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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

cstr: 32171.14.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
    否 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
    是 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 无 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 中 MAE<0.03 mm [39, 44-45]
    颜色信息 颜色通道分离 高 PAE<0.03 rad [48, 49]
    图案编码、解码 增加相移步数、多频条纹 低 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 高 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 差 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。 差 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。 好 简单 好 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。 好 复杂 好 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。 好 简单 好
    (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。 好 简单 好 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。 差 简单 差 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。 好 简单 好 适用
    下载: 导出CSV
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  • 收稿日期:  2023-04-16
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