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面向航空航天难加工材料磨削过程的模拟与智能控制

赵彪 雷小飞 陈涛 丁文锋 傅玉灿 徐九华 李海

赵彪, 雷小飞, 陈涛, 丁文锋, 傅玉灿, 徐九华, 李海. 面向航空航天难加工材料磨削过程的模拟与智能控制[J]. 金刚石与磨料磨具工程, 2023, 43(2): 127-143. doi: 10.13394/j.cnki.jgszz.2023.1002
引用本文: 赵彪, 雷小飞, 陈涛, 丁文锋, 傅玉灿, 徐九华, 李海. 面向航空航天难加工材料磨削过程的模拟与智能控制[J]. 金刚石与磨料磨具工程, 2023, 43(2): 127-143. doi: 10.13394/j.cnki.jgszz.2023.1002
ZHAO Biao, LEI Xiaofei, CHEN Tao, DING Wenfeng, FU Yucan, XU Jiuhua, LI Hai. Simulation and intelligent control during grinding process for difficult-to-machine materials in aerospace[J]. Diamond & Abrasives Engineering, 2023, 43(2): 127-143. doi: 10.13394/j.cnki.jgszz.2023.1002
Citation: ZHAO Biao, LEI Xiaofei, CHEN Tao, DING Wenfeng, FU Yucan, XU Jiuhua, LI Hai. Simulation and intelligent control during grinding process for difficult-to-machine materials in aerospace[J]. Diamond & Abrasives Engineering, 2023, 43(2): 127-143. doi: 10.13394/j.cnki.jgszz.2023.1002

面向航空航天难加工材料磨削过程的模拟与智能控制

doi: 10.13394/j.cnki.jgszz.2023.1002
基金项目: 航空发动机及燃气轮机基础科学中心项目(P2022-A-IV-002-001); 国家自然科学基金青年项目(52205475); 江苏省自然科学基金青年项目(BK20210295); 江苏省卓越博士后计划(2022ZB215); 直升机传动技术国家重点实验室项目(HTL-A-22G12)。
详细信息
    作者简介:

    赵彪,男,1991年生,博士、讲师。主要研究方向:难加工材料磨削机理与过程优化。E-mail:zhaobiao@nuaa.edu.cn

    通讯作者:

    丁文锋,男,1978年生,博士、教授。主要研究方向:难加工材料高效精密加工技术与应用研究。E-mail:dingwf2000@vip.163.com

  • 中图分类号: TG58; TG74

Simulation and intelligent control during grinding process for difficult-to-machine materials in aerospace

Funds: Science Center for Gas Turbine Project (P2022-A-IV-002-001), National Natural Science Foundation of China (52205475), Natural Science Foundation of Jiangsu Province ( BK20210295), Superior Postdoctoral Project of Jiangsu Province (2022ZB215), National Key Laboratory of Science and Technology on Helicopter Transmission (HTL-A-22G12)
More Information
    Author Bio:

    ZHAO Biao (1991—), Male, Ph.D., Lecturer, Research focus: mechanism and process optimization in grinding of difficult-to-cut materials

    Corresponding author: Email: dingwf2000@vip.163.com) Corresponding author: DING Wen-feng (1978—), Male, Ph.D., Professor, Research focus: high-efficiency precision machining technology and applications on difficult-to-cut materials.
  • 摘要:

    近年来,钛合金、高温合金、金属间化合物、高强度钢等难加工材料凭借优异性能广泛应用于航空航天领域关键构件。磨削作为难加工材料及关键构件精密制造的终加工方法,对制造质量与生产效率具有直接影响。然而,由于材料的难加工特性以及磨削过程的复杂性,导致磨削过程极易出现磨削力大、磨削温度高、砂轮磨损严重以及加工质量差等问题。本文针对航空航天难加工材料,以磨削加工过程模拟与智能控制技术为主线,总结了磨削过程力、温度、砂轮磨损及表面完整性等方面的研究进展和现存问题。最后,本文针对当前研究存在的主要问题,对未来磨削过程模拟与智能控制技术的发展趋势进行了展望。

     

  • 图  1  高强韧难加工材料应用范围

    Figure  1.  Applications of difficult-to-cut materials

    图  2  磨削过程各参量间关系

    Figure  2.  Relationship of each factor during grinding processes

    图  3  砂轮与齿面接触几何建模[18]

    Figure  3.  Geometric modeling of contact between grinding wheel and tooth surface[18]

    图  4  榫头成型磨削温度场预测[27]

    Figure  4.  Temperature field prediction of creep feed grinding blade root[27]

    图  5  考虑磨粒与工件相互作用(包括摩擦、犁耕和切削)的理论三维温度图[6]

    Figure  5.  Theoretical 3D temperature map considering different regimes of grain-workpiece interactions (including rubbing, ploughing and cutting)[6]

    图  6  砂轮轮廓磨损采集[34]

    Figure  6.  Grinding wheel profile wear collection[34]

    图  7  表面完整性范畴[35]

    Figure  7.  Scope of surface integrity[35]

    图  8  二维仿真磨粒轨迹与工件轮廓形貌[36]

    Figure  8.  2D simulation of abrasive trajectory and workpiece profile[36]

    图  9  两种模型在不同磨削方向上的残余应力分布[41]

    Figure  9.  Residual stress distribution of two models in different grinding directions [41]

    图  10  齿轮切削几何模型建模与形貌预测对比图[43]

    Figure  10.  Comparison between gear cutting geometric model modeling and profile prediction[43]

    图  11  机器人磨削系统与控制策略框图[49]

    Figure  11.  Block diagram of robot grinding system and control strategy[49]

    图  12  有限元模型与数字孪生结合过程示意图[52]

    Figure  12.  Schematic diagram of combination process of finite element model and digital twin[52]

    图  13  磨削温度监测流程图[53]

    Figure  13.  Flow chart of grinding temperature monitoring[53]

    图  14  视觉轮廓磨削系统及工件局部轮廓在线误差检测原理图[60]

    Figure  14.  Schematic diagram of visual contour grinding system and local contour image of workpiece online error detection[60]

    图  15  在线监测自适应控制系统模型[61]

    Figure  15.  On-line monitoring adaptive control system model[61]

    图  16  改进烟花算法优化过程结构图[65]

    Figure  16.  Improved fireworks algorithm optimization process structure diagram[65]

    图  17  航天航空难加工材料磨削过程的模拟与智能控制总结与展望

    Figure  17.  Summary and prospect of simulation and intelligent control of grinding process of difficult materials in aerospace

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  • 收稿日期:  2023-02-24
  • 修回日期:  2023-03-05
  • 录用日期:  2023-03-08
  • 刊出日期:  2023-04-20

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