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面向复杂型腔工件高效数控加工的刀具优选技术研究
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摘要
型腔工件在现代工业生产中涉及面非常广泛,如涉及到汽车、家电、机床等制造行业广泛应用的模具系统的核心构件,航天航空、海洋工程等领域高端装备的机舱等结构件,以及复杂金属工艺品的凹型曲面等。型腔工件通常形状复杂、品种多样,致使数控加工过程复杂,易于出现加工效率不高,质量难于保证等实际问题。同时,型腔加工还面临着短工期、高质量、低成本的迫切需求。因此,型腔的高效数控加工是一个亟待解决的问题。刀具优选是实现型腔高效数控加工的关键内容之一,对提高型腔加工的效率和质量,并降低成本有重要作用。为此,本文面向型腔的高效数控加工,对刀具优选技术展开研究,主要内容如下:
     分析型腔数控加工对刀具要求的特点,明确型腔数控加工刀具优选所包含的主要内容,构建一个包含目标层、优化功能层、技术支持层和数据层的刀具优选技术框架,在此基础上,阐述本文刀具优选的技术过程和关键技术。
     在分析加工目标、工件、机床和工艺等因素对刀具材料决策过程的影响的基础上,提出一种面向复杂切削实况的刀具材料决策方法。该方法设计并构建若干与常用加工目标相应的、并包含待考察刀具材料性能指标及其初步权重的模板供决策选择;建立工件、机床和工艺的特征体系用于提取实际加工情况下工件、机床和工艺的具体特征;利用知识推理等方法导出工件、机床和工艺的特征对刀具材料性能的约束与侧重,并将约束用于筛选出合格的刀具材料,将侧重用于修正用户所选模板中的刀具材料性能指标权重;在此基础上,利用模板中的性能指标与修正后的指标权重建立刀具材料评价模型,实现对合格刀具材料的评价与择优。应用案例说了该方法的可行性和实用性。
     在优选型腔加工的刀具直径和刀具组合的过程中,判别加工域是否可以被拆分具有重要的基础意义。为此,提出一种用于判别型腔加工域是否可分的概念及方法——型腔铣削单纯区及其判别方法。首先提出铣削单纯区的概念,给出其定义,指出铣削单纯区是一类当且仅当使用一种刀具就可实现最优加工的特殊区域,并且具有不可再分性、完全覆盖性和效益最优性等三大特点。然后给出并论证铣削单纯区的判别条件,从加工成本的角度建立铣削单纯区的判别模型,并在此基础上设计了铣削单纯区的判别算法。算例结果证明了所提出的概念及方法的理论价值和实用价值。
     提出一种支持型腔粗加工刀具序列高效优化的刀具筛选方法。通过对比刀具组合过程中因不同刀具的优势互补而产生的效益增量与因换刀带来的相关效益损失量,建立一种用于判断刀具序列是否有效的分析模型;在此基础上,从刀具序列的组合形态的角度构造并证明一种可以判别部分冗余刀具的规则,将该规则与基于几何、设备和工艺等约束的刀具筛选方法相串联,可获得良好的刀具筛选效果。算例结果表明所提方法在去除部分冗余刀具上效果明显。
     提出一种改进的型腔粗加工可行刀具序列构建方法。对现行的基于有向图的可行刀具序列构建方法进行分析,指出对刀具进行近似纯数学上的排列组合使得解空间偏大,进而制约刀具序列优化效率是该方法的主要不足;通过对刀具序列有效性的分析,发现可行刀具序列构建过程中刀具之间存在的互斥特性,并将该特性引入至现行的可行刀具序列构建方法之中,加强对解空间的约束,实现对大部分无效序列的预先排除。算例结果表明,改进后的方法可明显排除大部分的无效刀具序列,对实现刀具序列的高效优化具有良好的支持作用。
Pockets are widely applied in modern industry. For instance, pockets are core components of mould systems of manufacturing industries like automobile, appliances, and machine tools. Pockets are also structural member of high-end equipments in fields like aerospace, aviation, and oceaneering. In addition, pockets refer to modeling faces of complex metal artwork. For the complex shape and high manufacturing quality of pockets, most pockets can only be machined on multi-axis NC machine tools with complex machining process, which is prone to practical problems like low machining efficiency, low quality, and high cost. For these reasons, the study on methods and technologies of high-efficiency NC machining of complex pocket is of great importance. Due to the cutting tool selection affects the machining time, quality and cost greatly in pocket NC machining, in this paper, methods and technologies of cutting tool selection for high-efficiency NC machining of complex pocket are studied.
