Characterization of CFRP Defects Based on Differential Phase Infrared Image Reconstruction

The widespread utilization of carbon fiber reinforced polymers (CFRPs) in various fields, such as aviation and aerospace, has been observed. Nonetheless, the presence of subtle defects severely impacts the material's service life, rendering the detection of such defects a top priority. In this study, we utilize infrared thermography to identify defects in CFRP. We introduce a novel method grounded in the principles of differential phase infrared image reconstruction. This approach adeptly mitigates the tail-dragging artifact stemming from line laser scanning and reduces the inherent thermal wave background noise associated with phase-locked pulse detection. Consequently, it facilitates the extraction of more precise defect information from the infrared matrix, enhancing the overall diagnostic efficacy. The findings demonstrate that the reconstructed image exhibits sharper defect boundaries. Through a comparative analysis of the signal-to-noise ratios within defective image blocks, this investigation showcases outstanding noise suppression in non-defective regions. This effectively addresses the limitations associated with near-Gaussian light sources in heat wave detection.