Pydic: 2D-DIC Code Accuracy Evaluation for Strain Field Measurements

Bibliographic Details
Parent link:Electron Devices and Materials (EDM)=Proceedings of the 2024 IEEE 25th International Conference of Young Professionals, Altai, 28 June-2 July 2024. P. 980-983.— .— Piscataway: IEEE, 2024
Main Author: Abouellail A. F. A. Abdelmeguid Fathy Ahmed
Other Authors: Trigub M. V. Maksim Viktorovich
Summary:Заглавие с экрана
Modern personal computer machines with high-capacity processors allow the application of advanced techniques in the field of testing and inspection for civil and mechanical engineering. Digital Image Correlation is currently one of the most cost-effective and user-friendly optical and noncontact techniques for strain field measurements. Pydic is a free and open source Python code for local 2D Digital Image Correlation. It was developed by Damien André, SPCTS/ENSIL-ENSCI, Limoges, France. Pydic is based on OpenCV, a well-known open-source computer vision and machine learning library. In this work, the Pydic code was validated for strain field measurements using a set of speckled images provided by the SEM DIC challenge. The same set of speckled images was used to compute the strain field with GOM correlate software. An accuracy assessment was made by comparing the results of Pydic code and GOM correlate software; also, the results published in the DIC challenge report were considered in the comparison. The results show an acceptable agreement by visual comparison and the computed strain field range. The weaknesses of Pydic code were highlighted, and future work for code improvement was discussed
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Published: 2024
Subjects:
Online Access:https://doi.org/10.1109/EDM61683.2024.10615130
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=682437