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A spectral pedestrian-based approach for modal identification

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journal contribution
posted on 2022-05-30, 08:58 authored by Andre JesusAndre Jesus, Stana Živanović, Amir Alani

The dynamic behaviour of footbridges is characterised by modal properties such as natural frequencies, mode shapes, damping ratios and modal masses. Their estimation via modal tests often requires expensive or difficult-to-operate equipment (e.g. shaker and instrumented impact hammer) or, sometimes unavailable high signal-to-noise ratios in tests relying on natural (e.g. wind, airborne noise and ground-borne vibration) excitation. In addition, the modal properties determined in modal tests do not necessarily apply to the structure under pedestrian traffic in case of amplitude-dependent frequencies and damping ratios. The current work proposes a novel approach that stands in contrast to the widely used tests, based on modal identification using an excitation induced by a single pedestrian. In order to account for estimation and observation uncertainties, the relationship between the power spectrum of the response and its modal properties is described with a likelihood function. It is shown that it is possible to reliably estimate modal properties using pedestrian walk forces measured in the laboratory, and dynamic responses measured when the same pedestrian is crossing a footbridge at timed pacing rates. The approach is validated using numerical and field data for a 16.9 m long fibre reinforced polymer footbridge. This work paves a new way for simple and low cost modal testing in structural dynamics. 

Funding

Characterising dynamic performance of fibre reinforced polymer structures for resilience and sustainability

Engineering and Physical Sciences Research Council

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History

School

  • Architecture, Building and Civil Engineering

Published in

Journal of Sound and Vibration

Volume

470

Publisher

Elsevier

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

Acceptance date

2019-12-13

Publication date

2019-12-19

Copyright date

2019

ISSN

0022-460X

Language

  • en

Depositor

Dr Andre Jesus. Deposit date: 27 May 2022

Article number

115157

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