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

Research output: Contribution to conferenceConference Paper

8 Scopus citations

Abstract

© 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.
Original languageAmerican English
Pages729-734
Number of pages6
DOIs
StatePublished - 1 Jan 2003
Externally publishedYes
EventIEEE International Symposium on Industrial Electronics -
Duration: 1 Jan 2003 → …

Conference

ConferenceIEEE International Symposium on Industrial Electronics
Period1/01/03 → …

Fingerprint Dive into the research topics of 'Detection and treatment of faults in automated machines based on Petri nets and Bayesian networks'. Together they form a unique fingerprint.

Cite this