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 conferenciaArtículo 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 originalInglés estadounidense
Páginas729-734
Número de páginas6
DOI
EstadoPublicada - 1 ene 2003
Publicado de forma externa
EventoIEEE International Symposium on Industrial Electronics -
Duración: 1 ene 2003 → …

Conferencia

ConferenciaIEEE International Symposium on Industrial Electronics
Período1/01/03 → …

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    Riascos, L. A. M., Cozman, F. G., & Miyagi, P. E. (2003). Detection and treatment of faults in automated machines based on Petri nets and Bayesian networks. 729-734. Papel presentado en IEEE International Symposium on Industrial Electronics, . https://doi.org/10.1109/ISIE.2003.1267910