摘要
提出了采用BP神经网络和RBF神经网络对锅炉过热器和再热器壁温进行预测的方法,经过网络训练和测试,使预测的管壁温度有一定的准确度。RBF神经网络较BP神经网络误差更小,更稳定,更适合于预测锅炉过热器和再热器的管壁温度。
A prediction method for tube- wall temperature in superheater and reheater of boilers, which adopts BP neural network and RBF neural network,has been put forward,through training and testing of the neural networks, making the above - mentioned prediction method to have certain accuracy. Comparatively speaking,the error of RBF neural network is more smaller than that of BP neural net- work,the work of RBF neural network is more stable, and is mroe suitable to predict the tube - wall temperature in superheater and reheater of boilers.
出处
《热力发电》
CAS
北大核心
2012年第5期22-26,共5页
Thermal Power Generation
关键词
锅炉
过热器
再热器
神经网络
壁温
预测
superheater
reheater
tube - burst
neural network
wall temperature
prediction
作者简介
E- mail： suyaolei0309@sina, com
