内齿珩轮强力珩齿齿面粗糙度预测与工艺参数优化
|
摘要
为了有效降低汽车高档变速箱齿轮传动噪声,针对强力珩齿工艺参数对齿轮表面粗糙度Ra的影响,在一定工艺参数范围内采用响应曲面法设计强力珩齿试验,并建立Ra预测模型,分析强力珩齿的珩轮转速nH、Z向进给量fZ和X向进给量fX等工艺参数对被珩齿面Ra的影响规律;在满足齿面Ra≤0.36μm的精度下,通过布谷鸟搜索算法优化出最大强力珩齿效率的一组工艺参数。结果表明,在一定内齿珩轮强力珩齿工艺参数范围内,nH对被珩齿轮工件表面粗糙度影响最大,fZ和fX的影响程度基本相当,通过响应曲面法建立的表面粗糙度模型置信度高;经优化的一组强力珩齿工艺参数所加工的齿轮表面粗糙度Ra值满足齿面精度要求,可在珩齿前对被珩齿轮工件表面质量进行预测和控制。
Aiming at the influence of power honing process parameters on gear surface roughness Ra,a Response Surface Methodology(RSM)experiments were carried out to build Raprediction model,and the influence rules of internal teeth honing wheel power honing gear process parameters including honing wheel revolution nH,feed rate in Z direction fZand feed rate in Xdirection fX on Ra was analyzed.Under the condition that tooth surface Ra was less than or equal to 0.36μm precision,Cuckoo Search(CS)algorithm was used to optimize a set of process parameters maximum strength honing efficiency.The results showed that the nH had biggest influence on gears'surface roughness in the honing process parameters within a certain range,the effect of fZand fX were almost the same,thus the high confidence of surface roughness modeled by RSM could be optimally select the honing parameters;the surface roughness value Raof gear machined by the optimized set of Gear Honing Parameters met the requirement of tooth surface accuracy,which could control and predict the gears'surface quality before power honing.
Aiming at the influence of power honing process parameters on gear surface roughness Ra,a Response Surface Methodology(RSM)experiments were carried out to build Raprediction model,and the influence rules of internal teeth honing wheel power honing gear process parameters including honing wheel revolution nH,feed rate in Z direction fZand feed rate in Xdirection fX on Ra was analyzed.Under the condition that tooth surface Ra was less than or equal to 0.36μm precision,Cuckoo Search(CS)algorithm was used to optimize a set of process parameters maximum strength honing efficiency.The results showed that the nH had biggest influence on gears'surface roughness in the honing process parameters within a certain range,the effect of fZand fX were almost the same,thus the high confidence of surface roughness modeled by RSM could be optimally select the honing parameters;the surface roughness value Raof gear machined by the optimized set of Gear Honing Parameters met the requirement of tooth surface accuracy,which could control and predict the gears'surface quality before power honing.
引文
[1]ZHANG Shouyuan,LI Yujun,YANG Lianghui.Whine noise improvement and sound quality enhancement in an electric car[J].Automotive Engineering,2016,38(10):1245-1251(in Chinese).[张守元,李玉军,杨良会.某电动汽车车内噪声改进与声品质提升[J].汽车工程,2016,38(10):1245-1251.]
[2]AMINI N,WESTBERG H,KLOCKE F,et al.An experimental study on the effect of power honing on gear surface topography[J].Gear Technology,1999,16(1):11-18.
[3]SANDRO S,MONI R F,LINCOLN C B.Particle swarm optimization for Achieving the minimum profile error in honing process[J].Precision Engineering:Journal of the International Societies for Precision Engineering and Nanotechnology,2014,38(4):759-768.
[4]ZHAI Jingmei,YING Can,XU Xiao.Surface roughness prediction of integration knowledge modeling into date mining[J].Computer Integrated Manufacturing Systems,2012,18(5):1046-1053(in Chinese).[翟敬梅,应灿,徐晓.知识建模和数据挖掘融合的粗糙度预测新方法[J].计算机集成制造系统,2012,18(5):1046-1053.]
