An Automated Image Processing Method to Detect Progressive Matrix Cracking in CFRP Composites Using X-Ray Micro-Computed Tomography

Abstract Carbon Fibre Reinforced Polymer (CFRP), thanks to their excellent specific stiffness and strength compared to metals, composites are considered as suitable materials for liquid hydrogen LH 2 tanks. However, the cryogenic operating conditions required for LH₂ storage (20 K) present significant challenges to the structural integrity of CFRP, especially due to matrix cracking induced by thermal cycling and mismatched thermal expansion coefficients between fibres and matrix. Such damage can compromise the leak tightness of a tank and lead to hydrogen release. This paper presents a method to automatically detect, count and measure matrix crack density, under static loading, using X-ray micro-computed tomography (µCT) in CFRP laminates through digital image processing. By considering the image dimensions, the method calculates crack density along the different plies of a specimen. The proposed method was used for inspecting the progression of transverse matrix cracks in cross-ply CFRP laminates. The results demonstrate that µCT is an effective non-destructive evaluation (NDE) technique for characterising early-stage matrix cracking in CFRP laminates. The proposed method achieved a minimum detectable crack density of 0.05 cracks/mm.