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A new probabilistic frequency-domain approach for influence line extraction from static transmissibility measurements under unknown moving loads
Wang-Ji Yan; Ka-Veng Yuen
2020-05-16
Source PublicationEngineering Structures
ISSN0141-0296
Volume216Pages:110625
Abstract

On the basis of the amazing theoretical finding that there is equivalence between the static transmissibility subjected to moving loads and the ratio of two influence lines in the frequency domain, a new approach is proposed to extract the influence lines for a beam-like structure under moving loads. To accommodate the uncertainties involved in the measurements as well as modelling error, the relationship between response measurements and the Fourier transform of influence lines is embedded in the framework of Bayesian inference with the aid of complex-valued probabilistic model of prediction error. The formulas are presented for closed-form transformation between the solutions of FFT coefficients and those of inverse FFT coefficients. Analytical solutions of the Most Probable Values (MPVs) as well as posterior uncertainties of the influence lines in both frequency domain and spatial domain are derived. Two applications are conducted to verify the efficiency and accuracy of the fast Bayesian scheme. It is shown that the new approach can be realized by avoiding the ill-poseness nature of inverse problem. Due to the introduction of the concept of static transmissibility, given that the reference influence line is known in advance, this method possesses an obvious advantage in avoiding using the knowledge of the moving loads. As a frequency-domain approach, it can reduce the computational complexity of influence line extraction by avoiding complicated matrix manipulation.

KeywordInfluence Line Bayesian Analysis Moving Loads Transmissibility Structural Health Monitoring Bridge
DOI10.1016/j.engstruct.2020.110625
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering
WOS SubjectEngineering, Civil
WOS IDWOS:000539276800005
PublisherELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
Scopus ID2-s2.0-85084614699
Fulltext Access
FWCI1.239922
Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorWang-Ji Yan
AffiliationState Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering,University of Macau,Macau,China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Wang-Ji Yan,Ka-Veng Yuen. A new probabilistic frequency-domain approach for influence line extraction from static transmissibility measurements under unknown moving loads[J]. Engineering Structures,2020,216:110625.
APA Wang-Ji Yan,&Ka-Veng Yuen.(2020).A new probabilistic frequency-domain approach for influence line extraction from static transmissibility measurements under unknown moving loads.Engineering Structures,216,110625.
MLA Wang-Ji Yan,et al."A new probabilistic frequency-domain approach for influence line extraction from static transmissibility measurements under unknown moving loads".Engineering Structures 216(2020):110625.
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