Weld Pool Surface Research Articles

Characterization of the underwater welding arc bubble through a visual sensing method

To evaluate the effectiveness of arc bubble, the influences of controllable arc bubble on the process stability and microstructural evolution of welded joint under different welding conditions were investigated. The main welding conditions, including onshore welding, conventional underwater wet welding (UWW) and mechanical constraint assisted UWW (MC-UWW), were characterized and compared. The exerted mechanical constraint resists the arc bubble detachment and keeps the larger arc bubble attached to the weld pool surface for providing better protective effect of welding region. The adverse effect of surrounding water with its higher heat conduction is not negligible compared with onshore welding, and the mechanical coupling between arc bubble and constraint device plays a vital role in affecting the arc stability and joint quality. Microstructure analyses revealed that under the same welding parameters, the proportion of brittle microstructure in weld metal follows the order: UWW > MC-UWW > onshore welding. A more stable wet welding process can be realized by controlling the arc bubble detachment, which provides a new orientation for wet welding technique application.

Supervised Learning of Human Welder Behaviors for Intelligent Robotic Welding

Current industrial welding robots are mostly articulated arms with a pre-programmed set of movement, which lack the intelligence skilled human welders possess. In this paper, human welder's response against 3-D weld pool surface is learned and transferred to the welding robots to perform automated welding tasks. To this end, an innovative teleoperated virtualized welding platform is utilized to conduct dynamic training experiments by a human welder whose arm movements together with the 3-D weld pool characteristic parameters are recorded. The data is off-line rated by the welder and a fuzzy classifier is trained, using an adaptive neuro-fuzzy inference system (ANFIS), to automate the rating. Data from the training experiments are then automatically classified such that top rated data pairs are selected to model and extract “good response” minimizing the effect from “bad operation” made during the training. A supervised ANFIS model is then proposed to correlate the 3-D weld pool characteristic parameters and welder's adjustment on the welding speed. The obtained model is then transferred to the welding robot to perform automated welding task as an intelligent controller. Experiment results verified that the proposed model is able to control the process under different welding current as well as under disturbances in speed and measurement. A foundation is thus established to selectively learn “good response” to rapidly extract human intelligence to transfer into welding robots.

Fusing machine algorithm with welder intelligence for adaptive welding robots

Current industrial welding robots are mostly articulated arms with a pre-programmed set of movement. These robots lack the adaptation and intelligence skilled human welders possess. With the recent developments in measuring 3D weld pool surface in GTAW, the critical process feedback available to human welders also becomes available to welding robots. To effectively use this critical feedback to equip welding robots, welders’ responses to this critical feedback have been modeled. It is arguable that human may have better robustness against process certainties but machine algorithms may be designed to be quicker in response. Switching among them appropriately may improve the performance but should base on a scientific criterion. Further, fusing them together may even better perform than simply switching. In this paper, a criterion is established to automatically rate the performance from each of the three algorithms being fused – one machine algorithm and two human response models/algorithms. A fuzzy system has been proposed and established to fuse the decisions from these algorithms per their performance ratings. Simulation confirms the superiority of the fusion method to any of these three algorithms. Automated welding experiments conducted by welding robot verifies that the fusion based welding speed controller was robust under different welding currents and input disturbances. A foundation is thus established to developing next generation intelligent welding robots by fusing machine and human intelligence.

Welding torch attitude-based study of human welder interactive behavior with weld pool in GTAW

Skilled human welder adjusts welding parameters including the welding torch attitude, moving speed and position to control weld quality and avoid weld defects based on real time observed varying weld pool surface for precision joining using gas tungsten arc welding (GTAW). However, welder behavior/adjustment appears to be a complex reactive response. To understand this complex response and develop intelligent robotic arc welding, a new scheme that correlated welding torch attitude to weld pool surface to study welder behavior in torch adjustment as response to weld pool was proposed and realized. The torch attitude and the 3D weld pool surface were synchronously measured using a wire inertial measuring unit (IMU) and a laser vision-based approach. An image processing algorithm was developed to extract the characteristic parameters of the weld pool surface from the laser stripes reflected by the specular pool surface. The improved quaternion-based unscented Kalman filter was used to estimate the torch orientation from its inertial measurement data, showing that the torch attitude has been obtained with an acceptable error in the order of 1°(x axis and y axis) and 2°(z axis). Several experiments were performed and the correlation of the corresponding data was detailed. It indicates that the change of torch attitude represents the welder's operating skills, welding experience and smart decision. The three characteristic parameters reflect the welder's reactive response on the torch adjustments. The curvature radius of laser stripes can predict the changing trends of the weld pool surface, providing the needed information for welders to make a smart decision. The proposed scheme is feasible for measuring and analyzing the welder's skills and experience.

