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A new methodology based on fuzzy set theory and fault tree analysis for failure diagnosis in nuclear power plants.

机译:基于模糊集理论和故障树分析的核电站故障诊断新方法。

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摘要

A new methodology based on the fuzzy set theory and fault tree analysis techniques has been developed to be used as a fuzzy diagnostic technique for failure recognition of nuclear power plant systems. The methodology utilizes important signs of trouble that may be detected through the perception of a human operator, e.g., smell, noise, leakages, vibrations, or any unusual behavior, as sources of fuzzy information for diagnosis of abnormal states of system components through the solution of the "Inverse Problem of Fuzzy Relational Equations (IPFRE)". The new methodology has generalized the Tsukamoto and Terano's algorithm for solving the IPFRE from dealing with ordinary fuzzy sets of type 1 with crisply defined grades of membership to fuzzy sets of type 2 whose grades of membership themselves are fuzzy sets represented by fuzzy numbers. This generalization solves the situations when ill-defined grades of membership are encountered, allows more fuzziness in the system to be appropriately treated, and enables the grades of membership to be specified in linguistic terms and mathematically treated.; The new methodology utilizes the well established techniques of fault tree analysis as powerful tools to identify the kind and level of possible failures and causal symptoms of the systems which are described by means of fault trees. A technique based on both the probability theory and fuzzy set theory for the computation of fuzziness propagation in Fault Tree Analysis (FTA) is developed to utilize the available probabilistic description of the basic events of the fault trees. In this technique, a normalization procedure is suggested to transform the probability distributions expressing the occurrences of the basic events to fuzzy numbers expressing the fuzzy probability of failures of the basic events.; The fuzzy diagnostic technique has been tested and applied to a nuclear power plant system described by means of fault trees using a computer code FUZYDIAG (Fuzzy Diagnosis) which has been developed in the C-language. Results show the feasibility of using the developed fuzzy diagnostic technique for failure recognition of nuclear power plant systems. The technique is general and can be applied to other types of plant systems.
机译:已经开发了一种基于模糊集理论和故障树分析技术的新方法,作为核电站系统故障识别的模糊诊断技术。该方法利用可通过操作员的感知来检测到的故障的重要标志,例如气味,噪音,泄漏,振动或任何异常行为,作为模糊信息的来源,用于通过解决方案诊断系统组件的异常状态“模糊关系方程的反问题(IPFRE)”。新方法将Tsukamoto和Terano的算法泛化为解决IPFRE,从处理具有明确定义的隶属度的类型1的普通模糊集到拥有隶属度本身是由模糊数表示的模糊集的类型2的模糊集。这种概括解决了遇到会员资格等级定义不明确的情况,允许对系统中的更多模糊性进行适当处理,并使会员资格等级可以用语言术语指定并进行数学处理。新的方法论利用故障树分析的完善技术作为强大的工具,以识别通过故障树描述的系统的可能故障和因果症状的种类和级别。为了利用故障树基本事件的可用概率描述,开发了一种基于概率论和模糊集理论的故障树分析(FTA)中的模糊传播计算技术。在该技术中,建议使用规范化过程将表示基本事件发生的概率分布转换为表示基本事件失败的模糊概率的模糊数。模糊诊断技术已经过测试,并已应用到使用故障诊断树描述的核电站系统中,该故障树使用了C语言开发的计算机代码FUZYDIAG(模糊诊断)。结果表明,使用开发的模糊诊断技术进行核电站系统故障识别的可行性。该技术是通用的,可以应用于其他类型的工厂系统。

著录项

  • 作者

    Abdelhai, Mohamed Ibrahim.;

  • 作者单位

    The University of Tennessee.;

  • 授予单位 The University of Tennessee.;
  • 学科 Engineering Nuclear.
  • 学位 Ph.D.
  • 年度 1993
  • 页码 185 p.
  • 总页数 185
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 原子能技术;
  • 关键词

  • 入库时间 2022-08-17 11:50:01

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