• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.320-323
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• 2001

Nowadays, computer network has been rapidly developed. And we have made efforts to use it in wide field. So we can exchange data without spacial restriction using internet. If we develop monitoring system using internet, we have the effect of reducing time and space. Therefore, in this paper, we developed TCP/IP network and client/server system. And We applied them to resistance spot welding quality monitoring system.

• Journal of Welding and Joining
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• v.9 no.3
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• pp.34-40
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• 1991

An automatic welding system was constructed with a personal computer to capture the welding data in addition to vision seam tracking for the gas metal arc welding process. The monitoring of welding signals is composed of the acquisition of welding voltage and current, obtained by using two differential amplifiers and A/D converters, and processing of the measured data. Using interrupt handing circuit for time sharing, two jobs of seam tracking and monitoring were performed at the required sampling time. Relations between welding signals and various welding circumstances were analyzed from the experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.10
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• pp.7-13
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• 2006

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.345-348
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• 2008

Recently, in Weld Processing field, unmanned and automatic system construction has experienced the rapid growth, and diverse signal processing has been employed in order to translate the exact weld pattern. It this paper, We will suggest the effective neural network which can deride the weld quality in arc weld and monitoring system in real time. In addition, We will present the pre-processing for selecting the study data, and the method to evaluate the wave of weld more precisely and accurately through known Neural Network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.407-412
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• 2009

Recently, in Weld Processing field, unmanned and automatic system construction has experienced the rapid growth, and diverse signal processing has been employed in order to translate the exact weld pattern. In this paper, We will suggest the effective neural network which can decide the weld quality in arc weld and monitoring system in real time. In addition, We will present the pre-processing for selecting the study data, and the method to evaluate the wave of weld more precisely and accurately through known Neural Network.

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.149-151
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• 2006

• Proceedings of the KWS Conference
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• 2001.05a
• /
• pp.46-48
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• 2001

• Journal of Welding and Joining
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• v.30 no.1
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• pp.44-50
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• 2012

• Journal of Welding and Joining
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• v.30 no.1
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• pp.19-26
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• 2012

• Proceedings of the KWS Conference
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• 1998.10a
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• pp.157-159
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• 1998