关键字：Two phase flow;Frequency domain analysis - Learning systems - Signal analysis - Signal denoising - Wavelet transforms

摘要：The wavelet transform(WT) is only limited to the time-frequency analysis of the signal, and denoising method based on WT will ignore the details of the signal, which can result in the loss of useful components in the signal. Although the fractional Fourier transform(FRFT) breaks through the limitation of the time-frequency domain, that is it can analyze the signal in the fractional domain, it cannot represent the local characteristics of the signal. In this paper, we propose a method of fractional wavelet transform(FRWT), which not only retains the advantages of multi-resolution analysis of wavelet analysis, but also retains the function of FRFT signal in the fractional order domain, in addition, the method can make up for the defects of FRFT which can not characterize the local information of the signal. We apply this method to the denoising of two-phase flow signals and find that achieve a better performance.<br/> &copy; 2018 IEEE.

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