首页 | 本学科首页   官方微博 | 高级检索  
     

基于模糊模式识别的凝汽器故障诊断研究
引用本文:卢绪祥,李录平,李邵霞,陈前军,周可. 基于模糊模式识别的凝汽器故障诊断研究[J]. 电工标准与质量, 2000, 0(3)
作者姓名:卢绪祥  李录平  李邵霞  陈前军  周可
作者单位:长沙电力学院动力工程系!湖南长沙410077(卢绪祥,李录平,陈前军,周可),长沙电力学校动力系!湖南长沙410131(李邵霞)
基金项目:湖南省科委资助项目 !( 1 997 2 90 )
摘    要:分析了凝汽器工作过程及故障机理 ,建立了凝汽器典型故障集、征兆集及典型故障特征向量集合 .应用模糊模式识别方法及最大隶属原则 ,建立了凝汽器故障诊断模型 ,并以实例验证该模型识别故障的准确性 .实践证明 ,该模型简单实用 ,能有效地识别凝汽器故障

关 键 词:凝汽器  故障诊断  模糊模式识别  最大隶属原则

Study of Fault Diagnosis for Condenser Based on Fuzzy Pattern Recognition
LU Xu xiang , LI Lu ping , LI Shao xia , CHEN Qian jun , ZHOU Ke. Study of Fault Diagnosis for Condenser Based on Fuzzy Pattern Recognition[J]. Journal of Changsha University of Electric Power(Natural Science Edition), 2000, 0(3)
Authors:LU Xu xiang    LI Lu ping    LI Shao xia    CHEN Qian jun    ZHOU Ke
Affiliation:LU Xu xiang 1, LI Lu ping 1, LI Shao xia 2, CHEN Qian jun 1, ZHOU Ke 1
Abstract:Condenser's working process and fault mechanism are analyzed and its typical fault concourses,symptom concourses & typical fault feature vectors are established.By applying fuzzy pattern recognition and maximum membership rule,fault diagnosis model for condenser has been established and its accuracy for identifying faults is tested and verified.The practice shows that the model is simple and practical,therefore the faults of condenser can be effectively identified by using it.
Keywords:condenser  fault diagnosis  fuzzy pattern recognition  maximum membership rule
本文献已被 CNKI 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号