On the precision evaluation in non-linear sensor network design

Autores
Hernández, José Luis; Simón, Silvia; Carnero, Mercedes; Minetti, Gabriela F.; Salto, Carolina
Año de publicación
2023
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The aim of this work is to provide a tool for evaluating the precision of process variable estimates in the context of the optimal design of a sensor network in chemical plants. One of the possible formulations for the optimal design of an instrumentation system for monitoring tasks is the solution of nonlinear optimization problems with constraints, where the objective function is the cost of the instrument and the constraints are the observability and global precision associated with a sensor placement. When a metaheuristic approach is used to solve this problem, a methodology for computing the constraints is needed to evaluate the quality of a proposed solution. A simulation technique has been selected to solve the precision associated with a set of measurements. The simulator requires a variable classification methodology and a data reconciliation function that consists of solving another non-linear optimization. The proposed strategies have been applied to a continuous stirred tank reactor, a nonlinear problem including flows, compositions, and temperatures related by mass and energy balances. Results demonstrating the performance of the proposed metaheuristics are presented.
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Sensor Network Design
optimization
Monte Carlo approach
variable estimates
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/164845

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network_name_str SEDICI (UNLP)
spelling On the precision evaluation in non-linear sensor network designHernández, José LuisSimón, SilviaCarnero, MercedesMinetti, Gabriela F.Salto, CarolinaCiencias InformáticasSensor Network DesignoptimizationMonte Carlo approachvariable estimatesThe aim of this work is to provide a tool for evaluating the precision of process variable estimates in the context of the optimal design of a sensor network in chemical plants. One of the possible formulations for the optimal design of an instrumentation system for monitoring tasks is the solution of nonlinear optimization problems with constraints, where the objective function is the cost of the instrument and the constraints are the observability and global precision associated with a sensor placement. When a metaheuristic approach is used to solve this problem, a methodology for computing the constraints is needed to evaluate the quality of a proposed solution. A simulation technique has been selected to solve the precision associated with a set of measurements. The simulator requires a variable classification methodology and a data reconciliation function that consists of solving another non-linear optimization. The proposed strategies have been applied to a continuous stirred tank reactor, a nonlinear problem including flows, compositions, and temperatures related by mass and energy balances. Results demonstrating the performance of the proposed metaheuristics are presented.Red de Universidades con Carreras en Informática2023-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf48-57http://sedici.unlp.edu.ar/handle/10915/164845enginfo:eu-repo/semantics/reference/url/https://sedici.unlp.edu.ar/handle/10915/163107info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:43:41Zoai:sedici.unlp.edu.ar:10915/164845Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:43:41.999SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv On the precision evaluation in non-linear sensor network design
title On the precision evaluation in non-linear sensor network design
spellingShingle On the precision evaluation in non-linear sensor network design
Hernández, José Luis
Ciencias Informáticas
Sensor Network Design
optimization
Monte Carlo approach
variable estimates
title_short On the precision evaluation in non-linear sensor network design
title_full On the precision evaluation in non-linear sensor network design
title_fullStr On the precision evaluation in non-linear sensor network design
title_full_unstemmed On the precision evaluation in non-linear sensor network design
title_sort On the precision evaluation in non-linear sensor network design
dc.creator.none.fl_str_mv Hernández, José Luis
Simón, Silvia
Carnero, Mercedes
Minetti, Gabriela F.
Salto, Carolina
author Hernández, José Luis
author_facet Hernández, José Luis
Simón, Silvia
Carnero, Mercedes
Minetti, Gabriela F.
Salto, Carolina
author_role author
author2 Simón, Silvia
Carnero, Mercedes
Minetti, Gabriela F.
Salto, Carolina
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Sensor Network Design
optimization
Monte Carlo approach
variable estimates
topic Ciencias Informáticas
Sensor Network Design
optimization
Monte Carlo approach
variable estimates
dc.description.none.fl_txt_mv The aim of this work is to provide a tool for evaluating the precision of process variable estimates in the context of the optimal design of a sensor network in chemical plants. One of the possible formulations for the optimal design of an instrumentation system for monitoring tasks is the solution of nonlinear optimization problems with constraints, where the objective function is the cost of the instrument and the constraints are the observability and global precision associated with a sensor placement. When a metaheuristic approach is used to solve this problem, a methodology for computing the constraints is needed to evaluate the quality of a proposed solution. A simulation technique has been selected to solve the precision associated with a set of measurements. The simulator requires a variable classification methodology and a data reconciliation function that consists of solving another non-linear optimization. The proposed strategies have been applied to a continuous stirred tank reactor, a nonlinear problem including flows, compositions, and temperatures related by mass and energy balances. Results demonstrating the performance of the proposed metaheuristics are presented.
Red de Universidades con Carreras en Informática
description The aim of this work is to provide a tool for evaluating the precision of process variable estimates in the context of the optimal design of a sensor network in chemical plants. One of the possible formulations for the optimal design of an instrumentation system for monitoring tasks is the solution of nonlinear optimization problems with constraints, where the objective function is the cost of the instrument and the constraints are the observability and global precision associated with a sensor placement. When a metaheuristic approach is used to solve this problem, a methodology for computing the constraints is needed to evaluate the quality of a proposed solution. A simulation technique has been selected to solve the precision associated with a set of measurements. The simulator requires a variable classification methodology and a data reconciliation function that consists of solving another non-linear optimization. The proposed strategies have been applied to a continuous stirred tank reactor, a nonlinear problem including flows, compositions, and temperatures related by mass and energy balances. Results demonstrating the performance of the proposed metaheuristics are presented.
publishDate 2023
dc.date.none.fl_str_mv 2023-10
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info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/reference/url/https://sedici.unlp.edu.ar/handle/10915/163107
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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