图像处理在焊缝跟踪中的应用研究

随着焊接过程自动化和智能化的发展,基于图像处理技术的焊缝位置检测和焊接缺陷检测过程越来越受到国内外学者的重视.本文对焊缝自动跟踪系统中有关图像处理方面的内容作了分析.详细分析了图像处理技术在焊缝跟踪过程中的应用,其中包括图像预处理,边缘检测和特征点提取等图像处理过程;并对当前焊缝跟踪中的图像处理技术存在的问题和解决方法作了一些总结和分析,最后对其应用前景作了展望.     

焊缝图像处理与焊缝中心的提取

随着焊接过程自动化和智能化的发展,图像处理技术越来越受到国内外学者的重视,它在焊缝自动跟踪系统中也有广泛的应用.本文介绍了图像处理的基本过程,其中包括图像预处理,图像分割,边缘检测和特征点提取等图像处理过程,总结了一些传统和新型的图像处理算法,并着重分析了焊缝中心提取的几种方法,提出了一种求取平均值的简单有效的方法.     

焊缝图像处理与焊缝中心的提取

随着焊接过程自动化和智能化的发展，图像处理技术越来越受到国内外学者的重视，它在焊缝自动跟踪系统中也有广泛的应用。本文介绍了图像处理的基本过程，其中包括图像预处理，图像分割，边缘检测和特征点提取等图像处理过程，总结了一些传统和新型的图像处理算法，并着重分析了焊缝中心提取的几种方法，提出了一种求取平均值的简单有效的方法。     

焊缝图像处理技术在激光拼焊中的应用

基于拼板激光焊接工程中的视觉跟踪系统,应用相关图像处理技术,建立了一种焊缝跟踪的图像处理流程模型,并通过实验验证了该模型的正确性.     

基于概率连续模型的激光视觉焊缝自动跟踪

针对目前在实际焊接过程中多数焊缝自动跟踪系统对飞溅、弧光等噪声干扰十分敏感,从而造成焊接精度损失的问题,设计了能够实时检测焊缝特征图像的线激光视觉传感器,并根据其几何模型建立了精确的测量模型。跟踪过程中以线性表示模型对观测矢量进行建模并利用仿射变换模型对焊缝运动进行描述,提出了基于概率连续模型的焊缝跟踪算法。充分利用图像中激光条纹和背景噪声的空间一致性,结合刻画邻域结构内像素点间相互关系的一阶马尔可夫随机场理论,推导出焊缝跟踪问题的目标函数。采用基于最小二乘法与最大流/最小割的迭代算法对其进行求解,最终获取准确的焊缝位置。搭建了焊缝跟踪试验平台,并在实际焊接环境中应用所提算法进行焊缝跟踪试验。试验结果表明该算法的跟踪精度达?0.109 1 mm,平均每帧图像处理时间不长于45 ms,并且激光条纹与焊接熔池的最小距离可达24 mm,能够克服强烈噪声干扰,实现实时、准确的焊缝跟踪。     

基于区域生长算法激光深熔焊监测图像处理研究

根据同轴监测系统采集到的熔池和小孔的同轴视觉传感原始图像特点,分析了数字图像处理的方法并提出相应图像处理的流程。通过监测沿垂直速度方向熔池灰度分布实现了对熔宽的监测,通过对小孔顶部和底部尺寸的监测实现对熔透状态的监测。经过图像处理后的焊接区域同轴监测图像可以清晰的获得熔池轮廓及小孔尺寸,为实现焊接过程中熔池宽度和小孔的穿透状态的监测做准备。针对激光对接焊,提出焊缝跟踪的处理算法,不仅实现了焊接质量包括熔宽与熔透状态的监测,还实现焊接质量与焊缝跟踪一体化监测。     

