Skip to main content

Assessment of Speckle Pattern for Use in Digital Image Correlation Analysis Using Simulated Displacement Field

  • Conference paper
  • First Online:
Structural Integrity Assessment

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

  • 1444 Accesses

Abstract

Local stresses and strains near the crack tip control fatigue crack growth process. Calculation of elastic–plastic strains and stresses at the crack tip requires solving the nonlinear boundary value problem of a cracked body. Analytical solutions of such problems for varied structural geometry are rarely attainable. A popular method of structural integrity assessment involves stress field characterization ahead of the crack tip. Stress Intensity Factor (SIF) calculation using full-field displacement from digital image correlation (DIC) results is a popular experimental method. Reliable estimation of displacement field from successive images of a specimen under deformation relies largely on intensity profile and its gradient on the specimen, known as speckle patterns . Application of DIC in integrity assessment of structural components of infrastructure and power plant systems should begin with speckle pattern characterization. Speckle pattern characterization can be carried out using two images without any motion or images with rigid-body motions (rigid-body translation and rotation) or images obtained using constant strain tests. The goal of speckle pattern characterization is to quantitatively compare the imposed motion with the recovered motion from DIC and estimation of minimum displacement resolution. Although characterizing speckle pattern using the methods suggested above is relatively straightforward, reproducing representative speckles for multiple cases is a challenge. To overcome this challenge, a speckle pattern assessment procedure, which uses simulated displacement field, is proposed in the present study. A rigid transformation and constant strain condition are simulated and the effectiveness of speckle pattern in capturing simulated displacement from DIC analysis is observed. Error distribution in the estimation of displacement is plotted. For quantitative evaluation of error in length, image calibration is also carried out.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

a :

crack length

K :

stress intensity factor

K max :

maximum stress intensity factor

ΔK :

applied stress intensity range

{r, φ} :

polar coordinates

σ x , σ y , τ xy :

stress components in plane stress

ν :

poisson’s ratio

W :

width of specimen

B :

breadth of specimen

\( \sigma_{YS} \) :

Yield stress

References

  1. P. K. Rastogi, (ed.), Photomechanics, vol 77 (Springer, Berlin, Heidelberg, 2000)

    Google Scholar 

  2. B. Pan, K. Qian, H. Xie, A. Asundi, Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review Meas. Sci. Technol. 20(6), 062001 (2009)

    Article  Google Scholar 

  3. H.T. Goldrein, S.J.J.P. Palmer, J.M. Huntley, Automated fine grid technique for measurement of large-strain deformation maps. Opt. Lasers Eng. 23(5), 305–318 (1995)

    Article  Google Scholar 

  4. J. S. Sirkis, T. J. Lim, Displacement and strain measurement with automated grid methods. Exp. Mech. 31(4), 382–388 (1991)

    Article  Google Scholar 

  5. W. Peters, W. H. Ranson, Digital imaging techniques in experimental stress analysis. Opt. Eng. 21(3), 427–431 (1982)

    Google Scholar 

  6. H. A. Bruck, S. R. McNeill, M. A. Sutton, W. H. Peters, Digital image correlation using Newton-Raphson method of partial differential correction. Exp. Mech. 29(3), 261–267 (1989)

    Article  Google Scholar 

  7. P. F. Luo, Y. J. Chao, M. A. Sutton, W. H. Peters, Accurate measurement of three-dimensional deformations in deformable and rigid bodies using computer vision. Exp. Mech. 33(2), 123–132 (1993)

    Article  Google Scholar 

  8. B. K. Bay, T. S. Smith, D. P. Fyhrie, M. Saad, Digital volume correlation: Three-dimensional strain mapping using X-ray tomography. Exp. Mech. 39(3), 217–226 (1999)

    Article  Google Scholar 

  9. R. Julien, From pictures to extended finite elements : Extended digital image correlation (X-DIC) Correlation d’ images num ‘eriques’ etendue (CIN E). Science 335(80), 1–8 (2007)

    Google Scholar 

  10. S. Roux, F. Hild, Digital image mechanical identification (DIMI). Exp. Mech. 48(4), 495–508 (2008)

    Article  Google Scholar 

  11. H. Tippur, C. Periasamy, A digital gradient sensor for nondestructive evaluation and stress analysis. SPIE Newsroom (2013)

    Google Scholar 

  12. F. Hild et al., Toward 4D mechanical correlation. Adv. Model. Simul. Eng. Sci. 3(1), 17 (2016)

    Google Scholar 

  13. H. Lu, P. D. Cary, Deformation measurements by digital image correlation: Implementation of a second-order displacement gradient. Exp. Mech. 40(4), 393–400 (2000)

    Article  Google Scholar 

  14. X.-Y. Liu et al., Quality assessment of speckle patterns for digital image correlation by Shannon entropy. Opt. Int. J. Light Electron Opt. 126(23), 4206–4211 (2015)

    Article  Google Scholar 

  15. Z. Chen, X. Shao, X. Xu, X. He, Optimized digital speckle patterns for digital image correlation by consideration of both accuracy and efficiency. Appl. Opt. 57(4), 884 (2018)

    Article  Google Scholar 

  16. J. B. Estrada, C. Franck, Intuitive interface for the quantitative evaluation of speckle patterns for use in digital image and volume correlation techniques. J. Appl. Mech. 82(9), 095001 (2015)

    Article  Google Scholar 

  17. P. Lopez-Crespo, A. Shterenlikht, E. A. Patterson, J. R. Yates, P. J. Withers, The stress intensity of mixed mode cracks determined by digital image correlation. J. Strain Anal. Eng. Des. 43(8), 769–780 (2008)

    Article  Google Scholar 

  18. S. N. Atluri, A. S. Kobayashi, Mechanical responses of materials. Handb. Exp. Mech. 1–37 (1993)

    Google Scholar 

Download references

Acknowledgements

The authors thank the Director and Advisor (Management), CSIR-SERC for their valuable guidance, encouragement, and support in the R&D activities. The cooperation and support extended by the technical staff of Fatigue & Fracture Laboratory of CSIR-SERC in carrying out the experimental investigations is gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Abhishek Kumar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kumar, A., Vishnuvardhan, S., Gandhi, P. (2020). Assessment of Speckle Pattern for Use in Digital Image Correlation Analysis Using Simulated Displacement Field. In: Prakash, R., Suresh Kumar, R., Nagesha, A., Sasikala, G., Bhaduri, A. (eds) Structural Integrity Assessment. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-8767-8_51

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-8767-8_51

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-8766-1

  • Online ISBN: 978-981-13-8767-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics