DETECTION AND ANALYSIS OF WELD POOL SHAPE FOR CO2 SHORT CIRCUITING ARC WELDING

0 INTRODUCTIONIt is well known that skilled welding operatorscan estimate and control beam quality by mainlyobServing the weld POOl. This means the POOl im8gecontains abundant inforTnation during weldprocess. So that, sensing information from POOl imeqedirectly is becoming a new method to control the weldquality.Following the advances in computer vision andM camera tecbnoogy, more and more researchesusing weld opl image for sensing welding processeshave been carried out, usually in T…     

Penetration Estimation of GMA Backing Welding Based on Weld Pool Geometry Parameters

Penetration estimation is a prerequisite of the automation of backing welding based on vision sensing technology.However, the arc interference in welding process leads to the di culties of extracting the weld pool characteristic information, which brings great challenges to the penetration estimation. At present, most researches focus on the extraction of weld pool geometry parameters, and the visual sensing systems are complex in structure and complicated in the image processing algorithms. The research of penetration estimation based on weld pool geometry parameters is still in the exploratory stage. The purpose of this paper is to research the relationship between the weld pool geometry parameters and the penetration during backing welding and to estimate penetration using the weld pool geometry parameters. A passive vision sensing test system for gas metal arc(GMA) backing welding was established. An image processing algorithm was developed to extract the weld pool geometry parameters, namely,the area, maximum width and length, half-length, length-width ratio and advancing contact angle(simplified as AWP,MWWP, MLWP, HLWP, LWR and ACA, respectively). The corresponding relationships between the weld pool geometry parameters and the penetration state were explored by analysing their changes with the welding current and speed. The distribution of the weld pool geometry parameters corresponding to penetration was determined. When the AWP of the weld pool is within a certain range and the values of LWR and ACA are close to their maximum and minimum respectively, the penetration is in good condition. A mathematical model with the weld pool geometry parameters as independent variables and the back-bead width(the indicator of the penetration state) as a dependent variable was established based on multivariable linear regression analysis, and relevant statistical tests were carried out. Multivariable linear regression equations for the weld pool geometry parameters and the back-bead width were deduced according to the variations in the current and speed, and the equations can be used to estimate the penetration of backing welding. The study provides a solution to penetration estimation of GMA backing welding based on automatic vision sensing.     

非熔化极气体保护焊接熔池表面形貌三维传感及其装置设计

熔池表面形貌的传感及其三维恢复在焊接机理研究和成形控制中均有着深远的意义,然而焊接过程中强弧光的干扰和熔池表面的镜面特性使得熔池表面的三维传感非常困难。利用小功率结构光条纹激光器投射激光条纹于非熔化极气体保护焊(Gas tungsten arc welding, GTAW)熔池表面,由成像屏接收熔池表面镜面反射过来的激光条纹,利用镜头前附加了与激光器波长匹配的窄带滤光片的电荷耦合器件(Charge-coupled device, CCD)摄像机观察成像屏上的条纹变化,从而获得熔池表面的高度等三维信息。为了便于研究传感规律及确定传感器结构参数间的最佳组合,设计了一套传感装置,并利用该传感装置在强弧光下获得了清晰的能够反映GTAW熔池表面形貌的激光反射条纹图像。     

Visual sensing and penetration control in aluminum alloy pulsed GTA welding

In this paper, visual sensing and penetration control in aluminum (Al) alloy pulse gas tungsten arc welding were researched. Firstly, a three-optical-route visual sensor was designed. The sensor can capture the weld pool from three directions at the same time. After analyzing the influences of different factors on weld pool image, serials of clear and stable weld pool images were obtained. Then, image processing technologies were developed to compute back topside weld pool geometry parameters. Wavelet transform and Canny operator were synthesized to get all edges in the weld pool image. After noise removal and calibration, the breaking edges of weld pool were obtained, and then piecewise curve fitting based on polynomial function were used to recover the whole weld pool edge. Lastly, proportional–integral–differential and a multiplex controller were designed to control penetration in welding process. Experiments proved that visual-based penetration control can insure welding quality well from weld pool width and reinforcement.     

