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随着我国核能应用规模的扩大,核电厂安全成为核能发展中的重要研究课题;为了保障核电厂的安全运行,国内外提出了各种方法对核电厂进行状态监测、故障诊断和故障预报。符号有向图(SDG)能够简洁有效地对各种故障模式进行描述,并且在解释故障传播路径方面有一定优势,但存在节点阈值确定困难的问题,为此提出结合主元分析(PCA)与符号有向图进行研究,PCA通过分析残差检测故障的发生,然后SDG对PCA得到的残差确定节点状态,进行推理,得出故障的类型。通过模拟器PCTRAN的数据测试,验证该方法能及时准确地检测到故障并诊断出故障的类型。
With the expansion of the application of nuclear energy in our country, nuclear power plant safety has become an important research topic in the development of nuclear power. In order to ensure the safe operation of nuclear power plants, various methods have been proposed to monitor the status, diagnose and predict the failure of nuclear power plants. The Symbol Directed Graph (SDG) can describe various fault modes concisely and effectively and has certain advantages in explaining the fault propagation path. However, there is a problem that the node threshold is difficult to be determined. In this paper, Symbolic digraph, PCA analyzes the residuals and detects the occurrence of faults. SDG then determines the states of the residuals obtained by PCA and deduces the types of faults. Through the data test of simulator PCTRAN, it is verified that this method can detect the fault in time and accurately and diagnose the type of fault.