Sensing and seam tracking of welding line in backingless V groove welding

Abstract

The formation of stable back beads in the first layer weld during one side multilayer welding is important to achieve high quality welded metal joints. The authors tried to apply the switch back welding method to butt welding to join discs with flat metal plates without backing plates. During the welding, the gap was detected by processing the weld pool image taken with a CCD camera. Moreover, the tip of the electrode wire is changing owing to a curve of its wire extension in accordance with a rotation of the torch axis. Even though teaching is achieved before the welding, the weaving centre is shifted from the gap centre. The controller of the seam tracking was designed to prevent any steady state error.     

Vision based seam tracking system for underwater flux cored arc welding

Abstract

Manual underwater welding is usually time consuming, expensive and hard to perform because of the rigorous underwater environment. Automatic underwater welding can be performed faster at less cost and with higher quality. An automatic seam tracking system for underwater flux cored arc welding has been developed. It consists of a vision sensing module, a seam recognition module, a fuzzy controller (FC) and an X–Y travel platform. The vision sensing module can capture clear seam images during welding, successfully resolving the problem of welding arc interference during underwater flux cored arc welding. The seam recognition module filters, enhances and thresholds the seam images and then recognises the seam deviation angle with a three layer back propagation neural network. The FC outputs the control parameters according to the seam deviation angle and then controls the X–Y platform to drive the torch to the centre of the seam. In this study, three different welds were considered: a straight line, a kinked straight line and an S curved line. These welds were tracked real timely during underwater flux cored arc welding. The results show that this seam tracking system can meet the requirements of the automatic underwater flux cored arc welding.     

Parametric approach to positional fault detection in short arc welding

Abstract

This work investigates a parametric technique for short arc welding fault detection. The independent component analysis algorithm is applied to split welding voltage and current signals into arcing and short circuiting regions. A series of parameters including means, medians and normalised inner products are calculated by processing the different sections of welding electrical data. Out of position welds in overlap joints are studied with investigation of the connection between parameters and short arc welding features. The effect of changing shielding gas is also illustrated. Figures of merit to quantify the change in various parameters between faulty and good welds are compared and discussed. It is shown that the data separation into two regions with independent component analysis is useful in providing various parameters that can assist in short arc welding fault detection under different conditions.     

Statistics of signature images for arc welding fault detection

Abstract

The present work covers the statistical analysis of signature images for weld quality monitoring and fault detection. Welding signature images are two-dimensional histograms of voltage and current data. Signatures from production welding are compared with reference good welding using a statistical analysis of both the principal components, which are fitted with shifted normal distributions, and the remainders not explained by the principal components, which are fitted with a multidimensional normal distribution. A signature basis set is employed, allowing efficient real time computations. The statistical data fits are illustrated with data from overlap welds, and examples of fault detection with out of position welds are given.     

Misalignment detection and enabling of seam tracking for friction stir welding

Abstract

This paper describes a technique for determining the position of a friction stir welding (FSW) tool with respect to the weld seam during welding. Forces are used as a feedback signal, and a general regression neural network is trained to predict offset position given weld forces. Experimental results demonstrate the accuracy of the developed position predictor. This technique is proposed for online misalignment detection or as a position estimator for in-process tracking of the weld seam for FSW and robotic FSW.     

Voltage change in the GMAW process due to the influence of a droplet travelling in the arc

Abstract

Experimental measurements have been made to investigate the meaning of the fluctuation or noise of electrical signals for the gas metal arc welding process through globular to spray transfer mode, with particular attention being paid to the so-called 'drop spray' transition mode. The results reveal that the welding arc voltage is significantly affected by the molten droplet travelling in the arc. A sharp drop in arc voltage appears just after the detachment of the droplet, reaching its minimum quickly and then recovering, according to the location of the droplet in the arc. Although the full explanation of the feature requires further study, we believe that an important influence is the geometrical effect. The existence of the droplet in the arc path significantly affects the geometrical shape of the arc and arc attachment at the anode, and hence the overall voltage of the arc.     

