This paper develops a new fibre tracking algorithm to efficiently locate fibre centrelines (skeletons), from X-ray Computed Tomography (X-ray CT) images of carbon fibre reinforced polymer (CFRP), which are then used to generate micro-scale finite element models. Threedimensional images with 330nm voxel resolution of multidirectional [+45/90/-45/0] CFRP specimens were obtained by fast synchrotron X-ray CT scanning. Conventional image processing techniques, such as a combination of filters, delineation of plies, binarisation of images, and fibre identification by local maxima and ultimate eroding points, were tried first but found insufficient to produce continuous fibre centrelines for segmentation, especially in regions with highly congested fibres. The new algorithm uses a global overlapping stack filtering step followed by a local fibre tracking step. Both steps are based on the Bayesian inference theory.The new algorithm is found capable of efficiently define fibre centrelines for the generation of micro-scale finite element models with high fidelity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.