反应堆补水系统诊断贝叶斯网络的建立和应用

Constitution and Application of Reactor Make-up System’s Fault Diagnostic Bayesian Networks

  • 摘要: 建立了补水系统贝叶斯故障诊断网络。在结合补水系统结构特点、运行规程和专家经验的基础上构建了初始诊断贝叶斯网络,运用基于微粒群优化的贝叶斯网络学习算法学习故障数据集,进一步构建完整网络,并进行推理分析。所建网络能有效分析和更新系统中各节点故障概率,为故障诊断提供辅助决策。

     

    Abstract: A fault diagnostic Bayesian network of reactor make-up system was constituted. The system’s structure characters, operation rules and experts’ experience were combined and an initial net was built. As the fault date sets were learned with the particle swarm optimization based Bayesian network structure, the structure of diagnostic net was completed and used to inference case. The built net can analyze diagnostic probability of every node in the net and afford assistant decision to fault diagnosis.

     

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