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Petri net

About: Petri net is a research topic. Over the lifetime, 25039 publications have been published within this topic receiving 406994 citations.


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TL;DR: A technique is presented whereby queueing network models and generalized stochastic Petri nets are combined in such a way as to exploit the best features of both modeling techniques, and the resulting hierarchical modeling approach is useful in the solution of complex models of system behavior.
Abstract: A technique is presented whereby queueing network models and generalized stochastic Petri nets are combined in such a way as to exploit the best features of both modeling techniques. The resulting hierarchical modeling approach is useful in the solution of complex models of system behavior. The authors have chosen two examples from the recent literature to illustrate the power and scope of this technique. They also demonstrate how folding of the generalized stochastic Petri net models for these two examples is useful in obtaining efficiently solvable, approximate models (bounding models). >

123 citations

Journal Article
TL;DR: It is argued that appreciated tools from biochemistry and also low-level Petri nets can yield only part of the desired results, whereas executable high-level net models lead to a number of valuable additional insights by combining symbolic analysis and simulation.
Abstract: Computer assisted analysis and simulation of biochemical pathways can improve the understanding of the structure and the dynamics of cell processes considerably The construction and quantitative analysis of kinetic models is often impeded by the lack of reliable data However, as the topological structure of biochemical systems can be regarded to remain constant in time, a qualitative analysis of a pathway model was shown to be quite promising as it can render a lot of useful knowledge, e g, about its structural invariants The topic of this paper are pathways whose substances have reached a dynamic concentration equilibrium (steady state) It is argued that appreciated tools from biochemistry and also low-level Petri nets can yield only part of the desired results, whereas executable high-level net models lead to a number of valuable additional insights by combining symbolic analysis and simulation

123 citations

Journal ArticleDOI
TL;DR: A failure prediction method for PM by state estimation using the Kalman filter is presented, which can achieve early failure detection and isolation for fault diagnosis but also facilitates event count, system state description, and automatic shutdown or regulation.
Abstract: Preventive maintenance (PM) is an effective approach for reliability enhancement. Time-based and condition-based maintenance are two major approaches for PM. In contrast, condition-based maintenance can be a better and more cost-effective type of maintenance than time-based maintenance. However, irrespective of the approach adopted for PM, whether a failure can be detected early or even predicted is the key point. This paper presents a failure prediction method for PM by state estimation using the Kalman filter. To improve preventive maintenance, this study uses a hybrid Petri-net modeling method coupled with fault-tree analysis and Kalman filtering to perform failure prediction and processing. A Petri net arrangement, viz, early failure detection and isolation arrangement (EFDIA), is used; it facilitates alarm, early failure detection, fault isolation, event count, system-state description, and automatic shutdown or regulation. These functions are very useful for health-monitoring and preventive-maintenance of a system. This study implements EFDIA to an application-specific integrated circuit on a Xilinx Demonstration Board. A condition-monitoring system of a thermal power plant is used as an example to demonstrate the proposed scheme. Linking the Kalman filter to the EFDIA Petri net, a condition-based failure prediction and processing scheme has been completed for preventive maintenance. This paper presents a failure prediction and processing scheme for PM via the thermal power-plant example, by using a hybrid Petri net modeling method endowed with fault-tree analysis and Kalman filtering. The FPN (Petri net dealing with system failure) has to be constructed beforehand. The next step is to obtain control charts for all fault places in the FPN in order to prescribe thresholds and increment times for every step in Kalman prediction. Afterwards, the system model of each place in the FPN must be derived to perform Kalman filtering. With these prerequisites, this method can be applied to any system. The proposed Petri net approach not only can achieve early failure detection and isolation for fault diagnosis but also facilitates event count, system state description, and automatic shutdown or regulation. These capabilities are very useful for health monitoring and PM of a system. Since the triggering signal of S/sub i/ place of the EFDIA in Section IV (S/sub i/ is a place for the Kalman-predicted indicator value of the sensing signal for the Petri net dealing with system failure) indicates that subsystem #i performance is going to reach the prescribed failure threshold, the signal can be provided via the Kalman filtering method in Section III. Linking the Kalman filter to the EFDIA Petri net, a condition-based failure prediction and processing scheme has been completed for preventive maintenance.

123 citations

Journal ArticleDOI
TL;DR: This article is an extended version of the paper with same title, which appeared as a plenary address in the Proceedings of CONCUR’2003, which relies on Petri net unfoldings and event structures, as means to manipulate trajectories of systems with concurrency.
Abstract: In this paper we study the diagnosis of distributed asynchronous systems with concurrency. Diagnosis is performed by a peer-to-peer distributed architecture of supervisors. Our approach relies on Petri net unfoldings and event structures, as means to manipulate trajectories of systems with concurrency. This article is an extended version of the paper with same title, which appeared as a plenary address in the Proceedings of CONCUR?2003.

123 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023290
2022662
2021466
2020574
2019651
2018751