Title :
Diagnosis of electrical and mechanical faults of induction motor
Author :
Nakamura, H. ; Yamamoto, Y. ; Mizuno, Y.
Author_Institution :
TOENEC Corp., Nagoya
Abstract :
This paper proposes a new method for fault diagnosis of induction motors based on Hidden Markov Model, which is widely used in the field of speech recognition. In order to carry out pattern recognition, current waveforms running in stator winding are analyzed for motors with short circuit fault in stator windings or with broken rotor bars. Frequency spectrum of current are also investigated. The usefulness of the proposed diagnosis method is verified through pattern recognitions for arbitrary current waveforms obtained by experiments.
Keywords :
fault diagnosis; hidden Markov models; induction motors; pattern recognition; stators; current waveforms; electrical fault diagnosis; hidden Markov model; induction motor; mechanical fault diagnosis; pattern recognition; rotor bars; short circuit fault; stator winding; stator windings; Bars; Circuit faults; Fault diagnosis; Hidden Markov models; Induction motors; Pattern analysis; Pattern recognition; Rotors; Speech recognition; Stator windings;
Conference_Titel :
Electrical Insulation and Dielectric Phenomena, 2006 IEEE Conference on
Conference_Location :
Kansas City, MO
Print_ISBN :
1-4244-0547-5
Electronic_ISBN :
1-4244-0547-5
DOI :
10.1109/CEIDP.2006.311984
