Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/149990
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dc.contributor.authorZhu, Yi-Chenen_US
dc.contributor.authorAu, Siu-Kuien_US
dc.date.accessioned2021-05-19T08:21:42Z-
dc.date.available2021-05-19T08:21:42Z-
dc.date.issued2019-
dc.identifier.citationZhu, Y. & Au, S. (2019). Bayesian modal identification method based on general coherence model for asynchronous ambient data. Mechanical Systems and Signal Processing, 132, 194-210. https://dx.doi.org/10.1016/j.ymssp.2019.06.025en_US
dc.identifier.issn0888-3270en_US
dc.identifier.other0000-0003-1007-0689-
dc.identifier.other0000-0002-0228-1796-
dc.identifier.urihttps://hdl.handle.net/10356/149990-
dc.description.abstractA Bayesian frequency domain method for modal identification using asynchronous ambient data has been proposed previously. It provides a flexible and economical way to conduct ambient vibration tests as time synchronisation among data channels is not required. To simplify computation, zero coherence among synchronous data groups is assumed in the method, which inevitably introduces modelling error and lacks the ability of quantifying the synchronisation degree among different groups. To address these issues, a Bayesian modal identification method with a general coherence assumption among synchronisation groups is proposed in this paper. Computational difficulties are addressed and an efficient algorithm for determining the most probable values of modal properties is proposed. Synthetic and laboratory data examples are presented to validate the proposed method. It is also applied to modal identification of a full-scale ambient test, which illustrates the feasibility of the proposed method to real asynchronous data under field test configurations. For the cases investigated the proposed method does not lead to significant improvement in the identification accuracy of modal parameters compared to the method with zero coherence assumption. This is consistent with previous experience regarding the robustness of the zero coherence assumption and is now verified in this work. One may use the latter in practice for computational efficiency if the synchronisation degree among different groups is not demanded.en_US
dc.language.isoenen_US
dc.relation.ispartofMechanical Systems and Signal Processingen_US
dc.rights© 2019 Elsevier Ltd. All rights reserved. This paper was published in Mechanical Systems and Signal Processing and is made available with permission of Elsevier Ltd.en_US
dc.subjectEngineering::Civil engineeringen_US
dc.titleBayesian modal identification method based on general coherence model for asynchronous ambient dataen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US
dc.identifier.doi10.1016/j.ymssp.2019.06.025-
dc.description.versionAccepted versionen_US
dc.identifier.scopus2-s2.0-85067801720-
dc.identifier.volume132en_US
dc.identifier.spage194en_US
dc.identifier.epage210en_US
dc.subject.keywordsAmbient Dataen_US
dc.subject.keywordsAsynchronous Dataen_US
dc.description.acknowledgementThis paper is partially supported by UK Engineering & Physical Research Council (EP/N017897/1). The financial support is gratefully acknowledged.en_US
item.grantfulltextopen-
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