摘要
对核动力装置进行状态监测与诊断的层次、步骤、系统结构进行了阐述,并结合专家知识对核动力装置典型故障建立了故障知识库;在此基础上,将径向基函数(RBF)人工神经网络引入到核动力装置故障诊断中,使其与模糊神经网络(FNN)进行邦联,提高了神经网络的诊断速度和准确性.用Visual Basic 6.0编制了系统程序.该系统对典型故障进行了诊断,得到了预期的效果.
This paper expatiates the levels, process and architecture of the status monitoring and fault diagnosis of the NPP （ nuclear power plant）. Meanwhile, a fault knowledge base for the typical faults of the NPP is founded by the expert knowledge. On the basis of these works, in order to improve the diagnosis speed and accuracy of the neural network, the RBF （radial basis function） neural network and FNN （fuzzy neural network） are confedera- ted. Moreover, Visual Basic 6.0 is chosen to program the diagnosis system. The results of diagnosing the model faults by this system are satisfactory.
出处
《应用科技》
CAS
2007年第5期46-49,共4页
Applied Science and Technology
