• Proceedings of the KWS Conference
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• 2002.10a
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• pp.307-313
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• 2002

This paper describes a weld pool monitoring technique, which is based on the weld pool image analysis. The proposed image analysis algorithm uses machine vision techniques to extract geometrical information from the weld pool image such as maximum weld pool width, gap width and misalignment between the joint longitudinal axis and the welding wire. These can be related to the welding parameters (welding voltage and current, wire feed speed and standoff) to produce control actions necessary to ensure that the required weld quality will be achieved. The experiments have shown that the algorithm is able to produce good estimates of the weld pool geometry; however, the adjustment of the camera parameters affects the image quality and, consequently, has a great influence over the estimation.

• International Journal of Korean Welding Society
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• v.3 no.2
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• pp.15-23
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• 2003

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 were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Welding and Joining
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• v.18 no.5
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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.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels 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 in less than 40 experiments.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.33-41
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• 2019

The influence of two parameters on fatigue damage predictions of a variably loaded cantilever beam has been examined. The first parameter is the geometry of the cantilever beam and the weld connecting it to a rear panel. Variables of the geometry examined here include the cantilever length, the weld width on the critical cross-section and the angle of the critical cross-section. The second parameter is the safety factor, as set out by the Eurocode 3 standard. An analytical approach has been used to calculate the stresses at the critical cross-section and standard rainflow counting has been used for the extraction of the load cycles from the load history. The results here suggest that a change in the width and angle of the critical cross-section has a non-linear impact on the fatigue damage. The results also show that the angle of the critical cross-section has the biggest influence on the fatigue damage and can cause the weld to withstand fatigue better. The second parameter, the safety factor, is shown to have a significant effect on the fatigue damage calculation, whereby a slight increase in the endurance safety factor can cause the calculated fatigue damage to increase considerably.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.64-72
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• 2001

Weld line is one of serious troubles which are observed in a plastic part manufactured by a injection molding process. This is caused by many process factors, which are molding pressure, temperature, velocity, location of a injection gate, mold geometry and material properties. investigation on the effects of these process factors to the appearance of a weld line was carried out using a finite element method. Filling and packing analyses were carried out by modifying both the configuration of the injection gates and cavity thickness. Proper locations of the injection gates could be determined by considering molding pressure, temperature, velocity and frozen layer, and whereby the weld line was controled. In order to make a weak appearance of the weld line, flow velocity and flow front in a cavity were also investigated by modifying a cavity thickness. As a result, flow front was extended around the corner in the cavity by changing the flow velocity and hence the appearance of the weld line was much weakened.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.133-138
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• 2003

In this study, numerical investigation has been performed on the evolution of weld pool geometry with moving free surface during low-energy density laser welding process. The free surface elevates near the weld pool edge if ${\partial}{\sigma}/dT$ is dominantly negative. On the contrary, the free surface rise at the center of weld pool in case of mainly positive ${\partial}{\sigma}/dT$. The predicted weld pool width and depth with moving free surface are 5∼15%$5{\sim}15%$ greater than those with flat weld pool surface. It is considered that weld pool surface oscillation during melting process augments convective heat transfer rate in the weld pool.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.111-116
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• 1999

Over the last few years, there has been a growing interest in quantitative representation of heat transfer and fluid flow phenomena in weld pools in order to relate the processing conditions to the quality of the weldment produced and to use this information for the optimization and robotization of the welding process. Normally, a theoretical model offers a powerful alternative to estimate the important input parameters and to calculate the effects of varying any of parameters. To solve this problem, a transient 2D(two-dimensional) heat conduction and a transient 2D axisymmetric heat and fluid model were developed for determining weld bead geometry and temperature distribution for the GMA(Gas Metal Arc) welding process. The equation was solved using a general thermofluid-mechanics computer program, PHOENICS code, which is based on the SIMPLE algorithm. The simulation results showed that the calculated bead geometry from two developed models reasonably agree with the experiment result.

• Proceedings of the KWS Conference
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• 1996.10a
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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.