基于经验小波变换的干耦合超声检测Lamb波信号分析
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摘要
为提取出干耦合Lamb波检测信号中的有用信息,采用经验小波变换(empirical wavelet transform,EWT)对检测信号进行分析。首先定义一组经验尺度和经验小波函数,根据傅里叶变换结果对信号频谱进行分割,提取出围绕中心频率具有紧支撑特性的不同频段;然后通过选择合适函数,建立紧支撑的小波框架;最后对信号进行经验小波变换,得到不同的分解模态。针对玻璃纤维复合材料板的干耦合Lamb波检测实验结果表明:采用EWT方法能够分解出信号中不同的固有模态,揭示信号的频率结构,区分缺陷的大小,反映Lamb波传播特性。与经验模态分解(empirical mode decomposition,EMD)方法相比,EWT方法计算量小,分解模态少,没有虚假和无法解释的分量,显示该方法的优越性。
In order to extract useful information in the dry-coupled Lamb wave detection signal, the empirical wavelet transform(EWT) method was used to analyze the detection signal. Firstly, a set of empirical scales and empirical wavelet functions were defined. According to the results of Fourier transform, the spectrum of the signal was segmented, and different frequency bands with tightly-supported characteristics around the center frequency were extracted. Then a tightly supported wavelet frame was established by selecting an appropriate function. Finally, the signal was subjected to empirical wavelet transform to obtain different decomposition modes. The experimental results of dry-coupled Lamb wave detection for glass fiber composite panels showed that the EWT method can be used to decompose different intrinsic modes in the signal, which reveal the frequency structure and the size of the defect, and reflect the propagation characteristics of Lamb wave.Compared with the EMD method, the EWT method has little computation, less decomposition modes and no false and unexplained components, which shows the superiority of the method.
In order to extract useful information in the dry-coupled Lamb wave detection signal, the empirical wavelet transform(EWT) method was used to analyze the detection signal. Firstly, a set of empirical scales and empirical wavelet functions were defined. According to the results of Fourier transform, the spectrum of the signal was segmented, and different frequency bands with tightly-supported characteristics around the center frequency were extracted. Then a tightly supported wavelet frame was established by selecting an appropriate function. Finally, the signal was subjected to empirical wavelet transform to obtain different decomposition modes. The experimental results of dry-coupled Lamb wave detection for glass fiber composite panels showed that the EWT method can be used to decompose different intrinsic modes in the signal, which reveal the frequency structure and the size of the defect, and reflect the propagation characteristics of Lamb wave.Compared with the EMD method, the EWT method has little computation, less decomposition modes and no false and unexplained components, which shows the superiority of the method.
引文
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[3]HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J].Proc.Roy.Soc.London A,1998,454(1971):903-995.
[4]TORRES M E,COLOMINAS M A,SCHLOTTHAUER G,et al.A complete ensemble empirical mode decomposition with adaptive noise[J].Proc.IEEE Int.Acoust.Speech Signal PROCESS,2011(5):4144-4147.
[5]HOU T Y,SHI Z.Adaptive data analysis via sparse timefrequency representation[J].Adv.Adapt.Data Anal.,2011(2):1-28.
[6]JAFFARD S,MEYER Y,RYAN R D.Wavelets:Tools for Science and Technology[M].USA:SIAM,2001.
[7]MALLAT S.A wavelet tour of signal processing:The spare way,3rd ed[M].USA:Elsevier/Academic,2009.
[8]MEYER Y.Wavelets,vibrations and scalings[M].USA:Amer.Math.Soci.1997.
[9]MALVAR H S.Lapped transforms for efficient transform/subband coding[J].IEEE Trans.Acoust,Speech Signal Process,1990,38(6):969-978.
[10]MEYER F G,COIFMAN R R.Brushlets:A tool for directional image analysis and image compression[J].Appl.Computat.Harmon.Anal,1997,4(2):147-187.
[11]DAUBECHIES I,LU J,WU H T.Synchrosqueezed wavelet transforms:An empirical mode decomposition-like tool[J].Appl.Computat.Harmon.Anal,2011,30(2):243-261.
[12]JEROME G.Empirical wavelet transform[J].IEEETRANSACTIONS ON SIGNAL PROCESSING,2013,61(16):3999-4010.
[13]李志农,朱明,褚福磊,等.基于经验小波变换的机械故障诊断方法研究[J].仪器仪表学报,2014,35(11):2423-2431.
[14]李沁雪,廖晓文,张清华,等.基于EWT和多尺度熵的轴承特征提取及分类[J].轴承,2016(1):48-52.