Review of current waveform control effects on weld geometry in gas metal arc welding process

Mvola, Belinga; Kah, Paul; Layus, Pavel

doi:10.1007/s00170-018-1879-z

Cited by 44 publications

(17 citation statements)

References 35 publications

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“…Arc heat is the main heat source during the arc period. In order to compare the heating power of different waveform control methods to the weld pool, Equation (1) was used to calculate the welding power for all waveform control methods, Equations (2) and (3) were used to calculate the welding line energy on the base metal [12,13].…”

Section: The Metal Transfer Process and Impact On The Weld Poolmentioning

confidence: 99%

“…Currently, there are a variety of S-GMAW waveform control methods on the market, which can be divided into two types. The first method is represented by Surface Tension Transfer (STT) [2] and Cold Arc process [3]. This type of methods reduces the circuit current at the beginning and end of the short circuit period to permit a smooth touch and break of the bridge of the molten metal, preventing spatter.…”

Section: Introductionmentioning

confidence: 99%

“…The liquid bridge explosion is related to the instantaneous power density of liquid bridge metal. (2) The weld pool oscillation is triggered by the pressure of the electric explosion. The oscillation of the weld pool can be monitored visually by high-speed photography imaging.…”

mentioning

confidence: 99%

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Study on Short-Circuiting GMAW Pool Behavior and Microstructure of the Weld with Different Waveform Control Methods

Chen

Xue

Wang

et al. 2019

Metals

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In order to study internal relation among the behavior of the weld pool, the microstructure of weld bead and the waveform of short-circuiting gas metal arc welding (S-GMAW), a high speed photograph-images analysis system was formed to extract characteristics of weld pool behavior. Three representative waveform control methods were used to provide partly and fully penetrated weld pools and beads. It was found that the behavior of the weld pool was related to the instantaneous power density of the liquid bridge at the break-up time. Weld pool oscillation was triggered by the explosion of the liquid bridge, the natural oscillation frequencies were derived by the continuous wavelet transform. The change of weld pool state caused the transition of oscillation mode, and it led to different nature oscillation frequencies between partial and full penetration. Slags flow pattern could be an indication of the weld pool flow. Compared with the scattered slags on fully penetrated weld pool, slag particles accumulated on partially penetrated weld pools. The oscillating promoted the convection of the welding pool and resulted in larger melting width and depth, the grain size, and the content of pro-eutectoid ferrite in the weld microstructure of S235JR increased, the content of acicular ferrite decreased.

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Section: The Metal Transfer Process and Impact On The Weld Poolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Study on Short-Circuiting GMAW Pool Behavior and Microstructure of the Weld with Different Waveform Control Methods

Chen

Xue

Wang

et al. 2019

Metals

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“…The Gas Metal Arc Welding (GMAW) process is among the most prominent of these methods for several reasons: including the high adequacy in implementation at different thicknesses of the blanks to be welded, and most importantly, the possibility of adapting to the automatic implementation. Welding joints require some mechanical rigidity that depends on the control of the weld dimensions by controlling the amount of molten metal to improve the quality of welding and avoid welding defects [3,4].…”

Section: Introductionmentioning

confidence: 99%

Arc Welding Current Control Using Thyristor Based Three-Phase Rectifiers Applied to Gas Metal Arc Welding Connected to Grid Network

Benaouda¹,

Babes²,

Bouchakour³

et al. 2021

JESA

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The purpose of the welding operation is to ensure the continuity of the materials to be assembled in large industrial sectors. This study aims to suggest a topology of the Thyristor based three-phase rectifiers applied to the Gas Metal Arc Welding (GMAW) process connected to the grid network, the output currents are controlled and using various pulsed forms such as square, annealing, and spike pulse operations and investigate and compare between the effects of the three references welding currents structures on the welding current, welding voltage, droplet diameter, and welding quality. To have the best pulse operation, the amplitude and frequency are kept the same for all operations, the application of meshing graphs in the references of welding currents structures, welding current, welding voltage, and droplet diameter can illustrate a clear comparison between them. The simulation results show that the square pulse operation is the best among them. The Single-Sided Amplitude Spectrum (SSAS) method is also applied to the welding current and droplet diameter of the three operations under slow and rapid droplet detachment rates to estimate the droplet detachment frequency. The results show the great success of the SSAS in estimating the precise frequency.

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“…Beside these, various predictive tools have been developed, such as mathematical models based on experimental results [1], artificial neural network (ANN) models [8], and numerical simulations [9]. Furthermore, many efforts have been carried out to highlight variables that affect weld penetration depth, such as shielding gas type [10,11], arc type [12], arc stability [13], gun angle [1], initial gap [14], welding current [15][16][17], arc voltage [15,18], and welding speed [15]. However, the limitation of having uncertainties in those welding parameters is not addressed.…”

Section: Introductionmentioning

confidence: 99%

A probabilistic model of weld penetration depth based on process parameters

Mansour

Zhu

Edgren

et al. 2019

Int J Adv Manuf Technol

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In welded structures using robotized metal active gas (MAG) welding, unwanted variation in penetration depth is typically observed. This is due to uncertainties in the process parameters which cannot be fully controlled. In this work, an analytical probabilistic model is developed to predict the probability of satisfying a target penetration, in the presence of these uncertainties. The proposed probabilistic model incorporates both aleatory process parameter uncertainties and epistemic measurement uncertainties. The latter is evaluated using a novel digital tool for weld penetration measurement. The applicability of the model is demonstrated on fillet welds based on an experimental investigation. The studied input process parameters are voltage, current, travel speed, and torch travel angle. The uncertainties in these parameters are modelled using adequate probability distributions and a statistical correlation based on the volt-ampere characteristic of the power source.Using the proposed probabilistic model, it is shown that a traditional deterministic approach in setting the input process parameters typically results in only a 50% probability of satisfying a target penetration level. It is also shown that, using the proposed expressions, process parameter set-ups satisfying a desired probability level can be simply identified. Furthermore, the contribution of the input uncertainties to the variation of weld penetration is quantified. This work paves the way to make effective use of the robotic welding, by targeting a specified probability of satisfying a desired weld penetration depth as well as predicting its variation.

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Review of current waveform control effects on weld geometry in gas metal arc welding process

Cited by 44 publications

References 35 publications

Study on Short-Circuiting GMAW Pool Behavior and Microstructure of the Weld with Different Waveform Control Methods

Study on Short-Circuiting GMAW Pool Behavior and Microstructure of the Weld with Different Waveform Control Methods

Arc Welding Current Control Using Thyristor Based Three-Phase Rectifiers Applied to Gas Metal Arc Welding Connected to Grid Network

A probabilistic model of weld penetration depth based on process parameters

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