Arc welding robot system with seam tracking and weld pool control based on passive vision

The automatic control in square-wave alternating current (AC) gas tungsten arc welding (GTAW) is significant for a “teach and playback” robot to overcome the variation of the seam trajectory and the seam gap in the welding process. This paper presents a welding robot system based on the real-time visual measurement in the different levels of the welding current. The primary objective is to measure the offset of the torch to the seam center and the size of seam gap by passive vision, track the seam and control the weld pool in real time. A novel visual image analysis algorithm was developed for seam tracking and seam gap measuring, free from robot calibration. The control algorithm based on the knowledge base was established to control the weld formation by regulating the welding current and wire feed rate. The welding practice for the rocket storage tank demonstrates the efficiency of the proposed system.     

基于手眼系统的线结构光焊缝跟踪系统设计

为了实现一般手眼系统与线结构光焊缝跟踪系统主要部件的复用,在一般手眼系统的基础上,加装激光器、滤光片、保护装置等设备,将其用作焊缝跟踪系统中的线激光结构光焊缝跟踪传感器。通过实验对原手眼系统的标定结果进行实验修正,使其可以替代线结构光焊缝跟踪传感器的标定。详细分析了安装激光器、滤光片、保护装置等对原手眼标定结果造成的影响,使用数据逼近的方法提高线激光结构光焊缝跟踪传感器的手眼标定精度;实验时先对手眼系统进行标定,得到相机坐标系到工具坐标系的原外参矩阵;再对使用原外参矩阵得到的焊点数据,与焊点的实际坐标的误差进行分析,修正手眼系统标定结果。通过实验验证了本方法在手眼系统标定结果基础上,进行加装机构后的线结构光焊缝跟踪传感器的手眼标定的平均精度可达0.53 mm,能够满足机器人焊接的需求。     

Passive vision based seam tracking system for pulse-MAG welding

Welding robots have been widely used in manufacturing process to substitute for human welders. However, most of them are rigid and cannot adjust to variations in the weld seam positions caused by natural welding environmental factors. To address this problem, this paper presents a passive vision-based robotic welding system, which can realize the seam tracking function for pulse-MAG welding. In this paper, the light spectrum of the welding process is analyzed to determine the optical filters used during the image capture. Then, a robust image processing method is proposed to extract the offset from the image which contains much noise. The transformation formula is calibrated to obtain the relationship between the image coordinate system and the robot coordinate system. The tracking strategy is designed to improve the tracking precision and the stability of the welding process. Finally, experiments are conducted on straight line and curved line seam to verify the feasibility of the developed system.     

A seam-tracking laser welding platform with 3D and 2D visual information fusion vision sensor system

In this paper, a laser welding experimental platform for narrow and burred seam welding (with seam width less than 0.1 mm) of complex three-dimensional (3D) surface based on eight-axis machine tool is introduced. A novel vision sensor system (which is named as HUST-SM) which based on visual information fusion of 3D and two-dimensional for detecting the narrow and burrs welding seam is also presented. Several experimental tests are applied to verify the features of this platform and the HUST-SM vision sensor system. Experimental results show that the vision sensor system has high precision and resolution for obtaining narrow seam information. The narrow seam of space curve welding tests demonstrates that the narrow seam welding can achieve high finish quality.     

A visual seam tracking system for robotic arc welding

A novel circular laser three-dimensional (3D) scanner is developed instead of a one-dimensional laser spot scanner (1D) and two-dimensional (2D) striped laser light. Using the proposed circular laser scanner, a seam tracking system is constructed, and architecture based on the Visual C++ and RAPID languages which determines the cooperation among image processing modules is carried out. Finally, real seam tracking experiments are investigated and the error analysis is carried out. The results show that: (1) the proposed system can realize seam tracking; (2) the precision of this system is affected by the light scanning system, calibration results, image processing, and the welding seam 3D algorithm—the tracking accuracy is satisfied for robotic arc welding; (3) this system can be used in a welding robot system as a weld seam finder, flatness detector, and weld seam tracker.     

