Please wait a minute...
工程设计学报  2017, Vol. 24 Issue (6): 687-693,716    DOI: 10.3785/j.issn.1006-754X.2017.06.012
整机和系统设计     
基于机器视觉的激光器封装自动对准系统
彭忠超, 戚媛婧, 舒斌, 颜科, 段吉安
中南大学 高性能复杂制造国家重点实验室, 湖南 长沙 410083
Automatic alignment system for laser device packaging based on machine vision
PENG Zhong-chao, QI Yuan-jing, SHU Bin, YAN Ke, DUAN Ji-an
State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China
 全文: PDF(6839 KB)   HTML
摘要:

在半导体激光器封装过程中,针对非球面透镜与半导体激光器的对准过程中存在人工操作精度低、效率低的缺点,开发了一套高精度自动化对准系统。系统以机器视觉技术为基础,配置高性能CCS光源和高分辨率Basler相机,能够实时采集高精度图像;利用累计概率Hough变换和迭代重加权最小二乘法等图像处理算法,快速拟合非球面透镜和半导体激光器的边缘直线,实现自动对准。该系统采集的图像精度达到了亚微米级别,而且在0.5 s内便可完成整个对准过程,极大提高了非球面透镜与半导体激光器封装精度与效率。本视觉对准系统基于高性能配置的精确的图像处理算法,对传统的封装技术作出了很大改进,对提高未来半导体激光器封装精度和效率具有较大的推动作用。

关键词: 机器视觉非球面透镜半导体激光器累计概率Hough变换迭代重加权最小二乘法    
Abstract:

Considering low precision and efficiency of manual operation in the alignment process between aspheric lens and semiconductor laser, a system of automatic alignment was designed based on the technology of machine vision which configured with high-performance light source of CCS and high-resolution camera of Basler, high-precision images could be obtained in real time. First, the edge of aspheric lens and the semiconductor laser was fitted into two straight lines according to the algorithms of progressive probability Hough transform and iterative weighted least squares. Then, the angle between two lines were calculated and adjusted automatically, high precision alignment between aspheric lens and semiconductor laser was achieved finally. Completing the whole process within 0.5 s at the accuracy of sub-micron level, the packaging efficiency, the accuracy of the aspheric lens and the semiconductor laser were improved greatly by system. Based on high performance configuration and precise image processing algorithm, the vision alignment system has greatly improved in the traditional packaging technology, which will greatly promote the encapsulation efficiency and accuracy of semiconductor lasers in the future.

Key words: machine vision    aspheric lens    semiconductor laser    progressive probability Hough transform    iterative weighted least square
收稿日期: 2017-09-05 出版日期: 2017-12-28
CLC:  TP23  
基金资助:

国家自然科学基金资助项目(51075402;50975293)

作者简介: 彭忠超(1993-),男,四川达州人,硕士生,从事机械自动化与激光焊接研究,E-mail:1337504646@qq.com,http://orcid.org/0000-0002-3430-8623
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
彭忠超
戚媛婧
舒斌
颜科
段吉安

引用本文:

彭忠超, 戚媛婧, 舒斌, 颜科, 段吉安. 基于机器视觉的激光器封装自动对准系统[J]. 工程设计学报, 2017, 24(6): 687-693,716.

PENG Zhong-chao, QI Yuan-jing, SHU Bin, YAN Ke, DUAN Ji-an. Automatic alignment system for laser device packaging based on machine vision[J]. Chinese Journal of Engineering Design, 2017, 24(6): 687-693,716.

链接本文:

https://www.zjujournals.com/gcsjxb/CN/10.3785/j.issn.1006-754X.2017.06.012        https://www.zjujournals.com/gcsjxb/CN/Y2017/V24/I6/687

