基于奇异值分解的连续小波消噪方法  

Continuous Wavelet Transform Denoising Method Based onSingular Value Decomposition

作　　者：梁霖[1] 徐光华[1] 侯成刚[1] 

机构地区：[1]西安交通大学机械工程学院

出　　处：《西安交通大学学报》2004年第9期904-908,共5页Journal of Xi'an Jiaotong University

基　　金：国家科技攻关"十五"计划专项经费资助项目 (2 0 0 1BA2 0 4B0 5);国家自然科学基金重点资助项目 (50 3 3 50 3 0 )

摘　　要：针对小波软阈值消噪的缺点,提出了一种基于奇异值分解的连续小波消噪方法.通过对小波变换的系数矩阵进行奇异值分解,将其中的信号特征成分和噪声分解到不同的正交子空间中,在子空间中选取集成信号特征成分的奇异值矢量进行重构,从而提取出淹没在噪声中的信号成分.通过仿真数据的对比分析和工程测试信号的应用,表明该方法适用于冲击成分信号的提取,与软阈值消噪法相比,它提取出的信号特征成分更完整,信噪比更高.Aimed at the deficiency of soft-thresholding denoising, a new continuous wavelet transform (CWT) denoising method based on singular value decomposition (SVD) was proposed. The matrix of CWT, which contains signal and noise, was obtained via morlet wavelet, and then, instead of the soft-thresholding method, the SVD was applied to decompose the signal features and noise into different orthogonal sub-spaces. With the reconstruction of the singular vectors in sub-space, the signal features were extracted effectively. Experimental results and industrial measurements on fault diagnosis show that the approach, compared with the soft-thresholding denoising, is an efficient tool to extract impact component from mechanical signals.

关 键 词：连续小波变换 奇异值分解 消噪 

分 类 号：TH133.3[机械工程—机械制造及自动化]