The welding deviation detection is the basis of robotic tracking welding, but the on-line real-time measurement of welding deviation is still not well solved by the existing methods. There is plenty of information in ...The welding deviation detection is the basis of robotic tracking welding, but the on-line real-time measurement of welding deviation is still not well solved by the existing methods. There is plenty of information in the gas metal arc welding（GMAW） molten pool images that is very important for the control of welding seam tracking. The physical meaning for the curvature extremum of molten pool contour is revealed by researching the molten pool images, that is, the deviation information points of welding wire center and the molten tip center are the maxima and the local maxima of the contour curvature, and the horizontal welding deviation is the position difference of these two extremum points. A new method of weld deviation detection is presented, including the process of preprocessing molten pool images, extracting and segmenting the contours, obtaining the contour extremum points, and calculating the welding deviation, etc. Extracting the contours is the premise, segmenting the contour lines is the foundation, and obtaining the contour extremum points is the key. The contour images can be extracted with the method of discrete dyadic wavelet transform, which is divided into two sub contours including welding wire and molten tip separately. The curvature value of each point of the two sub contour lines is calculated based on the approximate curvature formula of multi-points for plane curve, and the two points of the curvature extremum are the characteristics needed for the welding deviation calculation. The results of the tests and analyses show that the maximum error of the obtained on-line welding deviation is 2 pixels（0.16 ram）, and the algorithm is stable enough to meet the requirements of the pipeline in real-time control at a speed of less than 500 mm/min. The method can be applied to the on-line automatic welding deviation detection.展开更多
为研究冷金属过渡(cold metal transition,CMT)电弧增材制造铝合金传热传质与熔池流动特性,基于Fluent软件建立了三维CMT电弧增材制造数值模型.模型中,采用动网格技术模拟焊丝竖直方向上的往复运动,利用流体体积法捕获气/液界面,焓-孔...为研究冷金属过渡(cold metal transition,CMT)电弧增材制造铝合金传热传质与熔池流动特性,基于Fluent软件建立了三维CMT电弧增材制造数值模型.模型中,采用动网格技术模拟焊丝竖直方向上的往复运动,利用流体体积法捕获气/液界面,焓-孔隙率法追踪固/液界面,并施加周期热量输入和阶段电弧力作用来等效电弧放电行为,研究分析了焊道成形传热传质过程与熔池动态行为.结果表明,焊道成形初期,熔池余高和坡度较大,形貌犹如半个球体,成形后期热量积累造成焊道余高后方较前方略小,而后端熔宽较前端略宽;单滴过渡周期内,焊丝机械回抽对熔池表面流动影响最为明显,液桥断裂产生较大反冲作用于熔池;熔池内部则是电磁力作为主导驱动力产生一股顺时针环流,环流随燃弧阶段周期切换而不断加强与减弱,并基本贯穿整个过渡周期,使得熔池内部热对流更加充分.模拟结果与试验结果显示吻合良好.展开更多
The metal transfer mode of electron beam welding （EBW） with filler wire was studied experimentally. The spatial position between the electron beam and the filler wire was defined. Basing on the charge coupled device...The metal transfer mode of electron beam welding （EBW） with filler wire was studied experimentally. The spatial position between the electron beam and the filler wire was defined. Basing on the charge coupled device （CCD） visual sensing system, the metal transfer mode of filler wire was investigated. The results showed that there were five transfer modes during EBW process due to different wire feed rates and spatial positions between beam and filler wire, such as short-circuiting mode, molten metal bridge mode, small droplet mode, big droplet mode and mixed mode. By comparing the weld appearance of different transfer modes, the molten metal bridge transfer was proved to be the best transfer mode.展开更多
