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上海交通大学硕士学位论文基于人工神经网络的全燃高炉煤气锅炉燃烧预报研究姓名:朱宇翔申请学位级别:硕士专业:动力工程指导教师:陆方;王乃义20081001IBP,ABSTRACTIIStudyofpurefiringBFGboiler’sburningpredictionbasedonANNABSTACTAsaby-passproductofsteelplant,BFG(blastfurnacegas)isakindoflowheatvaluefuelandpoisonousgas.PurefiringBFGboilerhasitsowncharactersofdesign,manufactureandoperationbecauseofusingBFGfuel.TheoperationofpurefiringBFGboilerisconnectedwithblasterfurnace’soperatingsituationtightly.It’svaluableforpurefiringBFGboilertopredictburningsituationaccordingtoblasterfurnace’ssituation.ThispaperanalysesinfluentialfactorsofpurefiringBFGboiler’scombustionstabilitybasedonproduce,charactersandcombustiontheoryofBFG.Then,itbuildsforecastingmodelofpurefiringBFGboiler’scombustionbasedonBPANN(artificialneuralnetwork)andadaptsdatafromoperationtotrainandexaminemodel.Themodelcanpresentthetechnicalguaranteeforoptimizingoperation,andtheforecastingmodelofcombustioncanmeettherequirementthroughexperiment.Keywords:PurefiringBFGboiler;influentialfactorsofcombustionstability;ANN;forecastingmodelofcombustion;1211.1220T/H,1.2COWARDZABETAKIS[10]HUBUER[6]2[1][5][7][11]1J.GREEN[8]BABCOK&WILCOXERDEMIVTURKY,(OG)(BFG)(COG)(NG)BFGOG[12][13]273[14]CSI200MW[15]135MW[18]BP[16]8[17]1.350%1)2)BPBP43)4)MATLABBP5)BPCO6)1.452.12.1.1C+O2=CO22C+O2=2COC+H2O=CO+H2CO2+C=2CO3Fe2O3+CO=2Fe3O4+CO2Fe3O4+CO=3FeO+CO2FeO+CO=Fe+CO23Fe2O3+H2=2Fe3O4+H2OFe3O4+H2=3FeO+H2OFeO+H2=Fe+H2OCOH21)21%22~24%2)63)2-1%21~252121~25%15~1811~134.5~7.0%23~2627~2935~40%1~41~22.5~3.5%54~5758~5952~55KJ/Nm33385.8~41803340~37624598~50162.1.22C+O2=2COCO2+C=2CO12Nm3Vg=N2/N2*F2-1VgNm3/tN2%N2%FNm3/tVg=100C/CO2+CO+CH4*0.536Nm3/t2-2C=C1+C2+C3-C4-C5C1C2C3C4C5CO2COCH470.536Nm3CO2COCH41Nm310~40[36]2.22.2.1BFG(BlasterFurnaceGas)BFGBFGCOH2N2CO21)CO281.25Kg/m3,Q=16269kJ/m3,12.574.2%,644--658,,,.2)H22.0160.0899Kg/m3,Q=10747.5kJ/m3,4.274%,580--590,3)N2281.25Kg/m3,4)CO2441.98Kg/m3,2.2.2BFGBFGBlasterFurnaceGas28003500kJ/Nm3,1500700BFG25%CON2CO270%BFG70036BFG2.2.3BFG[51]82-2BFG2-3BFGCO%CO2%H2%N2%kJ/Nm3123.222.43.151.33268.02222322.92.751.43199.558322.523.42.451.73103.956421.923.92.2523006.504521.324.21.952.62898.258BFG[26]2-41)BFGMBFGMXiMiM=1/100XiMi2-3%%CO23.22125CO222.41925H23.114N251.350573268kJ/Nm330003600kJ/Nm3=50mg/Nm310g/Nm3MKg/m3PasKJ/m3*N228.01341.250416.61.302H22.0160.08998.341.298CO28.0191.250616.61.302CO244.011.977113.81.6209M=CO*28+CO2*44+N2*28+H2*2/100=23.2*28+22.4*44+51.3*28+3.1*2/100=30.782)BFG=1/100Xii2-4=1/2240XiMi=M/2240=1.37Kg/m33)BFGCP/CVCP=1/100XiCPI2-5CV=1/100XiCViCP=1.373KJ/m3*CV=0.9947KJ/m3*4)BFGt=((273+C)