Influence of molten metal flow on undercutting formation in GMAW

Molten metal flow on weld pool surface in gas metal arc welding process is investigated using a vision-based sensing system and an interpolation algorithm. Bead formation is investigated by analysing flow patterns and its driving forces of weld pool under different welding speed, welding current and shielding gas. Results show that if longitudinal to transverse velocity ratio exceeds 2.0 in the front of weld pool, outward molten metal mainly driven by arc force cannot reach the widest section of the weld pool. Meanwhile, the transverse spreading of molten metal is still hindered in the middle of weld pool as it turns to be inward flow dominated by Marangoni force. These phenomena impede molten metal supply to weld toes which causes undercutting defect. Scaling analysis shows that the predicted undercutting defect agrees well with that resulted from experiments.

Effect of modified flux on MIG arc brazing-fusion welding of aluminum alloy to steel butt joint

Pulsed MIG arc brazing-fusion welding process was applied to realize the butt joining of galvanized steel and 5052 aluminum alloy with no enclosed slot or groove adopted. A modified flux mixture was developed to improve the butt joint performance. After applying the modified flux, weld appearance became better and the spreadability of filler metal was also greatly improved. During brazing-fusion welding process, flux floating on the surface of welding pool weakened the surface tension between filler metal and Fe and reduced the evaporation of Zn, which both led to the greatly enhanced spreadability. The analysis of intermetallic compounds (IMCs) at brazed interface showed that Fe3Al was formed at upper side of steel plate, while Fe2Al5 was formed at other areas with the consideration of its lowest Gibbs free energy under certain temperature range. With modified flux, the tensile strength of the joint could reach up to 120MPa, which was about 60% of that of 5052 aluminum alloy base metal. From the fractured surface, two different fracture modes were identified, tear fracture and intergranular fracture, which confirmed that joint fractured in a brittle mode. The crack initiated at the front side of brazed interface due to the thicker IMCs layer, then propagated to the surface before the whole joint failed. The improved spreadability of filler metal on the top and back sides of steel plate due to the application of flux, contributed to the improvement of joint strength.

Influence of Pilot Gas Composition on Convective Pattern of Weld Pool Surface in Plasma Keyhole Arc Welding

Influence of Pilot Gas Composition on Convective Pattern of Weld Pool Surface in Plasma Keyhole Arc Welding

Influence of the focal position on the melt flow during laser welding of steel

For keyhole laser welding of tempered steel, we show that the characteristic formation of eddies in the melt flow significantly depends on the focal position. The local melt flow velocities and accelerations were analyzed in-situ by means of x-ray imaging. It was observed that the keyhole geometry as well as the direction of rotation of the eddy close to the weld pool surface changes when the focal-position is shifted by one Rayleigh length.

Modelling of bead hump formation in high speed gas metal arc welding

Without any presupposed mechanism, a unified three-dimensional model is developed to predict the formation of humping bead in high speed gas metal arc welding, which considers the three phase coupling of solid, liquid and gas and the effect of shear stress exerting on weld pool surface caused by arc plasma. A strong backward fluid flow in weld pool is identified as the major factor for bead hump formation. The generation of thin liquid transition zone and its premature solidification are two conditions responsible for the occurrence of humped weld. In case of low inner contact angle between the liquid metal and workpiece surface, the bead hump is still generated. With increasing welding current, the bead hump can be suppressed.

Frequency characteristics of weld pool oscillation in pulsed gas tungsten arc welding

A direct relationship exists between the frequency of weld pool oscillation and weld joint penetration. In this paper, a novel laser vision method to detect the weld pool oscillation frequency in traveling pulsed gas tungsten arc welding was proposed. Several experiments with varying weld joint penetrations for traveling welding were conducted, and the frequency was extracted using an image-processing algorithm. The characteristics of weld pool oscillation frequency with different joint penetrations were analyzed from two aspects: surface oscillation and internal flow of liquid metal in the weld pool. Results show an oscillated mode of weld pool surface and an internal flow of partial and full joint penetration, which indicate a single oscillation frequency. In critical joint penetration, weld pool oscillation has the features of partial and full joint penetration, and generate two oscillation frequencies. This study provides a forceful foundation for the accurate detection of different joint penetration statuses.

Study on surface appearance, geometry size, and delta-ferrite content of ZrO2-aided TIG welding of AISI 316LN stainless steel

This study investigated the influence of oxide with a more negative Gibbs free energy (ΔG) on the surface appearance, geometry size, and delta-ferrite (δ-Fe) content of AISI 316LN stainless steel subjected to flux-aided tungsten inert gas (TIG) welding. Powdered ZrO2 of various particle sizes mixed with 80 % water/20 % acetone solution was used as flux. The potential advantages of ZrO2-aided TIG welding were also demonstrated. The results show that nanoscale ZrO2 flux produces a TIG weld with a slag-free surface, but it did not significantly increase the depth-to-width ratio of the weld. The present work also found that ZrO2 flux slag influences the δ-Fe content of AISI 316LN stainless steel weld. ZrO2-aided TIG welding has low tendency to form undercut ting and allows high-speed welding. The potential advantages of the ceramic slag created by the ZrO2 flux are a small tem-perature difference between the center and edges of welding pool surface, a low solidified rate of liquid metal at the rear of the welding pool, as well as alleviation of the arc pressure at the front of the welding pool.

