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支承机匣磨抛参数建模与稳健优化研究

曾爱 黄飞 王玉泉 杨滨涛 张玉

曾爱, 黄飞, 王玉泉, 等. 支承机匣磨抛参数建模与稳健优化研究[J]. 航空动力学报, 2024, 39(6):20220678 doi: 10.13224/j.cnki.jasp.20220678
引用本文: 曾爱, 黄飞, 王玉泉, 等. 支承机匣磨抛参数建模与稳健优化研究[J]. 航空动力学报, 2024, 39(6):20220678 doi: 10.13224/j.cnki.jasp.20220678
ZENG Ai, HUANG Fei, WANG Yuquan, et al. Modeling and robust optimization of grinding and polishing parameters of support casing[J]. Journal of Aerospace Power, 2024, 39(6):20220678 doi: 10.13224/j.cnki.jasp.20220678
Citation: ZENG Ai, HUANG Fei, WANG Yuquan, et al. Modeling and robust optimization of grinding and polishing parameters of support casing[J]. Journal of Aerospace Power, 2024, 39(6):20220678 doi: 10.13224/j.cnki.jasp.20220678

支承机匣磨抛参数建模与稳健优化研究

doi: 10.13224/j.cnki.jasp.20220678
基金项目: 国家自然科学基金(11802140); 中国航发集团重点研发与推广(科技攻关)(ZZCX-2020-024)
详细信息
    作者简介:

    曾爱(1995-),男,工程师,硕士生,主要从事航空发动机机匣结构力学和机加技术方面研究。E-mail:2567457751@qq.com

  • 中图分类号: V26

Modeling and robust optimization of grinding and polishing parameters of support casing

  • 摘要:

    针对支承机匣内孔磨抛表面质量难以保证及磨抛效率低问题,开展了磨抛工艺参数对表面质量影响研究。基于Preston理论建立了螺旋式磨抛材料去除量方程,理论上揭示了螺旋式磨抛工艺参数对表面质量的影响规律。通过正交实验进行方差灵敏度分析,探寻出打磨轮目粒度、打磨轮进给速度、打磨轮转速和抛光时间等影响因子对材料去除率和表面粗糙度影响规律及贡献率,在此基础上以材料去除率和表面粗糙度为优化研究目标,构建了基于Kriging响应面近似模型的稳健优化设计数学模型,采用粒子群算法进行计算求解,计算出2611组优化解。结合实际工程要求,最佳的工艺参数为目粒度1400目、进给速度3 mm/s、转速3600 r/min、抛光时间9 min,为磨抛工程领域的工艺质量改善提供技术支撑。

     

  • 图 1  30Cr2Ni2WVA不锈钢热工艺过程

    Figure 1.  30Cr2Ni2WVA stainless steel thermal process

    图 2  零件与打磨轮接触视图

    Figure 2.  View of the part in contact with the grinding wheel

    图 3  螺旋式磨抛视图

    Figure 3.  Spiral grinding and polishing view

    图 4  零件加工过程

    Figure 4.  Part machining process

    图 5  参数相关矩阵图

    Figure 5.  Correlation matrix diagram of various parameters

    图 6  各设计变量贡献率

    Figure 6.  Contribution rate of each design variable

    图 7  主因子与输出响应拟合响应面

    Figure 7.  Principal factors fitting response surfaces to output responses

    图 8  参数在样本空间概率密度

    Figure 8.  Probability density of parameters in sample space

    图 9  参数空间分布

    Figure 9.  Spatial distribution of parameters

    图 10  帕累托优化解

    Figure 10.  Pareto optimal solution

    表  1  设计空间

    Table  1.   Design space

    设计变量 X1/目 X2/(mm/s) X3/(r/min) X4/min
    下限 400 2 1000 5
    上限 2 000 3.5 4000 20
    下载: 导出CSV

    表  2  工艺参数水平表

    Table  2.   Process parameters level table

    水平 $ {X}_{1} $/目 $ {X}_{2} $/(mm/s) $ {X}_{3} $/(r/min) $ {X}_{4} $/min
    1 400 2 1000 5
    2 800 2.5 2 000 10
    3 1200 3 3000 15
    4 2 000 3.5 4000 20
    下载: 导出CSV

    表  3  实验结果

    Table  3.   Test results

    序号 X1/目 X2/(mm/s) X3/(r/min) X4/min Y1/
    (μm/min)
    Y2/
    μm
    1 1 1 1 1 0.191 0.150
    2 1 2 2 2 1.794 0.130
    3 1 3 3 3 2.010 0.104
    4 1 4 4 4 2.850 0.108
    5 2 1 2 3 0.288 0.080
    6 2 2 1 4 0.569 0.091
    7 2 3 4 1 3.476 0.088
    8 2 4 3 2 4.239 0.103
    9 3 1 3 4 0.080 0.025
    10 3 2 4 3 0.490 0.027
    11 3 3 1 2 0.531 0.021
    12 3 4 2 1 0.782 0.026
    13 4 1 4 2 0.119 0.019
    14 4 2 3 1 0.252 0.022
    15 4 3 2 4 0.410 0.020
    16 4 4 1 3 0.425 0.018
    下载: 导出CSV
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  • 收稿日期:  2022-09-12
  • 网络出版日期:  2023-11-29

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