Damage Severity Assessment of Timber Bridges using Frequency Response Functions (FRFs) and Artificial Neural Networks (ANNs)

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dc.contributor.author Dackermann, Ulrike en_US
dc.contributor.author Li, Jianchun en_US
dc.contributor.author Samali, Bijan en_US
dc.contributor.author Choi, Fook Choon en_US
dc.contributor.author Crews, Keith en_US
dc.contributor.editor Saporiti Machado, Jose; Palma, Pedro; Louren??o, Paulo B. en_US
dc.date.accessioned 2012-10-12T03:36:28Z
dc.date.available 2012-10-12T03:36:28Z
dc.date.issued 2011 en_US
dc.identifier 2011000883 en_US
dc.identifier.citation Dackermann Ulrike et al. 2011, 'Damage Severity Assessment of Timber Bridges using Frequency Response Functions (FRFs) and Artificial Neural Networks (ANNs)', , Laboratorio Nacional de Engenharia Civil, Lisboa, Portugal, , pp. 63 en_US
dc.identifier.issn en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19237
dc.description.abstract This paper presents a novel vibration-based technique that utilises changes in frequency response functions (FRFs) to assess advancement of damage in timber bridges. In the proposed method, damage patterns embedded in FRF data are extracted and analysed by using a combination of principal component analysis (PCA) and artificial neural network (ANN) techniques for estimation of severity levels of damage. To demonstrate the method, it is applied to a laboratory four-girder timber bridge, which is gradually inflicted with accumulative damage at different locations and severities. To extract damage features in FRFs and to compress the large size of FRF data, FRFs are transferred to the principal component space adopting PCA techniques. PCA-compressed FRF data are then used as inputs to ANNs to identify severities of damage. The excellent severity predictions obtained from the ANNs show that FRF data can potentially be very good indicators for the assessment of damage advancements in timber bridges. en_US
dc.language English en_US
dc.publisher Laboratorio Nacional de Engenharia Civil en_US
dc.relation.isbasedon en_US
dc.title Damage Severity Assessment of Timber Bridges using Frequency Response Functions (FRFs) and Artificial Neural Networks (ANNs) en_US
dc.parent International Conference on Structural Health Assessment of Timber Structures en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Lisboa, Portugal en_US
dc.identifier.startpage 63 en_US
dc.identifier.endpage en_US
dc.identifier.endpage 71 en_US
dc.cauo.name FEIT.School of Civil and Environmental Engineering en_US
dc.conference Verified OK en_US
dc.for 090500 en_US
dc.personcode 995216 en_US
dc.personcode 930859 en_US
dc.personcode 870186 en_US
dc.personcode 044012 en_US
dc.personcode 930410 en_US
dc.percentage 100 en_US
dc.classification.name Civil Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom International Conference on Structural Health Assessment of Timber Structures en_US
dc.date.activity 20110616 en_US
dc.location.activity Lisbon en_US
dc.description.keywords damage identification, timber, bridge, structural health monitoring, artificial neural network, frequency response function, principal component analysis en_US
dc.staffid 930410 en_US


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