Electric arc shape and weld bead geometry analysis under the electromagnetic constriction and expansion effect

The present study deals with the extended version of our previous research work. In this article, for predicting the entire weld bead geometry and engineering stress–strain curve of the cold metal transfer (CMT) weldment, a MATLAB based application window (second version) is developed with certain modifications. In the first version, for predicting the entire weld bead geometry, apart from weld bead characteristics, x and y coordinates (24 from each) of the extracted points are considered. Finally, in the first version, 53 output values (five for weld bead characteristics and 48 for x and y coordinates) are predicted using both multiple regression analysis (MRA) and adaptive neuro fuzzy inference system (ANFIS) technique to get an idea related to the complete weld bead geometry without performing the actual welding process. The obtained weld bead shapes using both the techniques are compared with the experimentally obtained bead shapes. Based on the results obtained from the first version and the knowledge acquired from literature, the complete shape of weld bead obtained using ANFIS is in good agreement with the experimentally obtained weld bead shape. This motivated us to adopt a hybrid technique known as ANFIS (combined artificial neural network and fuzzy features) alone in this paper for predicting the weld bead shape and engineering stress–strain curve of the welded joint. In the present study, an attempt is made to evaluate the accuracy of the prediction when the number of trials is reduced to half and increasing the number of data points from the macrograph to twice. Complete weld bead geometry and the engineering stress–strain curves were predicted against the input welding parameters (welding current and welding speed), fed by the user in the MATLAB application window. Finally, the entire weld bead geometries were predicted by both the first and the second version are compared and validated with the experimentally obtained weld bead shapes. The similar procedure was followed for predicting the engineering stress–strain curve to compare with experimental outcomes.

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Prediction and optimization of weld bead geometry in gas metal arc welding process using RSM and fmincon

Journal of Mechanical Engineering Research ◽

10.5897/jmer2013.0271 ◽

2013 ◽

Vol 5 (8) ◽

pp. 154-165 ◽

Cited By ~ 10

Author(s):

P. Sreeraj

Keyword(s):

Arc Welding ◽

Gas Metal Arc Welding ◽

Welding Process ◽

Weld Bead ◽

Bead Geometry ◽

Weld Bead Geometry ◽

Metal Arc Welding ◽

Arc Welding Process

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Assessment of weld bead geometry in modified shortcircuiting gas metal arc welding process for low alloy steel

Materials and Manufacturing Processes ◽

10.1080/10426914.2021.1906897 ◽

2021 ◽

pp. 1-19

Author(s):

Din Bandhu ◽

Kumar Abhishek

Keyword(s):

Alloy Steel ◽

Arc Welding ◽

Gas Metal Arc Welding ◽

Welding Process ◽

Weld Bead ◽

Bead Geometry ◽

Low Alloy Steel ◽

Weld Bead Geometry ◽

Metal Arc Welding ◽

Arc Welding Process

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Evaluation of the Effect of the Water in the Contact Tip on Arc Stability and Weld Bead Geometry in Underwater Wet FCAW

Soldagem & Inspeção ◽

10.1590/0104-9224/si2204.11 ◽

2017 ◽

Vol 22 (4) ◽

pp. 401-412 ◽

Cited By ~ 1

Author(s):

Marcelo Teodoro Assunção ◽

Alexandre Queiroz Bracarense

Keyword(s):

Weld Bead ◽

Bead Geometry ◽

Weld Bead Geometry ◽

Arc Stability

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A Model for In-Process Control of Thermal Properties During Welding

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.3153017 ◽

1989 ◽

Vol 111 (1) ◽

pp. 40-50 ◽

Cited By ~ 15

Author(s):

C. C. Doumanidis ◽

D. E. Hardt

Keyword(s):

Process Control ◽

Thermal Response ◽

Weld Bead ◽

Distributed Parameter ◽

Bead Geometry ◽

Actual Process ◽

Weld Bead Geometry ◽

Thermally Activated ◽

Real Time Tracking ◽

Welding Processes

The control of welding processes has received much attention in the past decade, with most attention placed on real-time tracking of weld seams. The actual process control has been investigated primarily in the context of weld bead geometry regulation, ignoring for the most part the metallurgical properties of the weld. This paper addresses the latter problem through development of a model for in-process control of thermally activated material properties of weld. In particular, a causal model relating accessible inputs to the outputs of weld bead area, heat affected zone width, and centerline cooling rate at a critical temperature is developed. Since the thermal system is a distributed parameter, nonlinear one, it is modelled numerically to provide a baseline of simulation information. Experiments are performed that measure the thermal response of actual weldments and are used to calibrate the simulation and then to verify the basic dynamics predicted. Simulation results are then used to derive a locally linear transfer function matrix relating inputs and outputs. These are shown to be nonstationary, depending strongly upon the operating point and the boundary conditions.

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Predicting Bead Geometry of 2F-Fillet Joint Welded by Small Wire SAW

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.576.185 ◽

2012 ◽

Vol 576 ◽

pp. 185-188 ◽

Cited By ~ 2

Author(s):

Shahfuan Hanif Ahmad Hamidi ◽

Abdul Ghalib Tham ◽

Yupiter H.P. Manurung ◽

Sunhaji Kiyai Abas

Keyword(s):

Welding Current ◽

Weld Bead ◽

Welding Parameter ◽

Bead Geometry ◽

Weld Bead Geometry ◽

Absolute Deviation ◽

Fillet Weld ◽

Welding Condition ◽

Code Of Practice ◽

The Cost

The cost of development of WPS will be very expensive if the welding parameter is selected based on trial and error. Optimal welding condition cannot be easily guessed unless the operator has records of good welding. If a calculator that can predict the welding parameter for the desired bead geometry accurately, such tool will be extremely useful for any fabrication industry. This paper intends to investigate the correlation between the welding parameter and weld bead geometry of 2F position T-fillet carbon steel, when welded by 1.2 mm diameter wire submerged arc welding. Keeping only one parameter as variable, 2F fillet weld coupons are welded by SAW with a range of welding current, welding voltage and welding speed. Only weld bead geometry that complied with the quality requirement of code of practice AWS D1.1 is considered. The trendline graph is created to fit the correlation between the heat input and the fillet weld geometry. By incorporating the trendline formulas into the calculator, the weld bead geometry can be predicted accurately for any welding parameter. The mean absolute deviation (MAD) between the predicted geometry and the experimental results is less than 0.50mm.

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Development of Mathematical Models for Prediction of Weld Bead Geometry of GTAW Stainless Steel

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.867.88 ◽

2017 ◽

Vol 867 ◽

pp. 88-96

Author(s):

S.M. Ravikumar ◽

P. Vijian

Keyword(s):

Stainless Steel ◽

Process Parameters ◽

Welding Current ◽

Weld Bead ◽

304 Stainless Steel ◽

Graphical Form ◽

Bead Geometry ◽

Depth Of Penetration ◽

Weld Bead Geometry ◽

Bead Width

Welding input process parameters are playing a very significant role in determining the weld bead quality. The quality of the joint can be defined in terms of properties such as weld bead geometry, mechanical properties and distortion. Experiments were conducted to develop models, using a three factor, five level factorial design for 304 stainless steel as base plate with ER 308L filler wire of 1.6 mm diameter. The purpose of this study is to develop the mathematical model and compare the observed output values with predicted output values. Welding current, welding speed and nozzle to plate distance were chosen as input parameters, while depth of penetration, weld bead width, reinforcement and dilution as output parameters. The models developed have been checked for their adequacy. Confirmation experiments were also conducted and the results show that the models developed can predict the bead geometries and dilution with reasonable accuracy. The direct and interaction effect of the process parameters on bead geometry are presented in graphical form.

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Experimental and Numerical Analysis on TIG Arc Welding of Stainless Steel Using RSM Approach

Metals ◽

10.3390/met11101659 ◽

2021 ◽

Vol 11 (10) ◽

pp. 1659

Author(s):

Sasan Sattarpanah Karganroudi ◽

Mahmoud Moradi ◽

Milad Aghaee Attar ◽

Seyed Alireza Rasouli ◽

Majid Ghoreishi ◽

...

Keyword(s):

Heat Flux ◽

Stainless Steel ◽

Welding Speed ◽

Arc Welding ◽

Welding Process ◽

Weld Bead ◽

Bead Geometry ◽

Depth Of Penetration ◽

Weld Bead Geometry ◽

Bead Width

This study involves the validating of thermal analysis during TIG Arc welding of 1.4418 steel using finite element analyses (FEA) with experimental approaches. 3D heat transfer simulation of 1.4418 stainless steel TIG arc welding is implemented using ABAQUS software (6.14, ABAQUS Inc., Johnston, RI, USA), based on non-uniform Goldak’s Gaussian heat flux distribution, using additional DFLUX subroutine written in the FORTRAN (Formula Translation). The influences of the arc current and welding speed on the heat flux density, weld bead geometry, and temperature distribution at the transverse direction are analyzed by response surface methodology (RSM). Validating numerical simulation with experimental dimensions of weld bead geometry consists of width and depth of penetration with an average of 10% deviation has been performed. Results reveal that the suggested numerical model would be appropriate for the TIG arc welding process. According to the results, as the welding speed increases, the residence time of arc shortens correspondingly, bead width and depth of penetration decrease subsequently, whilst simultaneously, the current has the reverse effect. Finally, multi-objective optimization of the process is applied by Derringer’s desirability technique to achieve the proper weld. The optimum condition is obtained with 2.7 mm/s scanning speed and 120 A current to achieve full penetration weld with minimum fusion zone (FZ) and heat-affected zone (HAZ) width.

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