基于因果时间特征方法的离散事件系统在线诊断多智能体体系结构

R. Saddem, F. Ben Hmida
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引用次数: 0

摘要

工业环境正变得越来越动态、复杂和不确定。在这种情况下,建立安全系统是一个主要的要求和巨大的挑战,没有合适的诊断工具和方法是无法实现的。早期诊断方法大多集中在线下进行。证明了分布对实现复杂工业系统更好的诊断有很大的贡献。本文以离散事件系统(DES)为研究对象,介绍了一种基于因果时序特征(CTS)的分布式故障在线诊断方法。提出的解决方案依赖于多智能体体系结构,其中多个自主智能体在诊断过程中相互合作和协调其动作。
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Multiagent architecture for online diagnosis of discrete event systems using causal temporal signature approach
Industrial environments are becoming more and more dynamic, complex, and uncertain. In such conditions, building safe systems is a major requirement and a big challenge which cannot be achieved without suitable diagnosis tools and methods. The early diagnosis approaches were mostly centralized and done offline. It was then proved that distribution is of a great contribution to realize better diagnosis of complex industrial systems. This paper focuses on Discrete Event Systems (DES) and introduces a distributed approach for online faults diagnosis in DES using Causal Temporal Signatures (CTS). The proposed solution relies on a multiagent architecture where multiple autonomous agents cooperate and coordinate their actions in the diagnosis process.
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