Extracting displacement and strain fields from checkerboard images with the Localized Spectrum Analysis

Michel Grediac 1 Benoît Blaysat 1 Frédéric Sur 2
2 MAGRIT - Visual Augmentation of Complex Environments
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
Abstract : The performance of white-light full-field measurement methods strongly depends on the nature of the pattern used to mark the surface on which displacements and strains are measured. Finding optimized patterns is therefore a topical question. The aim of this study is to examine the case of the checkerboard pattern. It is first shown that this periodic pattern can be processed with a Fourier-based technique such as LSA. Experiments are then carried out to compare the noise level in displacement and strain maps obtained by processing classic 2D grid and checkerboard images. The conclusion is that the noise level observed in displacement and strain maps is significantly lower with a checkerboard than with a classic 2D grid. A notched specimen is finally tested to illustrate that very low strain levels can be measured with checkerboard patterns.
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Michel Grediac, Benoît Blaysat, Frédéric Sur. Extracting displacement and strain fields from checkerboard images with the Localized Spectrum Analysis. Experimental Mechanics, Society for Experimental Mechanics, 2019, 59 (2), pp.207-218. 〈https://link.springer.com/article/10.1007%2Fs11340-018-00439-2〉. 〈10.1007/s11340-018-00439-2〉. 〈hal-01926054〉

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