Development of an Optical Displacement Transducer for Routine Testing of Asphalt Concrete
Publication: Journal of Materials in Civil Engineering
Volume 28, Issue 9
Abstract
Routine mechanical characterization of asphalt concrete is performed under small-strain levels with on-specimen linear variable displacement transducers (LVDTs) as deformation measuring devices. An optical LVDT was conceptually proposed and evaluated in this study to serve as a viable noncontact alternative to physical LVDTs. The envisioned device consists of a pair of low-end low-resolution grayscale cameras, each monitoring a virtual gauge point, i.e., a small untreated surface area of the tested specimen. The gauge length is the distance between the two virtual gauge points, and the sought-after information is their differential in-plane translation. Digital image correlation techniques were employed for the measurement, operated on the natural material texture without requiring speckle coating. As a first step toward evaluating the concept, the study explored both the precision and the accuracy that may be achieved with one low-resolution image sensor. A calibration scheme was also offered for introducing object-scale dimensions into the analysis. From this predevelopment study it is concluded that the envisioned optical LVDT is viable, rendering the idea worthy of consideration.
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Acknowledgments
The authors wish to thank Mr. Alexey Kharitonov from OpteamX Industrial Cameras Ltd. for allowing access to the imaging equipment and for providing setup guidance as well as experimental assistance. The financial support of Netivei Israel—National Transport Infrastructure Company Ltd. is also acknowledged.
References
AASHTO. (2007). “Standard method of test for determining the creep compliance and strength of hot-mix asphalt (HMA) using the indirect tensile test device.” AASHTO T322, Washington, DC.
AASHTO. (2011). “Standard method of test for determining dynamic modulus of hot-mix asphalt concrete mixtures.” AASHTO T342, Washington, DC.
ARA (Applied Research Associates). (2004). “Guide for the mechanistic-empirical design of new and rehabilitated pavement structures.”, National Cooperative Highway Research Program, Transportation Research Board, Washington, DC.
Baker, S., and Matthews, I. (2004). “Lucas-Kanade 20 years on: A unifying framework.” Int. J. Comput. Vision, 56(3), 221–255.
Berfield, T. A., Patel, J. K., Shimmin, R. G., Braun, P. V., Lambros, J., and Sottos, N. R. (2007). “Micro- and nanoscale deformation measurement of surface and internal planes via digital image correlation.” Exp. Mech., 47(1), 51–62.
Bergonnier, S., Hild, F., Rieunier, J., and Roux, S. (2005). “Strain heterogeneities and local anisotropy in crimped glass wool.” J. Mater. Sci., 40(22), 5949–5954.
Birgisson, B., Montepara, A., Romeo, E., Roncella, R., Roque, R., and Tebaldi, G. (2009). “An optical strain measurement system for asphalt mixtures.” Mater. Struct., 42(4), 427–441.
Bornert, M., et al. (2009). “Assessment of digital image correlation measurement errors: Methodology and results.” Exp. Mech., 49(3), 353–370.
Chehab, G. R., Seo, Y., and Kim, Y. R. (2007). “Viscoelastoplastic damage characterization of asphalt-aggregate mixtures using digital image correlation.” Int. J. Geomech., 111–118.
Chu, T. C., Ranson, W. F., Sutton, M. A., and Peters, W. H. (1985). “Applications of digital image correlation techniques to experimental mechanics.” Exp. Mech., 25(3), 232–244.
Coleri, E., and Harvey, J. T. (2011). “Analysis of representative volume element for asphalt concrete laboratory shear testing.” J. Mater. Civ. Eng., 1642–1653.
Crammond, G., Boyd, S. W., and Dulieu-Barton, J. M. (2013). “Speckle pattern quality assessment for digital image correlation.” Opt. Lasers Eng., 51(12), 1368–1378.
Daniel, J. S., Chehab, G. R., and Kim, Y. R. (2004). “Issues affecting measurement of the complex modulus of asphalt concrete.” J. Mater. Civ. Eng., 469–476.
Debella-Gilo, M., and Kääb, A. (2011). “Sub-pixel precision image matching for measuring surface displacements on mass movements using normalized cross-correlation.” Remote Sens. Environ., 115(1), 130–142.
De Maesschalck, R., Jouan-Rimbaud, D., and Massart, D. L. (2000). “Tutorial: The Mahalanobis distance.” Chemom. Intell. Lab. Syst., 50(1), 1–18.
