|
OALib Journal期刊
ISSN: 2333-9721
费用：99美元
|
|
|
|
改进bp神经网络在低氮燃烧优化中的应用
, PP. 106-111
Keywords: 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
Abstract:
基于燃煤锅炉低氮燃烧优化试验数据,建立了预测nox排放浓度和锅炉效率的改进bp神经网络模型,通过样本学习,该网络可以精确描述锅炉运行参数与nox排放浓度和锅炉效率之间的非线性映射关系。仿真结果表明,网络的nox排放浓度和锅炉效率预测值的相对误差分别小于3.92%和7.6%,能够描述nox排放浓度和锅炉效率随sofa风门开度和运行氧量变化的规律,而且预测精度高、泛化能力强,可为燃煤锅炉低氮燃烧优化提供指导。
| [1] | 中国火电厂氮氧化物排放控制技术方案研究报告[r].中国环保产业协会,2008.reportonthetechnicalschemesofreducingnoxemissionforcoal-firedpowerplantsinchina[r].chinaenvironmentalprotectionindustryassociation,2008(inchinese).
|
| [2] | 关于公布全国燃煤机组脱硫脱硝设施等重点大气污染减排工程名单的公告[第48号][r].中华人民共和国环境保护部,2014.listofkeyairpollutionemissionreductionprojectsbyusingdesulfurizationanddenitrationfacilitiesforcoal-firedpowerplants[no.48].ministryofenvironmentalprotectionofthepeople’srepublicofchina,2014(inchinese).
|
| [3] | 李凌,余岳峰,吕玮华,等.基于神经网络的锅炉低nox排放系统辨识[j].锅炉技术,2003,34(1):68-71.liling,yuyuefeng,luweihua,et.al.artificialneuralnetworkmodelusedtoidentificationthesystemoflownoxemission[j].boilertechnology,2003,34(1):68-71.
|
| [4] | 朱群志,李芳芹,任建兴,等.燃煤电站锅炉nox排放的人工神经网络建模及优化分析[j].华东电力,2008,36(10):128-130.zhuzhiqun,lifangqin,renjianxing,etal.artificialneuralnetworkmodelsofnoxemissionforcoal-firedboilersandoptimizationofstaged-aircombustion[j].eastchinaelectricpower,2008,36(10):128-130.
|
| [5] | 张砺彦,麦永强,张月辉,等.基于神经网络的大型燃煤电厂so2和nox的污染物预测模型[j].热力发电,2008,37(10):9-13.zhangliyan,maiyongqiang,zhangyuehui,etal.predictionmodelforpollutantsso2andnoxfromlarge-scalecoal-firedpowerplantbasedonneuralnetwork[j].thermalpowergeneration,2008,37(10):9-13.
|
| [6] | 许昌,吕剑虹.基于生成机理的燃煤电站锅炉nox排放量神经网络模型[j].中国电机工程学报,2004,24(10):233-237.xuchang,lyujianhong.artificialneuralnetworksmodelfornoxemissioninapulverized-coalpowerstationboilerongenerationmechanism[j].proceedingsofthecsee,2004,24(10):233-237.
|
| [7] | 陈庆文,马晓茜,刘翱.大型电站锅炉混煤掺烧的nox排放特性预测与运行优化[j].中国电机工程学报,2009,29(23):20-26.chenqingwen,maxiaoqian,liuao.predictionandoperationoptimizationfornoxemissionpropertyoflarge-scalemixedcoal-firedutilityboiler[j].proceedingsofthecsee,2009,29(23):20-26.
|
| [8] | zhouh,cenk,fanj.modelingandoptimizationofthenoxemissioncharacteristicsofatangentiallyfiredboilerwithartificialneuralnetworks[j].energy,2004,29(1):167-183.
|
| [9] | 王新军,王飞,马增益,等.用于电厂煤粉锅炉nox排放监测的bp神经网络试验研究[j].动力工程,2002,22(5):1979-1982.wangxinjun,wamgfei,mazengyi,etal.researchonthebackpropagationneuralnetworkusedforthemonitorofthenoxreleaseofthepowerplantboiler[j].powerengineering,2002,22(5):1979-1982.
|
| [10] | 刘芳,张德珍,赵文杰.电站锅炉燃烧系统的神经网络建模[j].电力科学与工程,2010,26(6):33-37.liufang,zhangdezhen,zhaowenjie.neuralnetworkmodelingforcombustionsystemofpowerplantboiler[j].electricpowerscienceandengineering,2010,26(6):33-37.
|
| [11] | 何勇超.采用燃烧系统模型预测锅炉效率和nox排放浓度[j].热力发电,2013,42(4):65-69.heyongchao.combustionsystemmodelbasedpredictionofboilerefficiencyandnoxemission[j].thermalpowergeneration,2013,42(4):65-69.
|
| [12] | 秦鹏,林中达.基于改进型elman神经网络和遗传算法的锅炉在线燃烧优化[j].锅炉技术,2005,36(5):37-41.qinpeng,linzhongda.on-lineoptimizingcombustionfortheboilerbasedonmodifiedelmanneuralnetworkandgeneticalgorithm[j].boilertechnology,2005,36(5):37-41.
|
| [13] | 鲍春来,张竞飞.基于rbf神经网络模型的电站锅炉燃烧优化[j].发电设备,2013,27(2):97-100.baochunlai,zhangjingfei.combustionoptimizationofpowerplantboilersbasedonrbfneuralnetworkmodel[j].powerequipment,2013,27(2):97-100.
|
| [14] | 王志心,包德梅,曹黎明,等.锅炉燃烧系统神经网络建模及多目标优化研究[j].发电设备,2012,26(2):97-99,118.wangzhixin,baodemei,caoliming,etal.multi-objectiveneuralnetworkoptimizationforboilercombustionsystems[j].powerequipment,2012,26(2):97-99,118.
|
| [15] | 高大启.有教师的线性基本函数前向三层神经网络结构研究[j].电路与系统学报,1997,2(3):31-37.gaodaqi.onstructuresofsupervisedlinearbasisfunctionfeedforwardthree-layeredneuralnetworks[j].journalofcircuitsandsystems,1997,2(3):31-37.
|
| [16] | 吕玉坤,彭鑫,赵锴.电站锅炉热效率与nox排放混合建模与优化[j].中国电机工程学报,2011,31(26):16-22.lyuyukun,pengxin,zhaokai.hybridmodelingoptimizationofthermalefficiencyandnoxemissionofutilityboiler[j].proceedingsofthecsee,2011,31(26):16-22.
|
| [17] | 周昊,茅建波,池作和,等.燃煤锅炉低氮氧化物燃烧特性的神经网络预报[j].环境科学,2002,23(2):18-22.zhaohao,maojianbo,chizuohe,etal.predictinglownoxcombustionpropertyofacoal-firedboiler[j].environmentalscience,2002,23(2):18-22.
|
Full-Text
|
|
Contact Us
service@oalib.com QQ:3279437679 
WhatsApp +8615387084133
|
|
