• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.643-646
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• 2000

In this study, we constructed a preview-sensing visual sensor system for weld seam tracking in real time in GMA welding. A sensor part consists of a CCD camera, a band-pass filter, a diode laser system with a cylindrical lens, and a vision board for inter frame process. We used a commercialized robot system which includes a GMA welding machine. To extract the weld seam we used a inter frame process in vision board from that we could remove the noise due to the spatters and fume in the image. Since the image was very reasonable by using the inter frame process, we could use the simplest way to extract the weld seam from the image, such as first differential and central difference method. Also we used a moving average method to the successive position data of weld seam for reducing the data fluctuation. In experiment the developed robot system with visual sensor could be able to track a most popular weld seam, such as a fillet-joint, a V-groove, and a lap-joint of which weld seam include planar and height directional variation.

• Proceedings of the KWS Conference
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• 2004.05a
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• pp.21-23
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• 2004

파이프용접에서 특정용접을 하기 위한 최적의 용접조건 선정하는 작업은 대개 많은 시간과 비용을 요구한다. 최근에 인공지능(AI) 기술을 이용하여 용접변수를 결정하기 위해서는 생산성, 용접결함 등 여러 가지 요소를 고려해야 한다고 주장한다. (중략)

• 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.

• Proceedings of the KWS Conference
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• 2005.06a
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• pp.352-354
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• 2005

This paper shows the development of Digital Thyristor CMA Welding machine system. This system using 8 bit microprocessor. The system has the digital welding process and also constant voltage using fuzzy controller.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2019-2024
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• 2011

The effect of the wear of contact tips on the weld beads made by a Gas Metal Arc Welding(GMAW) process was studied. In order to correlate between the wear of tips and beads, the droplet transfer was investigated by a high speed camera and waveform shapes, and the condition of beads was examined by a low magnification camera as well. It was found that the worn contact tip had caused to shift the contact point between the tip and the welding wire which resulted in nonuniform beads. In addition, the worn contact tip had changed the welding resistance and brought about the arc instability during welding.

• Journal of Welding and Joining
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• v.12 no.1
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• pp.59-72
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• 1994

This paper presents an on-line quality monitoring and control method to obtain a uniform weld quality in gas metal arc welding (GMAW) processes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to assess the integrity of the weld quality. Since a good quality weld is characterized by a relatively high depth-to-width ratio in its dimensions, the second geometrical parameter is regulated to a desired one. The monitoring variables are the surface temperatures measured at various points on the top surface of the weldment which are strongly related to the formation of the weld pool The relationship between the measured temperatures and the weld pool size is implemented on the multilayer perceptrons which are powerful for realization of complex mapping characteristics through training by samples. For on-line quality monitoring and control, it is prerequisite to estimate the weld pool sizes in the region of transient states. For this purpose, the time history of the surface temperatures is used as the input to the neural estimator. The control purpose is to obtain a uniform weld quality. In this research, the weld pool size is directly regulated to a desired one. The proposed controller is composed of a neural pool size estimator, a neural feedforward controller and a conventional feedback controller. The pool size estimator predicts the weld pool size under growing. The feedforward controller compensates for the nonlinear characteristics of the welding process. A series of simulation studies shows that the proposed control method improves the overall system response in the presence of changes in torch travel speed during GMA welding and guarantees the uniform weld quality.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1054-1061
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• 2011

GMA welding process is a production process to improve productivity for the provision of higher quality of material, These includs numerous process variables that could affect welding quality, productivity and cost savings. Recently, the welding part of construction equipment had frequent failure of major components in the welding part of each subsidiary material due to shock which is very poor according to the welding part. Therefore, the implementation of sound welding procedure is the most decisive factor for the reliability of construction machinery. The data generated through experimens conducted in this study has validated its effectiveness for the optimization of bead geometry and process variables is presented. The criteria to control the process parameters, to achieve a healthy bead geometry. This study has developed mathematical models and algorithms to predict or control the bead geometry in GMA fillet welding process.

• Journal of Welding and Joining
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• v.14 no.5
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• pp.87-94
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• 1996

It has been well known in GMA welding process that wire feeding speed (WFS) or deposition rate increases linealy with the increase of wire extension. In this investigation, however, such an well-known relationship was .reconsidered in terms of contact-tube to work distance (CTWD) instead of wire extension. To verify the proposed relationship between WFS and CTWD, bead-on-plate welding was performed with various CTWDs in the range of 15∼35mm under the condition of near-constant voltage and current As expected, the test results showed an excellent linear relation between WFS and CTWD. Furthermore, the value of the slope turned out to be quite similar to those of previous investigators obtained either theoretically or experimentally through the Precise measurement of electrode extension. Present result also demonstred that the increase of CTWD could be very practical measure for increaring deposition rate without any increase of heat input Depending on the tip recess the practical maximum of CTWD was appeared to be limited somewhere in 25∼30mm mainly due to the entrappment of porocity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.1219-1220
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• 2012

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.111-116
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• 1999

Over the last few years, there has been a growing interest in quantitative representation of heat transfer and fluid flow phenomena in weld pools in order to relate the processing conditions to the quality of the weldment produced and to use this information for the optimization and robotization of the welding process. Normally, a theoretical model offers a powerful alternative to estimate the important input parameters and to calculate the effects of varying any of parameters. To solve this problem, a transient 2D(two-dimensional) heat conduction and a transient 2D axisymmetric heat and fluid model were developed for determining weld bead geometry and temperature distribution for the GMA(Gas Metal Arc) welding process. The equation was solved using a general thermofluid-mechanics computer program, PHOENICS code, which is based on the SIMPLE algorithm. The simulation results showed that the calculated bead geometry from two developed models reasonably agree with the experiment result.