Modeling of the Combustion Optimizing Based on RBF Neural Networks

Lei Chen, Youcheng Xie, Zhongli Shen, Huilin Fu
{"title":"Modeling of the Combustion Optimizing Based on RBF Neural Networks","authors":"Lei Chen, Youcheng Xie, Zhongli Shen, Huilin Fu","doi":"10.1109/CCCM.2008.327","DOIUrl":null,"url":null,"abstract":"A combustion optimizing model based on RBF neural networks is set up, and the optimizations of providing coal volume and real generating electricity power are actualized. At the same time, the simulation model is established by MATLAB. The simulation research is processed. The simulation result indicates: in the stabilization state, if the boiler load, power plant coal character (the distinctness of coal heat glowing volume), combustion supplying air volume or combustion inducing air volume changes, the combustion optimizing model based on RBF neural networks can find the optimum values of providing coal volume and real generating electricity power. This result lays a strong base for optimal control and on-line prediction of the boiler.","PeriodicalId":326534,"journal":{"name":"2008 ISECS International Colloquium on Computing, Communication, Control, and Management","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 ISECS International Colloquium on Computing, Communication, Control, and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCCM.2008.327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

A combustion optimizing model based on RBF neural networks is set up, and the optimizations of providing coal volume and real generating electricity power are actualized. At the same time, the simulation model is established by MATLAB. The simulation research is processed. The simulation result indicates: in the stabilization state, if the boiler load, power plant coal character (the distinctness of coal heat glowing volume), combustion supplying air volume or combustion inducing air volume changes, the combustion optimizing model based on RBF neural networks can find the optimum values of providing coal volume and real generating electricity power. This result lays a strong base for optimal control and on-line prediction of the boiler.
基于RBF神经网络的燃烧优化建模
建立了基于RBF神经网络的燃烧优化模型,实现了供煤量和实际发电功率的优化。同时,利用MATLAB建立了仿真模型。进行了仿真研究。仿真结果表明:在稳定状态下,当锅炉负荷、电厂煤特性(煤热发光量的差异性)、燃烧供风量或诱导风量发生变化时,基于RBF神经网络的燃烧优化模型能够找到供煤量和实际发电功率的最优值。该结果为锅炉的最优控制和在线预测奠定了坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信