[1] 范增明,李卓,钱丽勋,等.非球面透镜组激光光束整形系统[J].红外与激光工程,2012,41(2):353-357. FAN Zeng-ming, LI Zhuo, QIAN Li-xun, et al. Aspherical lens laser beam shaping system[J]. Infrared and Laser Engineering, 2012, 41(2):353-357.
[2] 何永辉,王康健,石桂芬,等.基于机器视觉的高速带钢孔洞检测系统[J].应用光学,2007,28(3):345-349. HE Yong-hui, WANG Kang-jian, SHI Gui-fen, et al. High-speed hole inspection system for steel strips based on machine vision[J]. Journal of Applied Optics, 2007, 28(3):345-349.
[3] 何勇,孙钊,李华厦,等.机器视觉技术及其在机械制造自动化中的应用[J].黑龙江科技信息,2016(24):119. HE Yong, SUN Zhao, LI Hua-sha, et al. Machine vision technology and its application in mechanical manufacturing automation[J]. Heilongjiang Science and Technology Information, 2016(24):119.
[4] 赵伟杰,高勇.机器视觉在光纤端面缺陷检测中的应用[J].现代电子技术,2011,34(19):136-139. ZHAO Wei-jie, GAO Yong. Application of machine vision in defects inspection of optical fiber end surface[J]. Modern Electronic Technology, 2011, 34(19):136-139.
[5] 桂卫华,阳春华,徐德刚,等.基于机器视觉的矿物浮选过程监控技术研究进展[J].自动化学报,2013,39(11):1879-1888. GUI Wei-hua, YANG Chun-hua, XU De-gang, et al. Machine-vision-based online measuring and controlling technologies for mineral flotation:a review[J]. Acta Automatica Sinica, 2013, 39(11):1879-1888.
[6] 王运哲,白雁兵,张博,等.机器视觉系统的设计方法[J].现代显示,2011,22(11):24-27. WANG Yun-zhe, BAI Yan-bing, ZHANG Bo, et al. Machine vision system design method[J]. Advanced Display, 2011, 22(11):24-27.
[7] 杨丹,刘亚威,张小洪,等.高精度图像测量与对准系统的算法研究[J].计算机科学,2003,30(12):132-135. YANG Dan, LIU Ya-wei, ZHANG Xiao-hong, et al. Research on the algorithms of high accuracy image measurement and registration system[J]. Computer Science, 2003, 30(12):132-135.
[8] 董晶,杨夏,于起峰.基于边缘连接的快速直线段检测算法[J].光学学报,2013,33(3):213-220. DONG Jing, YANG Xia, YU Qi-feng. fast line segment detection based on edge connecting[J]. Acta Optica Sinica, 2013, 33(3):213-220.
[9] BRADSKI Gary,KAEBLER Adrian.学习OpenCV(中文版)[M].于仕琪,刘瑞祯译.北京:清华大学出版社,2009:175-177. BRADSKI Gary, KAEBLER Adrian. Learning OpenCV[M]. Translated by YU Shi-qi, LIU Rui-zhen. Beijing:Press of Tsinghua University, 2009:175-177.
[10] KIRYATI N, ELDAR Y, BRUCKSTEIN A M, et al. A probabilistic Hough transform[J]. Pattern Recognition, 1991, 2(4):303-316.
[11] MATAS J, GALAMBOS C, KITTLER J, et al. Robust detection of line using the progressive probabilistic Hough transform[J]. Computer Vision and Image Understanding, 2000, 78(1):119-137.
[12] 肖宿,韩国强.基于变量分离和加权最小二乘法的图像复原[J].计算机应用研究,2012,29(4):1584-1587. XIAO Su, HAN Guo-qiang. Image restoration based on variable splitting and weighted least squares[J]. Application Research of Computers, 2012, 29(4):1584-1587.
[13] 仲崇豪,姚宜斌,刘强,等.加权整体最小二乘的迭代解法[J].大地测量与地球动力学,2014,34(4):153-156. ZHONG Chong-hao, YAO Yi-bin, LIU Qiang, et al. Iterative method of weighted whole least squares[J]. Journal of Geodesy and Geodynamics, 2014, 34(4):153-156.
[14] SZELISKI Richard.计算机视觉:算法与应用(中文版)[M].艾海舟,兴军亮译.北京:清华大学出版社,2012:233-235. SZELISKI Richard. Computer vision:algorithms and applications[M]. Translated by AI Hai-zhou, XING Jun-liang. Beijing:Press of Tsinghua University, 2012:233-235.
[15] 王惠华,游福成,段怀锋,等.基于二值图像连通域提取的图像滤波方法[J],北京印刷学院学报,2015,23(6):39-41.WANG Hui-hua, YOU Fu-cheng, DUAN Huai-feng, et al. An image filtering method to extract connected domain in binary image[J]. Journal of Beijing Institute of Graphic Communication, 2015, 23(6):39-41.
[16] 熊波,尹周平.滑动平均和改进权重函数的快速非局部平均图像去噪算法[J].中国图象图形报,2012,17(5):628-634.XIONG Bo, YIN Zhou-ping. Fast non-localmeans for image de-noising on moving average and modified weight function[J]. Journal of Image & Graphics, 2012, 17(5):628-634.
[17] 徐阳,曹杰.一种基于对比度阈值的改进SIFT算法[J].电子设计工程,2012,20(19):174-177. XU Yang, CAO Jie. Improved SIFT algorithm based on the contrast threshold[J]. Electronic Design Engineering, 2012, 20(19):174-177.
[1] 李军星,李燕科,牛凯岑,邱明,王治华,庞晓旭,陈立海. 基于双方差随机过程的半导体激光器寿命评估[J]. 工程设计学报, 2022, 29(3): 293-299.
[2] 张爱云, 王吉华, 高崴, 张美娟. 基于机器视觉的VVT发动机转子缺陷检测系统设计[J]. 工程设计学报, 2021, 28(6): 776-784.
[3] 李梦. 基于机器视觉的车道线在线识别系统设计[J]. 工程设计学报, 2020, 27(4): 498-507.
[4] 乔景慧, 李岭. 基于机器视觉的电视机背板检测及自适应抓取研究[J]. 工程设计学报, 2019, 26(4): 452-460.
[5] 张伟, 高慧敏. 笔管缺陷自动化检测系统设计与研究[J]. 工程设计学报, 2019, 26(3): 346-353.
[6] 乔 峰,郑 堤,胡利永,魏玉艳. 基于机器视觉实时决策的智能投饵系统研究[J]. 工程设计学报, 2015, 22(6): 528-533.
[7] 周真, 齐忠亮, 秦勇, 丁国超. 半导体激光器恒温控制系统的高精度温度测量研究[J]. 工程设计学报, 2012, 19(3): 221-224.
[8] 罗 胜. 基于机器视觉的鞋楦数字化及类似方法对比[J]. 工程设计学报, 2007, 14(1): 57-61.