Open AccessResearch on WT-SVD Bilayer Filter Denoising for Downhole Signal
Author(s) -
Yuyan Yang,
Aiqing Huo,
Qi Feng
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/799/1/012030
Subject(s) - singular value decomposition , noise reduction , singular value , signal (programming language) , wavelet , noise (video) , filter (signal processing) , mathematics , algorithm , video denoising , matrix (chemical analysis) , pattern recognition (psychology) , computer science , artificial intelligence , materials science , physics , eigenvalues and eigenvectors , computer vision , image (mathematics) , programming language , quantum mechanics , composite material , object (grammar) , video tracking , multiview video coding
Aiming at the problem of singularity and mutation points after wavelet denoising with improved layered threshold when denoising the downlink signal received in the downhole in rotary steering drilling, a bilayer filtering denoising method based on singular value decomposition is proposed. This method combines wavelet denoising and singular value decomposition denoising, and adopts the WT-SVD bilayer filtering denoising method to construct a matrix of the wavelet improved layered threshold denoising signal, and then performs singular value decomposition and recovery on the matrix signal. The number of selected singular values and the structure of the reconstruction matrix were determined through experiments, and the signal waveforms, signal-to-noise ratio, root mean square error and correlation coefficients of three different denoising methods including singular value decomposition, wavelet improved layered threshold and WT-SVD bilayer filtering are compared and studied. The final experimental results show that the WT-SVD bilayer filtering denoising method is effective.