摘要
自美国三哩岛核电站事故以来,故障诊断在核电站中的作用越来越被重视。为探索故障诊断在我国核电站中的应用,介绍了应用于复杂系统不确定性行为的智能故障诊断方法——动态不确定因果图(DUCG)。文中模型以中国广核集团有限公司宁德1号核电机组为原型构建,并利用与此机组对应的核电模拟机数据进行验证,保证了验证的有效性。验证结果表明,采用DUCG方法,能准确对核电站的典型故障进行识别和诊断,展现故障的发展过程,得到引发故障的原因事件和相应概率。
Since the Three Mile Island Nuclear Power Plant accident happened in U.S.,the role of fault diagnosis in nuclear power plants has been gotten more attention.To explore the fault diagnosis of nuclear power plants in China,the intelligent fault diagnosis method named DUCG(dynamic uncertain causality graph)was described,which can be applied to a complex system of uncertainty.A model based on Unit 1of Ningde Nuclear Power Plant,CGNPC(China Guangdong Nuclear Power Group)was established and the model was validated by the corresponding simulator,ensuring the validation of effectiveness.Validation results show that the DUCG method can accurately identify the typical nuclear power plant faults and can also show the development process of faults,successfully getting what caused the failure event and the corresponding probabilities.
出处
《原子能科学技术》
EI
CAS
CSCD
北大核心
2014年第S1期496-501,共6页
Atomic Energy Science and Technology
基金
国家自然科学基金资助项目(61273330
61402266)
