Damage Identification for Prestressed Adjacent Box-Beam Bridges

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 st...

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Main Authors: Kenneth K. Walsh, Brendan T. Kelly, Eric P. Steinberg
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Advances in Civil Engineering
Online Access:http://dx.doi.org/10.1155/2014/540363
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spelling doaj-6cc11a66496640fe92ff8d646b1daeff2020-11-24T23:03:46ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942014-01-01201410.1155/2014/540363540363Damage Identification for Prestressed Adjacent Box-Beam BridgesKenneth K. Walsh0Brendan T. Kelly1Eric P. Steinberg2Department of Civil Engineering, Ohio University, Athens, OH 45701, USAGPD Group, 1801 Watermark Drive, Suite 150, Columbus, OH 43215, USADepartment of Civil Engineering, Ohio University, Athens, OH 45701, USAStructural 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.http://dx.doi.org/10.1155/2014/540363
collection DOAJ
language English
format Article
sources DOAJ
author Kenneth K. Walsh
Brendan T. Kelly
Eric P. Steinberg
spellingShingle Kenneth K. Walsh
Brendan T. Kelly
Eric P. Steinberg
Damage Identification for Prestressed Adjacent Box-Beam Bridges
Advances in Civil Engineering
author_facet Kenneth K. Walsh
Brendan T. Kelly
Eric P. Steinberg
author_sort Kenneth K. Walsh
title Damage Identification for Prestressed Adjacent Box-Beam Bridges
title_short Damage Identification for Prestressed Adjacent Box-Beam Bridges
title_full Damage Identification for Prestressed Adjacent Box-Beam Bridges
title_fullStr Damage Identification for Prestressed Adjacent Box-Beam Bridges
title_full_unstemmed Damage Identification for Prestressed Adjacent Box-Beam Bridges
title_sort damage identification for prestressed adjacent box-beam bridges
publisher Hindawi Limited
series Advances in Civil Engineering
issn 1687-8086
1687-8094
publishDate 2014-01-01
description 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.
url http://dx.doi.org/10.1155/2014/540363
work_keys_str_mv AT kennethkwalsh damageidentificationforprestressedadjacentboxbeambridges
AT brendantkelly damageidentificationforprestressedadjacentboxbeambridges
AT ericpsteinberg damageidentificationforprestressedadjacentboxbeambridges
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