Título :	Robust optimal sensor configuration using the value of information
Autor :	Cantero-Chinchilla, Sergio Papadimitriou, Costas Chiachío, Juan Chiachío, Manuel Koumoutsakos, Petros Fabro, Adriano Todorovic Chronopoulos, Dimitrios
metadata.dc.contributor.affiliation:	University of Bristol, Department of Mechanical Engineering University of Thessaly, Department of Mechanical Engineering University of Granada, Department of Structural Mechanics & Hydraulics Engineering, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) Harvard University, School of Engineering and Applied Sciences ETH Zürich, Computational Science and Engineering Laboratory University of Brasilia, Department of Mechanical Engineering, Department of Mechanical Engineering & Mecha(tro)nic System Dynamics (LMSD)
Assunto::	Ondas (Física) Sensores Monitoramento
Fecha de publicación :	9-nov-2022
Editorial :	Wiley
Citación :	CANTERO-CHINCHILLA, Sergio et al. Robust optimal sensor configuration using the value of information. Structural Control Health Monitoring, v. 29, n.12, e3143, dez. 2022. DOI: https://doi.org/10.1002/stc.3143. Disponível em: https://onlinelibrary.wiley.com/doi/10.1002/stc.3143. Acesso em: 22 fev. 2024.
Abstract:	Sensing is the cornerstone of any functional structural health monitoring tech nology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for optimal sensor configuration based on the value of information that accounts for (1) uncertainties from updatable and nonupdatable parameters, (2) variability of the objective function with respect to nonupdatable parameters, and (3) the spatial correlation between sensors. The optimal sensor configuration is obtained by maximizing the expected value of information, which leads to a cost-benefit analysis that entails model parameter uncertainties. The proposed methodology is demonstrated on an application of structural health monitor ing in plate-like structures using ultrasonic guided waves. We show that accounting for uncertainties is critical for an accurate diagnosis of damage. Furthermore, we provide critical assessment of the role of both the effect of modeling and measurement uncertainties and the optimization algorithm on the resulting sensor placement. The results on the health monitoring of an aluminum plate indicate the effectiveness and efficiency of the proposed methodology in discovering optimal sensor configurations.
metadata.dc.description.unidade:	Faculdade de Tecnologia (FT) Departamento de Engenharia Mecânica (FT ENM)
Licença::	This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
DOI:	https://doi.org/10.1002/stc.3143
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