Autonomous seam acquisition and tracking system for multi-pass welding based on vision sensor

Automatic welding technology is a solution to increase welding productivity and improve welding quality, especially in thick plate welding. In order to obtain high-quality multi-pass welds, it is necessary to maintain a stable welding bead in each pass. In the multi-pass welding, it is difficult to obtain a stable weld bead by using a traditional teaching and playback arc welding robot. To overcome these traditional limitations, an automatic welding tracking system of arc welding robot is proposed for multi-pass welding. The developed system includes an image acquisition module, an image processing module, a tracking control unit, and their software interfaces. The vision sensor, which includes a CCD camera, is mounted on the welding torch. In order to minimize the inevitable misalignment between the center line of welding seam and the welding torch for each welding pass, a robust algorithm of welding image processing is proposed, which was proved to be suitable for the root pass, filling passes, and the cap passes. In order to accurately track the welding seam, a Fuzzy-P controller is designed to control the arc welding robot to adjust the torch. The Microsoft Visual C++6.0 software is used to develop the application programs and user interface. The welding experiments are carried out to verify the validity of the multi-pass welding tracking system.     

基于旋转电弧轮式焊接机器人运动学建模及仿真

旋转电弧轮式焊接机器人的焊炬执行机构由十字滑块和小车左右差速驱动轮两个运动单元构成。针对其机构设计的稳定性以及可控性等问题,根据运动特点推导出焊炬的运动学模型,由旋转电弧焊缝跟踪原理应用Matlab/Simulink进行焊缝跟踪仿真,实现了机构设计以及控制方法对焊缝跟踪的影响。仿真结果证明了该模型的有效性和正确性,为旋转电弧移焊接机器人的机构设计、稳定性分析以及控制器设计提供了理论依据。     

视觉传感铜包铝线缆TIG焊缝自动跟踪系统

针对铜包铝线缆TIG焊常出现焊偏的问题,研制一种采用视频摄像传感器的焊缝自动跟踪系统。以弧光为主动光源,在电弧前方20 mm处对铜皮对口缝进行摄像。采用模拟电路对视频信号进行放大、整形和以动态平均值为基准的二值化等处理,极大降低了信号处理的时间,并准确获得铜皮对口缝的脉冲信号。确定铜皮对口缝偏差方向判断及偏差大小计算的方法。试验结果表明,该焊接过程采用视频摄像传感器识别铜皮对口缝方法是可行的,能实现铜包铝线缆TIG焊的焊缝自动跟踪控制,系统响应周期小于60 ms,跟踪精度小于0.1 mm。     

焊接过程控制电弧传感方法的研究

根据熔化极体气保护电弧焊的电弧自身特性提出了一种电弧传感方法。它可以检测坡口或焊接接头的断面形状,进而能测量接头中心位置,从而实现了电弧传感式的焊缝跟踪控制。由于采用电弧传感,因而此方法简洁,设备简单,成本低且工作可靠,对于推广应用极为有意义。由计算机控制焊枪摆动,可实现可编程的多种摆动模式的控制。研究中还推导出电弧传感方法的数学模型,它提示了电弧传感的基本原理,也为采用此方法的控制算法的研究与应用提供了理论依据。     

焊缝跟踪应用的线激光视觉伺服控制系统

设计了一套由三轴直角坐标机器人、线激光传感器和工业计算机组成的焊缝跟踪系统。研究了该系统所涉及的测量原理、特征点测量方法和基于模糊自适应的控制方法。通过高斯核相关算法(KCF)在焊接过程中实时检测焊缝特征点,并根据测量原理计算获得特征点相对于相机坐标系的三维坐标值。设计了一种自适应模糊控制器,通过自适应模糊控制器计算坐标的偏差值和偏差变化率得到焊枪末端运动轨迹的控制量,同时对模糊控制器的输入输出论域、模糊规则和隶属函数进行实时动态更新。实施了焊缝跟踪实验。结果显示:采用最大焊接电流为350 A的惰性气体保护焊(MIG),在强烈弧光和飞溅的干扰下,该系统能实时跟踪焊接工件,跟踪精度为0.325 3mm,传感器测量频率为20Hz。焊接过程中焊枪末端运行平稳,焊缝轨迹跟踪准确,且抗干扰能力,能满足焊接应用要求。     

