Title :
Switch fault diagnosis of PM brushless DC motor drive using adaptive fuzzy techniques
Author :
Awadallah, M.A. ; Morcos, M.M.
Author_Institution :
Kansas State Univ., Manhattan, KS, USA
fDate :
3/1/2004 12:00:00 AM
Abstract :
An adaptive neuro-fuzzy inference system (ANFIS) is developed to diagnose open switch faults of PM brushless dc motor drives. Features extracted under healthy and faulty operations using wavelet transform are used to train ANFIS. Testing of the proposed diagnostic system shows it could not only diagnose the fault but identify the faulty switch as well. Good agreement between experimentation and simulation is obtained.
Keywords :
adaptive systems; brushless DC motors; fault location; fuzzy neural nets; inference mechanisms; motor drives; permanent magnet motors; wavelet transforms; PM motor drive; adaptive neuro-fuzzy inference system; brushless DC motor drive; feature extraction; machine fault diagnosis; switch fault diagnosis; wavelet transform; Bridges; Brushless DC motors; Commutation; DC motors; Fault diagnosis; Feature extraction; Fuzzy systems; Switches; System testing; Wavelet transforms;
Journal_Title :
Energy Conversion, IEEE Transactions on
DOI :
10.1109/TEC.2004.824213
