偷窥国产在线91,亚洲无线国产观看原创,日本精品aⅴ一区二区三区,久久九九兔免费精品6

簡(jiǎn)介：JOURNALOFMATERIALSPROCESSINGTECHNOLOGY142200320–28DELTAFERRITEPREDICTIONINSTAINLESSSTEELWELDSUSINGNEURALNETWORKANALYSISANDCOMPARISONWITHOTHERPREDICTIONMETHODSMVASUDEVANA,?,AKBHADURIA,BALDEVRAJA,KPRASADRAOBAMETALLURGYANDMATERIALSGROUP,INDIRAGANDHICENTREFORATOMICRESEARCH,KALPAKKAM,INDIABDEPARTMENTOFMETALLURGY,INDIANINSTITUTEOFTECHNOLOGY,CHENNAI,INDIARECEIVED2MAY2002RECEIVEDINREVISEDFORM11DECEMBER2002ACCEPTED17FEBRUARY2003ABSTRACTTHEABILITYTOPREDICTTHEDELTAFERRITECONTENTINSTAINLESSSTEELWELDSISIMPORTANTFORMANYREASONSDEPENDINGONTHESERVICEREQUIREMENT,MANUFACTURERSANDCONSUMERSOFTENSPECIFYDELTAFERRITECONTENTASANALLOYSPECIFICATIONTOENSURETHATWELDCONTAINSADESIREDMINIMUMORMAXIMUMFERRITELEVELRECENTRESEARCHACTIVITIESHAVEBEENFOCUSEDONSTUDYINGTHEEFFECTOFVARIOUSALLOYINGELEMENTSONTHEDELTAFERRITECONTENTANDCONTROLLINGDELTAFERRITECONTENTBYMODIFYINGTHEWELDMETALCOMPOSITIONSOVERTHEYEARS,ANUMBEROFMETHODSINCLUDINGCONSTITUTIONDIAGRAMS,FUNCTIONFITMODEL,FEEDFORWARDBACKPROPAGATIONNEURALNETWORKMODELHAVEBEENPUTFORWARDFORPREDICTINGTHEDELTAFERRITECONTENTINSTAINLESSSTEELWELDSAMONGALLTHEMETHODS,NEURALNETWORKMETHODWASREPORTEDTOBEMOREACCURATECOMPAREDTOOTHERMETHODSAPOTENTIALRISKASSOCIATEDWITHNEURALNETWORKANALYSISISOVERFITTINGOFTHETRAININGDATATOAVOIDOVERFITTING,MACKAYHASDEVELOPEDABAYESIANFRAMEWORKTOCONTROLTHECOMPLEXITYOFTHENEURALNETWORKMAINADVANTAGESOFTHISMETHODARETHATITPROVIDESMEANINGFULERRORBARSFORTHEMODELPREDICTIONSANDALSOITISPOSSIBLETOIDENTIFYAUTOMATICALLYTHEINPUTVARIABLESWHICHAREIMPORTANTINTHENONLINEARREGRESSIONINTHEPRESENTWORK,BAYESIANNEURALNETWORKBNNMODELFORPREDICTIONOFDELTAFERRITECONTENTINSTAINLESSSTEELWELDHASBEENDEVELOPEDTHEEFFECTOFVARYINGCONCENTRATIONOFTHEELEMENTSONTHEDELTAFERRITECONTENTHASBEENQUANTIFIEDFORTYPE309AUSTENITICSTAINLESSSTEELANDTHEDUPLEXSTAINLESSSTEELALLOY2205THEBNNMODELISFOUNDTOBEMOREACCURATECOMPAREDTOTHATOFTHEOTHERMETHODSFORPREDICTINGDELTAFERRITECONTENTINSTAINLESSSTEELWELDS?2003ELSEVIERSCIENCEBVALLRIGHTSRESERVEDKEYWORDSNEURALNETWORKANALYSISDELTAFERRITECONTENTAUSTENITICSTAINLESSSTEELDUPLEXSTAINLESSSTEEL1INTRODUCTIONTHEABILITYTOESTIMATETHEDELTAFERRITECONTENTACCURATELYHASPROVENVERYUSEFULINPREDICTINGTHEVARIOUSPROPERTIESOFAUSTENITICSSWELDSAMINIMUMDELTAFERRITECONTENTISNECESSARYTOENSUREHOTCRACKINGRESISTANCEINTHESEWELDS1,2,WHILEANUPPERLIMITONTHEDELTAFERRITECONTENTDETERMINESTHEPROPENSITYTOEMBRITTLEMENTDUETOSECONDARYPHASES,EGSIGMAPHASE,ETC,FORMEDDURINGELEVATEDTEMPERATURESERVICE3ATCRYOGENICTEMPERATURES,THETOUGHNESSOFTHEAUSTENITICSSWELDSISSTRONGLYINFLUENCEDBYTHEDELTAFERRITECONTENT4INDUPLEXSTAINLESSSTEELWELDMETALS,ALOWERFERRITELIMITISSPECIFIEDFORSTRESSCORROSIONCRACKINGRESISTANCEWHILETHEUPPERLIMITISSPECIFIEDTOENSUREADEQUATEDUCTILITYANDTOUGHNESS5HENCE,DEPENDINGONTHESERVICEREQUIREMENTALOWERLIMITAND/ORANUPPERLIMITONDELTAFERRITECONTENTISGENERALLYSPECIFIEDDURINGTHESELEC?CORRESPONDINGAUTHORTEL91411480232FAX91411440381EMAILADDRESSDEVIGCARERNETINMVASUDEVANTIONOFFILLERMETALCOMPOSITION,THEMOSTACCURATEDIAGRAMTODATEWRC1992ISUSEDGENERALLYTOESTIMATETHE?FERRITECONTENT6THECREQANDNIEQFORMULAEUSEDFORGENERATINGTHEWRC1992CONSTITUTIONDIAGRAMISGIVENBYCREQCRMO07NBANDNIEQNI35C20N025CUTHELIMITATIONOFTHESEEQUATIONSISTHATVALUESOFTHECOEFFICIENTSFORTHEDIFFERENTELEMENTSREMAINUNCHANGEDIRRESPECTIVEOFTHECHANGEINTHEBASECOMPOSITIONOFTHEWELDHOWEVER,THERELATIVEINFLUENCEOFEACHALLOYINGADDITIONGIVENBYTHEELEMENTALCOEFFICIENTSINTHECREQANDNIEQEXPRESSIONSISLIKELYTOCHANGEOVERTHEFULLCOMPOSITIONRANGEFURTHERMORE,THESEEXPRESSIONSIGNORETHEINTERACTIONBETWEENTHEELEMENTSALSO,THEREAREANUMBEROFALLOYINGELEMENTSTHATHAVENOTBEENCONSIDEREDINTHEWRC1992DIAGRAMELEMENTSLIKESI,TI,WHAVENOTBEENGIVENDUETOCONSIDERATIONS,THOUGHTHEYAREKNOWNTOINFLUENCETHEDELTAFERRITECONTENTHENCE,THEDELTAFERRITECONTENTESTIMATEDUSINGTHEWRC1992DIAGRAMWOULDALWAYSBELESSACCURATEANDMAYNEVERBECLOSETOTHEACTUALMEASUREDVALUEINTHEFUNCTIONFITMODEL7FORESTIMATINGFERRITE,THEDIFFERENCEINFREEENERGYBETWEENTHEFERRITEANDTHEAUSTENITEWASCALCULATED09240136/–SEEFRONTMATTER?2003ELSEVIERSCIENCEBVALLRIGHTSRESERVEDDOI101016/S092401360300430822MVASUDEVANETAL/JOURNALOFMATERIALSPROCESSINGTECHNOLOGY142200320–28FIG1SCHEMATICDIAGRAMOFTHENETWORKSTRUCTURESHOWINGTHEINPUTNODES,HIDDENUNITSANDTHEOUTPUTNODEFUNCTIONSOTHATEACHINPUTCONTRIBUTESTOEVERYHIDDENUNIT,WHERENISTHETOTALNUMBEROFINPUTVARIABLESHITANH??N?JW1IJXJΘ1I??3HERETHEBIASISDESIGNATEDASΘANDISANALOGOUSTOTHECONSTANTINLINEARREGRESSIONTHETRANSFERFROMTHEHIDDENUNITSTOTHEOUTPUTISLINEAR,ANDISGIVENBYYN?IW2IHIΘ24THEOUTPUTYISTHEREFOREANONLINEARFUNCTIONOFXJ,WITHTHEFUNCTIONUSUALLYSELECTEDFORFLEXIBILITYBEINGTHEHYPERBOLICTANGENTTHUS,THENETWORKISCOMPLETELYDESCRIBEDIFTHENUMBEROFINPUTNODES,OUTPUTNODESANDTHEHIDDENUNITSAREKNOWNALONGWITHALLTHEWEIGHTSWIJANDBIASESΘITHESEWEIGHTSWIJAREDETERMINEDBYTRAININGTHENETWORKANDINVOLVESMINIMIZATIONOFAREGULARIZEDSUMOFSQUAREDERRORSTHEBNNANALYSISOFMACKAY10ALLOWSTHECALCULATIONOFERRORBARSWITHTWOCOMPONENTSONEREPRESENTINGTHEPERCEIVEDLEVELOFNOISEΣVINTHEOUTPUTANDTHEOTHERINDICATINGTHEUNCERTAINTYINTHEDATAFITTINGTHISLATTERCOMPONENTOFTHEERRORBARSEMANATINGFROMTHEBAYESIANFRAMEWORKALLOWSTHERELATIVEPROBABILITIESOFTHEMODELSWITHDIFFERENTCOMPLEXITYTOBEASSESSEDTHISENABLESESTIMATIONOFQUANTITATIVEERRORBARS,WHICHVARYWITHTHEPOSITIONINTHEINPUTSPACEDEPENDINGONTHEUNCERTAINTYINFITTINGTHEFUNCTIONINTHATSPACEHENCE,INSTEADOFCALCULATINGAUNIQUESETOFWEIGHTS,APROBABILITYDISTRIBUTIONOFWEIGHTSISUSEDTODEFINETHEUNCERTAINTYINFITTINGTHEREFORE,THESEERRORBARSBECOMELARGEWHENDATAARESPARSEORLOCALLYNOISYINTHISCONTEXT,AVERYUSEFULMEASUREOFTHEERRORISTHELOGARITHMOFTHEPREDICTIVEERRORLPEGIVENBYTHEFOLLOWINGLPE?N12?TN?YN2ΣN2YLOG2ΠΣNY1/2?5WHERETISTHETARGETFORTHESETOFINPUTSX,WHILEYTHECORRESPONDINGNETWORKOUTPUTΣYISRELATEDTOTHEUNCERTAINTYOFFITTINGFORTHESETOFINPUTSXBYUSINGLPE,THEPENALTYFORMAKINGAWILDPREDICTIONISREDUCEDIFTHATPREDICTIONISACCOMPANIEDBYANAPPROPRIATELYLARGEERRORBAR,WITHALARGERVALUEOFTHELPEIMPLYINGABETTERMODELFURTHER,BYTHISMETHODITISALSOPOSSIBLETOAUTOMATICALLYIDENTIFYTHEINPUTVARIABLESTHATARESIGNIFICANTININFLUENCINGTHEOUTPUTVARIABLE,ASTHEINPUTVARIABLESTHATARELESSSIGNIFICANTAREDOWNWEIGHTEDINTHEREGRESSIONANALYSIS31OVERFITTINGPROBLEMINBNNANALYSIS,TWOSOLUTIONSAREIMPLEMENTEDWHICHCONTRIBUTETOAVOIDOVERFITTINGTHEFIRSTISCONTAINEDINTHEALGORITHMDUETOMACKAY12THECOMPLEXITYPARAMETERSΑANDΒAREINFERREDFROMTHEDATA,THEREFOREALLOWINGAUTOMATICCONTROLOFTHEMODELCOMPLEXITYTHESECONDRESIDESINTHETRAININGMETHODTHEDATABASEISEQUALLYDIVIDEDINTOATRAININGSETANDATESTINGSETTOBUILDAMODEL,ABOUT80NETWORKSARETRAINEDWITHDIFFERENTNUMBEROFHIDDENUNITSANDSEEDS,USINGTHETRAININGSETTHEYARETHENUSEDTOMAKEPREDICTIONSONTHEUNSEENTESTINGSETANDARERANKEDBYLPE32COMMITTEEMODELTHENETWORKSWITHDIFFERENTNUMBEROFHIDDENUNITSWILLGIVEDIFFERENTPREDICTIONSBUTPREDICTIONSWILLALSODEPENDONTHEINITIALGUESSMADEFORTHEPROBABILITYDISTRIBUTIONOFTHEWEIGHTSTHEPRIOROPTIMUMPREDICTIONSAREOFTENMADEUSINGMORETHANONEMODEL,BYBUILDINGACOMMITTEETHEPREDICTIONˉYOFACOMMITTEEOFNETWORKSISTHEAVERAGEPREDICTIONOFITSMEMBERS,ANDTHEASSOCIATEDERRORBARISCALCULATEDACCORDINGTOEQ6ˉY1L?LYLΣ21L?LΣL2Y1L?LYL?ˉY26WHERELISTHENUMBEROFNETWORKSINACOMMITTEENOTETHATWENOWCONSIDERTHEPREDICTIONSFORAGIVENSINGLESETOFINPUTSANDTHATEXPONENTLREFERSTOTHEMODELUSEDTOPRODUCETHECORRESPONDINGPREDICTIONYLINPRACTICE,ANINCREASINGNUMBEROFNETWORKSAREINCLUDEDINACOMMITTEEANDTHEIR

