A novel analytical framework for qualitative Model-Based Fault Diagnosis

S. Baniardalani, J. Askari, A. Afzalian
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引用次数: 8

Abstract

This paper presents a unified analytical framework for qualitative Model-Based Fault Diagnosis (MBFD), similar to the quantitative MBFD. Dioid Algebra is used in addition to ordinary Algebra for simulation qualitative models. The framework is illustrated and adapted in details for three main qualitative diagnostic methods which employ Stochastic, Non-Deterministic, and Timed Automata, respectively. Using the proposed methodology, we are able to compute quantitative residuals for qualitative models. Therefore some useful and practical computational tasks can be carried out on the obtained residuals. One of the main contributions of the paper is introducing a new approach to qualitative structured residual generation, which is applied to timed automata models.
基于模型的定性故障诊断分析框架
本文提出了一种统一的定性基于模型的故障诊断(MBFD)分析框架,类似于定量的MBFD。除了普通代数外,还使用二类代数来模拟定性模型。该框架详细说明了三种主要的定性诊断方法,分别采用随机、非确定性和时间自动机。使用提出的方法,我们能够计算定性模型的定量残差。因此,可以对得到的残差进行一些实用的计算任务。本文的主要贡献之一是引入了一种新的定性结构化残差生成方法,并将其应用于时间自动机模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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