Field Validation of a Statistical-Based Bridge Damage-Detection Algorithm
Publication: Journal of Bridge Engineering
Volume 18, Issue 11
Abstract
This paper describes a field validation of a second-generation, statistical-based damage-detection algorithm and its ability to detect actual damage in bridges accurately. The algorithm had been theoretically validated previously. For the field tests, in lieu of introducing damage to a public bridge, two sacrificial specimens that simulated damage-sensitive locations of the bridge were mounted on the bridge, and different types and levels of damage in the form of cracks and simulated corrosion were induced in the specimens. Using strain data collected from sensors on the sacrificial specimens and on the bridge, the algorithm correctly identified the damage. Analysis of data from sensors far away from the damaged area revealed a relatively high false-positive rate.
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Acknowledgments
The authors thank the Iowa DOT for funding this work. The authors also thank the staff of the Iowa DOT Office of Bridges and Structures and, specifically, Ahmad Abu-Hawash and Bruce Brakke for their interest in and help with this developmental work. Other contributing members of the Iowa State team, whose field assistance made this work possible, are Travis Hosteng and Doug Wood.
References
Chintalapudi, K., et al. (2006). “Monitoring civil structures with a wireless sensor network.” IEEE Internet Comput., 10(2), 26–34.
Doebling, S. W., Farrar, C. R., Prime, M. B., and Shevitz, D. W. (1996). “Damage identification and health monitoring of structural and mechanical system from changes in their vibration characteristics: A literature review.” Rep. LA-13070-MS, Los Alamos National Laboratory, Los Alamos, NM.
Doornink, J. D. (2006). “Damage detection in bridges through fiber optic structural health monitoring.” Proc. SPIE Int. Soc. Opt. Eng., 6371.
Guan, H., Karbhari, V. M., and Sikorsky, C. S. (2007). “Long-term structural health monitoring system for a FRP composite highway bridge structure.” J. Intell. Mater. Syst. Struct., 18(8), 809–823.
Lu, P. (2008). “A statistical based damage detection approach for highway bridge structural health monitoring.” Doctoral dissertation, Iowa State Univ., Ames, IA.
Olund, J., and DeWolf, J. (2007). “Passive structural health monitoring of Connecticut’s bridge infrastructure.” J. Infrastruct. Syst., 13(4), 330–339.
Panigrahi, S. K., Chakraverty, S., and Mishra, B. K. (2009). “Vibration based damage detection in a uniform strength beam using genetic algorithm.” Meccanica, 44(6), 697–710.
Phares, B. M., Wipf, T. J., Ping, L., Greiman, L., and Pohlkamp, M. (2011). “An experimental validation of a statistical-based damage-detection approach.” Rep. No. InTrans Project 08-336, Bridge Engineering Center, Iowa State Univ., Ames, IA.
Wang, S., Ren, Q., and Qiao, P. (2006). “Structural damage detection using local damage factor.” J. Vib. Control,12(9), 955–973.
Wipf, T. J., Phares, B. M., and Doornink, J. D. (2007). “Monitoring the structural condition of fracture-critical bridges using fiber optic technology.” Rep. No. IHRB Project TR-493, Center for Transportation Research and Education, Iowa State Univ., Ames, IA.
Yuan, S., Lai, X., Zhao, X., Xu, X., and Zhang, L. (2005). “Distributed structural health monitoring system based on smart wireless sensor and multi-agent technology.” Smart Mater. Struct., 15(1), 1–8.
Information & Authors
Information
Published In
Journal of Bridge Engineering
Volume 18 • Issue 11 • November 2013
Pages: 1227 - 1238
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Feb 16, 2012
Accepted: Jan 14, 2013
Published online: Oct 15, 2013
Published in print: Nov 1, 2013
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