• 연구논문집
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• s.32
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• pp.55-64
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• 2002

Performance demonstration with real flawed specimens has been strongly required for nondestructive evaluation of safety class components in nuclear power plant. Specimen has been designed to produce mechanical fatigue flaw with tension stress and fatigue flaw has been produced to control stress and cycle, for suitable roughness. Notch condition is considered for control of fracture mode. After seal welding for fracture surface, final welding was performed to complete flaw specimen with GTAW(Gas Tungsten Arc welding) and FCAW(Flux Cored Arc Welding). It was demonstrated flaw size of flawed specimen by radiographic. testing and ultrasonic testing.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.1
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• pp.45-53
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• 2003

For the improvement of welding performance, high-efficiency inverter system was designed and applied that system to the conventional large scale Flashbutt welder. The inverter systems are consists of full bridge PWM power control system and DSP controller. This inverter system has increased switching frequency of power control system of Flashbutt welder. For the test of application effects, we compared an our inverter control system with a conventional thyristor control system. In the results, we confirmed that our system has decreased the welding spatter amouts and improved welding performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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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.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.93-101
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• 2007

Aluminum alloy which is one of the light materials has been tried to apply to light weight vehicle body. In order to do that, welding technology is very important. In case of the aluminum laser welding, the strength of welded part is reduced due to porosity, underfill, and magnesium loss. To overcome these problems, laser welding of aluminum with filler wire was suggested. In this study, experiment about laser welding of AA5182 aluminum alloy with AA5356 filler wire was performed according to process parameters such as laser power, welding speed and wire feed rate. The tensile strength was measured to find the weldability of laser welding with filler wire. The models to estimate tensile strength were suggested using three regression models and one neural network model. For regression models, one was the multiple linear regression model, another was the second order polynomial regression model, and the other was the multiple nonlinear regression model. Neural network model with 2 hidden layers which had 5 and 3 nodes respectively was investigated to find the most suitable model for the system. Estimation performance was evaluated for each model using the average error rate. Among the three regression models, the second order polynomial regression model had the best estimation performance. For all models, neural network model has the best estimation performance.

• Journal of Welding and Joining
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• v.34 no.2
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• pp.67-72
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• 2016

Aluminum alloy is one of light weight material and it is used to make LNG tank and ship. However, in order to weld aluminum alloy high density heat source is needed. In this paper, I-butt welding of Al 5083 with 6mm thickness using Plasma-MIG welding was carried out. The experiment was performed to investigate the influence of plasma-MIG welding parameters such as plasma current, wire feeding rate, MIG-welding voltage and welding speed on the tensile strength of weld. In addition we suggested 3 strength estimation models which are second order polynomial regression model, multiple nonlinear regression model and neural network model. The estimation performance of 3 models was evaluated in terms of average error rate (AER) and their values were 0.125, 0.238, and 0.021 respectively. Neural network model which has training concept and reflects non -linearity was best estimation performance.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.336-341
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• 2002

Recent developments in sensor hardware and in advanced software have made it feasible to consider automating some of the most difficult welding operations. This paper describes some techniques used to automate successfully multipass submerged arc welding operations typically used in pressure vessel manufacture, shipbuilding, production of offshore structures and in pipe mills.

• Journal of Welding and Joining
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• v.24 no.5
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• pp.67-73
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• 2006

Laser welding is suitable for welding to the aluminum alloy sheet. In order to apply the aluminum laser welding to production line, parameters should be optimized. In this study, the optimal welding condition was searched through the genetic algorithm in laser welding of AA5182 sheet with AA5356 filler wire. Second-order polynomial regression model to estimate the tensile strength model was developed using the laser power, welding speed and wire feed rate. Fitness function for showing the performance index was defined using the tensile strength, wire feed rate and welding speed which represent the weldability, product cost and productivity, respectively. The genetic algorithm searched the optimal welding condition that the wire feed rate was 2.7 m/min, the laser power was 4 kW and the welding speed was 7.95 m/min. At this welding condition, fitness function value was 137.1 and the estimated tensile strength was 282.2 $N/mm^2$.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.64-70
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• 2002

This paper shows the results of the development of a small size of digital type continuous and intermittent welding auto-carriage based on microprocessor (Intel 80196KC) for welding process with long welding line. The developed welding auto-carriage loads welding torch and tracks welding line. It is an automaton largely used for welding process with a lot of long welding lines such as shipbuilding and structure. Most traditional auto-carriages have been developed based on analog circuit for open loop control. So this analog circuit welding auto-carriage cannon control welding speed. Specially welding auto-carriage for intermittent welding condition is so complicated and has the low precision of control performance in welding distance and non-welding distance. The auto-carriage developed in this paper has the following characteristics: It has not only functions of traditional carriage but also functions such as pseudo-welding process of big iron structures, intermittent welding in order to limit heat for welding thin plates, crater treatment of the final step of welding, acceleration at the initial step of welding and deceleration in the final step of welding. The main control board of auto-carriage, power supply system and DC motor drive wee developed and manufactured. The welding speed and the welding distance of the developed auto-carriage are controlled accurately by feedback control using photo-sensor. Hardware and software robust against the heat and noise produced on the welding process are developed.

• Corrosion Science and Technology
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• v.6 no.1
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• pp.33-35
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• 2007

Welding technology plays an important role in the fabrication of structure, and this has led to an increasing attention in the use of high quality advanced welding technology such as power beam welding, friction stir welding, and laser-arc hybrid welding, etc. At the same time, welding can influence various factors in the performance of plant and equipment, and corrosion behaviour of weldment has been one of the major issues for both welding and corrosion research engineers. The aim of this paper is to give a short survey of the recent technical trends of welding and corrosion behaviours including the electrochemical corrosion, stress corrosion cracking, and corrosion fatigue in connection with the welding materials, welding process, and welding fabrication.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6282-6288
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• 2014

$CO_2$ welding is used widely in the field. On the other hand, welding defects occur when welders cannot adjust the current and voltage needed for welding and have to stop working to adjust the current and voltage, causing sudden cooling down of the welding structure inside a vehicle or tank where the control panel is invisible or when work site is far. This study used three types of existing $CO_2$ welders. This also applied SS400 rolled steel for welding structural purposes for remote control torch welding, perform a welding test through v-groove butt welding with a remote control torch and existing $CO_2$ welding torch, conducted visual inspection on the appearance of a welded top bead. In addition, the appearance quality of the welding part was monitored mainly through penetrant testing and a bending test to evaluate the welding defect reduction and the effect on the performance and compatibility by replacing the existing welder.