三维工艺设计中的特征识别技术研究
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摘要
高效快捷的工艺设计方法是企业及时地把设计理念转化为真实产品的重要保证。工艺信息的获取是工艺设计的基础,其关键是如何从设计模型中直接获取工艺信息,特征识别作为工艺信息获取的重要方法一直是研究的热点。因此,本文针对三维工艺设计中的特征识别技术,采用切削体分解组合的方法进行研究,研究内容主要包括以下几个方面。
结合工艺设计的实际情况,提出了切削体分解过程中的单元切削体、分割面、工序切削体等包含丰富工艺信息的概念。研究了单元切削体的建模方式,采用自定义扩展的属性邻接图描述本文所要构建的单元切削体,建立了车、铣等典型加工方法的单元切削体形式。
针对不同设备的加工能力,研究了切削体分解成单元切削体的具体算法,阐述了分解流程及其中涉及到的凹边的判定依据,探讨了参与分解切削体的分割面的形成方法及其的分割准则。分析了工艺加工中基准先行、先面后孔、先粗后精等原则在分解算法中的表现方式。
针对相同设备的加工能力范围,研究了相似单元切削体组合成工序切削体的方法及流程,分析了如何在组合过程中考虑工艺原则及空间几何约束等因素,并探讨了若干典型的工艺原则所对应的组合原则。
探讨了非形状特征的识别方法,并结合切削体分解法对形状特征的识别阐述如何将识别的结果应用到工序切削体的工艺映射过程中。论文末尾给出了一个应用该算法识别某具体零件加工特征的实例,并在SolidWorks软件平台上实现了部分关键技术,从而验证了该方法在理论上的可行性。
本文所研究的特征识别方法是在原有的切削体分解法基础上进行了扩展,创新之处表现在识别特征的过程中不仅考虑实体的几何拓扑信息,更融入了工艺原则的约束,与工艺设计的应用结合更为紧密。论文所研究的特征识别方法为提高工艺设计的自动化水平和智能化程度探索了一条新途径。
The efficient and fast process planning method is important guarantee for enterprises to convert design concepts into real product quickly. The extraction of process information is basis of process planning, and the key point is how to extract process information from CAD models directly. As one of the most important method for extracting process information, feature recognition has been always became research hotspot. Therefore, feature recognition technology of 3D process planning has been researched in this thesis using delta volume decomposition and combination method. The main contents and works of this thesis are as follow.
Combined with actual situation of process planning, the concepts of cell delta volume, partition surface, process delta volume in the decomposition process were put forward, and the concepts contain abundant process information. The modeling method of cell delta volume was researched. The cell delta volume models were builded by self-Defined Extended Attributed Adjacency Graph. The turning, milling and other typical cell delta volume were builded.
According to different equipment processing capacity, the method of decomposing delta volume into cell delta volume was researched. The decomposition process and judgment rule of concave edge involved were expounded. The generating way and segmental rule of partition surface used to decompose delta volume were discussed. The reflect way in decomposition algorithm of principles in process planning about benchmark first, plane first, rough first. etc was analyzed.
According to machining capabilities of the same equipment, the method and process of combining similar cell delta volume into process delta volume were researched. The factors of how to consider process principle and geometric constraint in the algorithm were analyzed. Some actual combination principles corresponding with some typical process principles were discussed.
The recognition method of non form feature was discussed. Combined with form feature recognition using delta volume decomposition method, the method how to apply the result of recognition to process matching of process delta volume was expounded. In the end of the thesis, an example was given to explain how to recognize machining features of a actual part by the algorithm. Some key technology was realized in SolidWorks system. Therefore, the feasibility of the algorithm was proved in theory.
The feature recognition method researched in this thesis is extension of exist volume decomposition. The innovation lies in the point that in the process of feature recognition, it considers not only geometric topology information, but also constraints of process rules. It combines with actual situation of process planning more closely. The feature recognition technology researched in this thesis explores a new way for enhancing automation level and deepening intelligence degree of process planning.
