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张秉刚, 石铭霄, 陈国庆, 冯吉才. 基于视觉传感的电子束深熔焊焊缝表面成形的预测[J]. 焊接学报, 2011, (12): 1-4,36.
引用本文: 张秉刚, 石铭霄, 陈国庆, 冯吉才. 基于视觉传感的电子束深熔焊焊缝表面成形的预测[J]. 焊接学报, 2011, (12): 1-4,36.
ZHANG Binggang, SHI Mingxiao, CHEN Guoqing, FENG Jicai. Prediction of weld appearance of electron beam deep penetration welding based on visual sensing[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2011, (12): 1-4,36.
Citation: ZHANG Binggang, SHI Mingxiao, CHEN Guoqing, FENG Jicai. Prediction of weld appearance of electron beam deep penetration welding based on visual sensing[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2011, (12): 1-4,36.

基于视觉传感的电子束深熔焊焊缝表面成形的预测

Prediction of weld appearance of electron beam deep penetration welding based on visual sensing

  • 摘要: 基于视觉传感的方法,获得了钛合金电子束焊熔池图像.采用二值形态学图像处理算法对熔池图像进行了处理,得到了熔池的边缘,并在此基础上利用自己开发的一套熔宽提取程序实现了熔宽的准确提取.找到了熔宽的波动性与焊缝表面成形之间的对应关系,当熔宽波动较大时,表面成形较差,而当熔宽波动较小时,表面成形较好.经过分析,提出用变异系数CV作为表征量对焊缝表面成形进行描述.结果表明,所开发的图像处理算法的熔宽检测误差均在0.1 mm以内,完成整个熔宽提取过程所需时间大约为30 ms,可以满足实时检测的需要.变异系数可以反应焊缝表面成形的好坏,为焊缝表面成形的控制创造了条件.

     

    Abstract: Basing on visual sensing method, the electron beam welding molten pool image of titanium alloy was obtained. The binary morphological image processing algorithm was used to process the molten pool image for getting the molten pool edge, moreover, the molten pool width was obtained by using a suite of processing programs for molten pool extraction. The correspondence relationship between the fluctuation of molten pool width and weld appearance is found, i. e. the weld appearance is poor when the fluctuation of molten pool width is relatively large, but the weld appearance is good when the fluctuation of molten pool width is relatively small. Based on analysis, the coefficient of variation CV was proposed as characterization to describe the weld appearance. The results show that the developed image processing algorithms are reliable, and the detected errors are less than 0.1 mm, at the same time the whole extraction process of molten pool width only needs approximately 30 milliseconds, which could meet the needs of real time detection. The coefficient of variation can reflect the quality of weld appearance and it can be used as a parameter to control the weld appearance.

     

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