Process decomposition and test selection for distributed fault diagnosis

Elodie Chanthery, Anna Sztyber, Louise Travé-Massuyès, Carlos Gustavo Pérez-Zuñiga

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

Decomposing is one way to gain efficiency when dealing with large scale systems. In addition, the breakdown into subsystems may be mandatory to reflect some geographic or confidentiality constraints. In this context, the selection of diagnostic tests must comply with decomposition and it is desired to minimize the number of subsystem interconnections while still guaranteeing maximal diagnosability. On the other hand, it should be noticed that there is often some flexibility in the way to decompose a system. By placing itself in the context of structural analysis, this paper provides a solution to the double overlinked problem of choosing the decomposition of the system by leveraging existing flexibility and of selecting the set of diagnostic tests so as to minimize subsystem interconnections while maximizing diagnosability.

Idioma originalInglés
Título de la publicación alojadaTrends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices - 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, Proceedings
EditoresHamido Fujita, Jun Sasaki, Philippe Fournier-Viger, Moonis Ali
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas914-925
Número de páginas12
ISBN (versión impresa)9783030557881
DOI
EstadoPublicada - 2020
Evento33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020 - Kitakyushu, Japón
Duración: 22 set. 202025 set. 2020

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen12144 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020
País/TerritorioJapón
CiudadKitakyushu
Período22/09/2025/09/20

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