     The characteristics of pocket and pocket machining are analyzed to conduct the main task of cutting tool selection of pocket NC machining. In order to support high-efficiency NC machining of pocket, a technology architecture of cutting tool selection is established, which consists of four levels: object level, function level, supporting technology level and data level. Based on the technology architecture, the process of cutting tool selection and the critical technologies of this paper are elaborated.
     Due to the numerous types of the cutter material in modern NC machining, and the complexity and diversity of the machining site condition (including machining target, workpiece, machine tools and machining process), the optimal selection of cutter material becomes difficult. To solve the problem, the effect of the above four machining site conditions on cutter material decision is analyzed, based on which a cutter material decision method oriented to complex machining site condition is proposed. According to common machining target, this method designs and builds several templates for user to choose, which contain cutter material performance index and initial index weight. The characteristics architecture of workpiece、machine tools and machining process is set up to identify and extract the specific characteristics in practical machining. Methods like knowledge reasoning are applied to derive constraints and correction coefficient of cutter material performance from the three aspects of characteristics. The constraints are used to screen out qualified cutter material, and the correction coefficient is used to revise the cutter material performance index weight of the user chosen template. On the bases of the performance index and revised index weight, the cutter material evaluation model is established, and the evaluation and optimal selection of qualified cutter material is realized. The case study indicates the feasibility and practicability of the method.
     The geometry of pocket is generally complex, and it is usually necessary to optimize tool sequence (TS) while improving the pocket machining efficiency. As the proper division of machining region is a foundation for high-efficiency TS, whether the machining region could be divided becomes a basic problem. In order to solve the problem, a concept of simplex region (SR) is proposed, and the recognition method of SR is put forward. The concept and definition of SR is given, which indicates that SR is a special region that could be machined in high efficiency by just one cutting tool. Then, the recognition condition of SR is analyzed and demonstrated, the recognition model is set up from the perspective of machining cost, and the recognition algorithm of SR is designed. The given case study of SR recognition proves the theoretical and practical value of the presented concept and method.
     Cutter screening is an important link in the TS optimization of pocket rough machining, and is aimed at screening out feasible cutters. However, most current cutter screening methods are based on constrains extracted from pocket geometry, machining tools, and machining process, and rarely take constrains between cutters into consideration, thus, redundant cutters appear in feasible cutter set. In this paper, a mathematic model by analyzing benefits increment and benefits decrement in cutters combination process is established for analyzing validity of TS. In addition, a redundant cutter judging rule based on the model is constructed and demonstrated. By connecting the existing cutters screening methods and the new rule for judging redundant cutters, a new cutter screening method for high-performance TS optimization is obtained. The realization techniques of the new method, including the machining ability estimate of cutters and validity calculation of TS, are studied. The case study indicates the ability of the method to eliminate part of the redundant cutting tools.
     Constructing feasible TS is another important link in the TS optimization of pocket rough machining, which takes certain permutation and combination method to obtain a series of optional feasible TS. This paper analyzes the current feasible TS constructing method based on directed graph, and point out its approximately pure mathematical permutation and combination of cutting tools leads to oversize solution space, thereby restricts the optimization performance. In order to improve the current method, based on analyzing the advantages and disadvantages generated in the process of cutting tools combining, an analytical model for judging the validity of TS is established. By importing this model to the current method, large amount of the invalid TS are eliminated from the solution space, thus the optimization performance is accordingly promoted. The implementing technologies (including the TS validity analysis) of the new method are studied. The case study shows the obvious effect of the improved method on eliminating invalid tool sequences.
