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光栅投影在机三维形貌检测技术研究进展

吕虹毓 李茂月 蔡东辰 赵伟翔

吕虹毓, 李茂月, 蔡东辰, 赵伟翔. 光栅投影在机三维形貌检测技术研究进展[J]. 中国光学(中英文), 2023, 16(3): 500-513. doi: 10.37188/CO.2022-0083
引用本文: 吕虹毓, 李茂月, 蔡东辰, 赵伟翔. 光栅投影在机三维形貌检测技术研究进展[J]. 中国光学(中英文), 2023, 16(3): 500-513. doi: 10.37188/CO.2022-0083
LV Hong-yu, LI Mao-yue, CAI Dong-chen, ZHAO Wei-xiang. Research progress of grating projection on machine 3D topography inspection technology[J]. Chinese Optics, 2023, 16(3): 500-513. doi: 10.37188/CO.2022-0083
Citation: LV Hong-yu, LI Mao-yue, CAI Dong-chen, ZHAO Wei-xiang. Research progress of grating projection on machine 3D topography inspection technology[J]. Chinese Optics, 2023, 16(3): 500-513. doi: 10.37188/CO.2022-0083

光栅投影在机三维形貌检测技术研究进展

doi: 10.37188/CO.2022-0083
基金项目: 国家自然科学基金资助项目(No. 51975169);黑龙江省普通高校基本科研业务费专项资金资助项目(No. 2019-KYYWF-0204)
详细信息
    作者简介:

    吕虹毓(1996—),男,山东济宁人,博士研究生,2021年于哈尔滨理工大学获得硕士学位,主要研究方向为计算机视觉及光学非接触式测量技术等。E-mail:lhy3007@126.com

    李茂月(1981—),男,山东青岛人,博士,教授,博士生导师,2004 年于南京林业大学获得学士学位,2007 年于长安大学获得硕士学位,2012 年于哈尔滨工业大学获得博士学位,主要从事智能加工与光学检测技术方面的研究。E-mail:lmy0500@163.com

  • 中图分类号: TH741

Research progress of grating projection on machine 3D topography inspection technology

Funds: Supported by National Natural Science Foundation of China (No. 51975169) ;the Fundamental Research Fundation for Universities of Heilongjiang Province (No. 2019-KYYWF-0204)
More Information
  • 摘要:

    基于视觉的测量方式对航天、军工以及电子芯片等先进制造领域具有良好应用前景以及深远的发展意义,而基于结构光的在机三维视觉检测技术,是目前精密加工领域的热点与难点之一。本文以结构光在机三维测量流程为主线,将其中的关键技术,包括测量标定、相位优化求解、在机三维点云处理及不同特征曲面重构中的技术要求、涉及的方法和原理、相关研究现状及目前存在的问题,进行论述与总结。最后,根据未来相关技术的实际需求,在加工现场标定、动态实时三维重构、亚微米及纳米级测量、测量-加工一体化数据传输技术等方面进行了展望,并提出了相应的研究思路。

     

  • 图 1  零件测量技术发展趋势

    Figure 1.  Development trend of part measurement technology

    图 2  基于结构光的在机检测系统架构

    Figure 2.  Architecture of an on-machine detection system based on structured light

    图 3  GOM ATOS ScanBox 8360三维测量系统

    Figure 3.  GOM ATOS ScanBox 8360 3D measurement system

    图 4  本课题组研发的单目结构光智能在机检测平台

    Figure 4.  Monocular structured light intelligent on-machine detection platform developed by our research group

    图 5  基于数字光栅投影的三维测量流程

    Figure 5.  3D measurement flow based on digital grating projection

    图 6  畸变投影系统光路

    Figure 6.  Optical path of the distorted projection system

    图 7  薄壁叶片表面反光现象

    Figure 7.  Surface reflection phenomenon of thin-walled blades

    图 8  反光形成的点云缺失

    Figure 8.  Missing point cloud formed by reflection

    图 9  (a)全自动曝光增强三维测量系统及(b),(c)方法流程[32]

    Figure 9.  (a) Full automatic exposure enhancement 3D measurement system and (b), (c) it’s flow chart[32]

    图 10  紧凑型反光金属工件三维测量系统[36]

    Figure 10.  Three dimensional measurement system of compact reflective metal workpiece[36]

    图 11  结构光投影测量模型

    Figure 11.  Structured light projection measurement model

    图 12  基于点云优化信息的修复方法流程[50]

    Figure 12.  Repair method flow based on point cloud optimization information[50]

    图 13  基于GA-BP算法的点云孔洞修补流程

    Figure 13.  Point cloud hole repair process based on the GA-BP algorithm

    图 14  无人车搭载机械臂的大型叶片测量重构[56]

    Figure 14.  Measurement and reconstruction of a large blade of an unmanned vehicle equipped with a manipulator[56]

    图 15  微细管孔内表面三维重构模型[61]

    Figure 15.  3D reconstruction model of the inner surface of a microtubule hole [61]

    图 16  航天发动机机匣

    Figure 16.  Aerospace engine casing

    图 17  视点规划测量过程

    Figure 17.  Viewpoint planning measurement process

    表  1  光学测量系统平台性能及特点

    Table  1.   Performance and characteristics of the optical measurement system platform

