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切削力系数辨识的贝叶斯推断方法

冯伟 蔡思捷 籍永建 刘保国

冯伟,蔡思捷,籍永建, 等. 切削力系数辨识的贝叶斯推断方法[J]. 机械科学与技术,2020,39(6):898-903 doi: 10.13433/j.cnki.1003-8728.20190163
引用本文: 冯伟,蔡思捷,籍永建, 等. 切削力系数辨识的贝叶斯推断方法[J]. 机械科学与技术,2020,39(6):898-903 doi: 10.13433/j.cnki.1003-8728.20190163
Feng Wei, Cai Sijie, Ji Yongjian, Liu Baoguo. Applying Bayesian Inference to Identification of Cutting Coefficients[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(6): 898-903. doi: 10.13433/j.cnki.1003-8728.20190163
Citation: Feng Wei, Cai Sijie, Ji Yongjian, Liu Baoguo. Applying Bayesian Inference to Identification of Cutting Coefficients[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(6): 898-903. doi: 10.13433/j.cnki.1003-8728.20190163

切削力系数辨识的贝叶斯推断方法

doi: 10.13433/j.cnki.1003-8728.20190163
基金项目: NFSC-河南联合基金重点项目(U1604254)、省属高校基本科研业务费专项基金项目(2018QNJH04)及河南工业大学高层次人才科研启动基金项目(2017BS010)资助
详细信息
    作者简介:

    冯伟(1981−),讲师,博士,研究方向为高效精密加工、机械动力学,wfeng@haut.edu.cn

    通讯作者:

    刘保国,教授,博士生导师,bguoliu@haut.edu.cn

  • 中图分类号: TG548

Applying Bayesian Inference to Identification of Cutting Coefficients

  • 摘要: 快速标定斜角切削力系数的方法在切削力建模中得到了广泛应用,但该方法忽略了系数辨识过程中的不确定性因素。针对此问题,提出了一种基于贝叶斯推断的切削力系数辨识方法。推导了镶齿面铣刀铣削力解析模型,给出了快速标定斜角切削力系数的线性回归方法。通过马尔科夫链蒙特卡罗方法从切削力系数的后验分布中生成样本,然后基于贝叶斯推断方法评价切削力系数的变化。在给定的实验条件下,分别用线性回归方法和贝叶斯推断方法进行切削力系数辨识,将计算得到的铣削力与实验铣削力值进行对比,结果表明贝叶斯推断方法具有更高的预测精度。
  • 图  1  刀片切削刃轮廓及切削力

    图  2  铣削力测量实验装置

    图  3  铣削力系数抽样结果

    图  4  铣削力系数先验分布为正态分布时的后验分布

    图  5  铣削力系数分布为均匀分布时的后验分布

    图  6  仿真与实验得到的铣削力对比

  • [1] 赵凯, 刘战强. 铣削力预测方法和影响因素综述[J]. 机械科学与技术, 2015, 34(8): 1190-1200

    Zhao K, Liu Z Q. An overview on milling force prediction methods and influencing factors[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(8): 1190-1200 (in Chinese)
    [2] 朱锟鹏, 李科选, 梅涛, 等. 微铣削力建模研究进展[J]. 机械工程学报, 2016, 52(17): 20-34

    Zhu K P, Li K X, Mei T, et al. Progress of cutting force modelling in micromilling[J]. Journal of Mechanical Engineering, 2016, 52(17): 20-34 (in Chinese)
    [3] Altintas Y. Manufacturing automation: metal cutting mechanics, machine tool vibrations, and CNC design[M]. New York: Cambridge University Press, 2012.
    [4] 刘强, 李忠群.数控铣削加工过程仿真与优化:建模、算法与工程应用[M].北京:航空工业出版社, 2011

    Liu Q, Li Z Q. Simulation and optimization of CNC milling process-Modeling, algorithms and applications[M]. Beijing: Aviation Industry Press, 2011 (in Chinese)
    [5] Park S S, Qin Y M. Robust regenerative chatter stability in machine tools[J]. The International Journal of Advanced Manufacturing Technology, 2007, 33(3-4): 389-402
    [6] Hajdu D, Insperger T, Stepan G. Robust stability analysis of machining operations[J]. The International Journal of Advanced Manufacturing Technology, 2017, 88(1-4): 45-54
    [7] Huang X Z, Zhang Y M, Lv C M. Probabilistic analysis of dynamic stability for milling process[J]. Nonlinear Dynamics, 2016, 86(3): 2105-2114
    [8] 刘宇, 王振宇, 杨慧刚, 等. 微铣削中考虑时变切削力系数的颤振稳定性预测[J]. 振动与冲击, 2018, 37(3): 160-166

    Liu Y, Wang Z Y, Yang H G, et al. Chatter stability prediction for micro-milling processes with time-varying cutting force coefficients[J]. Journal of Vibration and Shock, 2018, 37(3): 160-166 (in Chinese)
    [9] Löser M, Otto A, Ihlenfeldt S, et al. Chatter prediction for uncertain parameters[J]. Advances in Manufacturing, 2018, 6(3): 319-333
    [10] Karandikar J M, Schmitz T L, Abbas A E. Application of bayesian inference to milling force modeling[J]. Journal of Manufacturing Science and Engineering, 2014, 136(2): 021017
    [11] Mehta P, Kuttolamadom M, Mears L. Mechanistic force model for machining process-theory and application of bayesian inference[J]. The International Journal of Advanced Manufacturing Technology, 2017, 91(9-12): 3673-3682
    [12] Gözü E, Karpat Y. Uncertainty analysis of force coefficients during micromilling of titanium alloy[J]. The International Journal of Advanced Manufacturing Technology, 2017, 93(1-4): 839-855
    [13] 杨毅青, 张斌, 刘强. 铣削建模中多种切削力模型的分析比较[J]. 振动工程学报, 2015, 28(1): 82-90

    Yang Y Q, Zhang B, Liu Q. Analysis and comparison of various cutting force models in the milling process simulation[J]. Journal of Vibration Engineering, 2015, 28(1): 82-90 (in Chinese)
    [14] Schmitz T L, Smith K S. Machining dynamics: frequency response to improved productivity[M]. New York: Springer Publishing Co., 2008
    [15] Wang H R, Wang C, Wang Y, et al. Bayesian forecasting and uncertainty quantifying of stream flows using metropolis-Hastings Markov Chain Monte Carlo algorithm[J]. Journal of Hydrology, 2017, 549: 476-483
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出版历程
  • 收稿日期:  2019-04-16
  • 刊出日期:  2020-06-05

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