Diagnosis of eccentricity and broken rotor bar related faults of induction motor by means of motor current signature analysis

Abstract

Detection of faults in electrical motors is very important for avoiding unpredicted failures of the machines. Early detection and diagnosis of faults that may occur are desirable to ensure that operational effectiveness of an induction motor can be improved. In this paper, faults detection and classification using motor current signature analysis (MCSA) are presented. A series of simulations using the models of three phase cage induction motor is performed in different fault conditions, such as static, dynamic and mixed eccentricity and broken rotor bars. Designed models were implemented with the help of finite element method to provide data that makes it possible to diagnose presence of any type of faults, as well as to analyze obtained and calculated results. Models were designed on the basis of characteristics and parameters of real motor. The results are illustrated in the form of graphs and tables that make visible illustration for effectiveness of the used diagnosis method.