目的 为实现叶片抛磨的高效率和高表面质量一致性,提出了一种叶片双面对称抛磨路径规划方法。方法 首先,该方法以叶片中弧线设计参数为基础,建立基于中弧线法线的叶片对称抛磨轨迹,实现双侧抛磨轮接触叶片时一一对应。其次,为实现抛磨过程中百叶轮与叶片表面法向接触,基于中弧线的法向量构建机器人的姿态约束方程,优化机器人末端运动轨迹。最后,以叶片双侧抛磨路径的距离为基础建立机器人第七轴控制模型,在四点TCP标定法的基础上改进适用于内部坐标系的标定,解决叶片装夹偏差问题,最终实现叶片双面对称抛磨。结果 仿真及实验结果表明,所提出的叶片双面对称抛磨轨迹规划方法,使两叶片表面平均粗糙度值分别由0.5、0.8 μm降低到0.29、0.36 μm。在叶片形状轮廓误差方面,两叶片由最大轮廓度误差1.301 mm和0.384 mm降低到平均截面轮廓误差分别为0.449 mm和0.137 mm。并且采用双面同时抛磨的方式,使抛磨时间缩短50%。结论 考虑到叶片的叶盆和叶背曲面存在曲率变化一致的趋势,将中弧线作为叶片抛磨路径规划、机器人末端姿态约束的基础,经理论分析和实验验证,该叶片抛磨路径规划方法具有可行性,且有效提高了叶片表面加工质量一致性和抛磨效率。可为机器人双面抛磨叶片的高表面加工质量、高轮廓度一致性和抛磨效率提供理论依据。
Abstract
It is an improved blade surface polishing path planning method, which realizes the high efficiency and high surface quality consistency of blade polishing. The unstable polishing caused by the one-sided force on the blade during single-sided polishing is an obstacle to the good surface shape and integrity of the blade after polishing. The work aims to investigate the symmetric polishing path planning of the blade.
In order to realize the one-to-one correspondence when the double-sided polishing wheel contacts the blade, the cross-section lines of the concave and convex surfaces of the blade are extracted as the basis of the polishing path planning, and the mean line of the cross-section line is solved after discrete sampling of the cross-section line. The symmetric polishing trajectory of the blade is established based on the normal of the mean line, and the one-to-one corresponding double-sided polishing path is obtained by extending the normal of each discrete point to the concave and the convex surfaces from the starting end of the mean line. In order to achieve consistent contact between the impeller and the blade surface during the polishing process, the attitude constraint equations of the robot are constructed based on the normal vectors of the mean line to optimize the robot's end motion trajectory. Finally, the seventh axis control model of the robot is established on the basis of the distance of the polishing path on both sides of the blade, combined with the structural characteristics of the double-sided polishing platform. On the basis of the standard four-point TCP calibration method, the calibration applicable to the internal coordinate system is improved to solve the blade clamping deviation and finally realize the double-sided symmetric polishing of the blade.
Two aero-engine blades are selected to analyze the minimum radius of curvature of the concave and convex surfaces, and to determine the parameters of blade polishing, such as the size of the polishing wheel, the abrasive size, and the rotational speed. The double-sided symmetric polishing trajectory planning and actual polishing experiments are carried out. Compared with the double-sided polishing path based on the planning of the normal direction of the blade cross-section curve, the method proposed has a smaller normal contact error, which can better ensure the integrity of the shape of the blades during the polishing. The experimental results show that the average roughness of the two blade surfaces is reduced from the initial 0.5 μm and 0.8 μm to 0.29 μm and 0.36 μm, respectively. In terms of blade shape contour error, these two blades were reduced from the maximum contour error of 1.301 mm and 0.384 mm to an average cross-section contour error of 0.449 mm and 0.137 mm, respectively. Compared with that before polishing, the mean and variance of the surface roughness after polishing are greatly reduced. In addition, the use of simultaneous polishing on both sides reduces the polishing time by 50%.
