为了提高红外调制热像法对复合材料缺陷的检测能力, 研究了利用基于复Morlet小波相位分析的红外热像序列处理方法。依据热激励调制频率和红外图像采样频率, 自适应地选择小波变换尺度总数, 然后利用复Morlet小波系数相位从原始热像序列重建相位图序列。对含有分层缺陷的玻璃纤维增强复合材料参考试件进行了调制热像检测实验, 以信噪比为评价指标对该方法的实际处理效果进行了定量评定, 并与傅里叶变换法进行了对比。结果表明: 复Morlet小波相位法可以分离调制热像信号的低频和高频噪声, 能稳定地提取试件不同深度的分层缺陷, 对热激励调制频率的变化有良好宽容性, 因此是调制热像法的有效数据处理方法。

In order to increase the detection capability of infrared modulated thermography for defects in composite materials, an infrared image sequence processing method using the complex Morlet wavelet phase analysis was studied. According to the modulation frequency of thermal excitation and the sampling frequency of infrared imaging, the total number of scales used in wavelet transform was selected adaptively, and then a phase image sequence was reconstructed from the raw thermal image sequence by using the complex Morlet wavelet coefficients. An experiment of modulated thermography was performed on a glass fiber reinforced plastic reference sample containing delamination defects, the application effects of the method were quantitatively evaluated and compared with the Fourier transform method by the signal-to-noise ratio. The results show that the complex Morlet wavelet phase method can separate the low frequency and high frequency noise from the thermal image signal, and extract the subsurface defects at different depth robustly; it keeps a good tolerance to the change of the modulation frequency; so it is an effective algorithm of the modulated thermography.