DocumentCode :
2662033
Title :
Detection and diagnosis of hybrid dynamic systems based on time fuzzy Petri nets
Author :
Loures, Eduardo Rocha ; Pascal, Jean-Claude
Author_Institution :
Lab. for Anal. & Archit. of Syst., CNRS, Toulouse, France
Volume :
2
fYear :
2004
fDate :
10-13 Oct. 2004
Firstpage :
1825
Abstract :
This paper presents a detection and diagnosis method based on a qualitative model of the process. Starting from an identification process a fuzzy partitioning of the variables evolution is made, defining for each measured variable a number of qualitative states. Then time fuzzy intervals representing the moment of state change are defined. The process behaviour is represented by time fuzzy Petri nets (TFPN). The evolution of the model is the consequence of events detection due to the partitioning bounds crossing. According to the membership possibility of an event to the estimated time interval it is possible to reason about a fault occurrence. The fuzzy data issue from the TFPN components allows evaluating the causes of the fault - the diagnosis.
Keywords :
Petri nets; fault diagnosis; identification; process control; detection method; diagnosis method; fault occurrence; hybrid dynamic system; identification process; qualitative model; time fuzzy Petri nets; Automata; Equations; Fault detection; Fuzzy control; Fuzzy systems; Mathematical model; Monitoring; Petri nets; Production systems; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-8566-7
Type :
conf
DOI :
10.1109/ICSMC.2004.1399920
Filename :
1399920
Link To Document :
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