期刊文献+

铝合金焊接熔池图象传感器 被引量:3

Image sensor for welding pool of aluminum alloy
下载PDF
导出
摘要 采用图象处理与模式识别的方法对铝合金的焊接质量进行智能控制还没有成功 ,因为铝合金表面不同于其它黑色金属 ,铝合金表面反射全波段的可见光 ,熔池与周围金属的灰度对比度极弱 ,在焊接电流较大时弧光强烈 ,弧光以及熔池周围金属的反射光足以掩盖熔池 ,普通的光学传感器无法在上述苛刻条件下取得铝合金焊接熔池区域的图象。通过光谱分析 ,可以设计全新的光学传感器 ,利用普通工业CCD摄像机获得清晰的铝合金焊接熔池区域图象 。 The way that use the image proceeding and the pattern recognition to intelligently control the quality of the aluminum alloy's welding has not been succeed in the manufacture.It is mainly because that the surface of the aluminum can reflect the visible light in whole wave range. The contrast between the welding pool and the plate nearby is too weak,the arc light and the light reflected by the surface of the aluminum is so strong that it submerges the welding pool.We designed a completely new optical sensor on the base of the analysis to the light spectrum,and obtained the clear picture of the welding pool during the aluminum alloy's welding by using the common industrial CCD camera;and with the new algorithm provided by myself,the desirable characteristic parameters of the welding pool of aluminum alloy's welding is obtained.This means that which provides a good background for advance aluminum alloy's intelligent welding.
出处 《传感器技术》 CSCD 北大核心 2001年第10期14-16,共3页 Journal of Transducer Technology
关键词 铝合金 图象传感器 焊接熔池 aluminum alloy TIG welding spectral analysis image sensor
  • 相关文献

参考文献6

  • 1李鹏九.焊接过程弧光传感的应用基础研究[M].哈尔滨:哈尔滨工业大学,1997.68-106.
  • 2张广军 耿正 等.铝合金变极性TIG焊图象传感方法的研究[J].焊接学报,1997,(12):96-100.
  • 3Zhao D B,Proceedings of Spie Int Society for Optical Engineering,1999年,38卷,3期,91页
  • 4李鹏九,学位论文,1997年,68页
  • 5Kovacevic R,J Manufact Sci Eng Trans ASME,1997年,119卷,5期,161页
  • 6张广军,焊接学报,1997年,12期,96页

共引文献2

同被引文献15

  • 1吕学勤,张轲,吴毅雄.焊缝自动跟踪的发展现状与展望[J].机械工程学报,2003,39(12):80-85. 被引量:55
  • 2Shibata N, Hirai A, Takano Y, et al. Development of groove recognition algorithm with visual sensor. Welding Research Abroad,2000,46(6): 9 ~ 17.
  • 3Shibata N, Hirai A, Takano Y. Development of groove recognition algorithm with visual sensor. Welding Research Abroad, 2000, 46(6): 9 ~ 17.
  • 4Boillot J P, Galibois A , Uota K. Present situation and future trendsin vision- guided welding robots. Published in the Proceeds From the 38th Annual Conference of Metallurgists, 1999..
  • 5Chen S B, Lou Y J, Wu L, et al. Intelligent methodology for sensing. Welding Journal, 2000, 79(6): 151s~163s.
  • 6Bae K Y, Lee T H, Ahn K C. An optical sensing system for seam tracking and weld pool control in gas metal arc welding of steel pipe.Journal of Materials Processing Technology, 2002, 120( 1 ~ 3): 458~465.
  • 7Chen Jihong, Zhou Huicheng, Yang Daoshan, et al. Research on a geometric model - based 3D inspection machine. Proc SPIE, 1997,2909:215 ~ 222.
  • 8Clark T A. The use of laser based triangulation techniques in optical inspection of industrial structures. Proc SPIE, 1990, 1332:50 ~ 56.
  • 9Yu Jeyong, Na Suckjoo. A study on vision sensors for seam tracking of height - varying weldment. Mechatronics, 1997(7) :599 ~ 612.
  • 10陈强,孙振国.计算机视觉传感技术在焊接中的应用[J].焊接学报,2001,22(1):83-90. 被引量:58

引证文献3

二级引证文献27

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