视觉激光焊在汽车制造业中的应用研究

激光焊接技术具有精度高、效率高、焊接成本低等优势,是汽车制造业中主要的加工技术之一。随着计算机技术的发展,图像处理的速度与精度等都有了长足的进步,可以满足机械加工工艺的要求,而机器视觉激光焊接技术符合柔性化生产、个性化定制的发展趋势,因此基于视觉控制与视觉伺服的激光焊接技术是今后的发展方向之一。本文主要对机器人视觉激光焊接系统的组成进行了概述,分析了视觉激光焊接的关键技术,如:焊接机器人、图像处理技术、焊接工件位姿误差检测、焊缝(焊点)轨迹跟踪控制、自适应控制、焊缝缺陷检测等;介绍了视觉激光焊接机器人在汽车制造业中的应用实例,并展望了视觉激光焊接技术的发展趋势。     

客车底盘骨架对接焊缝的视觉跟踪系统

根据客车底盘骨架对接焊缝的特点,设计了基于激光视觉传感的焊缝跟踪系统。针对图像处理运算量大的特点,为减少图像处理时间,提出了加窗处理算法。视觉传感系统采集并分析焊缝图像得出焊缝偏差,控制系统根据焊缝偏差指导机器人移动焊枪进行实时纠偏控制。实验结果表明,所设计的焊缝跟踪系统满足焊缝跟踪的精度要求,可以用于底盘骨架的焊接。     

基于多帧图像焊缝缺陷轨迹跟踪的X射线实时检测技术

正基于X射线实时成像的焊缝缺陷在线检测是重要焊接结构连续生产过程中的关键环节,而动态图像处理技术是实现在线自动检测的关键。对于高噪声焊缝X射线实时图像,采用单帧图像处理算法无法克服缺陷误检与漏检之间的矛盾,需要研究多帧关联的图像处理方法。目前该领域已有的X射线多帧实时动态图像处理主要采用图像匹配方法或帧间缺陷匹配方法,前者在进行相关度计算时实时性较差,后者对低对比度缺陷容易产生漏检。另外,现有的焊缝缺陷检测图像处理算法对     

应用形态学运算的焊缝X射线图像处理研究

应用数学形态学方法对钢管焊缝X射线检测的图像处理进行了详细地分析研究,通过对钢管焊缝检测灰度图像的去噪、增强和分割处理的实例,讨论了灰度形态学图像处理的方法及其在焊缝射线检测中的应用。实验结果证明了处理方法及其技术实现的实用性和可行性。     

Real-time image processing for vision-based weld seam tracking in robotic GMAW

Image capturing and processing is important in using vision sensor to effectively track the weld seam and control the weld quality in robotic gas metal arc welding (GMAW). Using vision techniques to track weld seam, the key is to acquire clear weld images and process them accurately. In this paper, a method for real-time image capturing and processing is presented for the application in robotic seam tracking. By analyzing the characteristic of robotic GMAW, the real-time weld images are captured clearly by the passive vision sensor. Utilizing the main characteristics of the gray gradient in the weld image, a new improved Canny edge detection algorithm was proposed to detect the edges of weld image and extract the seam and pool characteristic parameters. The image processing precision was further verified by using the random welding experiments. Results showed that the precision range of the image processing can be controlled to be within ±0.3 mm in robotic GMAW, which can meet the requirement of real-time seam tracking.     

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。     

Seam Tracking Technology for Hyperbaric Underwater Welding

Automatic weld seam tracking technology to be used in hyperbaric underwater damaged pipeline repair welding is much more important, because of poor bevel preparation and severe working condition. A weld seam tracking system based on digital signal processing(DSP) passive light weld image processing technology has been established. A convenient charge coupled device(CCD) camera system was used in the high pressure environment with the help of an aperture and focus altering mechanism to guarantee overall image visibility in the scope of pressure below 0.7 MPa. The system can be used in the hyperbaric environment to pick up the real welding image of both the welding arc and the welding pool. The newly developed DSP technology was adopted to achieve the goal of system real time characteristics. An effective weld groove edge recognition technique including narrow interesting window opening, middle value wave filtering, Sobel operator weld edge detecting and edge searching in a defined narrow area was proposed to remove the guide error and system accuracy was ensured. The results of tracking simulation and real tracking application with arc striking have proved the validity and the accuracy of the mentioned system and the image processing method.     

