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高动态范围条纹结构光在机检测技术及应用进展

刘泽隆 李茂月 卢新元 张明垒

刘泽隆, 李茂月, 卢新元, 张明垒. 高动态范围条纹结构光在机检测技术及应用进展[J]. 中国光学(中英文), 2024, 17(1): 1-18. doi: 10.37188/CO.2023-0068
引用本文: 刘泽隆, 李茂月, 卢新元, 张明垒. 高动态范围条纹结构光在机检测技术及应用进展[J]. 中国光学(中英文), 2024, 17(1): 1-18. doi: 10.37188/CO.2023-0068
LIU Ze-long, LI Mao-yue, LU Xin-yuan, ZHANG Ming-lei. On-machine detection technology and application progress of high dynamic range fringe structured light[J]. Chinese Optics, 2024, 17(1): 1-18. doi: 10.37188/CO.2023-0068
Citation: LIU Ze-long, LI Mao-yue, LU Xin-yuan, ZHANG Ming-lei. On-machine detection technology and application progress of high dynamic range fringe structured light[J]. Chinese Optics, 2024, 17(1): 1-18. doi: 10.37188/CO.2023-0068

高动态范围条纹结构光在机检测技术及应用进展

doi: 10.37188/CO.2023-0068
基金项目: 国家自然科学基金资助项目(No. 51975169);黑龙江省自然科学基金资助项目(No. LH2022E085)
详细信息
    作者简介:

    刘泽隆(1996—),男,黑龙江大庆人,博士研究生,2022 年于哈尔滨理工大学获得硕士学位,主要从事图像处理和机器视觉方面的研究。E-mail:LZL_LOUIS1231@163.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

On-machine detection technology and application progress of high dynamic range fringe structured light

Funds: Supported by National Natural Science Foundation of China (No. 51975169); Natural Science Foundation of Heilongjiang Province(No. LH2022E085)
More Information
  • 摘要:

    条纹结构光技术是近年来发展迅速的非接触式测量方法,为机械加工在机检测提供了新的解决方案。由于加工环境光线复杂且金属零件本身具有高反光的特性,造成结构光在机检测的精度降低。将高动态范围(High Dynamic Range,HDR)技术应用于结构光检测中,可抑制高反光的影响,实现金属零件在复杂场景的测量。本文首先介绍了结构光测量原理,总结出HDR结构光在机检测面临的难点;其次,对HDR结构光技术进行了全面综述,以机械加工在机检测为背景,对基于硬件设备的HDR技术和基于条纹算法的HDR技术分别进行了归纳分析;然后,根据在机检测的条件需求,对各类技术进行总结,并比较不同方法的优缺点和在机检测的适用性;最后,结合近年来先进制造技术和精密测量的研究热点,对潜在应用进行分析,提出技术展望。

     

  • 图 1  结构光测量原理示意图[8]

    Figure 1.  Schematic diagram of monocular structured light measurement principle[8]

    图 2  结构光在机检测示意图

    Figure 2.  Schematic diagram of structured light on-machine detection

    图 3  结构光在机检测系统架构

    Figure 3.  Architecture of on-machine detection system of structured light

    图 4  曝光融合算法流程[17]

    Figure 4.  The process of exposure fusion algorithm[17]

    图 5  Xiang设计的偏振测量系统[24]

    Figure 5.  Polarization measurement system designed by Xiang[24]

    图 6  封闭激光腔内COPMD测量系统[26]

    Figure 6.  COPMD measurement system in an enclosed laser cavity[26]

    图 7  条纹反射在位面形检测系统中的装置[30]

    Figure 7.  Fringe reflection setup in on-machine surface measurement system[30]

    图 8  大口径抛物面反射镜实验装置图[31]

    Figure 8.  Experimental device diagram of large diameter parabolic reflector[31]

    图 9  Jiang所提方法的测量结果[41]

    Figure 9.  The measurement results by Jiang’s method[41]

    图 10  彩色图像不同通道亮度衰减原理图[51]

    Figure 10.  Schematic diagram of brightness attenuation in different channels of color image[51]

    图 11  Liu所提方法的动态物体测量结果[53]

    Figure 11.  The measurement results of dynamic objects by Liu’s method[53]

