Title :
Monitoring and diagnosis of induction motors electrical faults using a current Park´s vector pattern learning approach
Author :
Nejjari, H. ; Benbouzid, M.E.H.
Author_Institution :
Univ. of Picardie, Amiens, France
Abstract :
This paper deals with the monitoring and the diagnosis of induction motors electrical faults using a current Park´s vector pattern learning approach. Stator current Park´s vector patterns are, in this case, first learned, using artificial neural networks, and then used to discern between a “healthy” and a “faulty” induction motor
Keywords :
computerised monitoring; electrical faults; fault diagnosis; induction motors; learning (artificial intelligence); machine testing; machine theory; neural nets; power engineering computing; stators; artificial neural networks; current Park´s vector pattern learning approach; electrical fault diagnosis; electrical fault monitoring; induction motors; stator currents; Artificial neural networks; Condition monitoring; Fault diagnosis; Induction motors; Inspection; Neural networks; Real time systems; Sensor systems; Signal detection; Stators;
Conference_Titel :
Electric Machines and Drives, 1999. International Conference IEMD '99
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-5293-9
DOI :
10.1109/IEMDC.1999.769090
