Identification of added mass on a two-storey framed structure utilising FRFs and 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.editor Sam Fragomeni, Srikanth Venkatesan, Nelson T.K. Lam, Sujeeva Setunge en_US
dc.date.accessioned 2012-10-12T03:36:34Z
dc.date.available 2012-10-12T03:36:34Z
dc.date.issued 2011 en_US
dc.identifier 2010000052 en_US
dc.identifier.citation Dackermann Ulrike, Li Jianchun, and Samali Bijan 2011, 'Identification of added mass on a two-storey framed structure utilising FRFs and ANNs', , CRC Press/Balkema, The Netherlands, , pp. 757-762. en_US
dc.identifier.issn 978-0-415-61657-7 en_US
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. en_US
dc.language English en_US
dc.publisher CRC Press/Balkema en_US
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon http://dx.doi.org/10.1201/b10571-137 en_US
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.title Identification of added mass on a two-storey framed structure utilising FRFs and ANNs en_US
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) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation The Netherlands en_US
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.for 090506 en_US
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.custom Australasian Conference on the Mechanics of Structures and Materials en_US
dc.date.activity 20101207 en_US
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


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