引文
[1]刘航.模具制造技术[M].西安:西安电子科技大学出版, 2006.
    [2]飞机机体零件的高速加工[OL]. [2011-03-18]. http://wenku.baidu.com/view/f75429d149649b6648d747d7.html
    [3]飞机制造中需要用机床加工的典型零件[OL]. [2011-03-18]. http://china.toocle.com/cbna/item/2008-11-03/4047714.html
    [4]王彪,张兰.数控加工技术[M].北京:中国林业出版社, 2006.
    [5]蔡玉俊.模具型腔高效数控加工策略及参数优化研究[D].大连理工大学, 2005.
    [6] 2011年我国模具产业发展形势展望及预测[OL]. [2011-03-18]. http://news.machine365.com/content/2011/0308/295604.html
    [7]中国模具行业“十二五”发展规划[OL]. [2011-03-18]. http://www.molds.cn/html/blog/56/21545.htm
    [8]易平.面向模具企业的生产过程管理系统的研究与开发[D].华中科技大学, 2005.
    [9]李俊龙.面向模具制造过程的信息管理系统研究与开发[D].大连理工大学, 2004.
    [10]胡明茂.汽车模具制造企业工具管理系统的研制与开发[D].武汉科技大学, 2007.
    [11]邹泽明.面向敏捷制造的数控集成平台及其在模具制造企业中的应用[D].上海交通大学, 2006.
    [12]苑荣华,孙杰,宋戈,等. 69111铣削加工参数优化研究[J].工具技术. 2009(11): 18-21.
    [13]曾孝云,樊庆文,谢玉凤.正交试验在难加工材料切削参数优化中的应用[J].工具技术.2004, 38(6): 43-44.
    [14]吴江妙,杨志强. Inconel 718合金高速切削加工的工艺参数优化[J].机械制造. 2009, 47(10): 53-55.
    [15]王晓琴,艾兴,赵军,等.涂层刀具铣削Ti6A14V刀具寿命及切削参数优化[J].武汉理工大学学报. 2008, 30(10): 109-112.
    [16]陈志同,张保国.面向单元切削过程的切削参数优化模型[J].机械工程学报. 2009, 45(05): 230-236.
    [17]李涛,陈世平.铣削加工中切削用量的优化[J].工具技术. 2009, 43(12): 59-61.
    [18]刘晶,李旭东,靳永强.金属切削参数多目标优化及有限元分析[J].工具技术. 2009, 43(10): 61-63.
    [19]王蕾,葛研军,巩亚东,等.基于客户机/服务器的数控铣削工艺参数优化[J].中国机械工程. 2003, 14(10): 858-860.
    [20]张臣,周来水,余湛悦,等.基于仿真数据的数控铣削加工多目标变参数优化[J].计算机辅助设计与图形学学报. 2005, 17(05): 1039-1045.
    [21]蒋亚军,娄臻亮,李明辉.基于模糊粗糙集理论的模具数控切削参数优化[J].上海交通大学学报. 2005, 39(07): 1115-1118.
    [22]卢泽生,王明海.基于遗传算法的超精密切削表面粗糙度预测模型参数辨识及切削用量优化[J].机械工程学报. 2005, 41(11): 158-162.
    [23]武星星,朱喜林,李晓梅.基于混合输入型模糊系统的机械加工参数优化[J].中国机械工程. 2007, 18(03): 273-276.
    [24]武星星,朱喜林,杨会肖.自适应神经模糊推理系统改进算法在机械加工参数优化中的应用[J].机械工程学报. 2008, 44(1): 199-204.
    [25]朱喜林,吴博达,武星星,等. BP网络在优化机械加工参数中的应用[J].计算机集成制造系统-CIMS. 2004, 10(09): 1139-1143.
    [26]朱小平,王涛.基于多目标粒子群算法的切削用量多决策优化研究[J].组合机床与自动化加工技术. 2010(03): 27-29.