结合工艺设计的实际情况,提出了切削体分解过程中的单元切削体、分割面、工序切削体等包含丰富工艺信息的概念。研究了单元切削体的建模方式,采用自定义扩展的属性邻接图描述本文所要构建的单元切削体,建立了车、铣等典型加工方法的单元切削体形式。
针对不同设备的加工能力,研究了切削体分解成单元切削体的具体算法,阐述了分解流程及其中涉及到的凹边的判定依据,探讨了参与分解切削体的分割面的形成方法及其的分割准则。分析了工艺加工中基准先行、先面后孔、先粗后精等原则在分解算法中的表现方式。
针对相同设备的加工能力范围,研究了相似单元切削体组合成工序切削体的方法及流程,分析了如何在组合过程中考虑工艺原则及空间几何约束等因素,并探讨了若干典型的工艺原则所对应的组合原则。
探讨了非形状特征的识别方法,并结合切削体分解法对形状特征的识别阐述如何将识别的结果应用到工序切削体的工艺映射过程中。论文末尾给出了一个应用该算法识别某具体零件加工特征的实例,并在SolidWorks软件平台上实现了部分关键技术,从而验证了该方法在理论上的可行性。
本文所研究的特征识别方法是在原有的切削体分解法基础上进行了扩展,创新之处表现在识别特征的过程中不仅考虑实体的几何拓扑信息,更融入了工艺原则的约束,与工艺设计的应用结合更为紧密。论文所研究的特征识别方法为提高工艺设计的自动化水平和智能化程度探索了一条新途径。
The efficient and fast process planning method is important guarantee for enterprises to convert design concepts into real product quickly. The extraction of process information is basis of process planning, and the key point is how to extract process information from CAD models directly. As one of the most important method for extracting process information, feature recognition has been always became research hotspot. Therefore, feature recognition technology of 3D process planning has been researched in this thesis using delta volume decomposition and combination method. The main contents and works of this thesis are as follow.
Combined with actual situation of process planning, the concepts of cell delta volume, partition surface, process delta volume in the decomposition process were put forward, and the concepts contain abundant process information. The modeling method of cell delta volume was researched. The cell delta volume models were builded by self-Defined Extended Attributed Adjacency Graph. The turning, milling and other typical cell delta volume were builded.
According to different equipment processing capacity, the method of decomposing delta volume into cell delta volume was researched. The decomposition process and judgment rule of concave edge involved were expounded. The generating way and segmental rule of partition surface used to decompose delta volume were discussed. The reflect way in decomposition algorithm of principles in process planning about benchmark first, plane first, rough first. etc was analyzed.
According to machining capabilities of the same equipment, the method and process of combining similar cell delta volume into process delta volume were researched. The factors of how to consider process principle and geometric constraint in the algorithm were analyzed. Some actual combination principles corresponding with some typical process principles were discussed.
The recognition method of non form feature was discussed. Combined with form feature recognition using delta volume decomposition method, the method how to apply the result of recognition to process matching of process delta volume was expounded. In the end of the thesis, an example was given to explain how to recognize machining features of a actual part by the algorithm. Some key technology was realized in SolidWorks system. Therefore, the feasibility of the algorithm was proved in theory.
The feature recognition method researched in this thesis is extension of exist volume decomposition. The innovation lies in the point that in the process of feature recognition, it considers not only geometric topology information, but also constraints of process rules. It combines with actual situation of process planning more closely. The feature recognition technology researched in this thesis explores a new way for enhancing automation level and deepening intelligence degree of process planning.
引文
[1]张胜文,赵良才.计算机辅助工艺设计——CAPP系统设计[M].北京：机械工业出版社,2005.
[2]肖伟跃CAPP中的智能信息处理技术[M].长沙：国防科技大学出版社,2002.
[3]张振明.现代CAPP的应用与发展趋势[J]. CAD/CAM与制造业信息化,2004,(21)：30-31.
[4]关文天,丘宏俊,陶华.基于特征转换的CAD/CAPP集成技术研究[J].机床与液压,2004,(11)：160-163.
[5]周广平.网络化加工特征识别方法研究[D].杭州：浙江大学,2004.
[6]任明轩.基于STEP文件特征识别系统的研究[D].天津：天津大学,2007.
[7]李伟平,谷正气,邓彪.面向CAD/CAPP/CAM的特征识别技术[J].中国机械工程,2006,17(10)：249-253.
[8]Bojan Babic, Nenad Nesic, Zoran Miljkovic. A review of automated feature recognition with rule-based pattern recognition[J]. Computers in Industry,2008,59(4):321-337.
[9]张振明,许建新,贾晓亮.现代CAPP技术与应用[M].西安：西北工业大学出版社,2003.
[10]吴江.基于特征识别的CAD/CAPP集成技术研究[D].南京：南京航空航天大学,2005.
