• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.189-193
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• 1997

Generally, though we use the vision sensor or arc sensor in welding process, it is difficult to define the welding parameters which can be applied to the weld quality control. Especially, the important parameters is Arc Voltage, Welding Current, Welding Speed in arc welding process and they affect the decision of weld bead shape, the stability of welding process and the decision of weld quality. Therefore, it is difficult to determine the unique relationship between the weld bead geometry and the combination of various welding condition. Due to the various difficulties as mentioned, we intend to use Fuzzy Logic and Neural Network to solve these problems. Therefore, the combination of Fuzzy Logic and Neural network has an effect on removing the weld defects, improving the weld quality and turning the desired weld bead shape. Finally, this system can be used under what kind of welding process adequately and help us make an estimate of the weld bead shape and remove the weld defects.

• International Journal of Korean Welding Society
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• v.4 no.1
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• pp.30-37
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• 2004

There have been continuous efforts on automating welding processes. This automation process could be said to fall into two categories, weld seam tracking and weld quality evaluation. Recently, the attempts to achieve these two functions simultaneously are on the increase. For the study presented in this paper, a vision sensor is made, a vision system is constructed and using this, the 3 dimensional geometry of the bead is measured on-line. For the application as in welding, which is the characteristic of nonlinear process, a fuzzy controller is designed. And with this, an adaptive control system is proposed which acquires the bead height and the coordinates of the point on the bead along the horizontal fillet joint, performs seam tracking with those data, and also at the same time, controls the bead geometry to a uniform shape. A communication system, which enables the communication with the industrial robot, is designed to control the bead geometry and to track the weld seam. Experiments are made with varied offset angles from the pre-taught weld path, and they showed the adaptive system works favorable results.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.96-96
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• 2009

The purpose of this study is to clarify the transitional behavior and main factor of excessive welding distortion caused by fabrication process of STS 304 vacuum vessel having double curvature for the efficient quality control of vacuum vessel. In order to do it, the predictive equations of the welding distortion in simple weldment of vacuum vessel were established by conventional finite element analysis. And the principal factor controlling the welding distortion was identified by evaluating the welding distortion of vacuum vessel in each fabrication process with FEA and simplified thermo elastic method. Based on the results, the principal factors of distortion of vacuum vessel were clarified as angular distortion and transverse shrinkage which are a source of excessive out-of plane distortion in the double curved vacuum vessel. It was expected that the FE analysis results of this study could contribute to establish the proper control method of welding distortion for double curved vacuum vessel.

• Journal of Welding and Joining
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• v.28 no.5
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• pp.99-105
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• 2010

Inverter DC resistance spot welding process has been very widely used for joining such as automotive body sheet metal. Because the lobe area of DC welding is larger than AC welding and DC welding has low electrode wear. So the use of Inverter DC resistance spot welding process has been further increased. And the application of high tensile steel is growing for light weight vehicle. To improve the weldability of high strength steel, the development of Inverter DC resistance spot welding system is more conducted. However, Inverter DC resistance spot welding system has a few problems. Current waveform is unstable and the expulsion has been occurred by characteristics of steel. In this study, inverter DC resistance spot welding system was made. And Fuzzy control algorithm was applied for constant current. The genetic algorithm was applied to optimize the fuzzy scaling factors, in order to optimize the fuzzy control.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.1-6
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• 2001

This paper describes several advances in sensor and process control techniques for applications in Submerged Arc Welding (SAW), which combine to give a fully automatic system capable of controlling and adapting the overall welding process. This technology has been applied in longitudinal and spiral pipe mills and in pressure vessel production.

• 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 Welding and Joining
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• v.29 no.6
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• pp.82-87
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• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.191-196
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• 1993

Since the welding process is complex and highly nonlinear, it is very difficult to accurately model the process for real-time control. In this paper, a discrete-time transfer function matrix model for gas metal arc welding process is proposed. Although this linearized model is valid only around the operating point of interest, the adaptation mechanism employed in the control system render this model useful over a wide operating range. A multivariable one-step-ahead adaptive control strategy combined with a recursive least-squares method for on-line parameter estimation is implemented in order to achieve the desired weld bead geometries. Command following and disturbance rejection properties of the adaptive control system for both SISO and MIMO cases are investigated by simulation and experiment.

• Journal of Welding and Joining
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• v.32 no.1
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• pp.53-60
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• 2014

The automatic arc welding is generally accepted as the preferred joining technique and commonly chosen for assembly of large metal structures such as in areas of automotive, aircraft and shipbuilding due to its joint strength, reliability, and low cost compared to other joint processes. Recently, several mathematical models have been developed and studied for control and monitoring welding quality, productivity, microstructure and weld properties in arc welding processes. This study indicates the prediction of process parameters for the expected welding quality with accordance to the adaptive GTA welding process. Furthermore, the mathematical models is also develop to aid the selection of an optimal welding process as the generation of process controls to predict the bead geometry as a function output parameters in the GTA welding process. The developed models through this study showed comparatively excellent predicted results, and will extend to other welding processes to integrate an optimized system for the robotic welding process.

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.77-79
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• 2006

While RSW(Resistance Spot Welding) have been the most successful sheet metal joining process in automotive industry, there are certain qualify issues due to the control system and its application process. Recent materials and coatings make the process more complicated resulting in new challenges for quality welds. In this research, an intelligent RSW system with adaptive control algorithm is introduced to overcome typical RSW issues and its applications to automotive body assembly are presented.