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Structural Engineering and Mechanics Volume 23, Number 1, May10 2006 , pages 75-95 DOI: https://doi.org/10.12989/sem.2006.23.1.075 |
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Jong Jae Lee and Chung Bang Yun
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| Abstract | ||
| Two-step identification approaches for effective bridge health monitoring are proposed to alleviate the issues associated with many unknown parameters faced in real structures and to improve the accuracy in the estimate results. It is suitable for on-line monitoring scheme, since the damage assessment is not always needed to be carried out whereas the alarming for damages is to be continuously monitored. In the first step for screening potentially damaged members, a damage indicator method based on modal strain energy, probabilistic neural networks and the conventional neural networks using grouping technique are utilized and then the conventional neural networks technique is utilized for damage assessment on the screened members in the second step. The effectiveness of the proposed methods is investigated through a field test on the northern-most span of the old Hannam Grand Bridge over the Han River in Seoul, Korea. | ||
| Key Words | ||
| bridge health monitoring; two-step approach; modal strain energy; probabilistic neural networks; neural networks; field tests. | ||
| Address | ||
| Jong Jae Lee; Department of Civil & Environmental Engineering, University of California Irvine,Irvine, CA, 92697, USA Chung Bang Yun; Smart Infra-Structure Technology Center, Korea Advanced Institute of Science and Technology, Yusong-gu, Daejeon 305-701, Korea | ||