/(T+C))*(T/273)1.52-6CC=143.7PasttPasTT=t+273K=7.98PasBFG190t=12.1Pas5)=0.02488W/m[35]2.32.3.1H2COCOH2COH2O2COH2102-1RPFig2-1SketchmapofchainreactionH21922OHHHOH+→+HOOHO+→+2OHOHH+→+2OHOHHOO+→+22OHOOOH+→+2HHOOHOH+→+222HHOHO+→+222OHHOHOO+→+22222HOHOHOO+→+2222HOOHHOHO+→+222HOHHOOH+→+2222HOHHOH+→+11222HOOHOOH+→+22HOMOHOHM+→++2OOMOM++→+2HOHMHOM++→+2MHHHM+→++22HOMHOM++→+HOMOHM++→+MCOO2COO2700700COOHOHH2O+CO→CO2+H2H2+O2→H2O2H2O2+M→2OH+MH2O2+CO→CO2+H2OOH+CO→CO2+HH+O2→OH+OH+O2+M→HO2+MO+H2→OH+HO+O2+M→O3+MHO2+CO→CO2+OHHO2→COO2[26][27]2.3.2,,.,,,,12T1T2CBCAQ1Q1=WHV=k0e-(E/RT)CBbCAaHV2-7W-----H-----k0----V----T2CBCAQ1=Ae-(E/RT)2-8Q2Q2=FT2-T12-9----F----BFQ2=BT2-T12-102-2Fig2-2Relationofkindlingpointandquantityofheat2-2Q1=Q2(dQ1/dT)=(dQ2/dT)T=[1-1-4RT1/E]/2R/E2-1113T=T1+R/ET122-122627372-5COH22-5CO20%=1.1CO13.7%,660COCO20%[36]2.3.32.3.3.1[26]COH2BFGBFG12CO+O2=2CO222H2+O2=2H2O2.3.3.21Nm3kJ/Nm3BFGBFGCOH2,COH2Hl=HH2MH2+HCOMco2-13Hl------BFGHH2HCO-------H2COMH2Mco--------BFGH2COH2CO/40060514COH22-6COH2kJ/Nm3126441079432682.3.3.31)BFGV0=1/21[0.5H2+0.5CO+(m+n/4)CMHn+1.5H2S-O2]2-14V0-------Nm3/Nm3H2CO------BFGV0=0.626Nm3/Nm32)VV=V0111.021.1V=1.021.1V02.3.3.41)=1CO2SO2N2H2O1Nm3VRO2=VCO2+VSO2=0.01CO2+CO+mCMHn+H2S2-15VRO2------VCO2VSO2------CO2SO2VRO2=0.456Nm3/Nm3VH2O0=0.01[H2+H2S+n/2CMHn+120(dg+V0da)]2-16VH2O0-------da-----VH2O0=0.031Nm3/Nm315VN20=0.79V0+0.01N22-17VN20--------VN20=1.008Nm3/Nm3Vf0=VRO2+VH2O0+VN202-18Vf0=1.495Nm3/Nm321CO2SO2N2H2OH2COVf=Vf0+-1V0=1.495+0.050.1*0.6262-192-72-7(=1.1)kJ/Nm3V0Nm3/Nm3VRO2Nm3/Nm3VH2O0Nm3/Nm3VN20Nm3/Nm3Vf0Nm3/Nm3VfNm3/Nm332680.6260.4560.0391.0081.5021.56531990.6120.4590.0340.9971.4911.55231030.5930.4590.0310.9851.4751.53530060.5740.4580.0290.9731.461.51828980.5520.4550.0260.9621.4431.4982-8(=1.1)kJ/Nm3CO2%N2%O2%H2O%326829.167.60.82.5319929.667.40.92.1310329.967.20.92300630.267.10.81.9289830.467.10.81.7Cp1KJ/m32-9CpkJ/Nm3Cp300Cp400Cp500Cp600Cp700Cp80032681.4816571.5069981.5327741.5583281.5812631.60231831991.4834821.5092241.5351791.5608991.5839551.60510831031.4849171.5108581.5369371.5627711.5859141.60714430061.4863051.5124341.5386321.5645761.5878021.60910928981.4869111.5132061.5394681.5654721.588741.61008116kJ/Nm3Cp900Cp1000Cp1100Cp1200Cp1300Cp140032681.6226341.6425931.6605741.6739461.6868381.7016531991.62551.6455171.6635261.6769151.6898031.7046231031.6275961.6476741.6657181.6791411.6920491.70688430061.6296171.649761.6678391.6812961.6942241.70908128981.6306131.6507741.6688591.6823161.6952361.7100932.3.3.5tthtC1Nm3Hl+Ig+Ia=If2
本文标题:基于人工神经网络的全燃高炉煤气锅炉燃烧预报研究
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