簡(jiǎn)介：MIXEDDSP/FPGAIMPLEMENTATIONOFANERRORRESILIENTIMAGETRANSMISSIONSYSTEMBASEDONJPEG2000MARCOGRANGETTO,ENRICOMAGLI,MAURIZIOMARTINA,FABRIZIOVACCACERCOMCENTERFORWIRELESSMULTIMEDIACOMMUNICATIONSDIPARTIMENTODIELETTRONICAPOLITECNICODITORINOCORSODUCADEGLIABRUZZI2410129TORINOITALYGRANGETTOMAGLIPOLITOITMARTINAVACCAVLSILABOLPOLITOITPH390115644195FAX39011564099ABSTRACTTHISPAPERDESCRIBESADEMONSTRATOROFANERRORRESILIENTIMAGECOMMUNICATIONSYSTEMOVERWIRELESSPACKETNETWORKS,BASEDONTHENOVELJPEG2000STANDARDINPARTICULAR,THEDECODERIMPLEMENTATIONISADDRESSED,WHICHISTHEMOSTCRITICALTASKINTERMSOFCOMPLEXITYANDPOWERCONSUMPTION,INVIEWOFUSEONAWIRELESSPORTABLETERMINALFORCELLULARAPPLICATIONSTHESYSTEMIMPLEMENTATIONISBASEDONAMIXEDDSP/FPGAARCHITECTURE,WHICHALLOWSTOPARALLELIZESOMECOMPUTATIONALTASKS,THUSLEADINGTOEFICIENTSYSTEMOPERATION1INTRODUCTION’NOWADAYS,THEREISAGROWINGINTERESTINTHEENDTOENDTRANSMISSIONOFIMAGES,ESPECIALLYMOTIVATEDBYTHESHORTTERMDEPLOYMENTOFNEXTGENERATIONMOBILECOMMUNICATIONSERVICESUMTSIMT2000HOWEVER,TRANSMISSIONINANETWORKED,TETHERLESSENVIRONMENTPROVIDESBOTHOPPORTUNITIESANDCHALLENGESTHEWIRELESSCONTEXTIMPLIESTHATTHEDATAMAYUNDERGOBITERRORSANDPACKETLOSSES,MAKINGITNECESSARYTOFORESEEERRORRECOVERYMODALITIESITISTHEREBYNECESSARYTHATIMAGECOMMUNICATIONTECHNIQUESAREPROVIDEDWITHTHEABILITYTORECOVER,ORATLEASTCONCEAL,THEEFFECTOFSUCHLOSSESTHEFORTHCOMINGJPEG2000IMAGECOMPRESSIONSTANDARDHASBEENDESIGNEDTOMATCHTHESEREQUIREMENTS,ANDEMBEDSSOMEERRORDETECTIONANDCONCEALMENTTOOLSTHISPAPERADDRESSESTHEDEVELOPMENTOFADEMONSTRATOROFANERRORRESILIENTJPEG2000111DECODERIMPLEMENTATIONFORIMAGECOMMUNICATIONOVERALOSSYPACKETNETWORKTHEROBUSTNESSTOPACKETERASURESISACHIEVEDBYCOMBININGTHEFLEXIBILITYOFTHEJPEG2000FRAMEWORKWITHTHEPOWERFULNESSOFSOURCECHANNEL078037147X/01/100002001IEEEADAPTIVE,OPTIMIZEDREEDSOLOMONCODESTHEDECODERIMPLEMENTATIONISPARTICULARLYSIGNIFICANTINTHECONTEXTOFWIRELESSPORTABLETERMINALSFORNEXTGENERATIONCELLULARSYSTEMS,WHERETHELIMITEDPOWERBUDGETANDAVAILABLEDIMENSIONSIMPOSESEVERECONSTRAINTSONTHEDESIGNOFAMULTIMEDIAPROCESSINGSYSTEM2SYSTEMOVERVIEWTHEFUNCTIONALUNITSOFTHEIMPLEMENTEDSYSTEM21JPEG2000IMAGECOMPRESSIONJPEG2000ISTHENOVELIS0STANDARDFORSTILLIMAGECODING,ANDISINTENDEDTOPROVIDEINNOVATIVESOLUTIONSACCORDINGTOTHENEWTRENDSINMULTIMEDIATECHNOLOGIESATTHETIMEOFTHISWRITING,THESTANDARDISINADVANCEDPUBLICATIONSTAGETHEFINALCOMMITTEEDRAFTLISTHEMOSTRECENTJPEG2000DESCRIPTIONPUBLICLYAVAILABLE,WHICHOURIMPLEMENTATIONCONFORMSTOJPEG2000NOTONLYYIELDSSUPERIORPERFORMANCEWITHRESPECTTOEXISTINGSTANDARDSINTERMSOFCOMPRESSIONCAPABILITYANDSUBJECTIVEQUALITY,BUTALSONUMEROUSADDITIONALFUNCTIONALITIES,SUCHASIOSSLESSANDLOSSYCOMPRESSION,PROGRESSIVETRANSMISSION,ANDERRORRESILIENCETHEARCHITECTUREOFTHEJPEG2000ISBASEDONTHETRANSFORMCODINGAPPROACHANIMAGEMAYBEDIVIDEDINTOSEVERALSUBIMAGESTILES,TOREDUCEMEMORYANDCOMPUTINGREQUIREMENTSABIORTHOGONALDISCRETEWAVELETTRANSFORMDWTISFIRSTAPPLIEDTOEACHTILE,WHOSEOUTPUTISASERIESOFVERSIONSOFTHETILEATDIFFERENTRESOLUTIONLEVELSSUBBANDSTHEN,THETRANSFORMCOEFFICIENTSAREQUANTIZED,INDEPENDENTLYFOREACHSUBBAND,WITHANEMBEDDEDDEADZONEQUANTIZEREACHSUBBANDOFTHEWAVELETDECOMPOSITIONISDIVIDEDINTORECTANGULARBLOCKSCODEBLOCKS,WHICHAREININTHEFOLLOWINGWEPROVIDEABRIEFDESCRIPTIONOF1330CODETHERECEIVEDBITSTREAMMAKESTHEUSEOFAREEDSOLOMONFPGAIMPLEMENTATIONVERYATTRACTIVETHEJPEG2000DECODERMODULE,ENTIRELYIMPLEMENTEDONDSP,ISCOMPOSEDBYFOURMAINBLOCKSSYNTAXPARSER,ENTROPYDECODEREBCOT,UNIFORMSCALARDEQUANTIZER,ANDINVERSEWAVELETTRANSFORMMOREOVER,TWOADDITIONALTASKS,DEVOTEDTOCOMMUNICATIONMANAGEMENTBETWEENDSP,FPGAANDAPERSONALCOMPUTER,HAVEBEENINTRODUCED31SYNTAXPARSERTHEPARSERISTHEFUNCTIONALBLOCKTHATINTERFACESTHEJPEG2000DECODERWITHTHERSDECODERITRETRIEVESRSDECODEDPACKETS,ANDEXTRACTSFROMTHECOMPRESSEDJPEG2000BITSTREAMALLTHERELEVANTINFORMATIONNEEDEDTOPERFORMIMAGERECONSTRUCTIONFIRSTLY,THEBITSTREAMMAINHEADERISREAD,WHICHCONTAINSINFORMATIONONTHEPARAMETERSUSEDDURINGTHEENCODINGPROCESSEGIMAGESIZE,WAVELETFILTERUSED,NUMBEROFDECOMPOSITIONLEVELS,QUANTIZATIONTHRESHOLDS,ANDSOONAFTERTHAT,TILEHEADERSAREREAD,WHICHPROVIDEINFORMATIONSPECIFICTOEACHIMAGETILEFINALLY,EACHPACKETCONTAINEDINTHEBITSTREAMISREAD,ANDTHEDATAANDPARAMETERSOFEACHCODEBLOCKAREEXTRACTED,ANDFEDASINPUTSTOTHEEBCOTDECODER32EBCOTRIGHTAFTERTHEBITSTREAMSYNTAXPARSER,THESUBSEQUENTSTAGEINTHEJPEG2000DECOMPRESSIONCHAINISTHEENTROPYDECODEREBCOTFROMANALGORITHMICPOINTOFVIEW,EBCOTISABLOCKBASEDBITPLANEENCODERFOLLOWEDBYAREDUCEDCOMPLEXITYARITHMETICCODERMQITSUBDIVIDESEACHWAVELETSUBBANDINTOADISJOINTSETOFRECTANGULARBLOCKS,CALLEDCODEBLOCKSTHENTHECOMPRESSIONALGORITHMISINDEPENDENTLYAPPLIEDTOEVERYCODEBLOCKTHESAMPLESOFEVERYCODEBLOCKAREARRANGEDINTOSOCALLEDBITPLANESTODECODEACODEBLOCK,EBCOTALWAYSSTARTSFROMTHEMOSTSIGNIFICANTBITPLANES,ANDTHENMOVESTOWARDSTHELEASTSIGNIFICANTONESTHECOMPRESSEDINFORMATIONOFEVERYCODEBLOCKISTHENARRANGEDINSEVERALQUALITYLAYERS,TOCREATEASCALABLECOMPRESSEDBITSTREAMCONCEPTUALLY,EACHQUALITYLAYERMONOTONICALLYINCREASESTHEKNOWLEDGEOFSAMPLESMAGNITUDES,IEINCREASESTHEQUALITYOFTHERECONSTRUCTEDIMAGEFORMALLY,EBCOTISMADEOFTHREEMAINSTEPS,NAMELYSIGNIFICANCEPROPAGATIONSP,MAGNITUDEREFINEMENTMR,ANDCLEANUPCLEACHOFTHEABOVESTEPSCANRESORTTOFOURDECODINGPRIMITIVES,NAMELYZEROCODING,SIGNCODING,MAGNITUDEREFINEMENTCODING,ANDRUNLENGTHCODINGTHEBITPLANEVISITINGORDERFOLLOWSTHESEQUENCESPMRCLITISWORTHNOTICINGTHATEVERYSAMPLEOFAGIVENCODEBLOCKISPROCESSEDINJUSTONEOFTHETHREESTEPSASFARASCOMPUTATIONALCOMPLEXITYISCONCERNED,CLDEMANDSTHELARGESTEFFORTDURINGTHEDECODINGOFTHEMOSTSIGNIFICANTBITPLANESASSPSTEPSAREAPPLIED,ANINCREASINGNUMBEROFSAMPLESBECOMESIGNIFICANT,ANDAREINSERTEDINALISTOFMRREADYSAMPLESPROGRESSIVELY,THELOADREQUIREDBYMRSTEPSGROWS,MAKINGTHEDECODEREFFICIENCYDIRECTLYDEPENDENTONTHEMRANDCLOPTIMIZATIONLEVELDURINGTHEDEVELOPMENTOFTHEEBCOTDECODERBLOCK,PARTICULARCAREHASBEENPOSEDONTHEDESIGNOFAGILEDATASTRUCTURES,PARTICULARLYSUITEDTODSPOPTIMIZEDCCODEOFMRANDCLSTEPS33UNIFORMSCALARDEQUANTIZERACCORDINGTOL,THEQUANTIZATIONMETHODSUPPORTEDBYJPEG2000ISCALLEDSCALARUNIFORMUNIFORMSCALARDEQUANTIZATIONCANBESIMPLYACCOMPLISHEDBYMEANSOFASINGLEMULTIPLICATIONFOREACHWAVELETCOEFFICIENT34INVERSEWAVELETTRANSFORMTHEDISCRETEWAVELETTRANSFORMCANBEEVALUATEDBYMEANSOFACONVOLUTIONBASEDKERNEL,ORALIFTINGBASEDKERNEL,THISLATTERBEINGTHEDEFAULTTRANSFORMKERNELEMPLOYEDINJPEG2000ITHASBEENDEMONSTRATED4THATTHELIFTINGSCHEMEMAYRUNUPTOTWICEASFASTASCONVOLUTIONTHEWAVELETTRANSFORMHASTOBEPERFORMEDONBOTHIMAGEROWSANDCOLUMNS,INORDERTOOBTAINASEPARABLETWODIMENSIONALSUBBANDDECOMPOSITIONJPEG2000PERFORMSFIRSTTHECOLUMNWISE,ANDTHENTHEROWWISEFILTERINGTHEDEFAULTFILTERUSEDFORLOSSYCOMPRESSIONISTHEWELLKNOWNDB9,7SINCEITDOESNOTHAVERATIONALCOEFFICIENTS,PARTICULARCAREOUGHTTOBEPOSEDTOTHEEFFECTSOFFINITEPRECISIONREPRESENTATION5DUETOTHEUSEOFAFIXEDPOINTTITMS320C6201DSP,ADETAILEDSTUDYOFINTERNALDATAREPRESENTATIONHASBEENPERFORMEDEXPERIMENTALRESULTSSHOWSTHATEXCELLENTPERCEPTIVEQUALITYCANBEACHIEVEDRECURRINGTO9FRACTIONALBITSFORFILTERCOEFFICIENTSINORDERTOOPTIMIZETHEDYNAMICRANGEAROUNDZERO,ADCSHIFTISFORESEENBYTHESTANDARD,ASTHEDCCOMPONENTCOULDLEADTOANEXCESSIVEGROWTHOFTHEDYNAMICRANGEOFLOWPASSSUBBANDCOEFFICIENTSMOREOVER,THELOWPASSFILTERSCANKEEPTHESAMPLESINAFIXEDRANGE,PROVIDEDTHATAUNITARYDCFILTERGAINISGUARANTEEDTHEJOINTEFFECTOFDCCOMPONENTSUPPRESSIONANDUNITARYGAINENSURESTHATRANGEREQUIREMENTSAREFULFILLEDDURINGTHEWHOLEWAVELETTRANSFORM35ADAPTIVEREEDSOLOMONPACKETDETHEDEINTERLEAVINGRSDECODERHASBEENMAPPEDONTHEFPGADEVICEITISSPLITINTOTWOFUNCTIONALSUBBLOCKSTHEFIRSTISTHEDEINTERLEAVER,THESECONDISTHERSDECODERTHEFORMERCOLLECTSPACKETSRECEIVEDFROMCODING1332

簡(jiǎn)介：INSTANTOPENCVFORIOSLEARNHOWTOBUILDREALTIMECOMPUTERVISIONAPPLICATIONSFORTHEIOSPLATFORMUSINGTHEOPENCVLIBRARYKIRILLKORNYAKOVALEXANDERSHISHKOVBIRMINGHAMMUMBAIPREFACEINSTANTOPENCVFORIOSISAPRACTICALGUIDE,SHOWINGEVERYIMPORTANTSTEPFORBUILDINGACOMPUTERVISIONAPPLICATIONFORTHEIOSPLATFORMITWILLHELPYOUTOPORTYOUROPENCVCODE,PROFILEANDOPTIMIZEIT,ANDTHENWRAPINTOAGUIAPPLICATIONTHISBOOKHELPSYOUTOLEARNHOWTOBUILDASIMPLE,BUTPOWERFULCOMPUTERVISIONAPPLICATIONFORTHEIOSDEVICESFROMSCRATCHTHROUGHOUTTHEBOOK,YOULLLEARNDETAILSTHATWILLHELPYOUTOBECOMEAPROFESSIONALATIOSDEVELOPMENTUSINGOPENCVASUSUAL,YOUBEGINWITHTHESIMPLE“HELLOWORLD“APPLICATION,BUTFINALLYYOUWILLBEABLETOCREATECOMPLEXIMAGEPROCESSINGAPPLICATIONSWITHSUPREMEEFFICIENCYEACHRECIPEISACCOMPANIEDWITHASAMPLEPROJECT,HELPINGYOUTOFOCUSONAPARTICULARASPECTOFTHETECHNOLOGYWHATTHISBOOKCOVERSFGETTINGSTARTEDWITHIOSSIMPLE,HELPSYOUTOSETUPYOURDEVELOPMENTENVIRONMENTANDRUNYOURFIRST“HELLOWORLD“IOSAPPLICATIONFDISPLAYINGANIMAGEFROMRESOURCESSIMPLE,INTRODUCESYOUTOBASICGUICONCEPTSONIOS,ANDCOVERSLOADINGOFANIMAGEFROMRESOURCESANDDISPLAYINGITONTHESCREENFLINKINGOPENCVTOANIOSPROJECTSIMPLE,EXPLAINSHOWTOLINKOPENCVLIBRARYANDCALLANYFUNCTIONFROMITFDETECTINGFACESWITHCASCADECLASSIFIERINTERMEDIATE,SHOWSHOWTODETECTFACESUSINGOPENCVFPRINTINGAPOSTCARDINTERMEDIATE,DEMONSTRATESHOWASIMPLEPHOTOEFFECTCANBEIMPLEMENTEDFWORKINGWITHIMAGESINGALLERYINTERMEDIATE,EXPLAINSHOWTOLOADANDSAVEIMAGESFROM/TOGALLERYFAPPLYINGARETROEFFECTINTERMEDIATE,DEMONSTRATESANOTHERINTERESTINGPHOTOEFFECTTHATMAKESPHOTOSLOOKOLDFTAKINGPHOTOSFROMCAMERAINTERMEDIATE,SHOWSHOWTOCAPTURESTATICIMAGESWITHCAMERA

