数控技术课程中超硬材料切削加工所涉及的关键问题的引入
Introduction of Key Problems in Super Hard Material Cutting in NC Technology Course
DOI: 10.12677/AE.2019.93063, PDF,   
作者: 董新峰*, 仇中柱, 韩清鹏:上海电力大学,能源与机械工程学院,上海
关键词: 数控加工超硬材料以切代磨NC Machining Superhard Material Cutting Instead of Grinding
摘要: 数控技术是机械专业的专业课程,其也是智能制造中的核心关键技术。数控技术课程主要在数控机床编程、数控运动控制原理、数控装置与检测装置、伺服控制系统等方面开展教学,实际加工过程中工件与刀具之间的相互作用对数控加工的要求涉及较少。文中首先以超硬材料的数控加工为例,对超硬材料的常用加工方法即切削加工及磨削进行了详细说明与比较,其次鉴于切削加工的高效加工特征,对以切代磨工艺的有点进行了说明,最后对以切代磨涉及的关键技术问题,即机床的加工刚度、机床加工精度、加工效率及绿色加工涉及的关键核心内容进行了讨论。通过本文超硬材料加工内容的引入,培养学生全方位动态思考问题的能力。
Abstract: NC technology is a professional course of mechanical specialty, and it is also the core key technology in intelligent manufacturing. The course of NC technology mainly focuses on NC machine tool programming, NC motion control principle, NC device and detection device, servo control system and so on. However, the interaction between workpiece and tool is seldom involved in the course of NC machining. Firstly, the NC machining of superhard materials is taken as an example, and the common processing methods of superhard materials, namely cutting and grinding, are described and compared in detail. Secondly, in view of the high efficiency of cutting, the advantages of cutting in-stead of grinding are explained. At last, the key issues related to cutting instead of grinding, such as machine tool stiffness, machine tool accuracy, machining efficiency and the key core content of green processing, are discussed in detail. By introducing the content of superhard material processing in this paper, students’ ability to think all-round and dynamically may be stimulated.
文章引用:董新峰, 仇中柱, 韩清鹏. 数控技术课程中超硬材料切削加工所涉及的关键问题的引入[J]. 教育进展, 2019, 9(3): 365-374. https://doi.org/10.12677/AE.2019.93063

参考文献

[1] 吕智, 谢志刚, 林峰, 等. 超硬材料在精密加工中的应用现状与展望[J]. 超硬材料工程, 2018(6): 43-46.
[2] 魏超, 马玉平, 韩源, 张遥, 陈雪辉. 飞秒激光加工超硬材料研究进展[J]. 激光与光电子学进展, 2019, 56(19): 190003.
[3] 应正健. 超硬材料车削过程的数值仿真研究[D]: [硕士学位论文]. 成都: 西华大学, 2012.
[4] 宋庭科, 李嫚, 张弘弢. PcBN刀具车削镍基高温合金切削性能研究[J]. 金刚石与磨料磨具工程, 2011, 31(1): 70-73.
[5] 董新峰,张建平, 等. 智能制造背景下我校机械工程课程体系建设探索[J]. 教育进展, 2018, 8(3): 273-282.
[6] 董新峰, 张为民, 李冰. 最大熵与交叉熵在平面磨削颤振预测中的研究[J]. 振动工程学报, 2013, 26(5): 786-791.
[7] 董新峰, 张为民, 姜源. 基于EMD复杂度与鉴别信息的磨削颤振预测[J]. 振动. 测试与诊断, 2012(4): 602-607.
[8] 卢秉恒, 主编. 机械制造技术基础[M]. 第四版. 西安: 西安交通大学.