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。
A fault diagnostic Bayesian network of reactor make-up system was constitu-ted .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 parti-cle swarm optimization based Bayesian network structure ,the structure of diagnostic net was completed and used to inference case .The built net can analyze diagnostic prob-ability of every node in the net and afford assistant decision to fault diagnosis .
出处
《原子能科学技术》
EI
CAS
CSCD
北大核心
2013年第10期1840-1844,共5页
Atomic Energy Science and Technology
关键词
补水系统
故障诊断
贝叶斯网络
微粒群优化
不确定性
make-up system
fault diagnosis
Bayesian network
particle swarm optimization
non-determinism
