Damage Detection in the Cable Structures of a Bridge Using the Virtual Distortion Method
Publication: Journal of Bridge Engineering
Volume 22, Issue 8
Abstract
This study investigated damage detection of cable structures in bridge engineering using the virtual distortion method (VDM). The main theory of damage detection based on the VDM, including the influence matrix, the stiffness reduction, and an optimized algorithm, was applied to damage detection in hangers in a real three-dimensional finite-element model (FEM) of an existing arch bridge. Two damage-detection methods for hangers were used. One method is based on the static VDM, which has high precision but requires more sensors. The other method is based on the dynamic VDM, which does not require many sensors but has a lower precision. The effectiveness of damage detection in hangers was investigated through a numerical simulation. The steps of damage detection that can be combined with practical engineering were determined. The anti-interference ability of the wind load, the optimal placement of sensors, and the antinoise capability were considered in the case study. It was verified that the proposed methods can rapidly and accurately identify the damage location and degree of damage.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This research work was jointly supported by the National Natural Science Foundation of China (Grants 51625802 and 51478081), the 973 Program (Grant 2015CB060000), and the Science Fund for Distinguished Young Scholars of Dalian (Grant 2015J12JH209).
References
Abdullah, A. B. M., Rice, J. A., Hamilton, H. R., and Consolazio, G. R. (2016). “Experimental and numerical evaluation of unbonded posttensioning tendons subjected to wire breaks.” J. Bridge Eng., 04016066.
Caprani, C. C. (2012). “Lifetime highway bridge traffic load effect from a combination of traffic states allowing for dynamic amplification.” J. Bridge Eng., 901–909.
Casciati, S., and Elia, L. (2016). “Damage localization in a cable-stayed bridge via bio-inspired metaheuristic tools.” Struct. Control Health Monit.
Chang, K. C., Kim, C. W., and Kawatani, M. (2014). “Feasibility investigation for a bridge damage identification method through moving vehicle laboratory experiment.” Struct. Infrastruct. Eng., 10(3), 328–345.
Chen, W. Z., and Yang, J. X. (2014). “Inspection and assessment of stay cables in cable stayed bridges.” Appl. Mech. Mater., 638–640, 954–960.
Chen, Z.-W., Zhu, S., Xu, Y.-L., Li, Q., and Cai, Q.-L. (2014). “Damage detection in long suspension bridges using stress influence lines.” J. Bridge Eng., 05014013.
Cho, K. H., et al. (2013). “Inspection robot for hanger cable of suspension bridge: Mechanism design and analysis.” IEE/ASME Trans. Mechatron., 18(6), 1665–1674.
Esfandiari, A., Rahai, A., Sanayei, M., and Bakhtiari-Nejad, F. (2016). “Model updating of a concrete beam with extensive distributed damage using experimental frequency response function.” J. Bridge Eng., 04015081.
Gaul, L., Sprenger, H., Schaal, C., and Bischoff, S. (2012). “Structural health monitoring of cylindrical structures using guided ultrasonic waves.” Acta Mech., 223(8), 1669–1680.
Hou, J., Jankowski, Ł., and Ou, J. (2013). “Structural damage identification by adding virtual masses.” Struct. Multidiscip. Optim., 48(1), 59–72.
Huang, D. (2011). “Vehicle-induced vibration of steel deck arch bridges and analytical methodology.” J. Bridge Eng., 241–248.
Kim, S.-W., Jeon, B.-G., Kim, N.-S., and Park, J.-C. (2013). “Vision-based monitoring system for evaluating cable tensile forces on a cable-stayed bridge.” Struct. Health Monit., 12(5–6), 440–456.
Kolakowski, P., Wikło, M., and Holnicki-Szulc, J. (2008). “The virtual distortion method-a versatile reanalysis tool for structures and systems.” Struct. Multidiscip. Optim., 36(3), 217–234.
Lan, C., Zhou, Z., and Ou, J. (2014). “Monitoring of structural prestress loss in RC beams by inner distributed Brillouin and fiber Bragg grating sensors on a single optical fiber.” Struct. Control Health Monit., 21(3), 317–330.
Larsen, A., and Larose, G. L. (2015). “Dynamic wind effects on suspension and cable-stayed bridges.” J. Sound Vib., 334, 2–28.
Li, H. N., Li, D. S., Ren, L., Yi, T.-H., Jia, Z.-G., and Li, K.-P. (2016). “Structural health monitoring of innovative civil engineering structures in Mainland China.” Struct. Monit. Maint., 3(1), 1–32.
Liu, Y., Ma, J., Nie, J., and Zhang, S. (2015). “Virtual distortion method-based finite element model updating of bridges by using static deformation.” J. Eng. Mech., B4015003.
MATLAB [Computer software]. MathWorks, Natick, MA.
MIDAS Civil [Computer software]. MIDAS Information Technology Company, Houston.
Nakamura, S., and Suzumura, K. (2012). “Experimental study on fatigue strength of corroded bridge wires.” J. Bridge Eng., 200–209.
Sloane, M. J. D., Betti, R., Marconi, G., Hong, A. L., and Khazem, D. (2012). “Experimental analysis of a nondestructive corrosion monitoring system for main cables of suspension bridges.” J. Bridge Eng., 653–662.
Sun, L., He, G., Wang, Y., and Fang, L. (2009). “An active set quasi-Newton method with projected search for bound constrained minimization.” Comput. Math. Appl., 58(1), 161–170.
Świercz, A., Kołakowski, P., and Holnicki-Szulc, J. (2008). “Damage identification in skeletal structures using the virtual distortion method in frequency domain.” Mech. Syst. Sig. Process., 22(8), 1826–1839.
Vanniamparambil, P. A., et al. (2013). “Novel optico-acoustic nondestructive testing for wire break detection in cables.” Struct. Control Health Monit., 20(11), 1339–1350.
Wang, X., Huang, C., Huang, P., and Yu, X. (2016). “Study on wind characteristics of a strong typhoon in near-ground boundary layer.” Struct. Des. Tall Special Build., 26(5).
Xu, F., Wang, X., and Wu, H. (2017). “Inspection method of cable-stayed bridge using magnetic flux leakage detection: Principle, sensor design, and signal processing.” J. Mech. Sci. Technol., 26(3), 661–669.
Yang, Y., Li, S., Nagarajaiah, S., Li, H., and Zhou, P. (2016). “Real-time output-only identification of time-varying cable tension from accelerations via complexity pursuit.” J. Struct. Eng., 04015083.
Yim, J., et al. (2013). “Field application of elasto-magnetic stress sensors for monitoring of cable tension force in cable-stayed bridges.” Smart Struct. Syst., 12(3–4), 465–482.
Zejli, H., Gaillet, L., Laksimi, A., and Benmedakhene, S. (2012). “Detection of the presence of broken wires in cables by acoustic emission inspection.” J. Bridge Eng., 921–927.
Zhang, Q., Jankowski, L., and Duan, Z. (2012). “Simultaneous identification of excitation time histories and parametrized structural damages.” Mech. Syst. Sig. Process., 33, 56–68.
Information & Authors
Information
Published In
Journal of Bridge Engineering
Volume 22 • Issue 8 • August 2017
Copyright
© 2017 American Society of Civil Engineers.
History
Received: Oct 27, 2016
Accepted: Feb 23, 2017
Published online: May 23, 2017
Published in print: Aug 1, 2017
Discussion open until: Oct 23, 2017
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.