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激光激励的Lamb波信号具有较宽的频带,且包含多个模态信息。本文采用二维傅里叶变换和时频分析等信号分析技术用于检测信号中的模态成分及缺陷信息识别。首先,对200组激光Lamb波信号进行二维傅里叶变换,得到信号的频率-波数图,可识别出激光Lamb波信号中的低阶A0、S0和高阶模态,并且A0模态能量高,可用于缺陷检测。随后对有、无缺陷状态下Lamb波信号进行连续小波变换,从时频图中识别出缺陷信号的频率成分,进一步提取特定频率下的小波系数幅值信号,实现了缺陷信息的识别。结果表明,二维傅里叶变换能较好地识别激光Lamb波的模态成分,而提取出的连续小波变换系数图,能准确实现缺陷定位。
The laser-excited Lamb wave signal has a wide frequency band and contains a plurality of modalities. In this paper, two-dimensional Fourier transform and time-frequency analysis of signal analysis techniques used to detect the signal modal components and defect information identification. First of all, 200 groups of laser Lamb wave signals are processed by two-dimensional Fourier transform to obtain the frequency-wavenumber map of the signal, which can identify the low-order A0, S0 and high-order modes in the laser Lamb wave signal and have high A0 modal energy, Can be used for defect detection. Then, the continuous wavelet transform of the Lamb wave with and without defect is carried out, the frequency components of the defect signal are identified from the time-frequency diagram, and the amplitude signals of the wavelet coefficients at a specific frequency are further extracted to realize the identification of the defect information. The results show that the two-dimensional Fourier transform can identify the mode components of the laser Lamb wave well, and the extracted continuous wavelet transform coefficient map can accurately locate the defect.