Carbon fiber reinforced polymers (CFRPs) are widely used in fields such as aviation and aerospace. However, subtle defects can significantly impact the material's service life, making defect detection a critical priority. In this paper, delamination defects in CFRP are detected using line laser infrared thermography, and a defect characterization algorithm that combines differential thermography with a frequency-domain filter is proposed. This approach effectively eliminates the trailing phenomenon caused by line laser scanning and produces defect feature images with a higher signal-to-noise ratio. The size of the processed defects is then measured using pixel deviation values combined with K-means edge detection. The results show that the measured dimensions of defects are larger than the actual dimensions at the initial stage of cooling after excitation and smaller than the actual dimensions at the end of the cooling phase. The maximum measurement error for defect size was 2.74 mm2 throughout the measurement interval. In addition, defect depth evaluation was achieved by fitting the curve of defect depth against the peak value in the frequency domain, with the resultant R-square value were all higher than 0.9877. This confirms the validity and accuracy of the methodology used in this study.
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