    [27] Chu C N, Kim S Y, Lee J M, et al. Feed-Rate Optimization of Ball End Milling Considering Local Shape Features [J]. CIRP Annals - Manufacturing Technology. 1997, 46(1): 433-436.
    [28] Feng H, Su N. Integrated tool path and feed rate optimization for the finishing machining of 3D plane surfaces[J]. International Journal of Machine Tools & Manufacture. 2000, 40: 1557-1572.
    [29] Ko J H, Yun W S, Cho D. Off-line feed rate scheduling using virtual CNC based onan evaluation of cutting performance [J]. Compute Aided Design. 2003, 35: 383-393.
    [30] Ko J H, Cho D. Feed rate scheduling model considering transverse rupture strength ofa tool for 3D ball-end milling[J]. International Journal of Machine Tools & Manufacture. 2004, 44: 1047-1059.
    [31] Bae S, Ko K, Kim B H, et al. Automatic feedrate adjustment for pocket machining [J]. Compute Aided Design. 2003, 35: 495-500.
    [32] Salami R, Sadeghi M H, Motakef B. Feed rate optimization for 3-axis ball-end milling of sculptured surfaces [J]. International Journal of Machine Tools & Manufacture. 2007, 47: 760-767.
    [33] Qian L, Yang B, Lei S. Comparing and combining off-line feedrate rescheduling strategies in free-form surface machining with feedrate acceleration and deceleration[J]. Robotics and Computer-Integrated Manufacturing. 2008, 24(6): 796-803.
    [34]张臣,周来水,安鲁陵,等.基于铣削力仿真的离线进给速度优化技术[J].南京航空航天大学学报. 2009, 41(3): 358-363.
    [35]石磊,张英杰,李宗斌,等.切削力基本恒定约束下球头铣刀加工自由曲面切削参数的优化[J].中国机械工程. 2009, 20(23): 2773-2776.
    [36] Choy H S, Chan K W. Machining tactics for interior corners of pockets[J]. International Journal of Advanced Manufacturing Technology. 2002, 20(10): 741-748.
    [37] Narayanaswami R, Choi Y. NC machining of freeform pockets with arbitrary wall geometry using a grid-based navigation approach[J]. International Journal of Advanced Manufacturing Technology. 2001, 18(10): 708-716.
    [38] Chuang J, Yang D C H. A laplace-based spiral contouring method for general pocket machining[J]. International Journal of Advanced Manufacturing Technology. 2007, 34(7-8): 714-723.
    [39] Jeong J, Kim K. Tool path generation for machining free-form pockets using Voronoidiagrams[J]. International Journal of Advanced Manufacturing Technology. 1998, 14(12): 876-881.
    [40] Jeong J, Kim K. Generation of tool paths for machining free-form pockets with islands using distance maps[J]. International Journal of Advanced Manufacturing Technology.1999, 15(5): 311-316.
    [41] Jeong J, Kim K S. Generating tool paths for free-form pocket machining using z-buffer-based Voronoi diagrams[J]. International Journal of Advanced Manufacturing Technology. 1999, 15(3): 182-187.
    [42]谭显春,刘飞,曹华军,等.面向绿色制造的刀具选择决策模型及其应用[J].重庆大学学报(自然科学版). 2003, 26(3): 117-121.
    [43]闫莉,陈青.绿色切削加工中刀具选择的灰关联决策[J].工具技术. 2010, 44(5): 81-83.
    [44]毛文,洪顺华.绿色制造中刀具选择决策方案的模糊综合评价[J].机械制造与自动化. 2005, 34(4): 4-6, 7.
    [45] Arezoo B, Ridgway K, Al-Ahmari A M A. Selection of cutting tools and conditions of machining operations using an expert system[J]. Computers in Industry. 2000, 42: 43-58.
    [46]徐和国,王玉,周雄辉.基于实体模型的计算机辅助刀具选择系统[J].上海交通大学学报. 2005, 39(1): 113-116.
