Video extensometry measurement method for materials with large deformations

Haoran Shi; Zhijia Zhang; Minmin Yang

doi:10.1117/12.3036540

16 August 2024 Video extensometry measurement method for materials with large deformations

Haoran Shi, Zhijia Zhang, Minmin Yang

Proceedings Volume 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024); 132301V (2024) https://doi.org/10.1117/12.3036540
Event: Third International Conference on Machine Vision, Automatic Identification and Detection, 2024, Kunming, China

Abstract

This paper addresses the issue of segmentation errors in video extensometer caused by deformation, dispersion, and cracks in markers during the stretching process. A method combining frame -to-frame matching with deep learning is proposed to address the high robustness segmentation problem of black and white markers on materials undergoing large strains. The selection of template position during image matching and the update of the template throughout the stretching process are discussed. Experiments and analysis were conducted on various types of rubber and plastic specimens that exhibit significant strain and irregular deformation. The results demonstrate that this method can be applied to line marker-type video extensometers, enhancing the overall robustness of the measurement algorithm.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Haoran Shi, Zhijia Zhang, and Minmin Yang "Video extensometry measurement method for materials with large deformations", Proc. SPIE 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024), 132301V (16 August 2024); https://doi.org/10.1117/12.3036540

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