激光超声信号去噪的经验模态分解实现及改进  

Realization and improvement of laser ultrasonic signal denoising based on empirical mode decomposition

作　　者：罗玉昆[1] 罗诗途[1] 罗飞路[1] 潘孟春[1] 

机构地区：[1]国防科学技术大学机电工程与自动化学院,湖南长沙410073

出　　处：《光学精密工程》2013年第2期479-487,共9页Optics and Precision Engineering

基　　金：中国博士后科学基金面上资助项目(No.20100481509)

摘　　要：考虑激光超声检测过程中噪声对缺陷和材料特征分析和检测的影响,本文以激光超声信号去噪为目的,研究了基于经验模态分解(EMD)的激光超声信号时间尺度滤波过程。针对分解过程中固有模态函数(IMF)上有用信号与噪声的混叠现象对重构信噪比的影响,结合信号多模态和宽频带的特点,提出了基于峰度检验策略的时域加窗方法。该方法通过局部峰度检验判断重构起点附近IMF中有用信号的位置及信噪分界点,利用Turkey-Hanning窗保存有用信号,抑制噪声,实现信号与噪声的解混叠,改善重构信号质量。仿真和实验结果表明,该方法具有良好的自适应性,有效识别并分离了信号和噪声成分,信噪改善比达14dB以上,相对原始方法提升了3dB,相对性能增强了20%,并且改进效果随信号受污染程度的加重而愈发突出,有望在高噪声水平下发挥优势。To suppress the influence of noises associated with a laser ultrasonic testing process on the detection for defects and material parameters,the time-scale filtering process of laser ultrasonic signals is studied based on Empirical Mode Decomposition（EMD）.As the aliasing between useful signals and noises in Intrinsic Mode Functions（IMF） will reduce the reconstruction signal-to-noise ratio,a time-windowing method with kurtosis test strategy is proposed considering the multi-mode and broad-band characteristics of laser ultrasonic signals.With proposed method,the positions and boundaries of useful signals in IMFs near the reconstruction start are estimated by computing the local kurtosis values.Then,a Turkey-Hanning window is used to preserve useful signals and suppress the noises.Thus,aliasing removal is achieved and the reconstruction signal quality is improved.Simulation and experimental data show that the method proposed has a good self-adaptability,and it recognizes and separates the signal and noise components effectively.The signal-to-noise improvement factor is over 14 dB,which improves the original method by 3 dB and enhances the performance by 20%.Besides,as the heavier the signal is polluted,the better the improving effect is,the advantage of the method is expected to be given in high noise levels.

关 键 词：激光超声 信号去噪 经验模态分解 峰度检验 时域加窗 

分 类 号：TN249[电子电信—物理电子学] TP391[自动化与计算机技术—计算机应用技术]