Detection of wind turbine blades damage by spectrum-recognition using gaussian wavelet-entropy

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.