    [47]王玉,高崇辉,徐和国.模具型腔数控加工计算机辅助刀具选择研究[J].计算机集成制造系统. 2004, 10(2): 226-229.
    [48]蒋亚军,娄臻亮.规则推理与实例推理在模具加工刀具智能化选择中的应用[J].上海交通大学学报. 2005, 39(7): 1066-1069.
    [49]高荣.数控刀具选择器的设计[J].机床与液压. 2005(2): 57-59.
    [50]王云华.基于特征的高速铣刀优选系统开发[D].哈尔滨理工大学, 2007.
    [51]陈文.基于专家系统的数控刀具选配系统的研究与开发[D].重庆大学, 2006.
    [52]姚磊.基于STEP-NC特征建模及刀具选配系统研究[D].山东大学, 2006.
    [53]赵晖,闫献国,陈峙,等.基于工件加工工艺特征的数控刀具选配系统[J].组合机床与自动化加工技术. 2010(4): 101-102.
    [54]林朝平,郭国林.数控加工编程中铣刀选择的工艺分析[J].工具技术. 2006, 40(12): 68-69.
    [55]侯立中,解晓东.平装可转位铣刀的合理选用[J].工具技术. 2001, 35(4): 42-44.
    [56]宋志国,宋艳.高速铣削刀具及切削参数的选择[J].组合机床与自动化加工技术. 2009(1): 88-90.
    [57] Yang D C H, Han Z. Interference detection and optimal tool selection in 3-axis NC machining of free-form surfaces[J]. Computer-Aided Design. 1999, 31(5): 303-315.
    [58] Choi B K, Jun C S. Ball-end cutter interference avoidance in NC machining of sculptured surfaces[J]. CAD Computer Aided Design. 1989, 21(6): 371-378.
    [59] Ilushin O, Elber G, Halperin D, et al. Precise global collision detection in multi-axis NC-machining[J]. CAD Computer Aided Design. 2005, 37(9): 909-920.
    [60] Tang T D, Bohez E L J, Koomsap P. The sweep plane algorithm for global collisiondetection with workpiece geometry update for five-axis NC machining[J]. CAD Computer Aided Design. 2007, 39(11): 1012-1024.
    [61] Zhang W, Zhang Y F, Ge Q J. Interference-free tool path generation for 5-axis sculptured surface machining using rational Bezier motions of a flat-end cutter[J]. International Journal of Production Research. 2005, 43(19): 4103-4124.
    [62]蔡玉俊,王敏杰,刘志涛,等.面向刀具序列的模具型腔高效加工策略[M]. 2005: 11, 1291-1295.
    [63] Ren Y, Yau H T, Lee Y. Clean-up tool path generation by contraction tool method for machining complex polyhedral models[J]. Computers in Industry. 2004, 54(1): 17-33.
    [64] Lai W, Faddis T, Sorem R. Incremental algorithms for finding the offset distance andminimum passage width in a pocket machining toolpath using the Voronoi technique[J]. Journal of Materials Processing Technology. 2000, 100(1): 30-35.
    [65]王玉,徐和国,高崇辉,等.含雕塑曲面和岛的模具型腔粗加工刀具组合优化方法[J].机械工程学报. 2004, 40(12): 150-154.
    [66]马玉伟.平面型腔数控加工刀具直径确定与刀轨生成技术研究[D].南京航空航天大学, 2008.
    [67]花广如,杨晓红,徐和国.模具CATS系统中半精铣刀具直径决策算法[J].机械设计与制造. 2008(10): 215-216.
    [68] Hinduja S, Roaydi A, Philimis P, et al. Determination of optimum cutter diameter formachining 2.5-D pockets[J]. International Journal of Machine Tools and Manufacture.2001, 41(5): 687-702.
    [69]余东海,王成勇,张凤林.刀具涂层材料研究进展[J].工具技术. 2007, 41(6): 25-32.
    [70]肖寿仁,邓晓春.刀具涂层材料的现状与发展趋势[J].煤矿机械. 2006, 27(9): 4-6.
