Design of Robot Welding Seam Tracking System with Structured Light Vision

Robot welding is an important developing direction of welding automation and intelligentization, and automatic seam tracking technology is one of principal research domains. Nowadays, seam tracking system with structured light vision becomes a hot research. Structured light vision seam tracking products abroad are generally very expensive and can only be applied on special occasions. In China, the research of structured light vision seam tracking system is still just on the stage of experiments. A robot real-time seam tracking system with line structured light vision is designed. The hardware system is set up, a filtering method for line structure seam image is improved, and compared with common filtering, it has better effect and characteristic of real time. Two methods, fast template matching and fast Hough transform, to recognize the image coordinates of seam center are improved. Two new image recognition methods, structure element matching and comer detecting, are proposed. The comparison of seam image recognition shows that fast template matching and comer detecting are more precise and stable than the other two methods, and comer detecting is the best in real time. A simultaneous calibration for camera parameters and robot hand-eye is also proposed, and calculation shows that the calibration is effective and feasible. The robot seam tracking tests for linear and folded lap-joint are performed, which are based on the above four image recognition methods, and the results indicate that four image recognition methods are all applicable to real-time seam tracking, and the whole system sufficed for the requirements of real-time seam tracking. Automatic seam tracking with line structured light vision is feasible and has good versatility.

Seam Tracking and Visual Control for Robotic Arc Welding Based on Structured Light Stereovision

A real-time arc welding robot visual control system based on a local network with a multi-level hierarchy is developed in this paper. It consists of an intelligence and human-machine interface level, a motion planning level, a motion control level and a servo control level. The last three levels form a local real-time open robot controller, which realizes motion planning and motion control of a robot. A camera calibration method based on the relative movement of the end-effector connected to a robot is proposed and a method for tracking weld seam based on the structured light stereovision is provided. Combining the parameters of the cameras and laser plane, three groups of position values in Cartesian space are obtained for each feature point in a stripe projected on the weld seam. The accurate three-dimensional position of the edge points in the weld seam can be calculated from the obtained parameters with an information fusion algorithm. By calculating the weld seam parameter from position and image data, the movement parameters of the robot used for tracking can be determined. A swing welding experiment of type V groove weld is successfully conducted, the results of which show that the system has high resolution seam tracking in real-time, and works stably and efficiently.

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.

Seam tracking control for mobile welding robot based on vision sensor

To solve the seam tracking problem of mobile welding robot,a new controller based on the dynamics of mobile welding robot was designed using the method of backstepping kinematics into dynamics.A self-turning fuzzy controller and a fuzzy-Gaussian neural network(FGNN) controller were designed to complete coordinately controlling of cross-slider and wheels.The fuzzy-neural control algorithm was described by applying the Gaussian function and back propagation(BP) learning rule was used to tune the membership function in real time by applying the FGNN controller.To make the tracking more quickly and smoothly,the neural network controller based on dynamic model was designed,which utilized self-learning and self-adaptive ability of the neural network to deal with the partial uncertainty and the disturbances of the parameters of the robot dynamic model and real-time compensate the dynamics coupling.The results show that the selected control input torques make the system globally and asymptotically stable based on the Lyapunov function selected out;the accuracy of the proposed controller tracing is within ±0.4 mm and can satisfy the requirements of practical welding project.

Study of image processing for V-shape groove and robotic weld seam tracking based on laser vision

Single-stripe laser was applied to acquire V-shape groove contour information. Most of arc light and splash noise was removed and stripe laser image was kept by wavelet transform. Half-threshold algorithm was used for image segmentation and stripe laser image was gotten after refining. Weld seam center position was identified and extracted by extreme curvature corner detection method. The location of torch was detected to accord the frequency of computer program with robot program and serial communication program. The tracking experiments of sidelong, reflex and curve weld line show that the system can meet the demand of the tracking precision under normal welding conditions.

The characteristics of welding currents in a rotating arc leadtandem GMAW process and the weld-seam tracking

Tandem gas metal arc welding （ T-GMAW） process shows a high deposition rate that up to three times o f the single electrode GMAW, so the welding speed could be significantly increased in this process. However, the majority o f this process applications are based on the pre-programmed robotic welding, which does not allow them to track the seam real-time during welding. Rotating arc sensor, sensing the seam position by detecting the changing of welding currents, has been widely adopted in the automatic robot welding process. It is proposed in this paper to integrate the rotating arc sensor with a trailing torch to develop a new approach of rotating arc lead tandem gas metal arc welding （RLT-GMAW） process. The characteristics of the welding currents in the proposed new welding process were firstly studied, and then a self-turning fuzzy control seam tracking strategy was developed for the mobile robot automatic welding. The experimental results showed that the proposed RLT-GMAW process had an excellent seam tracking performance and high welding deposition rate. Even if there were some electromagnetic interactions between the two arcs, the deviation of the welding seam could also be reflected by the fluctuation of the welding currents on the leading arc once the correct welding parameters were selected. Based on the detected deviation, the welding tracking experiments showed that the proposed self-turning fuzzy controller had a good performance for the RLT-GMAW process seam tracking.

