Development of Advanced Tomography Data Analysis Techniques
In subproject D03 the focus is on the development of extended methods for tomography data analysis. The approach is to investigate the components of the specimens by segmenting them subvoxel-precisely and predict the distribution of the contained carbon fibers.
After the development of appropriate algorithms, the samples will be deformed by the application of force and then scanned again in the tomograph. The goal then is to determine the relationship between structure and stability. The multitemporal data sets produced in this process are matched using 3D-LSM (Least Squares Matching) in order to investigate not only the displacement vectors (caused by the temporal difference) but also the deformations and cracks with subvoxel accuracy. With the aim to further optimize the data quality and thus the data analysis, a sensor modeling and corresponding calibration strategies are developed, which largely eliminate the systematic errors of tomographs.
Publikationen / Publications
Liebold, F.; Lorenzoni, R.; Curosu, I.; Léonard, F.; Mechtcherine, V.; Paciornik, S.; Maas, H.-G. (2021) 3D Least Squares Matching Applied to Micro-Tomography Data in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 43, issue B2, p. 533–539 – https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-533-2021
Liebold, F.; Maas, H.-G. (2022) 3D-Deformationsanalyse und Rissdetektion in multitemporalen Voxeldaten von Röntgentomographen in: Kersten, T.; Tilly, N. [eds.] Proc. der 42. Wissenschaftlich-Technischen Jahrestagung der DGPF, Band 30, 05./06.10.2022 in Dresden, p. 105–116 – https://doi.org/10.24407/KXP:1796026123