dc.contributor.author | Brownjohn, JMW | |
dc.contributor.author | Au, S-K | |
dc.contributor.author | Zhu, Y | |
dc.contributor.author | Sun, Z | |
dc.contributor.author | Li, B | |
dc.contributor.author | Bassitt, J | |
dc.contributor.author | Hudson, E | |
dc.contributor.author | Sun, H | |
dc.date.accessioned | 2018-03-14T14:48:19Z | |
dc.date.issued | 2018-03-30 | |
dc.description.abstract | Vibration 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 problem | en_GB |
dc.description.sponsorship | The research was funded by the Engineering and Physical Sciences Research Council (grant EP/N017897/1
and EP/N017803) | en_GB |
dc.identifier.citation | Vol. 110, pp. 210–230 | en_GB |
dc.identifier.doi | 10.1016/j.ymssp.2018.03.027 | |
dc.identifier.uri | http://hdl.handle.net/10871/32108 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_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.subject | Bayesian operational modal analysis | en_GB |
dc.subject | suspension bridge | en_GB |
dc.subject | uncertainty | en_GB |
dc.subject | synchronisation | en_GB |
dc.title | Bayesian operational modal analysis of Jiangyin Yangtze River Bridge | en_GB |
dc.type | Article | en_GB |
dc.identifier.issn | 0888-3270 | |
dc.description | This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record | en_GB |
dc.identifier.journal | Mechanical Systems and Signal Processing | en_GB |