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In this work, the induction motor damage detection based on sound signal was developed by using simple microphone and sound card as sound data grabber to reduce the cost of instrument. For that purpose, the induction motor apparatus was constructed, and the artificial damages were applied to induction motor to make the conditions of unbalance, broken rotor, and bearing fault. The Fast Fourier Transform (FFT) and wavelet transform were then used to process sound signal, to show the signature of each type of damage. The results show that the unbalance exhibited very clear large wavelet coefficient in the frequency of 1x rotational speed. In the broken rotor bar damage, the strong red color of wavelet graph appeared in the sideband frequencies associated with the broken rotor bar (f BB ). Further more, the bearing fault case showed the different color contour of wavelet graph in the ball-pass outer raceway frequency (f BPOF ). It can be concluded that the using of sound signal and simple microphone were powerful tools to detect unbalance, broken rotor and bearing fault in induction motor.

The using of sound signal and simple microphone to detect damages in induction motor