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所属单位：自动化学院
发表刊物：JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
关键字：fault diagnosis partially observed Petri nets (POPNs) integer linear programming (ILP) generalized mutual exclusion constraints (GMECs)
摘要：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.
ISSN号：1004-4132
是否译文：否
发表时间：2017-10-01
合写作者：Liu, Wenliang,Zhou, Jianyong,孙艳,王志胜
通讯作者：刘久富