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整体叶盘机器人砂带磨削轨迹优化及其实验

李飞 陈树林 崔庞博 吴昕 肖贵坚

李飞, 陈树林, 崔庞博, 吴昕, 肖贵坚. 整体叶盘机器人砂带磨削轨迹优化及其实验[J]. 金刚石与磨料磨具工程, 2022, 42(1): 23-29. doi: 10.13394/j.cnki.jgszz.2021.0101
引用本文: 李飞, 陈树林, 崔庞博, 吴昕, 肖贵坚. 整体叶盘机器人砂带磨削轨迹优化及其实验[J]. 金刚石与磨料磨具工程, 2022, 42(1): 23-29. doi: 10.13394/j.cnki.jgszz.2021.0101
LI Fei, CHEN Shulin, CUI Pangbo, WU Xin, XIAO Guijian. Trajectory optimization and experiment of robotic belt grinding blisk[J]. Diamond &Abrasives Engineering, 2022, 42(1): 23-29. doi: 10.13394/j.cnki.jgszz.2021.0101
Citation: LI Fei, CHEN Shulin, CUI Pangbo, WU Xin, XIAO Guijian. Trajectory optimization and experiment of robotic belt grinding blisk[J]. Diamond &Abrasives Engineering, 2022, 42(1): 23-29. doi: 10.13394/j.cnki.jgszz.2021.0101

整体叶盘机器人砂带磨削轨迹优化及其实验

doi: 10.13394/j.cnki.jgszz.2021.0101
详细信息
  • 中图分类号: TG58; TG74

Trajectory optimization and experiment of robotic belt grinding blisk

  • 摘要: 整体叶盘具有结构复杂、材料难加工的特点,其加工精度和表面质量对航空发动机整体性能有至关重要的影响。当前,机器人砂带磨削技术已应用于整体叶盘类复杂曲面的磨削加工。然而,在磨削轨迹规划时多采用目标点均布的方式,这就要求目标点必须足够多,从而导致加工效率过低。基于改进的等弦高误差法对整体叶盘机器人砂带磨削的磨削轨迹进行优化分析,并开展相关仿真与实验验证。结果表明:改进的等弦高误差法可根据曲率变化优化磨削轨迹,减少目标加工点数量,从而提高加工效率。经实验验证,与轨迹优化前相比,优化后整体叶盘的加工效率提高了42.9%;优化后的表面粗糙度Ra可达0.26 μm,且叶片一致性较好,尤其是在曲率变化较大的位置。

     

  • 图  1  整体叶盘叶片型面砂带磨削轨迹离散示意图

    Figure  1.  Diagram of trajectory discrete for belt grinding of blisk blade

    图  2  变曲率等弦高误差计算示意图

    Figure  2.  Calculation schematic diagram of constant chord height error with variable curvature

    图  3  整体叶盘叶片机器人砂带磨削仿真流程图

    Figure  3.  Flow chart of simulating blisk grinding with robotic belt

    图  4  机器人砂带磨削仿真平台

    Figure  4.  Simulation platform of robotic belt grinding

    图  5  轨迹路径中目标点生成

    Figure  5.  Target point generation in trajectory path

    图  6  自动规划的加工轨迹

    Figure  6.  Machining trajectory of automatic planning

    图  7  轨迹规划仿真演示

    Figure  7.  Demonstration of trajectory planning simulation

    图  8  整体叶盘零件部分结构

    Figure  8.  Partial structure of blade

    图  9  机器人砂带磨削实验平台

    Figure  9.  Experiment platform of robotic belt grinding

    图  10  整体叶盘轨迹优化前后对比图

    Figure  10.  Comparison diagram before and after trajectory optimization of blisk

    图  11  轨迹优化前后表面形貌对比图

    Figure  11.  Comparison of surface morphology before and after trajectory optimization

    图  12  整体叶盘叶片粗糙度测量点分布图

    Figure  12.  Distribution map of roughness measurement points on blisk blade

    图  13  整体叶盘叶片轨迹优化前后表面粗糙度对比

    Figure  13.  Comparison of surface roughness before and after trajectory optimization for blisk blade

    表  1  机器人砂带磨削加工工艺参数设置

    Table  1.   Parameter setting of robotic belt grinding process

    砂带类型砂带粒度代号线速度vw / (m·s−1)进给速度vt / (mm·s−1)
    金刚石P2001020
    下载: 导出CSV
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  • 被引次数: 0
出版历程
  • 录用日期:  2021-11-22
  • 收稿日期:  2021-11-12
  • 修回日期:  2021-11-22
  • 网络出版日期:  2022-03-17

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