[11]赵汝嘉,孙波.计算机辅助工艺设计(CAPP)[M]北京：机械工业出版社,2003.
[12]Y Shen, J Shah. Recognition of machining features based on HSPCE decomposition, feature composition, and process centered classification[J]. ASME Transactions, Journal of Mechanical Design,1998,120(4):668-677.
[13]Emad S.Abouel Nasr, Ali K.Kamrani. A new methodology for extracting manufacturing features from CAD system[J]. Computers & Industrial Engineering,2006, (51):389-415.
[14]F.S.Y. Wong, K.B. Chuah, P.K. Venuvinod. Automated inspection process planning: Algorithmic inspection feature recognition, and inspection case representation for CBR[J]. Robotics and Computer-Integrated Manufacturing,2006,22 (3):56-68.
[15]Somashekar Subrahmanyam, Michael Wozyn. An overview of automatic feature recognition techniques for computer-aided process planning[J]. Computers in Industry, 1995,26(3):1-21.
[16]胡文伟.特征建模与特征识别及其在CAD/CAPP集成中的应用[D].南京：南京航空航天大学,2006.
[17]张红武.语义特征造型系统中相交特征识辨机制的研究[D].哈尔滨：哈尔滨理工大学,2005.
[18]陈树晓.基于零件三维特征模型的自动工艺规划研究[D].太原：中北大学,2007.
[19]卢世坤.基于特征识别技术的CAPP工艺卡自动生成研究[J].煤矿机械,2009,30(9)：129-130.
[20]Hiroshi Sakurai. Volume decomposition and feature recognition, part I:polyhedral objects[J]. Computer-Aided Design,1995,27(11):833-843.
[21]Hiroshi Sakurai. Volume decomposition and feature recognition, part II:curved objects[J]. Computer-Aided Design,1996,28(6):519-537.
[22]Yoonhwan, Hiroshi Sakurai. Recognition of maximal features by volume decomposition[J]. Computer-Aided Design,2002,34(3):195-207.
[23]陈洪丽,孙立镌.特征造型系统中基于圆柱的特征识别[J].哈尔滨理工大学学报,2006,11(4)：22-25.
[24]陈洪丽.语义特征造型系统中特征模型转换的研究[D].哈尔滨：哈尔滨理工大学,2006.
[25]徐正.三维CAPP中零件特征提取及基于遗传算法的工艺排序研究[D].武汉：华中科技大学,2005.
[26]邱飞燕CAPP. NET系统关键技术的研究与实现[D].南京：南京航空航天大学,2003.
[27]顾小峰.2.5维零件特征识别及其应用研究[D].西安：西北工业大学,2006.
[28]柯常忠,曾霞.实体造型特征识别技术的研究[J].装备制造技术,2007,(1)：1-3.
[29]金平.协同设计环境下的特征建模技术研究[D].重庆：重庆大学,2002.
[30]王大康,刘永峰,石亚宁.智能化CAPP系统的工艺决策[J].北京工业大学学报,2003,29(2)：129-132.
[31]花广如,周雄辉.特征识别的现状与存在的问题及解决方案[J].机床与液压,2008,36(4)：19-23.
[32]Martin G.Marchetta, Raymundo Q.Forradellas. An artificial intelligence planning approach to manufacturing feature recognition[J]. Computer-Aided Design,2010, (42): 248-256.
[33]赵鹏,盛步云,邓伟刚.工艺设计过程中的切削体分解组合策略[J].计算机集成制造系统,2010,16(9)：1793-1800.
[34]V.B.Sunil, Rupal Agarwal, S.S. Pande. An approach to recognize interacting features from B-Rep CAD models of prismatic machined parts using a hybrid (graph and rule based) technique[J]. Computers in Industry,2010, (61):686-701.
[35]V.B.Sunil, S.S. Pande. Automatic recognition of features from freeform surface CAD models[J]. Computer-Aided Design,2008, (40):502-517.
[36]Pralay Pala, A.M. Tiggab, A Kumarb. Feature extraction from large CAD databases using genetic algorithm[J]. Computer-Aided Design,2005,37(5):545-558.
[37]Shuming Gao, Wei Zhao, Hongwei Lin, et al. Feature suppression based CAD mesh model simplification[J]. Computer-Aided Design,2010, (42):1178-1188.
[38]Xionghui Zhou, Yanjie Qiu, Guangru HuaA et al. A feasible approach to the integration of CAD and CAPP[J]. Computer-Aided Design,2007,39(7):324-338.
