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基于改进的边界追踪算法的管道法兰焊缝识别

钱晓明, 杨丽娟, 楼佩煌

钱晓明, 杨丽娟, 楼佩煌. 基于改进的边界追踪算法的管道法兰焊缝识别[J]. 焊接学报, 2016, 37(12): 115-119.
引用本文: 钱晓明, 杨丽娟, 楼佩煌. 基于改进的边界追踪算法的管道法兰焊缝识别[J]. 焊接学报, 2016, 37(12): 115-119.
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QIAN Xiaoming, YANG Lijuan, LOU Peihuang. Recognition of weld seam for pipe flange based on improved boundary following algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2016, 37(12): 115-119.
Citation: QIAN Xiaoming, YANG Lijuan, LOU Peihuang. Recognition of weld seam for pipe flange based on improved boundary following algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2016, 37(12): 115-119.
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基于改进的边界追踪算法的管道法兰焊缝识别

  • 南京航空航天大学 机电学院, 南京 210016

基金项目: 江苏省重点研发计划项目（BE2016004-3）；江苏省精密与微细制造技术重点实验室开放基金项目；江苏省产学研合作前瞻性联合研究项目（BY2015003-11）

Recognition of weld seam for pipe flange based on improved boundary following algorithm

  • College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

摘要

    摘要
  • 摘要: 针对目前管道法兰焊接中存在的缺点，文中对管道法兰焊缝进行先检测后识别，提出了一种基于改进的边界追踪算法的管道法兰焊缝识别方法.在焊缝检测阶段，利用曲率角估计的方法精确确定焊缝位置.在焊缝识别阶段，利用膨胀和掩码操作，根据检测到的焊缝位置，提出了一种在原图中设置不规则感兴趣区域的方法；细化边缘，并提出一种过滤伪边缘的算法.通过实际焊缝的试验验证，结果表明，基于改进的边界追踪算法的管道法兰焊缝识别方法能够准确的识别焊缝边缘，并且系统的识别稳定性好.
    Abstract: For the disadvantages existing in the current pipe flange welding, a method was proposed to of recognize the weld seam for pipe flange based on improved boundary following algorithm, which is divided into two steps of detecting the position of weld seam and then recognizing the weld seam accurately. At first, a method of curvature estimation was applied to position the weld seam in the detecting process. Secondly, a method to set irregular region of interest through dilation and mask in the original image was proposed based on the position of weld seam. And then the edge was thinned, and an algorithm was proposed to filter the pseudo edge. Experiments results showed that the proposed method is reliable and can recognize the weld seam accurately.
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    • 参考文献(9)
  • [1] 中国焊接协会成套设备与专用机具分会, 中国机械工程学会焊接学会机器人与自动化专业委员会[M]. 北京:机械工业出版社, 2014.
    [2] 雷正龙, 吕涛, 陈彦宾, 等. 基于扫描激光视觉传感的焊缝图像特征信息识别[J]. 焊接学报, 2013, 34(5):54-58. Lei Zhenglong, Lü Tao, Chen Yanbin. et al. Features extraction for weld image of scanning laser sensing[J]. Transaction of the China Welding lnstitution, 2013, 34(5):54-58.
    [3] Xu P, Xu G, Tang X, et al. A visual seam tracking system for robotic arc welding[J]. The International Journal of Advanced Manufacturing Technology, 2008, 37(1-2):70-75.
    [4] 陈希章, 陈善本. 弧焊机器人起始焊接位置图像识别与定位[J]. 焊接学报, 2009, 30(4):17-20. Chen Xizhang, Chen Shanben. Recognition and positioning of start welding position for arc welding robot[J]. Transaction of the China Welding lnstitution, 2009, 30(4):17-20.
    [5] Shi Fanhuai, Lin Tao, Chen Shanben. Efficient weld seam detection for robotic welding based on local image processing[J]. The Industrial Robot, 2009, 36(3):277-283.
    [6] Chen Xizhang, Chen Shanben, Lin Tao. Recognition of macroscopic seam for complex robotic welding environment[J]. Lecture Notes in Control and Information Sciences, 2007, 362:171-178.
    [7] 申俊琦, 胡绳荪, 冯胜强. 自适应中值滤波在焊缝视觉跟踪中的应用[J]. 焊接学报, 2011, 32(3):57-60. Shen Junqi, Hu Shengsun, Feng Shengqian. Application of adaptive median filtering in vision seam tracking. Transaction of the China Welding lnstitution, 2011, 32(3):57-60.
    [8] Gonzalez R C, Wintz P. Digital image processing[J]. Prentice Hall International, 2002, 28(4):484-486.
    [9] Liu Hairong, Longin Jan Latecki, Liu Wenyu. A unified curvature definition for regular, polygonal, and digital planar curves[J]. International Journal of Computer Vision, 2008, 80(1):104-124.
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  • 收稿日期:  2014-11-13

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