簡(jiǎn)介：1AFFECTIVEINTELLIGENTCARINTERFACESWITHEMOTIONRECOGNITIONCHRISTINELLISETTIDEPARTMENTOFMULTIMEDIACOMMUNICATIONS,INSTITUTEURECOMSOPHIAANTIPOLIS,FRANCECHRISTINELISETTIEURECOMFRFATMANASOZSCHOOLOFCOMPUTERSCIENCE,UNIVERSITYOFCENTRALFLORIDAORLANDO,FLFATMACSUCFEDUABSTRACTINTHISPAPER,WEUNCOVERANEWPOTENTIALAPPLICATIONFORMULTIMEDIATECHNOLOGIESAFFECTIVEINTELLIGENTCARINTERFACESFORENHANCEDDRIVINGSAFETYWEALSODESCRIBETHEEXPERIMENTWECONDUCTEDINORDERTOMAPCERTAINPHYSIOLOGICALSIGNALSGALVANICSKINRESPONSE,HEARTBEAT,ANDTEMPERATURETOCERTAINDRIVINGRELATEDEMOTIONSANDSTATESFRUSTRATION/ANGER,PANIC/FEAR,ANDBOREDOM/SLEEPINESSWEDEMONSTRATETHERESULTSWEOBTAINEDANDDESCRIBEHOWWEUSETHESERESULTSTOFACILITATEAMORENATURALHUMANCOMPUTERINTERACTIONINOURMULTIMODALAFFECTIVECARINTERFACEFORTHEDRIVERSOFTHEFUTURECARS1INTRODUCTIONANDMOTIVATIONHUMANSARESOCIALBEINGSTHATEMOTEANDTHEIRCOGNITIONISAFFECTEDBYTHEIREMOTIONSEMOTIONSINFLUENCEVARIOUSCOGNITIVEPROCESSESINHUMANS,INCLUDINGPERCEPTIONANDORGANIZATIONOFMEMORYBOWER,1981,CATEGORIZATIONANDPREFERENCEZAJONC,1984,GOALGENERATION,EVALUATION,ANDDECISIONMAKINGDAMASIO,1994,STRATEGICPLANNINGLEDOUX,1992,FOCUSANDATTENTIONDERRYBERRYEKMANCHOVIL1991,ANDLEARNINGGOLEMAN,1995PREVIOUSSTUDIESALSOSUGGESTTHATPEOPLEEMOTEWHILETHEYAREINTERACTINGWITHCOMPUTERSREEVESGROSSLEVENSON,1997HOWEVER,INTERPRETINGTHEDATAWITHSTATISTICALMETHODSANDALGORITHMSISBENEFICIALINTERMSOFACTUALLYBEINGABLETOMAPTHEMTOSPECIFICEMOTIONSSTUDIESHAVEDEMONSTRATEDTHATALGORITHMSCANBEVERYSUCCESSFULLYIMPLEMENTEDFORRECOGNITIONOFEMOTIONSFROMPHYSIOLOGICALSIGNALSCOLLETETALCOLLET,VERNETMAURY,DELHOMME,DITTMAR,1997SHOWEDNEUTRALANDEMOTIONALLYLOADEDPICTURESTOPARTICIPANTSINORDERTOELICITHAPPINESS,SURPRISE,ANGER,FEAR,SADNESS,ANDDISGUSTTHEPHYSIOLOGICALSIGNALSMEASUREDWERESKINCONDUCTANCESC,SKINPOTENTIALSP,SKINRESISTANCESR,SKINBLOODFLOWSBF,SKINTEMPERATUREST,ANDINSTANTANEOUSRESPIRATORYFREQUENCYIRFSTATISTICALCOMPARISONOFDATASIGNALSWASPERFORMEDPAIRWISE,WHERE6EMOTIONSFORMED15PAIRSOUTOFTHESE15EMOTIONPAIRS,ELECTRODERMALRESPONSESSR,SC,ANDSPDISTINGUISHED13PAIRS,ANDSIMILARLYCOMBINATIONOFTHERMOCIRCULATORYVARIABLESSBFANDSTANDRESPIRATIONCOULDDISTINGUISH14EMOTIONPAIRSSUCCESSFULLYPICARDETALPICARD,HEALEY,VYZAS,2001USEDPERSONALIZEDIMAGERYANDEMOTIONALLYLOADEDPICTURESTOELICITHAPPINESS,SADNESS,ANGER,FEAR,DISGUST,SURPRISE,NEUTRALITY,PLATONICLOVE,ANDROMANTICLOVETHEPHYSIOLOGICALSIGNALSMEASUREDWEREGSR,HEARTBEAT,RESPIRATION,ANDELECTROCARDIOGRAMTHEALGORITHMSUSEDTOANALYZETHEDATAWERESEQUENTIALFORWARDFLOATINGSELECTIONSFFS,FISHERPROJECTION,ANDAHYBRIDOFTHESETWOTHEBESTCLASSIFICATIONACHIEVEMENTWASGAINEDBYTHEHYBRIDMETHOD,WHICHRESULTEDIN81OVERALLACCURACYHEALEY’SRESEARCHHEALEY,2000WASFOCUSEDONRECOGNIZINGSTRESSLEVELSOFDRIVERSBYMEASURINGANDANALYZINGTHEIRPHYSIOLOGICALSIGNALSSKINCONDUCTANCE,HEARTACTIVITY,RESPIRATION,ANDMUSCLEACTIVITYDURINGTHEEXPERIMENTPARTICIPANTSOFTHISSTUDYDROVEINAPARKINGGARAGE,INACITY,ANDONAHIGHWAYRESULTSSHOWEDTHATTHEDRIVERS’STRESSCOULDBERECOGNIZEDASBEINGRESTIERESTINGINTHEPARKINGGARAGE,CITYIEDRIVINGINTHEBOSTONSTREETS,ANDHIGHWAYIETWOLANEMERGEONTHEHIGHWAYWITH96ACCURACY22OURPRELIMINARYEMOTIONELICITATIONANDRECOGNITIONEXPERIMENTSINOUREMOTIONELICITATIONEXPERIMENTWEUSEDMOVIECLIPSANDDIFFICULTMATHEMATICALQUESTIONSTOELICITSIXEMOTIONSSADNESS,ANGER,SURPRISE,FEAR,FRUSTRATION,ANDAMUSEMENTANDANONINVASIVEWIRELESSWEARABLECOMPUTER–BODYMEDIASENSEWEARARMBANDFIGURE2–TOCOLLECTTHEPHYSIOLOGICALSIGNALSOFOURPARTICIPANTSGALVANICSKINRESPONSE,HEARTRATE,ANDTEMPERATUREFIGURE2BODYMEDIASENSEWEARARMBANDMATHEMATICALQUESTIONSWEREUSEDTOELICITFRUSTRATIONANDMOVIECLIPSWEREUSEDTOELICITTHEOTHERFIVEEMOTIONSMOVIECLIPSWERECHOSENBYCONDUCTINGAPILOTSTUDYTHATWASGUIDEDBYTHEPREVIOUSRESEARCHOFGROSSAND

簡(jiǎn)介：視頻會(huì)議通過(guò)視頻會(huì)議通過(guò)TCP/IP協(xié)議在個(gè)人電腦上的實(shí)現(xiàn)協(xié)議在個(gè)人電腦上的實(shí)現(xiàn)BYJOHNFMCGOWAN,PHDDESKTOPVIDEOEXPERTCENTERAPRIL24,1997總體簡(jiǎn)介總體簡(jiǎn)介目前，視頻會(huì)議系統(tǒng)通過(guò)TCP/IP協(xié)議的局域網(wǎng)和廣域網(wǎng)在個(gè)人電腦上大量的安裝和配置仍具有許多挑戰(zhàn)。除了視頻會(huì)議應(yīng)用程序之外，還有視頻會(huì)議系統(tǒng)的使用和在個(gè)人計(jì)算機(jī)之內(nèi)頻繁地修改如下五個(gè)子系統(tǒng)等挑戰(zhàn)。?視頻顯示?視頻采集?音頻輸出?音頻輸入?TCP/IP網(wǎng)絡(luò)（包括網(wǎng)卡和TCP/IP的軟件）每個(gè)子系統(tǒng)因本身就是較為復(fù)雜的。因此，在視頻會(huì)議系統(tǒng)的設(shè)施和配置期間，問(wèn)題可能會(huì)發(fā)生系統(tǒng)的任何地方。此外，程序又必須在用戶端安裝，而在大多數(shù)個(gè)人計(jì)算機(jī)上，視頻會(huì)議系統(tǒng)硬件和軟件并不是標(biāo)準(zhǔn)的。通常來(lái)講，不同的個(gè)人計(jì)算機(jī)上的軟硬件導(dǎo)致在每臺(tái)個(gè)人計(jì)算機(jī)安裝的硬件和軟件變化極大。即使一個(gè)經(jīng)驗(yàn)豐富的安裝高手在一臺(tái)特殊用戶的個(gè)人計(jì)算機(jī)上也可能遇到陌生的情況。所有版本的WINDOWSWINDOWS31,WINDOWSFORWORKGROUPS31,WINDOWS95,WINDOWS的即將發(fā)布的“MEMPHIS”,以及WINDOWSNT都是建立在一個(gè)有處理系統(tǒng)部件和VENDORSUPPLIED設(shè)備驅(qū)動(dòng)程序的復(fù)雜的系統(tǒng)之上的。一些設(shè)備驅(qū)動(dòng)程序?qū)嶋H上是通過(guò)硬件設(shè)備實(shí)現(xiàn),如視頻顯示卡,視頻采集板、聲卡、網(wǎng)卡等。其他的設(shè)備驅(qū)動(dòng)程序與硬件設(shè)備驅(qū)動(dòng)性能有很多共同之處,但除TCP/IP協(xié)議的實(shí)施和具有系統(tǒng)特征的軟件之外。設(shè)備驅(qū)動(dòng)程序是非常強(qiáng)大的,因?yàn)樵谒邪姹镜腤INDOWS系統(tǒng)中他們?cè)诮尤胗搀w和軟件上都處在一個(gè)特權(quán)水平上。即使是在WINDOWS95,WINDOWS31中,系統(tǒng)仍允許多個(gè)應(yīng)用程序占用操作系統(tǒng)的內(nèi)存或其他的應(yīng)用程序的內(nèi)存。設(shè)備驅(qū)動(dòng)操作的特權(quán)級(jí)別就意味著驅(qū)動(dòng)比一個(gè)應(yīng)用程序造成更為嚴(yán)重的損害。例如，難以言喻的奇怪的系統(tǒng)崩潰以及以及設(shè)備間沖突事故。此外，大多數(shù)的系統(tǒng)配置和安裝問(wèn)題都和驅(qū)動(dòng)有關(guān)。盡管在此領(lǐng)域中將會(huì)遇到很多的問(wèn)題不可能被預(yù)期,本文將會(huì)給出通過(guò)TCP/IP的網(wǎng)絡(luò)實(shí)現(xiàn)的個(gè)人電腦上的視頻會(huì)議系統(tǒng)的有關(guān)整個(gè)安裝和配置問(wèn)題的一個(gè)概述。視頻顯示視頻顯示視頻會(huì)議系統(tǒng)的重點(diǎn)在于個(gè)人計(jì)算機(jī)的視頻顯示視頻適配器和視頻驅(qū)動(dòng)程序。視頻顯示驅(qū)動(dòng)程序可以包含細(xì)微的錯(cuò)誤，這將導(dǎo)致與應(yīng)用程序發(fā)生沖突其中也包括與視頻會(huì)議的應(yīng)用程序發(fā)生沖突，造成包括一般保護(hù)錯(cuò)誤和在屏幕上更新等問(wèn)題在內(nèi)的許多問(wèn)題。一般來(lái)說(shuō)，要確保視頻卡具有的是最新驅(qū)動(dòng)程序。大部分主流的視頻卡和視頻芯片供應(yīng)商都會(huì)在其網(wǎng)站和FTP站點(diǎn)提供相應(yīng)產(chǎn)品的驅(qū)動(dòng)程序。對(duì)于部分用戶有可能使用特殊顯示卡驅(qū)動(dòng)而不是一般的視頻芯片驅(qū)動(dòng)程序的情況，用戶應(yīng)向芯片制造商獲取相應(yīng)的驅(qū)動(dòng)程序。例如，對(duì)于鉆石系列的多媒體視頻卡，無(wú)論是鉆石顯卡還是S3顯卡，其供應(yīng)商在生產(chǎn)鉆石系列芯片時(shí)都提供了相應(yīng)的驅(qū)動(dòng)程序。在鉆石系列中，同S3相比大大增強(qiáng)了鉆石顯卡的驅(qū)動(dòng)程序。的ISA和PCI視頻采集卡有時(shí)會(huì)遇到資源沖突，這是由于即插即型卡設(shè)計(jì)實(shí)現(xiàn)的缺陷所造成的。視頻采集是通過(guò)VFW驅(qū)動(dòng)程序來(lái)進(jìn)行處理的。在WINDOWS31和WINDOWSFORWORKGROUPS系統(tǒng)下所提供的最新的16位的VFW程序是VFW11E版本。而在WINDOWS95系統(tǒng)中提供了一個(gè)帶有視頻壓縮功能的32位的VFW版本，此版本和VFW11E版還有一些未知的差異和聯(lián)系，WINDOWS95系統(tǒng)中所提供的這個(gè)版本的VFW已經(jīng)具有視頻采集的功能了?；赪INDOWS95OEM服務(wù)版本2（OSR2）的ACTIVEMOVIE10，可以在WINDOWS95的早期版本中安裝，但它不提供任何對(duì)視頻拍攝的支持。視頻采集卡的軟件安裝過(guò)程中應(yīng)安裝VFW視頻采集驅(qū)動(dòng)程序。此驅(qū)動(dòng)是有如下行定義的MSVIDEOXXXXDRV在MICROSOFTWINDOWSSYSTEMINI文件中進(jìn)行驅(qū)動(dòng)選擇。視頻顯示應(yīng)處理的問(wèn)題視頻顯示應(yīng)處理的問(wèn)題?重新啟動(dòng)?檢查IRQ或者其他資源是否沖突?檢查視頻采集攝像頭和網(wǎng)線連接若有電氣連接故障微調(diào)網(wǎng)線?檢查視頻采集卡是否在主板上插裝好?用顯卡檢查視頻會(huì)議系統(tǒng)的錯(cuò)誤記錄文檔?確保有正確或者最新的顯卡適配器驅(qū)動(dòng)?用WINDOWS系統(tǒng)的控制面板重裝顯卡驅(qū)動(dòng)?使用顯卡安裝程序重新安裝顯卡驅(qū)動(dòng)?在WINDOWS31下，通過(guò)編輯SYSTEMINI中手動(dòng)安裝驅(qū)動(dòng)程序（請(qǐng)備份原始SYSTEMINI）?安裝新的或不同的顯卡視頻會(huì)議的應(yīng)用程序視頻會(huì)議的應(yīng)用程序視頻會(huì)議系統(tǒng)的客戶端視頻會(huì)議系統(tǒng)的客戶端安裝視頻會(huì)議系統(tǒng)的第一步都來(lái)自于應(yīng)用程序的安裝。這些通常是INSTALLSHIELD或其它商業(yè)公司提供的安裝程序。安裝程序?qū)惭b包括所有應(yīng)用的軟件組件。安裝程序經(jīng)常也會(huì)伴隨著安裝視頻會(huì)議系統(tǒng)所需的視頻捕獲卡和聲卡。不幸的是，安裝程序有時(shí)會(huì)安裝失敗。如果懷疑程序安裝的有問(wèn)題，請(qǐng)先卸載視頻會(huì)議系統(tǒng)的程序，然后重新運(yùn)行安裝程序進(jìn)行安裝。在絕大多數(shù)情況下，這樣操作都會(huì)有所幫助。總結(jié)總結(jié)視頻會(huì)議系統(tǒng)通過(guò)TCP/IP網(wǎng)絡(luò)在個(gè)人電腦上的實(shí)現(xiàn)可能會(huì)涉及大量的個(gè)人電腦和網(wǎng)絡(luò)的安裝和配置。不幸的是，在個(gè)人電腦上安裝和配置系統(tǒng)的硬件和軟件是很復(fù)雜一件事。但在個(gè)人電腦上安裝和配置系統(tǒng)的硬件和軟件也不是像研究火箭科學(xué)那樣艱難。它需要有很多的步驟來(lái)去實(shí)現(xiàn)，特別是對(duì)于像視頻會(huì)議系統(tǒng)這樣復(fù)雜的產(chǎn)品。單獨(dú)拿出每一步來(lái)說(shuō)都很簡(jiǎn)單，但很多簡(jiǎn)單的步驟組合在一起，導(dǎo)致了一個(gè)相當(dāng)復(fù)雜的過(guò)程。技術(shù)支持人員或用戶必須避免被繁雜的步驟和頻頻出現(xiàn)的各種奇怪的問(wèn)題所嚇倒，哪怕問(wèn)題是出現(xiàn)在WINDOWS系統(tǒng)上的安裝問(wèn)題。

