Structural damage detection of steel bridge girder using artificial neural networks and finite element models

Steel and Composite Structures

Volumn 14, Issue 4, 2013, Pages 367-377

  Hakim, S J S ^a   Abdul Razak, H ^a  

^a UNIVERSITY OF MALAYA   (Malaysia)

Author keywords

Artificial neural networks (ANNs); Backpropagation algorithm; Damage detection; Finite element; Natural frequency

Indexed keywords

BACKPROPAGATION ALGORITHMS; BEAMS AND GIRDERS; DEEP NEURAL NETWORKS; FINITE ELEMENT METHOD; MODAL ANALYSIS; NATURAL FREQUENCIES; NEURAL NETWORKS; PLATE GIRDER BRIDGES; STRUCTURAL ANALYSIS;

BIOLOGICAL NEURON; DAMAGE IDENTIFICATION; EFFECTIVE INPUTS; NATURAL FREQUENCIES AND MODES; STEEL BRIDGE GIRDERS; STEEL GIRDER BRIDGE; STRUCTURAL DAMAGE DETECTION; STRUCTURAL DAMAGE IDENTIFICATION;

DAMAGE DETECTION;

EID: 84876835623     PISSN: 12299367     EISSN: None     Source Type: Journal    
DOI: 10.12989/scs.2013.14.4.367     Document Type: Article

References (29)

1. Fonseca, E.T. and Vellasco, P.G.S. (2003), "A path load parametric analysis using neural networks", J. Construct. Steel Res., 59, 251-267.
2. Funahashi, K. (1989), "On the approximate realization of continuous mappings by neural networks", Neural Networks, 2(3), 183-192.
3. Hagan, M.T., Demuth, H.B. and Beale, M.H. (1996), Neural Network Design, PWS Publishing Company, Boston, MA, USA.
4. Hakim, S.J.S., Noorzaei, J., Jaafar, M.S., Jameel, M., Mohammadhassani, M. (2011), "Application of artificial neural networks to predict compressive strength of high strength concrete", Int'l J. Phys. Sci. (IJPS), 6(5), 975-981.
5. Hornik, K., Stinchcombe, M. and White, H. (1989), "Multilayer feed forward networks are universal approximator", Neural Networks., 2(5), 359-366. (Pubitemid 20609008)
6. Inglessis, P., Medina, S., Lopez, A., Febres, R. and Lopez, J.F. (2002), "Modelling of local buckling in tubular steel frames by using plastic hinges with damage", Steel Composite Struct., An Int'l J., 2(1),57-65.
7. Kim, H., Cui, J., Seo, H.Y. and Lee, Y.H. (2009), "Iterative neural network strategy for static model identification of an FRP deck", Steel and Composite Struct., An Int'l J., 9(5), 445-455.
8. Lam, H.F. and Ng, C.T. (2008), "The selection of pattern features for structural damage detection using an extended Bayesian ANN algorithm", J. Eng. Struct., 30(10), 2762-2770.
9. Lee, J.W., Kim, J.D., Yun, C.B., Yi, J.H. and Shim, M. (2002), "Health-monitoring method for bridges under ordinary traffic loadings", J. Sound Vib., 257(2), 247-264. (Pubitemid 35437535)
10. Leu, S.S. and Loch, S. (2004), "Neural-network-based regression model of ground surface settlement induced by deep excavation", 13(3), 279-289.
11. Lu, Y. and Tu, Z. (2004), "A two-level neural network approach for dynamic FE model updating including damping", J. Sound Vib., 275(3-5), 931-952.
12. Mehrjoo, M., Khaji, N., Moharrami, H. and Bahreininejad, A. (2008), "Damage detection of truss bridge joints using artificial neural networks," J. Expert Sys. Appl., 35(3), 1122-1131.
13. Mohammadhassani, M., Nezam Abadi-Pour, H., Zamin Jumaat, M., Jameel, M. and Arumugam, A.M.S. (2013a), "Application of artificial neural network (ANN) and linear regressions (LR) in predicting the deflection of concrete deep beams", Computer and Concrete, 11(3). [In Print]
14. Mohammadhassani, M., Nezamabadi-Pour, H., Jumaat, M., Jameel, M., Hakim, S.J.S. and Zargar, M. (2013b), "Application of the ANFIS model in deflection prediction of concrete deep beam", Struct. Eng. Mech., 45(3), 323-336.
15. Nam, K.K., Haeng, L.S., Sup, J.K. (2009)," Prediction on the fatigue life of butt-welded specimens using artificial neural network", Steel Composite Struct., An Int'l J., 9(6), 557-568.
16. Ni, Y.Q., Zhou, X.T. and Ko, J.M. (2006), "Experimental investigation of seismic damage identification using PCA-compressed frequency response functions and neural networks", J. Sound Vib., 290(1-2), 242-263. (Pubitemid 41802247)
17. Noorzaei, J., Hakim, S.J.S. and Jaafar, M.S. (2008), "An approach to predict ultimate bearing capacity of surface footings using artificial neural network", Indian Geotech. J., 38(4), 515-528.
18. Noorzaei, J., Hakim, S.J.S., Jaafar, M.S., Abang, A.A.A. and Thanoon, W.A.M. (2007), "An optimal architecture of artificial neural network for predicting of compressive strength of concrete", Indian Concrete J., 81(8), 17-24. (Pubitemid 350021725)
19. Park, J.H., Kim, J.T., Hong, D.S., Ho, D.D. and Yi, J.H. (2009)," Sequential damage detection approaches for beams using time-modal features and artificial neural networks", J. Sound Vib., 323, 451-474.
20. Ramadas, C., Balasubramaniam, K., Joshi, M. and Krishnamurthy, C.V. (2008), "Detection of transverse cracks in a composite beam using combined features of lamb wave and vibration techniques in ANN environment", Int'l J. Smart Sens. Intellig. Sys., 1(10), 970-984.
21. Rosales, M.B., Filipich, C.P. and Buezas, F.S. (2009), "Crack detection in beam-like structures", Eng. Struct., 31(10), 2257-2264.
22. Rytter, A. (1993), "Vibration based inspection of civil engineering structures", Ph.D. Thesis, Department of Building Technology and Structural Engineering, Aalborg University, Denmark.
23. Stull, C.J. and Earls, C.J. (2009), "A rapid assessment methodology for bridges damage by truck strikes", Steel Composite Struct., An Int'l J., 9(3), 223-237.
24. Suh, M.W., Shim, M.B. and Kim, M.Y. (2000), "Crack identification using hybrid neuro-genetic technique", J. Sound Vib., 234(4), 617-635.
25. Wu, Z.S., Xu, B. and Yokoyama, K (2002), "Decentralized parametric damage based on neural networks", J. Computer-Aided Civil Infrastruct. Eng., 17(3), 175-184. (Pubitemid 34458548)
26. Xu, B., Wu, Z.S. and Yokoyama, K. (2002), "A localized identification method with neural networks and its application to structural health monitoring", J. Struct. Eng., JSCE, 48A, 419-427.
27. Yau, J.D. (2005), "Damage detection of a cracked column via a neural network approach", J. Adv. Steel Struct., 2, 1749-1754.
28. Zapico, J.L., Gonzalez, M.P. Worden, K. (2003), "Damage assessment using neural networks", J. Mech. Sys. Signal Process., 17(1), 119-125.
29. Matlab 7.11 (R2010b), The MathWorks Inc., MA, USA. http://www.tnodiana. com