原子能科学技术Issue(11)：2103-2107,5.DOI:10.7538/yzk.2013.47.11.2103
基于RBF神经网络的NPP运行状态趋势预测
Trend Prediction of NPP Operating Conditions Based on RBF Neural Network
张黎明 1蔡琦 1宋梅村1
作者信息
- 1. 海军工程大学 核能科学与工程系，湖北 武汉 430033
- 折叠
摘要
Abstract
Considering that the fault diagnosis of nuclear power plant (NPP) adopting the traditional threshold way can hardly realize early warning ,the prediction model according to the variation trend of state parameter and making use of the good local characteristic of RBF neural network for predicting the trend of NPP operating conditions was introduced . The operating condition trends under the normal transition and the small-break loss-of-coolant accident were predicted . The results show that RBF neural network can predict the parameter’s change and the predicted value matches with the real value .关键词
核动力装置/运行状态/RBF神经网络/趋势预测Key words
nuclear pow er plant/operating condition/RBF neural netw ork/trend prediction分类
能源科技引用本文复制引用
张黎明,蔡琦,宋梅村..基于RBF神经网络的NPP运行状态趋势预测[J].原子能科学技术,2013,(11):2103-2107,5.
