Nondestructive Bridge Deck Evaluation Using Sub-mm 3D Laser Imaging Technology at Highway Speeds
Publication: Journal of Bridge Engineering
Volume 27, Issue 6
Abstract
Periodic bridge deck inspection is critically important in bridge management and maintenance. This paper presents a comprehensive bridge deck evaluation using sub-mm three-dimensional (3D) laser imaging technology in a nondestructive and efficient manner at highway speeds with complete lane coverage. A total of 58 bridge decks in Oklahoma were evaluated via Pave3D 8K system and 3D Safety Sensor. The Pave3D 8K system collected both 0.5-mm 3D height images, 2D grayscale images, and longitudinal profiler at highway speeds for bridge deck assessment in terms of distress detection and roughness evaluation. A Deep Learning-based method was applied to detect cracks automatically, and a manual tool was developed to label other distress for bridge decks and joints from the obtained images. Further, the 0.5-mm 3D images and longitudinal profiler data were combined to identify locations with roughness issues and the causes on bridge decks or approach slabs. Finally, the 3D Safety Sensor acquired 0.1-mm 2D/3D images for hydroplaning speed prediction of bridge decks. The evaluation results demonstrate the efficacy of the sub-mm 3D laser imaging technology for nondestructive bridge deck conditions and safety evaluations.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This work was supported by the research project, Sub-mm 3D Laser Imaging for Bridge Deck Surveys, sponsored by the Oklahoma Department of Transportation (ODOT). The opinions expressed in the paper are those of the authors, who are responsible for the accuracy of the facts and data herein and do not necessarily reflect the official policies of the sponsoring agency. This paper does not constitute a standard, regulation, or specification.
References
AASHTO. 2002. Bridge inspector’s reference manual (BIRM). Chapter 7 inspection and evaluation bridges decks and areas adjacent to bridge decks. Washington, DC: AASHTO.
Abdel-Qader, I., S. Yohali, O. Abudayyeh, and S. Yehia. 2008. “Segmentation of thermal images for nondestructive evaluation of bridge decks.” NDT & E Int. 41: 395–405. https://doi.org/10.1016/j.ndteint.2007.12.003.
ASCE. 2017. “Infrastructure report card.” MUD history, www.infrastructurereportcard.org. Accessed April 20, 2017. https://www.infrastructurereportcard.org/wp-content/uploads/2016/10/2017-Infrastructure-Report-Card.pdf.
ASTM. 2015. Standard practice for computing international roughness index of roads from longitudinal profile measurements. ASTM E1926-08. West Conshohocken, PA: ASTM.
Baiocchi, V., D. Dominici, and M. Mormile. 2013. “UAV application in post-seismic environment.” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XL-1/W2 (1): 21–25. https://doi.org/10.5194/isprsarchives-XL-1-W2-21-2013.
Carroll, E. A., and D. B. Rathbone. 2002. “Using an unmanned airborne data acquisition system (ADAS) for traffic surveillance, monitoring, and management.” In Proc., Int. Mechanical Engineering Congress and Exposition, 145–157. New York: ASME.
Coifman, B., M. McCord, R. G. Mishalani, M. Iswalt, and Y. Ji. 2006. “Roadway traffic monitoring from an unmanned aerial vehicle.” IEE Proc. Intel. Transport Syst. 153 (1): 11–20. https://doi.org/10.1049/ip-its:20055014.
de Haas, T., D. Ventra, P. E. Carbonneau, and M. G. Kleinhans. 2014. “Debris-flow dominance of alluvial fans masked by runoff reworking and weathering.” Geomorphology 217: 165–181. https://doi.org/10.1016/j.geomorph.2014.04.028.
Ding, Y. M., and H. Wang. 2020. “Computational investigation of hydroplaning risk of wide-base truck tyres on roadway.” Int. J. Pavement Eng. 21 (1): 122–133. https://doi.org/10.1080/10298436.2018.1445249.
Dorafshan, S., M. Maguire, N. V. Hoffer, and C. Coopmans. 2017. “Challenges in bridge inspection using small unmanned aerial systems: Results and lessons learned.” In Proc., Int. Conf., on Unmanned Aircraft Systems, 1722–1730. New York: IEEE.
