A Rough Sets Based Classifier for Induction Motors Fault Diagnosis

This paper describes the ongoing research on Rough Sets based classifier applied to Induction Motors fault diagnosis through Motor Current Signature Analysis (MCSA). The results of mechanical failures detection and how a Rough Sets based classifier is used as a monitoring system using current signature analysis in predictive maintenance are also described in this paper. Key-Words: Predictive Maintenance; Three-phase induction motor; Motor Current Signature Analysis; Rough Sets based classifier; Fault diagnosis.

[1]  Zdzislaw Pawlak,et al.  Rough classification , 1984, Int. J. Hum. Comput. Stud..

[2]  Mohamed El Hachemi Benbouzid A review of induction motors signature analysis as a medium for faults detection , 2000, IEEE Trans. Ind. Electron..

[3]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[4]  Jerzy Stefanowski,et al.  Rough classification in incomplete information systems , 1989 .

[5]  W. T. Thomson,et al.  Current signature analysis to detect induction motor faults , 2001 .

[6]  T.G. Habetler,et al.  Motor bearing damage detection using stator current monitoring , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[7]  V.H. Quintana,et al.  Classification of power system operation point using rough set techniques , 1996, 1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929).