精密设备各部件精度对加工件的精度预测技术的研究
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摘要
本文主要针对目前军用光学系统对大口径非球面光学元件的需求,研制高精度、高效率的非球面研磨加工机床,并采用精度分析与预测的理论和方法,对该机床主要部件进行误差分配,从而进一步完成对加工件的精度预测。该研究成果为优化切削参数、提高生产效率与加工精度提供了技术支持,有助于工艺师在一个更高的水平上对工艺编排和数控程序加以验证,从而充分发挥数控机床的功能和效率,显著降低企业的生产准备时间和制造成本。因此,本论文研究成果对精密非球面加工及其相关技术在我国的应用与开展具有重要的理论意义,对促进制造业技术水平和市场竞争能力的提高具有现实意义。论文着重研究并解决以下问题:
1.非球面元件加工轨迹的研究:非球面元件加工轨迹的形成;
2.表面误差在线测量、数据处理非球面加工工件误差数学模型;
This paper mainly aim at the demand of optical system for heavy caliber non-spherical surface optical element, research non-spherical surface grinding machine of high precision and efficiency, use precision analysis and predicted theory and method, distribute errors to main parts of the machine, in this way to complete the precise prediction of the jobs. The result provides technical supports to optimize cutting parameters, increase efficiency and machining precision, give helps to process engineers to examine technology edit and numerical control program, exploit function and efficiency of the machine, decrease production prepare time and manufacturing cost obviously. So the results of this paper have important theoretical significance to precision non spherical surface machining and interrelated technology in our nation, have practical significance to manufacturing engineering and competition in market. This paper solve the problems mainly at :
1. The research of non-spherical surface elements machining trace. The formation of non-spherical surface elements machining trace;
2. Surface error on-line measurement, data processing non-spherical work piece machining error mathematical model;
1.非球面元件加工轨迹的研究:非球面元件加工轨迹的形成;
2.表面误差在线测量、数据处理非球面加工工件误差数学模型;
This paper mainly aim at the demand of optical system for heavy caliber non-spherical surface optical element, research non-spherical surface grinding machine of high precision and efficiency, use precision analysis and predicted theory and method, distribute errors to main parts of the machine, in this way to complete the precise prediction of the jobs. The result provides technical supports to optimize cutting parameters, increase efficiency and machining precision, give helps to process engineers to examine technology edit and numerical control program, exploit function and efficiency of the machine, decrease production prepare time and manufacturing cost obviously. So the results of this paper have important theoretical significance to precision non spherical surface machining and interrelated technology in our nation, have practical significance to manufacturing engineering and competition in market. This paper solve the problems mainly at :
1. The research of non-spherical surface elements machining trace. The formation of non-spherical surface elements machining trace;
2. Surface error on-line measurement, data processing non-spherical work piece machining error mathematical model;
引文
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[3] Herbert Schulz,Klaus Bimschas. Oprimization of precision Machining by Simulation of the Cutting Process. Annals of the CIRP.1993,chapter3
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[20]李军.检测技术与仪表.北京:中国轻工业出版社,2000:155～163
[21]吴正毅.测试技术与测试信号处理.北京:清华大学出版社,1991:111～120
[22]卢碧红,葛研军,王启义等.虚拟数控车削加工精度预测系统研究.机械工程学报.2002:202～231
[23]卢碧红,葛研军.面向机械加工预测的模型结构.制造业自动化.2000:211～222
[24] L.Monostori.Artifieialneuralnetworksinintelligentmanufacturing.Robotiesand ComPuter Integrated Manufacturing.1992,chapter3
[25] V.Karri. Performance in Oblique Cuttingusing Conventional Methods and Neural Networks. Neural ComPuting&APPlieations.1999,chapter1
[26]机械制造中加工误差相关分析法.李传声,机械设计与制造.1989 131～142
[27] T.Efrati ,H.Flaehner. Neural Network Based Traeking Control of Mechanieal Systems. Journal of dynicsystems,measure mentandeontrol.1999:244～250
