Issue |
MATEC Web Conf.
Volume 281, 2019
International Conference of Engineering Risk (INCER 2019)
|
|
---|---|---|
Article Number | 01004 | |
Number of page(s) | 5 | |
Section | Civil Infrastructures: Bridges, Structures, Dams | |
DOI | https://doi.org/10.1051/matecconf/201928101004 | |
Published online | 21 May 2019 |
A predator-prey optimization for structural health monitoring problems
1 ESIB, Université Saint-Joseph, Mar Roukos, PoB. 11-154, Riad El Solh, Beyrouth, Liban
2 Université Clermont Auvergne, CNRS, Institut Pascal, 63000 Clermont-Ferrand, France
3 CIDECO, 2 av. Blaise Pascal, 63178 Aubière, France
* christelle.geara@net.usj.edu.lb
Monitoring a structure using permanent sensors has been one of the most interesting topics, especially with the increase of the number of aging structures. Such a technique requires the implementation of sensors on a structure to predict the condition states of the structural elements. However, due to the costs of sensors, one must judiciously install few sensors at some defined locations in order to maximize the probability of detecting potential damages. In this paper, we propose a methodology based on a genetic algorithm of type predator-prey with a Bayesian updating of the structural parameters, to optimize the number and location of the sensors to be placed. This methodology takes into consideration all uncertainties related to the degradation of the elements, the mechanical model and the accuracy of sensors. Starting with two initial populations representing the damages (prey) and the sensors (predator), the genetic algorithm evolves both populations in order to converge towards the optimal configuration of sensors, in terms of number and location. The proposed methodology is illustrated by a two-story concrete frame structure.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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