    [71]艾兴,刘战强,赵军,等.高速切削刀具材料的进展和未来[J].制造技术与机床. 2001(8):21-25.
    [72]顾承珠,张成新.加工一般零件和超硬度金属零件所用刀具材料的分析与研究[J].煤矿机械. 2004(11): 77-79.
    [73]于启勋,朱正芳.刀具材料的历史、进展与展望[J].机械工程学报. 2003, 39(12): 62-66.
    [74]储开宇. 21世纪刀具材料的发展与应用[J].制造技术与机床. 2010(7): 63-67.
    [75]程伟,叶伟昌.现代刀具材料发展新动向[J].现代制造工程. 2003(9): 86-89.
    [76]来沁雄.高速钢刀具性能与材料选用[J].科技情报开发与经济. 2003, 13(5): 129-130.
    [77]杨叔子.机械加工工艺师手册[M].北京:机械工业出版社, 2002.
    [78]袁哲俊,刘华明.刀具设计手册[M].北京:机械工业出版社, 1999.
    [79]李德华,陈志勇.钛合金切销中刀具材料选用及加工工艺介绍[J].机械制造. 2002, 40(1): 17-19.
    [80]于凤云,张经充.钻削高强度钢EH360刀具材料的优选[J].煤矿机械. 2001(2): 37-39.
    [81]周泽智.钛合金材料切削加工刀具的选择[J].机械制造. 2001, 39(8): 17-19.
    [82]董必辉.不锈钢加工用刀具切削参数选择分析[J].机械制造与自动化. 2007, 36(6): 91-93.
    [83]刘长付,汪小文,葛兆斌,等.高速切削刀具材料的特性与选用[J].机械制造. 2001, 39(8): 13-15.
    [84]李友生,邓建新,李甜甜,等.不同刀具材料高速车削钛合金的性能研究[J].武汉理工大学学报. 2009, 31(15): 29-32.
    [85]沈卫平.航空材料加工中刀具材料的选用[J].航空制造技术. 2007(7).
    [86]袁人炜,陈明.高速切削加工中刀具材料的选用[J].机械工程师. 2000(2): 5-6.
    [87]王珺,孙建仁.干式加工刀具设计及刀具材料的选择[J].机械研究与应用. 2004, 17(2): 30-32.
    [88]邹浩波,张宇,戴丽玲.高速切削加工的刀具材料及其合理选择[J].机械研究与应用. 2005, 18(3): 6-8.
    [89]丁杰,赵杰,张振金.高速切削加工刀具材料的性能分析及合理化选择[J].现代制造工程. 2007(6): 81-84.
    [90]赵亮培.高速切削加工中刀具材料的合理选择[J].组合机床与自动化加工技术. 2009(4):67-69.
    [91]申丽国,韩至骏.选择高速钢刀具材料的专家模糊聚类算法[J].机械工程学报. 1995, 31(3): 51-56.
    [92]席洪波,蔡安江.基于模糊综合评判的数控刀具材料优选[J].制造技术与机床. 2008(9):112-114.
    [93]王友利,侯忠滨.基于规则推理的刀具材料智能选择系统[J].工具技术. 2008, 42(2): 27-30.
    [94]林勇,周洪玉,李振加,等.刀具优选的权重决策[J].哈尔滨理工大学学报. 2005, 10(3):28-30.
    [95]刘战强,万熠,艾兴.刀具材料智能选择系统的研究与开发[J].中国机械工程. 2003, 14(21): 1871-1873.
    [96]王新晴,王耀华,刘安心.基于径向基神经网络的刀具材料与形式的多层次多目标优选技术[J].中国机械工程. 2001(S1): 205-207.
    [97]韩式国.模具型腔数控加工刀具优选[D].山东大学, 2004.
    [98] Lee Y, Chang T. Application of computational geometry in optimizing 2.5D and 3D NC surface machining[J]. Computers in Industry. 1995, 26(1): 41-59.