Farradine, P. 2005. Use of unmanned aerial vehicles in traffic surveillance and traffic management., Tech. Rep. Florida Department of Transportation.
Fei, Y., K. C. P. Wang, A. Zhang, C. Chen, J. Q. Li, Y. Liu, G. Yang, and B. Li. 2019. “Pixel-level cracking detection on 3D asphalt pavement images through deep-learning-based CrackNet-V.” IEEE Trans. Intell. Transp. Syst. 21 (1): 273–284. https://doi.org/10.1109/TITS.2019.2891167.
Gallaway, B. M., G. G. Hayes, D. L. Ivey, W. B. Ledbetter, and R. M. Olson. 1979. Pavement and geometric design criteria for minimizing hydroplaning. FHWA-RD-79-30. College Station, TX: Texas Transportation Institute.
Gucunski, N., S. Kee, H. M. La, B. Basily, A. Maher, and H. Ghasemi. 2015. “Implementation of a fully autonomous platform for assessment of concrete bridge decks RABIT.” In Proc., of Structures Congress, 367–378. Reston, VA: ASCE.
Henderson, B., J. Dickes, G. Gimini, and C. Olmedo. 2016. FHWA LTPP guidelines for measuring bridge approach transitions using inertial profilers. FHWA-HRT-16-072. Washington, DC: FHWA.
Horne, W. B., and R. C. Dreher. 1963. Phenomena of pneumatic tire hydroplaning. Hampton, VA: National Aeronautics and Space Administration, Longley Research Center.
Khedr, S. A., and T. M. Breakah. 2011. “Rutting parameters for asphalt concrete for different aggregate structures.” Int. J. Pavement Eng. 12 (1): 13–23. https://doi.org/10.1080/10298430903578960.
Kumar, S. S., A. Kumar, and T. Fwa. 2010. “Analyzing effect of tire groove patterns on hydroplaning speed.” J. East. Asia Soc. Transp. Stud. 2010 (8): 2018–2031.
Laurent, J., D. Lefebvre, and E. Samson. 2008. “Development of a new 3D transverse laser profiling system for the automatic measurement of road cracks.” In Proc., 6th Symp. on Pavement Surface Characteristics, SURF 2008. Paris, France: PIARC.
Lee, H. S., M. Carvajal, C. Holzschuher, and B. Choubane. 2021. “Florida department of transportation’s enhanced hydroplaning prediction tool.” Transp. Res. Rec. 2675: 340–352. https://doi.org/10.1177/03611981211011479.
Lim, R. S., H. M. La, and W. Sheng. 2014. “A robotic crack inspection and mapping system for bridge deck maintenance.” IEEE Trans. Autom. Sci. Eng. 11 (2): 367–378. https://doi.org/10.1109/TASE.2013.2294687.
Lu, Q., M. Li, M. Gunaratne, C. Xin, M. M. Hoque, and M. Rajalingola. 2018. Best practices for construction and repair of bridge approaches and departures. Report No. BDV25-977-31. Tallahassee, FL: Florida DOT.
McGhee, K. K. 2002. A new approach to measuring the ride quality of highway bridges. VTRC 02-R10. Charlottesville, VA: Virginia Transportation Research Council.
Minor, J., K. R. White, and R. S. Busch. 1988. Condition surveys of concrete bridge components—User’s manual. NCHRP Rep. No. 312. Washington, DC: National Cooperative Highway Research Program.
Mishra, D., J. McAtee, M. Chowdhury, B. Chittoori, E. Tutumluer, and J. Nicks. 2021. Statistical analysis of pavement profiler data to evaluate the bump at the end of the bridge. FHWA-HRT-21-037. Washington, DC: Federal Highway Administration.
NBIS (National Bridge Inspection Standards). 2004. 23 C.F.R. §650.303-§650.313.
Nicks, J. E., and M. T. Adams. 2018. “Quantifying the bump at the end of the bridge with inertial profilers pilot study: Comparing deep versus shallow foundation systems.” In Proc., Int. Foundations Congress & Equipment Expo. Reston, VA: ASCE.
ODOT. 2020. BrM bridge inspection field manual for Oklahoma bridges. Oklahoma City, OK: Oklahoma Department of Transportation Bridge Division.