基于摆动电弧传感的管道焊接焊缝跟踪技术研究现状

基于电弧传感器的焊缝跟踪技术是目前焊接领域的一个重要研究方向,精确的焊缝跟踪可以快速实现焊缝的精确定位,是保证焊接质量的关键。介绍了摆动频率影响跟踪精度的工作原理,综述了电弧传感器的发展与研究现状,分析了各类电弧传感器的应用特点,论述了摆动电弧传感器的在管道焊接机器人系统中集成应用情况。     

CO2焊接超声传感焊缝跟踪控制规则与参数

介绍了一种CO2焊接非接触超声传感焊缝跟踪系统.该系统采用了Fuzzy-P控制理论.由于控制系统的控制规则、控制参数与控制系统性能密切相关,因此,要提高系统的控制性能,必须对系统的控制规则、控制参数进行优化处理.文中首先介绍了Fuzzy-P控制理论和参数自调整模糊控制规则;然后通过计算机仿真研究,确定了参数自调整模糊控制的比例因子α1和α2、系统输出比例因子K等控制参数,确定了Fuzzy-P控制的阈值ev.试验结果表明,采用计算机仿真研究确定的Fuzzy-P控制规则和控制参数是正确的,能够满足实际CO2焊接超声传感焊缝跟踪系统的控制要求.     

基于Kalman滤波的磁控旋转电弧传感器焊缝跟踪偏差预测

针对磁控摆动电弧扫描焊缝获取有用信息量少的问题,提出了一种基于Kalman滤波的磁控旋转电弧传感器焊缝跟踪偏差预测方法. 文中简述了磁控旋转电弧传感器的基本原理,对磁控旋转电弧的运动轨迹进行了仿真,利用位置传感器对电弧进行定位,采用四分圆周采样法,运用Kalman滤波原理进行滤波处理,分析了这种方法的基本原理和计算步骤,在此基础上得到空间曲线焊缝的偏差信息,并引入加权预测矫正因子对焊缝的偏差信息进行预测矫正. 结果表明,该方法用于磁控旋转电弧焊缝自动跟踪可行,提高了焊缝跟踪的精度,为预测方法用于焊缝偏差算法提供了科学依据.     

The characteristics of welding currents in a rotating arc lead tandem 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 of the single electrode GMAW,so the welding speed could be significantly increased in this process.However,the majority of 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-GMA W process seam tracking.     

Artificial neural networks and acoustic emission applied to stability analysis in gas metal arc welding

Abstract

The present paper describes the application of neural networks to obtain a model for estimating the stability of gas metal arc welding (GMAW) process. A neural network has been developed to obtain and model the relationships between the acoustic emission (AE) signal parameters and the stability of GMAW process. Statistical and temporal parameters of AE signals have been used as input of the neural networks; a multilayer feedforward neural network has been used, trained with back propagation method, and using Levenberg Marquardt's algorithm for different network architectures. Different welding conditions have been studied to analyse the incidence of the parameters of the process in acoustic signals. The AE signals have been processed by using the wavelet transform, and have been characterised statistically. Experimental results are provided to illustrate the proposed approach. Finally a statistical analysis for the validation of the experimental results obtained is presented. As a main result of the study, the effectiveness of the application of the artificial neural networks for modelling stability analysis in welding processes has been demonstrated. The regression analysis demonstrates the validity of neural networks to predict the stability of welding process using the statistical characterisation of the signal parameters of AE that have been calculated.     

Arc power and efficiency in gas tungsten arc welding of aluminium

Abstract

A calorimetric study of gas tungsten arc welding of aluminium is described. The present study comprised experiments in which autogenous welding runs were each made on a block of electrical conductor grade aluminium. The blocks were all approximately cubic in shape which, when combined with the high thermal conductivity of aluminium, ensured that their temperature equalised soon after the completion of a run. Each sample was immersed in insulating material before welding so that heat losses to the surroundings were minimised. Thermocouples were attached to the block in each experiment and the bulk temperature rise was related to the energy input associated with the welding run. The effects of arc polarity, alternating current balance, shielding gas composition, arc length and welding current on the arc power and arc efficiency were investigated. The results obtained with alternating current are compared to those for direct current, and the differences are explained.     

视觉传感焊缝跟踪技术的发展状况及实施方案探讨

介绍了用于焊缝跟踪的几种视觉传感方法及控制技术的原理，特点，在此基础上提出了一种基于结构光焊缝激光跟踪系统的实施方案，该方案能够将三维控制转换为一维控制，控制简单，实施容易，对焊缝跟踪系统的研制有一定的参考作用。     

基于ACFM技术的焊缝跟踪传感器设计与实现

根据交变磁场测量法（ACFM）的基本原理，设计了一种由激励线圈和感应线圈组成的交变磁场传感器，可对空间“点”磁场进行测量。通过大量实验，研究了传感器位置和不同焊缝宽度对传感信号的影响规律。根据传感信号的变化规律，提出了相应的信号处理的方法，为ACFM方法用于焊缝跟踪奠定了良好的基础。     

双丝GMAW焊接的电弧干扰和中断分析

为了进一步了解双丝焊接过程中电弧干扰的规律以及有规律的断弧现象,设计了不同焊接电流参数值的匹配系列试验,同步拍摄了电弧形态并采集了两电弧的电流、电压波形.通过理论推导出的双丝电弧的偏移量公式分析了上述试验结果并得到了基本符合的结论：增大另一电弧与该电弧的电流比例,该电弧中断频率增加.最后将高速摄影拍摄到的电弧图片与采集...     