通过对管道全位置熔化极气体保护焊(gas metal arc welding,GMAW)熔池图像的研究分析,发现并验证了其根焊熔池图像尖端与焊缝坡口中心位置重合的现象,依据此规律性特征,提出了一种基于熔池图像尖端信息的焊接偏差测定方法.该方法的基本...通过对管道全位置熔化极气体保护焊(gas metal arc welding,GMAW)熔池图像的研究分析,发现并验证了其根焊熔池图像尖端与焊缝坡口中心位置重合的现象,依据此规律性特征,提出了一种基于熔池图像尖端信息的焊接偏差测定方法.该方法的基本原理是,在对焊接过程熔池CCD图像进行中值滤波、小波变换、连通区域分割等图像处理后,以搜索算法测得的根焊熔池图像尖端位置信息作为焊缝坡口中心位置的坐标值,此值与焊丝中心坐标值之差即为焊接偏差量.试验证明,此方法能从根焊熔池图像中实时测定焊接偏差量,为实现机器人自动焊缝跟踪控制提供了可靠依据.展开更多
在熔化极气体保护焊(gas metal welding,GMAW)焊接过程中,由于弧光干扰严重,视觉系统难以同时准确提取焊缝和焊丝尖端,从而影响焊缝跟踪的精度.针对这个问题,提出一种定位焊枪中心来替代定位焊丝尖端的焊接偏差测定方法,并对该方法进行...在熔化极气体保护焊(gas metal welding,GMAW)焊接过程中,由于弧光干扰严重,视觉系统难以同时准确提取焊缝和焊丝尖端,从而影响焊缝跟踪的精度.针对这个问题,提出一种定位焊枪中心来替代定位焊丝尖端的焊接偏差测定方法,并对该方法进行了可行性论证.首先,在增强熔池图像中的焊缝、焊枪边缘轮廓信息后,设置矩形窗获得边缘采样点.然后,使用聚类算法筛选出正确的边缘采样点,根据采样点利用最小二乘法拟合出焊缝直线和焊枪椭圆方程.最后,计算当前图像焊枪中心与焊缝直线的距离,与基准图像中的对应距离进行比较,测定出焊枪位置偏差量和焊枪摆幅偏差量.实际验证结果表明,焊枪中心与焊丝尖端的替代误差在0.2 mm以内,满足跟踪精度要求,具有较强的工程实际意义.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51275051,51505035)National Hi-tech Research and Development Program of China(863 Program,Grant No.2009AA04Z208)Beijing Education Commission Innovation Ability Upgrade Program of China(Grant No.TJSHG201510017023)
文摘The welding deviation detection is the basis of robotic tracking welding, but the on-line real-time measurement of welding deviation is still not well solved by the existing methods. There is plenty of information in the gas metal arc welding（GMAW） molten pool images that is very important for the control of welding seam tracking. The physical meaning for the curvature extremum of molten pool contour is revealed by researching the molten pool images, that is, the deviation information points of welding wire center and the molten tip center are the maxima and the local maxima of the contour curvature, and the horizontal welding deviation is the position difference of these two extremum points. A new method of weld deviation detection is presented, including the process of preprocessing molten pool images, extracting and segmenting the contours, obtaining the contour extremum points, and calculating the welding deviation, etc. Extracting the contours is the premise, segmenting the contour lines is the foundation, and obtaining the contour extremum points is the key. The contour images can be extracted with the method of discrete dyadic wavelet transform, which is divided into two sub contours including welding wire and molten tip separately. The curvature value of each point of the two sub contour lines is calculated based on the approximate curvature formula of multi-points for plane curve, and the two points of the curvature extremum are the characteristics needed for the welding deviation calculation. The results of the tests and analyses show that the maximum error of the obtained on-line welding deviation is 2 pixels（0.16 ram）, and the algorithm is stable enough to meet the requirements of the pipeline in real-time control at a speed of less than 500 mm/min. The method can be applied to the on-line automatic welding deviation detection.
