Towards deconvolution to enhance the grid method for in-plane strain measurement
Identifieur interne : 000C58 ( Main/Exploration ); précédent : 000C57; suivant : 000C59Towards deconvolution to enhance the grid method for in-plane strain measurement
Auteurs : Frédéric Sur [France] ; Michel Grediac [France]Source :
- Inverse Problems and Imaging [ 1930-8337 ] ; 2014-03.
English descriptors
- mix :
Abstract
The grid method is one of the techniques available to measure in-plane displacement and strain components on a deformed material. A periodic grid is first transferred on the specimen surface, and images of the grid are compared before and after deformation. Windowed Fourier analysis-based techniques permit to estimate the in-plane displacement and strain maps. The aim of this article is to give a precise analysis of this estimation process. It is shown that the retrieved displacement and strain maps are actually a tight approximation of the convolution of the actual displacements and strains with the analysis window. The effect of digital image noise on the retrieved quantities is also characterized and it is proved that the resulting noise can be approximated by a stationary spatially correlated noise. These results are of utmost importance to enhance the metrological performance of the grid method, as shown in a separate article.
Url:
DOI: 10.3934/ipi.2014.8.259
Affiliations:
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<front><div type="abstract" xml:lang="en">The grid method is one of the techniques available to measure in-plane displacement and strain components on a deformed material. A periodic grid is first transferred on the specimen surface, and images of the grid are compared before and after deformation. Windowed Fourier analysis-based techniques permit to estimate the in-plane displacement and strain maps. The aim of this article is to give a precise analysis of this estimation process. It is shown that the retrieved displacement and strain maps are actually a tight approximation of the convolution of the actual displacements and strains with the analysis window. The effect of digital image noise on the retrieved quantities is also characterized and it is proved that the resulting noise can be approximated by a stationary spatially correlated noise. These results are of utmost importance to enhance the metrological performance of the grid method, as shown in a separate article.</div>
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