Influence of the Paint Coating Thickness in Digital Image Correlation Experiments
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Influence of the Paint Coating Thickness in Digital Image Correlation Experiments

Authors: Jesús A. Pérez, Sam Coppieters, Dimitri Debruyne

Abstract:

In the past decade, the use of digital image correlation (DIC) techniques has increased significantly in the area of experimental mechanics, especially for materials behavior characterization. This non-contact tool enables full field displacement and strain measurements over a complete region of interest. The DIC algorithm requires a random contrast pattern on the surface of the specimen in order to perform properly. To create this pattern, the specimen is usually first coated using a white matt paint. Next, a black random speckle pattern is applied using any suitable method. If the applied paint coating is too thick, its top surface may not be able to exactly follow the deformation of the specimen, and consequently, the strain measurement might be underestimated. In the present article, a study of the influence of the paint thickness on the strain underestimation is performed for different strain levels. The results are then compared to typical paint coating thicknesses applied by experienced DIC users. A slight strain underestimation was observed for paint coatings thicker than about 30μm. On the other hand, this value was found to be uncommonly high compared to coating thicknesses applied by DIC users.

Keywords: Digital Image Correlation, paint coating thickness, strain.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107139

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References:


[1] M.A. Sutton, J.J. Orteu and H.W. Schreier, Image Correlation for Shape, Motion and Deformation measurements, Springer Science+Business Media, New York, USA, 2009.
[2] J. Kang, “Microscopic Strain Mapping Based on Digital Image Correlation”, Society for Experimental Mechanics Inc., Proceedings of the XI International Congress and Exposition, Orlando, Florida, June, 2008.
[3] J. Chen, G. Xia, K. Zhou, G. Xia and Y. Qin, “Two-step digital image correlation for micro-region measurement”, Optics and Laser Engineering, vol. 43, pp. 836-846, 2005.
[4] A. Piekarczuk, M. Malesa, M. Kujawinska and K. Malowany, “Application of Hybrid FEM-DIC Method for Assessment of Low Cost Building Structures” Experimental Mechanics, vol. 52, no. 9, pp. 1297- 1311, April 2012.
[5] N. McCormick and J. Lord, “Digital image correlation for structural measurements” Proceedings of the Institution of Civil Engineers, vol. 165, Issue CE4, pp. 185-190, 2012.
[6] L. Chevalier, S. Calloch, F. Hild and Y. Marco, “Digital image correlation used to analyze the multiaxial behavior of rubber-like materials”, European Journal of Mechanics - A/Solids, vol. 20, no. 2, pp. 169-187, 2001.
[7] K. De Wilder, P. Lava, D. Debruyne, Y. Wang, G. De Roeck and L. Vandewalle, “Experimental investigation on the shear capacity of prestressed concrete beams using digital image correlation”, Engineering Structures, vol. 82, pp. 82-92, Jan. 2015.
[8] M. A. Caminero, M. Lopez-Pedrosa, C. Pinna and C. Soutis, “Damage Assessment of Composite Structures Using Digital Image Correlation”, Applied Composite Materials, vol. 21, no. 1, pp. 91-106, Feb. 2014.
[9] J.A. Pérez, S. Coppieters, E. Alcalá, “Measuring Strain Concentrations in Welded Junctions using Digital Image Correlation”, in Proc. of Young welding Professionals International Conference, Budapest, 2014, pp. 17-23.
[10] P. Lava, S. Cooreman, D. Debruyne, “Study of systematic errors in strain fields obtained via DIC using heterogeneous deformation generated by plastic FEA”, in Optics and Lasers in Engineering, vol. 48, no. 2, pp. 457-468, 2010.