monitoring of a 3-Phase Induction Motor

Induction motors are widely used in transportation, mining, petrochemical, manufacturing and in almost every other field dealing with electrical power. These motors are simple, efficient, highly robust and rugged thus offering a very high degree of reliability. But like any other machine, they are vulnerable to faults, which if left unmonitored and detected, might lead to catastrophic failure of the machine in the long run. Early detection and diagnosis of faults that may occur are desirable to ensure that, operational effectiveness of an induction motor is improved. In this work, faults detection and classification using fuzzy logic controller is presented. A series of simulations using the models of 3-phase squirrel cage induction motor was performed using MATLAB/Simulink under different faults conditions, such as, break in stator windings, turn-to-turn short-circuit, 3-phase to ground and unbalance in input voltage. Models were designed on the basis of characteristics and parameters of a real motor. The results that were obtained showed that the fuzzy logic controller was able to detect the various faults of the 3-phase induction motor with high accuracy.