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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/3022
Title: Application of Diagnostic Technique for Noise Characteristic to Judging Wind Turbine Blade Abnormity in Actual Operation
Other Titles: 噪音特徵診斷技術應用在風機葉片實際運轉異常之判斷
Authors: Chao-Nan Wang
Yao-Chi Tang 
Keywords: Morlet Wavelet;Marginal Spectrum;Regression Analysis;Feature Extraction
Issue Date: 1-Apr-2017
Publisher: 中國機械工程學會
Journal Volume: 38
Journal Issue: 2
Start page/Pages: 145-153
Source: Journal of the Chinese Society of Mechanical Engineers
Abstract: 
This paper provides an estimation model for noise signal characteristic diagnosis based on the Time-Frequency analysis technique. The marginal spectrum and statistical regression analysis is used as an estimation method for feature extraction. In order to approach the actual conditions, with the assistance of Department of Renewable Energy, Taiwan Power Company, the noise signals of a blade-damaged wind turbine and normal wind turbine are measured. In the case of low wind speed and noise, the time-frequency spectra are compared, and the feature magnification indicator is analyzed. The results show that the blade crack is caused by high frequency noise, mainly above 4000Hz. The time-varying analysis of the indicator shows that the index value is apparently enlarged when the damaged blade rotation is measured by microphone, and the number of damaged blades can be obtained.
URI: http://scholars.ntou.edu.tw/handle/123456789/3022
ISSN: 0257-9731
DOI: ://WOS:000401682600004
10.29979/JCSME
Appears in Collections:系統工程暨造船學系

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