Quantification of the internal structure and automatic generation of voxel models of textile composites from X-ray computed tomography data

X-ray computed tomography provides an opportunity for a detailed examination of the inner structure of fibre reinforced composites. Three-dimensional images, obtained with micro-CT, can be used for a realistic modelling of composite materials. All modelling objectives imply the knowledge of the orientations of the fibres inside the composite, which determine the local (anisotropic) properties. This paper investigates application of the structure tensor, a concept from the image processing field, to the determination of the orientations of fibres and to segment the image into the material's components, for the purpose of an automatic generation of a voxel-based description of the representative volume element. The segmentation of the images of CFRP materials into its components is performed by thresholding, or by clustering in a two-dimensional parameter space of the degree of anisotropy and average grey value or one of the components of the orientation vector. Clustering allows not only separating the matrix from the yarns, but also distinguishing the yarns of different primary orientations.