Failure prognosis in discrete events systems based on extended Time petri nets: example of an electric car battery cell

Author(s):  
Redouane Kanazy ◽  
Samir Chafik ◽  
Eric Niel ◽  
Mohamed Zouagui
Author(s):  
Juan L. G. Guirao ◽  
Fernando L. Pelayo

This paper provides an overview over the relationship between Petri Nets and Discrete Event Systems as they have been proved as key factors in the cognitive processes of perception and memorization. In this sense, different aspects of encoding Petri Nets as Discrete Dynamical Systems that try to advance not only in the problem of reachability but also in the one of describing the periodicity of markings and their similarity, are revised. It is also provided a metric for the case of Non-bounded Petri Nets.


2003 ◽  
Vol 36 (13) ◽  
pp. 189-197 ◽  
Author(s):  
Didier Lime ◽  
Olivier H. Roux

Author(s):  
Juan L. G. Guirao ◽  
Fernando L. Pelayo

This paper provides an overview over the relationship between Petri Nets and Discrete Event Systems as they have been proved as key factors in the cognitive processes of perception and memorization. In this sense, different aspects of encoding Petri Nets as Discrete Dynamical Systems that try to advance not only in the problem of reachability but also in the one of describing the periodicity of markings and their similarity, are revised. It is also provided a metric for the case of Non-bounded Petri Nets.


SIMULATION ◽  
2017 ◽  
Vol 94 (8) ◽  
pp. 753-762 ◽  
Author(s):  
Fei Liu ◽  
Hongmei Zhang

Time Petri nets (TPNs) have been widely used for modeling discrete event systems such as manufacturing, supply chain, and military systems. However, TPNs still have many drawbacks in some scenarios where an operation or process is associated with probability, and also lack appropriate simulation algorithms for analyzing different types of systems. In this paper, we address these two issues by proposing a class of extended time Petri nets (ETPNs) and presenting an appropriate simulation algorithm. We illustrate and validate our approach using a hypothetic command and control system, which shows that this approach could be a powerful tool for modeling and analyzing discrete event systems.


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