Abstract
Since presentation of the 2013 Murray Lecture focusing on developments in digital image correlation (DIC), the methods have continued to expand internationally and their use has begun to grow in fields where there was less activity in the past. First, a brief history of digital image correlation methods is presented from the perspective of the first author, followed by a discussion of recent trends associated with the use of digital image correlation methods in academics, governmental laboratories and industrial settings. In the remainder of the article, new results are provided in three areas where DIC methods have seen rapid growth; application of StereoDIC or three-dimensional DIC (3D-DIC) to the study of wall structures in civil engineering; the use of Volumetric DIC or Digital Volume Correlation (DVC) to quantify the internal response of a specially-designed composite material and in the area of model validation for another application in civil engineering; transfer length measurements in pre-stressed concrete beams.
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Notes
As is noted in the next few sentences, this original work was followed by additional studies that led to an archival publication in 1987 (see [10]).
After joining the faculty at Southern Illinois University-Carbondale, Prof. TC Chu performed preliminary photogrammetric experiments with his PhD student circa 1990 [17].
What is not shown in the report is an additional set of measurements obtained of the crown region on top of the aircraft test article. Though the experimental process was successful on the crown region, data was not included in the report due to excessive reflectivity of the crown region in the sunlight during the imaging process. The reflections limited the measurement area to a small portion of the field of view and hence were not sufficient to evaluate the response of the key section of interest on the crown.
It is possible to increase the gain on most scientific grade cameras if additional lighting is not available. However, when increasing gain, one increases both the intensity pattern signal and noise simultaneously, which may affect the accuracy of the measurements.
Similar results to those shown in Table 3 were obtained for strains in three separate experiments and for in-plane displacements in all but one experiment. For the outlier experiment, the measured in-plane displacements using average images had mean values that were 10× higher than in other experiments. The source of the increased bias in the mean values is unknown, but may have been due to unexpected laboratory floor vibrations which induced deleterious motions of the stereo camera system during the image acquisition process.
Standard deviations for the various experimentally determined parameters are not reported since only a limited number of independent experiments were performed.
In some applications, CT scanning is performed where the z-direction dimension of a voxel in an image is increased to reduce the size of the images, introducing additional errors in the DIC—based measurements along this direction.
Initial studies mounted the cameras firmly to the horizontal I-beam within the load-bearing frame structure. During this initial experiment, it was observed that release of pretension in the tendons during flame cutting of the cable strands was far more violent than expected, causing shock waves in the frame structure as the cable separated. The shock waves propagated up the vertical I-beams and across the horizontal I-beam, resulting in relative motion of the cameras and defocusing of one camera, so that no data was obtained. Based on this observation, all further experiments were performed with the cameras mounted on an independent vertical structure.
Preliminary baseline experiments performed using halogen lights showed a continually increasing and highly variable strain field on the specimen, with strains that reached 300 με after 1 h. It was determined that the halogen lights were heating both the specimen and the surrounding air, resulting in the observed pseudo-strains. Replacement of the halogen lights with low heat lights eliminated this problem.
The small range of rotations was considered sufficient for these experiments since the specimen would experience very small rotations when the cables are released.
During initial heating up of the camera, various components of the camera may experience different temperatures and this can lead to differential expansion. Hence, if the cameras are calibrated before reaching the steady state, the calibration parameters obtained can be different from the actual steady state value. In these studies, the cameras were allowed to heat up for ~ 1 h prior to calibration.
