集成员故障诊断的因果策略

S. Ploix, S. Gentil
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引用次数: 6

摘要

集隶属度故障检测是一种很有前途的方法,因为它考虑了建模不确定性和测量误差的先验知识。它包括与测量和模型的一致性测试。然而,要实现对复杂过程的故障诊断,必须设计周密的诊断策略。为了实现诊断程序,因果分析允许将一致性测试集中在简单模型上,从而减少了计算量。本文介绍了该技术在某核废料处理厂的应用。首先解释了提出的诊断因果策略。然后证明了集成员一致性测试。最后,给出了一个故障场景来启发该方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Causal strategy for set-membership fault diagnosis
Set-membership fault detection is a promising approach because it takes into account a priori knowledge on modelling uncertainties and measurement errors. It consists in coherency tests with measurements and models. However, a careful diagnostic strategy has to be designed in order to achieve fault diagnosis of complex processes. To achieve the diagnostic procedure, a causal analysis allows focusing the coherency tests on simple models, resulting in a decrease of the amount of computations. This paper presents an application to a nuclear waste treatment plant. The proposed causal strategy for diagnosis is explained first. The set-membership coherency tests are then justified. Finally, a fault scenario is presented in order to enlighten the method.
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