Effect of out-of-plane specimen movement on strain measurement using digital-image-correlation-based video measurement in 2D and 3D

  • Joel Poling
  • Niranjan Desai
  • Gregor Fischer
  • Christos Georgakis
Original Paper


This study determined the effect of specimen out-of-plane movement relative to the sensor, on the accuracy of strains measured made applying 2D and 3D measurement approaches employing the state-of-the-art digital-image-correlation (DIC)-based tool iMETRUM. DIC provides a convenient and inexpensive non-contact approach to monitor structural health by measuring strains in structural systems and linking them to structural damage. This investigation was motivated by initially undetected damage at low strains in connections of a real-world bridge, whose detection would have prevented its spread, resulting in lower repair costs. This study builds upon an initial investigation that concluded that out-of-plane specimen movement reduces the accuracy of DIC-based strain measurements. Consequently, the effect of specimen out-of-plane displacement on the accuracy of strain measurements using the 2D and 3D measurement techniques was determined over a range of strain values and specimen out-of-plane displacements. It was concluded that the 2D system could measure strains as camera focus was being lost due to specimen out-of-plane movement, the effect of which became noticeable at about 0.025% strain and 2.5 mm displacement. The corresponding value for the 3D system was 0.06% strain at 0.5 mm out-of-plane displacement. Furthermore, it was concluded that the 2D system can measure strains in a real bridge, but it would be challenging to use the 3D system for this task. Furthermore, the 2D iMETRUM system is easier and less costly to implement in monitoring localized strains in steel bridges.


Digital Image Correlation Structural Health Monitoring 


  1. 1.
    Kaphle M, Tan A, Thambiratnam D (2009) Structural health monitoring of bridges using acoustic emission technology and signal processing techniques. In: Proc. 13th Asia Pacific Vibration Conference, New Zealand, November 22–25, 2009Google Scholar
  2. 2.
    Ahlborn TM, et al. (2010) The State-of-the-Practice of Modern Structural Health Monitoring for Bridges. Report prepared at the Department of Civil and Environmental Engineering, Michigan Tech Transportation Institute, Michigan Technological University, Houghton, Michigan, USA 49931Google Scholar
  3. 3.
    Gentile C, Bernardini G (2010) An interferometric radar for non-contact measurement of deflections on civil engineering structures: laboratory and full-scale tests. Struct Infrastruct Eng 6(5):521–534CrossRefGoogle Scholar
  4. 4.
    Desai N (2016) Small-Strain measurement in bridges using the digital image correlation (DIC) technique. In: Proc. SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 980530, Las Vegas NVGoogle Scholar
  5. 5.
    Desai N, Georgakis C, Fischer G (2016) A comparison between the minimum resolutions of two digital image correlation-based tools in making strain measurements. In: Proc. 5th IAJC-ISAM International Conference, November 6–8, 2016, Orlando, FloridaGoogle Scholar
  6. 6.
    Desai N, Georgakis C, Fischer G (2017) A comparison between the minimum resolutions of two digital image correlation-based tools in making strain measurements. Int J Eng Res Innov 8(2):113–126Google Scholar
  7. 7.
    Jiang R, Jauregui DV, White KR (2008) Close-range photogrammetry applications in bridge measurement: literature review, measurement. J Int Meas Confed (IMEKO) 41:823–834CrossRefGoogle Scholar
  8. 8.
    Jauregui DV, White KR, Woodward PE, Leitch KR (2003) Noncontact photogrammetric measurement of vertical bridge deflection. J Bridge Eng 8(4):212–222CrossRefGoogle Scholar
  9. 9.
    Mills J, Barber D (2004) Geomatics techniques for structural surveying. J Surv Eng 130(2):56–64CrossRefGoogle Scholar
  10. 10.
    Waterfall PM, Macdonald JHG, McCormick NJ (2012) Targetless precision monitoring of road and rail bridges using video cameras. In: Proc. 6 th International Conference on Bridge maintenance, Safety and Management (IABMAS 2012), Italy, July 8–12, 2012Google Scholar
  11. 11.
    Busca G, Cigada A, Mazzoleni P, Zappa E, Franzi M (2012) Cameras as displacement sensors to get the dynamic motion of a bridge: performance evaluation against traditional approaches. In: Proc. 6th International Conference on Bridge maintenance, Safety and Management (IABMAS 2012), Italy, July 8–12, 2012Google Scholar
  12. 12.
    Yarnold MT, Moon FL, Aktan AE, Glisic B (2012) Structural monitoring of the Tacony-Palmyra Bridge using video and sensor integration for enhanced data interpretation. In: Proc. 6 th International Conference on Bridge maintenance, Safety and Management (IABMAS 2012), Italy, July 8–12, 2012Google Scholar
  13. 13.
    Forno C, Brown S, Hunt RA, Kearney AM, Oldfield S (1991) The measurement of deformation of a bridge by Moire´ photography and photogrammetry. Strain 27(3):83–87CrossRefGoogle Scholar
  14. 14.
    Kim BG (1989) Development of a photogrammetric system for monitoring structural deformations of the sturgeon bay bridge, PhD Dissertation, University of Wisconsin, MadisonGoogle Scholar
  15. 15.
    Spero PAC (1983) The photogrammetric recording of historic transportation sites. VHTRC 83-R35, Virginia Highway & Transportation Research Council, Charlottesville, VirginiaGoogle Scholar
  16. 16.
    Nishimura S, Yoshihara H (2001) Utilization of digital information on Nishida bridge relocation and restoration. (accessed July 2007)
  17. 17.
  18. 18.
    Poling J, Desai N (2017) Effect of out-of-plane specimen movement on the accuracy of the smallest specimen strain measurable using the digital image correlation technique. SPIE Smart Structures NDE, Portland Oregon, March 27–29, 2017Google Scholar
  19. 19.
    Desai N, Poling J, Fischer G, Georgakis C (2017) Small strain measurement using digital image correlation-based iMETRUM in a specimen subjected to out-of-plane movement. In: 5th Annual International Conference on Architecture and Civil Engineering (ACE), May 8–9, 2017, SingaporeGoogle Scholar
  20. 20.
  21. 21.
    Matsumoto T, Motomura S (1984) Test of welding technique for repair of steel highway bridges. Transportation Research Record No. 950, Transportation Research Board, National Research Council, Washington D.C., pp. 157–163Google Scholar
  22. 22.
    Steel Bridge Design Handbook: Bridge Steels and Their Mechanical Properties. Publication No. FHWA-IF-12-052—Vol 1. U. S. Department of Transportation, Federal Highway Administration, November 2012Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Joel Poling
    • 1
  • Niranjan Desai
    • 1
  • Gregor Fischer
    • 2
  • Christos Georgakis
    • 3
  1. 1.Department of Mechanical and Civil EngineeringPurdue University NorthwestWestvilleUSA
  2. 2.Department of Civil EngineeringTechnical University of DenmarkLyngbyDenmark
  3. 3.Department of Engineering – Structural Monitoring and DynamicsAarhus UniversityAarhus CDenmark

Personalised recommendations