摘要
基于国内某300MW循环流化床锅炉的现场实验数据,对数据进行分析整理,并用神经网络辨识方法对主汽压模型进行系统辨识,得到主汽压的神经网络模型。所建立的模型基本上反映热工对象的实际运行状况;并对主汽压进行神经网络预测,仿真结果显示实际输出与预测值误差很小。
This paper is based on local data of a 300 MW circulating fluidized bed boiler at home, it analyses and coordinates the data, and using neural network to do system identification for the model of main steam pressure, then gains a neural network model of main steam pressure. The established model can basically reflect the actual operating status of thermal object; This paper also forecasts the main steam pressure using neural network, Simulation and operation results show that the error between actual output and forecast value is very small.
出处
《微计算机信息》
2011年第2期186-188,共3页
Control & Automation
关键词
循环流化床锅炉
神经网络
系统辨识
CFBB （Circulating Fluid Bed Boiler）
neural network
system identification
