Evaluation of robust functions for data reconciliation in thermal systems

Detalhes bibliográficos
Autor(a) principal: França, Regina Luana Santos de
Data de Publicação: 2016
Outros Autores: Oliveira Júnior, Antonio Martins, Souza, Domingos Fabiano Santana
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta scientiarum. Technology (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28188
Resumo: Process variables regularly control and evaluate industrial processes. Information with gross errors may in some cases not be attenuated by function reconciliation and change the calculation of process balance, leading optimization results towards non-feasible regions or to optimal sites. A promising alternative for reconciling functions is the use of robust functions. Current paper considers the above scenario and evaluates the fitness of some robust functions in solving in steady state chemical processes data reconciliation problems represented by linear and nonlinear systems in the presence of gross errors. Traditional Cauchy, Fair, Contaminated Normal and Logistic robust functions are used in the reconciliation problem where their estimates are compared to those obtained with the use of the latest features, such as New Target and Alarm. Rates for gross errors in tests were limited between 4 and 10σ of the measured current and elaborated a region of outliers. Results showed that New Target and Alarm functions are different from the others as the magnitude of the gross error increases, tending towards true rates specified by set point.
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spelling Evaluation of robust functions for data reconciliation in thermal systemsEvaluation of robust functions for data reconciliation in thermal systemsset measuresrobustnessefficiencynonlinear systemsReconciliação de Dadosset measuresrobustnessefficiencynonlinear systems.Reconciliação de dadosProcess variables regularly control and evaluate industrial processes. Information with gross errors may in some cases not be attenuated by function reconciliation and change the calculation of process balance, leading optimization results towards non-feasible regions or to optimal sites. A promising alternative for reconciling functions is the use of robust functions. Current paper considers the above scenario and evaluates the fitness of some robust functions in solving in steady state chemical processes data reconciliation problems represented by linear and nonlinear systems in the presence of gross errors. Traditional Cauchy, Fair, Contaminated Normal and Logistic robust functions are used in the reconciliation problem where their estimates are compared to those obtained with the use of the latest features, such as New Target and Alarm. Rates for gross errors in tests were limited between 4 and 10σ of the measured current and elaborated a region of outliers. Results showed that New Target and Alarm functions are different from the others as the magnitude of the gross error increases, tending towards true rates specified by set point.Process variables regularly control and evaluate industrial processes. Information with gross errors may in some cases not be attenuated by function reconciliation and change the calculation of process balance, leading optimization results towards non-feasible regions or to optimal sites. A promising alternative for reconciling functions is the use of robust functions. Current paper considers the above scenario and evaluates the fitness of some robust functions in solving in steady state chemical processes data reconciliation problems represented by linear and nonlinear systems in the presence of gross errors. Traditional Cauchy, Fair, Contaminated Normal and Logistic robust functions are used in the reconciliation problem where their estimates are compared to those obtained with the use of the latest features, such as New Target and Alarm. Rates for gross errors in tests were limited between 4 and 10σ of the measured current and elaborated a region of outliers. Results showed that New Target and Alarm functions are different from the others as the magnitude of the gross error increases, tending towards true rates specified by set point.Universidade Estadual De Maringá2016-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionMétodoMétodoapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/2818810.4025/actascitechnol.v38i2.28188Acta Scientiarum. Technology; Vol 38 No 2 (2016); 185-191Acta Scientiarum. Technology; v. 38 n. 2 (2016); 185-1911806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28188/pdf_145França, Regina Luana Santos deOliveira Júnior, Antonio MartinsSouza, Domingos Fabiano Santanainfo:eu-repo/semantics/openAccess2016-04-12T14:40:38Zoai:periodicos.uem.br/ojs:article/28188Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2016-04-12T14:40:38Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Evaluation of robust functions for data reconciliation in thermal systems
Evaluation of robust functions for data reconciliation in thermal systems
title Evaluation of robust functions for data reconciliation in thermal systems
spellingShingle Evaluation of robust functions for data reconciliation in thermal systems
França, Regina Luana Santos de
set measures
robustness
efficiency
nonlinear systems
Reconciliação de Dados
set measures
robustness
efficiency
nonlinear systems.
Reconciliação de dados
title_short Evaluation of robust functions for data reconciliation in thermal systems
title_full Evaluation of robust functions for data reconciliation in thermal systems
title_fullStr Evaluation of robust functions for data reconciliation in thermal systems
title_full_unstemmed Evaluation of robust functions for data reconciliation in thermal systems
title_sort Evaluation of robust functions for data reconciliation in thermal systems
author França, Regina Luana Santos de
author_facet França, Regina Luana Santos de
Oliveira Júnior, Antonio Martins
Souza, Domingos Fabiano Santana
author_role author
author2 Oliveira Júnior, Antonio Martins
Souza, Domingos Fabiano Santana
author2_role author
author
dc.contributor.author.fl_str_mv França, Regina Luana Santos de
Oliveira Júnior, Antonio Martins
Souza, Domingos Fabiano Santana
dc.subject.por.fl_str_mv set measures
robustness
efficiency
nonlinear systems
Reconciliação de Dados
set measures
robustness
efficiency
nonlinear systems.
Reconciliação de dados
topic set measures
robustness
efficiency
nonlinear systems
Reconciliação de Dados
set measures
robustness
efficiency
nonlinear systems.
Reconciliação de dados
description Process variables regularly control and evaluate industrial processes. Information with gross errors may in some cases not be attenuated by function reconciliation and change the calculation of process balance, leading optimization results towards non-feasible regions or to optimal sites. A promising alternative for reconciling functions is the use of robust functions. Current paper considers the above scenario and evaluates the fitness of some robust functions in solving in steady state chemical processes data reconciliation problems represented by linear and nonlinear systems in the presence of gross errors. Traditional Cauchy, Fair, Contaminated Normal and Logistic robust functions are used in the reconciliation problem where their estimates are compared to those obtained with the use of the latest features, such as New Target and Alarm. Rates for gross errors in tests were limited between 4 and 10σ of the measured current and elaborated a region of outliers. Results showed that New Target and Alarm functions are different from the others as the magnitude of the gross error increases, tending towards true rates specified by set point.
publishDate 2016
dc.date.none.fl_str_mv 2016-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Método
Método
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28188
10.4025/actascitechnol.v38i2.28188
url http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28188
identifier_str_mv 10.4025/actascitechnol.v38i2.28188
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/28188/pdf_145
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual De Maringá
publisher.none.fl_str_mv Universidade Estadual De Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Technology; Vol 38 No 2 (2016); 185-191
Acta Scientiarum. Technology; v. 38 n. 2 (2016); 185-191
1806-2563
1807-8664
reponame:Acta scientiarum. Technology (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta scientiarum. Technology (Online)
collection Acta scientiarum. Technology (Online)
repository.name.fl_str_mv Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv ||actatech@uem.br
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