A Non-Invasive Method for Condition Monitoring of Induction Motors Operating Under Arbitrary Loading Conditions

The literature review presents the various kinds of existing condition monitoring methods and highlights the need for an economical, intelligent fault diagnosis system for the motors that are being used in variable load applications. The motor current signature analysis (MCSA) has been used widely in previous research work for fault detection of the motor at full-load conditions. However, MCSA cannot detect faults under low-load conditions of the motor. This paper proposes the instantaneous power analysis (IPA) method for the bearing fault detection at various loading conditions of the motor. The experimental results indicate that IPA has more capability to detect faults under low-load conditions as compared to MCSA. Also, it has been shown that IPA carries an additional characteristic vibration frequency component which provides an extra piece of information that can be utilized in a reliable intelligent condition monitoring system. The proposed method has been validated through experiments at five different loading conditions of the motor.