焊接温度场焊缝识别及焊缝跟踪技术研究

论述焊接温度场焊缝识别方法及焊缝跟踪控制系统。系统采用焊接温度场传感器获得焊接工件背面热图像，通过改进的梯度算法对热图像的分析计算获得焊缝偏差，利用规则自校正模糊控制器实现焊缝跟踪。试验和实际生产运行表明系统能够准确识别焊缝，焊缝跟踪运行稳定可靠。     

基于焊接温度场的焊缝跟踪自调整模糊控制技术研究

对一种焊接智能控制系统进行了研究。采用ICCD从工件背后获得焊接温度场图像，通过对焊接温度场图像进行分析获得焊缝偏差信号，利用自调整模糊控制的方式调节纠偏，解决了焊接过程难以建模、焊接条件多变、简单模糊控制器控制效果不佳的问题。实际运行结果表明，该系统能够有效识别焊接偏差，并实现快速纠偏。     

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。     

焊缝跟踪FUZZY－P控制规则的研究

介绍了一种非接触超声传感焊缝跟踪系统。该焊缝跟踪系统采用了Fuzzy－P控制理论,即在大偏差时采用比例控制,在小偏差时采用自调整模糊控制。研究了Fuzzy－P控制的阈值和比例控制的规则。介绍了自调整模糊控制的原理,提出了焊缝跟踪中的双因数自调整模糊控制方法。在试验的基础上确定了双因数的数值。应用公式法生成了模糊控制规则表。同时分析了自调整模糊控制中的比例系数对系统动态特性的影响。通过试验确定了该系统中的比例系数的数值。试验证明,该跟踪系统具有快速、准确、稳定的特点,完全能够满足实际工程应用的需要。     

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。     

水下药芯焊丝焊接焊缝图象的边缘检测

焊缝图象的边缘检测是视觉传感焊缝自动跟踪的重要部分,但目前在焊缝图象处理中使用的传统边缘检测方式存在局限性。本文采用一种新的边缘检测算子－Ｃａｎｎｙ算子,对水下药芯焊丝焊接焊缝图象进行了边缘检测,并用数学方法对其进行了分析。结果表明,Ｃａｎｎｙ算子在抗噪性能和边缘定位精度这两方面优于传统微分类边缘检测算子,是一种性能较全面的边缘检测算子,适合于水下药芯焊丝焊接焊缝图象的边缘检测。     

基于DSP的水下焊缝跟踪系统设计

由于水的影响,水下的焊接很难控制,并且焊接器件的密封性也一直是个令人头疼的问题。根据水下焊接的特殊情况,本文作者研究设计了一套基于DSP的水下焊缝自动跟踪系统。该系统具有硬件结构简单、成本低廉、软件功能丰富、人机界面友好、操作简单易学等优点,为进一步进行水下焊接焊缝自动跟踪的研究打下了基础。     

一种用于焊缝跟踪的步进电机模糊控制系统

介绍一种用于焊缝跟踪的步进电机模糊控制系统，该系统可根据跟踪偏差进行参数自调整，改善了步进驱动系统的动静态特性，提高了缝跟踪精度。     

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。     

气幕式旋转电弧传感器结构设计

针对水下焊接焊缝质量差等问题,设计了一种用于水下局部干法焊接的气幕式旋转电弧传感器来改善水下焊接质量。传感器采用空心电机驱动,通过偏心机构可进行圆锥摆动;传感器的排水罩采用了收缩喷管的结构,有利于在喷嘴附近获得高速均匀的气流;加工出了气幕式旋转电弧传感器实物,经过上电测试表明运转情况良好且能有效采集到信号。     

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。     

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.     

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。     

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.     

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.     

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.     

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.     

规则自调整模糊控制的弧焊机器人焊缝纠偏研究

采用特征谐波法准确识别焊缝偏差,研究熔池对坡口的影响作用,采用补偿因子加权处理可有效地减小这种影响,因此提高了对偏羔的识别能力。采用规则自调整模糊控制器进行焊缝纠偏控制,以克服常规模糊控制器的不足,使其具有良好性能。     

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.     

ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

0 INTRODUCTION(The satisfied control of the overall weld process is not easily accomplished, largely due to the inadequacies of the available process models. Without exceptions, most welding control methods are based upon the analytical welding models. Although these models are derived directly from the physical laws that govern the main features of the weld pool, a number of assumptions are made to obtain the mathematical solutions and some variables are ignored due to the complexity of t…