Automatic qualitative trend simulation method for diagnosing faults in industrial processes

Autores
Maestri, Mauricio Leonardo; Ziella, Daniel Horacio; Cassanello Fernandez, Miryam Celeste; Horowitz, Gabriel Ignacio
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work proposes an automatic method of qualitative simulation for industrial processes to predict the steady-state measurement patterns arising from different faults. Due to their characteristics, qualitative simulations tend to generate multiple spurious solutions. The proposed method limits the number of such spurious solutions by automatically generating new qualitative equations from the generic quantitative model (i.e. without the need of knowing the value of its parameters) and using simple qualitative known relations or other readily available information. An algorithm to obtain such solutions from the set of qualitative equations is also presented.
Fil: Maestri, Mauricio Leonardo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Ziella, Daniel Horacio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cassanello Fernandez, Miryam Celeste. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Horowitz, Gabriel Ignacio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Qualitative Simulation
Fault Diagnosis
Confluences
Fault Trend Patterns
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/32081
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Automatic qualitative trend simulation method for diagnosing faults in industrial processesMaestri, Mauricio LeonardoZiella, Daniel HoracioCassanello Fernandez, Miryam CelesteHorowitz, Gabriel IgnacioQualitative SimulationFault DiagnosisConfluencesFault Trend Patternshttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This work proposes an automatic method of qualitative simulation for industrial processes to predict the steady-state measurement patterns arising from different faults. Due to their characteristics, qualitative simulations tend to generate multiple spurious solutions. The proposed method limits the number of such spurious solutions by automatically generating new qualitative equations from the generic quantitative model (i.e. without the need of knowing the value of its parameters) and using simple qualitative known relations or other readily available information. An algorithm to obtain such solutions from the set of qualitative equations is also presented.Fil: Maestri, Mauricio Leonardo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ziella, Daniel Horacio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cassanello Fernandez, Miryam Celeste. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Horowitz, Gabriel Ignacio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier2014-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/32081Horowitz, Gabriel Ignacio; Cassanello Fernandez, Miryam Celeste; Ziella, Daniel Horacio; Maestri, Mauricio Leonardo; Automatic qualitative trend simulation method for diagnosing faults in industrial processes; Elsevier; Computers and Chemical Engineering; 64; 1-2014; 55-620098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009813541400009Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2014.01.007info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:58:19Zoai:ri.conicet.gov.ar:11336/32081instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:58:19.659CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Automatic qualitative trend simulation method for diagnosing faults in industrial processes
title Automatic qualitative trend simulation method for diagnosing faults in industrial processes
spellingShingle Automatic qualitative trend simulation method for diagnosing faults in industrial processes
Maestri, Mauricio Leonardo
Qualitative Simulation
Fault Diagnosis
Confluences
Fault Trend Patterns
title_short Automatic qualitative trend simulation method for diagnosing faults in industrial processes
title_full Automatic qualitative trend simulation method for diagnosing faults in industrial processes
title_fullStr Automatic qualitative trend simulation method for diagnosing faults in industrial processes
title_full_unstemmed Automatic qualitative trend simulation method for diagnosing faults in industrial processes
title_sort Automatic qualitative trend simulation method for diagnosing faults in industrial processes
dc.creator.none.fl_str_mv Maestri, Mauricio Leonardo
Ziella, Daniel Horacio
Cassanello Fernandez, Miryam Celeste
Horowitz, Gabriel Ignacio
author Maestri, Mauricio Leonardo
author_facet Maestri, Mauricio Leonardo
Ziella, Daniel Horacio
Cassanello Fernandez, Miryam Celeste
Horowitz, Gabriel Ignacio
author_role author
author2 Ziella, Daniel Horacio
Cassanello Fernandez, Miryam Celeste
Horowitz, Gabriel Ignacio
author2_role author
author
author
dc.subject.none.fl_str_mv Qualitative Simulation
Fault Diagnosis
Confluences
Fault Trend Patterns
topic Qualitative Simulation
Fault Diagnosis
Confluences
Fault Trend Patterns
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This work proposes an automatic method of qualitative simulation for industrial processes to predict the steady-state measurement patterns arising from different faults. Due to their characteristics, qualitative simulations tend to generate multiple spurious solutions. The proposed method limits the number of such spurious solutions by automatically generating new qualitative equations from the generic quantitative model (i.e. without the need of knowing the value of its parameters) and using simple qualitative known relations or other readily available information. An algorithm to obtain such solutions from the set of qualitative equations is also presented.
Fil: Maestri, Mauricio Leonardo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Ziella, Daniel Horacio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cassanello Fernandez, Miryam Celeste. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Horowitz, Gabriel Ignacio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description This work proposes an automatic method of qualitative simulation for industrial processes to predict the steady-state measurement patterns arising from different faults. Due to their characteristics, qualitative simulations tend to generate multiple spurious solutions. The proposed method limits the number of such spurious solutions by automatically generating new qualitative equations from the generic quantitative model (i.e. without the need of knowing the value of its parameters) and using simple qualitative known relations or other readily available information. An algorithm to obtain such solutions from the set of qualitative equations is also presented.
publishDate 2014
dc.date.none.fl_str_mv 2014-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/32081
Horowitz, Gabriel Ignacio; Cassanello Fernandez, Miryam Celeste; Ziella, Daniel Horacio; Maestri, Mauricio Leonardo; Automatic qualitative trend simulation method for diagnosing faults in industrial processes; Elsevier; Computers and Chemical Engineering; 64; 1-2014; 55-62
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/32081
identifier_str_mv Horowitz, Gabriel Ignacio; Cassanello Fernandez, Miryam Celeste; Ziella, Daniel Horacio; Maestri, Mauricio Leonardo; Automatic qualitative trend simulation method for diagnosing faults in industrial processes; Elsevier; Computers and Chemical Engineering; 64; 1-2014; 55-62
0098-1354
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S009813541400009X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2014.01.007
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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