作者
Phillip L. Reu,Benoît Blaysat,Edward Andò,Kaushik Bhattacharya,Cyrille Couture,Victor Couty,D. Deb,Samuel Fayad,Mark A. Iadicola,S. Jaminion,Markus Klein,Alexander K. Landauer,Pascal Lava,Mengying Liu,Li-li Luan,Sindre Nordmark Olufsen,Julien Réthoré,Emmanuel Roubin,Daniel Seidl,Thorsten Siebert,Olga Stamati,Évelyne Toussaint,Daniel Z. Turner,Chamanth Sai Reddy Vemulapati,Thorsten Weikert,Jean‐François Witz,Oliver Witzel,Jin Yang
摘要
The DIC Challenge 2.0 follows on from the work accomplished in the first Digital Image Correlation (DIC) Challenge Reu et al. (Experimental Mechanics 58(7):1067, 1). The second challenge was required to better quantify the spatial resolution of 2D-DIC codes. The goal of this paper is to outline the methods and images for the 2D-DIC community to use to evaluate the performance of their codes and improve the implementation of 2D-DIC. This paper covers the creation of the new challenge images and the analysis and discussion of the results. It proposes a method of unambiguously defining spatial resolution for 2D-DIC and explores the tradeoff between displacement and strain noise (or measurement noise) and spatial resolution for a wide variety of DIC codes by a combination of the images presented here and a performance factor called Metrological Efficiency Indicator (MEI). The performance of the 2D codes generally followed the expected theoretical performance, particularly in the measurement of the displacement. The comparison did however show that even with fairly uniform displacement performance, the calculation of the strain spatial resolution varied widely. This work provides a useful framework for understanding the tradeoff and analyzing the performance of the DIC software using the provided images. It details some of the unique errors associated with the analysis of these images, such as the Pattern Induced Bias (PIB) and imprecision introduced through the strain calculation method. Future authors claiming improvements in 2D accuracy are encouraged to use these images for an unambiguous comparison.