Numerical analysis of undercut defect mechanism in high speed gas tungsten arc welding

A computational fluid dynamics model is developed to investigate undercut defect formation in high speed gas tungsten arc welding (GTAW) process. Double-ellipse arc shear stress model and modified double-ellipse arc heat source and arc pressure models are used, which are self-adaptive to weld pool surface evolution. The heat and mass transfer in weld pool and solidified weld bead profile are simulated and the undercut mechanism are discussed. The prematurely solidified periphery part at maximum width of weld pool is the initiation of undercut defect and the inward velocity component at trailing periphery due to teardrop-shaped weld pool profile promotes subsequent undercut formation, which provides an explanation to the high tendency of undercut formation during high current and high speed welding. The undercut morphology is unremarkably influenced by Marangoni force and the capillary pressure hinders undercut formation to some extent. The developed model is validated by comparing undercut morphology and gouging region profile from both simulation and experiment.

Toward intelligent welding robots: virtualized welding based learning of human welder behaviors

Combining human welders (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next-generation intelligent welding robots that can perform precision welding similar to or even outperform skilled welders. In this study, an innovative human-machine welding paradigm, virtualized welding, is proposed that can transfer human intelligence to welding robots. A welding robot is augmented with sensors to observe the welding process and performs actual welding. A human welder operates a virtual welding torch and freely adjusts its movement in 3D space based on the visual feedback from the sensors. The adjustments together with the reconstructed 3D weld pool surfaces are recorded, analyzed, and utilized to form models representing human welder intelligence. To demonstrate the concepts behind the virtualized welding system and modeling method proposed, human welder’s adjustments are “selectively” learned and transferred to the welding robot to perform automated gas tungsten arc welding (GTAW). Experimental results verified the effectiveness of the learned human response models. A foundation is thus established to rapidly extract human intelligence and transfer it into welding robots.

A mobile sensing system for real-time 3D weld pool surface measurement in manual GTAW

An innovative mobile sensing system has been developed to non-intrusively monitor the manual pipe gas tungsten arc welding (GTAW) process. The system consists of a projective torch held by a welder, and a sensory helmet on the welder’s head. The three-dimensional (3D) weld pool surface is effectively measured in real-time as the welder performs the weld despite the movements of the torch and the helmet. In this study, the sensing system is first analyzed by numerical simulations in which the adjustment boundaries of the torch and helmet, i.e. their translation and orientation ranges, for effective sensing have been determined. Then, the sensing system is further evaluated using a simulation platform in which the movements of the helmet/welder’s head is mimicked by a tripod head with 6 degree-of-freedom (DOF), and a convex spherical mirror with a comparable size of a typical weld pool in a GTAW process is applied as a weld pool substitute. The effectiveness of the proposed system is validated by successfully capturing laser reflections from the mirror without great constraints on the welder’s movements of the torch and the helmet. Based on the analysis of the spatial relations among the torch, the helmet and the weld pool, an innovative real-time algorithm is proposed to reconstruct the 3D weld pool surface. The effectiveness and robustness of the algorithm have been verified by accurately reconstructing the convex spherical mirror surface despite the movements of the torch and the helmet in the simulation platform.

Effect of Active Gas on Weld Shape and Microstructure of Highly Efficient TIG Welded A516 Low Carbon Steel

A highly efficient TIG welding method was performed to increase the weld penetration and compared with the conventional TIG welding process. A double-shielded gas flow system was designed to apply Ar + CO2 mixed gas as the outer layer, while the inner layer remained pure argon to impede oxidation of the electrode. The results demonstrate that the addition of the active gas to the molten pool controls the Marangoni convection on the liquid pool surface so that the weld shape changes from a shallow shape to a deep and narrow weld pool owing to the change in direction of Marangoni convection. The increase in CO2 content from 0.5 to 2 % leads to the reduction in the weld depth which is due to the formation of a thick oxide layer on the weld pool surface and reduction in the interface between the shielding gas and the weld pool. Moreover, Preheating of the samples causes the formation of deeper fusion zone profiles which can be attributed to the slow cooling rate and the increase of heat concentration in the weld pool.

