Technical Papers
Jan 23, 2019

Field Deployment and Laboratory Evaluation of 2D Digital Image Correlation for Deflection Sensing in Complex Environments

Publication: Journal of Bridge Engineering
Volume 24, Issue 4

Abstract

This study explored the application of two-dimensional digital image correlation (2D-DIC) for measuring deflections of in-service bridges. Within the emerging area of image-based structural health monitoring, this work builds from previous efforts to deploy vision-based sensing techniques for describing the operational behavior of structures. Whereas the literature includes deflection measurement systems using cameras mounted on fixed ground near the bridge span at maximum distances of approximately 300 m, this work proposes an innovative setup that enables deflection measurement in remote, offshore, and complex environments. This paper first describes a laboratory study aimed at evaluating the system performance and identifying the sources of measurement error, thus determining the level of confidence in the results and the range of applicability. The laboratory study demonstrated that the setup, designed using an inexpensive consumer-grade imaging system, had an average error consistently less than 0.2 mm (0.0075 in.). In addition, the system was deployed during a field test on a high-profile bridge structure nearly 1 mile offshore. The test program and results are presented to assess the logistics and performance of the system during load testing. Results from the study indicate the feasibility of the proposed setup for measuring deflections without a fixed ground reference.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors acknowledge the Virginia Department of Transportation (VDOT) for providing access and logistical support for executing the field test. The contents of this paper reflect the views of the authors, but not necessarily the official views of the VDOT. A team of researchers from Virginia Tech, including Dr. Carin Roberts-Wollmann, Dr. Matthew Hebdon, James Riley, and Ezra Edwin, also contributed significantly to the collaborative field testing, which will be the subject of future publications. The authors thank undergraduate students Dequante McKoy and Ahmed Osman for their help with the experiments and data processing, Dr. Andrei Ramniceanu and Dr. Abdollah Bagheri for their help during the field test, and Keegan Gumbs for contributions to the laboratory study.