    测量系统平台测量精度距离量程优点缺点适用场景
    电子经纬仪10 μm0~150 m具有误差自修正功能,
    抗干扰性强
    内部元器件制造
    误差制约测量精度
    大尺寸零件装配
    及尺寸检测
    结构光投影测量系统0.1~20 μm0.1~10 m非逐点检测,测量效率高测量过程受反光影响复杂形貌零件,高效测量
    激光扫描仪0.1~10 μm0~80 m测量精度高,便携性好测量效率较低小尺寸零件,动态测量
    机械臂测量系统50 μm0~5 m自动化程度高场景约束性强,便携性较差全自动化加工检测场景
    白光干涉仪纳米级或亚纳米级150 μm~20 mm测量精度较高使用条件及要求较苛刻,
    测量效率低
    超精密加工及3C电子检测
    下载: 导出CSV

    表  2  典型自适应测量参数标定方法

    Table  2.   Typical adaptive measurement parameter calibration methods

    代表性学者技术方法优点缺点适用场景
    Yao[17]图像特征向量法标定精度高复杂度偏高工业化快速标定测量场景
    Gao[18]视野变焦控制法标定速度快,实时性好难以适用于复杂检测场景物距变化测量场景
    Moru[22]参数规律统计法无需设置初始参数较难获取精确参数区间采用定焦镜头的测量过程
    管雯璐[23]微型自动调节装置装置灵活、抗环境干扰强成本较高变温条件下的自动标定
    Hojong Choi[25]步进电机自动控制法不需人为干预,自动化水平高装置占用空间较多自适应焦距调节
    下载: 导出CSV

    表  3  典型的光饱和优化方法对比

    Table  3.   Comparison of typical optical saturation optimization methods

    代表性学者技术方法优点缺点适用场景
    Pinzek [29]多重曝光控制法曝光参数控制较方便,无需额外硬件系统难以根据环境定量精确控制曝光,
    耗时长
    环境光照影响较为主要时的检测
    Liu [32]全自动快速最佳曝光计算方法检测过程自动化水平
    较高
    易影响反射率较小部位,造成曝光
    不足
    表面尺寸较大的反光物体检测
    陈龙[35]局部自适应条纹投影法具有针对性的处理,
    不影响其他区域像素
    准确的灰度阈值较难
    确定
    叶片、轴类表面反射率
    差异大的对象检测
    Liu [37]多目视点配准法测量精度
    较高
    受测量空间限制,欠缺灵活性小范围精密物体的在机检测
    Zhang [38]偏振滤光
    片法
    可较精确控制光平衡需要添加额外的光学及控制硬件镜面物体的在机检测
    下载: 导出CSV

    表  4  在机动态相位补偿代表性方法对比

    Table  4.   Comparison of representative methods of on machine dynamic phase compensation

    代表性学者技术方法优点缺点适用场景
    Feng[40]周期性运动相位补偿法对规律性误差补偿效
    果好
    难以应用于复杂运动
    场景
    匀速运动状态的相位
    补偿
    Deng[41]条纹阶噪声分析法无需逐像素计算相位
    误差
    依赖实验条件及人工分析步骤存在噪声的动态场景
    测量
    郭逸凡[42]光流补偿法准确判断运动测量状态对环境光线过于敏感高速动态场景测量
    Kim[43]相移格雷码结合方式操作简单、测量速度快易引起新的测量误差实时在机三维扫描测量
    下载: 导出CSV

    表  5  常用的离群点去除方式

    Table  5.   Common outlier removal methods

    离群点去除方法适用场景
    基于迭代优化算法适合于在杂乱噪声中搜寻临近目标点
    基于邻域信息的
    点云聚类算法
    适合对具有特定类型的
    点云数据进行分类
    基于点云频率的滤波方式适合对较复杂形状点云模型的分割计算
    下载: 导出CSV

    表  6  不同类型曲面形貌重构技术对比

    Table  6.   Comparison of different types of surface reconstruction technologies

    曲面类型典型代表曲面特点测量难点适用测量策略曲面拟合方法
    大尺寸曲面零件涡轮发动机叶片、航空曲面零件形状较规律,曲面尺寸数米至数十米一次扫描难以测量出完整表面点云,且数据计算量庞大采用柔性测量装置并配合多视角点云拼接方式曲面片直接
    拟合法
    微型曲面零件微型精密半导体零件、精密光学器件曲面尺寸较微小
    (毫米级)
    点云分割难度较大,且较难解决
    过拟合和欠拟合问题
    搭载光学高倍镜头和立体显微镜的光栅条纹投影法的测量方式样条曲线
    拟合方法
    复杂形状及曲面结合体复杂腔体类零件结构复杂,面数较多点云模型拟合困难,测量繁琐,难以获得高精度且完整的点云模型接触式与非接触式结构
    光结合的测量方式
    基于特征约束及交互式曲面拟合方法
    下载: 导出CSV
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  • 收稿日期:  2022-04-28
  • 修回日期:  2022-05-31
  • 网络出版日期:  2022-09-28

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