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.     

Weld seam tracking and panorama image generation for on-line quality assurance

Traditionally, automated quality inspection of welding tasks relies on nonvisual information and is mainly done off-line. In this work, we introduce an image acquisition system which is capable of monitoring the welding process on-line, resulting in high-quality image information during an ongoing welding process. We show how to further exploit this image information by automatically tracking the weld seam position in the image, even under heavy smoke and gas disturbances. We exploit the high information redundancy between subsequent frames given by large overlap to generate a seamless image of the entire weld seam and effectively suppress adverse optical effects caused by, e.g., smoke and sparks.     

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。     

Development of a real-time laser-based machine vision system to monitor and control welding processes

In this study, a laser-based machine vision system is developed and implemented to monitor and control welding processes. The system consists of three main modules: a laser-based vision sensor module, an image processing module, and a multi-axis motion control module. The laser-based vision sensor is designed and fabricated based on the principle of laser triangulation. By developing and implementing a new image processing algorithm on the platform of LabVIEW, the image processing module is capable of processing the images captured by the vision sensor, identifying the different types of weld joints, and detecting the feature points. Based on the detected feature points, the position information and geometrical features of the weld joint such as its depth, width, plates mismatch, and cross-sectional area can be obtained and monitored in real time. Meanwhile, by feeding these data into the multi-axis motion control module, a non-contact seam tracking is achieved by adaptively adjusting the position of the welding torch with respect to the depth and width variations of the weld joint. A 3D profile of the weld joint is also obtained in real time for the purposes of in-process weld joint monitoring and post-weld quality inspection. The results indicate that the developed laser-based machine vision system can be well suited for the measurement of weld joint geometrical features, seam tracking, and 3D profiling.     

采用微型排水罩的药H焊丝水下焊接焊缝自动跟踪系统

针对水下焊接图像噪声大、清晰度差的特殊情况,设计并研制成功一套药芯焊丝水下焊接的视觉传感焊缝自动跟踪系统.该系统由视觉传感、图像预处理及偏差识别系统,控制系统和执行机构等组成.采用小波多尺度变换进行水下焊缝图像边缘提取,结果保留大多数的细节,得到有利于焊缝位置特征提取的预处理图像,在一种基于二值图像的焊缝中心位置识别算法计算后,得出焊缝偏差.在理论分析视觉传感焊缝自动跟踪系统模型的基础上,设计满足跟踪精度要求的规则自调整模糊算法.对影响跟踪系统精度的因素进行分析,并采用相应的措施以提高系统的精度.通过药芯焊丝湿法水下焊接焊缝自动跟踪试验表明,采用规则自调整模糊控制能够达到较高的焊缝跟踪精度.在斜线、折线和曲线三种不同形状待焊焊缝的跟踪试验中,系统都能满足药芯焊丝水下自动焊接的要求.经过改进微型排水罩,进行微型排水罩局部干法药芯焊丝水下焊接焊缝跟踪试验,采用规则自调整模糊控制,不仅得到满意的焊缝跟踪效果,还改善焊缝成形质量.     

图像处理在石油管道自动焊接中的应用

基于图像处理的手段使埋弧焊焊缝跟踪的自动化得以实现,图像处理要进行除噪、二值化、中值滤波、边缘检测、提取焊缝中心特征线,并使之数字化,比较计算得到焊缝与焊枪偏差量,工控机对此偏差量进行分析计算,最终控制系统驱动伺服电机带动执行机构对偏差量进行校正调整,消除焊缝焊枪之间的偏差量并能够实时对中。