基于卡尔曼滤波的焊缝检测技术研究

提出一种基于卡尔曼滤波技术的电弧焊焊缝检测新方法。利用视觉传感器获取弧焊区熔池图像,并抽取图像质心作为描述焊缝位置的特征矢量,建立图像质心状态方程和测量方程。在有色噪声模型的基础上,应用卡尔曼滤波对图像质心位置和质心位移进行状态估计,得到最小均方差条件下的焊缝位置最佳预测值,从而减小过程噪声和测量噪声引起的焊缝位置测量偏差,实现弧焊过程中焊缝位置的精确检测。计算机仿真及实际焊接试验结果验证了该方法的有效性。     

Obtaining weld pool vision information during aluminium alloy TIG welding

An image sensing system for the TIG (tungsten inert-gas arc) welding process of aluminium alloy was established. The relationships between the image sensing system and the characteristic of welding current were discussed in detail. Front and back images of the weld pool were obtained with different welding parameters. In order to process the image, the characteristics of an aluminium alloy were analysed. Image processing and pattern recognition were first used to obtain information from the TIG welding process for aluminium alloy. The image of the weld pool was pre-processed using a series of methods: a weighted median filter, a statistical threshold by expectation and the projection method. A neural network method was used to extract the edge of the images of the weld pool. The result of detecting the edge with a BP neural network were excellent. The symmetry of the weld pool for aluminium alloy was studied when the welding current is large. The edge of the image of the whole weld pool is obtained in a single side image and an accurate method for measuring the weld pool geometry parameter is provided. Experiments show that using the image sensing to control the TIG weld width for aluminium alloy is an effective method.     

用于焊缝位置识别的视觉模型设计与试验

理论与试验研究用于焊缝位置识别的视觉模型,该模型主要由弹性梯度下降训练法BP神经网络组成.在焊接工艺条件下,使用视觉传感器获取焊接区熔池图像,并选取特定区域进行中值滤波与图像灰度变换处理以增强被测对象的特征.在此基础上,计算和处理熔池特性参量(熔池图像质心差值、质心位移、质心移动速度)以及相对应的焊缝与电弧之间的偏差值,将其输入所设计的神经网络进行网络权值参数训练和推理学习,从而建立基于BP神经网络、具有一定认知和环境适应能力的焊缝位置识别视觉模型.对该模型进行通用性检验,试验结果表明该模型通过熔池特性参量可以较精确地识别焊缝位置.     

铝合金脉冲GTAW焊熔池表面反射模型研究

熟练焊工能够通过观察熔池表面的凸凹信息获取熔池的成形,在机器人智能化焊接过程中,采用视觉传感方式模拟焊工视觉获取熔池的形状信息。图像的灰度值决定于光源特性、物体表面形状、反射特性和摄像机特性。熔池图像隐含熔池的形状信息,为了从图像中提取熔池的形状信息,分析了铝合金脉冲GTAW焊的熔池表面反射特性,熔池表面由漫反射表面、镜面反射表面和互反射表面组成,建立了熔池表面反射模型。     

Three-dimensional vision-based sensing of GTAW: a review

Automated and robotic welding is now widely used in manufacturing industry. The control of the welding process plays a crucial role in producing quality welds in automated and robotic welding where the assistance from skilled welders is no longer available. In gas tungsten arc welding (GTAW) which is the primary arc welding process for precision joining of metals, the weld pool is the major source of information that can be used to assure the production of desired weld penetration which is the most critical factor determining the weld integrity. To meet this challenge, various sensing technologies have been proposed/studied to sense and obtain the feedback for the weld pool state. This paper summarizes the researches on weld pool state sensing: conventional sensing technologies, vision sensing technology, and multi-sensor information fusion technology, with emphasis on the analysis of three-dimensional vision sensing methods. And three-dimensional vision sensing, multi-sensor technology, intelligent modeling, and effective commercial product development show the future trends of GTAW penetration sensing.     

