基于SDG-QTA的核动力装置故障诊断技术研究

Research on Fault Diagnosis Based on SDG-QTA in Nuclear Power Plant

  • 摘要: 通过对核动力装置进行在线状态监测与故障诊断研究,帮助操作人员及时了解核动力装置的运行状态和事故进程,有助于操作人员进行正确操作,防止事故进一步恶化。符号有向图(SDG)能很好地展示出复杂系统变量之间的关系,同时具有建立模型简单、推理灵活等优点。本文采用SDG对核动力装置进行故障诊断研究。首先,将定性趋势分析(QTA)和阈值法结合对核动力装置进行状态监测。然后,采用SDG对核动力装置进行故障诊断,并通过SDG模型给出故障的传播路径。最后,以核电厂二回路典型故障为例,建立其SDG模型,并通过仿真机对该方法进行验证。

     

    Abstract: Research on online process monitoring and fault diagnosis (FD) in nuclear power plants (NPPs) helps operator timely know the state of system and do accurate operation in case of accident deterioration. The signed directed graph (SDG) can show the complex relationship between parameters and has advantages of establishing model conveniently, flexible inference and so on. So the SDG was adopted for FD in the paper. Firstly, the combination of qualitative trend analysis (QTA) and threshold was applied to process monitoring. Secondly, the SDG was utilized for FD and revealed the fault propagation path. Finally, the SDG model of the secondary-loop system in NPPs was built to verify the proposed method by simulator in the paper.

     

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