针对现场环境下的航空制孔垂直度检测问题,提出了一种基于激光测距的快速高精度测量方法。首先,利用膨胀芯轴在被测孔内稳定支撑并模拟孔的轴线,通过安装在芯轴上的激光测距传感器和角度编码器获取孔的端面点云数据,并拟合出端面法向量;最后,计算该法向量与被测孔轴线之间的夹角作为垂直度误差。为了提高装置测量精度,提出了基于RANSAC的三维点云重建算法,并通过向量合成法补偿由膨胀芯轴体现基准时所产生的系统误差。利用不同垂直度标准环规对所述装置进行了标定,并完成了平面样件及曲面样件的制孔垂直度测量实验。实验结果表明:该装置的测量重复性<0.01°,最大示值误差<±0.1°,单个孔的测量时间<1min,能够满足航空制孔垂直度的现场检测精度与速度要求。
Abstract
To solve the problem of verticality detection of aviation drilling holes on site, a fast and high-precision method is proposed based on laser ranging sensor. Firstly, an expansion mandrel is stably supported in the hole to simulate its axis. Then the point cloud data of the holes end face is obtained with the ranging sensor and an angle encoder, which are both installed on the mandrel. And the normal vector of the face is further fitted. Finally, the angle between the vector and the axis is calculated as the verticality. At the same time, a 3D point cloud reconstruction algorithm based on RANSAC is proposed to improve the measurement accuracy. The systematic error, caused by the reference reflected by the expansion mandrel, is compensated after the vectors are synthesized. The measuring device is calibrated by verticality gauges and the experiments of verticality detection are completed for both plane and curved parts. The result shows that the measurement repeatability is less than 0.01° and the maximum indication error is within ±0.1°. It takes less than one minute for each hole. So the requirements of the accuracy and efficiency for on-site detection can be met.
关键词
计量学 /
垂直度 /
航空制孔 /
激光测距 /
膨胀芯轴 /
点云重建 /
测量重复性
Key words
metrology /
verticality /
aviation drilling hole /
laser ranging /
expansion mandrel /
point cloud reconstruction /
measurement repeatability
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参考文献
［1］邢雪亮, 甘文波, 蒋朝根. 基于机器视觉的航空铆钉尺寸检测技术［J］. 计量学报, 2020, 41(5): 518-523.
Xing X L, Gan W B, Jiang C G. Measurement Technology of Aero rivets Based on Machine Vision［J］. Acta Metrologica Sinica, 2020, 41(5): 518-523.
［2］Bi S, Liang J. Robotic drilling system for titanium structures［J］. The international journal of advanced manufacturing technology, 2011, 54(5): 767-774.
［3］袁红璇. 飞机结构件连接孔制造技术［J］. 航空制造技术, 2007(1): 96-99.
Yuan H X. Manufacturing Technology of Connecting Hole for Aircraft Structural Parts［J］. Aeronautical Manufacturing Technology, 2007(1): 96-99.
［4］Shemeta P J. Angularity gage: U. S. 9354032［P］. 2016-05-31.
［5］毕运波, 徐超, 樊新田, 等. 基于视觉测量的沉头孔垂直度检测方法［J］. 浙江大学学报(工学版), 2017, 51(2): 312-318.
Bi Y B, Xu C, Fan X T, et al. Measuring Method of Countersunk Hole Verticality Based on Vision Measurement［J］. Journal of Zhejiang University (Engineering Science), 2017, 51(2): 312-318.
［6］Yu L, Bi Q, Ji Y, et al. Vision Based in-process Inspection for Countersink in Automated Drilling and Riveting［J］. Precision Engineering, 2019, 58: 35-46.
［7］石循磊, 杜坤鹏, 张继文, 等. 基于线激光扫描的飞机表面锪窝孔参数提取方法［J］. 机械工程学报, 2020, 56(8): 148-154.
Shi X L, Du K P, Zhang J W, et al. Parameter Extraction Method for Aircraft Surface Countersink Holes based on Line Laser Scanning［J］. Journal of Mechanical Engineering, 2020, 56(8): 148-154.
［8］徐超. 基于视觉测量的沉头孔垂直度检测新技术研究［D］. 杭州: 浙江大学, 2016.
［9］GB/T 1182-2018产品几何技术规范(GPS)几何公差形状、方向、位置和跳动公差标注［S］.
［10］Johnson M L, Faunt L M. Parameter Estimation by Least-squares Methods［J］. Methods in Enzymology, 1992, 210: 1-37.
［11］何凤涛, 陈雪梅, 熊衍龙, 等. 曲面自动化制孔技术研究现状与发展趋势［J］. 科学技术与工程, 2020, 20(29): 11834-11841.
He F T, Chen X M, Xiong Y L, et al. Research Status and Development Trend of Surface Automatic Hole Making Technology［J］. Science Technology and Engineering, 2020, 20(29): 11834-11841.
［12］孔德明, 黄紫双, 王书涛, 等. 基于分数阶傅里叶变换的NURBS曲面拟合［J］. 计量学报, 2021, 42(3): 294-300.
Kong D M, Huang Z S, Wang S T, et al. NURBS Surface Fitting Based on Fractional Fourier Transform［J］. Acta Metrology Sinica, 2021, 42(3): 294-300.
［13］宋尧. 机器人自动制孔末端执行器研制及制孔质量控制方法研究［D］. 上海: 上海交通大学, 2017.
［14］Fischler M A, Bolles R C. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography［J］. Communications of the ACM, 1981, 24(6): 381-395.
［15］Chum O, Matas J, Kittler J. Locally optimized RANSAC［C］//Joint Pattern Recognition Symposium. Springer, Berlin, Heidelberg, 2003: 236-243.
［16］Raguram R, Chum O, Pollefeys M, et al. USAC: A Universal Framework for Random Sample Consensus［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 35(8): 2022-2038.
［17］谢张宁, 姜志华, 朱惠臣, 等. 基于三维点云螺纹中轴线的拟合方法研究［J］. 计量学报, 2020, 41(8): 918-925.
Xie Z N, Jiang Z H, Zhu H C, et al. Research on Fitting Method of Central Axis of Three-dimensional Point Cloud Thread［J］. Acta Metrologica Sinica, 2020, 41(8): 918-925.
［18］王勇, 梁基超. 基于测量不确定度的测量过程特性分析［J］. 计量学报, 2022, 43(9): 1241-1244.
Wang Y, Liang J C. Analysis of Measurement Process Characteristics Based on Measurement Uncertainty［J］. Acta Metrologica Sinica, 2022, 43(9): 1241-1244.
［19］熊有伦. 机器人技术基础［M］. 武汉: 华中科技大学出版社, 1996: 15-22.
基金
直升机传动技术国家级重点实验室基金(HTL-0-21G10);江苏省大学生创新创业训练计划项目(2021cx005069);南京航空航天大学“实验技术研究与开发”重点项目(2020050500057871)
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