穿孔等离子弧焊正面弧光传感技术研究

小孔的稳定性是影响穿孔等离子弧焊焊接过程稳定性及接头质量的重要因素。在等离子弧发射光谱分析的研究基础上,研制了轻便实用的弧光传感器,采用普通光电器件和滤光镜片替代赘重昂贵的光谱分析系统,可以捕捉到表征小孔特征状态的信号。介绍了弧光传感器的组成、物理模型及信号特征。     

Ar+O_2 混合气体熔化极脉冲焊时的旋转喷射过渡特征

通过高速摄影方法,观察分析了在Ａｒ＋Ｏ２混合气体熔化极脉冲焊中形成旋转喷射过渡时的电弧形态和熔滴过渡形态。结果表明：当形成脉冲旋转喷射过渡时,熔滴呈液流束的形式向熔池过渡;焊接电弧呈鼓形;焊缝截面呈“扇形”或“锅底”形,它们与脉冲能量及气体物理性质等有关。     

Part-based model for visual detection and localization of gas tungsten arc weld pool

Observing the weld pool and measuring its geometrical parameters are important issues for automated and robotic welding, wherein the visual detection and localization of weld pool are critical steps. Previous methods of visual measurement of weld pool usually assume that the weld pool exists in a predefined area, and its contour should be a specific geometric shape and size. Furthermore, previous methods were only suited for the pool images with complete boundary information and with small disturbing/noise edge. When part of the pool boundary is seriously spoiled (for example, by reflection) or confused by pileup area, it is very difficult if not impossible to conduct the geometric measurement of weld pool. In this paper, we propose a robust visual detection and localization method for the pool of gas tungsten arc weld based on part-based modeling and recognition of objects. It provides an elegant framework for representing the outline of a weld pool and is especially efficient for weld pool detection and localization in cluttered scenes, when it is partially occluded or when similar-looking pileup area can act as additional distracters. Experiments on real images verified the proposed method.     

表面活性剂对TIG焊电弧现象及焊接熔深的影响

在变动焊接电流下检测电弧电压,考察A-TIG焊电弧收缩及活性剂的影响。采取适当的试验方法研究A-TIG焊活性剂对电弧现象及活性剂涂敷量对焊接熔深增加的作用。结果表明,A-TIG焊电弧是否产生收缩与所使用的活性剂有关,即使在电弧未产生收缩情况下,表面活性剂仍然对焊接熔深的增加有较大的作用。     

Experimental study and numerical modeling of arc and weld pool in stationary GTA welding of pure aluminum

In this study, a 2D mathematical model was developed for both arc and weld pool in stationary GTA welding. In arc model, current continuity equation has been solved in both arc and cathode regions without any assumption of fixed current density on the cathode surface which was essential in most previous works. The results of arc model were presented for both copper and aluminum anodes to investigate the effect of anode material on arc properties. It was seen that aluminum anode has lower maximum anode current density and heat flux but the distributions are wider than copper anode. Furthermore, shear stress on anode surface is higher in the case of aluminum anode. Also, calculated results of this study were compared with other available theoretical and experimental results. It has been shown that the agreement between calculated and experimental results was fairly good. The necessary information to simulate the weld pool, including the anode current density and heat flux to the workpiece were taken from the arc model. In this model, due to high thermal conductivity of pure aluminum, fluid flow into the weld pool was ignored. Effects of arc variables, i.e., arc length, applied current and welding time on the shape and size of the weld pool were investigated as well. In order to check the validity of the weld pool model, a comparison between calculated results and the results of our experimental tests was conducted. Generally, these comparisons reveal an acceptable agreement between calculated results and experimental data.     

A study on a vision sensor system for tracking the I-Butt weld joints

In this study, a visual sensor system for weld seam tracking the I-butt weld joints in GMA welding was constructed. The sensor system consists of a CCD camera, a diode laser with a cylindrical lens and a band-pass-filter to overcome the degrading of image due to spatters and arc light. In order to obtain the enhanced image, quantitative relationship between laser intensity and iris opening was investigated. Throughout the repeated experiments, the shutter speed was set at 1/1000 second for minimizing the effect of spatters on the image, and therefore the image without the spatter traces could be obtained. Region of interest was defined from the entire image and gray level of the searched laser stripe was compared to that of weld line. The differences between these gray levels lead to spot the position of weld joint using central difference method. The results showed that, as long as weld line is within ±15° from the longitudinal straight line, the system constructed in this study could track the weld line successfully. Since the processing time is no longer than 0.05 sec, it is expected that the developed method could be adopted to high speed welding such as laser welding.     

