基于改进的边界追踪算法的管道法兰焊缝识别
Recognition of weld seam for pipe flange based on improved boundary following algorithm
-
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.
-
Keywords:
- weld recognition /
- curvature estimation /
- boundary following /
- irregular ROI /
- pseudo edge filtering
-
-
[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. -
期刊类型引用(7)
1. 郑医，张宇慧，陈玉宝. BNi-2和BNi71CrSi钎料钎焊K405合金接头组织与性能比较. 电焊机. 2019(06): 37-40 . 
百度学术
2. 蔡正旭，史秀梅，焦磊，金凯，陈怡兰. 电真空器件用金银锗钎料研制. 焊接. 2019(07): 57-59+68 . 百度学术
3. 石宇皓，石成杰，吴炳英，林盼盼，林铁松，何鹏. 陶瓷连接技术及其应用. 精密成形工程. 2018(01): 10-22 . 百度学术
4. 朱永权，张丽霞，任伟，冯吉才. 表面活化Al_2O_3陶瓷与5005铝合金真空钎焊. 焊接学报. 2018(11): 78-82+132 . 本站查看
5. 朱成俊，李成思，董雪花. 采用两种银基活性钎料钎焊AlN陶瓷与可伐合金的接头组织与性能. 焊接学报. 2018(10): 16-19+40+129 . 本站查看
6. 杜金松，颜家振，曹建国，杨德勇，辛成来. 蓝宝石/4J33合金钎焊接头残余应力的数值模拟分析. 焊接学报. 2017(08): 87-90+132-133 . 本站查看
7. 秦典成，李保忠，肖永龙. 陶瓷金属化研究现状及发展趋势. 中国陶瓷工业. 2017(05): 30-36 . 百度学术
其他类型引用(4)
计量
- 文章访问数: 479
- HTML全文浏览量: 4
- PDF下载量: 201
- 被引次数: 11
下载:
