Skip to main content
SpringerLink
Log in

Stereo-DIC Uncertainty Quantification based on Simulated Images

  • Published:
Experimental Mechanics Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Balcaen R, Wittevrongel L, Reu PL, Lava P, Debruyne D (2017) Stereo-dic calibration and speckle image generator based on fe formulations. Exp Mech, 1–16

  2. Bornert M, Brmand F, Doumalin P, Dupr J-C, Fazzini M, Grdiac M, Hild F, Mistou S, Molimard J, Orteu J-J, Robert L, Surrel Y, Vacher P, Wattrisse B (2009) Assessment of digital image correlation measurement errors: methodology and results. Exp Mech 49(3):353–370

    Article  Google Scholar 

  3. Wang YQ, Sutton MA, Bruck HA, Schreier HW (2009) Quantitative error assessment in pattern matching Effects of intensity pattern noise, interpolation, strain and image contrast on motion measurements. Strain 45(2):160–178

    Article  Google Scholar 

  4. Lava P, Cooreman S, Coppieters S, De Strycker M, Debruyne D (2009) Assessment of measuring errors in dic using deformation fields generated by plastic fea. Opt Lasers Eng 47(7–8):747–753

    Article  Google Scholar 

  5. Pan B, Qian K, Xie H, Asundi A (2009) Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review. Measurement Science and Technology 20(6)

  6. Reu PL (2015) A realistic error budget for two dimension digital image correlation. Advancement of Optical Methods in Experimental Mechanics 3:189–193

    Google Scholar 

  7. Wang YQ, Sutton MA, Ke XD, Schreier WH, Reu LP, Miller JT (2011) On error assessment in stereo-based deformation measurements-part 1. Exp Mech 51(4):405–422

    Article  Google Scholar 

  8. Ke XD, Schreier WH, Sutton AM, Wang Y (2011) On error assessment in stereo-based deformation measurements-part 2. Exp Mech 51(4):423–441

    Article  Google Scholar 

  9. Reu PL (2013) Imaging methods for novel materials and challenging applications Conference proceedings of the society for experimental mechanics series 2013, vol 3. Springer, New York, pp 311–317

  10. Lava P, Pierron F, Reu PL (2014) Dic course-metrology beyond colors

  11. Orteu J, Garcia D, Robert L, bugarin F (2006) A speckle texture image generator Proceedings SPIE 6341, Speckle06: Speckles, From Grains to Flowers, 63410H

  12. Sutton MA, Orteu JJ, Schreier HW (2009) Image correlation for shape, motion and deformation measurements. Springer Science

  13. Wang Y, Lava P, Debruyne D (2015) Using super-resolution images to improve the measurement accuracy of dic Optical measurement techniques for systems and structures III, pp 353–361

  14. Wang Y, Lava P, Coppieters S, De Strycker M, Van Houtte P, Debruyne D (2012) Investigation of the uncertainty of dic under heterogeneous strain states with numerical tests. Strain 48(6):453–462

  15. Hua C (1990) An inverse transformation for quadrilateral isoparametric elements. Analysis and application. Finite Elements in Analysis and Design 7(2):159–166

    MATH  Google Scholar 

  16. Wittevrongel L (2015) R0276087. A self adaptive algorithm for accurate strain measurements using global digital image correlation. Other titles: Een zelfcorrigerend algoritme voor nauwkeurige rekmetingen met behulp van globale digitale beeldcorrelatie. PhD thesis, KU Leuven, https://lirias.kuleuven.be/handle/123456789/506239

  17. Reu PL (2013) Stereo-rig design: Stereo-angle selection part 4. Exp Tech 37(2):1–2

    Article  Google Scholar 

  18. http://www.matchidmbc.com/

  19. Chen J, Ding Z, Yuan F (2008) Theoretical uncertainty evaluation of stereo reconstruction 2nd International Conference on Bioinformatics and Biomedical Engineering. IEEE, pp 2378–2381

  20. Cox MG, Dainton MP, Harris PM (2001) Software support for metrology best practice guide no. 6 - uncertainty and statistical modelling. Technical report Centre for Mathematics and Scientific Computing

  21. Di Leo G, Liguori C, Paolillo A (2010) Propagation of uncertainty through stereo triangulation Instrumentation and Measurement Technology Conference (I2MTC). IEEE, pp 12–17

  22. Reu PL (2013) A study of the influence of calibration uncertainty on the global uncertainty for digital image correlation using a monte carlo approach. Exp Mech 53(9):1661–1680

    Article  Google Scholar 

  23. Schreier WH, Sutton AM (2002) Systematic errors in digital image correlation due to undermatched subset shape functions. Exp Mech 42(3):303–310

    Article  Google Scholar 

  24. Pan B, Yu L (2015) The errors in digital image correlation due to overmatched shape functions. Meas Sci Technol 26(4):045202

    Article  Google Scholar 

  25. Reu PL (2014) The art and applications, all about speckle: aliasing. Exp Tech 38:1–3

    Google Scholar 

  26. http://www.3ds.com/products-services/simulia/products/abaqus/

  27. Reu PL, Sweatt W, Miller T, Fleming D (2015) Camera system resolution and its influence on digital image correlation. Exp Mech 55(1):9–25

    Article  Google Scholar 

  28. Pierré JE, Passieux JC, Périé JN (2017) Finite element stereo digital image correlation: framework and mechanical regularization. Exp Mech 57(3):443–456

    Article  Google Scholar 

  29. Dufour JE, Hild F, Roux S (2015) Displacement and mechanical properties from isogeometric multiview stereocorrelation. J Strain Anal Eng Des 50(7):470–487

    Article  Google Scholar 

  30. Dufour JE, Beaubier B, Hild F, Roux S (2015) Cad-based displacement measurements with stereo-dic. principle and first validations. Exp Mech 55(9):1657–1668

    Article  Google Scholar 

  31. Beaubier B, Dufour JE, Hild F, Roux S, Lavernhe S, Lavernhe-Taillard K (2014) Cad-based calibration and shape measurement with stereodic - principle and application on test and industrial parts. Exp Mech 54(3):329–341

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. KU Leuven, Department of Materials Technology, Campus Ghent, Gebroeders Desmetstraat 1, 9000, Ghent, Belgium

    R. Balcaen & D. Debruyne

  2. Sandia National Laboratories, Albuquerque, NM, USA

    P.L. Reu

  3. MatchID, Wijmenstraat 21T, 9000, Ghent, Belgium

    P. Lava

Authors
  1. R. Balcaen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P.L. Reu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. P. Lava
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D. Debruyne
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R. Balcaen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Balcaen, R., Reu, P., Lava, P. et al. Stereo-DIC Uncertainty Quantification based on Simulated Images. Exp Mech 57, 939–951 (2017). https://doi.org/10.1007/s11340-017-0288-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11340-017-0288-9

Keywords

Search

Navigation