摘要
基于径向基函数神经网络,建立了大坝安全自动化监测的非线性故障自诊断系统。根据系统一步超前预报值与在线实测值的残差逻辑判决,对自动化监测系统的工作性能进行实时诊断。实例结果表明,基于RBF神经网络的大坝安全自动化监测故障自诊断系统能够较好地实现故障的在线诊断和实时隔离。
Based on the Radial Basis Function neural network,a kind of fault auto-diagnosis system of dam safety monitoring is established.According to the logic determination of the difference between the forcasting values and the measured values,the performance of the auto-monitoring system is diagnosised.Besides,an example is given.As a result,it shows that the auto-diagnosis system of dam safety monitoring based on RBF neural network can do a better work.
出处
《水电能源科学》
2004年第3期6-8,29,共4页
Water Resources and Power
基金
国家自然科学基金资助项目(50139030)
国家973项目基金资助(2002CB412707)
教育部夸世纪优秀人才培养计划基金资助项目(2003512643)。
关键词
大坝安全监测
故障诊断
神经网络
dam safety monitoring
fault diagnosis
neural network