References
Sutton MA, Orteu JJ, Schreier HW (2009) Image correlation for shape, motion and deformation measurements: basic concepts, theory and applications. Springer. ISBN: 978-0-387-78746-6
Anon (2003) Gilbert Louis Hobrough. Photogramm Rec 18(4):337–340
Shirai Y (1987) Three-dimensional computer vision. Springer Verlag. ISBN: 978-3-642-82431-9
Peters WH, Ranson WF (1982) Digital imaging techniques in experimental stress analysis. Opt Eng 21(3):427–431
Sutton MA, Wolters WJ, Peters WH III, Ranson WF, McNeill SR (1983) Determination of displacements using an improved digital correlation method. Image Vis Comput 1(3):1333–1339
Peters WH III, Ranson WF, Sutton MA, Chu TC, Anderson J (1983) Application of digital correlation methods to rigid body mechanics. Opt Eng 22(6):738–743
He Z-H, Sutton MA, Ranson WF, Peters WH III (1984) Two dimensional fluid velocity measurements by use of digital speckle correlation techniques. Exp Mech 24(2):117–121
Williams ML (1957) On the stress distribution at the base of a stationary crack. J Appl Mech 4(1):109–114
Chu TC, Ranson WF, Sutton MA, Peters WH III (1985) Application of digital image correlation techniques to experimental mechanics. Exp Mech 25(3):232–245
McNeill SR, Peters WH III, Sutton MA (1987) Estimation of stress intensity factor by digital image correlation. Eng Fract Mech 28(1):101–112
Sutton MA, Chao YJ (1988) Measurement of strains in a paper tensile specimen using computer vision and digital image correlation part I: data acquisition and image analysis system. J Tech Assoc Pap Pulping Ind 70(3):173–175
Chao YJ, Sutton MA (1988) Measurement of strains in a paper tensile specimen using computer vision and digital image correlation, part II: tensile specimen test. J Tech Assoc Pap Pulping Ind 70(4):153–156
Sutton MA, Cheng M, Peters WH, Chao YJ, McNeill SR (1986) Application of an optimized digital correlation method to planar deformation analysis. Image Vis Comput 4(3):143–150
Bruck HA, McNeill SR, Sutton MA, Peters WH III (1989) Determination of deformations using digital correlation with the Newton Raphson method for partial differential corrections. Exp Mech 29(3):261–267
Luo PF, Chao YJ, Sutton MA, Peters WH III (1993) Accurate measurement of three dimensional deformations in deformable and rigid bodies using computer vision. Exp Mech 33(2):123–133
Luo PF, Chao YJ, Sutton MA (1994) Application of stereo vision to 3-D deformation analysis in fracture mechanics. Opt Eng 33(3):981–990
Kahn-Jetter ZL, Chu TC (1990) Three-dimensional displacement measurements using digital image correlation and photogrammetry analysis. Exp Mech 30(1):10–16
Helm JD, McNeill SR, Sutton MA (1996) Improved 3-D Image correlation for surface displacement measurement. Opt Eng 35(7):1911–1920
McNeill SR, Helm JD, Lan JD, Sutton MA (1997) Experimental evaluation of surface deformations in three areas of a Boeing 727 aircraft due to internal pressure and tail loading, Report USC ME-1-1997, Submitted in June, 1997 to Matthew Miller, Boeing Seattle
Helm JD, Sutton MA, McNeill SR (2003) Deformations in wide, center-notched, thin panels: part I: three dimensional shape and deformation measurements by computer vision. Opt Eng 42(5):1293–1305
Helm JD, Sutton MA, McNeill SR (2003) Deformations in wide, center-notched, thin panels: part II: finite element analysis and comparison to experimental measurements. Opt Eng 42(5):1306–1320
Schreier HW, Braasch J, Sutton MA (2000) Systematic errors in digital image correlation caused by intensity interpolation. Opt Eng 39(11):2915–2921
Wang YQ, Sutton MA, Schreier HW (2009) Quantitative error assessment in pattern matching: effects of intensity pattern noise, interpolation, subset size and image contrast on motion measurements. J Strain 45:160–178
Lu H, Cary D (2000) Deformation measurements by digital image correlation: implementation of a second order displacement gradient. Exp Mech 40(4):393–400
Schreier HW, Sutton MA (2002) Systematic errors in digital image correlation due to undermatched subset shape functions. Exp Mech 42(3):303–310
Wang Y-Q, Sutton MA, Ke X-D, Schreier HW, Reu PL, Miller TJ (2011) On error assessment in stereo-based deformation measurements. Exp Mech 51(4):405–422
Ke X-D, Schreier HW, Sutton MA, Wang Y-Q (2011) Error assessment in stereo-based deformation measurements. Exp Mech 51(4):423–441
Bay BK, Smith TS, Fyhrie DP, Saad M (1999) Digital volume correlation: three-dimensional strain mapping using X-ray tomography. Exp Mech 33(3):217–226
Smith TS, Bay BK, Rashid MM (2002) Digital volume correlation including rotational degrees of freedom during minimization. Exp Mech 42(3):272–278
Sutton MA (2013) Computer vision-based, noncontacting deformation measurements in mechanics: a generational transformation. ASME Appl Mech Rev 65:050802-050802-23. doi:10.1115/1.4024984
Sutton MA, Hild F (2015) Recent advances and perspectives in digital image correlation. Exp Mech 55(1):1–8
Ghorbani R, Matta F, Sutton MA (2015) Full-field deformation measurement and crack mapping on confined masonry walls using digital image correlation. Exp Mech 55(1):227–243
Ghorbani R (2014) Context-sensitive seismic strengthening and repair of substandard confined masonry, PhD Dissertation. University of South Carolina, Columbia Campus
VIC-3D-Ver 7, www.correlatedsolutions.com