References

Alipour, M., D. K. Harris, and O. E. Ozbulut. 2016. “Vibration testing for bridge load rating.” Dyn. Civ. Struct. 2: 175–184.
Bartoli, G., L. Facchini, M. Pieraccini, M. Fratini, and C. Atzeni. 2008. “Experimental utilization of interferometric radar techniques for structural monitoring.” Struct. Control Health Monit. 15 (3): 283–298. https://doi.org/10.1002/stc.252.
Chan, T. H. T., D. B. Ashebo, H. Y. Tam, Y. Yu, T. F. Chan, P. C. Lee, and E. Perez Gracia. 2009. “Vertical displacement measurements for bridges using optical fiber sensors and CCD cameras: A preliminary study.” Struct. Health Monit. 8 (3): 243–249. https://doi.org/10.1177/1475921708102108.
Chen, T., P. B. Catrysse, A. El Gamal, and B. A. Wandell. 2000. “How small should pixel size be?” Proc. Soc. Photo-Opt. Ins. 3965: 451–460.
Correlated Solutions, Inc. 2017. VIC-2D v6 full-field deformation measurement system. Irmo, SC: Correlated Solutions, Inc.
Crammond, G., S. W. Boyd, and J. M. Dulieu-Barton. 2013. “Speckle pattern quality assessment for digital image correlation.” Opt. Lasers Eng. 51 (12): 1368–1378. https://doi.org/10.1016/j.optlaseng.2013.03.014.
Devore, J. L., N. R. Farnum, and J. A. Doi. 2014. Applied statistics for engineers and scientists. 3rd ed. Stamford, CT: Cengage Learning.
Dizaji, M. S., M. Alipour, and D. K. Harris. 2018. “Leveraging full-field measurement from 3D digital image correlation for structural identification.” Exp. Mech. 58 (7): 1049–1066. https://doi.org/10.1007/s11340-018-0401-8.
Dizaji, M., D. Harris, M. Alipour, and O. Ozbulut. 2017. “En‘vision’ing a novel approach for structural health monitoring—A model for full-field structural identification using 3D–digital image correlation.” InProc., 8th Int. Conf. on Structural Health Monitoring of Intelligent Infrastructure, 5–8. Winnipeg, MB, Canada: Intl. Society for Structural Health Monitoring of Intelligent Infrastructure, Univ. of Manitoba.
Feng, D., and M. Q. Feng. 2017. “Experimental validation of cost-effective vision-based structural health monitoring.” Mech. Syst. Sig. Process 88: 199–211. https://doi.org/10.1016/j.ymssp.2016.11.021.
Fukuda, Y., M. Q. Feng, and M. Shinozuka. 2010. “Cost-effective vision-based system for monitoring dynamic response of civil engineering structures.” Struct. Control Health Monit. 17 (8): 918–936. https://doi.org/10.1002/stc.360.
Hijazi, A., A. Friedl, and C. J. Kähler. 2011. “Influence of camera’s optical axis non-perpendicularity on measurement accuracy of two-dimensional digital image correlation.” Jordan J. Mech. Ind. Eng. 5 (4): 373–382.
Hua, T., H. Xie, S. Wang, Z. Hu, P. Chen, and Q. Zhang. 2011. “Evaluation of the quality of a speckle pattern in the digital image correlation method by mean subset fluctuation.” Opt. Laser Technol. 43 (1): 9–13. https://doi.org/10.1016/j.optlastec.2010.04.010.
Im, S. B., S. Hurlebaus, and Y. J. Kang. 2013. “Summary review of GPS technology for structural health monitoring.” J. Struct. Eng. 139 (10): 1653–1664. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000475.
Lecompte, D., A. Smits, S. Bossuyt, H. Sol, J. Vantomme, D. Van Hemelrijck, and A. M. Habraken. 2006. “Quality assessment of speckle patterns for digital image correlation.” Opt. Lasers Eng. 44 (11): 1132–1145. https://doi.org/10.1016/j.optlaseng.2005.10.004.
Nassif, H. H., M. Gindy, and J. Davis. 2005. “Comparison of laser Doppler vibrometer with contact sensors for monitoring bridge deflection and vibration.” NDT and E Int. 38 (3): 213–218. https://doi.org/10.1016/j.ndteint.2004.06.012.
Otsu, N. 1979. “A threshold selection method from gray-level histograms.” IEEE Trans. Syst., Man., Cybermetics 9 (1): 62–66. https://doi.org/10.1109/TSMC.1979.4310076.
Pan, B., K. Qian, H. Xie, and A. Asundi. 2009. “Two-dimensional digital image correlation for in-plane displacement and strain measurement: A review.” Meas. Sci. Technol. 20 (6): 062001. https://doi.org/10.1088/0957-0233/20/6/062001.
Pan, B., L. Tian, and X. Song. 2016. “Real-time, non-contact and targetless measurement of vertical deflection of bridges using off-axis digital image correlation.” NDT and E Int. 79: 73–80. https://doi.org/10.1016/j.ndteint.2015.12.006.
Peddle, J., A. Goudreau, E. Carson, and E. Santini-Bell. 2011. “Bridge displacement measurement through digital image correlation.” Bridge Struct. 7 (4): 165–173.
Ribeiro, D., R. Calçada, J. Ferreira, and T. Martins. 2014. “Non-contact measurement of the dynamic displacement of railway bridges using an advanced video-based system.” Eng. Struct. 75: 164–180. https://doi.org/10.1016/j.engstruct.2014.04.051.
Rice, J. A., C. Gu, C. Li, and S. Guan. 2012. “A radar-based sensor network for bridge displacement measurements.” Proc. SPIE 7981: 79810I.
Rodrigues, C., C. Félix, and J. Figueiras. 2011. “Fiber-optic-based displacement transducer to measure bridge deflections.” Struct. Health Monit. 10 (2): 147–156. https://doi.org/10.1177/1475921710373289.
Shariati, A., and T. Schumacher. 2017. “Eulerian-based virtual visual sensors to measure dynamic displacements of structures.” Struct. Control Health Monit. 24 (10): e1977. https://doi.org/10.1002/stc.1977.
Sohn, H., C. R. Farrar, F. M. Hemez, D. D. Shunk, D. W. Stinemates, B. R. Nadler. et al. 2004. A review of structural health monitoring literature: 1996–2001. Technical Rep. LA-13976-MS. Los Alamos, NM: Los Alamos National Laboratory.
Sutton, M. A., J.-J. Orteu, and H. W. Schreier. 2009. Image correlation for shape, motion and deformation measurements: Basic concepts, theory and applications. New York: Springer.
Wang, Z. Y., H. Q. Li, J. W. Tong, and J. T. Ruan. 2007. “Statistical analysis of the effect of intensity pattern noise on the displacement measurement precision of digital image correlation using self-correlated images.” Exp. Mech. 47 (5): 701–707. https://doi.org/10.1007/s11340-006-9005-9.
Yoneyama, S., A. Kitagawa, S. Iwata, K. Tani, and H. Kikuta. 2007. “Bridge deflection measurement using digital image correlation.” Exp. Tech. 31 (1): 34–40. https://doi.org/10.1111/j.1747-1567.2006.00132.x.
Yoneyama, S., and G. Murasawa. 2009. “Digital image correlation.” Exp. Mech. 31 (1): 34–40.

Information & Authors

Information

Published In

Go to Journal of Bridge Engineering
Journal of Bridge Engineering
Volume 24Issue 4April 2019

History

Received: Apr 5, 2018
Accepted: Sep 24, 2018
Published online: Jan 23, 2019
Published in print: Apr 1, 2019
Discussion open until: Jun 23, 2019

Permissions

Request permissions for this article.

Authors

Affiliations

Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Virginia McCormick Road, Charlottesville, VA 22904-4742 (corresponding author). ORCID: https://orcid.org/0000-0003-2018-134X. Email: [email protected]
Savannah J. Washlesky, S.M.ASCE
Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., Charlottesville, VA 22904-4742.
Devin K. Harris, A.M.ASCE
Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., Charlottesville, VA 22904-4742.

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share