Diagnosis of Motor Faults Using Sound Signature Analysis

Abstract: The objective of this paper is to present recent developments in the field of Induction motor fault signature analysis with particular regard to Sound signature analysis of induction motor of fan. The different types of fan faults that can be identified from the sound signature analysis [1] are, for example, rotor faults, bearing faults, unbalances wings etc. Corresponding to the above-mentioned faults, many types of machine fault signature analysis techniques [2] have been proposed for motor faults detection and diagnosis. These techniques include vibration monitoring, motor current signature analysis (MCSA) [3–6], electromagnetic field monitoring [7], chemical analysis, temperature measurability [8, 9], infrared measurement, acoustic noise analysis [10], and partial discharge measurement [11, 12]. Among these methods, vibration analysis, current analysis and Sound signature analysis are the most popular due to their easy measurability, high accuracy, and reliability.

Keywords: sound signature, motor faults, induction motor, fault detection techniques, wavelet analysis, sensor less monitoring