Spectral analysis for identifying faults in induction motors by means of sound

Induction motors are critical components for most industries. Induction motors failures may yield an unexpected interruption at the industry plant. Several conventional vibration and current analysis techniques exist by which certain faults in rotating machinery can be identified. Ever since the first motor was built, plant personnel have listened to the noises emanating from machines; with enough experience, a listener may make a fairly accurate estimate of the condition of a machine. Although there are several works that deal with vibration and current analysis for monitoring and detection of faults in induction motors, the analysis of sound signals has not been sufficiently explored as an alternative non-invasive monitoring technique. The contribution of this investigation is the development of a condition monitoring strategy that can make reliable assessment of the presence of a specific fault condition in an induction motor with a single fault present through the analysis of sound signal. The proposed methodology is based on the combination of Intrinsic Mode Functions (IMFs) and the Fast Fourier Transform (FFT) methods. Results show that the proposed methodology can be applied to sound signal analysis; there this detection technique is suited for detection of fault frequencies in induction motors.