基于视觉传感的焊缝跟踪控制系统

介绍了传感器在焊接生产中的应用和视觉传感原理。分析了视觉传感焊缝跟踪系统的原理和特点。提出焊缝图像特征提取方法和流程，以及实施焊缝跟踪控制的方法。系统采用条形光传感方法，选用CCD等光学器件组成焊缝图像传感系统，然后将获取的焊缝图形信息进行识别处理，获得焊接电弧与焊缝中心是否偏离、偏离方向和偏离程度的处理结果。根据这一结果，调整电孤与焊缝中心的相对位置，消除电弧与焊缝的偏离，达到焊接电弧准确跟踪焊缝的目的。     

一种用于球罐焊接机器人焊缝实时跟踪的线阵CCD传感器

根据球罐焊接机器人焊缝跟踪的要求和特点,设计了一种基于线阵CCD的视觉传感器。传感器所用线阵CCD的分辨率高,光电处理系统均由硬件实现。传感器与焊接机器人组成的焊缝跟踪系统焊缝偏差检测精度好、实时性好,并且可以避免焊接时弧光的干扰,能够满足球罐制造时多层多道焊接焊缝跟踪的工艺要求。     

一种适合焊接专机的激光焊缝跟踪应用

为确保焊接过程中焊枪始终沿焊缝运动,提升焊接质量,采用基于主动视觉传感技术的新一代激光视觉传感器实时采集焊缝轮廓的图像,由传感器控制柜按在PC界面上选定的算法进行图像处理与特征识别,提取焊缝跟踪点的位置坐标,并根据标定的参考位置和预设的比例关系转化为模拟电压量输出,进而驱动十字滑台上的伺服电机带动焊枪做出相应的纠偏动作。可编程逻辑控制器(PLC)被用来实现焊枪初始定位、滑台的手动控制与自动跟踪模式切换、安全互锁等功能。最终建立了一套适用于焊接专机的焊缝自动跟踪应用系统。实验结果表明,该系统安全实用,具备了良好的实时跟踪能力。     

Visual Tracking System for Welding Seams

To track the narrow butt welding seams in container manufacture, a visual tracking system based on smart camera is proposed in this paper. A smart camera is used as the sensor to detect the welding seam. The feature extraction algorithm is designed with the consideration of the characteristics of the smart camera, which is used to compute the error between the welding torch and the welding seam. Visual control system based on image is presented, which employs a programmable controller to control a stepper motor to eliminate the tracking error detected by the smart camera. Experiments are conducted to demonstrate the effectiveness of the vision system.     

集装箱大梁熔化极气体保护电弧焊的焊缝跟踪系统

集装箱大梁自动焊接过程中,工件表面的反射不均匀、弧光、飞溅和烟尘等因素容易造成焊缝偏差识别不准确或难以稳定识别,因此设计了一种用于集装箱大梁熔化极气体保护电弧焊的焊缝跟踪系统。基于低成本结构光视觉传感器建立了高鲁棒的焊缝特征提取模型,该模型采用激光条纹的直线斜率对随机采样一致性算法的随机采样过程进行优化,以在复杂环境下实现模型对焊缝特征的稳定提取。不均匀强反射工件表面的焊接试验结果表明：焊接参数300 A、29 V、1 m/min下,Y向、Z向的平均检测误差分别为0.22 mm和0.19 mm,实现了稳定高精度的焊缝跟踪。     

