球轴承磨床机构分析与磨削工艺参数优化
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摘要
球轴承是滚动轴承的一种类型，它主要应用在高速旋转的场合，其精度水平对一些设备的性能有着重要的影响。球轴承的内圈是球轴承的重要组成元件之一，它的沟道表面是滚动体滚动和承受载荷的主要表面。因此，对球轴承内圈沟道表面的磨削精度有着很高的要求。本文主要以3MZ1313球轴承内圈沟道磨床为研究对象，这是一台磨削球轴承内圈沟道表面的专用磨床，本文主要对其进行以下几个方面的研究工作：
（1）首先确定该轴承磨床机构模型有2条运动链和3个自由度，接着在该磨床机构的各构件上建立坐标系，并分别建立这2条运动链的运动学模型,并对它们分别进行求解。
（2）运用Pro/E3.0软件建立该轴承磨床机构的实体模型，并利用Pro/E3.0软件的运动仿真模块对其进行干涉检查，在没有干涉的前提下通过MECHANISM/Pro接口模块导入ADAMS2005中进行动力学仿真。
（3）对影响轴承内圈沟道磨削精度的主要影响因素进行了总结和分析，并以磨削过程中砂轮与工件接触后的振动以及砂轮架的振动对磨削精度的影响为例，进行了深入的分析。通过采取一定的措施并对其加以控制，来减小振动对其产生的影响。
（4）利用BP神经网络强大的非线性映射能力，建立磨削精度要求与磨削工艺参数之间的关系。在这里，按照均匀设计方法获得神经网络的输入和输出样本，并确定BP神经网络的结构，将得到的样本用来训练网络。BP神经网络还具有自学习功能，可以适应各种不断变化的磨削精度要求。最后，经过训练后的神经网络，其输入样本与输出样本之间有着很好的对应关系，实现了对磨削工艺参数的优化。
Ball bearing is one of the rolling bearings, it is mainly used in high-speedrotation occasions, its accuracy level has a great impact on the function of manymachines. The inner ring is an important component of the ball bearing, itschannel surface is the key surface which the rolling element rolls on and transferforce to. In this paper, I take the3MZ1313Ball Bearing Grinder for the objectof study. This is a special grinder for grinding the channel surface of the ballbearing’inner ring. In this paper, the research work is listed as the followingaspects:
(1) Firstly, I find out that the ball bearing grinder’ mechanism has twokinematics chains and three degrees of freedom, and work up some coordinatesof the constituent components of the grinder 'mechanism model. I respectivelyset up the kinematics models of the two chains, solve the two kinematicsmodels.
(2) I work up the solid model of the grinder 'mechanism by way ofPro/E3.0software, and use the motion simulation module of Pro/E3.0softwareto check the interference condition of the mechanism model. Without theinterferences, it can be imported into the software of ADAMS2005through theMECHANISM/Pro interface module, then carry out the dynamic simulation.
(3) I summarize out the main factors which affect the grinding accuracy ofthe ball bearing’ inner ring channel，analyze them in some ways. Next, I doin-depth analysis on the vibration models of the grinding wheel—work pieceand the grinding wheel frame in the process of grinding. Understanding howthey affect the grinding accuracy. By taking some measures，we can reduce theimpact of vibration on the grinding accuracy.
(4) BP neural network has powerful nonlinear mapping function, it canwork up the model of relationship between the grinding precision and thegrinding process parameters. The neural network input and output samples areobtained in accordance with uniform design method, in this paper. I design thestructure of the network according to the actual requirements, using these samples to train network. BP neural network also has a self-learning function, itcan adapt to the changing grinding precision requirements. Finally, after theneural network is trained, a good Correspondence is formed between the inputsamples and the output samples, and achieve the optimization of processparameters.
