• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.932-935
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• 2005

Three dimensional laser welding technology for light car body is studied. A robot, a seam tracking system and 4kW CW Nd:YAG laser are used for three dimensional robot laser welding system. The Laser system is used 4kW Nd:YAG laser(HL4006D) of Trumpf and the Robot system is used IRB6400R of ABB. The Seam tracking system is SMRT-20LS of ServoRobot. The welding joint of steel plate are butt and lap joint. The 3-D welding for Non-linear Tailored blank is performed after the observation experiments of bead on plate. Finally, the welding process for non-linear tailored blank and front side member is developed.

• Journal of Welding and Joining
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• v.27 no.5
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• pp.42-48
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• 2009

Pipe welding is used in various ranges such as civil engineering and ship building engineering. Until now, many technicians work for pipe welding manually under harmful, dangerous and difficult conditions. So it is necessary to install automation process. For automation pipe welding, relation between welding parameters & bead shape should be considered. Using this relation, bead shape could be expected from welding parameters. FCAW was used in this study. Instead of pipe workpiece, fillet joint plate is used, which were inclined 0,45,90,135,180 degree. By analyzing between welding parameters (current, welding speed, voltage) and bead shape parameters with non-linear multiple regression, bead shape parameters could be expected. Piecewise Cubic Hermite Interpolation was used to expect smooth curved bead shape with bead shape parameters. From these processes, bead shape could be expected from welding parameters.

• Journal of Welding and Joining
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• v.17 no.4
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• pp.85-92
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• 1999

In GMAW, the spatter is generated because of the variation of the arc state. If the arc state is quantitatively assessed, the control method to make the spatter be reduced is able to develop. This study was attempted to develop the optimal model that could estimate the arc state quantitatively. To do this, the generated spatters was captured under the limited welding conditions, and the waveforms of the arc voltage and of the welding current were collected. From the collected waveforms, the waveform factors and their standard deviations were produced, and the linear and non-linear regression models constituted using the factors and their standard deviations are proposed to estimate the arc state. the performance test to the proposed models was practiced. Obtained results are as follow. From the results of correlation analysis between the factors and the amount of the generated spatters, the standard deviations of the waveform factors have more the multiple regression coefficients than the waveform factors. Because the correlation coefficient between T and {TEX}$T_{a}${/TEX}, and s[T] and s[{TEX}$T_{a}${/TEX}] was nearly one, it was found that these factors have the same effect to the spatter generation. In the regression models to estimate the arc state, it was fond that the linear and the non linear models were also consisted of similar factors. In addition, the linear regression model was assessed the optimal model for estimating the arc state because the variance of data was narrow and multiple regression coefficient was highest among the models. But in the welding conditions which the amount of the generated spatters were small, it was found that the non linear regression model had better the estimation performance for the spatter generation than the linear.

• Proceedings of the KWS Conference
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• 2005.06a
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• pp.103-105
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• 2005

Laser welding technology for automobile body is studied. laser system, robot and seam tracking system are used for 3D laser welding system The laser system is used 4kW Nd:YAG laser(HL4006D) of Trumpf and the robot system is used IRB6400R of ABB. The seam tracking system is SMRT-20LS of ServoRobot. The welding joints of steel plate are butt and lap joint. The 3-D welding for non-linear tailored blank is performed after experiments of bead on plate. Finally, the welding process for non-linear tailored blank is developed.

• International Journal of Korean Welding Society
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• v.2 no.1
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• pp.40-44
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• 2002

Residual stress by welding should be reduced because that decreases the reliability on strength of welded structure. The reason is that the total stiffness of structure decreases by non-linear behavior of weldment under external load. The release of residual stress by mechanical loading and unloading is often performed in the fabrication of box structure for steel bridge. The proper degree of loading and unloading is significant at release method of residual stress by mechanical loading because that degree is changed by material and geometric shape of welded structure. Therefore, the simulation model that could exactly analyze the release of residual stress by mechanical loading is to be necessary. This simulation model should be established on the based of variable and accurate measurement data. In this study, the non-linear behavior of weldments under external loading and unloading, such as the decrease and increase of structure stiffness, was investigated by monitoring of nominal stress and strain. Tensile loading and unloading test under variable load was performed and the proper degree of stress relaxation was measured by sectioning technique using strain gauge.

