自适应提升小波在漏磁信号处理中的应用

Application of Adaptive Lifting Wavelet in MFL Signal Processing

为了解决在漏磁信号中的噪声抑制问题,采用提升小波变换的方法构造小波,在讨论了第二代小波变换基本原理及其特点的基础上,将自适应性引入提升方案中,提出了第二代小波的改进算法,用先更新后预测的改进提升方案解决自适应性引起的非线性问题。应用该算法对采集的漏磁信号进行消噪处理,并在阈值处理过程中引入了软硬阈值折衷法。仿真结果表明:与传统小波变换的去噪效果相比较,该文的信号降噪处理方法,不仅较好地剔除信号中的噪声,而且保留了原始信号中的有效成分,是一种可行的方法。

The lifting wavelet transform is employed to construct wavelet to solve the problem of noise suppression in the magnetic flux leakage （MFL） inspecting signals. According to the theory and characteristics of the second generation wavelet transform, the improved algorithm is proposed by using adaptive algorithm. The problem of nonlinear caused by adaptive algorithm is solved by using updating-before-predlcating lifting scheme. To verify the effectiveness of the improved lifting scheme, it is applied in the MFL inspecting signals noise reduction and the compromise algorithm between software-threshold and hard-threshold is used in the threshold processing. The simulated results show that our improved lifting scheme has achieved the noise reduction better than that achieved by traditional wavelet transform, which not only de-noises, but also retains the effective composition in the original signal. It is a feasible way to process MFL inspecting signals.