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人字齿轮最佳齿向修形设计的Kriging响应面法
引用本文:余澍民.人字齿轮最佳齿向修形设计的Kriging响应面法[J].机械与电子,2020,38(5):37-42.
作者姓名:余澍民
作者单位:中国电子科技集团第三十八研究所,安徽 合肥 230088
摘    要:为了最大程度地降低人字齿轮时变啮合刚度引起的振动,改善齿面载荷分布不均,将人字齿轮两侧修形量单独考虑,提出一种以动载系数最小、结合Kriging响应面的人字齿轮最佳齿向修形设计方法。首先,根据两侧修形量与时变啮合刚度函数建立的BP神经预测网络来得到Kriging响应面所需的样本数据。然后,通过Kriging模型建立时变啮合刚度各参数响应面。其次,建立人字齿轮弯扭轴耦合动力学模型,并将Kriging预测的人字齿轮时变啮合刚度函数带入动力学微分方程中,求解动载系数并建立响应面,得到全局最优齿向修形参数。最后,通过算例证实人字齿两侧最佳鼓形量并不一致,能够较好地补偿人字齿轮实际传动中由于误差和变形导致的两侧不同的啮合歪斜度,所优化获得的修形人字齿轮动载系数相比未修形下的动载系数减少41.29%,且比常规修形方法(ISO)的减少了15.04%。

关 键 词:人字齿轮传动  BP神经网络  Kriging响应面  齿向修形

Kriging Response Surface Method for Optimal A xial Modification of Herringbone Gear
YU Shumin.Kriging Response Surface Method for Optimal A xial Modification of Herringbone Gear [J].Machinery & Electronics,2020,38(5):37-42.
Authors:YU Shumin
Affiliation:No.38ResearchInstituteofCETC,Hefei230088,China
Abstract:Inordertominimizethevibrationcausedbythetime varyingmeshingstiffnessofherringbonegearandtoimproveunevendistributionoftoothsurfaceloads,consideringtheamountofmodificationonbothsidesofaherringbonegearseparately,amethodforoptimizationofherringbonegearaxial modificationwasproposedbasedonminimizeofdynamicloadfactorcombinedwithKrigingresponsesur face.Firstly,TheBPneuralnetworkwasestablishedbasedonthetwosidesofthelongitudinalcorrection andtime varyingmeshingstiffnessfunctiontoobtainthesampledataneededfortheKrigingresponse surface.Then,thetime varyingmeshingstiffnessparameterresponsesurfacewasestablishedbyKriging model.Secondly,thedynamicsmodelcoupledwithlateral,torsionalandshaftforherringbonegearpair wasestablished,andthetime varyingmeshingstiffnessfunctionwhichwaspredictedbyKriging ,appliedtodynamicaldifferentialequation,andthenthedynamicloadfactorresponsesurfacewasestablished,sooptimalparametersofglobelgearaxialmodificationwasobtained.Finally,exampleshowsthatthebest valueofcrowningonbothsidesoftheherringbonetoothisnotuniform,itcanbettercompensateforthe differentmeshingskewnesscausedbytheerroranddeformationintheactualtransmissionoftheherringbonegear.Thedynamicloadfactoroftheherringbonegearobtainedinthispaperisreducedby41.29% comparedtotheunmodifiedform,andisreducedby15.04%comparedwiththeconventionalmodification method(ISO).
Keywords:herringbonegears  BPneuralnetwork  Krigingresponsesurface  axialmodification
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