首页 | 本学科首页   官方微博 | 高级检索  
     

基于信号时频特征对金属跌落零件的报警方法
引用本文:毛汉领,黄振峰.基于信号时频特征对金属跌落零件的报警方法[J].机械强度,1997,19(4):6-9,12.
作者姓名:毛汉领  黄振峰
作者单位:[1]广西大学机械工程系 [2]浙江大学机械工程系
摘    要:针对核电站一回路系统中检测金属跌落零件误报警率高的问题,提出了基于信号时频域二维特征的神经网络报警方法。用改进的BP算法对模拟跌落零件试验的结果进行了处理,表明该报警方法是可行的。

关 键 词:核电站  报警  神经网络  跌落零件  监测  时频

THE ALARM METHOD ABOUT FALLING PARTS IN NUCLEAR POWER STATION BASED ON SIGNAL TIME FREQUENCY CHARACTERISTICS
Mao Hanling,Huang Zhengfeng,Chen Zhongyi.THE ALARM METHOD ABOUT FALLING PARTS IN NUCLEAR POWER STATION BASED ON SIGNAL TIME FREQUENCY CHARACTERISTICS[J].Journal of Mechanical Strength,1997,19(4):6-9,12.
Authors:Mao Hanling  Huang Zhengfeng  Chen Zhongyi
Affiliation:Mao Hanling Huang Zhengfeng Chen Zhongyi Department of Mechanical EngineeringGuangxi University,Nanning 530004,China Department of Mechanical EngineeringZhejiang University,Hangzhou 310027,China
Abstract:On the problem of alarm when parts are falling down in the nuclear power station,the Artificial Neural Network(ANN) method has been firts applied in realizing the alarm of falling parts based on the time frequency characteristics of impact signal.The data from experiments justify the method.
Keywords:nuclear power station  alarm  artificial neural network  
本文献已被 CNKI 维普 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