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

Author

Riascos, Luis A M ; Cozman, Fabio G. ; Miyagi, Paulo E.

Author_Institution

Sch. of Polytech, Sao Paulo Univ., Brazil

Volume

2

fYear

2003

fDate

9-11 June 2003

Firstpage

729

Abstract

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.

Keywords

Petri nets; automatic guided vehicles; belief networks; fault diagnosis; fault tolerance; Bayesian networks; Petri nets; automated guided machine; automated machines; fault detection; fault tolerant supervisor; fault treatment; Automation; Bayesian methods; Data mining; Fault detection; Fault diagnosis; Fault tolerance; Intelligent networks; Mathematical model; Petri nets; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 2003. ISIE '03. 2003 IEEE International Symposium on

Print_ISBN

0-7803-7912-8

Type

conf

DOI

10.1109/ISIE.2003.1267910

Filename

1267910