Browse > Article

Damage Detection of Bridge Structures Considering Uncertainty in Analysis Model  

Lee Jong-Jae (한국과학기술원 건설 및 환경공학과)
Yun Chung-Bang (한국과학기술원 건설 및 환경공학과)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.19, no.2, 2006 , pp. 125-138 More about this Journal
Abstract
The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.
Keywords
damage detection; bridge structures; neural networks; modeling uncertainty; mode shape differences; mode shape ratios;
Citations & Related Records
연도 인용수 순위
  • Reference
1 김정태, 류연선, 조현만(2002) 고유진동수 이용 손상추정법과 모드형상 이용 손상추정법에 의한 PSC 보의 비파괴 손상검색, 한국전산구조공학회논문집, 15(1), pp. 1229-3059
2 Chou, J. H., Ghaboussi, J. (2001) Genetic Algorithm in Structural Damage Detection. Computers and Structures, 79. pp.1335-1353   DOI   ScienceOn
3 Sampaio, R. P. C., Maia, N. M. M., Silva, J. M. M. (1999) Damage Detection Using The Frequency Response-Function Curvature Method, Journal of Sound and Vibration, 226(5), pp.1029-1042   DOI   ScienceOn
4 Wu, X.. Ghaboussi, J., Garret, J.H., Jr.(1992) Use of neural networks in detection of structural damage, Computers and Structures, 42(4), pp.649-659   DOI   ScienceOn
5 Yun, C. B., Bahng. E. Y.(2000) Substructural identification using neural networks, Computers and Structures, 77(1), pp.41-52   DOI   ScienceOn
6 Zou. Y., Tong. L., Steven. G. P.(2000) Vibration-Based Model-Dependent Damage (Delamination) Identification and Health Monitoring For Composite Structures - A Review, Journal of Sound and Vibration, 230(2), pp.357-378   DOI   ScienceOn
7 Ni, Y. Q., Wang, B. S., Ko. J. M.(2002) Constructing input vectors to neural networks for structural damage identification, Smart Materials and Structures, 11, pp.825-833   DOI   ScienceOn
8 Doebling, S. W., Farrar. C. R., Prime. M. B. (1998) A Summary Review of Vibration-Based Damage Identification Methods. the Shock and Vibration. Digest. 30(2). pp.91-105
9 Ni, Y. Q., Zhou, X. T., Ko, J. M., Wang, B. S. (2000) Vibration-based damage localization in Ting Kau Bridge using probabilistic neural network, Advances in Structural Dynamics,J.M. Ko and Y. L. Xu (eds.): Elsevier Science Ltd., Oxford, UK, Vol. II, pp.1069-1076
10 Zou, J., Chen. J., Pu, Y. P., Zhong, P.(2002) On the wavelet time-frequency analysis algorithm in identification of a cracked rotor, Journal of Strain Analysis, 37(3), pp.239-246   DOI   ScienceOn
11 Yun, C. B.. Yi, J. H.. Bahng, E. Y.(2001) Joint Damage Assessment of Framed Structures Using Neural Networks Technique, Engineering Structures, 23(5), pp.425-435   DOI   ScienceOn
12 Chase, S.B., Aktan, A.E. (eds.)(2001) Health Monitoring and Management of Civil Infrastructure Systems. SPIE Vol. 4337
13 Matsuoka, K. (1992) Noise injection into inputs in back-propagation learning. IEEE Transaction of Systems. Man. and Cybernetics. 22(3). pp.436-440   DOI   ScienceOn
14 윤정방, 장신애, 심성한, 이종재(2002) Hilbert-Huang Transform을 이용한 교량구조물의 손상추정기법, 한국전산구조공학회 가을 학술발표회 논문집 pp.453-458
15 Gawronski, W., Sawicki. J. T. (2000) Structural Damage Detection Using Modal Norms. Journal of Sound and Vibration. 229(1), pp.194-198   DOI   ScienceOn
16 Quek, S. T., Wang, Q., Zhang, L., Ong. K, H. (2001) Practical Issues in the Detection of Damage in Beams Using Wavelets. Smart Materials and Structures, 10, pp.1009-1017   DOI   ScienceOn
17 Ko, J. M., Chak, K. K., Wang, J. Y., Ni. Y. Q., Chen. T.H.T. (2003) Formulation of an uncertainty model relating modal parameters and environmental factors by using long-term monitoring data. Smart Systems and Nondestructive Evaluation for Civil Infrastructures. S.-C. Liu (ed.). SPIE Vol. 5057
18 Masri, S. F., Smyth, A. W.. Chasaiakos, A. G., Nakamura, M., Caughey, T. K.(1999) Training Neural Networks by Adaptive Random Search Techniques, Journal of Engineering Mechanics. 125(5). pp.123-132   DOI   ScienceOn
19 박승희, 윤정방, 노용래(2004) 강 구조물의 손상 검색을 위한 램 웨이브와 웨이브렛 계수의 효율적인 사용, 한국전산구조공학회 학술발표논문집, pp.429-436
20 Szewczyk, Z. P., Haiela. P.(1994) Damage detection in structures based on feature-sensitive neural networks, Journal of Computing in Civil Engineering. ASCE, 8(2), pp.163-178   DOI   ScienceOn
21 Lee, J. W., Kim, J. D., Yun, C. B., Yi, J. H., Shim, J. M. (2002) Health-Monitoring Method for Bridges under Ordinary Traffic Loadings. Journal of Sound and Vibration. 257(2). pp.247-264   DOI   ScienceOn