Importance of Exposure Time on DIC Measurement Uncertainty at Extreme Temperatures

  • T.Q. Thai
  • R.S. Hansen
  • A.J. Smith
  • J. Lambros
  • R.B. BerkeEmail author


Digital Image Correlation (DIC) is a popular optical method for deformation and strain measurement. At extreme temperatures, it is known that materials emit light in addition to reflecting the light supplied by a light source, and the emitted light can saturate a camera sensor. More recently, a novel variation of DIC, named ultraviolet (UV) DIC, extended the range of temperature further by using a UV bandpass filter to screen out some of the brightest glowing and external UV illumination to provide additional reflected lighting. In principle, for a given optical set-up the temperature range can be extended further by reducing the camera’s sensitivity to light, and exposure time is an instrumental parameter when setting such camera configurations. In this paper, we examine the influence of multiple exposure times on the uncertainty of UV-DIC correlation measurements. Rigid-motion experiments were performed at four different temperatures: room temperature, 1300oC, 1450oC, and 1600oC. At each temperature level, UV images were recorded for DIC at exposure times ranging from 500 μs to 61,000 μs – a range of over two orders of magnitude. The results showed abrupt increases of error at extremely dark or bright exposure times, but at intermediate exposure times the errors of UV-DIC were minimal. A normalized metric was presented in order to give a general guideline when choosing exposure time for camera sensitivity. It is recommended that cameras should be set at a suitable range of exposure time (between 10,000 μs and 40,000 μs for the camera used in this paper) in order to perform meaningful DIC up to 1600oC.


DIC extreme temperature exposure time ultraviolet light graphite Gleeble 



This work was funded in part by a grant from NASA’s Marshall Space Flight Center (award # 80MSFC18M0009) and by the Utah State University Office of Research and Graduate Studies. JL also wishes to acknowledge the support of the Air Force Office of Scientific Research (AFOSR) through grant number FA9550-16-1-0055.


