Stereo-DIC Uncertainty Quantification based on Simulated Images | Zendy

R. Balcaen | Zendy; P.L. Reu | Zendy; Pascal Lava | Zendy; Dimitri Debruyne | Zendy

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Stereo-DIC Uncertainty Quantification based on Simulated Images

Author(s) -

R. Balcaen,

P.L. Reu,

Pascal Lava,

Dimitri Debruyne

Publication year - 2017

Publication title -

experimental mechanics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.815

H-Index - 87

eISSN - 1741-2765

pISSN - 0014-4851

DOI - 10.1007/s11340-017-0288-9

Subject(s) - digital image correlation , solid mechanics , computer science , deformation (meteorology) , computer vision , observational error , artificial intelligence , selection (genetic algorithm) , algorithm , optics , mathematics , physics , statistics , meteorology , thermodynamics

Stereo digital image correlation (stereo-DIC) is in wide-spread use for full-field shape, motion and deformation-measurements. However there are very few papers investigating the influence of the setup on the measurement uncertainty. This is mainly due to the highly non-linear measurement chain involving both optical and numerical aspects, making it difficult to investigate how error sources are propagated through the stereo-DIC chain. Indeed, it is impossible to separate all the error sources that are present during a physical measurement. This paper tries to investigate a selection of error sources that are present during experiments. This is based on a simulator introduced in a previous article (Balcaen et al., Exp Mech, 1–16 2017) and briefly reviewed here. Based on these simulations we suggest some ”best-practices” guidelines of optimal stereo-DIC setups.status: publishe

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