计算机科学 ›› 2012, Vol. 39 ›› Issue (8): 210-214.

• 人工智能 • 上一篇    下一篇

基于时序的离散事件系统的可诊断性

李占山,陈 超,叶寒锋   

  1. (吉林大学符号计算与知识工程教育部重点实验室 长春130012);(吉林大学计算机科学与技术学院 长春130012)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Diagnosability of Discrete-event Systems Based on Temporal

  • Online:2018-11-16 Published:2018-11-16

摘要: 提出一种基于事件之间的时序关系判定可诊断性的方法。首先通过添加通讯事件把全局模型分解成几个局部模型来缩减模型的规模,删除局部模型中的无用路径以降低状态空间;其次利用通讯事件和可观测事件之间的时序关系,对受限局部模型的可诊断性进行判定,得出几个判定性质,然后把这些性质运用到局部模型的可诊断性判定中,以避免同步操作的高复杂性;最后通过实例对可诊断性判定的过程进行分析。

关键词: 模型分解,受限局部模型,可诊断性

Abstract: This paper proposed a new diagnosis approach based on the temporal relationship between events. In order to reduce the scale of the model, we first added some communication events to divide the global model. Then we deleted some useless road in the local models to reduce the space of states. According to the temporal relationship between communication events and observable events, we could get the diagnosability of the limited model and some properties. We used the properties to get the diagnosability of the local models, which avoids the high complexity of the synchronization operation. Finally we gave some examples to analysis the steps of the diagnosed process.

Key words: Model decomposition,Limited local modcl,Diagnosability

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