Detection and treatment of faults in automated machines based on Petri nets and Bayesian networks

L. A.M. Riascos; F. G. Cozman; P. E. Miyagi

doi:10.1109/ISIE.2003.1267910

Detection and treatment of faults in automated machines based on Petri nets and Bayesian networks

L. A.M. Riascos, F. G. Cozman, P. E. Miyagi

Resultado de la investigación: Contribución a una conferencia › Artículo de conferencia

8 Citas (Scopus)

Resumen

© 2003 IEEE. In this paper, a methodology for considering detection and treatment of faults in automated machines is introduced. This methodology is based on the integration of Petri nets for diagnosis (BPN) and Bayesian networks. After that, the integration among detection/treatment of faults and the "normal" processes (represented by Petri nets, PN) is possible. This integration allows us to develop a fault tolerant supervisor, which considers all the processes in the same structure. A case study of fault tolerant AGV is considered. Finally, a simulation tool for edition and analysis of models with these characteristics is introduced.

Idioma original	Inglés estadounidense
Páginas	729-734
Número de páginas	6
DOI	https://doi.org/10.1109/ISIE.2003.1267910
Estado	Publicada - 1 ene 2003
Publicado de forma externa	Sí
Evento	IEEE International Symposium on Industrial Electronics - Duración: 1 ene 2003 → …

Conferencia

Conferencia	IEEE International Symposium on Industrial Electronics
Período	1/01/03 → …

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10.1109/ISIE.2003.1267910

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AB - © 2003 IEEE. In this paper, a methodology for considering detection and treatment of faults in automated machines is introduced. This methodology is based on the integration of Petri nets for diagnosis (BPN) and Bayesian networks. After that, the integration among detection/treatment of faults and the "normal" processes (represented by Petri nets, PN) is possible. This integration allows us to develop a fault tolerant supervisor, which considers all the processes in the same structure. A case study of fault tolerant AGV is considered. Finally, a simulation tool for edition and analysis of models with these characteristics is introduced.

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