Visual Image Correlation for Bridge Displacement Measurement

Bridge owners and managers are overwhelmed with increasing maintenance costs and decreasing maintenance budgets, and efficient allocation of resources is dependent on the ability to perform objective assessments of bridge health. One method to objectively assess the performance of a structure is the installation of traditional sensors, which typically need to be in physical contact with the bridge and may require special equipment for access to key bridge elements as well as wiring for power supply and data acquisition. Visual image correlation (VIC) is a noncontact, optical measurement technique that can be used as an alternative to traditional bridge response measurement instruments such as strain gages or linear variable differential transformers, commonly referred to as LVDTs. VIC was applied to a series of laboratory and field experiments for verification of VIC application for civil structures in which the VIC system and traditional sensors simultaneously were deployed. The collected measurements were used for structural model verification, alternative distribution factor calculation and development of load rating factors for condition assessment. The results from the field deployment at the Powder Mill Road Bridge in Barre, Massachusetts are presented herein.

References
[1] ASCE, “Report Card for America's Infrastructure,” 2013. [2] AASHTO, “Bridging the Gap- Restoring and Rebuilding the Nation's Bridges,” American Association of State Highway and Transportation Officials, Washington, D.C., 2008. [3] AASHTO, Manual for Bridge Evaluation, Washington, D.C.: American Association of State Highway and Transportation Officials, 2010. [4] ISHMII, 2010. [Online]. Available: http://www.ishmii.org/Literature/SHMGlossaryDefinitions.html. [Accessed 21 January 2011]. [5] U. Attanayake, P. Tang and A. Servi, “Non-Contact Bridge Deflection Measurement: Application of Laser Technology,” in ICSECM, 2011. [6] F. Chang, “Structural Health Monitoring,” in Diagnostics & Prognostics to Structural Health Management, Stanford, CA, 2003. [7] ISHMII, “Structural Health Monitoring Seen as Essential for FHWA Vision,” 2006. [Online]. Available: http:www.ishmii.org/News/forFHWAvision.html. [8] B. Benmokrane, A. El-Salakawy and T. Lackey, “Designing and Testing of Concrete Bridge Decks Reinforced with Glass FRP Bars,” Journal of Bridge Engineering, pp. 217-229, 2006. [9] E. Santini-Bell, M. Sanayei, C. Javdekar and E. Slavsky, “Multi-Response Parameter Estimation for Finite Element Model Updating Using Non-Destructive Test Data,” Journal of Structural Engineering, pp. 133(4): 1068-1079, 2007. [10] A. Wahdeh, J. Caffrey and S. Masri, “A vision-based approach for the direct measurement of displacements in vibrating systems,” Smart Materials and Structures, 2003. [11] P. A. Fuchs, G. A. Washer, S. B. Chase and M. Moore, “Laser-Based Instrumentation for Bridge Load Testing,” Journal of Performance of Constructed Facilities, pp. 213-219, 2004. [12] T. Rodriguez and N. Garcia, “An adaptive real-time monitoring system,” Machine Vision and Applications, pp. 21:555-576, 2003. [13] E. Santini-Bell, P. A. Brogan, P. J. Lefebvre, J. T. Peddle, B. Brenner and M. Sanayei, “Digital Imaging for Bridge Deflection Measurement of a Steel Girder Composite Bridge,” in TRB 90th Annual Meeting Compendium of Papers DVD, Washington, D.C., 2011. [14] Correlated Solutions, Inc., “Principle of Digital Image Correlation,” 2010. [Online]. Available: http://www.correlatedsolutions.com/index.php/principle-of-digital-image-correlation. [Accessed 22 February 2011]. [15] M. Sanayei, J. Phelps, J. Sipple, E. Santini-Bell and B. Brenner, “Instrumentation, Nondestructive Testing, and FEM Updating for Bridge Evaluation using Strain Measurements.,” Accepted for publication in the Journal of Bridge Engineering, 2011. [16] J. T. Peddle, DIGITAL IMAGE CORRELATION AS A TOOL FOR BRIDGE LOAD RATING AND LONGTERM EVALUATION, Durham: University of New Hampshire, 2010. [17] E. Santini-Bell, P. Lefebvre, M. Sanayei, B. Brenner, J. Sipple and J. Peddle, “Objective Load Rating of a Steel-Girder Bridge Using Structural Modeling and Health Monitoring,” Journal of Structurel Engineering, vol. 139, pp. 1771-1779, 2013. [18] Mn/DOT, “Bridge Rating 101,” 2008. [Online]. Available: http://www.dot.state.mn.us/stateaid/LoadRatingClass101/BridgeRatingClass101allsections.pdf. [Accessed 4 April 2011]. [19] AASHTO, Manual for Bridge Evaluation, American Association of State and Highway Transportation Officials , 2011. [20] M. J. Chajes, D. R. Mertz and B. Commander, “Experimental Load Rating of a Posted Bridge,” Journal of Bridge Engineering, 1997.
Metrics
Usage Shares
Total Views
47 Page Views
Total Shares
0 Tweets
47
0 PDF Downloads
0
0 Facebook Shares
Total Usage
47