Title :
Diagnosis of short circuit fault of induction motor based on hidden markov model
Author :
Nakamura, H. ; Yamamoto, Y. ; Mizuno, Y.
Author_Institution :
TOENEC Corp., Nagoya
Abstract :
Short circuit of a stator winding is one of the most probable faults of induction motors. Once the fault occurs, the current waveform flowing in the winding will be distorted from sinusoidal depending on the degree of short circuit fault. In a series of experiments using induction motors with artificially introduced short circuit fault in stator windings, current waveforms were recorded and analyzed. A novel diagnostic system based on Hidden Markov Model was confirmed effective for diagnosis of short circuit faults through pattern recognition of current waveforms obtained in experiments.
Keywords :
Markov processes; electrical faults; fault diagnosis; induction motors; stators; windings; current waveform; hidden Markov Model; induction motors; short circuit fault; stator winding; Circuit faults; Fault diagnosis; Hidden Markov models; Induction motors; Laboratories; Monitoring; Pattern recognition; Speech recognition; Stator windings; Voltage;
Conference_Titel :
Electrical Insulation and Dielectric Phenomena, 2007. CEIDP 2007. Annual Report - Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-1482-6
Electronic_ISBN :
978-1-4244-1482-6
DOI :
10.1109/CEIDP.2007.4451509