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Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing

Assessing ageing infrastructure is a critical challenge for civil engineers due to the difficulty in the estimation and integration of uncertainties in structural models. Field measurements are increasingly used to improve knowledge of the real behavior of a structure; this activity is called struct...

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Autores principales: Bertola, Numa Joy, Papadopoulou, Maria, Vernay, Didier, Smith, Ian F. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751592/
https://www.ncbi.nlm.nih.gov/pubmed/29240684
http://dx.doi.org/10.3390/s17122904
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author Bertola, Numa Joy
Papadopoulou, Maria
Vernay, Didier
Smith, Ian F. C.
author_facet Bertola, Numa Joy
Papadopoulou, Maria
Vernay, Didier
Smith, Ian F. C.
author_sort Bertola, Numa Joy
collection PubMed
description Assessing ageing infrastructure is a critical challenge for civil engineers due to the difficulty in the estimation and integration of uncertainties in structural models. Field measurements are increasingly used to improve knowledge of the real behavior of a structure; this activity is called structural identification. Error-domain model falsification (EDMF) is an easy-to-use model-based structural-identification methodology which robustly accommodates systematic uncertainties originating from sources such as boundary conditions, numerical modelling and model fidelity, as well as aleatory uncertainties from sources such as measurement error and material parameter-value estimations. In most practical applications of structural identification, sensors are placed using engineering judgment and experience. However, since sensor placement is fundamental to the success of structural identification, a more rational and systematic method is justified. This study presents a measurement system design methodology to identify the best sensor locations and sensor types using information from static-load tests. More specifically, three static-load tests were studied for the sensor system design using three types of sensors for a performance evaluation of a full-scale bridge in Singapore. Several sensor placement strategies are compared using joint entropy as an information-gain metric. A modified version of the hierarchical algorithm for sensor placement is proposed to take into account mutual information between load tests. It is shown that a carefully-configured measurement strategy that includes multiple sensor types and several load tests maximizes information gain.
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spelling pubmed-57515922018-01-10 Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing Bertola, Numa Joy Papadopoulou, Maria Vernay, Didier Smith, Ian F. C. Sensors (Basel) Article Assessing ageing infrastructure is a critical challenge for civil engineers due to the difficulty in the estimation and integration of uncertainties in structural models. Field measurements are increasingly used to improve knowledge of the real behavior of a structure; this activity is called structural identification. Error-domain model falsification (EDMF) is an easy-to-use model-based structural-identification methodology which robustly accommodates systematic uncertainties originating from sources such as boundary conditions, numerical modelling and model fidelity, as well as aleatory uncertainties from sources such as measurement error and material parameter-value estimations. In most practical applications of structural identification, sensors are placed using engineering judgment and experience. However, since sensor placement is fundamental to the success of structural identification, a more rational and systematic method is justified. This study presents a measurement system design methodology to identify the best sensor locations and sensor types using information from static-load tests. More specifically, three static-load tests were studied for the sensor system design using three types of sensors for a performance evaluation of a full-scale bridge in Singapore. Several sensor placement strategies are compared using joint entropy as an information-gain metric. A modified version of the hierarchical algorithm for sensor placement is proposed to take into account mutual information between load tests. It is shown that a carefully-configured measurement strategy that includes multiple sensor types and several load tests maximizes information gain. MDPI 2017-12-14 /pmc/articles/PMC5751592/ /pubmed/29240684 http://dx.doi.org/10.3390/s17122904 Text en © 2017 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bertola, Numa Joy
Papadopoulou, Maria
Vernay, Didier
Smith, Ian F. C.
Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
title Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
title_full Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
title_fullStr Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
title_full_unstemmed Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
title_short Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
title_sort optimal multi-type sensor placement for structural identification by static-load testing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751592/
https://www.ncbi.nlm.nih.gov/pubmed/29240684
http://dx.doi.org/10.3390/s17122904
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