[28]赵庆志,赵玉刚.机床误差辨析.山东工程学院学报.1995(9)
[29] V.Karri. Performance in Oblique Cuttingusing Conventional Methods and NeuralNetworks. Neural ComPuting&APPlieations.8(1999):196～205
[30]孙建明,吴菊.关于机械制造几类问题的探讨.佳木斯工学院学报.1998:155～163
[31] G.E.Thyer. ComPuter Numerieal Control of Machineols. Industrial Press,1993,chapter 3
[32] L.Monostori. Artifieial neural networks in intelligent manufacturing. Robotiesand ComPuter IntegratedManufacturing.1992,124～127
[33]魏峰,侯健,胡宁.正确应用表面粗糙度参数.计量与测试技术.1994,6(3):352～361
[34]陈爱弟,王信义.零件加工质量(尺寸和表面粗糙度)在线检测技术研究.中国工程科学.2000:316～320
[35] P.B.Dhanish.Asim Plealgoritllllfore valuation of minimum zone eire ularityerrorfrom eoordinatedata.Joalofaehineolsdanufaeture.2002,chapter2
[36]张玉,刘平,胡新生等.轴线直线度和同轴度误差的理论研究.东北大学学报(自然科学版).1997:120～125
[37]卢碧红,葛研军.机械加工建模的传感器增强技术.机械与电子.2000(4):30～32
[38]L.Monostri.AstePtowards intelligent manufaeturing: modeling and monitoring of manufaeturing Processes through artificial neural networks. Armalsof the CIRP1994,42(l):485～488
[39]倪军.数控机床误差补偿研究的回顾与展望.中国机械工程.1997,8(l):29～33
[2] Tarng YS,Cheng ST. Int.J.Mach.Tools Manuract.1993,chapter2
[3] Herbert Schulz,Klaus Bimschas. Oprimization of precision Machining by Simulation of the Cutting Process. Annals of the CIRP.1993,chapter3
[4]史习敏,黎永明.精密机械设计.上海:上海科学技术出版社,1988年5月
[5]文秀兰,林安,谭昕,钟建琳.超精密加工技术与设备.北京:化学工业出版社,2006年1月:371～382
[6]费业泰.误差理论与数据处理.北京:机械工业出版社,2000年5月:15～16
[7]李庆详,王东生,李玉和.现代精密仪器设计北京:清华大学出版社,2004年2月:241～254
[8]李庆详.精密机械设计.北京:清华大学出版社,2005年12月:25～29
[9] Collins J A(Jack A).Mecznical Design of Machine Elements and Machines: A Failure Prenvention Perspective. New York: John Wiley,2003:87～131
[10] Lingaiah K. Machine Design Data book. New York: McGraw-Hill,2003,chapter3
[11]赵清亮,王景贺,李旦,懂申.超精密切削面临的问题.制造技术与机床.1999:199～220
[12]庞长涛.非球面加工先进技术.航空精密制造技术,2001:101～121
[13]蒋欣荣.微细加工技术.北京:北京电子工业出版社,1990
[14]袁巨龙,袁哲俊.石英基片双面抛光加工的研究.机床.1991(8)
[15]童竟主编.几何测量学.北京:机械工业出版社,1987
[16]刘贺云.精密加工技术.武汉:华中理工大学出版社,1991
[17]冯师颜.误差理论与实验数据处理.北京:科学出版社,1964:111～120
[18]郑绍濂.概率论和数理统计.上海:上海科学技术出版社,1978:37～42
[19]张世萁.测量误差及数据处理.科学出版社,1979:120～129
[20]李军.检测技术与仪表.北京:中国轻工业出版社,2000:155～163
[21]吴正毅.测试技术与测试信号处理.北京:清华大学出版社,1991:111～120
[22]卢碧红,葛研军,王启义等.虚拟数控车削加工精度预测系统研究.机械工程学报.2002:202～231
[23]卢碧红,葛研军.面向机械加工预测的模型结构.制造业自动化.2000:211～222
[24] L.Monostori.Artifieialneuralnetworksinintelligentmanufacturing.Robotiesand ComPuter Integrated Manufacturing.1992,chapter3
[25] V.Karri. Performance in Oblique Cuttingusing Conventional Methods and Neural Networks. Neural ComPuting&APPlieations.1999,chapter1
[26]机械制造中加工误差相关分析法.李传声,机械设计与制造.1989 131～142
[27] T.Efrati ,H.Flaehner. Neural Network Based Traeking Control of Mechanieal Systems. Journal of dynicsystems,measure mentandeontrol.1999:244～250
[28]赵庆志,赵玉刚.机床误差辨析.山东工程学院学报.1995(9)
[29] V.Karri. Performance in Oblique Cuttingusing Conventional Methods and NeuralNetworks. Neural ComPuting&APPlieations.8(1999):196～205
[30]孙建明,吴菊.关于机械制造几类问题的探讨.佳木斯工学院学报.1998:155～163
[31] G.E.Thyer. ComPuter Numerieal Control of Machineols. Industrial Press,1993,chapter 3
[32] L.Monostori. Artifieial neural networks in intelligent manufacturing. Robotiesand ComPuter IntegratedManufacturing.1992,124～127
[33]魏峰,侯健,胡宁.正确应用表面粗糙度参数.计量与测试技术.1994,6(3):352～361
[34]陈爱弟,王信义.零件加工质量(尺寸和表面粗糙度)在线检测技术研究.中国工程科学.2000:316～320
[35] P.B.Dhanish.Asim Plealgoritllllfore valuation of minimum zone eire ularityerrorfrom eoordinatedata.Joalofaehineolsdanufaeture.2002,chapter2
[36]张玉,刘平,胡新生等.轴线直线度和同轴度误差的理论研究.东北大学学报(自然科学版).1997:120～125
[37]卢碧红,葛研军.机械加工建模的传感器增强技术.机械与电子.2000(4):30～32
[38]L.Monostri.AstePtowards intelligent manufaeturing: modeling and monitoring of manufaeturing Processes through artificial neural networks. Armalsof the CIRP1994,42(l):485～488
[39]倪军.数控机床误差补偿研究的回顾与展望.中国机械工程.1997,8(l):29～33