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Failure Forecast Diagnosis of Small Wind Turbine using Acoustic Emission Sensor  

Bouno Toshio (Dept. of Electrical and Electronic Engineering University of Miyazaki)
Yuji Toshifumi (Dept. of Nuclear Engineering, Tokyo Institute of Technology)
Hamada Tsugio (Dept. of Electrical Engineering, Miyakonojo College of Technology)
Hideaki Toya (Dept. of Electrical Control Engineering, Tsuyama College of Technology)
Publication Information
KIEE International Transaction on Electrical Machinery and Energy Conversion Systems / v.5B, no.1, 2005 , pp. 78-83 More about this Journal
Abstract
Currently in Japan, the use of the small wind turbine is an upward trend. There are already many well established small wind turbine generators in use and their various failures have been reported. The most commonly sighted failure is blade damage. Thus the research purpose was set to develop a simple failure diagnostic system, where an Acoustic Emission (AE) signal was produced from the failure part of a blade which was measured by AE sensor. The failure diagnostic technique was thoroughly examined. Concurrently, the damage part of the blade was imitated, the AE signal was measured, and a FFT(Fast Fourier Transform) analysis was carried out, and was compared with the output characteristic. When one sheet of a blade was damaged 40mm or more, the level was computed at which failure could be diagnosed.
Keywords
small wind turbine; AE sensor; failure diagnosis; fast fourier transform; peak value; blade;
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