江苏理工大学学报(自然科学版)2001，Vol.23Issue(2)：26-28,3.
化工过程动态监控中的RBF神经网络方法研究
A Study on the RBF Neural Network Method Used for the Dynamic Monitoring of Chemical Processes
摘要
Abstract
Predicating the developing trends of a process and monitoring it on the basis of the analysis of measured data has long been a subject drawing wide attention of scholars at home and abroad.Considering the high training speed of RBF neural networks,a method based on a two-stage RBF neural network is proposed for the dynamic monitoring of chemical processes. The first stage is used to predicate the future variable values in the coming time, the second is used to forecast the faults.For the purpose of achieving reliable monitoring effects with limited samples, some measures are proposed to improve the interoperation performance of the RBF neural network, together with a transformation acting on the output of the second stage to determine the possibilities of the faults more accurately. They were applied to the dynamic monitoring for a distillation tower. The results showed a great success.关键词
动态监控/神经网络/预测/诊断分类
信息技术与安全科学引用本文复制引用
薛国新,史国栋,王其红,王洪元..化工过程动态监控中的RBF神经网络方法研究[J].江苏理工大学学报(自然科学版),2001,23(2):26-28,3.
