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考虑刀具底刃切削的CFRP铣削力精确建模研究

庆华楠 和延立 张圣光 朱胜伟 王大振

庆华楠, 和延立, 张圣光, 朱胜伟, 王大振. 考虑刀具底刃切削的CFRP铣削力精确建模研究[J]. 机械科学与技术, 2018, 37(4): 560-567. doi: 10.13433/j.cnki.1003-8728.2018.0411
引用本文: 庆华楠, 和延立, 张圣光, 朱胜伟, 王大振. 考虑刀具底刃切削的CFRP铣削力精确建模研究[J]. 机械科学与技术, 2018, 37(4): 560-567. doi: 10.13433/j.cnki.1003-8728.2018.0411
Qing Hua'nan, He Yanli, Zhang Shengguang, Zhu Shengwei, Wang Dazhen. Research on Precise Modeling of CFRP Milling Force Considering Bottom Edge of Tool[J]. Mechanical Science and Technology for Aerospace Engineering, 2018, 37(4): 560-567. doi: 10.13433/j.cnki.1003-8728.2018.0411
Citation: Qing Hua'nan, He Yanli, Zhang Shengguang, Zhu Shengwei, Wang Dazhen. Research on Precise Modeling of CFRP Milling Force Considering Bottom Edge of Tool[J]. Mechanical Science and Technology for Aerospace Engineering, 2018, 37(4): 560-567. doi: 10.13433/j.cnki.1003-8728.2018.0411

考虑刀具底刃切削的CFRP铣削力精确建模研究

doi: 10.13433/j.cnki.1003-8728.2018.0411
基金项目: 

西北工业大学基础研究基金项目(3102015JCS05009)资助

详细信息
    作者简介:

    庆华楠(1992-),硕士,研究方向为碳纤维复合材料加工技术,qhn471721171@126.com

    通讯作者:

    和延立,副教授,博士,heyl@nwpu.edu.cn

Research on Precise Modeling of CFRP Milling Force Considering Bottom Edge of Tool

  • 摘要: 针对碳纤维复合材料(CFRP)铣削提出了一种切削力精确建模方法,即考虑刀具底刃切削作用的铣削力机械模型,通过实验识别底刃和侧刃的切削力并分析了切削力变化规律,建立了切削力系数关于瞬时切削厚度、纤维切削角及切削速度的BP神经网络模型,进一步实现了对铣削力的预测。单向板和多向板的铣削验证实验表明考虑刀具底刃因素可以提高切削力预测的准确性,同时也验证了BP神经网络在CFRP切削力建模中的可行性。
  • [1] Puw H Y, Hocheng H. Milling force prediction for fiber reinforced thermoplastics[J]. American Society of Mechanical Engineers, 1993,45(10):97-108
    [2] Sheikh-Ahmad J Y. Machining of polymer composites[M]. New York:Springer, 2009
    [3] Sheikh-Ahmad J, Twomey J, Kalla D, et al. Multiple regression and committee neural network force prediction models in milling FRP[J]. Machining Science and Technology, 2007,11(3):391-412
    [4] Kalla D, Sheikh-Ahmad J, Twomey J. Prediction of cutting forces in helical end milling fiber reinforced polymers[J]. International Journal of Machine Tools and Manufacture, 2010,50(10):882-891
    [5] Wan M, Zhang W H, Yang Y. Phase width analysis of cutting forces considering bottom edge cutting and cutter runout calibration in flat end milling of titanium alloy[J]. Journal of Materials Processing Technology, 2011,211(11):1852-1863
    [6] Dang J W, Zhang W H, Yang Y, et al. Cutting force modeling for flat end milling including bottom edge cutting effect[J]. International Journal of Machine Tools and Manufacture, 2010,50(11):986-997
    [7] Martellotti M E. An analysis of the milling process[J]. Transactions of the ASME, 1941,63(8):677-700
    [8] Budak E, Altintas Y, Armarego E J A. Prediction of milling force coefficients from orthogonal cutting data[J]. Journal of Manufacturing Science and Engineering, 1996,118(2):216-224
    [9] Altintas Y. Manufacturing automation[M]. Cambridge:Cambridge University Press, 2000
    [10] Karpat Y, Bahtiyar O, Deĝer B. Mechanistic force modeling for milling of unidirectional carbon fiber reinforced polymer laminates[J]. International Journal of Machine Tools and Manufacture, 2012,56:79-93
    [11] Karpat Y, Polat N. Mechanistic force modeling for milling of carbon fiber reinforced polymers with double helix tools[J]. CIRP Annals, 2013,62(1):95-98
    [12] Henerichs M, Voβ R, Kuster F, et al. Machining of carbon fiber reinforced plastics:influence of tool geometry and fiber orientation on the machining forces[J]. CIRP Journal of Manufacturing Science and Technology, 2015,9:136-145
    [13] Wang D H, Ramulu M, Arola D. Orthogonal cutting mechanisms of graphite/epoxy composite. Part I:unidirectional laminate[J]. International Journal of Machine Tools and Manufacture, 1995,35(12):1623-1638
    [14] 王刚,万敏,刘虎,等.粒子群优化模糊系统的铣削力建模方法[J].机械工程学报,2011,47(13):123-130 Wang G, Wan M, Liu H, et al. Modeling of milling force by using fuzzy system optimized by particle swarm algorithm[J]. Journal of Mechanical Engineering, 2011,47(13):123-130(in Chinese)
    [15] 李伟,何鹏举,杨恒,等.基于粗糙集和改进遗传算法优化BP神经网络的算法研究[J].西北工业大学学报,2012,30(4):;01-606 Li W, He P J, Yang H, et al. An effective backpropagation algorithm for optimizing BP neural network based on rough set and modified genetic algorithm[J]. Journal of Northwestern Polytechnical University, 2012,30(4):;01-606(in Chinese)
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出版历程
  • 收稿日期:  2017-01-10
  • 刊出日期:  2018-04-05

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