期刊文献+

基于被动视觉的焊接过程多信息检测系统 被引量:2

Multi-information detection system of welding process based on passive vision
下载PDF
导出
摘要 针对焊接过程控制的要求,提出了一种基于被动视觉的焊接过程多信息检测系统,系统由工业CCD摄像机、窄带光学滤光片、计算机系统等组成,窄带滤光片以弧光较弱的950 nm为中心波长,以减少焊接过程中弧光的干扰,获得清晰的焊接图像.在焊接过程中,系统通过视觉信息对焊缝、电弧、熔池和焊丝等进行实时检测,提取电弧摆动的中心位置偏差、幅度偏差和角度偏差等多个特征参数,以此对焊枪进行控制,使得电弧的摆动中心和焊缝中心一致,摆动平面和焊缝中心垂直,摆动幅度和焊缝宽度相适应,避免了焊接过程的夹渣和未熔透等缺陷,保证了良好的焊后成形质量. As for the process control of the arc welding,a detection system for welding process was proposed based on passive vision,which was composed of industry CCD camera,narrow-band optical filters and computer.The center wavelength of the narrow-band optical filter was 950 nm,which could reduce the arc interference and help to obtain a clear image of in welding process.During the welding,the system can detect the arc,molten pool,wire in real time,and the characteristic parameters of the position deviation,amplitude deviation and angle deviation of the arc can be obtained.According to the obtained information,the welding torch can be controlled to make the arc move,which can make the swing center,the swing plane and the swing amplitude be adapted to the position and shape of the weld seam,avoid defects formation during welding and result in a good welding quality.
作者 郑军 潘际銮
出处 《焊接学报》 EI CAS CSCD 北大核心 2010年第11期49-52,共4页 Transactions of The China Welding Institution
基金 国家863高技术研究发展计划资助项目(2007AA04Z242)
关键词 焊接 被动视觉 多信息 实时 welding passive vision multi-information real-time
  • 相关文献

参考文献6

  • 1Zhao Xiangbin, Li Liangyu, Xiao Changliang, et al. Image proeessing in laser vision based weld tracking system [ J ]. Transactions of the China Welding Institution, 2006, 27(12) : 42 -48.
  • 2Kodama M, Iwabuti H, Iwabuti H. Arc sensor for simultaneous detection of torch aiming deviation and gap width-development of high frequency oscillation are[ J ]. Quarterly Journal of the Japan Welding Society, 2001, 19(2) : 287 -298.
  • 3Mahajan A, Figueroa F. Intelligent seam tracking using ultrasonic sensors for robotic welding[J]. Robotica, 1997, 15(3) : 275 - 281.
  • 4徐培全,唐新华,李莉娜,徐国祥,姚舜.视觉传感机器人焊缝跟踪系统[J].上海交通大学学报,2008,42(1):28-31. 被引量:12
  • 5席峰,宋永伦.基于视觉传感的焊缝跟踪控制系统[J].仪表技术与传感器,2006(5):30-31. 被引量:11
  • 6Xu D, Wang L K, Tan M. Image processing and visual control method for arc welding robot[ C]// In Proceedings of 2004 IEEE International Conference on Robotics and Biomimetics,2004:727 - 732.

二级参考文献4

共引文献20

同被引文献27

  • 1Chokkalingham S, Chndrasekhar N, Vasudevan M. Predicting the depth of penetration and weld bead width from the infratl thermal image of the weld pool using artificial neural network modeling I J ]. Journal of Intelligent Manufacturing, 2012, 23 (5) : 1995 - 2001.
  • 2Pal K, Pal S. Monitoring of weld penetration using arc acoustics [J]. Materials and Manufacturing Processes, 2011, 26(5) : 684 -693.
  • 3Zhang YM, Song H S. Monitoring and control of penetration in GTAW and pipe welding[J]. Welding Journal, 2013, 92(9) : 190s - 196s.
  • 4Choi J H, Lee J Y, Yoo C D. Simulation of dynamic behavior in a GMAW system [ J ]. Welding Journal, 2001,80 (10) : 239 - 245.
  • 5Artermis A. Thermal and solidification modeling of weld: a design tool approaehC D. US,Tufts University, 2002.
  • 6Thomsen J S. Advanced control methods for optimization of arc weldingC D. Aalborg, Aalberg University, 2005.
  • 7杨春利,张九海,王其隆.TIG焊熔池外激谐振与熔透的关系[J].焊接学报,1990,11(4):193-199. 被引量:10
  • 8张华,潘际銮,廖宝剑.焊接温度场的实时检测及熔透闭环控制[J].焊接学报,1998,19(3):176-183. 被引量:9
  • 9王欢,胡德安,陈益平,徐旭.基于网格的焊接车间信息集成系统构造分析[J].焊接技术,2010,39(3):53-55. 被引量:2
  • 10郭正华,温聪灵,郭吉萍.真空电子束焊CAPP系统的研究[J].热加工工艺,2010,39(5):118-120. 被引量:6

引证文献2

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部