摘要
针对核动力装置故障状态下征兆参数呈现出的灰色特征,提出将灰色聚类分析模型用于核动力装置故障诊断,采用了两种方法构造聚类模型。其一,基于AB0型灰色关联度分析的聚类模型主要通过核动力装置待检序列与标准故障模式序列间的AB0型关联度排序来分析故障类型;其次是基于灰色白化权函数分析的聚类模型主要由核动力装置待检序列与标准故障模式序列间的聚类系数值分析故障类型。以蒸汽发生器典型故障为例,验证了灰色聚类分析方法用于核动力装置故障诊断的可行性。分析结果表明,灰色聚类分析建模简单,可以实现故障的准确诊断。
Because of the grey features of symptom parameters when nuclear power plant is in failure state,This paper brings forward grey cluster models for fault diagnosis in nuclear power plant.Two methods are introduced in this paper to structure the grey cluster models.One cluster model based on AB 0 type grey correlation can analysis the fault type by ranking the AB 0 type grey correlations between the collected sequences and standard fault pattern sequences,the another cluster model based on grey whitening weight function can confirm the fault type by calculating the grey cluster values between the collected sequences and standard fault pattern sequences.An example of the steam generator typical failures is introduced to verify the feasibility of grey cluster analysis method for fault diagnosis in nuclear power plant.The results show that the grey cluster method has the advantages of simple model and reliable fault diagnosis results.
作者
宋辉
陆古兵
王飞
SONG Hui;LU Gubing;WANG Fei(Research Institute of Nucalear Power Operation.CNNC,Wuhan of Hubei Prov.430223;China Nuclear Science andEngineering College Naval Univ.of Engineering,Wuhan of Hubei Prov.430033,China;Zhe Jiang ThermalPower Construction Co.Ltd.CEEC,Hangzhou of Zhejiang Prov.310000,China)
出处
《核科学与工程》
CAS
CSCD
北大核心
2019年第1期139-145,共7页
Nuclear Science and Engineering
关键词
灰色聚类
核动力装置
蒸汽发生器
故障诊断
grey cluster
nuclear power plant
steam generator,fault diagnosis