@ARTICLE{Ameduri_Salvatore_Distributed_2019,
 author={Ameduri, Salvatore and Ciminello, Monica and Dimino, Ignazio and Concilio, Antonio and Catignani, Alfonso and Mancinelli, Raimondo},
 volume={vol. 66},
 number={No 1},
 journal={Archive of Mechanical Engineering},
 pages={111-127},
 howpublished={online},
 year={2019},
 publisher={Polish Academy of Sciences, Committee on Machine Building},
 abstract={An optimal sensor placement methodology is implemented and herein proposed for SHM model-assisted design and analysis purposes. The kernel of this approach analysis is a genetic-based algorithm providing the sensor network layout by optimizing the probability of detection (PoD) function while, in this preliminary phase, a classic strain energy approach is adopted as well established damage detection criteria. The layout of the sensor network is assessed with respect to its own capability of detection, parameterized through the PoD. A distributed fiber optic strain sensor is adopted in order to get dense information of the structural strain field. The overall methodology includes an original user-friendly graphical interface (GUI) that reduces the time-to-design costs needs. The proposed methodology is preliminarily validated for isotropic and anisotropic elements.},
 type={Artykuły / Articles},
 title={Distributed sensor placement optimization for computer aided structural health monitoring},
 URL={http://ochroma.man.poznan.pl/Content/110282/PDF/AME_2019_126375.pdf},
 doi={10.24425/ame.2019.126375},
 keywords={SHM, fiber optic, genetic optimization, strain energy},
}