Damage Detection in Truss Bridges under Moving Load Using Time History Response and Members Influence Line Curves

Document Type : Research Papers

Authors

1 Ph.D. Student, Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.

2 Associate Professor, Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.

Abstract

In recent years, damage detection has been an important issue in the condition assessment of structures. This research presents a new method for the detection of damaged members in truss bridges under moving load using the time history response and influence line curves of the members. For this reason, two different Finite Element (FE) models of truss bridges under moving load with different damage scenarios have been investigated. The damaged members are detected by adapting the difference curve shape of displacement responses obtained from the intact and damaged models to the axial force influence line curve shape of these members. The results demonstrate that when a member of a truss bridge is damaged, the difference curve of displacement responses is similar in shape to the influence line curve of the damaged member. It should be noted that the proposed method can accurately diagnose the damaged members with the displacement response of only one desired point of the truss bridge.

Keywords


Brunell, G. and Kim, Y.J. (2013). “Effect of local damage on the behavior of a laboratory-scale steel truss bridge”, Engineering Structures, 48, 281-291.
Chan, T.H. and Ashebo, D.B. (2006). “Theoretical study of moving force identification on continuous bridges”, Journal of Sound and Vibration, 295(3-5), 870-883.
Chang, K.C. and Kim, C.W. (2016). “Modal-parameter identification and vibration-based damage detection of a damaged steel truss bridge”, Engineering Structures, 122, 156-173.
De Biagi, V. (2016). Structural behavior of a metallic truss under progressive damage”, International Journal of Solids and Structures, 82, 56-64.
Doebling, S.W., Farrar, C.R., Prime, M.B. and Shevitz, D.W. (1996). “Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review”, Los Alamos National Laboratory, Report No. LA-13070-MS, USDOE, Washington, DC.
González, A. and Hester, D. (2013). “An investigation into the acceleration response of a damaged beam-type structure to a moving force”, Journal of Sound and Vibration, 332(13), 3201-3217.
He, W.Y., Ren, W.X. and Zhu, S. (2017). “Damage detection of beam structures using quasi-static moving load induced displacement response”, Engineering Structures, 145, 70-82.
Hester, D., Brownjohn, J., Huseynov, F., Obrien, E., Gonzalez, A. and Casero, M. (2020). “Identifying damage in a bridge by analysing rotation response to a moving load”, Structure and Infrastructure Engineering, 16(7), 1050-1065.
Hilber, H.M. and Hughes, T.J. (1978). “Collocation, dissipation and [overshoot] for time integration schemes in structural dynamics”, Earthquake Engineering and Structural Dynamics, 6(1), 99-117.
Kim, Y.W., Kim, N.I. and Lee, J. (2016). “Damage identification of truss structures based on force method and free vibration analysis”, Advances in Structural Engineering, 19(1), 3-13.
Law, S.S. and Zhu, X.Q. (2004). “Dynamic behavior of damaged concrete bridge structures under moving vehicular loads”, Engineering Structures, 26(9), 1279-1293.
Li, J. snd Hao, H. (2016). “Health monitoring of joint conditions in steel truss bridges with relative displacement sensors”, Measurement, 88, 360-371.
Li, J. and Law, S.S. (2012). “Damage identification of a target substructure with moving load excitation”, Mechanical Systems and Signal Processing, 30, 78-90.
Li, J., Law, S.S. and Hao, H. (2013). “Improved damage identification in bridge structures subject to moving loads: numerical and experimental studies”, International Journal of Mechanical Sciences, 74, 99-111.
Lingyun, W., Mei, Z., Guangming, W. and Guang, M. (2005). “Truss optimization on shape and sizing with frequency constraints based on genetic algorithm”, Computational Mechanics, 35(5), 361-368.
