Fault manifestability verification for discrete event systems

Autores
Ye, Lina; Dague, Philippe; Longuet, Delphine; Brandán Briones, Laura; Madalinski, Agnes
Año de publicación
2016
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Ponencia presentada en la 22nd European Conference on Artificial Intelligence ECAI-16. La Haya, Holanda del 29 agosto al 2 de septiembre de 2016.
Fil: Ye, Lina. Université Paris-Saclay. CentraleSupélec; France.
Fil: Ye, Lina. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Ye, Lina. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Brandán Briones, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.
Fil: Madalinski, Agnes. Otto-von-Guericke-University Magdeburg; Germany.
Fault diagnosis is a crucial and challenging task in the automatic control of complex systems, whose efficiency depends on the diagnosability property of a system. Diagnosability describes the system ability to determine whether a given fault has effectively occurred based on the observations. However, this is a very strong property that requires generally high number of sensors to be satisfied. Consequently, it is not rare that developing a diagnosable system is too expensive. To solve this problem, in this paper, we first define a new system property called manifestability that represents the weakest requirement on faults and observations for having a chance to identify on line fault occurrences and can be verified at design stage. Then, we propose an algorithm with PSPACE complexity to automatically verify it.
Fil: Ye, Lina. Université Paris-Saclay. CentraleSupélec; France.
Fil: Ye, Lina. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Ye, Lina. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Brandán Briones, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.
Fil: Madalinski, Agnes. Otto-von-Guericke-University Magdeburg; Germany.
Ciencias de la Computación
Fuente
e-ISSN: 1879-8314
Materia
Fault diagnosis
Manifestability
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Repositorio
Repositorio Digital Universitario (UNC)
Institución
Universidad Nacional de Córdoba
OAI Identificador
oai:rdu.unc.edu.ar:11086/548025
Acceder
id RDUUNC_72b135524bbdeaa027bf9f7ea72d3f9e
oai_identifier_str oai:rdu.unc.edu.ar:11086/548025
network_acronym_str RDUUNC
repository_id_str 2572
network_name_str Repositorio Digital Universitario (UNC)
spelling Fault manifestability verification for discrete event systemsYe, LinaDague, PhilippeLonguet, DelphineBrandán Briones, LauraMadalinski, AgnesFault diagnosisManifestabilityPonencia presentada en la 22nd European Conference on Artificial Intelligence ECAI-16. La Haya, Holanda del 29 agosto al 2 de septiembre de 2016.Fil: Ye, Lina. Université Paris-Saclay. CentraleSupélec; France.Fil: Ye, Lina. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.Fil: Ye, Lina. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.Fil: Dague, Philippe. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.Fil: Dague, Philippe. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.Fil: Longuet, Delphine. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.Fil: Longuet, Delphine. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.Fil: Brandán Briones, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.Fil: Madalinski, Agnes. Otto-von-Guericke-University Magdeburg; Germany.Fault diagnosis is a crucial and challenging task in the automatic control of complex systems, whose efficiency depends on the diagnosability property of a system. Diagnosability describes the system ability to determine whether a given fault has effectively occurred based on the observations. However, this is a very strong property that requires generally high number of sensors to be satisfied. Consequently, it is not rare that developing a diagnosable system is too expensive. To solve this problem, in this paper, we first define a new system property called manifestability that represents the weakest requirement on faults and observations for having a chance to identify on line fault occurrences and can be verified at design stage. Then, we propose an algorithm with PSPACE complexity to automatically verify it.Fil: Ye, Lina. Université Paris-Saclay. CentraleSupélec; France.Fil: Ye, Lina. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.Fil: Ye, Lina. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.Fil: Dague, Philippe. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.Fil: Dague, Philippe. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.Fil: Longuet, Delphine. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.Fil: Longuet, Delphine. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.Fil: Brandán Briones, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.Fil: Madalinski, Agnes. Otto-von-Guericke-University Magdeburg; Germany.Ciencias de la Computaciónhttps://orcid.org/0000-0003-1679-0804https://orcid.org/0000-0002-8394-276X2016info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://hdl.handle.net/11086/548025https://doi.org/10.3233/978-1-61499-672-9-1718e-ISSN: 1879-8314reponame:Repositorio Digital Universitario (UNC)instname:Universidad Nacional de Córdobainstacron:UNCenginfo:eu-repo/semantics/openAccess2025-09-29T13:44:27Zoai:rdu.unc.edu.ar:11086/548025Institucionalhttps://rdu.unc.edu.ar/Universidad públicaNo correspondehttp://rdu.unc.edu.ar/oai/snrdoca.unc@gmail.comArgentinaNo correspondeNo correspondeNo correspondeopendoar:25722025-09-29 13:44:27.278Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdobafalse
dc.title.none.fl_str_mv Fault manifestability verification for discrete event systems
title Fault manifestability verification for discrete event systems
spellingShingle Fault manifestability verification for discrete event systems
Ye, Lina
Fault diagnosis
Manifestability
title_short Fault manifestability verification for discrete event systems
title_full Fault manifestability verification for discrete event systems
title_fullStr Fault manifestability verification for discrete event systems
title_full_unstemmed Fault manifestability verification for discrete event systems
title_sort Fault manifestability verification for discrete event systems
dc.creator.none.fl_str_mv Ye, Lina
Dague, Philippe
Longuet, Delphine
Brandán Briones, Laura
Madalinski, Agnes
author Ye, Lina
author_facet Ye, Lina
Dague, Philippe
Longuet, Delphine
Brandán Briones, Laura
Madalinski, Agnes
author_role author
author2 Dague, Philippe
Longuet, Delphine
Brandán Briones, Laura
Madalinski, Agnes
author2_role author
author
author
author
dc.contributor.none.fl_str_mv https://orcid.org/0000-0003-1679-0804
https://orcid.org/0000-0002-8394-276X
dc.subject.none.fl_str_mv Fault diagnosis
Manifestability
topic Fault diagnosis
Manifestability
dc.description.none.fl_txt_mv Ponencia presentada en la 22nd European Conference on Artificial Intelligence ECAI-16. La Haya, Holanda del 29 agosto al 2 de septiembre de 2016.
Fil: Ye, Lina. Université Paris-Saclay. CentraleSupélec; France.
Fil: Ye, Lina. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Ye, Lina. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Brandán Briones, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.
Fil: Madalinski, Agnes. Otto-von-Guericke-University Magdeburg; Germany.
Fault diagnosis is a crucial and challenging task in the automatic control of complex systems, whose efficiency depends on the diagnosability property of a system. Diagnosability describes the system ability to determine whether a given fault has effectively occurred based on the observations. However, this is a very strong property that requires generally high number of sensors to be satisfied. Consequently, it is not rare that developing a diagnosable system is too expensive. To solve this problem, in this paper, we first define a new system property called manifestability that represents the weakest requirement on faults and observations for having a chance to identify on line fault occurrences and can be verified at design stage. Then, we propose an algorithm with PSPACE complexity to automatically verify it.
Fil: Ye, Lina. Université Paris-Saclay. CentraleSupélec; France.
Fil: Ye, Lina. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Ye, Lina. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Dague, Philippe. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Université Paris-Sud. Laboratoire de Recherche en Informatique; France.
Fil: Longuet, Delphine. Centre National de la Recherche Scientifique. Laboratoire de Recherche en Informatique; France.
Fil: Brandán Briones, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.
Fil: Madalinski, Agnes. Otto-von-Guericke-University Magdeburg; Germany.
Ciencias de la Computación
description Ponencia presentada en la 22nd European Conference on Artificial Intelligence ECAI-16. La Haya, Holanda del 29 agosto al 2 de septiembre de 2016.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11086/548025
https://doi.org/10.3233/978-1-61499-672-9-1718
url http://hdl.handle.net/11086/548025
https://doi.org/10.3233/978-1-61499-672-9-1718
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv e-ISSN: 1879-8314
reponame:Repositorio Digital Universitario (UNC)
instname:Universidad Nacional de Córdoba
instacron:UNC
reponame_str Repositorio Digital Universitario (UNC)
collection Repositorio Digital Universitario (UNC)
instname_str Universidad Nacional de Córdoba
instacron_str UNC
institution UNC
repository.name.fl_str_mv Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdoba
repository.mail.fl_str_mv oca.unc@gmail.com
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score 13.070432

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