    图 12  Hu所提方法对微小反光物体测量结果[60]

    Figure 12.  The measurement results of tiny reflective objects by Hu’s method[60]

    图 13  EBAM机床结构光在机检测设备[70]

    Figure 13.  On-machine detection equipment with structured light in EBAM machine tool[70]

    图 14  高动态范围条纹图像改善网络[72]

    Figure 14.  High dynamic range fringe pattern improvement network[72]

    表  1  三维视觉测量技术分类

    Table  1.   Classification of three-dimensional visual measurement technology

    视觉测
    量分类
    是否投
    射光源
    具体分类 特点
    被动视
    觉测量
    单目视觉测量 基于图像聚焦程度完成三维重建,多用于显微视觉测量中。
    双目视觉测量 根据三角测量原理实现三维重建,应用于双目立体摄像头。
    多目视觉测量 增加辅助相机,通过光束平差提高测量精度。
    主动视
    觉测量
    点扫描式 激光器投射光点,根据光标中心坐标和标定数据进行重建,测量效率低。
    线扫描式 激光器投射光条代替光点,提高效率,广泛应用于激光扫描仪中。
    面扫描式 通过投影仪投射二维结构光,单次投射覆盖区域大,测量效率最高。
    下载: 导出CSV

    表  2  基于硬件设备的HDR技术对比

    Table  2.   Comparison of HDR technologies based on hardware devices

    HDR技术 额外硬件 测量精度 参考文献
    相机曝光 MAE<0.1 mm [13, 17]
    偏振滤光片 偏振片 MAE<0.1 mm [23-24]
    相位偏折术 LCD显示屏 MAE<0.001 mm [27, 30-31]
    光度立体法 多个光源 MAE<0.01 mm [37-38]
    下载: 导出CSV

    表  3  基于条纹算法的HDR技术对比

    Table  3.   Comparison of HDR technologies based on fringe algorithm

    HDR技术 算法思路 算法复杂程度 测量精度 参考文献
    调整条纹强度 逐像素改变条纹灰度值 MAE<0.03 mm [39, 44-45]
    颜色信息 颜色通道分离 PAE<0.03 rad [48, 49]
    图案编码、解码 增加相移步数、多频条纹 PAE<0.02 rad [52, 55, 57]
    智能算法 神经网络处理高光图像、预测相位 RMSE<0.06 mm [70, 72]
    下载: 导出CSV

    表  4  各类HDR测量技术总结

    Table  4.   Summary of various HDR measurement technologies

    HDR技术 优点 缺点 光线条件
    适应性
    系统硬件设备 检测效率 加工在机检测
    相机曝光 无需添置额外硬件、无后续其他处理。 选择曝光时间具有一定盲目性,需多次测量合成最优数据。 单次曝光适应性较差,多重曝光适应性好。 简单 不适用
    偏振滤光片 额外硬件较为简单、无其他复杂算法。 单偏振通道易降低整体图像的SNR,使用多个偏振通道时,需多次调整偏振片角度合成最优数据。 单通道适应性较差,多通道适应性好。 单通道简单,多通道较复杂。 不适用
    相位偏折术 适用于类镜面物体的测量,测量精度高,无其他复杂算法 空间摆放位置受限制,不适用于金属等反光件。 简单 适用(镜面、类镜面工件)
    光度立体法 利用多照明系统实现视角补盲 建立的反射模型不具有普适性。 复杂 不适用
    调整条纹强度 逐像素调整图像亮度,条纹图像具有较高的SNR 对于场景和反射区域的标定需投射多组条纹确定映射关系,算法的效率需依靠投影仪的帧率决定。 简单
    (配合高速投影)
    适用(配合高速投影)
    颜色信息 算法简单,无其他复杂算法 对于带有颜色和纹理特征的被测物,测量精度会受到影响。 简单 适用
    图案编码、解码 算法简单 增加条纹频率和相移步数,影响了测量的效率,且测量精度较低。 简单 不适用
    智能算法 测量效率高,可以实现动态测量 算法复杂,成本较高,需要高度定制的训练样本。 简单 适用
    下载: 导出CSV
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  • 收稿日期:  2023-04-16
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