Liu, Y. and Zhang, S. (2018). “Damage localization of beam bridges using quasi-static strain influence lines based on the BOTDA technique”, Sensors, 18(12), 4446.
Mahmoud, M.A. (2001). “Effect of cracks on the dynamic response of a simple beam subject to a moving load”, Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 215(3), 207-215.
Marchesiello, S., Fasana, A., Garibaldi, L. and Piombo, B.A.D. (1999). “Dynamics of multi-span continuous straight bridges subject to multi-degrees of freedom moving vehicle excitation”, Journal of Sound and Vibration, 224(3), 541-561.
McGetrick, P.J., Kim, C.W., González, A. and Brien, E.J. (2015). “Experimental validation of a drive-by stiffness identification method for bridge monitoring”, Structural Health Monitoring, 14(4), 317-331.
Misiti, M., Misiti, Y., Oppenheim, G. and Poggi, J.M. (2007). Wavelet toolbox 4-user’s guide, The MathWorks. Inc., Massachusetts, USA.
Moradipour, P., Chan, T.H. and Gallage, C. (2017). “Benchmark studies for bridge health monitoring using an improved modal strain energy method”, Procedia Engineering, 188, 194-200
Mousavi, A.A., Zhang, C., Masri, S.F. and Gholipour, G. (2020). “Structural damage localization and quantification based on a CEEMDAN Hilbert transform neural network approach: A model steel truss bridge case study”, Sensors, 20(5), 1271.
Narkis, Y. (1994). “Identification of crack location in vibrating simply supported beams”, Journal of Sound and Vibration, 172(4), 549-558.
Pakrashi, V., O'Connor, A. and Basu, B. (2010). “A bridge-vehicle interaction based experimental investigation of damage evolution”, Structural Health Monitoring, 9(4), 285-296.
Perez-Ramirez, C.A., Machorro-Lopez, J.M., Valtierra-Rodriguez, M., Amezquita-Sanchez, J.P., Garcia-Perez, A., Camarena-Martinez, D. and Romero-Troncoso, R.D.J. (2020). “Location of multiple damage types in a truss-type structure using multiple signal classification method and vibration signals”, Mathematics, 8(6), 932.
Rezaifar, O. and Doostmohammadi, M.R. (2016). “Damage detection of axially loaded beam: A frequency-based method”, Civil Engineering Infrastructures Journal, 49(1), 165-172.
Samadi, D., Taghaddos, H., Nili, M.H. and Noghabaei, M. (2021). “Development of a bridge maintenance system using bridge information modeling”, Civil Engineering Infrastructures Journal, 54(2), 351-364. 
Sinou, J.J. (2009). “A review of damage detection and health monitoring of mechanical systems from changes in the measurement of linear and non-linear vibrations”, Mechanical Vibrations: Measurement, Effects and Control, 643-702.
Siriwardane, S.C. (2015). “Vibration measurement-based simple technique for damage detection of truss bridges: A case study”, Case Studies in Engineering Failure Analysis, 4, 50-58.
Sun, Z., Nagayama, T., Su, D. and Fujino, Y. (2016). “A damage detection algorithm utilizing dynamic displacement of bridge under moving vehicle”, Shock and Vibration, 2016(January), 1-9.
Systèmes, D. (2014). ABAQUS analysis user's manual 6.14-2. Dassault Systèmes Simulia Corp., Providence, RI, USA.
Unno, K., Mikami, A. and Shimizu, M. (2019). “Damage detection of truss structures by applying machine learning algorithms”, International Journal, 16(54), 62-67.
Yang, J., Hou, P., Yang, C., Yang, N. and Li, K. (2021). “Damage identification method of box girder bridges based on distributed long-gauge strain influence line under moving load”, Sensors, 21(3), 915.
Yu, L. and Chan, T.H. (2007). “Recent research on identification of moving loads on bridges”, Journal of Sound and Vibration, 305(1-2), 3-21.
Zhang, W., Li, J., Hao, H. and Ma, H. (2017). “Damage detection in bridge structures under moving loads with phase trajectory change of multi-type vibration measurements” Mechanical Systems and Signal Processing, 87, 410-425.
Volume 55, Issue 1
June 2022
Pages 183-194
  • Receive Date: 23 November 2020
  • Revise Date: 05 June 2021
  • Accept Date: 28 June 2021
  • First Publish Date: 01 June 2022