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首页> 外文期刊>Journal of Process Control >Functional diagnosability and detectability of nonlinear models based on analytical redundancy relations
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Functional diagnosability and detectability of nonlinear models based on analytical redundancy relations

机译:基于解析冗余关系的非线性模型的功能可诊断性和可检测性

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This paper introduces an original definition of diagnosability for nonlinear dynamical models called functional diagnosabillty. Fault diagnosability characterizes the faults that can be discriminated using the available sensors in a system. The functional diagnosability definition proposed in this paper is based on analytical redundancy relations obtained from differential algebra tools. Contrary to classical definitions, the study of functional diagnosability highlights some of the analytical redundancy relations properties related to the fault acting on the system. Additionally, it gives a criterion for detecting the faults. Interestingly, the proposed diagnosability definition is closely linked to the notion of identifiability, which establishes an unambiguous mapping between the parameters and the output trajectories of a model. This link allows us to provide a sufficient condition for testing functional diagnosability of a system. Numerical simulations attest the relevance of the suggested approach. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文介绍了非线性动力学模型的可诊断性的原始定义,称为功能诊断。故障可诊断性表征了可以使用系统中的可用传感器进行区分的故障。本文提出的功能可诊断性定义基于从微分代数工具获得的解析冗余关系。与经典定义相反,对功能可诊断性的研究强调了与作用在系统上的故障有关的一些分析冗余关系性质。另外,它提供了检测故障的标准。有趣的是,提出的可诊断性定义与可识别性概念紧密相关,可识别性在模型的参数和输出轨迹之间建立了明确的映射。此链接使我们能够为测试系统的功能可诊断性提供充分的条件。数值模拟证明了所建议方法的相关性。 (C)2015 Elsevier Ltd.保留所有权利。

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