（1）首先确定该轴承磨床机构模型有2条运动链和3个自由度，接着在该磨床机构的各构件上建立坐标系，并分别建立这2条运动链的运动学模型,并对它们分别进行求解。
（2）运用Pro/E3.0软件建立该轴承磨床机构的实体模型，并利用Pro/E3.0软件的运动仿真模块对其进行干涉检查，在没有干涉的前提下通过MECHANISM/Pro接口模块导入ADAMS2005中进行动力学仿真。
（3）对影响轴承内圈沟道磨削精度的主要影响因素进行了总结和分析，并以磨削过程中砂轮与工件接触后的振动以及砂轮架的振动对磨削精度的影响为例，进行了深入的分析。通过采取一定的措施并对其加以控制，来减小振动对其产生的影响。
（4）利用BP神经网络强大的非线性映射能力，建立磨削精度要求与磨削工艺参数之间的关系。在这里，按照均匀设计方法获得神经网络的输入和输出样本，并确定BP神经网络的结构，将得到的样本用来训练网络。BP神经网络还具有自学习功能，可以适应各种不断变化的磨削精度要求。最后，经过训练后的神经网络，其输入样本与输出样本之间有着很好的对应关系，实现了对磨削工艺参数的优化。
Ball bearing is one of the rolling bearings, it is mainly used in high-speedrotation occasions, its accuracy level has a great impact on the function of manymachines. The inner ring is an important component of the ball bearing, itschannel surface is the key surface which the rolling element rolls on and transferforce to. In this paper, I take the3MZ1313Ball Bearing Grinder for the objectof study. This is a special grinder for grinding the channel surface of the ballbearing’inner ring. In this paper, the research work is listed as the followingaspects:
(1) Firstly, I find out that the ball bearing grinder’ mechanism has twokinematics chains and three degrees of freedom, and work up some coordinatesof the constituent components of the grinder 'mechanism model. I respectivelyset up the kinematics models of the two chains, solve the two kinematicsmodels.
(2) I work up the solid model of the grinder 'mechanism by way ofPro/E3.0software, and use the motion simulation module of Pro/E3.0softwareto check the interference condition of the mechanism model. Without theinterferences, it can be imported into the software of ADAMS2005through theMECHANISM/Pro interface module, then carry out the dynamic simulation.
(3) I summarize out the main factors which affect the grinding accuracy ofthe ball bearing’ inner ring channel，analyze them in some ways. Next, I doin-depth analysis on the vibration models of the grinding wheel—work pieceand the grinding wheel frame in the process of grinding. Understanding howthey affect the grinding accuracy. By taking some measures，we can reduce theimpact of vibration on the grinding accuracy.
(4) BP neural network has powerful nonlinear mapping function, it canwork up the model of relationship between the grinding precision and thegrinding process parameters. The neural network input and output samples areobtained in accordance with uniform design method, in this paper. I design thestructure of the network according to the actual requirements, using these samples to train network. BP neural network also has a self-learning function, itcan adapt to the changing grinding precision requirements. Finally, after theneural network is trained, a good Correspondence is formed between the inputsamples and the output samples, and achieve the optimization of processparameters.
引文
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[3] H.K.Tonshoff, B.K arpuschewski, etl. Grinding Process Achievements and theirConsequences on Machine Tools Challenges and Opportunities Annals of CIRP[J].1998，47(2):651-655.
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[6]许进.CBN砂轮磨床的研制[D].上海：上海交通大学,2006.
[7] Xiaoping Li et al, A Free-A brasive Machining Approach to Dressing of Resin-BondedCBN Grinding Wheels, Journal of material Processing Technology[J].1995,(48):223-227.
[8]屈里强,朱宁.磨削加工中的CBN砂轮[J].金刚石与磨料磨具工程，2002.
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[29] Denavit J and Hartenberg R S,A Kinematic Notaytion for Lower Pair Mechanism Basedand Matrices. ASME J.Applied Mechanics [J].1955,(22):215-221.
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[31] Salah Faik，Holly Witteman Modeling of Impaet Dynamics: A Literature Survey.Intemational ADAMS User Conference [J].2000.
[32]石博强，申炎华，宁晓斌，李跃娟. ADAMS基础与工程范例教程[M].北京:中国铁道出版社，2007.9.
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[35]严思晗.轴承套圈沟道磨削的进给状态参数监测及其工艺试验研究[D].杭州：浙江大学，2008.
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[2]赵起超.数控凸轮磨床磨削力适应控制的研究[D].秦皇岛：燕山大学，2007.
[3] H.K.Tonshoff, B.K arpuschewski, etl. Grinding Process Achievements and theirConsequences on Machine Tools Challenges and Opportunities Annals of CIRP[J].1998，47(2):651-655.
[4]卢秉恒，赵万华，洪军.机械制造技术基础(第2版)[M].北京：机械工业出版社,2005.
[5]屈里强.数控轴承内圆磨床进给系统的设计与研究[D].合肥：合肥工业大学,2003.
[6]许进.CBN砂轮磨床的研制[D].上海：上海交通大学,2006.
[7] Xiaoping Li et al, A Free-A brasive Machining Approach to Dressing of Resin-BondedCBN Grinding Wheels, Journal of material Processing Technology[J].1995,(48):223-227.
[8]屈里强,朱宁.磨削加工中的CBN砂轮[J].金刚石与磨料磨具工程，2002.
