• Journal of Welding and Joining
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• v.29 no.3
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• pp.64-69
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• 2011

Since welding process for most pipelines with large diameter has been carried out by the manual process, automation of the welding process is necessary for the sake of consistent weld quality and improvement in productivity. Therefore the development of the optimized algorithm to decide the welding condition is an effective technique to prove the feasibility of interface standards and intelligent control technology to increase productivity and reduce the cost of system integration. In this study, the pipe welding experiment has been carried out using plused GMA welding process to select optimal welding condition. And necessary information in root-pass welding has been obtained by applying in the pipeline using the selected welding conditions through the welding experiment.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.1
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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 the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.87-93
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• 2005

In this paper, we analyzed ignition characteristics of combustible material and the waveform of power dissipation, voltage and current by poor contact. And the surface structure of plug by poor contact was analyzed. In the results of experiment, the heat generated by poor contact and ignited the combustible material on power cord sets. The insulation material was molten and carbonized by the heat conduction though plug pit and voids were formed inside of insulation material. The waveform of voltage and power dissipation distorted because of a growth of oxidation by poor contact. In particular, in case that load was big load, the waveform of voltage and power dissipation severely distorted as with the passage of time. The surface of plug pin was changed from erosion mark to welding mark according to big load. The results will be applied to the cause analysis of electrical disaster.

• Journal of Welding and Joining
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• v.17 no.5
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• pp.98-106
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• 1999

In GMAW, the spatters are generated according to the variation of the arc. Of the arc is stable, Few spatters are generated. But if unstable, too many spatters are generated. So, this means the spatters are dependent on the arc state. The aim of this study is to accurately estimate the arc state. To do this, the generated spatters were captured under the some welding conditions, and the waveforms of the arc voltage and welding current were collected. From the collected signals, the waveform factors and their standard deviations were extracted. Using these factors as input parameters of multi-layer artificial neural network, the learning for the weight of the generated spatters is performed and the estimation results to the real spatter are assessed. Obtained results are as follow: the linear correlation coefficient between the estimated result and the real spatters was 0.9986. And although the average convergence error was set 0.002, the estimated error to the real spatter was within 0.1 gr/min at each welding condition. In the estimation for the weight generated spatters, the result with multi-layer neural network was far better than with multiple regression analysis. Especially, even though under the welding condition which the arc state is unstable (the spatter is generated much more), very excellent estimation performance was shown.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.10
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• pp.141-149
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• 2008

Because aluminum has a lighter weight and higher strength than iron, it is frequently used in the transportation industry for the purpose of reducing the weight of a chassis, and thereby increasing fuel efficiency. However, there are some difficulties with arc welding aluminum due to its lower melting point, high thermal conductivity and oxidation coating on its surface. This study proposed using superposition ac pulse MIG arc welding, which has been improved from the pulse waveform of conventional MIG welding. A MIG arc welding power source was developed to test the effectiveness of this method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.644-649
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• 2017

In the automobile industry, there is growing demand for lightweight vehicles due to environmental problems and rising oil prices. Therefore, aluminum alloys and special materials are being used to reduce the weight of vehicles, but there are still many difficulties to overcome in terms of cost and strength. Therefore, the application of advanced high strength steel (AHSS)is increasing. AHSS has good strength and formability.Safety regulations are becoming stricter, and 1.2-GPa super-high-strength steels are gradually being applied for the center pillar and roof rails. Thus, the application of different kinds of steels in automobile bodiesis also increasing gradually. This study evaluates the resistance point weldability and the characteristics of a welded part of SGAFC1180 1.2t steel. A simulation was used to observe the nugget formation and its growth behavior. The prediction performance showed a similar tendency within an error rate of 10%. Also, the effect of this behavior on the process resistance and dynamic resistance was investigated,along with the correlation between the shear tensile strength and nugget diameter.