基于多數(shù)據(jù)融合傳感器的分布式溫度控制系統(tǒng)(中英文對(duì)照論文).doc

DISTRIBUTEDTEMPERATURECONTROLSYSTEMBASEDONMULTI-SENSORDATAFUSIONAbstract:Temperaturecontrolsystemhasbeenwidelyusedoverthepastdecades.Inthispaper,ageneralarchitectureofdistributedtemperaturecontrolsystemisputforwardbasedonmulti-sensordatafusionandCANbus.Anewmethodofmulti-sensordatafusionbasedonparameterestimationisproposedforthedistributedtemperaturecontrolsystem.Themajorfeatureofthesystemisitsgenerality,whichissuitableformanyfieldsoflargescaletemperaturecontrol.Experimentshowsthatthissystempossesseshigheraccuracy,reliability,goodrealtimecharacteristicandwideapplicationprospectKeywords:Distributedcontrolsystem；CANbus；intelligentCANnode；multi-sensordatafusion.1.IntroductionDistributedtemperaturecontrolsystemhasbeenwidelyusedinourdailylifeandproduction,includingintelligentbuilding,greenhouse,constanttemperatureworkshop,largeandmediumgranary,depot,andsoon1.Thiskindofsystemshouldensurethattheenvironmenttemperaturecanbekeptbetweentwopredefinedlimits.IntheconventionaltemperaturemeasurementsystemswebuildanetworkthroughRS-485Bususingasingle-chipmeteringsystembasedontemperaturesensors.Withtheaidofthenetwork,wecancarryoutcentralizedmonitoringandcontrolling.However,whenthemonitoringareaismuchmorewidespreadandtransmissiondistancebecomesfarther,thedisadvantagesofRS-485Busbecomemoreobvious.Inthissituation,thetransmissionandresponsespeedbecomeslower,theanti-interferenceabilitybecomesworse.Therefore,weshouldseekoutanewcommunicationmethodtosolvetheproblemsproducedbyRS-485Bus.Duringallthecommunicationmanners,theindustrialcontrol-orientedfieldbustechnologycanensurethatwecanbreakthroughthelimitationoftraditionalpointtopointcommunicationmodeandbuilduparealdistributedcontrolandcentralizedmanagementsystem.Asaserialcommunicationprotocolsupportingdistributedreal-timecontrol,CANbushasmuchmoremeritsthanRS-485Bus,suchasbettererrorcorrectionability,betterreal-timeability,lowercostandsoon.Presently,ithasbeenextensivelyusedintheimplementationofdistributedmeasurementandcontroldomains.Withthedevelopmentofsensorytechnology,moreandmoresystemsbegintoadoptmulti-sensordatafusiontechnologytoimprovetheirperformances.Multi-sensordatafusionisakindofparadigmforintegratingthedatafrommultiplesourcestosynthesizethenewinformationsothatthewholeisgreaterthanthesumofitsparts345.Anditisacriticaltaskbothinthecontemporaryandfuturesystemswhichhavedistributednetworksoflow-cost,resource-constrainedsensors2.DistributedarchitectureofthetemperaturecontrolsystemThedistributedarchitectureofthetemperaturecontrolsystemisdepictedintheFigure1.Ascanbeseen,thesystemconsistsoftwomodulesseveralintelligentCANnodesandamaincontroller.TheyareinterconnectedwitheachotherthroughCANbus.Eachmoduleperformsitspartintothedistributedarchitecture.Thefollowingisabriefdescriptionofeachmoduleinthearchitecture.31maincontrollerAsthesystemsmaincontroller,thehostPCcancommunicatewiththeintelligentCANnodes.Itisdevotedtosuperviseandcontrolthewholesystem,suchassystemconfiguration,displayingrunningcondition,parameterinitializationandharmonizingtherelationshipsbetweeneachpart.Whatsmore,wecanprintorstorethesystemshistorytemperaturedata,whichisveryusefulfortheanalysisofthesystemperformance3.2.IntelligentCANnodeEachintelligentCANnodeofthetemperaturecontrolsystemincludesfiveunits:MCUasinglechip,A/Dconversionunit,temperaturemonitoringunitsensorgroup,digitaldisplayunitandactuatorsacoolingunitandaheatingunit.TheoperatingprincipleoftheintelligentCANnodeisdescribedasfollows.Inthepracticalapplication,wedividetheregionofthecontrolobjectiveintomanycells,andlaytheintelligentCANnodesinsomeofthetypicalcells.Ineachnode,MCUcollectstemperaturedatafromthetemperaturemeasurementsensorgroupswiththeaidoftheA/Dconversionunit.Simultaneously,itperformsbasicdatafusionalgorithmstoobtainafusionvaluewhichismoreclosetotherealone.Andthedigitaldisplayunitdisplaysthefusingresultofthenodetimely,sowecanunderstandtheenvironmenttemperatureineverycontrolcellseparately.Bycomparingthefusionvaluewiththesetonebythemaincontroller,theintelligentCANnodecanimplementthedegenerativefeedbackcontrolofeachcellthroughenablingthecorrespondingheatingorcoolingdevices.IfthefusionresultisbiggerthanthesetvalueinthespecialintelligentCANnode,thecoolingunitwillbegintowork.Onthecontrary,ifthefusionresultislessthanthesetvalueinthenodetheheatingunitwillbegintowork.Bythismeanswecannotonlymonitortheenvironmenttemperature,butalsocanmakethecorrespondingactuatorworksoastoregulatethetemperatureautomatically.AtthesametimeeveryCANnodeisabletosenddataframetotheCANbuswhichwillnotifythemaincontrollerthetemperaturevalueinthecellsothatcontrollercanconvenientlymakedecisionstomodifytheparameterornot.SincetheCANnodescanregulatethetemperatureofthecellwheretheyare,thetemperatureinthewholeroomwillbekepthomogeneous.Whatsmore,wecanalsocontroltheintelligentnodebymodifyingthetemperaturessettingvalueonthehostPC.Generally,theprocessorsonthespotarenotgoodatcomplexdataprocessinganddatafusing,soitbecomesverycriticalhowtochooseasuitabledatafusionalgorithmforthesystem.Intheposteriorsection,wewillintroduceadatafusionmethodwhichissuitablefortheintelligentCANnodes。4.Multi-sensordatafusionTheaimtousedatafusioninthedistributedtemperaturecontrolsystemistoeliminatetheuncertainty,gainamorepreciseandreliablevaluethanthearithmeticalmeanofthemeasureddatafromfinitesensors.Furthermore,whensomeofthesensorsbecomeinvalidinthetemperaturesensorgroups,theintelligentCANnodecanstillobtaintheaccuratetemperaturevaluebyfusingtheinformationfromtheothervalidsensors.4.1.ConsistencyverificationofthemeasureddataDuringtheprocessoftemperaturemeasurementinourdesigneddistributedtemperaturecontrolsystem,measurementerrorcomesintobeinginevitablybecauseoftheinfluenceoftheparoxysmaldisturbortheequipmentfault.Soweshouldeliminatethecarelessmistakebeforedatafusion.Wecaneliminatethemeasurementerrorsbyusingscatterdiagrammethodinthesystemequippedwithlittleamountofsensors.ParameterstorepresentthedatadistributionstructureincludemedianTM,upperquartilenumberFv,lowerquartilenumberFLandquartiledispersiondF.Itissupposedthateachsensorinthetemperaturecontrolsystemproceedstemperaturemeasurementindependently.Inthesystem,thereareeightsensorsineachtemperaturesensorgroupoftheintelligentCANnode.SowecanobtaineighttemperaturevaluesineachCANnodeatthesametime.Wearrangethecollectedtemperaturedatainasequencefromsmalltolarge:T1,T2,T8Inthesequence,T1isthelimitinferiorandT8isthelimitsuperior.WedefinethemedianTMas:(1)TheupperquartileFvisthemedianoftheintervalTM,T8.ThelowerquartilenumberFListhemedianoftheintervalT1,TM.Thedispersionofthequartileis:（2）WesupposethatthedataisanaberrationoneifthedistancefromthemedianisgreaterthanadF,thatis,theestimationintervalofinvaliddatais:(3)Intheformula,aisaconstant,whichisdependentonthesystemmeasurementerror,commonlyitsvalueistobe0.5,1.0,2.0andsoon.Therestvaluesinthemeasurementcolumnareconsideredastobethevalidoneswithconsistency.AndtheSingle-ChipintheintelligentCANnodewillfusetheconsistentmeasurementvaluetoobtainafusionresult5.TemperaturemeasurementdatafusionexperimentByapplyingthedistributedtemperaturecontrolsystemtoagreenhouse,weobtainanarrayofeighttemperaturevaluesfromeightsensorsasfollowsThemeanvalueoftheeightmeasurementtemperatureresultisComparingthemeanvalue(8)Twiththetruetemperaturevalueinthecellofthegreenhouse,wecanknowthatthemeasurementerroris+0.5.Afterweeliminatethecarelesserrorfromthefifthsensorusingthemethodintroducedbefore,wecanobtainthemeanvalueoftherestsevendata(7)T=29.6,themeasurementerroris-0.4.ThesevenrestconsistentsensorcanbedividedintotwogroupswithsensorS1,S3,S7inthefirstgroupandsensorS2,S4,S6,S8inthesecondone.Thearithmeticalmeanofthetwogroupsofmeasureddataandthestandarddeviationareasfollowsrespectively:Accordingtoformula(13),wecaneducethetemperaturefusionvaluewiththesevenmeasuredtemperaturevalue.Theerrorofthefusiontemperatureresultis-0.3.Itisobviousthatthemeasurementresultfromdatafusionismoreclosetothetruevaluethanthatfromarithmeticalmean.Inthepracticalapplication,themeasuredtemperaturevaluemaybeverydispersiveasthemonitoringareabecomesbigger,datafusionwillimprovethemeasuringprecisionmuchmoreobviously.6.ConclusionsThedistributedtemperaturecontrolsystembasedonmulti-sensordatafusionisconstructedthroughCANbus.Ittakesfulladvantageofthecharacteristicsoffieldbuscontrolsystem-FDCS.Dataacquisition,datafusionandsystemcontrollingiscarriedoutintheintelligentCANnode,andsystemmanagementisimplementedinthemaincontroller(hostPC).ByusingCANbusanddatafusiontechnologythereliabilityandreal-timeabilityofthesystemisgreatlyimproved.Wearesurethatitwillbewidelyusedinthefuture.References1WaltzE.LiinasJ,Multi-sensorDataFusion,ArtechHouse,NewYork,1990.2PhilipsSemiconductors,(1995b).