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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/164845
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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 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/164845 |
url |
http://sedici.unlp.edu.ar/handle/10915/164845 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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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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openAccess |
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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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application/pdf 48-57 |
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