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Assessment of Digital Image Correlation Measurement Accuracy in the Ultimate Error Regime: Improved Models of Systematic and Random Errors

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Abstract

The literature contains many studies on assessment of DIC uncertainties, particularly in the ultimate error regime, when the shape function used to describe the material transformation perfectly matches the actual transformation. For pure sub-pixel translations, bias and random errors obtained for experimental or synthetic images show more complex evolution versus the fractional part of displacement than those predicted by the existing theoretical models. Indeed, small deviations arise, mainly around integer values of imposed displacements for noisy images, and they are interpreted as the unrepresentativeness of the underlying hypotheses of the theoretical models. In a first step, differences between imposed and measured displacements are analysed: random error is independent of fractional displacement, and systematic error does not decrease for values close to integer displacements whatever the noise level. Therefore, new prediction models are proposed based on the analysis of identified phenomena from synthetic speckle-pattern 8-bit images. The statistical approach used in this paper generalizes the methods proposed in the literature and mimics the experimental methodology usually used for displacement measurements performed in different subsets in the same image. Two closed-form expressions for the systematic and random errors and a linear interpolation scheme are developed. These models, depending only on image properties and the imposed displacement, are built with a very limited number of parameters. It is then possible to predict the evolution of bias and random errors from one to four images.

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Acknowledgements

The authors gratefully acknowledge the French CNRS (National Centre for Scientific Research) for supporting this research through the GDR2519 research network “Mesures de Champs et Identification en Mécanique des Solides”.

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Authors and Affiliations

  1. Laboratoire Navier, UMR 8205, CNRS, ENPC, IFSTTAR, Université Paris-Est, Marne-la-Vallée, France

    M. Bornert

  2. Institut P’, UPR 3346 CNRS, Université de Poitiers, SP2MI, Futuroscope Chasseneuil, France

    P. Doumalin & J.-C. Dupré

  3. CIMAP, UMR 6252, CNRS, CEA, Université de Caen Basse-Normandie, ENSICAEN, Caen, France

    C. Poilâne

  4. Université de Toulouse; Mines Albi, INSA, UPS, ISAE; ICA (Institut Clément Ader), Campus Jarlard, F-81013, Albi Cedex 09, France

    L. Robert

  5. Institut Pascal, UMR6602, CNRS, Université Blaise Pascal – IFMA, Aubière, France

    E. Toussaint

  6. Laboratoire de Mécanique et Génie Civil, UMR CNRS 5508, Université Montpellier 2, Montpellier, France

    B. Wattrisse

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  1. M. Bornert
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  2. P. Doumalin
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  3. J.-C. Dupré
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  4. C. Poilâne
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  5. L. Robert
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  6. E. Toussaint
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  7. B. Wattrisse
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Corresponding author

Correspondence to P. Doumalin.

Additional information

This paper is dedicated to the memory of our colleague Laurent Robert who animated the “Metrology” Workgroup of the GdR2519. He passed away on April 15th, 2015 after a long fight against myeloma cancer.

On behalf of the “Metrology” Workgroup of the French CNRS research network 2519 “Mesures de Champs et Identification en Mécanique des Solides / Full-field measurements and identification in solid mechanics”.

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Bornert, M., Doumalin, P., Dupré, JC. et al. Assessment of Digital Image Correlation Measurement Accuracy in the Ultimate Error Regime: Improved Models of Systematic and Random Errors. Exp Mech 58, 33–48 (2018). https://doi.org/10.1007/s11340-017-0328-5

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  • DOI: https://doi.org/10.1007/s11340-017-0328-5

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