The method proposed takes the mean line as the basis of blade polishing path planning and robot end attitude constraints, and the theoretical analysis and experimental verification show that the blade polishing path planning method is feasible and effectively improves the consistency of blade surface processing quality and polishing efficiency. It can provide theoretical basis for the high surface quality, high contour consistency and polishing efficiency of the robot double-sided blade polishing.
关键词
叶片 /
机器人 /
百页轮 /
对称抛磨 /
轨迹规划
Key words
blade /
robot /
flap wheel /
symmetric polishing /
trajectory planning
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参考文献
[1] AMOO L M.On the Design and Structural Analysis of Jet Engine Fan Blade Structures[J]. Progress in Aerospace Sciences, 2013, 60: 1-11.
[2] 朱大虎, 徐小虎, 蒋诚, 等. 复杂叶片机器人磨抛加工工艺技术研究进展[J]. 航空学报, 2021, 42(10): 524265.
ZHU D H, XU X H, JIANG C, et al.Research Progress in Robotic Grinding Technology for Complex Blades[J]. Acta Aeronautica et Astronautica Sinica, 2021, 42(10): 524265.
[3] JANG J, CHO K, YANG G H.Design and Experimental Study of Dragonfly-Inspired Flexible Blade to Improve Safety of Drones[J]. IEEE Robotics and Automation Letters, 2019, 4(4): 4200-4207.
[4] TSAI M J, CHANG J L, HAUNG J F.Development of an Automatic Mold Polishing System[J]. IEEE Transactions on Automation Science and Engineering, 2005, 2(4): 393-397.
[5] KE X L, YU Y H, LI K S, et al.Review on Robot- Assisted Polishing: Status and Future Trends[J]. Robotics and Computer-Integrated Manufacturing, 2023, 80: 102482.
[6] SONG J Z, CHEN Q L, LI Z D.A Peg-in-Hole Robot Assembly System Based on Gauss Mixture Model[J]. Robotics and Computer-Integrated Manufacturing, 2021, 67: 101996.
[7] HUO W G, XU J H, FU Y C.Grinding Force and Surface Integrity on Dry Belt Grinding of TA15 Titanium Alloys[J]. Key Engineering Materials, 2009, 416: 269-273.
[8] 黄云, 肖贵坚, 邹莱. 航空发动机叶片机器人精密砂带磨削研究现状及发展趋势[J]. 航空学报, 2019, 40(3): 022508.
HUANG Y, XIAO G J, ZOU L.Current Situation and Development Trend of Robot Precise Belt Grinding for Aero-Engine Blade[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(3): 022508.
[9] 徐小虎. 压气机叶片机器人砂带磨抛加工关键技术研究[D]. 武汉: 华中科技大学, 2019.
XU X H.Research on Key Technology of Robot Abrasive Belt Grinding and Polishing of Compressor Blades[D]. Wuhan: Huazhong University of Science and Technology, 2019.
[10] 李勋, 于建华, 赵鹏. 航空发动机叶片加工变形控制技术研究现状[J]. 航空制造技术, 2016, 59(21): 41-49.
LI X, YU J H, ZHAO P.Research Status of Machining Deformation Control Method and Technology of Aeroengine Blade[J]. Aeronautical Manufacturing Technology, 2016, 59(21): 41-49.
[11] 崔海军, 张明岐. 航空发动机叶片抛光技术现状及发展趋势[J]. 航空制造技术, 2015, 58(11): 128-131.
CUI H J, ZHANG M Q.Current Situation and Development Trend of Aircraft Engine Blade Polishing Technology[J]. Aeronautical Manufacturing Technology, 2015, 58(11): 128-131.
[12] 李大奇, 张雷, 叶卫东, 等. 叶片双面砂带磨削机床及磨削实验研究[J]. 组合机床与自动化加工技术, 2014(12): 148-149.
