• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2005년도 추계학술발표대회 개요집
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• pp.108-110
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• 2005

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2005년도 춘계학술발표대회 개요집
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• pp.349-351
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• 2005

• Journal of Welding and Joining
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• 제8권1호
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• pp.31-42
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• 1990

Arc must be stable during welding first of all other factors for obtaining sound weldment, especially in the automation of welding process. Arc stability is somewhat sophisticated phenomenon which is not clearly defined yet. In consumable electrode welding, the voltage and current variation due to metal transfer enables to assess arc stability. Recently, statistical analyses of the voltage and current waveform factors are performed to assess the degress of arc stability which is assessed and controlled by operator's own experience by now. But, considering the increasing need and the trend of automation of welding process, it is necessary to monitor arc stability in real-time. In this sutdy, the modified stability index composed of two voltage and current wvaeform factors (arc time and short circuit time) reduced from four factors (arc time, short circuit time, average arc current and average short circuit current) in Mita's index by the welding electrical circuit modeling is proposed and verified by experiments to be well estimating arc stability in the static sense. Also, the recursive calculation form estimating present arc stability in the dynamic sense is developed for real-time estimation. The results of applying the recursive index during welding show good estimation of arc stability in real-time. Therefore, the results of this study offers the mean for real-time control arc stability.

• 한국정보통신학회논문지
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• 제4권5호
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• pp.937-942
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 춘계종합학술대회
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• pp.369-373
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• 2001

In this paper, we proposes the steps adopted to construct the neural network model for GMAW welds. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters are influenced by numerous factors, such as welding current, arc voltage, torch travel speed, electrode condition and shielding gas type and flow rate etc. In traditional work, the structural mathematical models have been used to represent this relationship. Contrary to the traditional model method, neural network models are based on non-parametric modeling techniques. For the welding process modeling, the non-linearity at well as the coupled input characteristics makes it apparent that the neural network is probably the most suitable candidate for this task. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.166-166
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld qualify is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.