摘要
针对核动力屏蔽泵运行过程中出现的典型故障类型,本文研究了基于随机森林的诊断方法原理与实现过程,通过故障模拟试验获得了屏蔽泵故障状态振动信号数据。在此基础上进行了特征量提取与分析研究,然后采用随机森林算法对部分特征量样例数据进行分析建立了屏蔽泵故障诊断模型,最后利用剩余部分样例数据对诊断模型进行了验证,结果表明基于随机森林的屏蔽泵故障诊断方法性能良好。
For the typical faults that happened during the operation of canned motor pump in nuclear power system,the principle and implementation process of the diagnosis method based on random forests were studied in this paper,and the vibration signal data that characterize the faults of canned motor pump were obtained through the faults simulation test.On the basis of the above,first of all,the vibration features extraction and analysis were carried out,and then the faults diagnosis model for canned motor pump was established by using random forests algorithm to learn the part of the sample data.Finally,the diagnostic model was validated by using the remaining sample data,and the results showed that the fault diagnosis method based on random forests was good.
作者
段智勇
刘才学
艾琼
何攀
DUANG Zhiyong;LIU Caixue;AI Qiong;HE Pan(Nuclear Power Institute of China,Chengdu of Sichuan Prov.610213,China)
出处
《核科学与工程》
CAS
CSCD
北大核心
2020年第4期625-630,共6页
Nuclear Science and Engineering
关键词
屏蔽泵
振动信号
故障诊断
随机森林
Canned Motor Pump
Vibration Signal
Fault Diagnosis
Random Forests