[5]YIN Yanchao,DING Weigang.A novel cloud model prediction for surface roughness based on multidimensional&multirules reasoning[J].Journal of Mechanical Engineering,2016,52(15):204-212(in Chinese).[阴艳超,丁卫刚.切削加工表面粗糙度的多维多规则云预算方法[J].机械工程学报,2016,52(15):204-212.]
[6]TSAI Y S,CHEN J C,LOU S J.An in-process surface recognition system based on neural networks in end milling cutting operations[J].International Journal of Machine Tools&Manufacture,1999,39(4):583-605.
[7]SUYKENS J A K,VANDEWALLE J.Least squares support vector machine classifiers[J].Neural Processing Letters,1999,9(3):293-300.
[8]CAYDAS U,EKICI S.Support vector machines models for sur-face roughness prediction in CNC turning of AISI 304austeni-tic stainless steel[J].Journal of Intelligent Manufacturing,2012,23(3):639-650.
[9]SHI Wentian,WANG Xibin,LIU Yude,et al.A prediction model and experimental study of surface roughness in micro milling based on RSM[J].China Mechanical Engineering,2009,20(20):2399-2402(in Chinese).[石文天,王西彬,刘玉德,等.基于响应曲面法的微细铣削表面粗糙度预报模型与试验研究[J].中国机械工程,2009,20(20):2399-2402.]
[10]SHI Wentian,LIU Yude,WANG Xibin,et al.Experimental and prediction model for surface roughness in micro milling[J].Transactions of the Chinese Society for Agriculture Machinery,2010,41(1):211-214(in Chinese).[石文天,刘玉德,王西彬,等.微细铣削表面粗糙度预测与试验[J].农业机械学报,2010,41(1):211-214.]
[11]ZHANG Hongzhou,MING Weiwei,AN Qinglong,et al.Application of response surface methodology in surface roughness prediction model and parameter optimization[J].Journal of Shanghai Jiaotong University,2010,44(4):447-451(in Chinese).[张烘州,明伟伟,安庆龙,等.响应曲面法在表面粗糙度预测模型及参数优化中的应用[J].上海交通大学学报,2010,44(4):447-451.]
[12]YUAN Bin,HAN Jiang,WU Lulu,et al.A prediction model and experimental study of gear hobbing profile errors based on particle swarm optimization[J].China Mechanical Engineering,2016,27(20):2705-2711(in Chiense).[袁彬,韩江,吴路路,等.基于粒子群算法的滚削齿面综合轮廓误差预测模型与试验研究[J].中国机械工程,2016,27(20):2705-2711.]
[13]YUSUF S,RIZA M A.Surface roughness model for machining mild steel[J].Material and Design,2005,26(4):321-326.
[14]LUO Taijing.Evaluating method of the measuring gear tooth surface roughness[J].Journal of Mechanical Transmission,2009,33(5):95-98(in Chinese).[罗太景.齿轮轮齿表面粗糙度的评定与质量控制[J].机械传动,2009,33(5):95-98.]
[15]PUERTAS A I,LUIS P C J.Surface roughness prediction by factorial design of experiments in turning processes[J].Journal of Material Processing Technology,2003,143(144):390-396.
[16]SAYLES R S,THOMAS T R.Surfaces topography as a nonstationary random process[J].Nature,1978,27(1):431-434.
[17]Nano Focus.Optical 3D confocal microscope[EB/OL].[2017-05-12].http://www.megphy.com(in Chinese).[Nano Focus.光学3D共聚焦显微镜[EB/OL].[2017-05-12].http://www.megphy.com.]
[2]AMINI N,WESTBERG H,KLOCKE F,et al.An experimental study on the effect of power honing on gear surface topography[J].Gear Technology,1999,16(1):11-18.
[3]SANDRO S,MONI R F,LINCOLN C B.Particle swarm optimization for Achieving the minimum profile error in honing process[J].Precision Engineering:Journal of the International Societies for Precision Engineering and Nanotechnology,2014,38(4):759-768.
