365赌球

刘泽隆; 李茂月; 卢新元; 张明垒

doi:10.37188/CO.2023-0068

365赌球

doi: 10.37188/CO.2023-0068

哈尔滨理工大学先进制造智能化技术教育部重点实验室, 黑龙江哈尔滨 150080

基金项目:国家自然科学基金（No. 51975169）；黑龙江省自然科学基金（No. LH2022E085）资助项目

详细信息

作者简介:
刘泽隆（1996—），男，黑龙江大庆人，在读博士研究生，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： [email protected]

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：[email protected]

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- 网络出版日期: 2023-09-21

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Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China

Funds:Supported by Natural Science Foundation of China (No. 51975169); Natural Science Foundation of Heilongjiang Province(No. LH2022E085)

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Corresponding author: [email protected]

摘要

摘要:
随着工业制造不断向智能化、精密化、集成化方向发展，对加工过程进行在机检测，可及时反馈测量结果并补偿修正加工参数，有助于提高加工精度和效率。条纹结构光技术是近年来发展迅速的非接触式测量方法，具有测量原理简单、成本低、测量精度高、易于集成等特点，为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，测量结果不准确，将高动态范围（High Dynamic Range, HDR）技术应用于结构光检测中，可实现对金属零件在复杂场景的测量，抑制高反光的影响。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，按照基于硬件设备的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，对各类技术进行了总结，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，进行潜在应用分析，提出技术展望。
- 三维测量 /
- 结构光 /
- 条纹投影 /
- 高动态范围 /
- 在机检测
Abstract:
With the development of industrial manufacturing towards intelligence, precision and integration, on-machine verification of the machining process can provide timely feedback on measurement results, compensate and correct processing parameters, thereby aiding in enhancing machining accuracy and efficiency. Fringe structured light technology is a non-contact measurement method, which has developed rapidly in recent years. It has the characteristics of simple measurement principle, low costs, high measurement accuracy and easy integration, which provides a new solution for on-machine verification. However, the accuracy of structural for on-machine verification is compromised by the convoluted lighting in machining environments and metal parts’ high reflectivity, leading to inaccurate measurements. Applying high dynamic range (HDR) technology to structural light detection enables the measurement of metal parts in complex scenes and reduces the effect of high reflectivity. This paper introduces the measurement principle of structured light and summarizes the challenges of on-machine verification for HDR structured light. Subsequently, this paper provides a comprehensive review of HDR structured light technology. Based on the context of on-machine verification, the HDR technology using hardware equipment and the stripe algorithm are discussed and analyzed, respectively. Following this, different technologies are summarized according to the requirements of on-machine verification. The advantages and disadvantages of various methods are presented, and the applicability of on-machine verification is compared. Finally, the potential applications are analyzed, and the technological prospects will be proposed in combination with the research hotspots of advanced manufacturing technology and precision measurement in recent years.
- Three-dimensional measurement /
- structured light /
- fringe projection /
- high dynamic range /
- on-machine verification

HTML全文

图 1 结构光测量原理示意图^{[
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Figure 1. Schematic diagram of monocular structured light^{[
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图 2 结构光在机检测示意图

Figure 2. Schematic diagram of structured light on machine detection

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图 3 结构光在机检测系统架构

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

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图 4 曝光融合算法流程^{[
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Figure 4. The process of exposure fusion algorithm^{[

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图 5 Xiang设计的偏振测量系统^{[
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Figure 5. Polarization measurement system designed by Xiang^{[
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图 6 封闭激光腔内COPMD测量系统^{[
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Figure 6. COPMD measurement system in an enclosed laser cavity^{[

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图 7 条纹反射在位面形检测系统中的装置^{[
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Figure 7. Fringe reflection setup in on-machine surface measurement system^{[
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图 8 大口径抛物面反射镜实验装置图^{[
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Figure 8. Experimental device diagram of large diameter parabolic reflector^{[
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图 9 Jiang所提方法的测量结果^{[
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Figure 9. The measured results by Jiang's method^{[
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图 10 彩色图像不同通道亮度衰减原理图^{[
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Figure 10. Schematic diagram of brightness attenuation of different channels of color image^{[
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图 11 Liu所提方法的动态物体测量结果^{[
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Figure 11. The measured results of dynamic objects by Liu's method^{[
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图 12 Hu所提方法对微小反光物体测量结果^{[
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Figure 12. The measured results of tiny reflective objects by Hu's method^{[
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图 13 EBAM机床结构光在机检测设备^{[
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Figure 13. On-machine verification equipment with structured light in EBAM machine tool^{[
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图 14 高动态范围条纹图像改善网络^{[

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Figure 14. High dynamic range fringe pattern improvement network^{[
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图 15 封装芯片的检测设备及结果^{[
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Figure 15. Measured equipment and result of packaged chips^{[
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图 16 3D结构光医疗机器人

Figure 16. 3D structured light medical robot

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图 17 大口径非球面反射镜

Figure 17. Large aperture aspheric reflector

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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。

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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 ]

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表 3 基于条纹算法的HDR技术对比

Table 3. Comparison of HDR technology 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 ]

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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（需要高速投影）	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

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