Title :
Detection of wind turbine blades damage by spectrum-recognition using gaussian wavelet-entropy
Author :
Tsai, C.S. ; Hsieh, C.T. ; Lew, K.L.
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
In this paper, a complex continuous wavelet transform (CWT)-based entropy method is proposed to enhance the damage-detection capability of wind turbine blades. By embedding the time-frequency localization features in wavelets, wavelet entropy of acquired signals can be readily computed. This approach can form a quantitative index systematically to detect the damage of blades, anticipating formulating a forewarning mechanism for wind power system. Test results demonstrated the practicality and advantages of the method for the application considered.
Keywords :
blades; entropy; fault diagnosis; signal processing; wavelet transforms; wind turbines; Gaussian wavelet entropy; continuous wavelet transform; damage detection; entropy method; spectrum recognition; time frequency localization feature; wind power system; wind turbine blade damage; Blades; Continuous wavelet transforms; Entropy; Fatigue; Power generation; Renewable energy resources; Time frequency analysis; Wavelet transforms; Wind energy; Wind turbines; complex Gaussian wavelet; wavelet entropy; wind turbine blade;
Conference_Titel :
Anti-counterfeiting, Security, and Identification in Communication, 2009. ASID 2009. 3rd International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-3883-9
Electronic_ISBN :
978-1-4244-3884-6
DOI :
10.1109/ICASID.2009.5276949