Fischler, M. A., and Bolles, R. C. (1981). “Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography.” Commun. ACM, 24(6), 381–395.
Goldstein, D. B. (2009). “Physical limits in digital photography: Version 2.0.” 〈http://northlight-images.co.uk/downloadable_2/Physical_Limits_2.pdf〉 (Nov. 27, 2013).
Grédiac, M., and Hild, F. (eds.) (2012). Full-field measurements and identification in solid mechanics, Wiley, Hoboken, NJ.
Hackett, J. K., and Shah, M. (1990). “Multi-sensor fusion: A perspective.” Proc., IEEE Int. Conf. on Robotics and Automation, IEEE, New York, 1324–1330.
Haddadi, H., and Belhabib, S. (2008). “Use of rigid-body motion for the investigation and estimation of the measurement errors related to digital image correlation technique.” Opt. Lasers Eng., 46(2), 185–196.
Hild, F., Raka, B., Baudequin, M., Roux, S., and Cantelaube, F. (2002). “Multi-scale displacement field measurements of compressed mineral wool samples by digital image correlation.” Appl. Opt., 41(32), 6815–6828.
Hodge, V. J., and Austin, J. (2004). “A survey of outlier detection methodologies.” Artif. Intell. Rev., 22(2), 85–126.
Huang, Y. H., Liu, L., Sham, F. C., Chan, Y. S., and Ng, S. P. (2010). “Optical strain gauge vs. traditional strain gauges for concrete elasticity modulus determination.” Optik, 121(18), 1635–1641.
Kaloush, K. E., Mirza, M. W., Uzan, J., and Witczak, M. W. (2001). “Specimen instrumentation techniques for permanent deformation testing of asphalt mixtures.” J. Test. Eval., 29(5), 423–431.
Kelly, D. J., Azeloglu, E. U., Kochupura, P. V., Sharma, G. S., and Gaudette, G. R. (2007). “Accuracy and reproducibility of a subpixel extended phase correlation method to determine micron level displacements in the heart.” Med. Eng. Phys., 29(1), 154–162.
Kim, Y. R. (ed.) (2009). Modeling of asphalt concrete, ASCE, New York.
Kim, Y. R., Lutif, J. E. S., and Allen, D. H. (2009). “Determining representative volume elements of asphalt concrete mixtures without damage.” Transp. Res. Rec., 2127, 52–59.
Lecompte, D., et al. (2006). “Quality assessment of speckle patterns for digital image correlation.” Opt. Lasers Eng., 44(11), 1132–1145.
Levenberg, E., and Uzan, J. (2004). “Quantifying the confidence levels of deformation measurements in asphalt concrete.” J. Test. Eval., 32(5), 358–365.
Lucas, B., and Kanade, T. (1981). “An iterative image registration technique with an application to stereo vision.” Proc., Int. Joint Conf. on Artificial Intelligence (IJCAI), Vancouver, Canada, 674–679.
Marcellier, H., Vescovo, P., Varchon, D., Vacher, P., and Humbert, P. (2001). “Optical analysis of displacement and strain fields on human skin.” Skin Res. Technol., 7(4), 246–253.
Mazzoleni, P. (2013). “Uncertainty estimation and reduction in digital image correlation measurements.” Ph.D. dissertation, Polytechnic Univ. of Milan, Milan, Italy.
Nyce, D. S. (2004). Linear position sensors: Theory and application, Wiley, Hoboken, NJ.
Pan, B. (2013). “Bias error reduction of digital image correlation using Gaussian pre-filtering.” Opt. Lasers Eng., 51(10), 1161–1167.
Pan, B., Lu, Z., and Xie, H. (2010). “Mean intensity gradient: An effective global parameter for quality assessment of the speckle patterns used in digital image correlation.” Opt. Lasers Eng., 48(4), 469–477.
Pan, B., Qian, K., Xie, H., and Asundi, A. (2009). “Two-dimensional digital image correlation for in-plane displacement and strain measurement: A review.” Meas. Sci. Technol., 20(6), 1–17.
Pan, B., Xie, H., Wang, Z., Qian, K., and Wang, Z. (2008). “Study on subset size selection in digital image correlation for speckle patterns.” Opt. Express, 16(10), 7037–7048.
