Super-Resolution Processing of Synchrotron CT Images for Automated Fibre Break Analysis of Unidirectional Composites.

ABSTRACT: Fibre breaks govern the strength of unidirectional composite materials under tension. The progressive development of fibre breaks is studied using in situ X-ray computed tomography, especially with synchrotron radiation. However, even with synchrotron radiation, the resolution of the time-resolved in situ images is not sufficient for a fully automated analysis of continuous mechanical deformations. We therefore investigate the possibility of increasing the quality of low-resolution in situ scans by means of super-resolution (SR) using 3D deep learning techniques, thus facilitating the subsequent fibre break identification. We trained generative neural networks (GAN) on datasets of high-(0.3 μm) and low-resolution (1.6 μm) statically acquired images. These networks were then applied to a lo

SUBMITTER: Karamov R 

PROVIDER: S-EPMC10180951 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature