Determination of welding heat source parameters from actual bead shape

Azar, Amin S.; Ås, Sigmund Kyrre; Akselsen, Odd M.

doi:10.1016/j.commatsci.2011.10.025

Cited by 80 publications

(31 citation statements)

References 10 publications

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“…Quality is very vital in the welding process and it is important to note that the weld bead plays a major role in achieving the desired quality. The quality of the weld bead geometry and configuration are controlled by various welding process input parameters such as current, voltage and welding speed [13]. Liquid weld metal solidification during welding results in interfacial tensions that usually determine the final bead geometry [14].…”

Section: Characteristics Of Weld Bead Geometrymentioning

confidence: 99%

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Development of an Artificial Intelligence Powered TIG Welding Algorithm for the Prediction of Bead Geometry for TIG Welding Processes using Hybrid Deep Learning

Kesse

Buah

Handroos

et al. 2020

Metals

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Recent developments in artificial intelligence (AI) modeling tools allows for envisaging that AI will remove elements of human mechanical effort from welding operations. This paper contributes to this development by proposing an AI tungsten inert gas (TIG) welding algorithm that can assist human welders to select desirable end factors to achieve good weld quality in the welding process. To demonstrate its feasibility, the proposed model has been tested with data from 27 experiments using current, arc length and welding speed as control parameters to predict weld bead width. A fuzzy deep neural network, which is a combination of fuzzy logic and deep neural network approaches, is applied in the algorithm. Simulations were carried out on an experimental test dataset with the AI TIG welding algorithm. The results showed 92.59% predictive accuracy (25 out of 27 correct answers) as compared to the results from the experiment. The performance of the algorithm at this nascent stage demonstrates the feasibility of the proposed method. This performance shows that in future work, if its predictive accuracy is improved with human input and more data, it could achieve the level of accuracy that could support the human welder in the field to enhance efficiency in the welding process. The findings are useful for industries that are in the welding trade and serve as an educational tool.

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Section: Characteristics Of Weld Bead Geometrymentioning

confidence: 99%

“…Metals 2020, 10, x FOR PEER REVIEW 4 of 14 and welding speed [13]. Liquid weld metal solidification during welding results in interfacial tensions that usually determine the final bead geometry [14].…”

Section: Characteristics Of Weld Bead Geometrymentioning

confidence: 99%

Development of an Artificial Intelligence Powered TIG Welding Algorithm for the Prediction of Bead Geometry for TIG Welding Processes using Hybrid Deep Learning

Kesse

Buah

Handroos

et al. 2020

Metals

View full text Add to dashboard Cite

show abstract

“…Radius of the cylinder heat source r 2 was equal to the laser beam radius at focus, and radius of the surface heat flow r 1 was set to be 2r 2 , shown in Table 2. While the energy ratio of the surface heat flow e 1 and the body cylinder heat source e 2 , and the height of the cylinder heat source h were semi-empirical parameters [30,31], and values of these parameters at different simulation cases are shown in Table 3.…”

Section: Heat Source Modelmentioning

confidence: 99%

Effects of interfaces on heat transfer in laser welding of electrical steel laminations

Wang

Zhang

Lai

2015

International Journal of Heat and Mass Transfer

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“…Winczek applied the bimodal heat source model to establish a temperature field analytical model, which could well analyze the temperature of the multi-pass GMAW in the infinite body model [22].Some scholars have proposed some methods for determining the parameters of heat source models based on the geometry of the molten pool. A method named 'discretely distributed point heat source model' was developed by Azar to study the relationship between the experimentally measured data and the source model, the model divided the ellipsoid heat source model into the horizontal and vertical directions of the ellipsoidal heat source, and the parameters were determined based on the geometry of the molten pool [23]. Besides, according to the geometry of the oval pool of submerged arc welding, the oval heat source model was proposed by Aniruddha Ghosh, A. et al [24].…”

mentioning

confidence: 99%

Numerical Simulation and Experimental Research on Temperature Distribution of Fillet Welds

Zuo

Wang

et al. 2020

Materials

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In this paper, a matrix equation for the welding heat source model was proposed to calculate the fillet welds temperature distribution based on the penetration depth and molten width. A double ellipsoid heat source model of fillet weld was established firstly by physical experiment and simulation calculation, and then the orthogonal experiment was constructed based on the previous calculation methods and experimentally measured data. Finally, the matrix equation of the heat source model parameters was obtained by regression analysis based on the joint penetration and width. The experimental and numerical simulation of the temperature distribution had been performed for the fillet weld and the results show that (1) the heat flux increases in one direction, while, oppositely, it decreased in another direction; (2) simulation results were highly in accordance with experiments results. The results indicated that the double ellipsoidal heat source model calculated by the matrix equation is quite appropriate for predicting the transient temperature distribution on the fillet welds for the gas metal arc welding process.Materials 2020, 13, 1222 2 of 11 for calculating residual stress, deformation, and solidification [16,17]. First of all, the premise of obtaining an accurate temperature field was to formulate a heat source model that was consistent with the actual situation. A welding heat source model was established by Rosenthal's application of Fourier's law (that is, point, line, and surface heat sources), which could reasonably calculate the transient temperature distribution at a certain distance from the heat source. Rosenthal's analysis, however, is less accurate for the temperature in or near the fusion and heat-affected zones because the scheme defined that the physical properties of the material did not change with temperature. To overcome most of these limitations, other forms of heat source models have been proposed. It was worth mentioning that the double ellipsoid heat source model was proposed by Goldak, which could well describe the arc welding heat source model [18].Due to the development of computers, welding numerical simulations has made great progress [19]. A 3-D heat transfer model has been established by Kim et al., in which the temperature, weld pool shape, and the weld pool reinforcement surface during gas-metal arc fillet welding were analyzed. In the establishment of this model, not only the heat transfer from the welding arc was considered, but also the thermal effect of metal droplets was considered by the volume heat source [20]. By summarizing the calculation of the temperature field of the predecessors, the transient temperature analytical equation of the semi-infinite body under the three-dimensional motion heat source was obtained by Fachinotti et al. [21]. Winczek applied the bimodal heat source model to establish a temperature field analytical model, which could well analyze the temperature of the multi-pass GMAW in the infinite body model [22].Some scholars have proposed some methods...

show abstract

Determination of welding heat source parameters from actual bead shape

Cited by 80 publications

References 10 publications

Development of an Artificial Intelligence Powered TIG Welding Algorithm for the Prediction of Bead Geometry for TIG Welding Processes using Hybrid Deep Learning

Development of an Artificial Intelligence Powered TIG Welding Algorithm for the Prediction of Bead Geometry for TIG Welding Processes using Hybrid Deep Learning

Effects of interfaces on heat transfer in laser welding of electrical steel laminations

Numerical Simulation and Experimental Research on Temperature Distribution of Fillet Welds

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