[4]ZHAI Jingmei,YING Can,XU Xiao.Surface roughness prediction of integration knowledge modeling into date mining[J].Computer Integrated Manufacturing Systems,2012,18(5):1046-1053(in Chinese).[翟敬梅,应灿,徐晓.知识建模和数据挖掘融合的粗糙度预测新方法[J].计算机集成制造系统,2012,18(5):1046-1053.]
[5]YIN Yanchao,DING Weigang.A novel cloud model prediction for surface roughness based on multidimensional&multirules reasoning[J].Journal of Mechanical Engineering,2016,52(15):204-212(in Chinese).[阴艳超,丁卫刚.切削加工表面粗糙度的多维多规则云预算方法[J].机械工程学报,2016,52(15):204-212.]
[6]TSAI Y S,CHEN J C,LOU S J.An in-process surface recognition system based on neural networks in end milling cutting operations[J].International Journal of Machine Tools&Manufacture,1999,39(4):583-605.
[7]SUYKENS J A K,VANDEWALLE J.Least squares support vector machine classifiers[J].Neural Processing Letters,1999,9(3):293-300.
[8]CAYDAS U,EKICI S.Support vector machines models for sur-face roughness prediction in CNC turning of AISI 304austeni-tic stainless steel[J].Journal of Intelligent Manufacturing,2012,23(3):639-650.
[9]SHI Wentian,WANG Xibin,LIU Yude,et al.A prediction model and experimental study of surface roughness in micro milling based on RSM[J].China Mechanical Engineering,2009,20(20):2399-2402(in Chinese).[石文天,王西彬,刘玉德,等.基于响应曲面法的微细铣削表面粗糙度预报模型与试验研究[J].中国机械工程,2009,20(20):2399-2402.]
[10]SHI Wentian,LIU Yude,WANG Xibin,et al.Experimental and prediction model for surface roughness in micro milling[J].Transactions of the Chinese Society for Agriculture Machinery,2010,41(1):211-214(in Chinese).[石文天,刘玉德,王西彬,等.微细铣削表面粗糙度预测与试验[J].农业机械学报,2010,41(1):211-214.]
[11]ZHANG Hongzhou,MING Weiwei,AN Qinglong,et al.Application of response surface methodology in surface roughness prediction model and parameter optimization[J].Journal of Shanghai Jiaotong University,2010,44(4):447-451(in Chinese).[张烘州,明伟伟,安庆龙,等.响应曲面法在表面粗糙度预测模型及参数优化中的应用[J].上海交通大学学报,2010,44(4):447-451.]
[12]YUAN Bin,HAN Jiang,WU Lulu,et al.A prediction model and experimental study of gear hobbing profile errors based on particle swarm optimization[J].China Mechanical Engineering,2016,27(20):2705-2711(in Chiense).[袁彬,韩江,吴路路,等.基于粒子群算法的滚削齿面综合轮廓误差预测模型与试验研究[J].中国机械工程,2016,27(20):2705-2711.]
[13]YUSUF S,RIZA M A.Surface roughness model for machining mild steel[J].Material and Design,2005,26(4):321-326.
[14]LUO Taijing.Evaluating method of the measuring gear tooth surface roughness[J].Journal of Mechanical Transmission,2009,33(5):95-98(in Chinese).[罗太景.齿轮轮齿表面粗糙度的评定与质量控制[J].机械传动,2009,33(5):95-98.]
[15]PUERTAS A I,LUIS P C J.Surface roughness prediction by factorial design of experiments in turning processes[J].Journal of Material Processing Technology,2003,143(144):390-396.
[16]SAYLES R S,THOMAS T R.Surfaces topography as a nonstationary random process[J].Nature,1978,27(1):431-434.
[17]Nano Focus.Optical 3D confocal microscope[EB/OL].[2017-05-12].http://www.megphy.com(in Chinese).[Nano Focus.光学3D共聚焦显微镜[EB/OL].[2017-05-12].http://www.megphy.com.]