文摘为研究冷金属过渡(cold metal transition,CMT)电弧增材制造铝合金传热传质与熔池流动特性,基于Fluent软件建立了三维CMT电弧增材制造数值模型.模型中,采用动网格技术模拟焊丝竖直方向上的往复运动,利用流体体积法捕获气/液界面,焓-孔隙率法追踪固/液界面,并施加周期热量输入和阶段电弧力作用来等效电弧放电行为,研究分析了焊道成形传热传质过程与熔池动态行为.结果表明,焊道成形初期,熔池余高和坡度较大,形貌犹如半个球体,成形后期热量积累造成焊道余高后方较前方略小,而后端熔宽较前端略宽;单滴过渡周期内,焊丝机械回抽对熔池表面流动影响最为明显,液桥断裂产生较大反冲作用于熔池;熔池内部则是电磁力作为主导驱动力产生一股顺时针环流,环流随燃弧阶段周期切换而不断加强与减弱,并基本贯穿整个过渡周期,使得熔池内部热对流更加充分.模拟结果与试验结果显示吻合良好.
文摘The metal transfer mode of electron beam welding （EBW） with filler wire was studied experimentally. The spatial position between the electron beam and the filler wire was defined. Basing on the charge coupled device （CCD） visual sensing system, the metal transfer mode of filler wire was investigated. The results showed that there were five transfer modes during EBW process due to different wire feed rates and spatial positions between beam and filler wire, such as short-circuiting mode, molten metal bridge mode, small droplet mode, big droplet mode and mixed mode. By comparing the weld appearance of different transfer modes, the molten metal bridge transfer was proved to be the best transfer mode.
文摘基于电子束焊接过程的传热与受力物理过程分析,建立相应模型,对电子束定点焊接304不锈钢的温度场与流场进行数值模拟,研究电子束焊接熔池流动行为及焊缝成形规律.结果表明,电子束加热阶段,熔池上表面温度梯度达到106K/m,熔池表面峰值温度高,在沸点温度附近波动,强烈的金属蒸汽反作用力成为熔池流动的主要作用力,促使熔池中心下凹并不断波动,熔池冷却凝固阶段,金属蒸汽反作用力下降,熔池金属表面张力梯度引起的Marangoni对流成为熔池金属流动主要驱动力,促使焊缝表面熔宽增大,熔池凝固后焊缝上表面宽度为1.9 mm,中心处宽度为1.6 mm,下表面宽度为1.8 mm.
文摘通过对管道全位置熔化极气体保护焊(gas metal arc welding,GMAW)熔池图像的研究分析,发现并验证了其根焊熔池图像尖端与焊缝坡口中心位置重合的现象,依据此规律性特征,提出了一种基于熔池图像尖端信息的焊接偏差测定方法.该方法的基本原理是,在对焊接过程熔池CCD图像进行中值滤波、小波变换、连通区域分割等图像处理后,以搜索算法测得的根焊熔池图像尖端位置信息作为焊缝坡口中心位置的坐标值,此值与焊丝中心坐标值之差即为焊接偏差量.试验证明,此方法能从根焊熔池图像中实时测定焊接偏差量,为实现机器人自动焊缝跟踪控制提供了可靠依据.
文摘在熔化极气体保护焊(gas metal welding,GMAW)焊接过程中,由于弧光干扰严重,视觉系统难以同时准确提取焊缝和焊丝尖端,从而影响焊缝跟踪的精度.针对这个问题,提出一种定位焊枪中心来替代定位焊丝尖端的焊接偏差测定方法,并对该方法进行了可行性论证.首先,在增强熔池图像中的焊缝、焊枪边缘轮廓信息后,设置矩形窗获得边缘采样点.然后,使用聚类算法筛选出正确的边缘采样点,根据采样点利用最小二乘法拟合出焊缝直线和焊枪椭圆方程.最后,计算当前图像焊枪中心与焊缝直线的距离,与基准图像中的对应距离进行比较,测定出焊枪位置偏差量和焊枪摆幅偏差量.实际验证结果表明,焊枪中心与焊丝尖端的替代误差在0.2 mm以内,满足跟踪精度要求,具有较强的工程实际意义.
