Improved design of online fault diagnoser for partially observed Petri nets with generalized mutual exclusion constraints

This paper investigates the fault detection problem for discrete event systems (DESs) which can be modeled by partially observed Petri nets (POPNs). To overcome the problem of low diagnosability in the POPN online fault diagnoser in current use, an improved online fault diagnosis algorithm that inte...

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Published in:Journal of systems engineering and electronics 2017-10, Vol.28 (5), p.971-978
Main Authors: Liu, Jiufu, Liu, Wenliang Liu, Zhou, Jianyong, Sun, Yan, Wang, Zhisheng
Format: Article
Language:English
Subjects:
(ILP)
generalized
(POPNs)
integer
constraints
diagnosis
partially
exclusion
fault
GMECs
linear
mutual
nets
observed
Petri
programming
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container_end_page 978
container_issue 5
container_start_page 971
container_title Journal of systems engineering and electronics
container_volume 28
creator Liu, Jiufu
Liu, Wenliang Liu
Zhou, Jianyong
Sun, Yan
Wang, Zhisheng
description This paper investigates the fault detection problem for discrete event systems (DESs) which can be modeled by partially observed Petri nets (POPNs). To overcome the problem of low diagnosability in the POPN online fault diagnoser in current use, an improved online fault diagnosis algorithm that integrates generalized mutual exclusion constraints (GMECs) and integer linear programming (ILP) is proposed. Assume that the POPN structure and its initial markings are known, and the faults are modeled as unobservable transitions. First, the event sequence is observed and recorded. GMEC is used for elementary diagnosis of the system behavior, then the ILP problem of POPN is solved for further diagnosis. Finally, an example of a real DES to test the new fault diagnoser is analyzed. The proposed algorithm increases the diagnosability of the DES remarkably, and the effectiveness of the new algorithm integrating GMEC and ILP is verified.
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To overcome the problem of low diagnosability in the POPN online fault diagnoser in current use, an improved online fault diagnosis algorithm that integrates generalized mutual exclusion constraints (GMECs) and integer linear programming (ILP) is proposed. Assume that the POPN structure and its initial markings are known, and the faults are modeled as unobservable transitions. First, the event sequence is observed and recorded. GMEC is used for elementary diagnosis of the system behavior, then the ILP problem of POPN is solved for further diagnosis. Finally, an example of a real DES to test the new fault diagnoser is analyzed. The proposed algorithm increases the diagnosability of the DES remarkably, and the effectiveness of the new algorithm integrating GMEC and ILP is verified.</abstract><pub>College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China</pub><doi>10.21629/JSEE.2017.05.15</doi><tpages>8</tpages></addata></record>
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subjects (ILP)
generalized
(POPNs)
integer
constraints
diagnosis
partially
exclusion
fault
GMECs
linear
mutual
nets
observed
Petri
programming
title Improved design of online fault diagnoser for partially observed Petri nets with generalized mutual exclusion constraints
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