Peters, W. H., and Ranson, W. F. (1982). “Digital imaging techniques in experimental stress analysis.” Opt. Eng., 21(3), 427–431.
Reu, P. L. (2011). “Experimental and numerical methods for exact subpixel shifting.” Exp. Mech., 51(4), 443–452.
Roux, S., Hild, F., Viot, P., and Bernard, D. (2008). “Three-dimensional image correlation from X-ray computed tomography of solid foam.” Compos. Part A, 39(8), 1253–1265.
Scholey, G. K., Frost, J. D., Lo Presti, D. C. F., and Jamiolkowski, M. (1995). “A review of instrumentation for measuring small strains during triaxial testing of soil specimens.” Geotech. Test. J., 18(2), 137–156.
Seo, Y., Kim, Y. R., Witczak, M. W., and Bonaquist, R. (2002). “Application of digital image correlation method to mechanical testing of asphalt-aggregate mixtures.” Transp. Res. Rec., 1789, 162–172.
Sjögren, T., Persson, P. E., and Vomacka, P. (2011). “Analyzing the deformation behavior of compacted graphite cast irons using digital image correlation techniques.” Key Eng. Mater., 457, 470–475.
Stoilov, G., Kavardzhikov, V., and Pashkouleva, D. (2012). “A comparative study of random patterns for digital image correlation.” J. Theor. Appl. Mech., 42(2), 55–66.
Sutton, M. A., McNeill, S. R., Jang, J., and Babai, M. (1988). “Effects of subpixel image restoration on digital correlation error estimates.” Opt. Eng., 27(10), 870–877.
Sutton, M. A., Orteu, J., and Schreier, H. W. (2009). Image correlation for shape, motion and deformation measurements: Basic concepts, theory and applications, Springer, New York.
Tian, Q., and Huhns, M. N. (1986). “Algorithms for subpixel registration.” Comput. Vision Graphics Image Process., 35(2), 220–233.
uEye Cockpit [Computer software]. IDS Imaging Development Systems (IDS), Obersulm, Germany.
Ullidtz, P., et al. (2010). “CalME: Mechanistic-empirical design program for flexible pavement rehabilitation.” Transp. Res. Rec., 2153, 143–152.
Velasques, R. A. (2009). “On the representative volume element of asphalt concrete with applications to low temperature.” Ph.D. dissertation, Univ. of Minnesota, Minneapolis.
Wang, Y., and Cuitino, A. M. (2002). “Full-field measurements of heterogeneous deformation patterns on polymeric foams using digital image correlation.” Int. J. Solids Struct., 39(13–14), 3777–3796.
Weissman, S. L., Sackman, J. L., Harvey, J., and Long, F. (1999). “Selection of laboratory test specimen dimension for permanent deformation of asphalt concrete pavements.” Transp. Res. Rec., 1681, 113–120.
Witczak, M. W., Kaloush, K., Pellinen, T., El-Basyouny, M., and Von-Quintus, H. (2002). “Simple performance test for Superpave mix design.”, National Academy Press, Washington, DC.
Yaofeng, S., and Pang, J. (2007). “Study of optimal subset size in digital image correlation of speckle pattern images.” Opt. Lasers Eng., 45(9), 967–974.
Yi-qiu, T., Lei, Z., Meng, G., and Li-yan, S. (2012). “Investigation of the deformation properties of asphalt mixtures with DIC technique.” Constr. Build. Mater., 37, 581–590.
Zhang, J., Jin, G., Ma, S., and Meng, L. (2003). “Application of an improved subpixel registration algorithm on digital speckle correlation measurement.” Opt. Laser Technol., 35(7), 533–542.
Zhou, F., Fernando, E., and Scullion, T. (2010). “Development, calibration, and validation of performance prediction models for the Texas M-E flexible pavement design system.”, Federal Highway Administration, Washington, DC.
Zhou, P., and Goodson, K. E. (2001). “Subpixel displacement and deformation gradient measurement using digital image/speckle Correlation (DISC).” Opt. Eng., 40(8), 1613–1620.
Information & Authors
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Published In
Journal of Materials in Civil Engineering
Volume 28 • Issue 9 • September 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Jun 21, 2015
Accepted: Dec 15, 2015
Published online: Mar 21, 2016
Discussion open until: Aug 21, 2016
Published in print: Sep 1, 2016
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