Application of Diagnostic Technique for Noise Characteristic to Judging Wind Turbine Blade Abnormity in Actual Operation
Journal
Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao
Journal Volume
38
Journal Issue
2
Pages
145-153
Date Issued
2017
Author(s)
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. ? 2017, Chinese Mechanical Engineering Society. All right reserved.
Subjects
Electric utilities; Extraction; Feature extraction; Frequency estimation; Regression analysis; Turbomachine blades; Wind; Wind turbines; Diagnostic techniques; Marginal spectrum; Morlet Wavelet; Noise characteristic; Statistical regression analysis; Taiwan power companies; Time frequency analysis; Time varying analysis; Turbine components
SDGs
Other Subjects
Electric utilities; Extraction; Feature extraction; Frequency estimation; Regression analysis; Turbomachine blades; Wind; Wind turbines; Diagnostic techniques; Marginal spectrum; Morlet Wavelet; Noise characteristic; Statistical regression analysis; Taiwan power companies; Time frequency analysis; Time varying analysis; Turbine components
Type
journal article