一种智能型焊缝跟踪系统的研制

论述一种智能型焊缝跟踪系统,采用直接拍摄电弧式视觉传感器检测焊缝跟踪偏差,并通过一个自调整模糊控制器实现偏差的调节。整个跟踪过程可通过屏幕实时观察,所有的参数设置都通过人机对话实现。此外,还提出了一种新的焊缝图像处理方法来实时检测焊缝。试验表明,该系统能够对GTAW对接焊缝实现精确的跟踪。     

基于旋转电弧传感的弧焊机器人焊缝跟踪系统

研制了一套基于旋转电弧传感的弧焊机器人空间曲线焊缝智能跟踪控制系统。介绍了系统的硬件构成、软件设计及模糊控制方法。研究了不同焊接位置时，焊接熔池金属对坡口的影响作用，提出采用补偿因子加权处理方法，可有效提高平焊、横焊位置焊缝偏差的识别能力。针对立焊位置的脉冲焊接方法，采用形态滤波技术，通过提取脉冲焊接电流的上包络线，利用一次谐波法准确地对立焊焊缝进行了识别。试验结果表明，该焊缝跟踪控制系统对平焊、横焊及立焊位置的曲线焊缝跟踪效果良好，达到焊接工艺要求。     

Detection of micro gap weld using magneto-optical imaging during laser welding

Accurate seam tracking plays a critical role in acquisition of good weld. During laser butt joint welding, the laser beam focus must be controlled to follow the weld trajectory. The key problem to be solved is the automatic identification of weld position. An approach to detect the micro gap weld (gap width is less than 0.05 mm) based on magneto-optical imaging (MOI) is proposed. The laser butt joint welding of carbon steel was carried out. A magnetic excitation device was used to magnetize the weldment, and it was found that magnetic field distribution at the weld was different from other regions. The magnetized weldment was detected by using a magneto-optical sensor, and magneto-optical images of the weld were captured. By analyzing and processing weld MO images with low contrast and strong magnetic field noises, the weld center position could be detected accurately. Weld MO images at different laser welding speeds were investigated to analyze the varieties of image characteristics. Experimental results indicated that the magneto-optical imaging technique could be applied to detect the micro gap weld accurately, which provides a novel approach for automatic identification and tracking of micro gap weld during laser welding.     

视觉传感螺旋钢管埋弧焊内焊焊缝自动跟踪系统

针对螺旋钢管埋弧焊内焊,研制一种基于视觉传感的焊缝自动跟踪系统。以视频摄像机为传感器,在焊接点前方300 mm处检测递送边钝边棱边。对视频信号进行放大、整形和二值化处理,获得对应于钝边棱边的脉冲信号,以帧中心为基准,利用单片机进行偏离方向判断及偏差值计算,并将偏差信号以脉冲方式送入交流伺服电动机驱动器,由交流伺服电动机控制焊枪滑移台移动,确保焊丝实时对准焊缝。试验结果表明：采用视频摄像机识别钝边棱边实现焊缝自动跟踪的方法是可行的。系统响应周期小于50 ms,跟踪精度达±0.3 mm。     

A vision-based algorithm for seam detection in a PAW process for large-diameter stainless steel pipes

Manual monitoring and seam tracking through welding images in real-time, by naked eye or industrial TV are experience-dependant, subjective, labor-intensive, and sometimes biased. So it is necessary to realize computer-aided seam tracking. We have developed a plasma arc welding (PAW) seam-tracking system, which senses the molten and the seam in a frame using a vision sensor, and then detects the seam deviation to adjust the work piece motion adaptively to the seam position sensed by the vision sensor with our collaborator. In this paper, we propose a novel molten pool area image-processing algorithm based on machine vision. The algorithm processes each image at a speed of 20 frames/s in real-time to extract three feature variables to get the seam deviation. It is proved experimentally that the algorithm is very fast and effective. Issues related to the algorithm are also discussed.