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Hybrid probabilities and error-domain structural identification using ambient vibration monitoring

James-A. Goulet, Clotaire Michel and Ian F.C. Smith

Article (2013)

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Cite this document: Goulet, J.-A., Michel, C. & Smith, I. F.C. (2013). Hybrid probabilities and error-domain structural identification using ambient vibration monitoring. Mechanical Systems and Signal Processing, 37(1-2), p. 199-212. doi:10.1016/j.ymssp.2012.05.017
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Abstract

For the assessment of structural behaviour, many approaches are available to compare model predictions with measurements. However, few approaches include uncertainties along with dependencies associated with models and observations. In this paper, an error-domain structural identification approach is proposed using ambient vibration monitoring (AVM) as the input. This approach is based on the principle that in science, data cannot truly validate a hypothesis, it can only be used to falsity it. Error-domain model falsification generates a space of possible model instances (combination of parameters), obtains predictions for each of them and then rejects instances that have unlikely differences (residuals) between predictions and measurements. Models are filtered in a two step process. Firstly a comparison of mode shapes based on MAC criterion ensures that the same modes are compared. Secondly, the frequencies from each model instance are compared with the measurements. The instances for which the difference between the predicted and measured value lie outside threshold bounds are discarded. In order to include “uncertainty of uncertainty” in the identification process, a hybrid probability scheme is also presented. The approach is used for the identification of the Langensand Bridge in Switzerland. It is used to falsify the hypothesis that the bridge was behaving as designed when subjected to ambient vibration inputs, before opening to the traffic. Such small amplitudes may be affected by low-level bearing-device friction. This inadvertently increased the apparent stiffness of the structure by 17%. This observation supports the premiss that ambient vibration surveys should be cross-checked with other information sources, such as numerical models, in order to avoid misinterpreting the data.

Uncontrolled Keywords

Structural identification, Ambient vibration monitoring, Uncertainty, error-domain identification, Extended uniform distribution, Correlation, Error

Open Access document in PolyPublie
Subjects: 1000 Génie civil > 1000 Génie civil
Department: Département des génies civil, géologique et des mines
Research Center: Non applicable
Funders: Swiss National Science Foundation
Grant number: 200020-117670/1
Date Deposited: 15 Jan 2018 15:23
Last Modified: 24 Oct 2018 16:12
PolyPublie URL: https://publications.polymtl.ca/2890/
Document issued by the official publisher
Journal Title: Mechanical Systems and Signal Processing (vol. 37, no. 1-2)
Publisher: Elsevier
Official URL: https://doi.org/10.1016/j.ymssp.2012.05.017

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