Universal Detection and Classification Index of Incipient Rotor Bars Fault in Squirrel-Cage Motors

Abstract

With the advent of current signature analysis algorithms, many industries will be driven toward on-line, noninvasive diagnostic solutions. This paper proposes a method that can provide the information to diagnose rotor problems accurately and quantitatively using motor dynamic eccentricity sidebands as a universal rotor fault detection and classification index. Moreover, related research into the effects of rotor fault isolation from load torque will enable a determination of the relative severity of a broken rotor bar or any type of air-gap asymmetry. The objective of this paper is to also implement a proof-of-concept laboratory test of the suggested method. Three induction machines were tested on a dynamometer at twenty-eight loading points and different source and load conditions, verifying detection accuracy of the implemented technique.