基于多数据融合传感器的分布式温度控制系统(中英文对照论文).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基于多数据融合传感器的分布式温度控制系统摘要：在过去的几十年，温度控制系统已经被广泛的应用。对于温度控制提出了一种基于多传感器数据融合和CAN总线控制的一般结构。一种新方法是基于多传感器数据融合估计算法参数分布式温控系统。该系统的重要特点是其共性，其适用于很多具体领域的大型的温度控制。实验结果表明该系统具有较高的准确性、可靠性，良好的实时性和广泛的应用前景。关键词：分布式控制系统；CAN总线控制；智能CAN节点；多数据融合传感器。1介绍分布式温度控制系统已经被广泛的应用在我们日常生活和生产,包括智能建筑、温室、恒温车间、大中型粮仓、仓库等。这种控制保证环境温度能被保持在两个预先设定的温度间。在传统的温度测量系统中，我们用一个基于温度传感器的单片机系统建立一个RS-485局域网控制器网络。借助网络,我们能实行集中监控和控制.然而,当监测区域分布更广泛和传输距离更远,RS-485总线控制系统的劣势更加突出。在这种情况下，传输和响应速度变得更低，抗干扰能力更差。因此，我们应当寻找新的通信的方法来解决用RS-485总线控制系统而产生的问题。在所有的通讯方式中，适用于工业控制系统的总线控制技术，我们可以突破传统点对点通信方式的限制、建立一个真正的分布式控制与集中管理系统，CAN总线控制比RS-485总线控制系统更有优势。比如更好的纠错能力、改善实时的能力，低成本等。目前，它正被广泛的应用于实现分布式测量和范围控制。随着传感器技术的发展，越来越多的系统开始采用多传感器数据融合技术来提高他们的实现效果。多传感器数据融合是一种范式对多种来源整合数据,以综合成新的信息，比其他部分的总和更加强大。无论在当代和未来，系统的低成本，节省资源都是传感器中的一项重要指标。2分布式架构的温度控制系统分布式架构温度控制系统如图中所示的图1。可以看出，这系统由两个模块两个智能CAN节点和一个主要的控制器组成。每个模块部分执行进入分布式架构。下面的是简短的描述下各模块。3.1主要控制器作为系统的主要控制器，这主pc能和智能CAN节点通信。它致力于监督和控制整个系统，系统配置、显示运行状况、参数初始化和协调各部分间的关系。更重要的是，我们能打印或储存系统的历史温度的数据，这对分析系统性能是非常有用的。3.2智能CAN节点每一个温度控制系统的智能CAN节点有五个部分：MCU一个单片机，A/D转换单元，