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基于响应曲面法的CFRP超声振动辅助磨削工艺参数优化

纪道航 陈燕 郭南 梁宇红 季珺杰 汪永清

纪道航, 陈燕, 郭南, 梁宇红, 季珺杰, 汪永清. 基于响应曲面法的CFRP超声振动辅助磨削工艺参数优化[J]. 金刚石与磨料磨具工程, 2022, 42(5): 585-594. doi: 10.13394/j.cnki.jgszz.2022.0019
引用本文: 纪道航, 陈燕, 郭南, 梁宇红, 季珺杰, 汪永清. 基于响应曲面法的CFRP超声振动辅助磨削工艺参数优化[J]. 金刚石与磨料磨具工程, 2022, 42(5): 585-594. doi: 10.13394/j.cnki.jgszz.2022.0019
JI Daohang, CHEN Yan, GUO Nan, LIANG Yuhong, JI Junjie, WANG Yongqing. Optimizing process parameters of ultrasonic vibration assisted grinding CFRP based on response surface method[J]. Diamond & Abrasives Engineering, 2022, 42(5): 585-594. doi: 10.13394/j.cnki.jgszz.2022.0019
Citation: JI Daohang, CHEN Yan, GUO Nan, LIANG Yuhong, JI Junjie, WANG Yongqing. Optimizing process parameters of ultrasonic vibration assisted grinding CFRP based on response surface method[J]. Diamond & Abrasives Engineering, 2022, 42(5): 585-594. doi: 10.13394/j.cnki.jgszz.2022.0019

基于响应曲面法的CFRP超声振动辅助磨削工艺参数优化

doi: 10.13394/j.cnki.jgszz.2022.0019
基金项目: 国家科技重大专项(2017-Ⅶ-0015-0111);国家自然科学基金(51375234)。
详细信息
    通讯作者:

    陈燕,女,1969年生,教授、博士生导师。主要研究方向:难加工材料的高效精密加工技术。E-mail:ninaych@nuaa.edu.cn

  • 中图分类号: TG58; TG74

Optimizing process parameters of ultrasonic vibration assisted grinding CFRP based on response surface method

  • 摘要: 针对CFRP加工表面高质量和高效率相矛盾的问题,利用响应曲面法建立三维表面粗糙度Sa和表面损伤层深度Dd的二阶回归模型,并采用遗传算法进行多目标优化,获得小的SaDd和最大的材料去除率VMRR。结果表明:SaDd的回归模型显著、可靠性好,其中进给速度vfSaDd的影响最显著,磨削深度ap、主轴转速n和超声振幅A的影响次之。响应曲面分析结果显示:nAvfap以及vfA之间的交互作用对Sa影响显著;nAvfAvfap以及apA之间的交互作用对Dd影响显著。在SaDdVMRR权重占比分别为1/5、1/5和3/5的条件下,与中心点结果相比,优化后的Sa降低了11.01%,Dd降低了10.08%,VMRR提高了62.02%。且在优化工艺参数下的SaDd的试验值与预测值的相对误差绝对值分别为8.25%和9.41%,表明预测模型准确性较高,可用于CRFP超声振动磨削的工艺参数优化和预测。

     

  • 图  1  钎焊金刚石铣磨刀具

    Figure  1.  Brazed diamond milling tool

    图  2  试验平台

    Figure  2.  Experimental platform

    图  3  采样区域示意图

    Figure  3.  Schematic diagram of sampling area

    图  4  表面层损伤深度Dd示意图

    Figure  4.  Schematic diagram of surface layer damage depth Dd

    图  5  磨削表面三维轮廓形貌(Sa=7.29 μm)

    Figure  5.  Three-dimensional topography of grinding surface(Sa=7.29 μm)

    图  6  SaDd的模型预测值与实际值对比

    Figure  6.  Comparison between model predicted value and actual value of Sa and Dd

    图  7  Sa Dd 模型的标准残差概率分布图

    Figure  7.  Probability distribution of standard residuals of Sa and Dd models

    图  8  交互作用下的Sa响应曲面

    Figure  8.  Sa response surface under interaction

    图  9  交互作用下的Dd响应曲面

    Figure  9.  Dd response surface under interaction

    表  1  试验因素水平

    Table  1.   Experiment factors and levels

    编码水平因素
    主轴转速
    n / (r·min−1)
    进给速度
    vf / (mm·min−1)
    磨削深度
    ap / mm
    超声振幅
    A / μm
    −2 8 000 200.00 0.50 4.00
    −1 12 000 400.00 0.75 5.00
    0 16 000 600.00 1.00 6.00
    1 20 000 800.00 1.25 7.00
    2 24 000 1 000.00 1.50 8.00
    下载: 导出CSV

