Damage Identification for Prestressed Adjacent Box-Beam Bridges

Author:

Walsh Kenneth K.1,Kelly Brendan T.2,Steinberg Eric P.1

Affiliation:

1. Department of Civil Engineering, Ohio University, Athens, OH 45701, USA

2. GPD Group, 1801 Watermark Drive, Suite 150, Columbus, OH 43215, USA

Abstract

Structural health monitoring (SHM) has gained considerable attention as a tool for monitoring the health of civil infrastructure. For bridge infrastructure, previous methods have focused on the detection of localized damage through modal parameters extracted from the longitudinal direction of the structure. This paper investigates a new damage detection method based on the change in the first vertical mode extracted from the transverse direction of the bridge. The mode is determined through application of modal curve fitting to frequency response functions (FRFs) that are formed using vertical response data obtained in the direction perpendicular to the bridge’s longitudinal axis. Using this method, both local damage and global damage in the bridge reveal themselves as having a localized effect on the bridge response. Furthermore, damage is revealed in such a way that it enables differentiation of the damage types. To demonstrate the effectiveness of the method, modal parameters were extracted from acceleration data obtained from a finite element model of a full bridge. Analysis of the modal parameters showed that the proposed approach could not only detect both local and global bridge damage, but could also differentiate between damage types using only one mode shape. The proposed method was compared to a previously developed SHM method.

Publisher

Hindawi Limited

Subject

Civil and Structural Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3