Abstract
A camera exposure time control method that can automatically determine the optimal camera exposure time has been proposed for high-quality digital image correlation (DIC) measurement recently. However, due to the relatively long optimization time required by the adaptive algorithm, this method cannot rapidly find the optimal exposure time during certain high-temperature tests. To improve the efficiency of the camera exposure time control method, we adopted a more efficient adaptive exposure (AE) algorithm and compared its performance with the existing method. The previously used false-position algorithm and the improved average grayscale algorithm are first compared in a static test with changing ambient light. Results reveal that the improved average grayscale algorithm is more efficient in recording high-quality images, thus is recommended for the real high-temperature DIC measurement. The rapid adaptive optimal exposure time control method was then applied at the mid-test of the practical high-temperature DIC measurement to examine the effectiveness of the proposed method. Compared to the conventional fixed exposure mode, the rapid adaptive exposure time control method will enhance the robustness of the DIC system against the changing thermal radiation.
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References
Pan B (2018) Digital image correlation for surface deformation measurement: Historical developments, recent advances and future goals. Meas Sci Technol 29:82001. https://doi.org/10.1088/1361-6501/aac55b
Pan B, Kemao Q, Huimin X, Anand A (2009) Two-dimensional digital image correlation for in-plane displacement and strain measurement: A review. Meas Sci Technol. https://doi.org/10.1088/0957-0233/20/6/062001
Sutton MA, Wolters WJ, Peters WH, Ranson WF, McNeill SR (1983) Determination of displacements using an improved digital correlation method. Image Vis Comput 3:133–139. https://doi.org/10.1016/0262-8856(83)90064-1
Hoefnagels JPM, van Maris MPFHL, Vermeij T (2019) One-step deposition of nano-to-micron-scalable, high-quality digital image correlation patterns for high-strain in-situ multi-microscopy testing. Strain 55(6):e12330. https://doi.org/10.1111/str.12330
Janeliukstis J, Chen X (2021) Review of digital image correlation application to large-scale composite structure testing. Compos Struct 271:114143. https://doi.org/10.1016/j.compstruct.2021.114143
Gupta S, Shukla A (2012) Blast performance of marine foam core sandwich composites at extreme temperatures. Exp Mech 52:1521–1534. https://doi.org/10.1007/s11340-012-9610-8
Pan Z, Huang S, Su Y, Qiao M, Zhang Q (2020) Strain field measurements over 3000°C using 3D-Digital image correlation. Opt Laser Eng 127:105941–105942. https://doi.org/10.1016/j.optlaseng.2019.105942
Dai S, Cunningham PR, Marshall S, Silva C (2015) Open hole quasi-static and fatigue characterisation of 3D woven composites. Compos Struct 131:765–774. https://doi.org/10.1016/j.compstruct.2015.06.032
Xing HZ, Zhang QB, Ruan D, Dehkhoda S, Lu GX, Zhao J (2018) Full-field measurement and fracture characterisations of rocks under dynamic loads using high-speed three-dimensional digital image correlation. Int J Impact Eng 113:61–72. https://doi.org/10.1016/j.ijimpeng.2017.11.011
Ghulam Mubashar Hassan (2021) Deformation measurement in the presence of discontinuities with digital image correlation: A review. Opt Laser Eng 137. https://doi.org/10.1016/j.optlaseng.2020.106394
Pan B, Wu D, Xia Y (2012) An active imaging digital image correlation method for deformation measurement insensitive to ambient light. Opt Laser Technol 44:204–209. https://doi.org/10.1016/j.optlastec.2011.06.019
Grant BMB, Stone HJ, Withers PJ, Preuss M (2009) High-temperature strain field measurement using digital image correlation. J Strain Anal Eng 44:263–271. https://doi.org/10.1243/03093247JSA478
Pan B, Wu D, Gao J (2014) High-temperature strain measurement using active imaging digital correlation and infrared radiation heating. J Strain Anal Eng 49:224–232. https://doi.org/10.1177/0309324713502201
