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arXiv 1302.4936cs.AI
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具有定性可能性不确定性的实用模型诊断

Practical Model-Based Diagnosis with Qualitative Possibilistic Uncertainty

Matra Marconi Space(马特拉·马可尼空间公司);Universite Paul Sabatier(保尔·萨巴蒂埃大学);I.R.I.T.-C.N.R.S.(法国国家科学研究中心图卢兹信息研究所)

Didier Cayrac, Didier Dubois, Henri Prade

摘要:

提出了一种利用极不完整模型进行故障隔离的方法。它依赖于每个组件行为的单独描述,以及它们之间的联系,这使得推理能够集中到系统的相关部分。由于正常观测不需要解释,因此组件的行为仅限于异常传播。诊断解决方案是与观察结果一致的疾病(故障模式或异常特征),以及溯因解释。基于可能性理论的不确定性的有序表示提供了组件行为的简单的异常容忍描述。例如,我们可以区分在给定异常存在时或多或少肯定存在(或不存在)的效应和或多或少肯定存在(或不存在)的效应。一个现实的例子说明了这种方法的好处。

英文摘要:

An approach to fault isolation that exploits vastly incomplete models is presented. It relies on separate descriptions of each component behavior, together with the links between them, which enables focusing of the reasoning to the relevant part of the system. As normal observations do not need explanation, the behavior of the components is limited to anomaly propagation. Diagnostic solutions are disorders (fault modes or abnormal signatures) that are consistent with the observations, as well as abductive explanations. An ordinal representation of uncertainty based on possibility theory provides a simple exception-tolerant description of the component behaviors. We can for instance distinguish between effects that are more or less certainly present (or absent) and effects that are more or less certainly present (or absent) when a given anomaly is present. A realistic example illustrates the benefits of this approach.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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