Jesus, Andre ORCID: https://orcid.org/0000-0002-5194-3469, Alani, Amir and Zivanovic, Stana (2019) A pedestrian-based forced vibration approach for modal identification. In: EGU General Assembly 2019, 07-12 Apr 2019, Vienna, Austria.

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Abstract

A wide number of applications in vibration analysis rely on estimation of modal properties, such as natural frequencies,
mode shapes, damping ratios and modal masses [1]. Identified modal parameters form an information
baseline for model updating [2], sensor placement, damage detection [3] and structural performance evaluation [4].
Thus, the relevance of modal testing keeps increasing, particularly for slender and wobbly structures such as long
bridges.
At the same time, modal identification often relies on expensive and difficult-to-operate technical equipment, such
as shakers or impact hammers. Other drawbacks of these methods include high sensitivity to non-linearities, timeconsumption
and susceptibility to human-structure interaction effects.
As a consequence, this work investigates the applicability of a new spectral approach for modal identification in
slender structures. The approach is fast, cost-effective and easy-to-perform. It questions if is it possible to identify
modal properties, with a reliability comparable to standard modal tests, using only a human induced excitation.
The identification process requires two main inputs: recordings of structural responses under passage of a given
pedestrian at a timed pacing rate; and the pedestrian’s walk forces at the same pacing rate (which can be recorded
with an instrumented treadmill). Validation of the methodology is illustrated with a 16.9 m long fiber reinforced
polymer footbridge, instrumented with accelerometers, on which standard modal tests have been performed.
One of the most significant aspects of the proposed approach is its probabilistic treatment of the identification
process, which allows to learn the modal properties from data, while accounting for their estimation variability and
measurement noise. Moreover, the human excitation is described with a power spectral density model, based on
recorded pedestrian walk forces. In essence, a complex Gaussian log-likelihood function of the dynamic response
power spectrum is established and then sampled with the Metropolis–Hastings [5] algorithm. Future developments
aim to also account for identification bias.
Results indicate that the pedestrian-based approach can identify natural frequencies and damping ratios with a
reliability comparable to reference values, obtained with an impact hammer modal test. On the other hand, modal
masses are biased relatively to reference values. However, it is noted that even on standard tests, modal masses
pose a challenging identification problem. Consequently, the pedestrian-based approach developed in this work is
believed to pave a new way for modal identification in structural dynamics.
[1] J. Brownjohn, P. Reynolds, S.-K. Au, D. Hester, and M. Bocian, “Experimental modal analysis of civil structures:
state of the art,” presented at the SHMII – 7th International Conference on Structural Health Monitoring of
Intelligent Infrastructure, 2015.
[2] A. Jesus, P. Brommer, R.Westgate, K. Koo, J. Brownjohn, and I. Laory, “Bayesian structural identification of a
long suspension bridge considering temperature and traffic load effects,” Structural Health Monitoring, pp. 1–14,
Sep. 2018.
[3] A. Jesus, P. Brommer, R.Westgate, K. Y. Koo, J. Brownjohn, and I. Laory, “Modular Bayesian damage detection
for complex civil infrastructure,” JCSHM, no. Current Advances in Structural Health Monitoring, Dec. 2018.
[4] A. Jesus, P. Brommer, Y. Zhu, and I. Laory, “Comprehensive Bayesian structural identification using temperature
variation,” Engineering Structures, vol. 141, pp. 75–82, Jun. 2017.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Construction and engineering > Civil and environmental engineering Construction and engineering > Civil and structural engineering Construction and engineering
Depositing User:	Fabio Tosti
Date Deposited:	07 Jan 2020 16:32
Last Modified:	04 Nov 2024 12:48
URI:	https://repository.uwl.ac.uk/id/eprint/6674

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