Validation of evaporation-determined model of arc-cathode coupling in the peak current phase in pulsed GMA welding

2021 ◽  
Author(s):  
Marek Sebastian Simon ◽  
Oleg Mokrov ◽  
Rahul Sharma ◽  
Uwe Reisgen ◽  
Guokai Zhang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Weld Pool ◽  
Cathode Surface ◽  
Gma Welding ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Qualitative Reasoning ◽  
Current Phase ◽  
Temperature Plasma ◽  
Peak Current

Abstract A first experimental validation of the EDACC (evaporation-determined arc-cathode coupling) model is performend by comparing the experimental and simulated current in the peak current phase of a pulsed GMAW (gas metal arc welding) process. For this, the EDACC model was extended to limit the cathode surface temperature to a realistic value of <2400K. The information on the plasma for the EDACC model was gathered from literature and extrapolated and extended according to qualitative reasoning. The information on the cathode surface of the EDACC model was derived from a steady-state simulation of the weld pool, using an averaging approach over time for the energy and current. The weld pool surface temperature was compared to pyrometric measurements, that were performed for this work, and the agreement was found to be fair. The observed agreement between the modelled and experimentally determined current was within 10%. As strong assumptions were made for the comparison, the validation cannot be considered as final, but the assumptions are thoroughly analyzed and discussed. However the critical link between surface temperature, plasma temperature and total current transmitted could be reconstructed.

Transport Phenomena and Their Effect on Weld Quality in GMA Welding of Aluminum Alloys

Volume 3 ◽  
2004 ◽  
Author(s):  
H. Guo ◽  
H. L. Tsai ◽  
P. C. Wang
Keyword(s):  
Aluminum Alloys ◽  
Weld Pool ◽  
Gma Welding ◽  
Gas Metal Arc Welding ◽  
Welding Current ◽  
Weld Penetration ◽  
Three Dimensional Model ◽  
End Effects ◽  
Welding Arc ◽  
Micro Cracks

Gas metal arc welding (GMAW) of aluminum alloys has recently become popular in the auto industry to increase fuel efficiency of a vehicle. In many situations, the weld is short (say, less than two inches) and the “end effects” become very critical in determining the strength of the weld. At the beginning stage of the welding, when the metal is still “cold”, which is frequently called cold weld, limited weld penetration occurs. On the other hand, at the ending stage of the welding, a “crater” is formed involving micro-cracks and micro-pores. Both the cold weld and the crater can significantly decrease the strength of the weld and are more severe for aluminum alloys as compared to steels. Hence, there are strong needs to improve the GMAW process in order to reduce or eliminate the aforementioned end effects. In this paper, both mathematical modeling and experiments have been conducted to study the beginning stage, ending stage, as well as the quasi-steady-state stage of GMA welding of aluminum alloys. In the modeling, a three-dimensional model using the volume-of-fluid (VOF) method is employed to handle the free surfaces associated with the impingement of droplets into the weld pool and the weld pool dynamics. Transient weld pool shapes and the distributions of temperature and velocity in the weld pool are calculated. The predicted solidified weld bead shapes, including weld penetration and/or reinforcement, are in agreement with experimental results for welds in the aforementioned three stages. It was found that the thickness of the molten weld pool is smaller and there is no vortex developed, as compared to steel welding. The lack of penetration in cold weld is due to the lack of pre-heating by the welding arc. Three techniques are proposed and validated numerically to improve weld penetration by increasing the energy input at the beginning stage of the welding. The crater formation is caused by rapid solidification of the weld pool when the welding arc is terminated. By reducing welding current and reversing the welding direction before terminating the arc, the weld pool is maintained “hot” for a longer time allowing melt flow to fill-up the crater. This method is validated experimentally and numerically to be able to eliminate the formation of the crater and the associated micro-cracks.

scholarly journals An adaptive approach to compensate seam tracking error in robotic welding process by a moving fixture

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881620
Author(s):  
Reza Ebrahimpour ◽  
Rasul Fesharakifard ◽  
Seyed Mehdi Rezaei
Keyword(s):  
Weld Pool ◽  
Arc Welding ◽  
Sliding Mode ◽  
Gas Metal Arc Welding ◽  
Tracking Error ◽  
Welding Process ◽  
Seam Tracking ◽  
Ball Screw ◽  
Robotic Welding ◽  
Metal Arc Welding

Welding is one of the most common method of connecting parts. Welding methods and processes are very diverse. Welding can be of fusion or solid state types. Arc welding, which is classified as fusion method, is the most widespread method of welding, and it involves many processes. In gas metal arc welding or metal inert gas–metal active gas, the protection of the molten weld pool is carried out by a shielding gas and the filler metal is in the form of wire which is automatically fed to the molten weld pool. As a semi-metallic arc process, the gas metal arc welding is a very good process for robotic welding. In this article, to conduct the metal active gas welding torch, an auxiliary ball screw servomechanism is proposed to move under a welder robot to track the welded seam. This servomechanism acts as a moving fixture and operates separately from the robot. At last, a decentralized control method based on adaptive sliding mode is designed and implemented on the fixture to provide the desired motion. Experimental results demonstrate an appropriate accuracy of seam tracking and error compensation by the proposed method.

scholarly journals Prediction of GMA Welding Characteristic Parameter by Artificial Neural Network System