Pan B, Dong YL, Zhao J (2020) Ultraviolet 3D digital image correlation applied for deformation measurement in thermal testing with infrared quartz lamps. Chinese J Aeronaut 33:1085–1092. https://doi.org/10.1016/j.cja.2019.03.038
Berke RB, Lambros J (2014) Ultraviolet digital image correlation (UV-DIC) for high temperature applications. Rev Sci Instrum 85:45121. https://doi.org/10.1063/1.4871991
Yu L, Pan B (2021) Overview of high-temperature deformation measurement using digital image correlation. Exp Mech. https://doi.org/10.1007/S11340-021-00723-8
Chen B, Ji L, Pan B (2020) High-temperature stereo-digital image correlation using a single polarization camera. Appl Optics 59:4008–4015. https://doi.org/10.1364/AO.389396
Guo X, Liang J, Tang Z, Cao B, Yu M (2014) High-Temperature digital image correlation method for Full-Field deformation measurement captured with filters at 2600°C using spraying to form speckle patterns. Opt Eng 53:63101. https://doi.org/10.1117/1.OE.53.6.063101
Zhang S (2020) Rapid and automatic optimal exposure control for digital fringe projection. Opt Laser Eng 128:106029. https://doi.org/10.1016/j.optlaseng.2020.106029
Thai TQ, Smith AJ, Rowley RJ, Gradl PR, Berke RB (2020) Change of exposure time mid-test in high-temperature DIC measurement. Meas Sci Technol 31(7):075402. https://doi.org/10.1088/1361-6501/ab7bbf
Thai TQ, Hansen RS, Smith AJ, Lambros J, Berke RB (2019) Importance of exposure time on DIC measurement uncertainty at extreme temperatures. Exp Tech 43:261–271. https://doi.org/10.1007/s40799-019-00313-3
Pan B, Zhang X, Lv Y, Yu L (2022) Automatic optimal camera exposure time control for digital image correlation. Meas Sci Technol 33(10):105205. https://iopscience.iop.org/article/10.1088/1361-6501/ac750e
Pan B, Lu ZX, Xie HM (2010) Mean intensity gradient: an effective global parameter for quality assessment of the speckle patterns used in digital image correlation. Opt Lasers Eng 48:469–477. https://doi.org/10.1016/j.optlaseng.2009.08.010
Cho MH, Lee SG, Nam BD (1999) The fast auto exposure algorithm based on the numerical analysis. Proc SPIE Proc. SPIE 3650, Sensors, Cameras, and Applications for Digital Photography 3650:93–99, https://doi.org/10.1117/12.342853
Cvetkovic S, Jellema H, de With PHN (2010) Automatic level control for video cameras towards HDR techniques. Eurasip J Image Vide 2010:1–30. https://doi.org/10.1155/2010/197194
Bernacki J (2020) Automatic exposure algorithms for digital photography. Multimed Tools Appl 79:12751–12776. https://doi.org/10.1007/s11042-019-08318-1
Nasser K, Hyuk-Joon O, Shidate I, Yoo YF, Taluri R (2002) New approach to auto-white-balancing and auto-exposure for digital still cameras, Proc. SPIE 4669, Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications III. https://doi.org/10.1117/12.463431
Khoo SW, Karuppanan S, Tan CS (2016) A review of surface deformation and strain measurement using Two-Dimensional digital image correlation. Metrol Meas Syst 23:461–480. https://doi.org/10.1515/mms-2016-0028
Pan B, Xie H, Wang Z (2010) Equivalence of digital image correlation criteria for pattern matching. Appl Optics 49:5501. https://doi.org/10.1364/AO.49.005501
Thai TQ, Rowley RJ, Hansen RS, Berke RB (2021) How light emitted at high temperature affects common digital image correlation algorithms. Meas Sci Technol 32:129401. https://doi.org/10.1088/1361-6501/ac2319
Pan B (2014) An evaluation of convergence criteria for digital image correlation using inverse compositional Gauss-Newton algorithm. Strain 50(1):48–56. https://doi.org/10.1111/str.12066
Committee CAMH (2002) China aeronautical materials handbook. Standards Press of China, Beijing, pp 643–658
Acknowledgements
This work is supported by the National Science and Technology Major Project (J2019-V-0006-0099), National Natural Science Foundation of China (Grant No.12102022) and Beijing Natural Science Foundation (Grant No.3222006).
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Zhang, X., Yu, L. An Improved Automatic Camera Exposure Time Control Method for High-Temperature DIC Measurement. Exp Tech 47, 1019–1028 (2023). https://doi.org/10.1007/s40799-022-00607-z
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DOI: https://doi.org/10.1007/s40799-022-00607-z