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dc.contributor.authorKim, C. W.en
dc.contributor.authorKawatani, M.en
dc.contributor.authorHao, J.en
dc.contributor.alternative金, 哲佑ja
dc.date.accessioned2013-03-21T03:00:16Z-
dc.date.available2013-03-21T03:00:16Z-
dc.date.issued2012-05-
dc.identifier.issn1573-2479-
dc.identifier.urihttp://hdl.handle.net/2433/172227-
dc.description.abstractThis study is intended to investigate the feasibility of health monitoring of short span bridges based on modal parameter identification using the vibration data of the bridge induced by a moving vehicle. The idea of this study using the traffic-induced vibration of short span bridges which is a kind of non-stationary process is that the modal parameters identified repeatedly under a given moving vehicle provide a pattern which may provide useful information to decide current health condition of bridges. The autoregressive (AR) model is adopted for identifying modal parameters such as frequency and damping characteristics of the bridges. Mode shapes of bridges are obtained using multivariate AR model. Feasibility of the modal parameter identification for health monitoring of short span bridges is observed through a moving vehicle laboratory experiment. Pattern changes of identified parameters are observable by comparing the identification results between intact and damaged girders, which encourages the use of the method for long term health monitoring even for short span bridges.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherTaylor and Francis Group, LLC.en
dc.rights© 2012 Taylor & Francisen
dc.rightsThis is not the published version. Please cite only the published version.en
dc.rightsこの論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。ja
dc.subjectbridge health monitoringen
dc.subjectmoving vehicle laboratory experimenten
dc.subjectmodal parameter identificationen
dc.subjectautoregressive modelen
dc.subjectshort span bridgeen
dc.subjecttraffic-induced vibrationen
dc.titleModal parameter identification of short span bridges under a moving vehicle by means of multivariate AR modelen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.ncidAA12013016-
dc.identifier.jtitleStructure and Infrastructure Engineeringen
dc.identifier.volume8-
dc.identifier.issue5-
dc.identifier.spage459-
dc.identifier.epage472-
dc.relation.doi10.1080/15732479.2010.539061-
dc.textversionauthor-
dcterms.accessRightsopen access-
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