小城镇给水管网渗漏预测及机理研究

重庆大学硕士学位论文小城镇给水管网渗漏预测及机理研究姓名：李广浩申请学位级别：硕士专业：市政工程指导教师：张勤20060401IP()-0.91390.8151-0.430512.36900.00920.09600.4728PDtHm=+++0.11500.49290.00220.0065PmDHtM--=IIABSTRACTThewaterpipenetworkleakageisuniversalexistencephenomenonforthewatersupplyprofession.Itshouldbetreatsthesymptomsandthecausesforthewaterpipenetworkleakagequestion,andtakeeffectsapermanentcureasthegoal.Butwantfundamentallytosolvetheleakageproblem,weshouldcarriesontheanalysisfromtheleakagereasonandtheleakagemechanismaspect,thusprovidesthebasisforthechoiceleakagecontrolmethod,andtakesthepointedmeasure.Thetraditionalleakagedetectionmethodhasthepassiveleakdetectionmethod,thesoundlistenstotheleakdetectionmethod,theregiontoinstallthetablemethod,theregionleakdetectionmethodandsoon,alongwiththetechnicaldevelopment,theseleakagedetectioninstrumentsaccuraciesalsounceasinglyisenhancing,butthemallhavethequestionthattheleakagedetectionlagtheleakage.Becausethewaterpipenetworkisburiesintheunderground,passesthroughthelong-termusetobeabletohavetheleakageevencartridgeigniterinevitablyincertainlengthsofpipe,howeverthesebreakdownsnoteasilywasdiscoveredgenerallyintheshort-term,thishascreatedthemassivewaterresourceswaste.Therefore,ifwecanpromptlydiagnosethepipenetworkleakagepointanddecidesontheconcretepositionfirmly,ithasthevitaleconomicalsignificanceandthesocialsignificance.Thisarticletogivesthewaterpipenetworkleakagehistorydatathroughaseriesofmathematicsmethodtocarryontheanalysis,andfinallyestablishesforthewaterpipenetworkleakagefrequencymodelaswellasforthewaterpipenetworkleakageprobabilisticmodel,promulgatestheleakagehistorydataconcealmentthegeneralrule,notonlymayjudgedeliversthefuturechangetendencywhichthewaterpipenetworkleaks,moreovermaypromptlydeterminethepipenetworkpossibleleakageposition,likethis,ontheonehandfortheleakagecontrol,thepipenetworkmaintenanceprovidesthescientificbasis,ontheotherhandreducedforthewaterpipenetworkleakagerate,savedthemassivewaterresources.Thematerialdataofsmalltownwatersupplysystemisinsufficiently,thereforecollectsthematerialdataofthecityplotpipenetworkleakagematerialtosimulatethesmalltownpipenetworkcondition,andthroughtheleakagesituationpipenetworkmaterialstatisticalanalysisofthiscity,thusobtainsthewaterpipenetworkleakagefrequencyforecastmodel,aswellasusesthegrayconnectiondecidesthevaluecombinationforecastandmanynon-linearityreturndecidetwokindofdifferenttypesIIImodels.Producedthecitypipenetworkforthewaterpipenetworkfrequencyforecastmodelgivesthepipelineleakagefrequency,itsconcepthadthepipelineleakagesituationnumberoftimeseveryyearforeachkilometerpipeline,andthegrayconnectioncombinationforecastandmanynon-linearreturnobtainedtheequationforgivethewaterpipenetworkthepipelineleakageprobabilityconceptualmodel.Itsconcretemodelis:ThewaterpipenetworkleakagefrequencymodelP(Eachkilometerpipelinehasleakagenumberoftimeseveryyear):-0.91390.8151-0.4305412.36900.00920.09600.4728PDtHP=+++Thewaterpipenetworkleakageconceptprobabilisticmodel:0.11500.49290.00220.0065PmDHtM--=Keywords:Smalltown,Thewaterpipenetwork,Leakagemodel,Grayrelatinglevel111.1,,13.903km,,96.50%2.53%,0.353km0.2123km,0.006%,4682316,1400,,,[li1][1][2][li2],“”,()4,44,,,“”2,“”“”,“”,“”“”,()(),()19986682.063m263m3300m12.3%3.1[li3]%[3]31600m400230025%30[li4]%[4]70%31.2DMA1.2.1DMADMA[][5][li5]()1.10iq=∑1.11.2.2“”1.2.34[li6][6]1986,,,[7][li7]C,0.421LLLQAH=1.2LQ,3/secmLA,2mLHmG1985,(WAA)Germanopoulos,[8][li8],G1.181[()]2LijijijQCLHH=+1.3ijCijiHimijLijmArtificialNeuralNetworksANN[li9][9]GraySystem5[li10][10]PassionShamirHoward()0()()AtgNtNte+=1.4t()Nt0()NtgtA12[11][li11]-Rajani,ZhanKuraoka-xdyd1.51.6123xpippuEpETxdccca∂=+-Δ∂1.5(/,/,,,)iypspspDhDtEEvktdr=1.66pEuxpvPoissonpaipTΔsE,DTsk-1c2c3crSCADA[li12][12]1.2.4[13][13-15]7()()TheArtInTheWaterIndustry.::;1000-2000mFFT/;[14][16]1.2.58[15][17-22]1.31.3.12003BA808A15-2“”“”52[16][23]19970.6720.4430.8/m[17][24]91.3.21.3.31.11.1Figure1.1ThePathsDiagramoftheResearchingMethod1022.1[li18][25]SCADA2.22.2.13314891521337112.2.2200120011456200320042001200220032004171805km2003DN240068.54%80DN1600,DN1002.32.3.112345678[19][26]122.3.22000-20042.3.32.12.180.55%8.01%133.59%1.27%4.11%0.45%UPVC2.02%2.148111526UPVC1782.1—Table2.1TheAnalysisoftheSingleFactor-theMaterialoftheConduitUPVC10774817556271071337çi80.55%3.59%1.27%4.11%0.45%2.02%8.01%100%--2.1—Figure2.1TheAnalysisoftheSingleFactor-theMaterialoftheConduitDN100DN16002.22.2142.2—Table2.2TheAnalysisoftheSingleFactor-theDiameteroftheConduitDN100DN150DN200DN250DN300DN400DN5005731822262919427642.89%13.62%16.92%2.17%14.52%2.02%0.45%DN600DN800DN1000DN1200DN1400DN16006081844513364.49%0.60%1.35%0.30%0.30%0.37%100%2.2DN250DN400DN500DN600DN600DN250DN400DN5002.2—Figure2.2TheAnalysisoftheSingleFactor-theDiameteroftheConduit0-0.5m0.5-1.0m1.0-1.5m1.5-2.0m2.0-2.5m2.5-3.0m3.0-3.5m3.5-4.0m4.0m2.32.3152.3—Table2.3TheAnalysisoftheSingleFactor-theDepthoftheConduit(m)0-0.50.5-1.01.0-1.51.5-2.02.0-2.52.5-3.03.0-3.53.5-4.04.03632355922799232862413252.72%24.38%42.19%17.13%7.47%1.74%2.11%0.45%1.81%100%2.3—Figure2.3