CONDITION MONITORING OF INDUCTION MOTOR USING MOTOR CURRENT SIGNATURE ANALYSIS

Induction machines serve as the cornerstone and driving force of modern manufacturing and production systems. This research aims to monitor and analyse the operating performance of induction motors using motor current signature analysis (MCSA). MCSA is employed to process the current signal of a motor into a frequency spectrum, known as the current signature by applying the Fast Fourier Transform (FFT) algorithm. The underlying principle is that vibration generated in a motor is closely related to the changes of the magnetic field density, and the induced voltage varies with the stator current. A simulation model replicating the behaviour of an induction motor was developed and tested under various operating conditions. Advance techniques were used for data acquisition and analysis. The results obtained from both MATLAB/SIMULINK model and the experimental setup reveal that eccentricity faults in induction motors lead to increased current draw, resulting in transient instability, non-uniform acceleration and pulsating torque due to harmonic distortion.