[39]孙凤池,王龙山.机械加工工艺手册,第2卷加工技术卷[M].北京：机械工业出版社,2006.
[40]高曙明.自动特征识别技术综述[J].计算机学报,1998,21(3),281-288.
[41]K.Rahmani, B.Arezoo. A hybrid hint-based and graph-based framework for recognition of interacting milling features[J]. Computers in Industry,2007, (58):304-312.
[42]N.Ismail, N.Abu Bakar, A.H.Juri. Recognition of cylindrical and conical features using edge boundary classification[J]. International Journal of Machine Tools & Manufacture, 2005, (45):649-655.
[43]V.Rameshbabu, M.S.Shunmugam. Hybrid feature recognition method for setup planning from STEP AP-203[J]. Robotics and Computer-Integrated Manufacturing,2009, (25): 393-408.
[44]Yoonhwan Woo. Fast cell-based decomposition and applications to solid modeling[J]. Computer-Aided Design,2003, (35):969-977.
[45]W.F. Bronsvoort, A. Noort. Multiple-view feature modelling for integral product development[J]. Computer-Aided Design,2004, (36):929-946.
[46]Tobias Dipper, Xun Xu, Peter Klemm. Defining, recognizing and representing feature interactions in a feature-based data model[J]. Robotics and Computer-Integrated Manufacturing,2011, (27):101-114.
[47]A.J.Alvares, J.C.E.Ferreira, R.M.Lorenzo. An integrated web-based CAD/CAPP/CAM system for the remote design and manufacture of feature-based cylindrical parts[J]. J Intell Manuf,2008,19(6):643-659.
[48]王忠宾,许娟,陈禹六.基于多代理的智能CAPP系统体系结构研究[J].机械科学与技术,2007,26(6)：746-750.
[49]王丽娟,张新红.基于并行工程的CAD/CAPP系统集成与优化[J]. CAD/CAM与制造业信息化,2006,(4)：20-21.
[2]肖伟跃CAPP中的智能信息处理技术[M].长沙：国防科技大学出版社,2002.
[3]张振明.现代CAPP的应用与发展趋势[J]. CAD/CAM与制造业信息化,2004,(21)：30-31.
[4]关文天,丘宏俊,陶华.基于特征转换的CAD/CAPP集成技术研究[J].机床与液压,2004,(11)：160-163.
[5]周广平.网络化加工特征识别方法研究[D].杭州：浙江大学,2004.
[6]任明轩.基于STEP文件特征识别系统的研究[D].天津：天津大学,2007.
[7]李伟平,谷正气,邓彪.面向CAD/CAPP/CAM的特征识别技术[J].中国机械工程,2006,17(10)：249-253.
[8]Bojan Babic, Nenad Nesic, Zoran Miljkovic. A review of automated feature recognition with rule-based pattern recognition[J]. Computers in Industry,2008,59(4):321-337.
[9]张振明,许建新,贾晓亮.现代CAPP技术与应用[M].西安：西北工业大学出版社,2003.
[10]吴江.基于特征识别的CAD/CAPP集成技术研究[D].南京：南京航空航天大学,2005.
[11]赵汝嘉,孙波.计算机辅助工艺设计(CAPP)[M]北京：机械工业出版社,2003.
[12]Y Shen, J Shah. Recognition of machining features based on HSPCE decomposition, feature composition, and process centered classification[J]. ASME Transactions, Journal of Mechanical Design,1998,120(4):668-677.
[13]Emad S.Abouel Nasr, Ali K.Kamrani. A new methodology for extracting manufacturing features from CAD system[J]. Computers & Industrial Engineering,2006, (51):389-415.
[14]F.S.Y. Wong, K.B. Chuah, P.K. Venuvinod. Automated inspection process planning: Algorithmic inspection feature recognition, and inspection case representation for CBR[J]. Robotics and Computer-Integrated Manufacturing,2006,22 (3):56-68.
[15]Somashekar Subrahmanyam, Michael Wozyn. An overview of automatic feature recognition techniques for computer-aided process planning[J]. Computers in Industry, 1995,26(3):1-21.
[16]胡文伟.特征建模与特征识别及其在CAD/CAPP集成中的应用[D].南京：南京航空航天大学,2006.
[17]张红武.语义特征造型系统中相交特征识辨机制的研究[D].哈尔滨：哈尔滨理工大学,2005.