簡(jiǎn)介：航空攝影測(cè)量中的立體模型重建摘要本文描述的是現(xiàn)代航空攝影測(cè)量的操作問(wèn)題和基本的技術(shù)需要。當(dāng)立體模型重建時(shí)，利用航空攝影測(cè)量中的外方位元素決定攝影測(cè)量點(diǎn)的精度和在對(duì)應(yīng)的模型點(diǎn)中的Y視差分析。真正的航空攝影，在圖像的比例，由12500至160000，與DGPS/IMU的數(shù)據(jù)來(lái)源于各種地形，在中國(guó)由我們的POS支持的大型區(qū)域網(wǎng)平差計(jì)劃WUCAPS處理。實(shí)證結(jié)果證實(shí)來(lái)源于大型區(qū)域網(wǎng)平差的外方位元素的精度符合地形勘測(cè)規(guī)范的要求。然而，通過(guò)POS確定的外方位元素的精度不能滿足地形勘測(cè)規(guī)范的要求。關(guān)鍵詞空中三角測(cè)量（AT）；GPS（全球定位系統(tǒng)）；POS（定位和定向系統(tǒng)）；立體模型重建；地面控制點(diǎn)（GCPS）；精度導(dǎo)言航空攝影測(cè)量是從空中影像獲得關(guān)于地球表面的三維空間信息的科學(xué)和技術(shù)。攝影點(diǎn)的決定，其中通過(guò)使用圖像找出地面對(duì)象，是依據(jù)識(shí)別物體的遙感。并且問(wèn)題的關(guān)鍵是迅速和準(zhǔn)確地確定圖像的位置和行為上的即時(shí)影像。通過(guò)基于分布式地面控制點(diǎn)的空中三角測(cè)量滿足這一目標(biāo)。隨著空間定位技術(shù)的發(fā)展，遙感技術(shù)和計(jì)算機(jī)科學(xué)，以及空中三角測(cè)量的演變和發(fā)展走向沒(méi)有地面控制點(diǎn)的數(shù)字化勘測(cè)。早在1950年，攝影科學(xué)家就開(kāi)始研究如何利用各種輔助數(shù)據(jù)，以減少地面控制點(diǎn)的需要。然而，由于技術(shù)的局限性，方法沒(méi)有變成現(xiàn)實(shí)。直到20世紀(jì)70年代，出現(xiàn)了美國(guó)的全球定位系統(tǒng)（GPS），在航空攝影過(guò)程中人們僅得到通過(guò)載波相位差分全球定位系統(tǒng)（DGPS）技術(shù)來(lái)確定曝光駐地的位置即航攝照片的三個(gè)線性元素，用于執(zhí)行空中三角測(cè)量（簡(jiǎn)稱GPS支持AT）可以減少攝影對(duì)地面控制點(diǎn)的依賴，縮短測(cè)繪周期；并降低生產(chǎn)成本，在攝影測(cè)量的領(lǐng)域觸發(fā)革命。然而，GPS支持AT在空中攝影測(cè)量的操作是有利的，主要是在浩大和困難的區(qū)域，在中小型的比例尺，而不是帶狀區(qū)域和城市大比例尺測(cè)圖。在20世紀(jì)90年代，人們開(kāi)始探討采用GPS/LNS集成系統(tǒng)也稱POS獲取照片的位置和姿態(tài)即利用GPS獲得曝光駐地的位置，由IMU獲得圖像姿態(tài)元素，目的是照片的定向，最終目標(biāo)是取代區(qū)域空中。三角測(cè)量程序。現(xiàn)代數(shù)字?jǐn)z影測(cè)量學(xué)在4D產(chǎn)品DEM，DOM，DLG，DRG的自動(dòng)化的生產(chǎn)和空間數(shù)據(jù)庫(kù)的更新中將扮演一個(gè)重要角色。本文將介紹航空攝影測(cè)量學(xué)和相關(guān)的技術(shù)需要在當(dāng)前的操作應(yīng)用，特別是，攝影信息鏈的幾何定位精度可從計(jì)劃的設(shè)計(jì)應(yīng)如圖3所示，即不同模式的空中攝影。23數(shù)字映射從理論上說(shuō)，在得到準(zhǔn)確的內(nèi)外方位元素的圖像之后，可衡量的立體模型可利用模型重建恢復(fù)，其中我們可以做地形的測(cè)繪以及物體的自動(dòng)運(yùn)行。然而，目前的四維產(chǎn)品的生產(chǎn)工藝是單張照片的內(nèi)定向立體像對(duì)的相對(duì)定向?單一模型的絕對(duì)定向立體模型的測(cè)繪。該方法的模型只有通過(guò)POS支持??的航空攝影測(cè)量直接地理參考恢復(fù)。3實(shí)驗(yàn)和分析航攝定位有兩種方法。其中之一被稱作區(qū)域空中三角測(cè)量，關(guān)于圖像點(diǎn)的坐標(biāo)，地面控制點(diǎn)的坐標(biāo)和（或）圖像的外方位元素加權(quán)觀測(cè)值，并結(jié)合大型區(qū)域網(wǎng)平差來(lái)解決圖像定向參數(shù)和目標(biāo)點(diǎn)的空間坐標(biāo)，來(lái)作為方向控制點(diǎn)的立體模型繪圖和做高度精確的幾何定位的應(yīng)用。為不同尺度和地形類型的航空攝影測(cè)量，航攝照片辦公室操作的地形圖規(guī)格定義了各自空中三角測(cè)量方法，地面控制計(jì)劃，以及傳輸點(diǎn)精度的具體標(biāo)準(zhǔn)。這種方法已被建立并得到了廣泛的應(yīng)用。另一種是所謂的直接地理參考，假定高精確的圖像外方位元素是可以得到的，在立體像對(duì)中通過(guò)使用圖像坐標(biāo)系統(tǒng)的同名像點(diǎn)的坐標(biāo)，利用空間交會(huì)計(jì)算出對(duì)應(yīng)的目標(biāo)點(diǎn)物體的空間坐標(biāo)。這種方法直接地確定對(duì)象的位置，因此4D產(chǎn)品可以被生產(chǎn)。然后本文將主要討論當(dāng)利用各種方式獲得圖像的外方位元素時(shí)，如何定位精度可以完成立體模型的Y視差。

簡(jiǎn)介：VIRTUALREALITYMODELOFAIRPOLLUTIONMMUDROVA,APROCHAZKA,ANDMKOLNOVAINSTITUTEOFCHEMICALTECHNOLOGY,DEPARTMENTOFCOMPUTINGANDCONTROLENGINEERINGABSTRACTTHEPAPERISDEVOTEDTOTHEDESCRIPTIONOFVIRTUALREALITYMODELGENERATIONUSINGTHESYSTEMMATLABANDITSVIRTUALREALITYTOOLBOXTHESELECTEDPOSSIBILITIESOFINTERCONNECTIONOFBOTHSYSTEMSMATLABANDVRMLAREDEMONSTRATEDBYMEANSOFVISUALISATIONOFTWODIMENSIONALINTERPOLATIONOFAIRPOLLUTIONDATA1INTRODUCTIONPRESENTATIONOFTHREEDIMENSIONALDATACURRENTLYREPRESENTSAVERYTOPICALTHEMEINMANYAREAS,ANDNOTONLYTECHNICALONESCLEARANDINTELLIGIBLEARRANGEMENTSOFINFORMATIONINTHE3DMODELISNECESSARYFOREXAMPLEINMEDICINEANDITISUSEDMOREANDMOREFREQUENTLYINOTHERAREASRESULTSOFINFORMATIONPROCESSINGUSINGCOMPLEXMATHEMATICALTOOLSCANNATURALLYLEADTOFORMULATIONOFATHREEDIMENSIONALGRAPHICALMODELITHASBEENPOSSIBLETOOBSERVEORPROCESSSPATIALDATAFORALLUSERSOFPERSONALCOMPUTERSSINCETHEVRMLVIRTUALREALITYMODELINGLANGUAGEHADBEENDEVELOPED5,6,7THEMOSTFREQUENTLYUSEDINTERNETBROWSERSMSINTERNETEXPLORERANDNETSCAPENAVIGATORHAVEAVRMLVIEWERBUILTINTHEREAREALSOMANYOTHERFREEWAREPLUGINMODULESAVAILABLEONTHEINTERNETWITHWHICHONECANENTERTHEVIRTUALWORLDANDOBSERVEITANDPOSSIBLYCONTROLITASWELLTHANKSTOTHESEFACTS,ITISEXPECTEDTHATAREASOFAPPLICATIONSOF3DMODELINGWILLGROWTHEGOALOFTHISPAPERISTODESCRIBETHEPROCESSOFFORMULATIONOFA3DMODELOFAIRPOLLUTIONLEVELINTHECZECHREPUBLICUSINGTHESYSTEMMATLAB,ANDITSEXPORTTOVRML2BACKGROUNDTHEVIRTUALREALISTICSCENEESTABLISHESTOGENERALLYHAVETWOKINDSOFPATHSADOPTINGOPENGL,VRML，DIRECT3DISTHE1ST。FORNONCALCULATORPROFESSIONALPERSONNELTOSAY,MAKEUSEOFOPENGLTOWRITEACOMPLICATED3DSATELLITEOBSERVATIONSANDNAMELYCONCENTRATIONSOFDUSTPARTICLESINTHEAIRTHEONEYEARSTIMESERIESREPRESENTINGCURRENTCONCENTRATIONSOFTHEPM10POLLUTIONOBTAINEDFROMTHEAIMSTATIONSHASBEENKINDLYPROVIDEDBYTHECZECHHYDROMETEOROLOGICALINSTITUTEINPRAGUETHEDATAOBSERVEDATLOCATIONSPRESENTEDINFIG1WEREPREPROCESSEDBYMEANSOFCOMPENSATIONFORVALUESOFMEASUREMENTFAILURESANDELIMINATIONOFDISTANTVALUES4FIGURE1THEAIMSTATIONLAYOUTINTHECZECHREPUBLICWITHMARKEDDELAUNAYTRIANGULATION4TWODIMENSIONALINTERPOLATIONMETHODSITISPOSSIBLETOUSEVARIOUSINTERPOLATIONMETHODSFORESTIMATIONOFVALUESOFANOBSERVEDPOLLUTANTINOTHERNONMEASUREDPOINTSSPECIEDBYASELECTEDORTHOGONALNETTHEDESCRIPTIONANDCOMPARISONOFTHESEPROBLEMSHASBEENPRESENTEDIN4ITISPOSSIBLETOUSETHESIMPLESTMETHODOFTHE0THORDERTHENEARESTNEIGHBOURMETHODTHATINTERPOLATESTHESURROUNDINGSOFAGIVENSTATIONBYTHESAMEVALUEMEASUREDINTHESTATIONVORONOIDIAGRAMS1LIMITTHESURROUNDINGBORDERSRELATEDDELAUNAYTRIANGULATIONMETHODPRESENTEDINFIG1ISUSEDFORHIGHERORDERINTERPOLATIONBILINEAR,CUBIC,SPLINEASELECTEDMETHODAPPLIEDTOTHEARRAYOFCALCULATEDCONCENTRATIONSVALUESRESULTSINTHEORTHOGONALNETDE_NINGLONGITUDEANDLATITUDETHETHREEDIMENSIONALMODELREPRESENTSANATURALPRESENTATIONOFTHESERESULTS

