热力发电Issue(4)：106-111,119,7.DOI:10.3969/j.issn.1002-3364.2015.04.106
改进BP神经网络在低氮燃烧优化中的应用
Application of modified BP neural network in optimization of low NOx combustion for a pulverized coal boiler
陆军 1张广才 1徐党旗 1周平 1周飞1
作者信息
- 1. 西安热工研究院有限公司，陕西 西安 710032
- 折叠
摘要
Abstract
On the basis of field test data during optimization of low NOx combustion for a pulverized coal boiler,a modified BP neural network for prediction of NOx emission and boiler efficiency was established. After learning the tralning samples,the BP neural network can describe the non-linear relationship between the operation parameters and NOx emission and boiler efficiency.The simulation results show that the rela-tive error of prediction values of NOx emission and boiler efficiency is less than 3.92% and 7.6%,respec-tively,indicating the neural network can describe the change rules of NOx emission and boiler efficiency a-galnst the SOFA alr damper opening degree and oxygen content.This modified BP neural network has high prediction accuracy and stable generalization ability,which can provide guidance for optimization of low NOx combustion for pulverized coal boilers.关键词
燃煤锅炉/低氮燃烧/BP神经网络/燃烧优化/NOx 排放浓度/锅炉效率Key words
coal-fired boiler/low NOx combustion/BP neural network/combustion optimization/NOx emis-sion/boiler efficiency分类
能源科技引用本文复制引用
陆军,张广才,徐党旗,周平,周飞..改进BP神经网络在低氮燃烧优化中的应用[J].热力发电,2015,(4):106-111,119,7.