    [99] Bala M, Chang T C. Automatic cutter selection and optimal cutter path generation forprismatic parts[J]. International Journal of Production Research. 1991, 29(11): 2163-2176.
    [100] Veeramani D, Gau Y. Selection of an optimal set of cutting-tool sizes for 2 1/2 D pocket machining[J]. CAD Computer Aided Design. 1997, 29(12): 869-877.
    [101] D'Souza R, Wright P, Sequin C. Automated microplanning for 2.5-D pocket machining[J]. Journal of Manufacturing Systems. 2001, 20(4): 288-296.
    [102] D'Souza R M. Selecting an optimal tool sequence for 2.5D pocket machining while considering tool holder collisions[J]. Journal of Intelligent Manufacturing. 2006, 17(3): 363-372.
    [103] D'Souza R M, Ahmad Z. Applications of genetic algorithms in process-planning: Toolsequence selection for 2.5D pocket machining[C]. Philadelphia, PA, United states: American Society of Mechanical Engineers, 2006.
    [104] Joneja A, Weifeng Y, Lee Y. Greedy tool heuristic approach to rough milling of complex shaped pockets[J]. IIE Transactions (Institute of Industrial Engineers). 2003, 35(10): 953-963.
    [105]张英杰.面向多刀具组合方案选择的加工成本评价模型的研究[J].计算机集成制造系统.2008, 14(8): 1545-1549.
    [106] Yao Z, Gupta S K, Nau D S. A geometric algorithm for selecting optimal set of cutters for multi-part milling[C]. Ann Arbor, MI, United states: Association for ComputingMachinery, 2001.
    [107] Yao Z, Gupta S K, Nau D S. Algorithms for selecting cutters in multi-part milling problems[J]. Computer Aided Design. 2003, 35(9): 825-839.
    [108]花广如,徐和国,周雄辉,等.含岛型腔粗铣加工中刀具和步长优化决策方法[J].哈尔滨工业大学学报. 2006, 38(11): 1870-1873.
    [109]徐和国. 3D型腔加工中计算机辅助刀具选择系统关键技术的研究及应用[D].上海交通大学, 2004.
    [110] D'Souza R M, Sequin C, Wright P K. Automated tool sequence selection for 3-axis machining of free-form pockets[J]. Computer-Aided Design. 2004, 36(7): 595-605.
    [111] Yh C, Ys L, Sc F. Optimal cutter selection and machining plane determination for process planning and NC machining of complex surfaces[J]. Journal of Manufacturing Systems. 1998, 17(5): 371-388.
    [112] Ding X M, Lu Y Q, Fuh J Y H, et al. Optimal cutter selection for complex three-axis NC mould machining[J]. International Journal of Production Research. 2004, 42(22): 4785-4801.
    [113]尹震飚,刘飞,刘霜,等.型腔铣削单纯区及其判别方法[J].机械工程学报. 2010, 46(17): 133-139.
    [114]铣刀[OL]. [2011-03-18]. http://baike.baidu.com/view/22585.htm#sub22585
    [115]范玉鹏,冉瑞江,唐荣锡.雕塑曲面型腔粗加工刀位轨迹生成算法[J].计算机辅助设计与图形学学报. 1998, 10(3): 241-247.
    [116]刘飞.制造系统工程[M].第2版.北京:国防工业出版社, 2002.
    [117] D'Souza R M. On setup level tool sequence selection for 2.5-D pocket machining[J]. Robotics and Computer-Integrated Manufacturing. 2006, 22(3): 256-266.
    [118] Cus F, Zuperl U. Approach to optimization of cutting conditions by using artificial neural networks[J]. Journal of Materials Processing Technology. 2006, 173(3): 281-290.
    [119] Ding X M, Lu Y Q, Liu P L. Optimal cutter selection for complex mould machining[J]. SIMTech technical reports. 2005, 6(1): 84-88.
    [120]聂建林.数控刀具寿命智能化管理系统的研究[D].重庆:重庆大学, 2006.

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