采用虚拟立体视觉的航空发动机叶片点云测量方法

吴军; 马凯; 徐海涛; 王志军; 于之靖

doi:10.13433/j.cnki.1003-8728.20180123

采用虚拟立体视觉的航空发动机叶片点云测量方法

doi: 10.13433/j.cnki.1003-8728.20180123

1.
中国民航大学航空工程学院, 天津 300300;
2.
天津大学精密测试技术及仪器国家重点实验室, 天津 300072

基金项目:

国家自然科学基金与民航联合基金项目（U1533111）、精密测试及仪器国家重点实验室开放基金项目（pilab1707）及中央高校基本科研业务费项目（3122017033）资助

详细信息

作者简介:
吴军(1986-),讲师,硕士生导师,博士,研究方向为激光检测技术,j_wu@cauc.edu.cn

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- 文章访问数: 230
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- 被引次数: 0
出版历程
- 收稿日期: 2017-11-16
- 刊出日期: 2018-11-05

Points Cloud Measurement Method of Blade Surface for Aeroengine with Virtual Stereovision

1.
College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China;
2.
State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China

摘要

摘要: 叶片作为航空发动机的重要零部件，加工成本极为昂贵，为了实现对残损叶片的修复，必须精确获取叶片曲面点云数据，为修复提供数据支持。为此，研究了一种采用虚拟立体视觉的测量方法，首先分析虚拟立体视觉系统的数学模型，利用非参模型及精密靶标实现对系统内外参数的标定，然后采用KLT（Kanade-Lucas-Tomasi）算法结合外极线约束实现了叶片散斑点之间的立体匹配，最后采用点到投影射线距离平方和最小化作为约束条件求解叶片点云空间坐标，得到叶片曲面点云数据。实验结果表明，根据本文方法获取的叶片曲面点云数据拟合出的叶片曲面相关系数大于0.99，叶片曲面几何参数均值误差小于0.2 mm。本方法针对发动机叶片点云测量这一特殊应用环境，提出了一种简化的测量方法，实现了叶片点云的高精度、高可靠性测量。
- 虚拟立体视觉 /
- 叶片曲面 /
- 立体匹配 /
- 点云空间坐标
Abstract: Blade are important component in aeroengine with high cost. Therefore, in order to repair the damaged blades, the points cloud must be accurately obtained. This paper will propose a novel measurement method with the virtual stereo vision. Firstly, the principle and advantages of the virtual stereo vision are analyzed, and the internal and external parameters are calibrated by using the nonparametric model and precision calibration target. Then, the KLT (Kanade-Lucas-Tomasi)algorithm and epipolar constraints are used to realize the stereo matching between the speckle points. Finally, the method to minimize the sum of squared distance between the point and the projective ray is utilized as the constraint condition to calculate the spatial coordinates of blade point cloud. The experimental results show that the correlation coefficient of the fitting blade surface is larger than 0.99, and the mean error of blade surface geometry value is less than 0.2 mm. Therefore, the high accuracy and reliability for the points cloud of aeroengine blade can be acquired with a simplified system.
- monocular stereoscopic vision /
- blade surface /
- stereo matching /
- spatial coordinates of point cloud

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