[18]陈树晓.基于零件三维特征模型的自动工艺规划研究[D].太原：中北大学,2007.
[19]卢世坤.基于特征识别技术的CAPP工艺卡自动生成研究[J].煤矿机械,2009,30(9)：129-130.
[20]Hiroshi Sakurai. Volume decomposition and feature recognition, part I:polyhedral objects[J]. Computer-Aided Design,1995,27(11):833-843.
[21]Hiroshi Sakurai. Volume decomposition and feature recognition, part II:curved objects[J]. Computer-Aided Design,1996,28(6):519-537.
[22]Yoonhwan, Hiroshi Sakurai. Recognition of maximal features by volume decomposition[J]. Computer-Aided Design,2002,34(3):195-207.
[23]陈洪丽,孙立镌.特征造型系统中基于圆柱的特征识别[J].哈尔滨理工大学学报,2006,11(4)：22-25.
[24]陈洪丽.语义特征造型系统中特征模型转换的研究[D].哈尔滨：哈尔滨理工大学,2006.
[25]徐正.三维CAPP中零件特征提取及基于遗传算法的工艺排序研究[D].武汉：华中科技大学,2005.
[26]邱飞燕CAPP. NET系统关键技术的研究与实现[D].南京：南京航空航天大学,2003.
[27]顾小峰.2.5维零件特征识别及其应用研究[D].西安：西北工业大学,2006.
[28]柯常忠,曾霞.实体造型特征识别技术的研究[J].装备制造技术,2007,(1)：1-3.
[29]金平.协同设计环境下的特征建模技术研究[D].重庆：重庆大学,2002.
[30]王大康,刘永峰,石亚宁.智能化CAPP系统的工艺决策[J].北京工业大学学报,2003,29(2)：129-132.
[31]花广如,周雄辉.特征识别的现状与存在的问题及解决方案[J].机床与液压,2008,36(4)：19-23.
[32]Martin G.Marchetta, Raymundo Q.Forradellas. An artificial intelligence planning approach to manufacturing feature recognition[J]. Computer-Aided Design,2010, (42): 248-256.
[33]赵鹏,盛步云,邓伟刚.工艺设计过程中的切削体分解组合策略[J].计算机集成制造系统,2010,16(9)：1793-1800.
[34]V.B.Sunil, Rupal Agarwal, S.S. Pande. An approach to recognize interacting features from B-Rep CAD models of prismatic machined parts using a hybrid (graph and rule based) technique[J]. Computers in Industry,2010, (61):686-701.
[35]V.B.Sunil, S.S. Pande. Automatic recognition of features from freeform surface CAD models[J]. Computer-Aided Design,2008, (40):502-517.
[36]Pralay Pala, A.M. Tiggab, A Kumarb. Feature extraction from large CAD databases using genetic algorithm[J]. Computer-Aided Design,2005,37(5):545-558.
[37]Shuming Gao, Wei Zhao, Hongwei Lin, et al. Feature suppression based CAD mesh model simplification[J]. Computer-Aided Design,2010, (42):1178-1188.
[38]Xionghui Zhou, Yanjie Qiu, Guangru HuaA et al. A feasible approach to the integration of CAD and CAPP[J]. Computer-Aided Design,2007,39(7):324-338.
[39]孙凤池,王龙山.机械加工工艺手册,第2卷加工技术卷[M].北京：机械工业出版社,2006.
[40]高曙明.自动特征识别技术综述[J].计算机学报,1998,21(3),281-288.
[41]K.Rahmani, B.Arezoo. A hybrid hint-based and graph-based framework for recognition of interacting milling features[J]. Computers in Industry,2007, (58):304-312.
[42]N.Ismail, N.Abu Bakar, A.H.Juri. Recognition of cylindrical and conical features using edge boundary classification[J]. International Journal of Machine Tools & Manufacture, 2005, (45):649-655.
[43]V.Rameshbabu, M.S.Shunmugam. Hybrid feature recognition method for setup planning from STEP AP-203[J]. Robotics and Computer-Integrated Manufacturing,2009, (25): 393-408.
[44]Yoonhwan Woo. Fast cell-based decomposition and applications to solid modeling[J]. Computer-Aided Design,2003, (35):969-977.
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[46]Tobias Dipper, Xun Xu, Peter Klemm. Defining, recognizing and representing feature interactions in a feature-based data model[J]. Robotics and Computer-Integrated Manufacturing,2011, (27):101-114.
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