Diagnosis of damaged wind turbine blade by noise characteristics

Abstract

This study has proposed two estimation models of noise signal characteristic diagnosis based on time-domain and time-frequency analysis. The diagnosis of time domain was based on the fractal theory, and the result of fractal dimensions was converted into Gauss distribution, so as to provide a feature extraction for abnormality diagnosis of damaged blade. In addition, for time-frequency analysis, the wavelet methodwas used as the basis of signal analysis. The Morlet transform and mother wavelet were used for wavelet analysis of signal to obtain the result of time-frequency analysis. When the time axis was integrated, the marginal spectrum of frequency domain was obtained, and statistical regression analysis was used to provide another method of feature extraction diagnosis. The wind turbine blade signal was measured in actual wind turbine operation at Changhua Coastal Industrial Park for diagnostic analysis, so as to provide a multi-diagnostic model of wind turbine blade prewarning and health management models.