Multi-shape Crack Shape Characterization of CFRP Based on Infrared Thermography

When using infrared thermography inspection methods to characterize the shape of surface defects in CFRP materials, traditional methods are mainly based on the analysis of infrared images at a single point in time, which makes it difficult to characterize geometrical features with complex shapes. In order to comprehensively analyze the performance of defects in different heating stages, this paper adopts the optimized contour extraction method to obtain the closed contour, and then constructs a fusion model of multi-temporal contours based on the Hausdorff distance function combined with the iterative calculation of weighted averaging method in order to more accurately characterize the defects in the final boundary morphology, and the fitting degree is higher than 95 %; For the selection of edge detection algorithms, this paper compares four commonly used edge detection algorithms, Canny, Sobel, Prewitt and Roberts, and the Canny edge detection algorithm is the most suitable for this study from the fitting degree quantization; the morphology of the defects in the practical application is affected by the secondary damages, the external stresses and the material structure, and often presents complex geometric features. In this paper, multi-shape cracks are processed and characterized separately and the fitting degree is higher than 90 %. This experimental study not only improved the shape characterisation capabilities of infrared detection, but also provided more reliable technical support for the identification and assessment of complex defects.