학술논문

Research of Two Phase Flow Signal Denoising Based on Fractional Wavelet Transform
Document Type
Conference
Source
2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS) Data Driven Control and Learning Systems Conference (DDCLS), 2018 IEEE 7th. :698-703 May, 2018
Subject
Computing and Processing
Robotics and Control Systems
Wavelet transforms
Noise reduction
Wavelet analysis
Wavelet domain
Fourier transforms
Signal to noise ratio
fractional Fourier transform
fractional wavelet transform
denoising
gas-liquid two-phase flow
Language
Abstract
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.