文献翻译一种新型并联机床的尺寸公差分配Word格式.docx

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文献翻译一种新型并联机床的尺寸公差分配Word格式.docx

Theprototypeofanewtypeofparallelmachinetoolsisa6-6Stewartplatformmechanism.Comparedtothetraditionalmachinetool,aparallelmachinetoolpossessesmanyadvantages,suchashighprecision,highstructuralrigidityandhighmachiningforce/torquecapacity,etc.Currently,manyuniversitieshaveresearchonthiskindofmachinetools.AsshowninFig.1,theparallelmachinetoolcomprisesthefollowingfourparts:

afixedplatform,sixin-parallelactuators,thelengthvariationofeachactuatorisimplementedbyball-screwsandtheball-screwsaredrivenbyservomotors.Theballjointsconnectthefixedandmovingplatformswithball-screws;

aspindleisinstalledonmovingplatformbottom.Whenmachiningworkisbeingcarriedoutthevariationofthemovingplatformallowsaparallelmachinetooltomachinecomplicatedcurvedworkpiecesuchasdie,impelleretc.

ThedevelopingtendencyofmodernNCmachinetoolsishighspeedandhighprecision,andthemachinetoolerrorshavedirecteffectonmachinetoolprecision.Inordertomeettheprecisionspecified,ascientificdimensionaltoleranceallocationisurgentlyrequiredinthedesignofthiskindofmachinetool.Theerrorsofthemachinetoolincludethefollowingparts:

1)transmissionerrorintransmissionchains,i.e.,pitchcumulativeerroroftheball-screwineachactuatoranddeaddomainerrorduringstartingorreversingoperation;

2)lengthtransformerroroftheball-screwduetotheinfluenceofambienttemperature;

3)paresclearanceerrorthatconnectfixedandmovingplatform;

4)othererrors,i.e.,positioningerrorcausedbytransmissionrigidity,dynamicerrorcausedbymovingpartsmassandvelocitydamping.Theaboveerrorswillfinallyleadtoerroratthecutterheadofthemachinetool.Thispaperwillcarryoutresearchondimensionaltoleranceallocationbasedonakindofstatisticalexperimentmethod,Monte-Carlomethod.

2SOLUTIONOFINVERSEKINEMATICSFORMACHINETOOL

Thekinematicssolutionforthisparallelmachinetoolcanbeclassifiedintotwotypes.Whentheknownquantityisthelengthsofthesixactuatorsandtheorientationofthecutterhead,thisiscalleddirectkinematics;

Onthecontrary,whentheknownquantityisthepositionandtheorientationofthecutterheadandtheunknownquantityisthelengthsofthesixactuators,thisiscalledinversekinematics.Thesolutionofthedirectkinematicsofthemachinetoolisusedtomonitorwhilethesolutionoftheinversekinematicsofthemachinetoolisusedtocontrol.AsshowninFig.2,afixedcoordinateframeO-XYZisattachedtothefixedplatformandamovingcoordinateframeO’-X’Y’Z’isattachedtothemovingplatform.Thecenterofthejointconnectingtheitchactuatortothefixedplatformwillbedenotedas

whereasthecenterofthejointconnectingthesamelegtothemovingplatformwillbedenotedas

theY-axisofthefixedcoordinateframeisselectedalongthelinewhichbisectstheangle

andtheY’-axisofthemovingcoordinateframeisselectedalongthelinewhichbisectstheangle

.LetthepositionofpointO’withrespecttotheoriginofthefixedcoordinateframebedenotedbyvector

vectors

willbedefinedasthepositionvectorsofthemovingcoordinateframe,thuswecanwritethepositionvectorsofthemovingplatformjointsinfixedcoordinateframeas:

Wherematrix

istherotationmatrixdescribingtheorientationofthemovingplatformwithrespecttothefixedplatform,theelementsofmatrix

areshownbyRPYexpression.Let

beanglesthatthemovingplatformrotatesaboutX-axis,Y-axis,Z-axisofthefixedcoordinateframe,andthenwecanobtain:

Letvectors

bethepositionvectorsoftheplatformjointswithrespecttothefixedcoordinateframe,thenthelengthofeachactuatorcanbewrittenas:

3DIMENSIONALTOLERANCEALLOCATIONSWITHMONTE-CARLOMETHOD

2.1DeterminationofTotalDimensionalChainErroroftheMachineToolLinks

Inordertocarryoutdimensiontoleranceallocation,thevariationfeaturebetweentheerrorsofthein-parallellinksandorientationerrorofthecutterhead(orthecenterpointofthemovingplatform)needtoknow.Thedirectkinematicsisusedtoderivethecutterheaderrorfromthelinkerrorsofthemachinetool.Itisdifficulttoobtainanalyticalsolutionbydirectkinematics.Soaninverseerrorestimationmethodbywhichthelinkerrorscanbederivedfromthepositionandorientationerrorsofthecutterheadisadopted.

Thekeytothedimensionaltoleranceallocationistodeterminethetotaldimensionalchainerrorofthemachinetoollinks.Monte-Carlomethodisanumeralmethodtosolvemathematicsbasedonrandomsampling.Inthisparallelanevenly-distributedMonte-Carlorandomsimulationmethodon

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