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dc.contributor.authorBrownjohn, JMW
dc.contributor.authorAu, S-K
dc.contributor.authorZhu, Y
dc.contributor.authorSun, Z
dc.contributor.authorLi, B
dc.contributor.authorBassitt, J
dc.contributor.authorHudson, E
dc.contributor.authorSun, H
dc.date.accessioned2018-03-14T14:48:19Z
dc.date.issued2018-03-30
dc.description.abstractVibration testing of long span bridges is becoming a commissioning requirement, yet such exercises represent the extreme of experimental capability, with challenges for instrumentation (due to frequency range, resolution and km-order separation of sensor) and system identification (because of the extreme low frequencies). The challenge with instrumentation for modal analysis is managing synchronous data acquisition from sensors distributed widely apart inside and outside the structure. The ideal solution is precisely synchronised autonomous recorders that do not need cables, GPS or wireless communication. The challenge with system identification is to maximise the reliability of modal parameters through experimental design and subsequently to identify the parameters in terms of mean values and standard errors. The challenge is particularly severe for modes with low frequency and damping typical of long span bridges. One solution is to apply ‘third generation’ operational modal analysis procedures using Bayesian approaches in both the planning and analysis stages. The paper presents an exercise on the Jiangyin Yangtze River Bridge, a suspension bridge with a 1,385m main span. The exercise comprised planning of a test campaign to optimise the reliability of operational modal analysis, the deployment of a set of independent data acquisition units synchronised using precision oven controlled crystal oscillators and the subsequent identification of a set of modal parameters in terms of mean and variance errors. Although the bridge has had structural health monitoring technology installed since it was completed, this was the first full modal survey, aimed at identifying important features of the modal behaviour rather than providing fine resolution of mode shapes through the whole structure. Therefore, measurements were made in only the (south) tower, while torsional behaviour was identified by a single measurement using a pair of recorders across the carriageway. The modal survey revealed a first lateral symmetric mode with natural frequency 0.0536 Hz with standard error ±3.6% and damping ratio 4.4% with standard error ±88%. First vertical mode is antisymmetric with frequency 0.11 Hz ± 1.2% and damping ratio 4.9% ± 41%. A significant and novel element of the exercise was planning of the measurement setups and their necessary duration linked to prior estimation of the precision of the frequency and damping estimates. The second novelty is the use of the multi-sensor precision synchronised acquisition without external time reference on a structure of this scale. The challenges of ambient vibration testing and modal identification in a complex environment are addressed leveraging on advances in practical implementation and scientific understanding of the problemen_GB
dc.description.sponsorshipThe research was funded by the Engineering and Physical Sciences Research Council (grant EP/N017897/1 and EP/N017803)en_GB
dc.identifier.citationVol. 110, pp. 210–230en_GB
dc.identifier.doi10.1016/j.ymssp.2018.03.027
dc.identifier.urihttp://hdl.handle.net/10871/32108
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights© 2018 The Authors. Published by Elsevier Ltd. Open Access funded by Engineering and Physical Sciences Research Council. Under a Creative Commons license: https://creativecommons.org/licenses/by/4.0/
dc.subjectBayesian operational modal analysisen_GB
dc.subjectsuspension bridgeen_GB
dc.subjectuncertaintyen_GB
dc.subjectsynchronisationen_GB
dc.titleBayesian operational modal analysis of Jiangyin Yangtze River Bridgeen_GB
dc.typeArticleen_GB
dc.identifier.issn0888-3270
dc.descriptionThis is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recorden_GB
dc.identifier.journalMechanical Systems and Signal Processingen_GB


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