Study on contactless ultrasonic sensor and seam tracking

The sensitivity of contactless ultrasonic sensor is improved from 3.3% to 26% through acoustic and electric matching technique in this paper.Along dual crest lines auto seam tracking is firstly realized with contactless ultrasonic sensing.The focused acoustic lens is accurately designed, and a sonic beam with 0.5 mm in diameter is achieved. By means of software and hardware technique the accuracy of seam tracking with ultrasonic sensing is 0.5 mm in lateral direction and 0.2 mm in longitudinal direction respectively.

Novel Real-Time Seam Tracking Algorithm Based on Vector Angle and Least Square Method

Real-time seam tracking can improve welding quality and enhance welding efficiency during the welding process in automobile manufacturing.However,the teaching-playing welding process,an off-line seam tracking method,is still dominant in automobile industry,which is less flexible when welding objects or situation change.A novel real-time algorithm consisting of seam detection and generation is proposed to track seam.Using captured 3D points,space vectors were created between two adjacent points along each laser line and then a vector angle based algorithm was developed to detect target points on the seam.Least square method was used to fit target points to a welding trajectory for seam tracking.Furthermore,the real-time seam tracking process was simulated in MATLAB/Simulink.The trend of joint angles vs.time was logged and a comparison between the off-line and the proposed seam tracking algorithm was conducted.Results show that the proposed real-time seam tracking algorithm can work in a real-time scenario and have high accuracy in welding point positioning.

A machine vision approach to seam tracking in real-time in PAW of large-diameter stainless steel tube

Manual monitoring and seam tracking through watching weld pool images in real-time, by naked eyes or by industrial TV, are experience-depended, subjective, labor intensive, and sometimes biased. So it is necessary to realize the automation of computer-aided seam tracking. A PAW (plasma arc welding) seam tracking system was developed, which senses the molten pool and the seam in one frame by a vision sensor, and then detects the seam deviation to adjust the work piece motion adaptively to the seam position sensed by vision sensor. A novel molten pool area image-processing algorithm based on machine vision was proposed. The algorithm processes each image at the speed of 20 frames/second 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.

Study on the image processing of laser vision seam tracking system

Seam image processing is the basis of the realization of automatic laser vision seam tracking system, and it has become one of the important research directions. Adding windows processing, gray processing, fast median filtering, binary processing and image edge extraction are used to pretreat the seam image. In the post-processing of seam image, the feature points of the target image are succesfully detected by using center line extraction and feature points detection algorithm based on slope analysis. The whole processing time is less than 150 ms, and the real-time processing of seam image can be implemented.

Development of seam tracking system with ultrasonic sensor using self-tuning fuzzy control

One kind of the SAW seam tracking system with contactless ultrasonic sensor is presented in this paper. The new contactless ultrasonic sensor for seam tracking and the working principle of the seam tracking with the sensor are introduced. Based on the experiments, the optimal values of the fuzzy control parameters α and k 3 are defined by means of the off line adjusting method. Because the self tuning fuzzy control is adopted in the seam tracking system, the overshoot of the system is restrained, the steady state error is reduced, and the system's response speed is improved effectively. The results of the SAW seam tracking experiments show that this system's tracking accuracy is up to ±0.5 mm and the system can satisfy the requirements of the engineering application.

Seam-tracking based on dynamic trajectory planning for a mobile welding robot

A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By using a front-placed laser-based vision sensor to dynamically extract the location of the weld seam in front of torch,the trend and direction of the weld line is roughly obtained.The robot system autonomously and dynamically performs trajectory planning based on the isometric approximation model.Arc sensor technology is applied to detect the offset during welding process in real time.The dynamic compensation of the weld path is done in combination with the control of the mobile robot and the executive body installed on it.Simulated and experimental results demonstrate that the method effectively increases the stability of welding speed and smoothness of the weld track,and hence the weld formation in curves and corners is improved.

Arc sensing system for automatic weld seam tracking (Ⅱ)——Signal processing

Due to violent disturbance of the welding arc, signal processing is the key problem of application of the sensor. By means of the new technique the arc sensor can recognize not only V-groove but also lap joint and butt joint. The sensor has good recognition ability even for welding process with very large current disturbance, e.g. pulsed arc and short circuit welding process, etc. The proposed technique is developed on the basis of modern digital filtering theory and mathematic transformation of the signals from time domain into frequency domain.

Arc sensing system for automatic weld seam tracking(Ⅰ)——Mathematic model

Arc sensor, one of the most popular and effective sensors for automatic seam tracking of arc welding, is systematically studied. A mathematic model of the static and the dynamic properties of the sensor derived on the basis of control theory and experimental method are described. The model extends our understanding of arc sensor from qualitative level to quantitative level. This is important for its design and further development.