Edge detection and its application to recognition of arc weld image

Abstract Image sensor has been one of the key technologies in intellectualized robotics welding. Edge detection plays an important role when the vision technology is applied in intellectualized welding robotics technologies. There are all kinds of noises in welding environment. The algorithms in common use cannot be applied to the recognition of welding environment directly. The edge of images can be fell into four types. The weld images are classified by the characteristic of welding environment in this paper. This paper analyzes some algorithms of edge detection according to the character of welding image, some relative advantages and disadvantages are pointed out when these algorithms are used in this field, and some suggestions are given. The feature extraction of weld seam and weld pool are two typical problems in the realization of intellectualized welding. Their edge features are extracted and the results show the applicability of different edge detectors. The trndeoff between precision and calculated time is also considered for different application.     

波纹板焊缝跟踪激光传感器的性能研究

采用一种空间漫反射激光测距传感器,研究了波纹板倾斜角与测量结果的关系。在保证被测面上激光光点与传感器之间距离不变的条件下,对不同倾斜角的被测面进行了激光测距试验,并利用Phong光照模型解释了倾角对试验结果的影响。随着被测面倾角增加,传感器测量结果的偏差增大;当倾斜角小于45°时,测量结果的偏差在0.5 mm以内;当倾斜角大于45°时,测量结果的偏差大于0.5 mm。研究结果表明,该激光传感器可以用于检测不大于45°的波纹板,能够满足其折线焊缝跟踪的精度要求。     

侧向风场作用下横向焊接旋转电弧传感及焊缝跟踪

文中利用侧向风场的吹袭作用来抑制横焊熔池的下淌,研究了在侧向风场作用下焊缝成形质量和旋转电弧的传感特性. 提出了一种基于平面拟合的焊枪偏差和电极高度检测算法,实现了同一电流信号下焊枪偏差和电极高度的同时检测. 结果表明,适当控制侧风流量有助于抑制熔池下淌、改善焊缝成形. 但是随着风速的增加,焊接电弧的熄弧率升高、电弧传感的准确性降低. 针对焊接电流的噪声干扰,还设计了软阈值小波滤波算法,并开发了相应的模糊控制算法对焊枪偏差和电极高度进行调节,初步实现了横焊焊缝的成形控制和跟踪.     

An optical sensing system for seam tracking and weld pool control in gas metal arc welding of steel pipe

A visual sensing system was developed for automatic gas metal arc welding (GMAW) of the root pass of steel pipe. The system consisted of a vision sensor that consisted of a charge-coupled device (CCD) camera and lenses, a frame grabber, image processing algorithms, and a computer controller. A specially designed five-axis manipulator was used to position the welding torch and to provide the vision sensor with automatic access to view the welding position. During the root pass welding, an image of the weld pool and its vicinity was captured using the camera without interference of the intensive arc light by viewing at the instance of a short-circuit of the welding power. The captured image was then processed to recognize the weld pool shape. For seam tracking, the manipulator was used to adjust the torch position based upon the pool image to the groove center. The measured gap size was used to determine the appropriate welding conditions to obtain sound penetration. The welding speed was chosen using fuzzy logic with the knowledge of a skilled welder and measured gap. The automatic welding equipment demonstrated that both welding conditions and torch position could be appropriately controlled to obtain a sound weldment and a good seam tracking capability.     

Microstructures and properties of laser/arc hybrid welds and autogenous laser welds in pipeline steels

Abstract

Lasers are capable of producing welds with deep penetration, low distortion and faster travel speeds, compared to arc welding. More recently, laser/arc hybrid welding processes have also been generating interest for industrial fabrication. In this paper, six carbon–manganese, mainly pipeline, steels were welded using both autogenous Nd:YAG laser welding, and Nd:YAG laser/MAG hybrid welding. The improvements in weld microstructures and weld metal toughness that are possible when using the hybrid process are described and illustrated. Laser/arc hybrid welding is shown to be a process that can generate good quality welds in commercially available pipeline steels. It also has the potential to complete girth welds in these steels with significantly fewer welding passes than are currently required for arc welded pipelines, reducing the joint completion time.