Research on Fault Detection of Wind Turbine based on Wavelet Analysis

Fast Fourier Transform plays a very important role in signal analysis, but the Fast Fourier Transform traditional mutation fault fan are unable to analyze the trend of fault features, the beginning and the end, and these signals often contain important information, the fault at the same time, the local signal analysis Fast Fourier Transform of fault are also incapable of action. The method of multi scale wavelet theories and Fast Fourier Transform are combined, make up for the deficiency of the Fast Fourier Transform, and the method is applied to the fault diagnosis of fan, and achieved good results, experiments show that, this method can effectively improve the accuracy of fault diagnosis. Wavelet packet analysis due to the high, the low frequency part of the signal local refinement and retention time domain features of the original signal, which has good time-frequency localization characteristics, it can effectively identify the nonstationary signal, to achieve the purpose of fault diagnosis, get more and more extensive application in the field of fault diagnosis. Signal generating fan running most of the nonstationary signal, the wavelet packet analysis technology is used to diagnose the fault has practical significance.