Brzev S, Astroza M, Moroni O (2010) Performance of confined masonry buildings in the February 27, 2010 Chile earthquake. Earthquake Engineering Research Institute, Oakland
Meli R, Brzev S, Astroza M, Boen T, Crisafulli F, Dai J, Farsi M, Hart T, Mebarki A, Moghadam S, Quiun D, Tomaževič M, Yamin L (2011) Seismic design guide for low-rise confined masonry buildings. Earthquake Engineering Research Institute, Oakland
Alcocer SM, Klingner RE (2006) The Tecomán, México earthquake, January 21, 2003: an EERI and SMIS learning from earthquakes reconnaissance report. Earthquake Engineering Research Institute, Oakland
Eberhard MO, Baldridge S, Marshall J, Mooney W, Rix GJ (2010) The Mw 7.0 Haiti earthquake of January 12, 2010: USGS/EERI advance reconnaissance team report. U.S. Geological Survey
Forsberg F, Sjodahl M, Mooser R, Hack E, Wyss P (2010) Full three-dimensional strain measurements on wood exposed to three-point bending: analysis by use of digital volume correlation applied to synchrotron radiation micro-computed tomography image data. Strain 46(1):47–60
Zauel R, Yeni YN, Bay BK, Dong XN, Fyhrie DP (2006) Comparison of the linear finite element prediction of deformation and strain of human cancellous bone to 3D digital volume correlation measurements. ASME J Biomech Eng 128:1–6
Roberts BC, Perilli E, Reynolds KJ (2014) Application of the digital volume correlation technique for the measurement of displacement and strain fields in bone: a literature review. J Biomech 47(5):923–934
Morgeneyer TF, Helfen L, Mubarak H, Hild F (2013) 3D digital volume correlation of synchrotron radiation laminography images of ductile crack initiation: an initial feasibility study. Exp Mech 53(4):543–556
Germaneau A, Peyruseigt F, Mistouc S, Doumalin P, Dupré J-C (2010) 3D mechanical analysis of aeronautical plain bearings: validation of a finite element model from measurement of displacement fields by digital volume correlation and optical scanning tomography. Opt Lasers Eng 48(6):676–683
Pierron F, McDonald SA, Hollis D, Fu J, Withers PJ, Alderson A (2013) Comparison of the mechanical behaviour of standard and auxetic foams by X-ray computed tomography and digital volume correlation. Strain 49(6):467–482
Madia K, Tozzia G, Zhang QH, Tonga J, Cosseya A, Auc A, Hollis D, Hild F (2013) Computation of full-field displacements in a scaffold implant using digital volume correlation and finite element analysis. Med Eng Phys 35(9):1298–1312
Brault R, Germaneau A, Dupré JC, Doumalin P, Mistou S, Fazzini M (2013) In-situ analysis of laminated composite materials by X-ray micro-computed tomography and digital volume correlation. Exp Mech 53(7):1143–1151
Forsberg F, Siviour CR (2009) 3D deformation and strain analysis in compacted sugar using x-ray microtomography and digital volume correlation. Meas Sci Technol 20(9)
Lenoir N, Bornert M, Desrues J, Bésuelle P, Viggiani G (2007) Volumetric digital image correlation applied to X-ray microtomography images from triaxial compression tests on argillaceous rock. Strain 43(3):193–205
Mollenhauer D, Safriet S, Sutton MA, Schreier HW, Kistner M, Zhou E (2014) Characterization of strain distribution in a reinforced rubber-matrix composite using digital volume correlation. In: Kim H, Whisler D, Chen ZM, Bisagni C, Kawai M, Krueger R (eds) Proceedings of the 29th Annual American Society of Composites Conference
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Acknowledgments
The technical support of Profs. Juan Caicedo and Robert Mullen for the Civil Engineering studies, and also Profs. Jeffrey Helm (Lafayette College) and Stephen McNeill throughout our many years of image correlation research and development, are gratefully acknowledged. The efforts of civil engineering laboratory technical staff including Timothy Ross and Russell Inglett are also recognized and appreciated. The support of the University of South Carolina’s Departments of Mechanical Engineering and Civil and Environmental Engineering, as well as the Air Force Research Laboratory in Dayton, Ohio, is deeply appreciated. In addition, the editorial effort of Prof. Ioannis Chasiotis along with his detailed comments that greatly improved the overall presentation are deeply appreciated. Finally, the financial support provided by the Federal Railway Administration through DTFR53-14-C-00023, the National Aeronautics and Space Administration through NASA NNX13AD43A and the Department of Mechanical Engineering at the University of South Carolina through course load reduction is gratefully acknowledged.
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Appendix
Appendix
Several individuals contributed materially to the development of the digital image correlation methodology that is used today.
A brief historical account of their contributions is provided in the introduction to this article, including the development of DVC in the late 1990s. This appendix provides a set of photographs for each of the individuals who made contributions to the development and improvement of the methods.
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Sutton, M.A., Matta, F., Rizos, D. et al. Recent Progress in Digital Image Correlation: Background and Developments since the 2013 W M Murray Lecture. Exp Mech 57, 1–30 (2017). https://doi.org/10.1007/s11340-016-0233-3
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DOI: https://doi.org/10.1007/s11340-016-0233-3