簡(jiǎn)介：中文中文5640字出處出處STUDIESINPLANTSCIENCE,2001,8185196外文翻譯題目目植物土壤和肥料中硅的分析植物土壤和肥料中硅的分析土壤、植物和肥料中硅的分析方法2就是SIO2的重量。1122光譜光譜現(xiàn)代光譜技術(shù)的發(fā)展導(dǎo)致稱重方法被光譜法取代，光譜法更快速，更適合大量樣本的分析。這種方法常用于溶解含有硅的物質(zhì)。11221為光譜分析溶解硅為光譜分析溶解硅硅，存在很多物質(zhì)中，可以被強(qiáng)堿溶解像NA2CO3，NAOH，LIBO2，LIB2O3，氫氧化鈉是個(gè)好的選擇，因?yàn)闃悠房梢栽诒阋说逆囒釄逯械蜏剡M(jìn)行快速反應(yīng)（KILMER，1965）冷卻后，催化劑被酸溶解，硅可以在光譜儀中進(jìn)行測(cè)定。硅，存在很多物質(zhì)中，也可以在封閉消化系統(tǒng)中溶解，CSD技術(shù)和熱解的方法相比對(duì)樣品個(gè)體需要更少的關(guān)注，因此它適合測(cè)試大量樣品。對(duì)于典型的CSD溶解技術(shù)是將樣品與王水（硝酸和鹽酸）放在一個(gè)密閉的消化容器（有時(shí)稱做“消化炸彈”）內(nèi)進(jìn)行反應(yīng)，這個(gè)容器在干燥的烘箱內(nèi)100到110攝氏度下加熱2小時(shí)（JONES和DREHER，1996）。冷卻之后，加入H3BO3和樣品再次加熱10到15分鐘，以助于產(chǎn)生沉淀。EILIOTT和SNYDER（1991）發(fā)明了高壓誘導(dǎo)消化法（AID）來(lái)溶解水稻中硅，這種方法只需要用NAOH和H2O2作為反應(yīng)物，器材需要聚乙烯筒和高壓鍋。AID可以一次性處理40個(gè)或更多的樣本。AID利用高壓鍋產(chǎn)生壓力，而不是在消化容器中。BELL和SIMMONS（1997）發(fā)現(xiàn)了NIST和AID之間的差別。他們發(fā)現(xiàn)了NIST標(biāo)注不能識(shí)別硅，他們用AID方法測(cè)定了NIST的樣本確定了硅的含量。NONOZAMSKY（1984）也描述了一種快速的從植物組織中分離硅的方法。用他們的方法把陸生植物在室溫中浸泡在HCL和HF中一晚，過(guò)濾殘?jiān)?1222光譜分析溶解態(tài)的硅光譜分析溶解態(tài)的硅盡管硅可以在氮氧火焰下進(jìn)行原子光譜吸收測(cè)定（AAS）或者ICP方法測(cè)定，但這經(jīng)常決定于手工或原子顏色和更低的器材花費(fèi)、更低的設(shè)備限制。通常后者是更好的，因?yàn)槠涓菀妆挥^察。兩種方法相似，只是硅鉬藍(lán)的方法減少了一部分溶解的過(guò)程。樣本和鉬酸銨進(jìn)行反應(yīng)（KILMER，1965；HALLMARK1982等）加入酒石酸減少磷酸根的干擾。在反應(yīng)后溶液中加入硫酸鈉，1氨基2萘酚4磺酸，在650微米用硅鉬藍(lán)發(fā)，可以檢測(cè)到002MGL1的硅（BUNTING，1944）。后者用原子色譜儀分析大量的樣本。11223非破環(huán)性光譜測(cè)定總硅非破環(huán)性光譜測(cè)定總硅一些現(xiàn)代的技術(shù)已經(jīng)被用于測(cè)定土壤，植物和肥料中總硅的含量，而無(wú)需進(jìn)行預(yù)分析。X射線熒光光譜也被稱為X射線發(fā)射光譜或X射線光譜化學(xué)分析，通過(guò)硅在土壤和植物中沉淀聚集，盡管存在局限性，但今年來(lái)開(kāi)發(fā)了高科技的設(shè)備，使其可以快速分析各種樣品。近紅外光譜（NIRS）也是對(duì)樣品中的硅不產(chǎn)生破環(huán)。這種方法有一種可靠的基礎(chǔ)測(cè)樣品中的水和氮，但其他部分很少。統(tǒng)計(jì)協(xié)會(huì)和NIRS標(biāo)準(zhǔn)樣品建立一個(gè)大的數(shù)據(jù)庫(kù)，但標(biāo)準(zhǔn)和未知組成部分的關(guān)系可以通過(guò)古典的方法分析。由于其快速，分析簡(jiǎn)單，低花費(fèi)和在操作方面的改進(jìn)，NIRS

簡(jiǎn)介：外文文獻(xiàn)外文文獻(xiàn)提升自行車使用的設(shè)計(jì)策略研究提升自行車使用的設(shè)計(jì)策略研究1介紹介紹自行車，一種純粹依靠人力運(yùn)轉(zhuǎn)的機(jī)器，最早是被發(fā)明用來(lái)作為轉(zhuǎn)移和運(yùn)輸?shù)墓ぞ?它一直持續(xù)不斷地在結(jié)構(gòu)上被改進(jìn)以至于現(xiàn)在自行車不僅僅是用來(lái)作為有效的交通工具更是一種物理鍛煉工具和休閑活動(dòng)。2騎自行車可以讓騎車者在25KM/H的狀態(tài)下消耗780千卡路里，讓它變成了一種比其他物理鍛煉更有效的有氧運(yùn)動(dòng)。除此之外，考慮到國(guó)家每年在交通堵塞上付出的總數(shù)達(dá)到了228億元的花費(fèi)，增加1的自行車交通會(huì)產(chǎn)生經(jīng)濟(jì)的效果遠(yuǎn)比分解交通堵塞所引起的效果大，節(jié)省能源，并且也具有環(huán)境效益。并且，一千米自行車騎行可以減少167KG二氧化碳的排放。因此，自行車是一種非常具有環(huán)境效益的交通工具。1然而，現(xiàn)今在南韓的自行車使用率仍然低于發(fā)達(dá)國(guó)家。道路結(jié)構(gòu)以及政府交通政策將機(jī)動(dòng)車放在了首要位置,讓本來(lái)就不利的自行車使用狀況更為糟糕。自行車交通換乘在南韓只有12，遠(yuǎn)遠(yuǎn)低于日本的14以及荷蘭的27同時(shí)，南韓的自行車量產(chǎn)工業(yè)基礎(chǔ)也被削弱了，將第一占有率的市場(chǎng)轉(zhuǎn)向了中國(guó)生產(chǎn)的自行車。結(jié)果，貿(mào)易逆差大幅惡化以至于現(xiàn)今出口了需求中998的自行車。4這樣一種對(duì)自行車使用的漠不關(guān)心已經(jīng)導(dǎo)致了自行車使用率的降低和相關(guān)產(chǎn)業(yè)的削減。這份研究檢視了自行車設(shè)計(jì)的功能，作為一種自行車使用流行化的重要因素。根據(jù)調(diào)研，這份研究報(bào)告建議結(jié)構(gòu)靠攏那些物質(zhì)基礎(chǔ),社會(huì)基礎(chǔ),和自行車工業(yè)最終，它檢驗(yàn)了自行車設(shè)計(jì)的功能可以在此類的結(jié)構(gòu)內(nèi)容中有所表現(xiàn)。2理解圍繞自行車使用的背景理解圍繞自行車使用的背景2121用5W1H5W1H法在每一頁(yè)你的材料上分析自行車使用的狀況法在每一頁(yè)你的材料上分析自行車使用的狀況這一章分析了自行車使用依靠5W1H法實(shí)現(xiàn)的條件。激活自行車使用首先需要“什么”這個(gè)部分，意思就是說(shuō)，適當(dāng)?shù)墓δ?，結(jié)構(gòu)，和價(jià)格。“誰(shuí)”這個(gè)部分包括使用者的年齡、性別、地位、生活方式等等?！澳睦铩钡牟糠稚婕暗綀D233對(duì)于國(guó)內(nèi)自行車使用環(huán)境的分析對(duì)于國(guó)內(nèi)自行車使用環(huán)境的分析為了對(duì)于國(guó)內(nèi)自行車使用環(huán)境的分析，這一章節(jié)調(diào)查了自行車使用的六個(gè)區(qū)域/形式/內(nèi)容這些范圍來(lái)自臨時(shí)增加的自行車使用的內(nèi)容。31消費(fèi)者缺乏使用自行車的動(dòng)機(jī)消費(fèi)者缺乏使用自行車的動(dòng)機(jī)人們不是十分有動(dòng)機(jī)去使用自行車。根據(jù)一份由公共管理與安全部出示的調(diào)查，66的應(yīng)答者選擇了“缺少興趣”作為不使用自行車的原因。除為了鍛煉身體外，人們?cè)隍T自行車上找不到其他任何的益處那是因?yàn)槠嚱o了他們更快更舒適更安全的通勤體驗(yàn)（去工作場(chǎng)所和學(xué)校）。盡管由于交通堵塞和在鬧市區(qū)的停車?yán)щy帶來(lái)了時(shí)間的失以及金錢的損失，人們?nèi)匀徊辉敢廪D(zhuǎn)向騎自行車。在這種情況下，值得注意的是，在1970年代，荷蘭政府不得不依靠限制汽車的使用并且建造自行車道來(lái)提升自行車使用率。32自行車制造的工業(yè)基礎(chǔ)的減弱自行車制造的工業(yè)基礎(chǔ)的減弱因?yàn)槟享n現(xiàn)存越來(lái)越少的自行車制造的工業(yè)基礎(chǔ)，由中國(guó)制造的廉價(jià)自行車充斥了大部分的自行車供給。這種情況使得使用者可以以很低的價(jià)格購(gòu)買自行車，但是機(jī)械問(wèn)題以及不可靠的耐用度等問(wèn)題上升了。給予自行車發(fā)展和制造的工業(yè)力量已經(jīng)被消耗殆盡，看起來(lái)對(duì)于國(guó)內(nèi)的工業(yè)來(lái)說(shuō)要滿足自行車市場(chǎng)的潛在需求很難。33物質(zhì)基礎(chǔ)的缺乏物質(zhì)基礎(chǔ)的缺乏自行車道的數(shù)量在南韓遠(yuǎn)遠(yuǎn)不夠用。絕大多數(shù)在城市道路上鋪設(shè)的自行車

簡(jiǎn)介：附錄附錄ALABVIEWBASEDINSTRUMENTCURRENTTRANSFORMERCALIBRATORXINAIHALBAOYHSONG1NORTHCHINAELECTRICPOWERUNIVERSITY,BEIJING,CHINA1072062BRUNELUNIVERSITYUKABSTRACTTHEVIRTUALINSTRUMENTVIMAINLYREFERSTOBUILDALLKINDSOFINSTRUMENTSBYSOFTWARESUCHASLABVIEW,WHICHLIKESAREALINSTRUMENTBUILDINACOMPUTERITSMAINCHARACTERISTICSAREFLEXIBILITY,MULTIFUNCTIONS,MULTIPLEUSESFORONEPCCOMPUTER,GIVINGHIGHPERFORMANCE,ANDISLESSCOSTLYINTHISPAPER,THEVITECHNOLOGYISAPPLIEDTOTHETESTANDMEASUREMENTOFINSTRUMENTCURRENTTRANSFORMERTABYUSINGTHELABVIEW,THETAACCURACYCALIBRATORWASDEVELOPEDTHISVIRTUALT4CALIBRATORCANAUTOMATICALLYMEASURETHEACCURACYOFT4ANDCANINDICATETHERATIOERRORANDPHASEERRORCURVESTHETESTSANDCALIBRATIONFORTHETASHOWTHATTHEVIRTUALTACALIBRATORCANBEUSEDINPLACEOFTHETRADITIONALCALIBRATORANDISMUCHBETTERTHANTHETRADITIONALONEKEYWORDSINSTRUMENTCURRENTTRANSFORMERTA,TACALIBRATOR,VIRTUALINSTRUMENTS,LABVIEWIINTRODUCTIONSINCE1992THEVXIBUSREV14STANDARDWASESTABLISHEDBYTHEUNITEDSTATESANDLABVIEWWASPRESENTEDBYTHENATIONALINSTRUMENTSCONL,THEVIRTUALINSTRUMENTVIHAVELAINTHEFOUNDATIONFORITSCOMMERCIALUSETHEMAINCHARACTERISTICOFVIRTUALINSTRUMENTISTHATITMAKESINSTRUMENTSBYSOFTWAREMOSTOFTHETRADITIONALINSTRUMENTCANBEDEVELOPEDBYVITHEVIISAREALINSTRUMENTMADEBYTHEPERSONALCOMPUTERTHEINSTRUMENTCURRENTTRANSFORMERTAISWIDELYUSEDINALLKINDSOFCURRENTMEASUREMENTANDITHASTHEFUNCTIONSOFPROTECTION,ISOLATIONANDEXTENDINGTHEMEASURINGRANGEWITHTHERAPIDDEVELOPMENTOFCOMPUTERMEASUREMENTANDCONTROLTECHNOLOGY,ANDWITHTHESEQUENTEMERGENCEOFCURRENTTRANSFORMERANDTRANSDUCER,THEREISANINCREASINGNUMBEROFCURRENTTRANSFORMERSWITHHIGHACCURACYANDLOWSECONDARYCURRENTTHESTANDARDTASECONDARYCURRENTISUSUALLY1AOR5ASOMENONSTANDARDTASECONDARYCURRENTMAYBE01AORLOWERALTHOUGHWEHAVETHETECHNIQUEOFTABEINGMEASUREDRESPECTIVELYROANDR,R,ARESECONDARYWINDINGSRESISTANCEOFSTANDARDTA,ERRORCURRENTDETECTINGRESISTANCE,BURDENRESISTANCEOFTABEINGMEASUREDRESPECTIVELYTOANDK,TBT,AREVOLTAGESAMPLINGPOINTSWHICHCANCALCULATETHECURRENTINTHISPAPER,ONLYVOLTAGEBETWEENKANDT,VOLTAGEBETWEENTBANDT,AREBEINGMEASUREDANDTHEYREPRESENTTHEVOLTAGEONR,ANDR,RESPECTIVELYINGENERAL,THETACALIBRATORSPRINCIPLEOFTHESAMPLERESISTANCESHOULDBE1）ITCANNOTAFFECTTHEACCURACYOFTHECOMPARISONCIRCUITINTHEIDEALCONDITIONR,ANDRDSHOULDBE0,BUTITCANNOTBESAMPLEDSOTHEREMUSTBESAMPLERESISTANCE,INTHISPAPER,R,ASSHOWNINFIG,ISUSED1）THEMAGNITUDEOFTHESAMPLERESISTANCESHOULDMAKETHESAMPLEDSTANDARDCURRENTANDERRORCURRENTINPRORATAANDSHOULDNOTHAVETOOMUCHDIFFERENCETHESAMPLEDRESISTANCEISSETBYEXPERIMENTR,ISTHESECONDARYSTANDARDCURRENTSAMPLINGRESISTANCEANDCANBE01050,R,ISTHEERRORCURRENTSAMPLINGRESISTANCEANDCANBE,R,ISTHEBURDENRESISTANCEANDITDEPENDSONTHETABEINGMEASUREDESAMPLINGTHEVOLTAGEUOANDU,ONR,ANDR,RESPECTIVELY,THERATIOERRORANDPHASEERRORARESHOWEDONTHELEDTHROUGHSOMEPROCESSANDCALCULATIONSACCORDINGTOTHETAERRORSPHASEDIAGRAM,WHENIOISMAXIMUM,THEVALUEOFIDISTHERATIOERRORWHENIOCHANGESFROMNEGATIVETOPOSITIVEANDEQUALSTO0,THEVALUEOFIDISTHEPHASEERRORFORTHESAMEPRINCIPLE,THERELATIONSHIPISEQUALTOTHEVOLTAGESIGNALU,ANDUDSHOWEDINFIG3AANDBISREPRESENTTHERATIOERRORANDPHASEERRORSEPARATELYTHETASREALRATIOERRORCANDPHASEERROR6CANBEFOUNDOUTTHROUGHPROPERCALCULATION,

簡(jiǎn)介：外文文獻(xiàn)翻譯ADVANCEDCONTROLALGORITHMSEMBEDDEDINAPROGRAMMABLEABSTRACTTHISPAPERPRESENTSANINNOVATIVESELFTUNINGNONLINEARCONTROLLERASPECTADVANCEDCONTROLALGORITHMSFORPROGRAMMABLELOGICCONTROLLERSITISINTENDEDFORTHECONTROLOFHIGHLYNONLINEARPROCESSESWHOSEPROPERTIESCHANGERADICALLYOVERITSRANGEOFOPERATION,ANDINCLUDESTHREEADVANCEDCONTROLALGORITHMSITISDESIGNEDUSINGTHECONCEPTSOFAGENTBASEDSYSTEMS,APPLIEDWITHTHEAIMOFAUTOMATINGSOMEOFTHECONFIGURATIONTASKSTHEPROCESSISREPRESENTEDBYASETOFLOWORDERLOCALLINEARMODELSWHOSEPARAMETERSAREIDENTIFIEDUSINGANONLINELEARNINGPROCEDURETHISPROCEDURECOMBINESMODELIDENTIFICATIONWITHPREANDPOSTIDENTIFICATIONSTEPSTOPROVIDERELIABLEOPERATIONTHECONTROLLERMONITORSANDEVALUATESTHECONTROLPERFORMANCEOFTHECLOSEDLOOPSYSTEMTHECONTROLLERWASIMPLEMENTEDONAPROGRAMMABLELOGICCONTROLLERPLCTHEPERFORMANCEISILLUSTRATEDONAFIELDTESTAPPLICATIONFORCONTROLOFPRESSUREONAHYDRAULICVALVE’S2005ELSEVIERLTDALLRIGHTSRESERVEDKEYWORDSCONTROLENGINEERINGFUZZYMODELLINGINDUSTRIALCONTROLMODELBASEDCONTROLNONLINEARCONTROLPROGRAMMABLELOGICCONTROLLERSSELFTUNINGREGULATORS1INTRODUCTIONMODERNCONTROLTHEORYOFFERSMANYCONTROLMETHODSTOACHIEVEMOREEFFICIENTCONTROLOFNONLINEARPROCESSESTHANPROVIDEDBYCONVENTIONALLINEARMETHODS,TAKINGADVANTAGEOFMOREACCURATEPROCESSMODELSBEQUETTE,1991HENSONMURRAYSMITHSEBORG,1999INDICATETHATWHILETHEREISACONSIDERABLEANDGROWINGMARKETFORADVANCEDCONTROLLERS,RELATIVELYFEWVENDORSOFFERTURNKEYPRODUCTSEXCELLENTRESULTSOFADVANCEDCONTROLCONCEPTS,BASEDONFUZZYPARAMETERSCHEDULINGTAN,HANG,BABUSˇKA,OOSTERHOFF,OUDSHOORN,GUNDALA,HOO,HA¨GLANDSECTION3GIVESABRIEFDESCRIPTIONOFTHECTANDFINALLY,SECTION4DESCRIBESTHEAPPLICATIONOFTHECONTROLLERTOAPILOTPLANTWHEREITISUSEDFORCONTROLOFTHEPRESSUREDIFFERENCEONAHYDRAULICVALVEINAVALVETESTAPPARATUS2RUNTIMEMODULETHERTMOFTHEASPECTCONTROLLERCOMPRISESASETOFMODULES,LINKEDINTHEFORMOFAMULTIAGENTSYSTEMFIG1SHOWSANOVERVIEWOFTHERTMANDITSMAINMODULESTHESIGNALPREPROCESSINGAGENTSPA,THEONLINELEARNINGAGENTOLA,THEMODELINFORMATIONAGENTMIA,THECONTROLALGORITHMAGENTCAA,THECONTROLPERFORMANCEMONITORCPM,ANDTHEOPERATIONSUPERVISOROS21MULTIFACETEDMODELMFMTHEASPECTCONTROLLERISBASEDONTHEMULTIFACETEDMODELCONCEPTPROPOSEDBYSTEPHANOPOULUS,HENNING,ANDLEONE1990ANDINCORPORATESSEVERALMODELFORMSREQUIREDBYTHECAAANDTHEOLASPECIFICALLY,THEMFMINCLUDESASETOFLOCALFIRSTANDSECONDORDERDISCRETETIMELINEARMODELSWITHTIMEDELAYANDOFFSET,WHICHARESPECIFIEDBYAGIVENSCHEDULINGVARIABLESKTHEMODELEQUATIONOFFIRSTORDERLOCALMODELSIS

簡(jiǎn)介：PROCEEDINGSOFTHEIEEERASINTERNATIONALCONFERENCEONHUMANOIDROBOTSCOPYRIGHT?2001MECHANICALSYSTEMANDCONTROLSYSTEMOFADEXTEROUSROBOTHANDDIRKOSSWALD,HEINZW?RNUNIVERSITYOFKARLSRUHEDEPARTMENTOFCOMPUTERSCIENCEINSTITUTEFORPROCESSCONTROLANDROBOTICSIPRENGLERBUNTERING8BUILDING4028D76131KARLSRUHEEMAILOSSWALDIRAUKADE,WOERNIRAUKADEABSTRACTINRECENTYEARSNUMEROUSROBOTSYSTEMSWITHMULTIFINGEREDGRIPPERSORHANDSHAVEBEENDEVELOPEDALLAROUNDTHEWORLDMANYDIFFERENTAPPROACHESHAVEBEENTAKEN,ANTHROPOMORPHICANDNONANTHROPOMORPHICONESNOTONLYTHEMECHANICALSTRUCTUREOFSUCHSYSTEMSWASINVESTIGATED,BUTALSOTHENECESSARYCONTROLSYSTEMWITHTHEHUMANHANDASANEXEMPLAR,SUCHROBOTSYSTEMSUSETHEIRHANDSTOGRASPDIVERSEOBJECTSWITHOUTTHENEEDTOCHANGETHEGRIPPERTHESPECIALKINEMATICABILITIESOFSUCHAROBOTHAND,LIKESMALLMASSESANDINERTIA,MAKEEVENCOMPLEXMANIPULATIONSANDVERYFINEMANIPULATIONSOFAGRASPEDOBJECTWITHINTHEOWNWORKSPACEOFTHEHANDPOSSIBLESUCHCOMPLEXMANIPULATIONSAREFOREXAMPLEREGRASPINGOPERATIONSNEEDEDFORTHEROTATIONOFAGRASPEDOBJECTAROUNDARBITRARYANGLESANDAXISWITHOUTDEPOSITINGTHEOBJECTANDPICKINGITUPAGAININTHISPAPERANOVERVIEWONTHEDESIGNOFSUCHROBOTHANDSINGENERALISGIVEN,ASWELLASAPRESENTATIONOFANEXAMPLEOFSUCHAROBOTHAND,THEKARLSRUHEDEXTEROUSHANDIITHEPAPERTHENENDSWITHTHEPRESENTATIONOFSOMENEWIDEASWHICHWILLBEUSEDTOBUILDANENTIRENEWROBOTHANDFORAHUMANOIDROBOTUSINGFLUIDICACTUATORSKEYWORDSMULTIFINGEREDGRIPPER,ROBOTHAND,FINEMANIPULATION,MECHANICALSYSTEM,CONTROLSYSTEM1INTRODUCTIONTHESPECIALRESEARCHAREAHUMANOIDROBOTSFOUNDEDINKARLSRUHE,GERMANYINJULY2001ISAIMEDATTHEDEVELOPMENTOFAROBOTSYSTEMWHICHCOOPERATESANDINTERACTSPHYSICALLYWITHHUMANBEINGSINNORMALENVIRONMENTSLIKEKITCHENORLIVINGROOMSSUCHAROBOTSYSTEMWHICHISDESIGNEDTOSUPPORTHUMANSINNONSPECIALIZED,NONINDUSTRIALSURROUNDINGSLIKETHESEMUST,AMONGMANYOTHERTHINGS,BEABLETOGRASPOBJECTSOFDIFFERENTSIZE,SHAPEANDWEIGHTANDITMUSTALSOBEABLETOFINEMANIPULATEAGRASPEDOBJECTSUCHGREATFLEXIBILITYCANONLYBEREACHEDWITHANADAPTABLEROBOTGRIPPERSYSTEM,ASOCALLEDMULTIFINGEREDGRIPPERORROBOTHANDTHEHUMANOIDROBOT,WHICHWILLBEBUILTINTHEABOVEMENTIONEDRESEARCHPROJECT,WILLBEEQUIPPEDWITHSUCHAROBOTHANDSYSTEMTHISNEWHANDWILLBEBUILTBYTHECOOPERATIONOFTWOINSTITUTES,THEIPRINSTITUTEFORPROCESSCONTROLANDROBOTICSATTHEUNIVERSITYOFKARLSRUHEANDTHEIAIINSTITUTEFORAPPLIEDCOMPUTERSCIENCEATTHEKARLSRUHERESEARCHCENTERBOTHORGANIZATIONSALREADYHAVEEXPERIENCEINBUILDINGSUCHKINDOFSYSTEMS,BUTFROMSLIGHTLYDIFFERENTPOINTSOFVIEWTHEKARLSRUHEDEXTEROUSHANDIISEEFIGURE1BUILTATTHEIPR,WHICHISDESCRIBEDHEREINDETAIL,ISAFOURFINGEREDAUTONOMOUSGRIPPERTHEHANDSBUILTATTHEIAISEEFIGURE17AREBUILTASPROSTHESISFORHANDICAPPEDPEOPLETHEAPPROACHTAKENSOFARWILLBEPRESENTEDANDDISCUSSEDINTHEFOLLOWINGSECTIONS,ASITFOUNDSTHEBASISFORTHENOVELHANDOFTHEHUMANOIDROBOTFIGURE1KARLSRUHEDEXTROUSHANDIIFROMIPRPROCEEDINGSOFTHEIEEERASINTERNATIONALCONFERENCEONHUMANOIDROBOTSCOPYRIGHT?2001GRASPSTATESENSORSPROVIDEINFORMATIONABOUTTHECONTACTSITUATIONBETWEENTHEFINGERANDTHEOBJECTTHISTACTILEINFORMATIONCANBEUSEDTODETERMINETHEPOINTINTIMEOFTHEFIRSTCONTACTWITHTHEOBJECTWHILEGRASPING,ANDTOAVOIDUNDESIREDGRASPS,LIKEGRASPINGATANEDGEORATIPOFTHEOBJECTBUTITCANALSOBEUSEDTODETECTSLIPPAGEOFANALREADYGRASPEDOBJECT,WHICHMIGHTLEADTOALOSSOFTHEOBJECTOBJECTSTATEORPOSESENSORSAREUSEDTODETERMINETHESHAPE,POSITIONANDORIENTATIONOFANOBJECTINTHEWORKSPACEOFTHEGRIPPERTHISISNECESSARYIFTHESEDATAISNOTKNOWNEXACTLY,PRIORTOGRASPINGTHEOBJECTIFTHEOBJECTSTATESENSORSSTILLWORKSONAGRASPEDOBJECTITCANBEUSEDTOCONTROLTHEPOSEPOSITIONANDORIENTATIONOFAGRASPEDOBJECTTOO,EGTODETECTSLIPPAGEDEPENDINGONTHEACTUATORSYSTEMTHEGEOMETRICALINFORMATIONABOUTTHEFINGERJOINTPOSITIONCANBEMEASUREDATTHEMOVEMENTGENERATORORDIRECTLYATTHEJOINTFOREXAMPLEIFTHEREISASTIFFCOUPLINGBETWEENANELECTRICMOTORANDTHEFINGERJOINTTHENTHEJOINTPOSITIONCANBEMEASUREDBYANANGLEENCODERATTHEAXISOFTHEMOTORBEFOREORAFTERTHEGEARTHISISNOTPOSSIBLEIFTHECOUPLINGISLESSSTIFFANDAHIGHPOSITIONPRECISIONISDESIRED34THEMECHANICALSYSTEMOFTHEKARLSRUHEDEXTEROUSHANDIIINORDERTOPERMITMORECOMPLEXMANIPULATIONSLIKEREGRASPINGTHECURRENTKARLSRUHEDEXTEROUSHANDIIKDHIIWASBUILTWITH4FINGERSAND3INDEPENDENTJOINTSPERFINGERITISDESIGNATEDFORAPPLICATIONSININDUSTRIALENVIRONMENTSSEEFIGURE2ANDFORMANIPULATIONOFOBJECTSLIKEBOXES,CYLINDERS,SCREWSORNUTSTHEREFOREASYMMETRIC,NONANTHROPOMORPHICCONFIGURATIONOFFOURIDENTICALFINGERS,EACHROTATEDBY90°WASCHOSENSEEFIGURE3DUETOTHEEXPERIENCESGAINEDWITHTHEFIRSTKARLSRUHEDEXTEROUSHAND,LIKEEGMECHANICALPROBLEMSCAUSEDBYTHEDRIVEBELTSORCONTROLLINGPROBLEMSCAUSEDBYLARGEFRICTIONFACTORS,SOMEDIFFERENTDESIGNDECISIONSWERECHOSENFORTHEKDHIITHEDCMOTORSFORJOINT2AND3OFEACHFINGERAREINTEGRATEDINTOTHEPREVIOUSFINGERLIMBSEEFIGURE4THISPERMITSTHEUSEOFVERYSTIFFBALLSPINDLEGEARSFORTHEFORWARDINGOFTHEMOVEMENTTOTHEFINGERJOINTANGLEENCODERSDIRECTLYONTHEMOTORAXISBEFORETHEGEARAREUSEDASVERYPRECISEPOSITIONSTATESENSORSFIGURE4SIDEVIEWOFTHEKDHII3LASERSENSORSFIXATIONFRAMEONECOMPLETEFINGERCONTROLHARDWAREMICROCONTROLLERFIGURE3TOPVIEWOFTHEKDHIIFIGURE2KDHIIMOUNTEDONANINDUSTRIALROBOT

簡(jiǎn)介：BENDABILITYANDFORMINGBEHAVIOUROFHIGHSTRENGTHSTEELINUBENDINGOPERATIONPKAEWTATIP1,NPRASITKHETKHAN1,AKHANTACHAWANA1,VPREMANOND1,RHATO1,BSRESOMREONG1,NKOGA21KINGMONGKUT’SUNIVERSITYOFTECHNOLOGYTHONBURI,THAILAND2NIPPONINSTITUTEOFTECHNOLOGY,JAPANSUMMARYINTHISWORK,THEBENDABILITYANDFORMINGBEHAVIOUROFHIGHSTRENGTHSTEELSINUBENDINGWERESTUDIEDTHESHEETMATERIALSUSEDINTHEEXPERIMENTSAREJISSAPH440THICKNESS2MM,SPFH590THICKNESS2MMANDSPFC780YTHICKNESS12MMFIRSTLY,MINIMUMBENDRADIUSOFEACHMATERIALWASINVESTIGATEDNEXT,THEEXPERIMENTSTOCOMPARETHREEDIFFERENTMETHODSOFMINIMIZINGSPRINGBACKWERECARRIEDOUTTHEFIRSTMETHODIS,SOCALLEDBOTTOMINGTHATISTHEREDUCTIONOFSHEETTHICKNESSATTHEBOTTOMOFTHEWORKPIECEORATBENDEDANGLEBY10THESECONDONEISBOTTOMOVERBENDING,IE,THEMETHODTOOVERBENDTHEWORKPIECEATBOTTOMBY6OFORTHISMETHOD,THEPUNCHHAVINGACONCAVEBOTTOMSURFACEANDTHEBOTTOMPADHAVINGCORRESPONDEDCONVEXUPPERSURFACEHAVEBEENUSEDTHELASTONEISFLANGEOVERBENDING,IE,THEMETHODTOOVERBENDTHEFLANGEOFWORKPIECEBY6OTHISCANBEDONEBYUSINGTHEPUNCHHAVINGSIDERELIEFANGLETAPERPUNCHTHEPUNCHESANDDIESEDGERADIIARE5MMTHECLEARANCEBETWEENPUNCHANDDIEAREDETERMINEDTOBETHESAMEASMATERIALTHICKNESSTWOKINDSOFSHEETLAYOUTSWEREEXPERIMENTED,IE,THESHEETSWEREPLACEDINORDERTHATTHEIRROLLINGDIRECTIONSWERE1PARALLELAND2PERPENDICULARTOTHEBENDLINETHERESULTSREVEALEDTHATTHESPRINGBACKANGLEINCREASEDWITHTHESTRENGTHOFSHEETMATERIALTHEBOTTOMANDFLANGEOVERBENDINGMETHODSAREMOREEFFECTIVETOREDUCESPRINGBACKTHANBOTTOMINGMETHODINADDITION,FORBOTTOMINGMETHOD,THEFORCEREQUIREDWASABOUT8TIMESHIGHERTHANCONVENTIONALBENDINGFORCE1INTRODUCTIONNOWADAYS,HIGHSTRENGTHSTEELSHEETSHAVEBEENWIDELYUSEDINAUTOMOBILEINDUSTRYINORDERTOREDUCEWEIGHTOFTHEVEHICLESWHICHISSTRONGLYRELATEDTOTHEIRFUELCONSUMPTIONRATE14HOWEVER,ITISGENERALLYKNOWNTHATTHESTRENGTHOFTHESHEETS,WHICHISRELATIVELYHIGHERTHANTHATOFTHECONVENTIONALCARBONSTEELSHEETS,LEADSTOTHEIRLOWFORMABILITYANDHIGHSPRINGBACKOFTHEDEFORMEDPARTSMANYWORKSPROPOSEDTOREDUCESPRINGBACKOFTHEHIGHSTRENGTHSTEELFOREXAMPLES,MORI2PROPOSEDTOCONTROLTHESPRINGBACKOFTHEVBENDEDPARTBYUTILIZINGCNCSERVOPRESSTOREDUCETHESHEETTHICKNESSATBENDANGLENEXT,YAMANO3HASBEENSTUDIEDTOREDUCESIDEWALLCURLOFTHEDRAWBENDEDUSHAPEPARTBYUSINGSOCALLEDOVERRUNINDUCINGPUNCHYOSHIDA4STUDIEDACRASHFORMINGMETHODTOREDUCESPRINGBACKOFTHEPARTMADEOFHIGHSTRENGTHSTEELSHEETYANAGIMOTO5,6SHOWEDTHATSPRINGBACKFREEFORMINGOFHIGHSTRENGTHSTEELSHEETSCOULDBEACHIEVEDBYFORMINGTHESHEETATELEVATEDTEMPERATUREINTHERANGEOFWARMWORKINGTEMPERATUREHIGHERTHAN750KBUTCONSIDERABLYLOWERTHANHOTWORKINGTEMPERATURETHEMETHODSTOREDUCESPRINGBACKUSEDINTHEPREVIOUSWORKSAREMOSTLYBASEDONBOTTOMINGANDOVERBENDINGPRINCIPLESINTHISWORK,THEEXPERIMENTSTOCOMPARETHERESULTSOFTHREEDIFFERENTMETHODSOFMINIMIZINGSPRINGBACKWERECARRIEDOUTINORDERTOVERIFYTHEIREFFECTIVENESSINELIMINATIONTHESPRINGBACKOFHIGHSTRENGTHSTEELSHEETTHOSEMETHODSAREBOTTOMING,FLANGEOVERBENDINGANDBOTTOMOVERBENDING,RESPECTIVELYINADDITION,THEBENDABILITYWHICHISREPRESENTEDBYMINIMUMBENDRADIUSWASALSOINVESTIGATEDFORTHESHEETHAVINGTHESTRENGTHRANGEDFROM440TO780MPA2EXPERIMENTALSETUPANDMETHODOLOGYTHREEKINDSOFSHEETMATERIALS,ASSHOWNINTABLE1,WEREUSEDINTHEEXPERIMENTTHESHEETSWERECUTINTORECTANGULARSHAPEWITHDIMENSIONOF120X50MMTHEWORKPIECESHAVEBEENDEFORMED,BYTHETOOLSINFIG1A,INTOUSHAPEHAVINGDIMENSIONASSHOWNINFIG1BTHEDIESETISSHOWNINFIGTA12ICTP2008THE9THINTERNATIONALCONFERENCEONTECHNOLOGYOFPLASTICITY295ABOTTOMINGBFLANGEOVERBENDINGCBOTTOMOVERBENDINGFIG3THREEDIFFERENTMETHODSOFELIMINATIONSPRINGBACKUSEDINTHEEXPERIMENTS3RESULTSANDDISCUSSIONS31BENDABILITIESMINIMUMBENDRADIUSTHERATIOOFBENDINGFORCEREQUIREDANDSHEETTHICKNESSFOREACHMATERIALARESHOWNINFIG4ITISCLEARLYSHOWNTHATLARGERFORCESAREREQUIREDFORTHEMATERIALHAVINGHIGHERSTRENGTHANDFORTHEPUNCHHAVINGSMALLEREDGERADIUSINCASESOFUSINGTHEPUNCHWITHSHARPEDGERP0,THEREQUIREDFORCESARELARGESTWHICHARE187190TIMESOFTHOSEWHENUSINGTHEPUNCHHAVINGRP5MMTHERESULTSOFMINIMUMBENDRADIUSARESHOWNINTABLE2THEDEFORMEDPARTSWEREOBSERVEDBYBOTHVISUALMETHODANDOPTICALMICROSCOPEFOURDIFFERENTSYMBOLSWEREUSEDTODISTINGUISHTHEQUALITYOFPARTSTHEDEFINITIONOFEACHSYMBOLISINDICATEDBELOWTHESAMETABLETHESAMPLEPICTURES,INTHECASESOFUSINGSHARPEDGEPUNCH,CORRESPONDEDTOEACHSYMBOLARESHOWNINTABLE3ASTHERESULTS,FORALLTHREEKINDSOFSHEETMATERIALS,BENDINGPERPENDICULARTOROLLINGDIRECTIONISEASIERTHANBENDINGPARALLELTOROLLINGDIRECTION,ASGENERALLYKNOWNBENDABILITIES,WHICHAREREPRESENTEDBYMINIMUMBENDRADIUS,BECAMEWORSEWITHINCREASINGOFSTRENGTHOFMATERIALSFORSAPH440,THEWORKPIECESWITHOUTFRACTURECOULDBEOBTAINEDALTHOUGHUSINGTHEPUNCHWITHSHARPEDGERP0WHENBENDINGPERPENDICULARTOROLLINGDIRECTIONONTHEOTHERHAND,SPFH590COULDBESUCCESSFULLYBENDEDIFTHERATIOOFPUNCHRADIUSANDSHEETTHICKNESSWASLARGERTHAN050MOREOVER,THESAMERATIOSHOULDBELARGERTHAN083INTHECASEOFSPFC780YSHEETTHESEMIGHTBEEXPLAINEDBYTHEDIFFERENTVALUESOFTHEDUCTILITYOFTHESHEETMATERIALSTHEMINIMUMBENDRADIUSISSMALLERFORTHEMATERIALHAVINGHIGHERDUCTILITYELONGATIONATBREAKASSHOWNINTABLE132COMPARISONOFDIFFERENTMETHODSOFSPRINGBACKELIMINATIONTHEFORCETRAVELDIAGRAMSOFFORMINGSAPH440WORKPIECESBYCONVENTIONALUBENDING,BOTTOMING,FLANGEOVERBENDINGANDBOTTOMOVERBENDINGARESHOWNINFIG5THEMAXIMUMFORCESREQUIREDFORFIG4FORCESREQUIREDFORUBENDINGOFEACHMATERIALR56OR501T6OR5137108957318514911297244198163129051015202530R0R1R2R5SAPH440SPFH590SPFC780YPUNCHEDGERADIUSRPMMBENDINGFORCE/SHEETTHICKNESSKN/MMICTP2008THE9THINTERNATIONALCONFERENCEONTECHNOLOGYOFPLASTICITY297

簡(jiǎn)介：ORIGINALARTICLEGENERATINGTOOLPATHWITHSMOOTHPOSTURECHANGEFORFIVEAXISSCULPTUREDSURFACEMACHININGBASEDONCUTTER’SACCESSIBILITYMAPLLLIYFZHANGHYLILGENGRECEIVED26MAY2009/ACCEPTED16JULY2010/PUBLISHEDONLINE4AUGUST2010SPRINGERVERLAGLONDONLIMITED2010ABSTRACTINFIVEAXISHIGHSPEEDMILLING,ONEOFTHEKEYREQUIREMENTSTOENSURETHEQUALITYOFTHEMACHINEDSURFACEISTHATTHETOOLPATHMUSTBESMOOTH,IE,THECUTTERPOSTURECHANGEFROMONECUTTERCONTACTPOINTTOTHENEXTNEEDSTOBEMINIMIZEDTHISPAPERPRESENTSANEWMETHODFORGENERATINGFIVEAXISTOOLPATHSWITHSMOOTHTOOLMOTIONANDHIGHEFFICIENCYBASEDONTHEACCESSIBILITYMAPAMAPOFTHECUTTERATAPOINTONTHEPARTSURFACETHECUTTER’SAMAPATAPOINTREFERSTOITSPOSTURERANGEINTERMSOFTHETWOROTATIONALANGLES,WITHINWHICHTHECUTTERDOESNOTHAVEANYINTERFERENCEWITHTHEPARTANDTHESURROUNDINGOBJECTSBYUSINGTHEAMAPATAPOINT,THEPOSTURECHANGERATESALONGTHEPOSSIBLECUTTINGDIRECTIONSCALLEDTHESMOOTHNESSMAPORSMAPATTHEPOINTAREESTIMATEDBASEDONTHEAMAPSANDSMAPSOFALLTHESAMPLEDPOINTSOFTHEPARTSURFACE,THEINITIALTOOLPATHWITHTHESMOOTHESTPOSTURECHANGEISGENERATEDFIRSTSUBSEQUENTLY,THEADJACENTTOOLPATHSAREGENERATEDONEATATIMEBYCONSIDERINGBOTHPATHSMOOTHNESSANDMACHININGEFFICIENCYCOMPAREDWITHTRADITIONALTOOLPATHGENERATIONMETHODS,EG,ISOPLANAR,THEPROPOSEDMETHODCANGENERATETOOLPATHSWITHSMALLERPOSTURECHANGERATEANDYETSHORTEROVERALLPATHLENGTHTHEDEVELOPEDTECHNIQUESCANBEUSEDTOAUTOMATEFIVEAXISTOOLPATHGENERATION,INPARTICULARFORHIGHSPEEDMACHININGFINISHCUTKEYWORDSFIVEAXISMILLINGTOOLPATHGENERATIONCUTTERPOSTURECHANGEMACHININGSTRIPWIDTH1INTRODUCTIONASTHENEEDFORCOMPLEXCOMPONENTSSUCHASTHREEDIMENSIONAL3DMOULDSANDDIESHASRISEN,SCULPTUREDSURFACEMACHININGHASASSUMEDAMOREANDMOREIMPORTANTROLEINMANUFACTURINGFORTHELASTFEWDECADESTHEEMPLOYMENTOFFIVEAXISNUMERICALCONTROLNCMACHINESINSCULPTUREDSURFACEMACHININGOFFERSNUMEROUSADVANTAGESOVERTHREEAXISMODESUCHASSETUPREDUCTION,FASTMATERIALREMOVALRATES,ANDIMPROVEDSURFACEQUALITYTOMAKETHEBESTUSEOFFIVEAXISMACHINING,HOWEVER,PROBLEMSRELATEDTOCOMPLICATIONANDCOMPLEXITYCAUSEDBYTHETWOADDITIONALROTARYAXESHAVETOBESOLVEDONEOFTHECHALLENGINGTASKSISTOAUTOMATICALLYGENERATEERRORFREETOOLPATHWITHOUTUSERINTERACTIONFORMACHININGSCULPTUREDSURFACESINTHEPROCESSPLANNINGOFFIVEAXISFINISHCUT,THETOOLPATHGENERATIONTASKISTOSELECTATOOLPATHPATTERN,GENERATETHECUTTERCONTACTCCPOINTSTHATSATISFYTHEACCURACYREQUIREMENT,ANDDETERMINETHECUTTER’SPOSTUREORIENTATIONATEVERYCCPOINTWITHOUTCAUSINGANYINTERFERENCEDURINGTHISPROCESS,TOENSURETHEQUALITYOFTHEMACHINEDSURFACE,THESMOOTHDYNAMICSOFCUTTERMOTIONISAMUST,IE,THEPOSTURECHANGEFROMONEPOINTTOTHENEXTMUSTBEMINIMIZEDEXTREMECHANGEINCUTTERPOSTURE,WHICHISNECESSARYFORINTERFERENCEAVOIDANCE,ISAMAJORCAUSEFORTHEUNNATURALMOVEMENTOFTHECUTTERANDWILLLEADTOOVERANDUNDERCUTTINGINFIVEAXISFINISHANDUNDESIRABLEIRREGULARITYOFTHESURFACEAPPEARANCE1,2SOFAR,THEREISLIMITEDREPORTEDWORKONOBTAININGTHECUTTERLOCATIONCLDATAWITHSMOOTHCONTINUOUSCHANGEINCUTTERPOSTURESALONGAPRESETPATHANDCUTTINGDIRECTION1–3,ANDTHEREISNOREPORTEDMETHODTHATCANGENERATECLDATAWITHGLOBALOPTIMIZATIONOFCUTTERMOTIONDYNAMICSWITHRESPECTTOACUTTINGDIRECTIONINFIVEAXISFINISHCUTLLLIYFZHANGHYLILGENGDEPARTMENTOFMECHANICALENGINEERING,NATIONALUNIVERSITYOFSINGAPORE,10KENTRIDGECRESCENT,SINGAPORE119260,SINGAPOREEMAILMPEZYFNUSEDUSGINTJADVMANUFTECHNOL201153699–709DOI101007/S0017001028492EFFICIENCY,ANDINPARTICULAR,SMOOTHPOSTURECHANGESUSINGTHEAMAPSANDSMAPSATALLTHESAMPLEDPOINTSONTHESURFACE,THEOPTIMALTOOLPATHSAREGENERATEDSUCHTHATTHECHANGEINCUTTERPOSTUREISMINIMIZEDWHENPASSINGTHROUGHTHEGENERATEDCCPOINTSBESIDES,MACHININGSTRIPWIDTHBETWEENADJACENTPATHSISALSOCONSIDEREDTOACHIEVEHIGHMACHININGEFFICIENCY3THEACCESSIBILITYMAPOFACUTTERATAPOINTTHEACCESSIBILITYMAPAMAPISDEFINEDINRESPECTTOACUTTERPOSITIONEDATAPOINTONTHEPARTSURFACEITREFERSTOTHEPOSTURERANGEINTERMSOFTHETWOROTATIONALANGLES,ANDWITHINTHISRANGE,THECUTTERDOESNOTHAVEANYINTERFERENCEWITHTHEPARTANDTHESURROUNDINGOBJECTSTHEAMAPEFFECTIVELYCHARACTERIZESTHEACCESSIBILITYOFACUTTERTOAPOINT,WHICHPROVIDESIMPORTANTGEOMETRICINFORMATIONFORCUTTERSELECTIONANDINTERFERENCEFREETOOLPATHGENERATIONABRIEFINTRODUCTIONOFAMAPISGIVENHEREASSHOWNINFIG1A,THELOCALFRAMEXL?YL?ZLORIGINATESATTHEPOINTOFINTERESTPCWITHZLAXISALONGTHESURFACENORMALVECTOR,XLAXISALONGTHESURFACEMAXIMUMPRINCIPALDIRECTION,ANDYLAXISALONGTHESURFACEMINIMUMPRINCIPALDIRECTION21ACUTTERPOSTUREL,ΘMEANSTHATTHECUTTER’SAXISINCLINESCOUNTERCLOCKWISEWITHLABOUTYLAXISANDROTATESAΘABOUTZLAXISTHEAMAPOFTHECUTTERATTHISPOINTISREPRESENTEDINL,ΘDOMAININTHELOCALFRAMEINORDERTOFINDTHEAMAPATTHEPOINT,THEFOURACCESSIBLEPOSTURERANGESBASEDONTHEIRRESPECTIVEINTERFERENCEFREEATTRIBUTES,IE,MACHINEAXISLIMITSML,LOCALGOUGINGLG,REARGOUGINGRG,ANDGLOBALCOLLISIONGC,AREFOUNDFIRSTFORIMPLEMENTATION,THEPARTSURFACETOBEMACHINEDISFIRSTLYSAMPLEDINTOMPOINTSATASPECIFICPOINT,THEFEASIBLERANGEOFΘ–LBASEDONMLISFIRSTCALCULATEDΘISTHENUNIFORMLYSAMPLEDINTOKANGLESATEACHDISCRETEΘ,THEMINIMUMLNEEDEDTOELIMINATELGISFOUNDFORRGANDGC,THERANGEOFLATEACHDISCRETEΘTHATISINTERFERENCEFREEFROMALLTHEREMAININGM?1POINTSISIDENTIFIEDTHEAMAPATTHISPOINTISSIMPLYTHEINTERSECTIONOFTHESEFOURACCESSIBLEPOSTURERANGESSEEFIG1BTHEOVERALLALGORITHMFORFINDINGTHEAMAPFORACUTTERATAPOINTONTHEPARTSURFACEISCALLEDTHECUTTERACCESSIBILITYCAALGORITHMOBVIOUSLY,THECAALGORITHMISNUMERICALINNATUREWITHACOMPUTATIONALCOMPLEXITYOFΟKMFORMOREDETAILSABOUTTHEEVALUATIONOFTHEAMAP,READERSCANREFERTO22ADIRECTAPPLICATIONOFTHISAMAPCONCEPTISFORTHEOPTIMALCUTTERSELECTIONTOFINISHAGIVENSCULPTUREDSURFACE22BYAPPLYINGTHECAALGORITHMTOALLTHESAMPLEDPOINTSONAPARTSURFACE,ONECANJUDGEWHETHERACUTTERCANTRAVERSETHEWHOLESURFACEWITHOUTANYINTERFERENCETHEOPTIMALCUTTERCANTHEREFOREBETHELARGESTAVAILABLECUTTERWITHNONEMPTYAMAPSATALLSAMPLEDSURFACEPOINTS4THESMOOTHNESSMAPOFACUTTERATAPOINTSINCETHEAMAPONLYCHARACTERIZESTHEGEOMETRICPROPERTYOFTHECUTTER’SPOTENTIALCONFIGURATIONATAPOINT,ITISNECESSARYTOADDTHEDYNAMICPROPERTYOFTHECUTTERATTHEPOINTTOCOMPLETETHEINFORMATIONSETTHEDYNAMICPROPERTYOFCUTTERISACOMPLEXISSUEINVOLVINGMANYFACTORS,EG,FEEDRATE,CUTTINGLOAD,ANDPATHSMOOTHNESSSINCETHISWORKFOCUSESONFINISHINGTOOLPATHPLANNING,ONLYPATHSMOOTHNESSISCONSIDERED,WHICHISMEASUREDBYTHEPOSTURECHANGERATEPCROFTHECUTTERATTHEPOINTGIVENACCPOINTPIANDNEXTCCPOINTPI1ONAPATH,PCRIISDEFINEDASPCRI?JVIT1?VIJJPIT1?PIJD1TWHEREVIISTHEUNITVECTOROFCUTTERAXISALONGITSPOSTUREΘI,LIATPIINTHEGLOBALFRAMEBEFOREACUTTINGDIRECTIONISSELECTED,ITISNECESSARYTOOBTAINTHEPCRSALONGALLPOSSIBLECUTTINGDIRECTIONS,WHICHISCALLEDTHESMOOTHNESSATHECUTTERINTHELOCALFRAMEBTHEAMAPATPCXLYLPCZLΛΘFIG1THECUTTERAMAPATAPOINTONTHEPARTSURFACEATHECUTTERINTHELOCALFRAMEBTHEAMAPATPCINTJADVMANUFTECHNOL201153699–709701

簡(jiǎn)介：ELSEVIERJOURNALOFMATERIALSPROCESSINGTECHNOLOGY681199725726RJOURNALOFMATERIALSPOROCESS1NGTECHNOBGYADVANCESINTHEPREDSIONMACHININGOFSMALLDEEPHOLESZMWANGEOEZUGWU“,,DSUB“SCHOOLOFENGKWERINGVSTEMSANDDEIGN,SOUTHBANKUNILCRSIO,,LOMTMTSEI04,4,UKHDEPARTMENT/AHCHANICALENGINEERING,VOLTINGHAMTREML_TIRCRSITVVOTLHTGHAMNGI4BU,UKRECEIVED20OCTOBER1995ABSTRACTBASEDONTHEANALYSISOFTHEFORCESACTINGONADEEPHOLEDRILLINGHEADANDTHEUNDERSTANDINGOFTHEBURNISHINGACTIONOFTHECARBIDEGUIDEPADS,ANINVESTIGATIONOFTHEPRECISIONDRILLINGMETHODOFSMALLDEEPHOLESINDIFFICULTTOCUTMATERIALSWASCARRIEDOUTTHEINFLUENCEOFTOOLGEOMETRYANDCUTTINGPARAMETERSCUTTINGSPEEDSANDFEEDRATESONTHESURFACEQUALITYOFTHEDRILLEDHOLESWASSTUDIED,THERESULTSOFWHICHINDICATINGTHAT1020MMSMALLDEEPHOLESOFHIGHTOLERANCEGRADESIT7TOIT9ANDLOWERSURFACEROUGHNESSVALUESRDINTHERANGEOF0216TJMCANBEACHIEVEDANDTHEPROBLEMOFAXIALDEVIATIONOFHOLESDRILEDMINIMISEDUNDEROPTIMISEDCUTTINGPARAMETERSBYMEANSOFTHENEW/IMPROVEDBTADRILL“,,1997ELSEVIERSCIENCESAKEYWORDSDIFFICULTTOCUTMATERIALSSMALLDEEPHOLESPRECISIONDRILLINGSTABILITYBURNISHINGACTION1INTRODUCTIONDEEPHOLEMACHININGISRECOGNISEDASADIFFICULTPROCESSDUETOTHECONFINEDCUTTINGSPACEANDTHEPOORCUTTINGCONDITIONS,DIFFICULTCHIPBREAKINGANDCHIPREMOVAL,ANDCANTILEVEREDCUTTINGACTION,ASWELLASPOORMACHININGSYSTEMSTIFFNESSFRAZAOETAL1POINTEDOUTTHAT“THEMACHININGOFHOLESOFHIGHLENGTHTODIAMETERRATIOTOHIGHSTANDARDSOFSIZE,PARALLELISM,STRAIGHTNESSANDSURFACEFINISHHASALWAYSPRESENTEDPROBLEMS“LOWMACHINABILITYOFDIFFICULTTOCUTMATERIALSMAKESITMOREDIFFICULTTOACHIEVETHEPROCESSEFFICIENTLYANDECONOMICALLY,ESPECIALLYINTHESOLIDDRILLINGOFSMALLDEEPHOLESCURRENTLY,THEREARETHREEMAINTECHNIQUESAVAILABLEFORDEEPHOLEDRILLING,IETHEGUN,THEBTAFROMBORINGTREPANNINGASSOCIATIONANDTHEEJECTORDRILLINGSYSTEMS2,3THEBASICPRINCIPLESOFEACHPROCESSARETHESAME,BUTTHEBTAPROCESSINITIALLYDEVELOPEDINGERMANYDURINGWORLDWARTWOREPRESENTSTHEMOSTECONOMICALMETHODFORDEEPHOLEDRILLINGWITHHIGHLENGTHTODIAMETERRATIO4THEBTAPROCESSCANCOVERALARGERANGEOFBOREDIAMETERS6750RAMANDHIGHLENGTHTODIAMETERRATIOSUPTO1005SMALLBTATOOLSUNDER20RAMNORMALLYCONSISTOFASINGLECUTTINGTIPWITHTWOCORRESPONDINGAUTHORFAX44171815769909240136/97/1700?1997ELSEVIERSCIENCESAALLRIGHTSRESERVEDPIIS0924013696000295SELLPILOTINGCARBIDEPADSFIG1WHENDRILLINGWITHTHESELFPILOTINGTOOLINTEGRATEDWITHAHIGHPRESSURECOOLANTSYSTEMWHICHFLUSHESTHECHIPBACKTHROUGHTHEINTERIOROFTHEBORINGBAR,THECUTTINGFORCESGENERATEDATTHECUTTINGEDGESAREBALANCEDBYGUIDEPADSRUBBINGAGAINSTTHEBOREWALLTHISMEANSTHATTHEREISBURNISHINGACTIONOFTHEGUIDEPADSONTHEWALLOFTHEMACHINEDHOLEITISDUETOTHEBURNISHINGANDFIXEDSIZEACTIONOFTHEGUIDEPADSCOMBINEDWITHINTERIORCHIPREMOVALMETHODOFTHEBTAPROCESSANDTHEUSEOFANEXTREMELYRIGIDCYLINDRICALBORINGBARTHATHIGHPRECISIONDEEPHOLESCANISACHIEVEDINONEPASS6,7THISWORKISAIMEDATDEVELOPINGARELIABLEMETHODFORTHEPRECISIONDRILLINGOFSMALLDEEPHOLESINDIFFICULOCUTMATERIALSGUDEPADSE±RDLNGRMCUT±NGLIP/FIGTHEBTADRILLINGHEADZMWANGETAL/JOURNAL/“MATERIALSPROCESSINGTECHNOLOGY680997257261259350030002500200010005003000250020001500ANDBTORQUEAXIALFORCEATTHEOUTEREDGEISOBTAINEDPERIODAWHENTHEMIDDLEEDGEENTERS,THEREALAXIALFORCEINCREASESTOBPOINTWHENTHEINNEREDGEMAKESCONTACTWITHTHEWORKPIECE,ARESULTANTAXIALTBRCEKTWITHAPOINTCISOBSERVEDTHEAXIALFORCEINCREASESSUDDENLYASSOONASTHECOREISCUTANDTHEGUIDEPADSENTERTHEMACHINEDHOLEAFTERASHORTPERIOD,ASTABLEAXIALFORCEFADEVELOPSTHECUTTINGTORQUETANDTHERESULTANTTORQUETAWEREMEASUREDINTHESAMEWAYFIG4BSHOWINGATYPICALTORQUETIMECURVEASSHOWNINFIG2,THESUPPORTINGFORCEACTINGONEACHOFTHEGUIDESDEPENDSMAINLYONBOTHTHEMAGNITUDEANDTHEDIRECTIONOFFANDTHEPOSITIONALANGLESQHANDQ2OFTHEGUIDEPADSATQH87°ANDQ2183THESUPPORTINGFORCEONGNEARLYEQUALSTHECUTTINGFORCEF,WHILSTTHEFORCEONG2ISABOUT20OFTHECUTTINGFORCEF10THEREFOREITCANBECONSIDEREDTHATTHEFIRSTPADGBEARSTHECUTTINGIRCEF,WHILETHESECONDPADG2DETERMINESTHEDIAMETEROFTHEDRILLEDHOLE2EXPERIMENTALPROCEDURESBASEDONTHECAREFULINVESTIGATIONOFTHEBTADEEPHOLEDRILLINGPROCESS,INCLUDINGTHEANALYSISOFTHEFORCESACTINGONTHEDEEPHOLEDRILLINGHEAD,THEOBSERVATIONOFTHEDRILLINGSTABILITYANDTHEUNDERSTANDINGOFTHEBURNISHINGACTIONOFTHEGUIDEPADS,ANIMPROVED16THESTUDYINDICATESTHAT1020MMSMALLDEEPHOLESOFHIGHTOLERANCEGRADESIT7TOIT9FIG6ANDLOWERSURFACEROUGHNESSVALUESRAINTHERANGEOF02TO16PMFIG7CANBEACHIEVEDUNDERTHEOPTIMISEDCUTTINGPARAMETERSBYMEANSOFTHENEW/IMPROVEDTYPEOFBTADRILL31EFFECTOFTOOLGEOMETRYEXPERIMENTALINVESTIGATIONOFDEEPHOLEDRILLINGINDIFFICULTTOCUTMATERIALCRNI3MOVINDICATESTHATTHEGOODSURFACEFINISH,HIGHDIMENSIONACCURACYANDTHEIMPROVEDRUNOUTOFTHEMACHINEDDEEPHOLESCANBEATTRIBUTEDPARTLYTOTHEHIGHSTABILITYOFTHEDRILLINGHEADANDTHEIMPROVEDBURNISHINGACTIONOFTHEGUIDEPADSTHEHIGHSTABILITYOFTHEDRILLINGHEADISACHIEVEDBYARRANGINGTHETWOCARBIDEPADSATPOSITIONALANGLESOF8095°AND180190°ANDINSERTINGANASSISTANTPILOTINGCARBIDEPADAT270275°CLOCKWISEFROMTHECUTTIFFGEDGESTHEVIBRATIONRESISTINGPADSATTHEBACKOFDRILLINGHEADFURTHERPROMOTETHESTABILITYOFTHEDRILLINGHEADDUETOTHEIRDAMPINGACTIONANOTHERSIGNIFICANTCONTRIBUTIONOFTHESOFTPADSISTOSUPPRESSTHEAXIALDEVIATIONOFHOLE,WHICHLATTERISONEOFTHEMAINPROBLEMSFACEDINDEEPHOLEDRILLING,ESPECIALLYINDIFFICULTTOCUTMATERIALSWHENASLENDERBORINGBARBEARSAHIGHAXIALFORCE,BENDINGOFTHEBAROCCURSANDTHEDRILLINGHEADINTHESUPPORTPILOTINGBUSHINCLINESINTHISCASE,THEMISGUIDANCEOFTHEDRILLINGHEADWILLENCOURAGETHERUNOUTOFTHEHOLETHEINTRODUCTIONOFTHEVIBRATIONRESISTINGPADSRESULTSINASTABLECANTILEVEREDGUIDINGPROCESSANDELIMINATESORRAIN