基于结构光视觉的激光拼焊焊缝质量检测方法研究

在基于结构光视觉的激光拼焊焊缝表面质量检测系统中,需要准确获得焊缝结构光条纹中心线和特征点的位置.由于焊接过程中的各种噪声干扰,使得焊缝图像复杂多变,因此选择合理高效的图像处理算法是非常重要的.针对这一问题,对结构光视觉焊缝质量检测系统图像处理方法进行了深入研究.在图像预处理中,首先通过开窗处理来获得兴趣区域,采用中值滤波去除图像噪声.在结构光条纹中心线提取过程中,提出了一种新的模板法获得了条纹的边界并用几何中心法提取了条纹中心线;最后,使用斜率分析法提取了特征点.试验表明,该方法具有较高的特征点检测可靠性,并且运算速度快、抗干扰能力强,具有较高实用价值.     

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。     

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.     

Vision-based initial weld point positioning using the geometric relationship between two seams

This paper presents a novel vision-based initial weld point positioning method for the welding systems of container manufacture. The new method is based on the geometric relationship between the two seams at the two different stages of the whole welding task such as the initialization stage and the welding stage. The torch is aligned with the initial weld point manually at the first stage, and the image feature and the parameters of the seam line are computed. At the second stage, the target image feature of the seam line is firstly computed using the geometric relationship, then the alignment of the torch is automated based on the difference between the target and the current image features. The geometric relationship between the two seams is analyzed, and then the realization of the new method including the image processing, the computation of the parameters of the seam line, and the control system design is given in detail. Finally, experiments are well conducted to prove the effectiveness of the proposed initial weld point positioning method.     

Compact visual control system for aligning and tracking narrow butt seams with CO2 gas-shielded arc welding

In this paper, a visual control system is proposed to locate the start welding position and track the narrow butt welding seam in container manufacturing. It estimates the error between the welding torch and the welding seam with a camera and a panel computer. It adjusts the torch’s position via a stepper motor to eliminate the error. A decision controller with three gates is designed to decide the working procedure. Feature extraction algorithms are designed according to the seams and pre-weld spots. The seam line and the position of the pre-weld spot are detected to locate the start welding position in initial aligning. Then the torch is aligned to the seam. In the welding stage, the reference feature is determined with many frames of images based on their statistical property. The current estimated feature is checked to ensure only normal features to be used for welding seam tracking. Experiments are well conducted to verify the effectiveness of the proposed system and methods.     

基于结构光视觉的激光拼焊焊缝质量检测方法研究

焊缝质量自动检测是实现焊接自动化的关键技术。文中在分析结构光视觉检测原理的基础上,建立了基于结构光视觉的激光拼焊焊缝质量检测系统并对检测系统的图像处理方法进行了研究。对原始图像进行了开窗处理和中值滤波,并使用迭代阈值法获得了结构光光纹。提出了一种简化的模板获得了光纹的边界点并使用几何中心法提取了光纹中心线。使用平均斜率法识别出光纹中心线的特征点。分析了激光拼焊焊缝截面轮廓的特点并建立了截面轮廓几何参数计算方法。实验结果表明该检测系统可以完成焊缝截面轮廓相关参数的计算。     

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。     

Discerning Weld Seam Pro les from Strong Arc Background for the Robotic Automated Welding Process via Visual Attention Features

In the robotic welding process with thick steel plates, laser vision sensors are widely used to profile the weld seam to implement automatic seam tracking. The weld seam profile extraction(WSPE) result is a crucial step for identifying the feature points of the extracted profile to guide the welding torch in real time. The visual information processing system may collapse when interference data points in the image survive during the phase of feature point identification, which results in low tracking accuracy and poor welding quality. This paper presents a visual attention featurebased method to extract the weld seam profile(WSP) from the strong arc background using clustering results. First, a binary image is obtained through the preprocessing stage. Second, all data points with a gray value 255 are clustered with the nearest neighborhood clustering algorithm. Third, a strategy is developed to discern one cluster belonging to the WSP from the appointed candidate clusters in each loop, and a scheme is proposed to extract the entire WSP using visual continuity. Compared with the previous methods the proposed method in this paper can extract more useful details of the WSP and has better stability in terms of removing the interference data. Considerable WSPE tests with butt joints and T-joints show the anti-interference ability of the proposed method, which contributes to smoothing the welding process and shows its practical value in robotic automated welding with thick steel plates.     

基于膨胀和Hough变换的焊缝位置检测方法

对视觉焊缝跟踪图像处理的方法进行了研究.首先,将彩色图像灰度化,再通过滤波、直方图均衡化等进行图像分割;然后,利用边缘检测和数学形态学中的膨胀算子将目标区域连通;最后,利用Hough变换找出焊缝的边界线和中心线.该方法不仅可以较快地把焊缝整个区域提取出来,而且可以检测出焊缝偏离的位置和方向.实验运行结果表明该方法精度高...     

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.     

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.     

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.     

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.     

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。     

An automated weld seam tracking system for thick plate using cross mark structured light

This paper presents a weld seam tracking system using cross mark structured light. The hardware of the proposed system consists of a two degrees of freedom (DOF) welding robot, a camera with cross mark structured light, and two computers. The system has two parts namely visual sensing and motion control. In the visual sensing part, the cross mark of the structured light is utilized to set a region of interest (ROI). In the ROI, an adapted line fitting algorithm is employed to estimate the lines. Then, intersections of the lines are computed and used as the pin points for templates creating. During the matching process, a modified template matching is used to detect the edges of V-groove weld seam. By using this technique, a huge computational cost in image processing can be reduced, and therefore the tracking can be made in real time. The position based visual servoing with proportional-derivative(PD) and velocity feedback controller is designed for seam tracking. The experimental results show that the proposed method performs the real-time tracking efficiently with sufficient accuracy.     

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.     

分形理论和LOWESS方法在球罐焊接坡口检测中的应用

针对球罐焊接过程坡口边缘灰度变化不明显 ,受噪声和其它干扰信息的影响很难准确及时地处理图像的弱点 ,本文提出了分形理论和LOWESS方法相结合的图像处理方法。该方法是根据坡口图像的特点 ,首先利用LOWESS方法通过拟合坡口图像每一行的灰度值最低点求出坡口的中心线 ,然后利用图像的分形特征求坡口边缘相对于坡口中心线的偏移量 ,从而进行坡口边缘的识别。实验结果证明 ,该方法不仅能准确地识别出坡口图像的边缘 ,而且节省了图像处理的时间 ,为焊接过程的实时控制提供了可靠的信息     

Study on the deformation mechanism for forming shafts without concavity during the near-net forming cross wedge rolling process

Intelligent robotic welding involves replicating the role of a manual professional welder to adaptively control the welding process. This is necessary to achieve accurate, fast and high-quality welding process in addition to the challenging factors for humans to operate in the welding environment. Therefore, robotic welding exists since the early days of robotics and it is still an active research area. This is why there have been numerous researches in this area for a very long time. Among various techniques proposed by researchers for the adaptive control of the robotic welding process, vision-based control is the most popular due to its non-invasiveness. Therefore, in this paper, we review, analyse and categorise the proposed vision-based techniques with the aim of covering the different image processing and feature extraction aspect of the techniques. The focus is mainly on the active vision system where various image processing techniques have been utilised in extracting the welding seam features. The challenges and difficulties to extract seam features in active vision system have been highlighted. The trends and new approaches have been indicated in order to provide a comprehensive source for researchers who are planning to carry out research related to the intelligent robot vision techniques for welding automation.     

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.     

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。