基于电流多特征融合的窄间隙P-GMAW摆动电弧传感焊缝跟踪方法

电弧传感是实现窄间隙焊接焊缝跟踪的主要方式之一。针对电弧传感稳定性差、可靠性低的问题,提出融合摆动周期内电流信息的多个统计学特征进行偏差提取的方法,克服单一数据特征容易受到电弧稳定性影响、导致传感精度下降的问题。首先,提取电流信号的多个时域特征,计算特征矩阵与偏差矢量相关性;然后,取相关性高的特征用主成分分析的方法进行融合,取前两个主成分作为观测数据;最后,基于多分类的支持向量机模型对其进行分类试验。试验结果表明最大误差为0.2 mm,0.1 mm以内的误差占93.75%。该方法对比传统方法精度有所提升,对比神经网络方法,所用训练样本少,训练过程更加简单。

基于结构光的飞机蒙皮对缝自主测量跟踪技术

针对飞机蒙皮对缝间隙和阶差的自动化测量问题,以线结构光视觉检测技术为基础,研究了蒙皮对缝自主测量跟踪方法。将传统的基于图像形态学的处理方法和光流法结合,实现了对蒙皮对缝特征的实时跟踪,从而确定间隙和阶差的测量位置。通过实测数据对手眼标定参数进行修正,提高了对缝跟踪的精度。结果表明,当跟踪速度为7 mm/s时,对缝跟踪的位置精度大于0.500 mm,对缝跟踪的姿态精度大于0.5°,跟踪系统具有较好的准确性和稳定性,能够满足飞机蒙皮对缝跟踪的要求。

基于EKF的GMAW实时焊缝跟踪研究

熔化极气体保护电弧焊(gas metal arc welding,GMAW)焊接过程存在惯性大、时滞大等非线性特征以及不确定的干扰因素。为了提高焊接质量,文章提出了一种基于扩展卡尔曼滤波器(extended kalman filter,EKF)算法的焊缝实时跟踪技术,采用霍尔电流传感器来捕捉实时焊接电流。为了实现焊枪摆动中心始终对准焊缝中心,文章通过有限长单位冲激响应滤波器(finite impulse response,FIR)对采集的电流进行滤波,并建立提取焊枪高度和水平偏差的数学模型,采用EKF实现控制焊枪。通过在有垂直和水平方向偏差的焊缝上进行实验验证,结果跟踪精度可达到±0.25 mm,所以该方法可满足机器人实时跟踪的要求。

机器人焊接技术在管道焊接中的应用现状

为介绍管道焊接中机器人焊接技术的应用情况,按照技术出现的顺序对油气管道焊接技术进行概括,分析了不同自动化焊接设备的工作原理,同时对工程中常用的设备进行了举例。文中介绍了管道铺设工程中相关的管道焊接检测技术以及管道接头腐蚀防护技术,最后介绍了焊接机器人的发展趋势,包括基于运动仿真的越障焊接、扩大应用场景与功能、引入新的传感器与原理。

基于地理信息系统的大倾角煤层飞矸运移研究

针对大倾角煤层工作面底板的不规则性和飞矸形状的多样性,利用工作面底板等高线等地理信息系统数据建立真实工作面底板三维网格模型,结合能量跟踪法(ETM)自编C++程序,模拟得到相同质量不同形状的四类典型形状飞矸在实际工作面运移的运动轨迹,以及任意时刻的线速度、角速度和能量变化曲线,分析了形状对飞矸运移规律的影响。为验证本文方法的准确性和可行性,与采用Rockyfor3D软件模拟的轨迹进行了对比。结果表明,椭球体飞矸的运移能力远大于多面体飞矸;正多面体飞矸比一般多面体飞矸运移距离更远,碰撞的能量损失更小;正多面体飞矸的棱边数与飞矸在碰撞中的能量损失量成反比,多棱边正多面体飞矸造成危险的可能性最大。

焊接机器人在钢结构制造中的研究与应用

传统人工焊接存在自动化程度低、效率低下、质量参差不一等问题,而焊接机器人能大幅提高焊接效率,节省人力及改善焊接质量,保障同类焊缝的一致性,可被大规模应用于钢结构生产制造,因此,制造行业正逐渐向无人化、智能化方向转型。以油类垃圾箱为研究对象,采用Solidworks构建三维模型并进行静力学校核计算,利用Robot Stutio建立焊接工作站模拟仿真,对焊接轨迹进行离线编程,采用龙门式焊接机器人进行现场示教,调试激光纠偏系统,完成对油类垃圾箱的单片焊接,为焊接机器人在钢结构行业提供了应用依据。最后探讨了先进焊缝追踪技术和智能化焊接机器人,明确了焊接机器人未来应用的方向和趋势。