LI D Q, ZHANG L, YE W D, et al.Research on Double-Side Machine Tool and Grinding Experiment for Blade Finishing[J]. Modular Machine Tool & Automatic Manufacturing Technique, 2014(12): 148-149.
[13] 张海洋, 杨文玉, 张家军, 等. 叶片机器人砂带磨抛的轨迹规划研究[J]. 机电工程, 2014, 31(5): 578-581.
ZHANG H Y, YANG W Y, ZHANG J J, et al.Trajectory Planning for Roboticbelt Grinding of Turbine Blade[J]. Journal of Mechanical & Electrical Engineering, 2014, 31(5): 578-581.
[14] WEI W, CHAO Y.A Path Planning Method for Robotic Belt Surface Grinding[J]. Chinese Journal of Aeronautics, 2011, 24(4): 520-526.
[15] XIAO G J, CHEN S L, SONG K K, et al.A Novel Trajectory Planning Method Based on Reverse Compensation of Profile Error for Robotic Belt Grinding of Blisk[J]. Journal of Manufacturing Processes, 2022, 84: 508-521.
[16] 郭一鸣, 梁永收, 李飞闯, 等. 近净成形叶片重构曲面刀具轨迹自适应规划[J]. 航空制造技术, 2023, 66(17): 110-119.
GUO Y M, LIANG Y S, LI F C, et al.Adaptive Planning Method for Tool Path in Reconstructing Surfaces of Near-Net Shape Blade[J]. Aeronautical Manufacturing Technology, 2023, 66(17): 110-119.
[17] 赵耀耀, 陈松, 李昌龙, 等. 基于多轴刀路轨迹的自由曲面磁粒研磨试验[J]. 表面技术, 2023, 52(4): 319-328.
ZHAO Y Y, CHEN S, LI C L, et al.Test on Magnetic Abrasive Finishing of Free-form Surface Based on Multi-axis Tool Path Trajectory[J]. Surface Technology, 2023, 52(4): 319-328.
[18] 罗来臻, 赵欢, 王辉, 等. 复杂曲面机器人磨抛位姿优化与刀路规划[J]. 机械工程学报, 2022, 58(3): 284-294.
LUO L Z, ZHAO H, WANG H, et al.Pose Optimization and Tool Path Planning for Robotic Grinding of Complicated Curved Surface[J]. Journal of Mechanical Engineering, 2022, 58(3): 284-294.
[19] ROSOSHANSKY M, XI F (. Coverage Based Tool-Path Planning for Automated Polishing Using Contact Mechanics Theory[J]. Journal of Manufacturing Systems, 2011, 30(3): 144-153.
[20] LV Y J, PENG Z, QU C, et al.An Adaptive Trajectory Planning Algorithm for Robotic Belt Grinding of Blade Leading and Trailing Edges Based on Material Removal Profile Model[J]. Robotics and Computer-Integrated Manufacturing, 2020, 66: 101987.
[21] PIEGL L, TILLER W.The NURBS Book[M]. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997
[22] PAGANI L, SCOTT P J.Curvature Based Sampling of Curves and Surfaces[J]. Computer Aided Geometric Design, 2018, 59: 32-48.
[23] CRAIG J J.Introduction to Robotics: Mechanics and Control[M]. Pearson Education, Inc, 1986.
[24] 丁士杰, 李成刚, 李志鹏, 等. 基于三轴移动平台的机器人标定算法研究[J]. 机械与电子, 2024, 42(5): 57-63.
DING S J, LI C G, LI Z P, et al.Research on the Calibration Algorithms for Robot Based on a Three axis Moving Platform[J]. Machinery & Electronics, 2024, 42(5): 57-63.
[25] 崔荣钺. 六自由度工业机器人运动学标定方法研究[D]. 济南: 济南大学, 2024.
CUI R Y.Research on Kinematic Calibration Methods for 6-DOF Industrial Robots[D]. Jinan: University of Jinan, 2024.
基金
国家自然科学基金（52105474,52375460）; 山西省回国留学人员科研资助项目（2023-58）
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