Olmedo, C., B. Henderson, G. Cimini, and J. Springer. 2015. “Bump determination at bridge approach transitions using inertial profilers.” In Proc., Conf. of the Transportation Association of Canada. Ottawa: Transportation Association of Canada.
Ong, G. P., and T. F. Fwa. 2007. “Wet-pavement hydroplaning risk and skid resistance: Modeling.” J. Transp. Eng. 133 (10): 590–598. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:10(590).
Otero, L., N. Gagliardo, D. Dalli, W. Huang, and P. Cosentino. 2015. Proof of concept for using unmanned aerial vehicles for high mast pole and bridge inspections. FDOT Final Rep. No. BDV28 TWO 977-02. Melbourne, FL: Dept. of Engineering System, Florida Institute of Technology.
Ouyang, W., and B. Xu. 2013. “Pavement cracking measurements using 3D laser-scan images.” Meas. Sci. Technol. 24 (10): 105204. https://doi.org/10.1088/0957-0233/24/10/105204.
Park, K., N. E. Thomas, and W. K. Lee. 2007. “Applicability of the international roughness index as a predictor of asphalt pavement condition.” J. Transp. Eng. 133 (12): 706–709. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:12(706).
Rajalingola, M. 2017. “Analysis of distress in asphalt pavement transitions on bridge approaches and departures.” Master’s thesis, Dept. of Civil and Environmental Engineering, Univ. of South Florida.
Rufino, D., K. BaRaKa, and M. Darter. 2001. Development of a bridge smoothness specification for Illinois DoT. Report No. FHWA-IL-UI-279. Springfield, IL: Illinois DoT.
Sayers, M., T. Gillespie, and C. Queiroz. 1982. International experiment to establish correlation and standard calibration methods for road roughness measurements. Washington, DC: The World Bank.
Scott, M., A. Rezaizadeh, A. Delahaza, C. G. Santos, M. Moore, B. Graybeal, and G. Washer. 2003. “A comparison of nondestructive evaluation methods for bridge deck assessment.” NDT & E Int. 36: 245–255. https://doi.org/10.1016/S0963-8695(02)00061-0.
Tsai, Y. J., C. Jiang, and Z. Wang. 2012. “Pavement crack detection using high-resolution 3D line laser imaging technology.” In Proc., 7th RILEM Int. Conf., on Cracking in Pavements, 169–178. Delft, Netherlands: Delft University of Technology.
Wang, K. C. P. 2011. “Elements of automated survey of pavements and a 3D methodology.” J. Mod. Transp. 19 (1): 51–57. https://doi.org/10.1007/BF03325740.
Wang, K. C. P., W. Luo, and J. Q. Li. 2014. “Hydroplaning risk evaluation of highway pavements based on IMU and 1 mm 3D texture data.” In Proc., 2nd Transportation & Development Congress, edited by A. Varma and G. D. Gosling, 511–522. Reston, VA: ASCE.
Yoon, S., G.-H. Gwon, J.-H. Lee, and H.-J. Jung. 2021. “Three-dimensional image coordinate-based missing region of interest area detection and damage localization for bridge visual inspection using unmanned aerial vehicles.” Struct. Health Monit. 20 (4): 1462–1475. https://doi.org/10.1177/1475921720918675.
Zhang, C., D. Walters, J. M. Kovacs, and Q. K. Hassan. 2014. “Applications of low altitude remote sensing in agriculture upon farmers’ requests—A case study in northeastern Ontario, Canada.” PLoS ONE 9 (11): e112894. https://doi.org/10.1371/journal.pone.0112894.
Information & Authors
Information
Published In
Journal of Bridge Engineering
Volume 27 • Issue 6 • June 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Nov 21, 2021
Accepted: Mar 3, 2022
Published online: Apr 15, 2022
Published in print: Jun 1, 2022
Discussion open until: Sep 15, 2022
Authors
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
- Guolong Wang, Kelvin C.P. Wang, Guangwei Yang, Joshua Qiang Li, Walt Peters, Evaluation of Bridge Approach Slab and Dynamic Load Allowance Using Sub-mm 3D Laser Imaging Technology, Journal of Bridge Engineering, 10.1061/JBENF2.BEENG-6155, 28, 7, (2023).