Identification of added mass on a two-storey framed structure utilising FRFs and ANNs

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dc.contributor.author Dackermann, U
dc.contributor.author Li, J
dc.contributor.author Samali, B
dc.contributor.editor Fragomeni, S
dc.contributor.editor Venkatesan, S
dc.contributor.editor Lam, NTK
dc.contributor.editor Setunge, S
dc.date.accessioned 2012-10-12T03:36:34Z
dc.date.issued 2011-01
dc.identifier.citation Incorporating Sustainable Practice in Mechanics of Structures and Materials - Proceedings of the 21st Australasian Conference on the Mechanics of Structures and Materials (ACMSM21), 2011, pp. 757 - 762
dc.identifier.isbn 978-0-415-61657-7
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19321
dc.description.abstract This paper presents a vibration~based damage detection method that utilises frequency response functions (FRFs) to identify added mass on a two-storey framed structure. Added mass is used to simulate frequency changes due to structural damage. Artificial neural networks (ANNs) are employed to map changes in FRFs to locations of the added mass. In order to obtain suitable inputs for neural network training, principal component analysis (PCA) techniques are adopted to reduce the size of the FRF data and to filter noise. A hierarchy of neural network ensembles is used to take advantage of individual measurement characteristics from different sensors. The method is tested on laboratory and numerical models of a two-storey framed structure. From the two kinds of structures, FRF data are determined and compressed utilising PCA techniques. The PCAreduced FRFs are then used as input patterns for training and testing of ANN ensembles predicting different locations of added mass.
dc.publisher CRC Press/Balkema
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isreplacedby 10453/33171
dc.relation.isreplacedby http://hdl.handle.net/10453/33171
dc.rights This is an electronic version of an article published in [include the complete citation information for the final version of the article as published in the print edition of the journal Incorporating Sustainable Practice in Mechanics and Structures of Materials. Incorporating Sustainable Practice in Mechanics and Structures of Materials is available online at: www.tandfonline.com with the open URL of your article http://dx.doi.org/10.1201/b10571-137
dc.subject vibration-based damage detection, frequency response functions, Artificial neural networks, structural damage,
dc.title Identification of added mass on a two-storey framed structure utilising FRFs and ANNs
dc.type Conference Proceeding
dc.parent Incorporating Sustainable Practice in Mechanics of Structures and Materials - Proceedings of the 21st Australasian Conference on the Mechanics of Structures and Materials (ACMSM21)
dc.journal.number en_US
dc.publocation The Netherlands en_US
dc.publocation Berlin, Germany
dc.identifier.startpage 757 en_US
dc.identifier.endpage 762 en_US
dc.cauo.name FEIT.School of Civil and Environmental Engineering en_US
dc.conference Verified OK en_US
dc.conference Australasian Conference on the Mechanics of Structures and Materials
dc.for 090506 Structural Engineering
dc.personcode 995216 en_US
dc.personcode 930859 en_US
dc.personcode 870186 en_US
dc.percentage 100 en_US
dc.classification.name Structural Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.edition 1
dc.custom Australasian Conference on the Mechanics of Structures and Materials en_US
dc.date.activity 20101207 en_US
dc.date.activity 2010-12-07
dc.location.activity Melbourne, Australia en_US
dc.description.keywords vibration-based damage detection, frequency response functions, Artificial neural networks, structural damage, en_US
dc.staffid en_US
dc.staffid 870186 en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group /University of Technology Sydney/Strength - Built Infrastructure
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history General (ID: 2)
utslib.collection.history School of Civil and Environmental Engineering (ID: 334)


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