Weld pool surface temperature measurement from polarization state of thermal emission

This paper presents a passive polarimetry method using a division of aperture optical device in order to measure the temperature distribution at the weld pool surface. Thermal emission from a hot liquid metal was investigated at a near-infrared wavelength corresponding to a blind spectral window of a helium plasma generated during gas tungsten arc welding process. The refractive index of liquid metal and the surface radiance are deduced from the polarisation state of thermal emissions. Based upon the knowledge of both characteristics, the temperature distribution can be calculated.

Dynamic nonlinear modeling of 3D weld pool surface in GTAW

Abstract As the weld pool contains abundant information about the welding process, the skilled welder always utilizes the observed information to control the weld pool to get a good weld quality. In this paper, a real-time vision sensing technology is used as the eyes of the welder to observe the gas tungsten arc welding (GTAW) pool surface and a 3D reconstruction technology is used to reconstruct the observed weld pool surface in three-dimensions. The geometric parameters are obtained from the reconstructed pool surface. Step responses are conducted to acquire the relationship between the weld pool geometric parameters and the random variation of current, and the time-domain analysis of the system is done. Various random experiments are also conducted and the dynamic relationship of the weld current and the weld pool geometric parameters is established by means of a non-linear Hammerstein model.

3D Reconstruction Algorithm of Weld Pool Surface Based on Computer Vision Technology

As is well known that sensing and measuring the weld pool surface is very important to design intelligent weld- ing machines which is able to imitate a skilled human welder who can choose suitable welding parameters. Therefore, in this paper, we concentrate the problem of weld pool surface 3D reconstruction, which is a key issue in intelligent welding machines development. Firstly, the framework of the weld pool surface 3D reconstruction system is described. The weld pool surface 3D reconstruction system uses a single camera stereo vision system to extract original data from weld pool, and then the left and right image are collected. Afterwards, we utilize Pixel difference square and matching algorithm and Stereo matching algorithm to process images. Next, the 3D reconstruction of weld pool surface is constructed using the point cloud data. Secondly, stereo matching based weld pool surface 3D reconstruction algorithm is illustrated. In this al- gorithm, the matching cost function is computed through the Markov random field, and then the weighted matching cost is calculated via the guided filter. Thirdly, to test the performance of our proposed algorithm, we develop an experimental platform to measure weld pool width, length, convexity and the previous inputs based on a linear model predictive con- troller. Experimental results demonstrate that the proposed 3D reconstruction algorithm of weld pool surface can achieve high quality under both current disturbance and speed disturbance.

3D Reconstruction Algorithm of Weld Pool Surface Based on Computer Vision Technology

As is well known that sensing and measuring the weld pool surface is very important to design intelligent welding machines which is able to imitate a skilled human welder who can choose suitable welding parameters. Therefore, in this paper, we focused on the problem of weld pool surface 3D reconstruction, which is a key issue in intelligent welding machines development. Firstly, the framework of the weld pool surface 3D reconstruction system is described. The weld pool surface 3D reconstruction system uses a single camera stereo vision system to extract original data from weld pool, and then the left and right images are collected. Afterward, we utilize Pixel difference square and matching algorithm and Stereo matching algorithm to process images. Next, the 3D reconstruction of weld pool surface is constructed using the point cloud data. Secondly, stereo matching based weld pool surface 3D reconstruction algorithm is illustrated. In this algorithm, the matching cost function is computed through the Markov random field, and then the weighted matching cost is calculated via the guided filter. Thirdly, to test the performance of our proposed algorithm, we develop an experimental platform to measure weld pool width, length, convexity and the previous inputs based on a linear model predictive controller. Experimental results demonstrate that the proposed 3D reconstruction algorithm of weld pool surface can achieve high quality under both current disturbance and speed disturbance.

Numerical investigation of weld pool behaviors and ripple formation for a moving GTA welding under pulsed currents

The complex transport phenomena and their effects on the weld pool dynamics and surface rippling in moving gas tungsten arc welding (GTAW) under pulsed currents are studied by using a 3D transient numerical model. The distributions of the melt-flow velocity and temperature, and weld bead formation are simulated. The effects of welding conditions, including welding current waveform, pulse frequency and welding speed, on the weld penetration, formation and final appearance of ripples are discussed. It is found that surface ripples are formed under pulsed current due to the up-and-down weld pool motion, caused mainly by the periodically varied current and solidification rate of weld pool. The results show that for the cases with the same average current, the pulsed current leads to the deeper weld penetration than continuous current, and the higher peak current corresponds to the higher ripples and deeper penetration. The larger pulse frequency results in the more uniform thermal energy distributions on the workpiece and tends to decrease the solidification rate, leading to the more uniform penetration depths, the smaller pitch and height of the ripples. A slow travel speed is helpful to reduce pitch of the ripples but also at the risk of the reduced effective penetration. Finally, a GTAW experiment for the case of continuous current is conducted to validate the modeling predictions in terms of weld width, penetration depth and the formation of ripples.