Title :
Advanced signal processing techniques for fault detection and diagnosis in a wind turbine induction generator drive train: A comparative study
Author :
Ahmar, E. Al ; Choqueuse, V. ; Benbouzid, M.E.H. ; Amirat, Y. ; El Assad, J. ; Karam, R. ; Farah, S.
Author_Institution :
Lab. Brestois de Mcanique et des Systmes (LBMS EA 4325), Univ. of Brest, Brest, France
Abstract :
This paper deals with the diagnosis of Wind Turbines based on generator current analysis. It provides a comparative study between traditional signal processing methods, such as periodograms, with more sophisticated approaches. Performances of these techniques are assessed through simulation experiments and compared for several types of fault, including air-gap eccentricities, broken rotor bars and bearing damages.
Keywords :
asynchronous generators; fault location; signal processing; wind turbines; fault detection; fault diagnosis; generator current analysis; induction generator drive; signal processing; wind turbine; Bars; Monitoring; Rotors; Signal resolution; Spectrogram; Time frequency analysis; Wind turbines; failure diagnosis; motor current signature analysis; time-frequency signal processing methods; wavelet analysis;
Conference_Titel :
Energy Conversion Congress and Exposition (ECCE), 2010 IEEE
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-5286-6
Electronic_ISBN :
978-1-4244-5287-3
DOI :
10.1109/ECCE.2010.5617707