“P82C150:CANseriallinkedI/Odevice(SLIO)withdigitalandanalogportfunctions”,preliminaryDataSheet,October1995.3Aslam,J.,Li,Q.,Rus,D.,Threepower-awareroutingalgorithmsforsensornetworks,WirelessCommunicationsandMobileComputing,pp.187208,2003.4R.C.Luo,M.G.Kay,MultisensorIntegrationandFusioninIntelligentSystems,IEEETrans.onSystems,Man,andCybernetics,Vol.19,No.5,pp.901-931September/October,1989.5PauLF,Sensorsdatafusion,JournalofIntelligentandRoboticSystem,pp.103-106,1998.6ThomopoulosSC.,Sensorintegrationanddatafusion,JournalofRoboticSystems,pp.337-372,1990.7RaoBSY,Durrant-WhyteHF,SheenJA,Afullydecentralizedmulti-sensorsystemfortrackingandsurveillance,TheInternationalJournalofRoboticsResearch,MassachusettsInstituteofTechnology,Vol12,No.1,pp.20-44,Feb1993.8TenneyRR,JrsandellNR,Detectionwithdistributedsensors,AES,Vol17,pp.501-510,1981基于多數(shù)據(jù)融合傳感器的分布式溫度控制系統(tǒng)摘要：在過去的幾十年，溫度控制系統(tǒng)已經(jīng)被廣泛的應(yīng)用。對(duì)于溫度控制提出了一種基于多傳感器數(shù)據(jù)融合和CAN總線控制的一般結(jié)構(gòu)。一種新方法是基于多傳感器數(shù)據(jù)融合估計(jì)算法參數(shù)分布式溫控系統(tǒng)。該系統(tǒng)的重要特點(diǎn)是其共性，其適用于很多具體領(lǐng)域的大型的溫度控制。實(shí)驗(yàn)結(jié)果表明該系統(tǒng)具有較高的準(zhǔn)確性、可靠性，良好的實(shí)時(shí)性和廣泛的應(yīng)用前景。關(guān)鍵詞：分布式控制系統(tǒng)；CAN總線控制；智能CAN節(jié)點(diǎn)；多數(shù)據(jù)融合傳感器。1介紹分布式溫度控制系統(tǒng)已經(jīng)被廣泛的應(yīng)用在我們?nèi)粘Ｉ詈蜕a(chǎn),包括智能建筑、溫室、恒溫車間、大中型糧倉、倉庫等。這種控制保證環(huán)境溫度能被保持在兩個(gè)預(yù)先設(shè)定的溫度間。在傳統(tǒng)的溫度測(cè)量系統(tǒng)中，我們用一個(gè)基于溫度傳感器的單片機(jī)系統(tǒng)建立一個(gè)RS-485局域網(wǎng)控制器網(wǎng)絡(luò)。借助網(wǎng)絡(luò),我們能實(shí)行集中監(jiān)控和控制.然而,當(dāng)監(jiān)測(cè)區(qū)域分布更廣泛和傳輸距離更遠(yuǎn),RS-485總線控制系統(tǒng)的劣勢(shì)更加突出。在這種情況下，傳輸和響應(yīng)速度變得更低，抗干擾能力更差。因此，我們應(yīng)當(dāng)尋找新的通信的方法來解決用RS-485總線控制系統(tǒng)而產(chǎn)生的問題。在所有的通訊方式中，適用于工業(yè)控制系統(tǒng)的總線控制技術(shù)，我們可以突破傳統(tǒng)點(diǎn)對(duì)點(diǎn)通信方式的限制、建立一個(gè)真正的分布式控制與集中管理系統(tǒng)，CAN總線控制比RS-485總線控制系統(tǒng)更有優(yōu)勢(shì)。比如更好的糾錯(cuò)能力、改善實(shí)時(shí)的能力，低成本等。目前，它正被廣泛的應(yīng)用于實(shí)現(xiàn)分布式測(cè)量和范圍控制。隨著傳感器技術(shù)的發(fā)展，越來越多的系統(tǒng)開始采用多傳感器數(shù)據(jù)融合技術(shù)來提高他們的實(shí)現(xiàn)效果。多傳感器數(shù)據(jù)融合是一種范式對(duì)多種來源整合數(shù)據(jù),以綜合成新的信息，比其他部分的總和更加強(qiáng)大。無論在當(dāng)代和未來，系統(tǒng)的低成本，節(jié)省資源都是傳感器中的一項(xiàng)重要指標(biāo)。2分布式架構(gòu)的溫度控制系統(tǒng)分布式架構(gòu)溫度控制系統(tǒng)如圖中所示的圖1。可以看出，這系統(tǒng)由兩個(gè)模塊兩個(gè)智能CAN節(jié)點(diǎn)和一個(gè)主要的控制器組成。每個(gè)模塊部分執(zhí)行進(jìn)入分布式架構(gòu)。下面的是簡(jiǎn)短的描述下各模塊。3.1主要控制器作為系統(tǒng)的主要控制器，這主pc能和智能CAN節(jié)點(diǎn)通信。它致力于監(jiān)督和控制整個(gè)系統(tǒng)，系統(tǒng)配置、顯示運(yùn)行狀況、參數(shù)初始化和協(xié)調(diào)各部分間的關(guān)系。更重要的是，我們能打印或儲(chǔ)存系統(tǒng)的歷史溫度的數(shù)據(jù)，這對(duì)分析系統(tǒng)性能是非常有用的。3.2智能CAN節(jié)點(diǎn)每一個(gè)溫度控制系統(tǒng)的智能CAN節(jié)點(diǎn)有五個(gè)部分：MCU一個(gè)單片機(jī)，A/D轉(zhuǎn)換單元，