基于视觉跟踪的大型容器焊接机器人的研制

研制了一种基于 CCD视觉焊接轨迹跟踪技术的无导轨焊接机器人。该机器人由新颖的 CCD视觉传感器来实时检测机器人行走机构与焊枪的跟踪位置偏差量 ,并据此由微机控制系统实现对机器人行走机构与焊枪的二级自动跟踪。该机器人采用永磁式柔性磁轮机构作为支持行走单元 ,使焊接机器人具有了节省导轨、轨线适应性强的优点。焊接工艺评定试验结果表明 ,此焊接机器人自动跟踪精度高 ,焊缝质量好 ,工作稳定可靠。     

基于DSP的焊缝自动跟踪控制系统设计

设计了一种基于DSP的用于球罐全位置多层焊自动跟踪的控制系统，对其工作原理、控制系统的硬件设计和软件程序设计等要点进行了阐述。该系统应用于球罐全位置多层自动焊接机器人中，实现了无导轨自动焊接全位置焊缝与多层多道焊接的自动跟踪。焊接工艺试验结果表明，焊接机器人自动跟踪精度高、焊缝质量好、工作稳定可靠。     

基于机器视觉的焊接轨迹跟踪技术

本文针对海上风电装备高焊接质量和可靠性要求,提出了基于机器视觉的焊接轨迹跟踪技术,本方案主要由五部分组成:视觉传感系统、焊接机器人、控制系统、送丝系统、图像处理系统,其中视觉传感器系统是整个焊缝跟踪系统的核心部分,包括工业CCD摄像机、激光发生器和窄带通滤光片三个重要元件,通过对比实验确定了视觉传感器与工件、焊枪之间的位置关系,并设计了视觉传感器夹具,对工业CCD摄像机标定,结果表明:本文所依托项目采集的图像质量较优,满足焊缝跟踪的图像处理需求,图像处理算法能有效地凸显焊缝图像中激光带信息和去除无关信息,实现强干扰复杂环境下焊缝特征点的准确识别。     

狭小空间直角角焊缝移动焊接机器人系统研制

针对大型结构件中狭小空间角焊缝焊接,提出了一种基于旋转电弧传感的新型移动焊接机器人系统。系统包括轮式移动本体、二维运动平台、旋转电弧传感器和超声传感器;系统采用二级跟踪策略——机器人本体粗跟踪和二维运动平台精确跟踪,采用旋转电弧传感器作为焊缝跟踪传感器,采用超声传感器作为避障传感器;建立了运动学模型,设计了参数自调整模糊控制器。实验表明该机器人系统能实现小空间中大折角角焊缝的自动焊接。     

旋转电弧传感器的研制

介绍了电弧传感的基本原理及旋转电弧传感器用于焊接接头跟踪的工作原理。针对焊缝跟踪对传感器的要求，研制了一种适用于焊接机器人的轻便、紧凑、高速旋转的电弧传感器。详细介绍了高速旋转电弧传感器的旋转驱动电路、位置检测电路以及焊接电流采样电路。实验证明所设计的电路抗干扰能力强，旋转速度稳定，测位脉冲可靠，焊接电流的采集线性度好。该电弧传感器已在焊接机器人焊缝跟踪控制系统中得到成功应用。     

电弧传感技术在焊缝跟踪中的应用

正焊缝跟踪的实质就是使焊接电弧对准焊接位置从而保证焊接接头成形和焊接质量,它通过传感器检测电弧偏离焊缝的信息,并经自动控制系统调节电弧与焊缝的相对位置,使偏离减小,直到消失。因此一套结构简单、工作可靠、灵敏度高的焊缝跟踪传感器,对于高度自动化的焊接机器人至关重要。     

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。     

深度视觉技术在焊接轨迹识别中的研究综述

机器视觉在机器人自动焊接领域得到广泛应用。图像识别可以对不同的焊接对象进行有效识别,而识别及跟踪焊缝轨迹是实现自动焊缝的关键问题。分析了焊接轨迹跟踪传感器的发展历程,讨论了视觉传感器在焊缝识别跟踪上的应用,对焊缝图像处理方法进行了分析,总结了视觉焊缝跟踪技术现状。分析结果表明,TOF相机更适合于焊缝跟踪应用,研究鲁棒性强的图像去噪方法和基于深度学习的焊缝图像分割方法是未来的发展方向,同时提出了稳定性好、精度高,效率好的深度视觉焊缝跟踪控制系统思路。     

