Jesus, Andre and Stana, Zivanovic (2020) A spectral pedestrian-based approach for modal identification. UWE https://researchdata.uwe.ac.uk/id/eprint/529/
Brief summary of project
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.
Additional Information: | Based on paper published in the Journal of Sound and Vibration | ||||
---|---|---|---|---|---|
Uncontrolled Keywords: | power spectral density, modal identification, FRP footbridge, pedestrian excitation, Metropolis–Hastings, likelihood function | ||||
UWE College/School: | College of Arts, Technology and Environment > School of Architecture and Environment | ||||
Creators: | Jesus, Andre and Stana, Zivanovic | ||||
Related Datasets: |
|
||||
URI: | https://researchdata.uwe.ac.uk/id/eprint/529 | ||||
Resource language: | English |
Data
Explore Further
Read more research from the creator(s):
- Jesus, Andre
- Stana, Zivanovic
Read publications using this data:
Find other related resources: