高速铣削表面粗糙度预测与铣削参数优化分析

《高速铣削表面粗糙度预测与铣削参数优化分析》由会员上传分享，免费在线阅读，更多相关内容在学术论文-天天文库。

1、-------哈尔滨理工大学工程硕士学位论文ResearchonSurfaceRoughnessPredictionandParameterOptimizationofHighSpeedMillingAbstractThehighspeedcuttingbecauseofitshigherefficiencyandaccuracyfullyisappliedinvariousfield.Evenso,inordertomakeitfurtherdevelopment,manyrestrictingfactorsiswaitedforsolving.Atpresent,toobtainsing

2、leoneofthehighefficiencyandaccuracyisnotenough.Howtosimultaneouslyobtainhigherefficiencyunderthepartsaccuracyguaranteedinordertobetterandfullyplaytheadvantagesofhighspeedmachining.Asaresult,ithasveryimportantrealisticmeaningthatthekeytechnologiesofhighspeedmillingsurfaceroughnessarestudied.Theinflu

3、enceofvariousfactorsonthehighspeedmillingsurfaceroughnessis analyzed.Themethodoftheoryfuzzyisputforwardtoobtainmoreaccurate predictionmodel.Andthefuzzysystemistrainedbythealgorithmwhichcombine withleastsquaremethodandthebasicantcolonyalgorithm.Thecontrasttestshows thatthefinalconvergenceerroroffuzz

4、ysystemtrainedbyimprovedalgorithmis thesmallestandtheconvergenceeffectofwhichisoptimal.Themodelobtainedby thefuzzysystemispredictedthroughthetestdataandthecorrectnessandaccuracy ofthemodelbasedonthenewfuzzysystemisprovedtobebetter.Inaddition, millingparameteroptimizationmathematicalmodelisestablish

5、edwhichput machiningaccuracyandefficiencyastheoptimizationgoalandthoughtheresidual stressandthetoollifeasconstraints.AndtheDynamicAntAlgorithmGenetic Algorithmisadoptedtooptimizethemodelcalculation.Themethodnotonlyretains theadvantageofstrongrobustnessoftheoriginalsinglealgorithmbutalsoimprove itsl

6、ocalsearchingabilityandconvergence.Fordifferentprocessingrequirements, theaccuratemillingparametercombinationcanbegotmorequickly.Finally,with VisualC++6.0asthesoftwaredevelopmentplatform,millingparameter optimizationsystemisdevelopedtorealizetheMATLABsoftwarecalls,whichcan completerapidpredictionof

7、high-speedmillingsurfaceroughness.Bythesystem thetimeofpracticalproductionissavedandtheprocessingefficiencyisimproved.II-----------哈尔滨理工大学工程硕士学位论文Afterthekeytechnologiesofsurfaceroughnesspredictionbasedonhi