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...

Full description

Bibliographic Details
Main Authors: Numa Joy Bertola, Maria Papadopoulou, Didier Vernay, Ian F. C. Smith
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/17/12/2904
_version_ 1811185232806674432
author Numa Joy Bertola
Maria Papadopoulou
Didier Vernay
Ian F. C. Smith
author_facet Numa Joy Bertola
Maria Papadopoulou
Didier Vernay
Ian F. C. Smith
author_sort Numa Joy Bertola
collection DOAJ
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.
first_indexed 2024-04-11T13:25:58Z
format Article
id doaj.art-aeff1084fc054ad8bb67252a7790d39b
institution Directory Open Access Journal
issn 1424-8220
language English
last_indexed 2024-04-11T13:25:58Z
publishDate 2017-12-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj.art-aeff1084fc054ad8bb67252a7790d39b2022-12-22T04:22:04ZengMDPI AGSensors1424-82202017-12-011712290410.3390/s17122904s17122904Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load TestingNuma Joy Bertola0Maria Papadopoulou1Didier Vernay2Ian F. C. Smith3ETH Zurich, Future Cities Laboratory, Singapore-ETH Centre, 1 CREATE Way, CREATE Tower, Singapore 138602, SingaporeETH Zurich, Future Cities Laboratory, Singapore-ETH Centre, 1 CREATE Way, CREATE Tower, Singapore 138602, SingaporeETH Zurich, Future Cities Laboratory, Singapore-ETH Centre, 1 CREATE Way, CREATE Tower, Singapore 138602, SingaporeApplied Computing and Mechanics Laboratory (IMAC), School of Architecture, Civil and Environmental Engineering (ENAC), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, SwitzerlandAssessing 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.https://www.mdpi.com/1424-8220/17/12/2904structural identificationmeasurement systemssensorsmodel falsificationjoint entropyuncertaintiesload tests
spellingShingle Numa Joy Bertola
Maria Papadopoulou
Didier Vernay
Ian F. C. Smith
Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
Sensors
structural identification
measurement systems
sensors
model falsification
joint entropy
uncertainties
load tests
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 structural identification
measurement systems
sensors
model falsification
joint entropy
uncertainties
load tests
url https://www.mdpi.com/1424-8220/17/12/2904
work_keys_str_mv AT numajoybertola optimalmultitypesensorplacementforstructuralidentificationbystaticloadtesting
AT mariapapadopoulou optimalmultitypesensorplacementforstructuralidentificationbystaticloadtesting
AT didiervernay optimalmultitypesensorplacementforstructuralidentificationbystaticloadtesting
AT ianfcsmith optimalmultitypesensorplacementforstructuralidentificationbystaticloadtesting