[9]邸淑英.3MZl36型全自动球轴承内圈沟磨床的改造设计[J].精密制造与自动化,2008(1):33-34.
[10]合军，常美丽，冯万寿，赵修同.偏心往复机构在轴承内径磨床中的应用分析[J].轴承，2006(2)：19-21.
[11]程光大.数控全自动轴承内圈滚道磨床研制成功[J].设备管理&维修，2000，1(1):48.
[12]沈宝杰，张强，何立淮，刘树军.数控轴承磨床故障模式及其原因[J].山东大学学报(工学版).2004，6(3):18-22.
[13]张敬.高速轴承内圆磨床结构动态分析与优化设计[D].南京:东南大学，2007.
[14]张平飞，高丽.轴承加工磨床数控化改造的应用研究.《新技术新工艺》数字技术与机械加工工艺装配[J].2009，(10):33-34.
[15]殷年久.轴承套圈内圆磨床的测控一体化改造[J].轴承，2007(13):17-18
[16]陈文杰. M28125轴承磨床数控化改造[D].武汉:华中科技大学，2006.
[17]修世超，冯强，王瑶.磨削工艺绿色度评价指标体系及影响因素分析[J].金刚石与磨料磨具工程，2007,159(3):60-63.
[18]杨晓蔚．滚动轴承重要性与技术含量纵论[C].中国轴承论坛第二届会议论文集，2002:29-30.
[19]胡金祥.高速内圆磨床热态与动态特性研究[D].南京:东南大学，2007.
[20] Jorgensen，Bert R．；Shin，Yung C．Dynamics of spindle-bearing systems at high speedsincluding cutting load effects. Journal of Manufacturing Science and Engineering，Transactions of the ASME[J].1998,120(2):387-394.
[21]轴承行业教材编审委员会．轴承磨工工艺[M]．北京：机械工业出版杜，1986.
[22] Hahn, R.S. Controlled Force Grinding—a New Technique for Precision InternalGrinding[J]. Trans. ASME J. of Eng. for Ind.1964,86:2.
[23] Hahn,R.S.and Lindsay R.P. Principlesof Gringing’5-partseries Machinery[M].NewYork,1971.
[24] Hahn,R.S.,‘Some Characteristics of Controlled Force Grinding’，Proceedings of theSixth International Machine Tool Design Research Conference[C].1965:597.
[25]徐起贺，周艳红.任意结构数控机床机构运动学建模与求解[J].机械工程学报:2002，38(10):31-36.
[26]郑建荣. ADAMS—虚拟样机技术入门与提高[M].北京：机械工业出版社,2001.
[27]孙恒，陈作模，葛文杰.机械原理[M].北京:高等教育出版社，2006.
[28]陈涛.多坐标数控机床后置处理系统的研究与开发[D].武汉：华中科技大学，2003.
[29] Denavit J and Hartenberg R S,A Kinematic Notaytion for Lower Pair Mechanism Basedand Matrices. ASME J.Applied Mechanics [J].1955,(22):215-221.
[30]林清安.Pro／E野火3．0中文版零件设计应用实例[J].北京:电子工业出版社，2007.
[31] Salah Faik，Holly Witteman Modeling of Impaet Dynamics: A Literature Survey.Intemational ADAMS User Conference [J].2000.
[32]石博强，申炎华，宁晓斌，李跃娟. ADAMS基础与工程范例教程[M].北京:中国铁道出版社，2007.9.
[33]谭志飞，黄辉先．基于Pr0／E和ADAMS的机械手运动仿真[J]．机械工程师,2007(4)：129-130．
[34]蔡光起，巩亚东，宋贵亮译.磨削技术理论与应用[M].沈阳：东北大学出版社,2002.
[35]严思晗.轴承套圈沟道磨削的进给状态参数监测及其工艺试验研究[D].杭州：浙江大学，2008.
[36] Snoeys, R, Maris,M. and Pcters,J. Thermally Induced Damage in Grinding [J].Annals ofthe CIRP.1978,27(2):571.
[37] Torrance, A. A.. Metallurgical Effects Associated with Grinding [C]. Proceedings of theTwelfth International Machine Tool Design and Research Conference,1978:637.
[38]薛源顺，宋秋云，邵时美.磨工工艺学[M].北京:科学普及出版社，2002.
[39]黄沿江.精密数控磨床振动测试与减振技术研究[D].厦门:厦门大学，2008.
[40] Hahn,R.S. Vibration Problems and Solutions Grinding [J]. ASTME Paper,1969,(69):246.
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