RECONSTRUCTION OF WELD POOL SURFACE BASED ON SHAPE FROM SHADING

A valid image-processing algorithm of weld pool surface reconstruction according to an input image of weld pool based on shape from shading (SFS) in computer vision is presented. The weld pool surface information is related to the backside weld width, which is crucial to the quality of weld joint. The image of weld pool is recorded with an optical sensing method. Firstly, the reflectance map model, which specifies the imaging process, is estimated. Then, the algorithm of weld pool surface reconstruction based on SFS is implemented by iteration scheme and speeded by hierarchical structure. The results indicate the accuracy and effectiveness of the approach.     

Prevention of humping bead associated with high welding speed by double-electrode gas metal arc welding

Manufacturing productivity can be improved by increasing the welding speed. However, humping bead will occur when welding speed is beyond a certain value. An experimental system of double-electrode gas metal arc welding (DE-GMAW) was developed to implement high speed welding and prevent from humping bead formation. The DE-GMAW appropriately partition the heat energy between the wire and the base metal so that higher deposition rate of filler wire and suitable shape and size of weld pool are ensured. The arc images captured during DE-GMAW process were used to optimize the geometric parameters between the gas tungsten arc welding and the gas metal arc welding (GMAW) torches. The main arc and bypass arc integrated well and satisfactory weld bead formation was obtained. Through observing the weld pool behaviors from side view during DE-GMAW process, it was found that the height of both solidified and molten region at the pool tail is almost flat so that no humping bead was formed during DE-GMAW with the welding speed up to 1.7?m/min. The side view images of weld pool in DE-GMAW were compared with those in conventional GMAW, and the reason why DE-GMAW can suppress humping bead is shortly discussed.     

连续脉冲GTAW不同熔透状态熔池振荡 频率特征及分析*

熔池振荡频率与熔池尺寸具有直接物理对应关系,但常规弧压、弧光方法很难实现连续焊接振荡频率提取。提出一种激光视觉测量方法用于连续焊接振荡频率检测。对连续焊接条件下部分、临界及全熔透状态下的熔池振荡激光条纹进行采集,通过图像处理算法提取不同熔透状态下的频率特征,并从激光条纹变化形态、熔池表面振荡和液态金属内部流动对不同频率特征进行分析。结果表明,激光视觉法能够精确检测熔池表面金属轴向及横向的流动;在部分和全熔透状态下熔池表面及内部金属以单一模式进行振荡,存在单一特征频率;在临界熔透状态下由于熔池约束条件的变化,使其表面振荡及内部金属振荡具有部分和全熔透的振荡特征,表现出两种特征频率;不同熔透状态的振荡频率特征可为精确检测不同熔透状态提供依据。     

Prediction of pulsed GTAW penetration status based on BP neural network and D-S evidence theory information fusion

This paper used multi-sensor information fusion technology in pulsed gas tungsten arc welding. Arc sensor, visual sensor, and sound sensor were used simultaneously to obtain weld current, voltage, weld pool image, and weld sound information about the pulsed gas tungsten arc welding process, and special algorithms were designed to extract the respective signal features of different sensors’ information. Then D-S evidence theory was used to fuse the different signal features to predict the penetration status about the welding process. Aimed at the difficulty of obtaining basic probability assignment in D-S evidence theory, back-propagation (BP) neural network was used to obtain the basic probability assignment. Experiments were done to obtain data for training the BP neural network and test the prediction reliability of D-S evidence theory information fusion, and comparison results showed that D-S evidence theory could effectively use the information obtained by different sensors and obtain better prediction result than single sensor.     

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.