RESEARCH ARTICLE


Damage Identification of Continuous Rigid Frame Concrete Bridge



Shengnan Huang*, 1, Lieping Ye2, Xinzheng Lu2
1 Civil and Environmental Engineering Institute, University of Science and Technology Beijing, Beijing 100083, China
2 Key Laboratory of Civil Engineering Safety and Durability of Ministry of Education, Department of Civil Engineering, Tsinghua University, Beijing 100084, China


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Creative Commons License
© 2014 Huang et al;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Civil and Environmental Engineering Institute, University of Science and Technology Beijing, Beijing 100083, China; Tel:(+86)13810593480; E-mail: huangcn03@mails.tsinghua.edu.cn


Abstract

During a bridge service life, many factors can cause damage accumulation such as overloaded traffic, fatigue effect, and so on. Hence, the identification of potential damages has been received wide attention to prevent such sudden fatal accident. An experiment of a continuous rigid frame concrete bridge, which had 3 spans and a total length of 18 meters, was presented in this paper. Two load stages and ten different load steps were simulated to test various scenario of long-term loading and different levels of overload. Curvature mode method was adopted to detect the damage during the exercises. The changes of curvature modes were used to detect damage after the ten load steps. This method performed excellent to identify the damage position of the bridge. So, it is concluded that the curvature modes can be used to detect damage in actual structures. In addition, the Finite-Element Analysis (FEA) was utilized, and the experimental recurring was verified positively through FEA model.

Keywords: Bridge, curvature mode, damage identification, dynamic fingerprint, experimental study, FEA.