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Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory

A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The framework is developed to handle virtual sensing under output-only vibration measurements. The OSP ma...

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Detalles Bibliográficos
Autores principales: Ercan, Tulay, Papadimitriou, Costas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8153162/
https://www.ncbi.nlm.nih.gov/pubmed/34068203
http://dx.doi.org/10.3390/s21103400
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author Ercan, Tulay
Papadimitriou, Costas
author_facet Ercan, Tulay
Papadimitriou, Costas
author_sort Ercan, Tulay
collection PubMed
description A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The framework is developed to handle virtual sensing under output-only vibration measurements. The OSP maximizes a utility function that quantifies the expected information gained from the data for reducing the uncertainty of quantities of interest (QoI) predicted at the virtual sensing locations. The utility function is extended to make the OSP design robust to uncertainties in structural model and modeling error parameters, resulting in a multidimensional integral of the expected information gain over all possible values of the uncertain parameters and weighted by their assigned probability distributions. Approximate methods are used to compute the multidimensional integral and solve the optimization problem that arises. The Gaussian nature of the response QoI is exploited to derive useful and informative analytical expressions for the utility function. A thorough study of the effect of model, prediction and measurement errors and their uncertainties, as well as the prior uncertainties in the modal coordinates on the selection of the optimal sensor configuration is presented, highlighting the importance of accounting for robustness to errors and other uncertainties.
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spelling pubmed-81531622021-05-27 Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory Ercan, Tulay Papadimitriou, Costas Sensors (Basel) Article A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The framework is developed to handle virtual sensing under output-only vibration measurements. The OSP maximizes a utility function that quantifies the expected information gained from the data for reducing the uncertainty of quantities of interest (QoI) predicted at the virtual sensing locations. The utility function is extended to make the OSP design robust to uncertainties in structural model and modeling error parameters, resulting in a multidimensional integral of the expected information gain over all possible values of the uncertain parameters and weighted by their assigned probability distributions. Approximate methods are used to compute the multidimensional integral and solve the optimization problem that arises. The Gaussian nature of the response QoI is exploited to derive useful and informative analytical expressions for the utility function. A thorough study of the effect of model, prediction and measurement errors and their uncertainties, as well as the prior uncertainties in the modal coordinates on the selection of the optimal sensor configuration is presented, highlighting the importance of accounting for robustness to errors and other uncertainties. MDPI 2021-05-13 /pmc/articles/PMC8153162/ /pubmed/34068203 http://dx.doi.org/10.3390/s21103400 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ercan, Tulay
Papadimitriou, Costas
Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory
title Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory
title_full Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory
title_fullStr Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory
title_full_unstemmed Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory
title_short Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory
title_sort optimal sensor placement for reliable virtual sensing using modal expansion and information theory
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8153162/
https://www.ncbi.nlm.nih.gov/pubmed/34068203
http://dx.doi.org/10.3390/s21103400
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