    表  2  因素设计及测试结果

    Table  2.   Factor design and test results

    序号
    m
    磨削参数响应结果
    nvfapASa / μmσSa / μmDd / μmσDd / μm
    1 0 0 −2 0 4.66 0.25 55.96 11.38
    2 1 −1 −1 −1 3.87 0.20 45.63 8.81
    3 1 −1 1 −1 3.79 0.15 73.36 12.46
    4 0 0 0 −2 6.60 0.29 138.66 22.58
    5 0 0 0 0 5.28 0.26 108.70 8.42
    6 1 1 1 −1 7.06 0.33 156.59 18.68
    7 −1 1 −1 −1 7.29 0.31 161.52 21.05
    8 0 0 2 0 6.95 0.26 145.89 13.02
    9 0 0 0 0 5.58 0.26 117.15 8.42
    10 −1 −1 1 1 4.68 0.18 94.18 15.88
    11 −1 1 −1 1 5.42 0.35 113.89 12.05
    12 −1 1 1 1 7.36 0.29 154.54 19.43
    13 −1 1 1 −1 8.30 0.41 218.65 23.68
    14 −1 −1 −1 −1 4.93 0.19 103.44 9.17
    15 0 0 0 0 5.81 0.26 122.11 8.42
    16 0 0 0 0 5.75 0.26 120.65 8.42
    17 0 −2 0 0 3.90 0.25 88.28 10.28
    18 −1 −1 1 −1 5.85 0.18 122.77 14.93
    19 −1 −1 −1 1 5.39 0.27 113.24 21.26
    20 0 0 0 0 6.19 0.26 129.91 8.42
    21 0 0 0 2 7.16 0.31 150.27 15.91
    22 0 2 0 0 5.98 0.23 205.31 21.82
    23 −2 0 0 0 6.40 0.21 134.49 20.19
    24 0 0 0 0 5.56 0.26 116.85 8.42
    25 1 −1 1 1 6.18 0.34 129.84 23.63
    26 1 1 1 1 7.00 0.33 147.00 15.71
    27 1 1 −1 −1 3.97 0.17 83.42 9.08
    28 2 0 0 0 3.98 0.22 70.96 12.72
    29 0 0 0 0 5.86 0.26 102.11 8.42
    30 1 1 −1 1 5.52 0.18 120.22 14.63
    31 1 −1 −1 1 5.23 0.28 109.73 17.03
    下载: 导出CSV

    表  3  Sa的方差分析

    Table  3.   Variance analysis of Sa

    项目平方和自由度均方值FP备注
    模型 37.89 14 2.71 15.78 < 0.000 1 非常显著
    n 5.46 1 5.46 31.83 < 0.000 1 3
    vf 10.87 1 10.87 63.38 < 0.000 1 1
    ap 7.21 1 7.21 42.07 < 0.000 1 2
    A 0.34 1 0.34 1.96 0.180 6 4
    nvf 0.58 1 0.58 3.38 0.084 6
    nap 0.32 1 0.32 1.90 0.187 6
    nA 4.78 1 4.78 27.85 < 0.000 1
    vfap 2.57 1 2.57 14.99 0.001 4
    vfA 1.19 1 1.19 6.93 0.018 1
    apA 0.10 1 0.10 0.59 0.453 3
    n2 0.45 1 0.45 2.63 0.124 5
    vf2 1.02 1 1.02 5.92 0.027 1
    ap2 0.02 1 0.02 0.13 0.722 7
    A2 2.51 1 2.51 14.64 0.001 5
    残差 2.74 16 0.17
    失拟项 2.26 10 0.23 2.77 0.112 3 不显著
    纯误差 0.49 6 0.08
    总和 40.64 30
    R2=0.932 5
    下载: 导出CSV

    表  4  Dd的方差分析

    Table  4.   Variance analysis of Dd

    项目平方和自由度均方值FP备注
    模型 41 019.85 14 2 929.99 32.58 <0.000 1 非常显著
    n 4 916.29 1 4 916.29 54.67 <0.000 1 3
    vf 14 885.82 1 14 885.82 165.52 <0.000 1 1
    ap 7 550.43 1 7 550.43 83.96 < 0.000 1 2
    A 68.33 1 68.33 0.76 0.396 3 4
    nvf 274.71 1 274.71 3.05 0.099 7
    nap 154.60 1 154.60 1.72 0.208 3
    nA 4 842.00 1 4 842.00 53.84 < 0.0001
    vfap 1 399.13 1 1 399.13 15.56 0.001 2
    vfA 2 169.56 1 2 169.56 24.12 0.000 2
    apA 741.04 1 741.04 8.24 0.011 1
    n2 422.38 1 422.38 4.70 0.045 7
    vf2 1 471.65 1 1 471.65 16.36 0.000 9
    ap2 527.39 1 527.39 5.86 0.027 7
    A2 1 242.08 1 1 242.08 13.81 0.001 9
    残差 1 438.94 16 89.93
    失拟项 942.49 10 94.25 1.14 0.456 3 不显著
    纯误差 496.46 6 82.74
    总和 42 458.79 30
    R2=0.966 1
    下载: 导出CSV

    表  5  不同权重占比下的优化结果

    Table  5.   Optimized results under different weight ratios

    组号权重因素优化结果
    参数结果
    ${W_{{S_{\rm{a}}}}} $${W_{{D_{\rm{d}}}}} $${W_{{V_{{\rm{MRR}}}}}} $n
    (r·min−1)
    vf
    (mm·min−1)
    ap
    mm
    A
    μm
    Sa
    μm
    Dd
    μm
    VMRR
    (mm3·min−1)
    11/31/31/323 693882.360.904.413.3481.212 902.41
    23/51/51/523 864999.980.724.691.9368.592 630.45
    31/53/51/523 602714.270.974.053.5052.182 512.22
    41/51/53/523 999745.941.304.495.09105.013 538.53
    中心点 16 000600.001.006.005.72116.782 184.00
    下载: 导出CSV

    表  6  SaDd试验值与预测值对比

    Table  6.   Comparison of Sa and Dd test values with predicted values

    项目三维表面粗糙度

    Sa /μm
    表面层损伤深度

    Dd /μm
    试验值4.6795.13
    预测值5.09105.01
    相对误差绝对值8.25%9.41%
    下载: 导出CSV
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  • 收稿日期:  2022-03-14
  • 修回日期:  2022-05-13
  • 刊出日期:  2022-10-10

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