基于自适应阈值的提升小波包漏磁信号去噪研究

Research on De-noising MFL Signals Based on Adaptive Threshold Lifting Wavelet Package

为了更好地实现对原始漏磁信号噪声的抑制，针对硬阈值函数和软阈值函数中存在的问题，提出一种自适应阈值选择方法，研究了基于该方法的提升小波包降噪算法。采用小波包和提升小波包，分别在硬阈值、软阈值和自适应阈值处理函数下，对含噪信号进行降噪效果的分析和比较，并给出了漏磁信号在自适应提升小波包算法下的降噪效果。仿真结果表明：该方法具有更高的分辨率和近似优化能力，在保留原始漏磁信号有效成分的同时，能更好地去除噪声。

In order to solve the problem of noise reduction in the magnetic flux leakage （MFL）signals better,and the problems in the hard and soft threshold functions,an adaptive threshold function is put forward and a lifting wavelet package de-noising method based on the adaptive threshold function for MFL signals is researched. The noisy signal is de-noised by wavelet package and lifting wavelet package individually adopting hard threshold method, soft threshold method and adaptive threshold method, and the corresponding performance is analyzed. The de-noising performance of adaptive threshold lifting wavelet package for practical MFL signal is given. The research results show that the adaptive threshold lifting wavelet package holds higher resolution and proximal optimization ability which cannot only retain effective composition in the original MFL signals,but also de-noise better.