机器人抛光系统中的刀具轨迹生成，力反馈控制及过程优化

发布时间：2020-12-29 17:14

　　产品表面的光滑光亮,不仅使产品更具有吸引力,而且还能改善其导电性能、耐腐蚀性能,抗生物污染性能等。然而,产品表面抛光需要人工操作,劳动强度大、费力、费时、费用昂贵、且容易出错。此外,由于经常接触有害的抛光粉尘和高分贝噪音,抛光工人的健康也受到威胁。工业机器人具有可编程、重复性好、精度高等优点,可以用于产品表面抛光。然而,对于复杂的自由曲面,机器人抛光还面临许多问题,现已成为工业应用的瓶颈。本论文针对复杂曲面的机器人抛光提出了一套新的方法。该方法的核心是具有力反馈控制的刀具路径规划以及基于实验设计（Design of Experiment,DOE）的抛光工艺参数优化。刀具路径规划旨在确保覆盖面积,而力反馈可以确保表面质量。在刀具路径规划中考虑了机器人运动的奇异性、关节运动极限和生产率,从而使机器人能在保证轨迹平稳的前提下快速移动。此外,作者还设计了一个的机器人末端执行器以实现力反馈控制。这一方法在眼镜架抛光的实验中得到了验证。实验结果证明这一方法能很好地控制抛光力,超过了产品的表面质量要求和抛光生产率要求。抛光工艺参数优化的目的是达到最大的抛光生产率。首先采用Taguchi方法分析了不同... 

【文章来源】：中国科学院大学(中国科学院深圳先进技术研究院)广东省

【文章页数】：105 页

【学位级别】：博士

【文章目录】：
Dedication
摘要
Abstract
Chapter1:Introduction to Robot Polishing
    1.1.Surface polishing in industry and challenges
    1.2.Robot polishing,advantages and concerns
    1.3.Organization of thesis
Chapter2:Literature Review
    2.1.Robot polishing system
        2.1.1.Passive compliance control
        2.1.2.Active compliance control
    2.2.High-quality surface achievement
        2.2.1.End effector design and implementation
        2.2.2.Surface roughness prediction model
        2.2.3.Path generation
        2.2.4.Detection of surface quality
    2.3.Prediction Methods for the Material Removal During Polishing
        2.3.1.Prediction Methods for the Material Removal Based on Models
        2.3.2.Prediction Methods for the Material Removal Based on Experimental Data
Chapter3:Surface Quality Measurement
    3.1.Glossiness
        3.1.1.Factors which affects glossiness
            3.1.1.1.Effect of refractive index on glossiness
            3.1.1.2.Effect of angle of incident on glossiness
            3.1.1.3.Effect of surface topography on glossiness
    3.2.Surface roughness
        3.2.1.Arithmetic average roughness height
        3.2.2.Root mean square roughness
        3.2.3.Skewness and Kurtosis
    3.3.Surface roughness measuring instruments
Chapter4:Path Planning under Force Control in Robotic Polishing of the Complex Curved Surfaces
    4.1.The Proposed Method
        4.1.1.Workstation Building
            4.1.1.1.Polishing Tool Selection
            4.1.1.2.End Effector Selection
        4.1.2.Force Control Strategy
            4.1.2.1.Tangential Force Component Control
            4.1.2.2.Normal Force Component Control
        4.1.3.Tool Path Planning Strategy
            4.1.3.1.Surface Division
            4.1.3.2.Tool Path Generation for Individual Part Surfaces
            4.1.3.3.Tool Path Stitching （Connection of all part surfaces in single path）
            4.1.3.4.Singularity
    4.2.Results and discussions
        4.2.1.Surface Roughness
        4.2.2.Glossiness
    4.3.Summary
Chapter5:Optimization of the Polishing Efficiency and Torque by Using Taguchi Method and ANOVA in Robotic Polishing
    5.1.Experimental procedure
        5.1.1.Workpiece and Polishing Tool
        5.1.2.Experimental Setup
        5.1.3.Taguchi Method and Polishing Parameters
        5.1.4.Analysis of Variance（ANOVA）
        5.1.5.Regression
    5.2.Results and discussion
        5.2.1.Analysis of the Means and S/N Ratios of the Results
        5.2.2.Analysis of ANOVA
        5.2.3.Regression Analysis of Polishing Efficiency and Torque
        5.2.4.Confirmatory Test at optimal input parameters
    5.3.Summary
Chapter6:Conclusions and Future Work
Biblography
About the Author
Publications during Doctoral Degree


【参考文献】：
期刊论文
[1]基于Preston方程的不锈钢曲面抛磨工艺参数分析[J]. 吴昌林,王韦,李强,王备.  机械制造与自动化. 2012(04)
[2]Structure and Control of an Inverter Type Power Source for Robot Arc Welding[J]. 都东,韩赞东,肖平,张前,张人豪.  Tsinghua Science and Technology. 1998(02)



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