Detection of bearing fault in inverter fed induction motor by transformative techniques

Nowadays, the induction motor with advanced power electronics inverters is being popularized in the industries for variable speed applications. Especially, the Squirrel Cage Induction Motor(SCIM) fed with PWM inverters provides the greater advantages on cost and energy efficiency for varying speed applications as compared to other available industrial solutions. Such kind of drives is recently gathering enormous gratitude in the multi-megawatt industrial drive applications. In the present paper, a Sinusoidal Pulse Width Modulation (SPWM) inverter fed SCIM dynamic simulation model is developed in the recent MATLAB/Simulink environment. Through the model, the bearing fault of the SCIM has been diagnosed by Digital Signal Processing (DSP) based transformative techniques in transient as well as steady state conditions. The time domain and wavelet transform is used for early fault detection purpose while Fast Fourier Transform (FFT) for steady state condition. In the past, it has widely been observed that the FFT algorithm unable to diagnose bearing fault in the transient and no-load conditions. Therefore, in the present work, we are making an attempt to give solution of such problems. As a result, an early diagnosis of bearing fault is possible for all load conditions and may avoid the motor to reach in the ruinous conditions. Therefore, industries may save large revenues.