• Journal of Welding and Joining
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• v.21 no.1
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• pp.66-71
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• 2003

The release of residual stress by mechanical loading and unloading is often performed in the fabrication of box structure fur steel bridge. The proper degree of loading and unloading is significant at release method of residual stress by mechanical loading because that degree is changed by material and geometric shape of welded structure. Therefore, the simulation model that could exactly analyze the release of residual stress by mechanical loading is to be necessary. In this study, the non-linear behavior of weldments under external loading and unloading, such as the decrease and increase of structure stiffness, was investigated by monitoring of nominal stress and strain. Tensile loading and unloading test and the proper degree of stress relaxation was measured by sectioning technique using strain gauge. Analysis model that is indispensable for the effective application of MSR method was established on the basis of test and measurement result.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.372-377
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• 2002

Residual stress by welding should be reduced because that decreases the reliability on strength of welded structure. The reason is that the total stiffness of structure decreases by non-linear behavior of weldment under external load. The release of residual stress by mechanical loading and unloading is often performed in the fabrication of box structure for steel bridge. The proper degree of loading and unloading is significant at release method of residual stress by mechanical loading because that degree is changed by material and geometric shape of welded structure. Therefore, the simulation model that could exactly analyze the release of residual stress by mechanical loading is to be necessary. This simulation model should be established on the based of variable and accurate measurement data. In this study, the non-linear behavior of weldments under external loading and unloading, such as the decrease and increase of structure stiffness, was investigated by monitoring of nominal stress and strain. Tensile loading and unloading test under variable load was performed and the proper degree of stress relaxation was measured by sectioning technique using strain gauge.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.539-544
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• 1998

Generally, welding gap is a serious factor of a falling-off in weld quality among various kind of weld defect. Welding gap is created between two work piece in GMAW(Gas Metal Arc Welding) of horizontal fillet weld because surface of workpiece is not flat by cutting process. In these days, there were many attempts to detect welding gap. though we prevalently use the vision sensor or arc sensor in welding process, it is difficult to detect welding gap for improvement of welding quality. But we have a trouble to find relationship between welding gap and many welding parameters due to non-linearity of welding process. As mentioned about the various difficult problem, we can detect welding gap precisely using neural networks which are able to model non-linear function. Also, this paper was proposed real-time monitoring of weld bead shape to find effect of welding gap and to estimate weld quality. Monitoring of weld bead shape examined the correlation of welding parameters with bead eometry using learning ability of neural networks. Finally, the developed system, welding gap detecting system and bead shape monitoring system, is expected to the successful capability of automation of welding process by result of simulation.

• International Journal of Korean Welding Society
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• v.2 no.1
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• pp.29-32
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• 2002

In previous study, the decrease and recovery of total stiffness in welded structure was discussed on the basis of experimental examination through tensile loading and unloading test of welded specimen. The recovery of structure stiffness was caused by the release of welding residual stress through mechanical loading. In this study, analysis model that is indispensable for the effective application of MSR method was established on the basis of test and measurement result. Thermal elasto-plastic analysis for welding process was performed by non- coupled analysis. Analysis results of welding process were transfer to elasto-plastic model for tensile loading & unloading by restart technique. In elasto-plastic analysis model for mechanical loading & unloading, hardening appearance of weld metal was considered by rezoning technique and tying technique was used for JIG condition of test machine.

• International Journal of Korean Welding Society
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• v.1 no.2
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• pp.36-44
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• 2001

To get the appropriate welding process variables, mathematical modeling in conjunction with many experiments is necessary to predict the magnitude of weld bead shape. Even though the experimental results are reliable, it has a difficulty in accurately predicting welding process variables for the desired weld bead shape because of nonlinear and complex characteristics of welding processes. The welding condition determined for the desired weld bead shape may cause the weld defect if the welding current/voltage/speed combination is improperly selected. In this study, the $2^{n-1}$ fractional factorial design method and correlation parameter were used to investigate the effect of the welding process variables on the fillet joint shape, and the multiple non-linear regression analysis was used for modeling the gas metal arc welding(GMAW）parameters of the fillet joint. Finally, a fuzzy rule-based method and a neural network method were proposed so that the complexity and non-linearity of arc welding phenomena could be effectively overcome. The performance of the proposed neuro-fuzzy system was evaluated through various experiments. The experimental results showed that the proposed neuro-fuzzy system could effectively check the welding conditions as to whether or not weld defects would occur, and also adjust the welding conditions to avoid these weld defects.