基于图像处理的焊缝实时跟踪技术研究

为了提高焊接产品质量及生产效率,改善工人恶劣的劳动条件,运用视觉传感器采集焊缝图像,实时传送至计算机中进行图像处理。提出了焊缝实时跟踪系统的原理,设计了合理的焊接机构。选用ABB IRB1410弧焊机器人,用RobotStudio软件建立了机器人焊接工作站。通过灰度线性拉伸法处理图像后,焊缝轮廓清晰,对比度明显提高。利用图像骨架法准确提取到焊缝中心线,设计了焊缝实时处理系统,可以快速地处理图像。在机器人焊接时,控制焊枪始终与焊缝中心对齐,即可以实现焊缝实时跟踪焊接。实验结果表明,得到的图像处理流程可靠,方法准确且适应性强,设计的焊缝实时跟踪系统应用广泛。     

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。     

The acquisition and processing of real-time information for height tracking of robotic GTAW process by arc sensor

Aiming at the deficiencies of the vision technology that canot be used in the height tracking of the 3D weld seam during teaching-playback robot gas tungsten argon welding (GTAW) process, this paper designed a set of arc sensor system for height tracking of weld seam, which can effectively acquire arc voltage signals. The characteristic values of arc voltage signals are extracted and a linear relational model between arc voltage and arc length was established by using appropriate denoising algorithm. The experimental results demonstrate that the error between the arc length calculated by linear model and the real arc length was very small, which is accurate enough to meet the requirements of the follow-up height tracking and controlling during the welding robot GTAW process.     

Robot welding seam tracking method based on passive vision for thin plate closed-gap butt welding

A passive vision sensor is added to a teaching and playback welding robot for pulsed gas tungsten arc welding, which is normally used in the welding of thin plate closed-gap butts. This paper presents a seam tracking method based on this sensor through period visual measurement of the offset between the torch and the seam center. A robust image processing algorithm is developed to extract the seam center. A kind of ARX(auto-regressive with exogenous input) model is studied to describe the relationship between the rectifying voltage and the offset. The fuzzy PID(proportional-integral-derivative) seam tracking controller is analyzed and designed in consideration of various offsets based on the ARX model. The experimental results on straight line weld display a good seam tracking capability of the proposed method.     

AUTOMATIC SEAM TRACKING SYSTEM OF SUBMERGED ARC WELDING BASED ON FUZZY-P CONTROLLER

An automatic seam tracking system used in submerged arc welding is presented. In the system, the linear CCD vision sensor is installed in front of the welding torch. Laser structure light emitted by the semiconductor laser irradiates on a slant to work-piece surface and forms a structure light strip on work-piece surface. Scatter light of the strip is received by linear CCD on top of the seam and the image information of seam can be obtained. By way of image processing and applying Fuzzy-P controller in tracking process, automatic seam tracking has been realized accurately. Anti-disturbing ability of the system to work-piece surface status has been enhanced largely by classified microadjus-tment of torch height.     

基于图像处理的爬壁机器人焊缝识别与跟踪

基于爬壁机器人移动平台和单目相机的图像采集系统,设计了一种焊后焊缝图像处理方法,将改进的自适应中值滤波算法与灰度形态学方法结合,实现从信噪比较高的图像中提取特征。采用基于边缘检测和Hough变换的焊缝位置提取算法,经测试识别准确率达70%,且单幅图像平均处理时间为200ms,能满足管道爬壁机器人行进过程中的实时焊缝跟踪,并提供了一种引导机器人沿焊缝前进的自主定向方案。     

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.     

基于旋转电弧的机器人角焊缝跟踪建模及仿真

通过对现有旋转电弧传感器采集的焊缝偏差信息和六自由度焊接机器人运动学模型进行研究,结合曲线角焊缝的特点,推导出纠正焊缝偏差后的焊接机器人工具坐标系相对于原工具坐标系的变换矩阵。在此基础上,结合焊接机器人的运动学反解,建立了曲线角焊缝跟踪及焊枪姿态调整模型。输入给定左右偏差及高低偏差信号,利用MATLAB对模型进行仿真验证,结果证明了该模型的有效性与正确性,从而为旋转电弧传感应用于焊接机器人及设计其焊缝跟踪系统提供了理论参考。     

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.