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Fault diagnosis based on deep knowledge model of signed directed graph in power plant thermal system
Author(s): CAO Wen-liang, WANG Bing-shu, MA Yong-guang, MA Liang-yu
Pages: 79-
83
Year: 2005
Issue:
5
Journal: JOURNAL OF NORTH CHINA ELECTRIC POWER UNIVERSITY
Keyword: 电站热力系统; 故障诊断; 符号有向图; 定性推理;
Abstract: 鉴于符号有向图(Signed Directed Graph,SDG)深层知识模型的推理方法是一种完备的揭示系统故障的有效方法,提出将基于SDG的方法应用于电站热力系统的故障诊断中.应用该方法首先建立了除氧器系统的SDG模型,然后根据各个故障根源得出系统的子SDG模型,最后根据这些子图导出除氧器的故障诊断规则库.诊断时,通过将系统变量的定量值转换为定性值,将实际故障工况与所建立的故障规则进行比较,得到故障源的定性诊断结果.案例研究表明,该方法具有较好的解释性和诊断的快速性,且能有效解决仿真培训过程中误操作自诊断问题.
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