  1. 1.
    Sutton MA, Orteu JJ, Schreier H (2009) Image Correlation for Shape, Motion and Deformation Measurements: Basic Concepts,Theory and Applications. Springer USGoogle Scholar
  2. 2.
    Chu TC, Ranson WF, Sutton MA (1985) Applications of digital-image-correlation techniques to experimental mechanics. Exp Mech 25:232–244. CrossRefGoogle Scholar
  3. 3.
    Ramos T, Braga DFO, Eslami S et al (2015) Comparison Between Finite Element Method Simulation, Digital Image Correlation and Strain Gauges Measurements in a 3-Point Bending Flexural Test. Procedia Eng 114:232–239. CrossRefGoogle Scholar
  4. 4.
    Berfield TA, Patel JK, Shimmin RG et al (2007) Micro- and Nanoscale Deformation Measurement of Surface and Internal Planes via Digital Image Correlation. Exp Mech 47:51–62. CrossRefGoogle Scholar
  5. 5.
    Carroll J, Abuzaid W, Lambros J, Sehitoglu H (2010) An experimental methodology to relate local strain to microstructural texture. Rev Sci Instrum 81:083703. CrossRefGoogle Scholar
  6. 6.
    Gradl PR (2016) Digital Image Correlation Techniques Applied to Large Scale Rocket Engine Testing. In: AIAA Propulsion and Power 2016 Conference. Salt Lake City, UT, United StatesGoogle Scholar
  7. 7.
    Carr J, Baqersad J, Niezrecki C, Avitabile P (2016) Full-Field Dynamic Strain on Wind Turbine Blade Using Digital Image Correlation Techniques and Limited Sets of Measured Data From Photogrammetric Targets. Exp Tech 40:819–831. CrossRefGoogle Scholar
  8. 8.
    Wang W, Xu C, Jin H et al (2017) Measurement of high temperature full-field strain up to 2000 °C using digital image correlation. Meas Sci Technol 28:035007. CrossRefGoogle Scholar
  9. 9.
    Yoneyama S (2016) Basic principle of digital image correlation for in-plane displacement and strain measurement. Adv Compos Mater 25:105–123. CrossRefGoogle Scholar
  10. 10.
    Meyer P, Waas AM (2015) Measurement of In Situ-Full-Field Strain Maps on Ceramic Matrix Composites at Elevated Temperature Using Digital Image Correlation. Exp Mech 55:795–802. CrossRefGoogle Scholar
  11. 11.
    Berke RB, Lambros J (2014) Ultraviolet digital image correlation (UV-DIC) for high temperature applications. Rev Sci Instrum 85:045121. CrossRefGoogle Scholar
  12. 12.
    Reu P (2013) Stereo-rig Design: Lens Selection – Part 3. Exp Tech 37:1–3. Google Scholar
  13. 13.
    Reu P (2013) Calibration: A good calibration image. Exp Tech 37:1–3. Google Scholar
  14. 14.
    Reu P (2015) All about speckles: Contrast. Exp Tech 39:1–2. Google Scholar
  15. 15.
    Lyons JS, Liu J, Sutton MA (1996) High-temperature deformation measurements using digital-image correlation. Exp Mech 36:64–70. CrossRefGoogle Scholar
  16. 16.
    Grant BMB, Stone HJ, Withers PJ, Preuss M (2009) High-temperature strain field measurement using digital image correlation. J Strain Anal Eng Des 44:263–271. CrossRefGoogle Scholar
  17. 17.
    Chen X, Xu N, Yang L, Xiang D (2012) High temperature displacement and strain measurement using a monochromatic light illuminated stereo digital image correlation system. Meas Sci Technol 23:125603. CrossRefGoogle Scholar
  18. 18.
    Blaber J, Adair BS, Antoniou A (2015) A methodology for high resolution digital image correlation in high temperature experiments. Rev Sci Instrum 86:035111. CrossRefGoogle Scholar
  19. 19.
    Pan B, Wu D, Wang Z, Xia Y (2011) High-temperature digital image correlation method for full-field deformation measurement at 1200 °C. Meas Sci Technol 22:015701. CrossRefGoogle Scholar
  20. 20.
    Novak MD, Zok FW (2011) High-temperature materials testing with full-field strain measurement: Experimental design and practice. Rev Sci Instrum 82:115101. CrossRefGoogle Scholar
  21. 21., Inc. Fine Extruded Graphite Rod, 0.5"OD x 12"L. Accessed 9 Apr 2018
  22. 22.
    OMEGA Engineering, Inc. Thermocouple Type K Reference Table. In: Thermocouples. Accessed 11 Mar 2018
  23. 23.
    Reu P (2013) Stereo-rig Design: Lighting—Part 5. Exp Tech 37:1–2. Google Scholar
  24. 24.
    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 45:160–178. CrossRefGoogle Scholar
  25. 25.
    Wang Y-Q, Sutton MA, Ke X-D et al (2011) On Error Assessment in Stereo-based Deformation Measurements. Exp Mech 51:405–422. CrossRefGoogle Scholar
  26. 26.
    Ke X-D, Schreier HW, Sutton MA, Wang YQ (2011) Error Assessment in Stereo-based Deformation Measurements. Exp Mech 51:423–441. CrossRefGoogle Scholar

Copyright information

© The Society for Experimental Mechanics, Inc 2019

Authors and Affiliations

  • T.Q. Thai
    • 1
  • R.S. Hansen
    • 1
  • A.J. Smith
    • 1
  • J. Lambros
    • 2
  • R.B. Berke
    • 1
    Email author
  1. 1.Department of Mechanical and Aerospace EngineeringUtah State UniversityLoganUSA
  2. 2.Department of Aerospace EngineeringUniversity of Illinois, Urbana-ChampaignUrbanaUSA

Personalised recommendations