• Journal of Welding and Joining
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• 제16권4호
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• pp.63-72
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• 1998

In this study, the effects of the current pulsing conditions, on the spatter generation rate during the $CO_2$ gas metal arc welding (GMAW) were investigated. Normally using the inverter type power supply, of which the welding current waveform was regulated to reduce the spatter generation rate, but in this study pulsing was imposed on the welding current. Observation of the metal transfer phenomena during the pulsed current GMAS indicated that the droplet transfer from the electrode via the short circuit transfer and the repelling transfer mode could be minimized by selecting optimum combinations of pulsing parameters, which include base and peak current, base and pak duration. It was also demonstrated in this study that proper combinations of the pulsing parameters led to reduce generation of spatters during GMAW shielded by $CO_2$ gas.

• 한국군사과학기술학회지
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• 제8권1호
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• pp.5-13
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• 2005

In order to evaluate the credibility of the welded joint design for combat vehicle using A12519, the numerical analysis for the joint model has been studied and the results are compared with the experimental works by the impact projectiles. The numerical approach using LS-DYNA involves the process of the crack initiation and propagation as well as the applications of the failure criteria for both the ductile and brittle failures. The good agreement between the numerical and experimental works are proved.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.608-611
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• 2002

In GMAW(Gas Metal Arc Welding) process, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality. Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWB (contact- tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using negro-fuzzy algorithm. Neural networks was applied to design FL(fuzzy logic). The parameters of input membership functions and those of consequence functions in FL were tuned through the method of learning by backpropagation algorithm. Bead geometry could be reasoned from welding current, arc voltage, travel speed on FL using the results learned by neural networks.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.538-541
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• 1996

The flow of the molten drop in the GMAW was observed to explain the mechanism of its formation and break-up process. Fluid flew analysis was made with the assumption that the electrode wire acts like fluid, and it is shown how the convection of the drop inside affects its flow, from the formation to the break-up of the drop. In later part, the process of the spray mode development at high current is shown, as well as the one of the globular mode, by the fluid flow analysis.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.558-561
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding Process in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noise such spatter and arc light. The adaptive Hough transformation was used to extract the laser stripe and to obtain specific weld points In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of Welding and Joining
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• 제16권2호
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• pp.40-47
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• 1998

In the present study, depressions of the GMA weld pool due to the impact of droplet are numerically investigated. The numerical simulation is conducted on the basis of the Navier-Stokes equation and the volume of fluid(VOF) functions. The kinetic energy of transferring droplet makes a depression of the weld pool surface. The surface active element affects the depression of the weld pool. The droplets transferred efficiently to the bottom of the weld pool, along with electromagnetic force make the finger shape penetration at the high current GMAW.

• Journal of Welding and Joining
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• 제18권5호
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.454-457
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• 1997

The purpose of this study is to develop an optimal model, using existing models, that is able to estimate the amount of spatter utilizing artificial neural network in the short circuit transfer mode of gas metal arc (GMA) welding. The amount of spatter generated during welding can become a barometer which represents the process stability of metal transfer in GMA welding, and it depends on some factors which constitute a periodic waveforms of welding current and arc voltage in short circuit GMA welding. So, the 12 factors, which could express the characteristics for the waveforms, and the amount of spatter are used as input and output variables of the neural network, respectively. Two neural network models to estimate the amount of spatter are proposed: A neural network model, where arc extinction is not considered, and a combined neural network model where it is considered. In order to reduce the calculation time it take to produce an output, the input vector and hidden layers for each model are optimized using the correlation coefficients between each factor and the amount of spattcr. The est~mation performance of each optimized model to the amount of spatter IS assessed and compared to the est~mation performance of the model proposed by Kang. Also, through the evaluation for the estimation performance of each optimized model, it is shown that the combined neural network model can almost perfectly predict the amount of spatter.

• 한국기계기술학회지
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• 제13권1호
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• pp.17-22
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• 2011

As the quality of a weld joint is strongly influenced by process parameters the welding process, an intelligent algorithms that can predict the bead geometry and shape to accomplish the desired mechanical properties of the weldment should be developed. In this study, prepared by ${\Phi}1.6mm$ GMA welding of metal wire nose Advice jowelui 350A 600A grade level inverter welder and DAIHEN SCR's were carried out using welding. Welding conditions were 5.5m/min wire feed rate the welding current is rapidly transmit approximately 260A, welding voltage was about 30V. CTWD a 22mm, shielding gas was Ar 20L/min and the welding speed was a 240mm/min. Using data collected during welding equipment welding current and welding voltage waveform was analyzed by measuring the volume of the transition mode. Addition of $CaCO_3$ as a loss of the spread of the weld bead dilution rate decreased, suggesting that, GMA in the overlay welding bead shape control, dilution control and may be used as a welding flux is considered. Stabilizing effect of the arc by the Ca-containing $CaF_2$, $CaCO_3$, $CaMg(CO_3)_2$, respectively, welding flux 0.1wt.% added GMA welding and weld overlay were evaluated with dilution, $CaF_2$, and $CaMg(CO_3)_2$ added to the dilution of Seemed to increase.

• Journal of Welding and Joining
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• 제30권6호
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• pp.49-55
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• 2012

The tandem welding process is one of the most efficient welding processes widely used in material joining technique such as manufacturing of strong and durable structures. It facilitates high rate of joint filling with little increase in the overall rate of heat input due to the simultaneous deposition from two electrode wires. The two electrodes in tandem welding process helps in high-efficiency and high productive of welding process. In this study a automated tandem welding system is developed to determine the correlation between cathode and anode and compared with current ratio of the two electrode torch. Three different inter-electrode distances were chosen, 25mm, 35mm and 45mm to perform the experiment with three different current ratio. From the experiment results, the current ratio between two torch has a large impact on width, height and depth of penetration. In addition, a stable bead geometry is obtained when inter-electrode distance is 35mm.