• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2005년도 추계학술발표대회 개요집
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• pp.108-110
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• 2005

• Journal of Welding and Joining
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• 제14권5호
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• pp.113-121
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• 1996

The arc sensor has been most widely used for weld seam tracking through welding current or voltage variation. In this work, the relation between the arc light intensity and welding condition is investigated using heat balance in the Plasma for its possible application to seam tracking in the GMAW process. The arc light intensity is derived to be the function of the arc length and welding current Experiments are carried out to verify the proposed heat balance model. Performances of least square and integration methods to process the signals for seam tracking are compared experimentally. Predicted arc light intensity shows reasonably good agreement with experimental results. The weld seam is successfully tracked through the arc light intensity. The least square and integration methods demonstrate almost same performance of seam tracking with $CO_2$gas shielding.

• Journal of Welding and Joining
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• 제16권3호
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• pp.44-54
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• 1998

In this study a new arc sensor algorithm for automatic weld seam tracking was proposed, which uses the relative welding current variation according to the tip-to-workpiece distance in GMA welding. Since the new developed arc sensor algorithm is not sensitive to unstable factors of arc signal, the system is expected to get rid of the problems of already existing arc sensor system which include the difficulty of modeling the process for various welding conditions and limitation of application to thick plate welding. Thus the system is applicable not only to thick plate welding but also to thin plate welding. To implement the new arc sensor algorithm the system parameters which include sampling time, averaging range, weighting factor of moving averaging, basic compensation time, and basic compensation distance were determined by experimental analysis. Consequently this system has shown the successful tracking capability for the various welding conditions.

• International Journal of Korean Welding Society
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• 제3권1호
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• pp.8-16
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• 2003

A major concern in Gas Metal Arc (GMA) welding process is the determination of welding process variables such as wire diameter, gas flow rate, welding speed, arc current and welding voltage and their effects on the desired weld bead dimensions and shape. To successfully accomplish this objective, 81 welded samples from mild steel AS 1204 flats adopting the bead-on-plate technique were employed in the experiment. The experimental results were used to develop a mathematical model to predict the magnitude of bead geometry as follows; weld bead width, weld bead height, weld bead penetration depth, weld penetration shape factor, weld reinforcement shape factor, weld bead total area, weld bead penetration area, weld bead reinforcement area, weld bead dilution, length of weld bead penetration boundary and length of weld bead reinforcement boundary, and to establish the relationships between weld process parameters and bead geomery. Multiple regression analysis was employed for investigating and modeling the GMA process and significance test techniques were applied for the interpretation of the experimental data.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1996년도 특별강연 및 추계학술발표 개요집
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1996년도 특별강연 및 춘계학술발표 개요집
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• pp.13-14
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• 1996

High Frequency Electric Resistance Welding process has been widely used in manufacturing welded steel pipes because of its high welding speed and quality. This process utilizes the skin effect as well as the proximity effect of the high frequency current in heating the skelp edge. In this study, an analytical solution of the edge temperature was obtained based on several assumptions. The assumptions includes the expontial decay of weldingcurrent from the surface and neglect of the heat loss in the welding direction. This calculation shows a good agreement with the observations made from the high speed camera. Using tile analytical model, tile heat required as a function of the welding speed and the skelp thickness was determined. These results were compared with the experimental results obtained.

• Journal of Welding and Joining
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• 제11권4호
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• pp.44-56
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• 1993

The arc welding processes are substantially nonlinear, in addition to being highly coupled multivariable systems, Frequently, not all the variables affecting the welding quality are known, nor may they be easily quantified. From this point of view, decoupling between the welding parameters from the welding quality is very difficult, which makes it also difficult to control the welding parameters for obtaining the desired welding quality. In this study, a neural network based on the backpropagation algorithm was implemented and adopted for the selection of gas metal arc welding parameters of the fillet joint, that is, welding current, arc voltage and welding speed. The performance of the neural network for modeling the relationship between the welding quality and welding parameters was presented and evaluated by using the actual welding data. To obtain the optimal neural network structure, various types of the neural network structures were tested with the experimental data. It was revealed that the neural network can be effectively adopted to select the appropriate gas metal arc welding parameter of fillet joints for a given weld quality.

• Journal of Welding and Joining
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• 제21권3호
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• pp.85-91
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• 2003

Narrow gap welding has many advantages over conventional V-grooved butt welding such as high productivity, small deformation and improved mechanical property of joints. With narrower groove gap, less arc heat input is expected will all the other advantages of narrow gap welding. The main defects of narrow gap welding include the lack of root fusion, convex bead surface and irregular surface, all of which have negative effects on the next welding pass. This paper suggests an up-and-down torch oscillation for ultra narrow gap welding with gap size of 5mm and investigates the proper welding conditions to fulfill the reliable and high welding quality. First, GMA welding model was suggested for ultra narrow gap welding system with Halmoy's model referenced for wire melting modeling. And the arc length in ultra narrow gap was defined. Secondly, based on the experimental results of up-and-down torch oscillation welding, phase shift of current and wire extension length were simulated for varying oscillation frequency to show that weld the bead shape in ultra narrow gap welding can be predicted. As the result, it was confirmed that reliable weld quality in ultra narrow gap welding can be achieved with up-and-down torch oscillation above 15Hz due to its ability to provide uniform heat input along the sidewall of gap.

• Journal of Welding and Joining
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• 제13권2호
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• pp.115-121
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• 1995

As the metal transfer in the GMAW process affects the weld quality and productivity, the mechanism of molten formation and detachment has been investigated at various welding conditions. The force balance and pinch instability models have been widely used to analyze the metal transfer in the globular and spray modes, respectively A new approach is proposed in this work by minimizing the energy of molten drop system. Effects of the surface tension, gravity, electromagnetic and drag forces are considered with no presumed molten drop geometry. Effects of various welding conditions on the metal transfer are explained. The results show that the proposed mode can be applied to the globular and spray transfer modes. When compared with other models, results of the proposed model show better agreements with the available experimental data, which demonstrates the validity of the present model.

• 한국정밀공학회지
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• 제18권1호
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• pp.162-170
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• 2001

In torch weaving in arc welding on V groove, the heat input distribution on groove surface is a main factor determining the bead shape and the weld quality with and without the weld defects such as undercut, overlap, etc. In this study, we calculate the heat input varying with the welding current, arc voltage, welding speed and the touch weaving condition using numerical method. And we investigate the heat input distribution on groove surface while applying the various grooves having 2 dimensional heat sources.