2014 ◽  
Vol 1061-1062 ◽  
pp. 481-491 ◽  
Author(s):  
Il Soo Kim ◽  
Ji Hye Lee ◽  
Javad Malekani ◽  
Prasad K.D.V. Yarlagadda
Keyword(s):  
Intelligent Systems ◽  
Gma Welding ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Optimal Number ◽  
Ann Model ◽  
Data Set ◽  
Advantages And Disadvantages ◽  
Marquardt Algorithm ◽  
Artificial Neural

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

Effects of Welding Current on Metal Transfer and Weld Pool Dynamics in Gas Metal Arc Welding

2006 ◽  
Author(s):  
J. Hu ◽  
H. L. Tsai ◽  
P. C. Wang
Keyword(s):  
Weld Pool ◽  
Arc Welding ◽  
Gma Welding ◽  
Gas Metal Arc Welding ◽  
Metal Transfer ◽  
Dominant Factor ◽  
Transient Temperature ◽  
Transfer Mode ◽  
Metal Arc Welding ◽  
Metal Transfer Mode

In gas metal arc welding (GMAW), current is one of the most important factors affecting the mode of metal transfer and subsequently the weld quality. Recently, a new technology using pulsed currents has been employed to achieve the one droplet per pulse (ODPP) metal transfer mode with the advantages of low average currents, a stable and controllable droplet generation, and reduced spatter. In this paper, the comprehensive model recently developed by the authors was used to study the influences of different current profiles on the droplet formation, metal transfer, and weld pool dynamics in GMA, welding. Five types of welding currents were studied, including two constant currents and three waveform currents. In each type, the transient temperature and velocity distributions of the arc plasma and the molten metal, and the shapes of the droplet and the weld pool were calculated. The results showed that a higher electromagnetic force was generated at a higher current and becomes the dominant factor that detaches the droplet from the electrode tip. A smaller droplet size and a higher droplet frequency were obtained for a higher current. The model has demonstrated that a stable ODPP metal transfer mode can be achieved by choosing a current with proper waveform for given welding conditions.

A Study on the Three-Dimensional Analysis of Heat and Fluid Flow in Gas Metal Arc Welding Using Boundary-Fitted Coordinates

1994 ◽  
Vol 116 (1) ◽  
pp. 78-85 ◽  
Author(s):  
J.-W. Kim ◽  
S.-J. Na
Keyword(s):  
Surface Tension ◽  
Fluid Flow ◽  
Weld Pool ◽  
Surface Deformation ◽  
Driving Forces ◽  
Gma Welding ◽  
Gas Metal Arc Welding ◽  
Three Dimensional ◽  
Weld Bead ◽  
Surface Boundary

Computer simulation of three-dimensional heat transfer and fluid flow in gas metal arc (GMA) welding has been studied by considering the three driving forces for weld pool convection, that is the electromagnetic force, the buoyancy force, and the surface tension force at the weld pool surface. Molten surface deformation, particularly in the case of GMA welding, plays a significant part in the actual weld size and should be considered in order to accurately evaluate the weld pool convection. The size and profile of the weld pool are strongly influenced by the volume of molten electrode wire, impinging force of the arc plasma, and surface tension of molten metal. In the numerical simulation, difficulties associated with the irregular shape of the weld bead have been successfully overcome by adopting a boundary-filled coordinate system that eliminates the analytical complexity at the weld pool and bead surface boundary. The method used in this paper has the capacity to determine the weld bead and penetration profile by solving the surface equation and convection equations simultaneously.

An Improved Weld Seam Extraction Method Using Saliency Detection for Pipe-Line Welding Based on GMAW and Passive Light

2014 ◽  
Vol 598 ◽  
pp. 160-163 ◽  
Author(s):  
Pei Yun Zhou ◽  
Jing Li ◽  
Ning Min Shen ◽  
Fang Li
Keyword(s):  
Weld Pool ◽  
Weld Seam ◽  
Saliency Detection ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Seam Tracking ◽  
Metal Arc Welding ◽  
Pipe Line ◽  
Weld Seam Extraction ◽  
The Right

To meet the need of the automation and intelligence of welding process, it’s very important to extract the edge of weld seam accurately for seam tracking. According to the characteristics of GMAW (gas metal arc welding), an image sensing system of weld pool region based on CCD (Charge-coupled Device) is established. An improved method of weld seam extraction is presented. Firstly, weld pool region localization method using saliency detection is proposed, and weld seam region is obtained from the right edge of weld pool, then Sobel transformation and computation model is used to extract the edge of weld seam. Experimental results show that our method can obtain a more accurate weld seam edge and cost less than other method.

Solid Freeform Fabrication by GMA Welding: Geometry Modeling, Adaptation and Control

1999 ◽  
Author(s):  
Yong-Min Kwak ◽  
Charalabos Doumanidis
Keyword(s):  
Shape Control ◽  
Laser Scanning ◽  
Gma Welding ◽  
Solid Freeform Fabrication ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Full Density ◽  
Surface Geometry ◽  
Bead Width ◽  
Freeform Fabrication

Abstract This paper introduces the Gas Metal Arc Welding process with deposition shape control to solid freeform fabrication for large sculpted metal objects and rapid tooling of molds and dies. Besides full density and toughness properties, GMAW deposition must ensure near-net-shape surface geometry. To this end, an analytical model of deposited morphology is derived, based on linearized superposition of ellipsoidal unit deposition globules. The time-varying parameters of these primitives are identified in-process using laser scanning measurements of the bead width. An experimental description of width on the GMAW inputs is also established. On this basis, bead width control through the wire feed is implemented in real time, using Smith prediction to cope with sensor delays, and feedforward to compensate for the predeposited terrain. This controller was validated in the laboratory, in stainless steel deposition in single and overlaid beads.

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