DocumentCode :
2641456
Title :
Wind turbine bearing failure detection using generator stator current homopolar component ensemble empirical mode decomposition
Author :
Amirat, Yassine ; Choqueuse, Vincent ; Benbouzid, Mohamed
Author_Institution :
ISEN, Brest, France
fYear :
2012
fDate :
25-28 Oct. 2012
Firstpage :
3937
Lastpage :
3942
Abstract :
Failure detection has always been a demanding task in the electrical machines community; it has become more challenging in wind energy conversion systems because sustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. Indeed the most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the generator health degeneration, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper provides then an assessment of a failure detection techniques based on the homopolar component of the generator stator current and attempts to highlight the use of the Ensemble Empirical Mode Decomposition (EEMD) as a tool for failure detection in wind turbine generators for stationary and non stationary cases.
Keywords :
electric generators; failure (mechanical); stators; wind power; wind turbines; cost reduction; current homopolar component; electrical machines community; ensemble empirical mode decomposition; failure detection techniques; generator health degeneration; generator stator current; proactive response; productivity maximisation; wind energy conversion systems; wind farm sustainability; wind farm viability; wind turbine bearing; wind turbine generators; Alternators; Connectors; Helium; Monitoring; Reliability; Training; Wind turbine; bearing failure; ensemble empirical mode decomposition; homopolar component; induction generator; stator current;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
Conference_Location :
Montreal, QC
ISSN :
1553-572X
Print_ISBN :
978-1-4673-2419-9
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2012.6389263
Filename :
6389263
Link To Document :
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