• Journal of Welding and Joining
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• v.26 no.6
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• pp.1-3
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• 2008

• Proceedings of the KWS Conference
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• 2000.10a
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• pp.78-80
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• 2000

• Proceedings of the KWS Conference
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• 2004.05a
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• pp.188-190
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• 2004

가스메탈아크용접(gas metal arc welding, 이하 'GMA용접' 이라고 함)은 용가재로서 소모전극 와이어를 일정한 속도로 용융지에 공급하면서 와이어 선단과 모재 사이에서 전기적 아크가 발생되도록 하는 용접법이다. (중략)

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.23-23
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• 2009

우수한 용접부 품질 때문에 TIG를 이용한 오비탈 용접은 파이프 용접에 널리 사용되고 있다. 하지만 루트갭이 없고 루트페이스가 큰 맞대기 오비탈 용접의 위보기 및 경사상진자세에서는 오목한 이면비드가 형성되기 쉽지만, 이러한 문제를 극복하기 위한 연구는 희박한 실정이다. 본 연구에서는 위보기 및 경사상진자세에서 볼록한 이면비드의 형성을 연구하기위해서 용융지의 제어 방법을 적극적으로 검토하였다. 4mm 두께의 SS400 시편을 위보기 및 경사상진자세에서 각각 Bead-on-plate 용접하고, 이 때 비드성형기의 사용에 따른 비드 형상 변화를 관찰하였다. 텅스텐 전극과 비드 성형기간의 거리(Tip To Former Distance, 이하 TTFD)를 4.5mm에서 7.5mm로 1mm단위로 변경시켜 실험하였으며, TTFD가 증가할수록 위보기 및 경사상진자세에서 이면비드 높이가 감소하였으며 표면비드의 처짐이 증가하였다.

• Journal of Welding and Joining
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• v.6 no.4
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• pp.1-6
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• 1988

아크용접에 로보트가 적용되면서 그 적용대상 폭을 넓히기 위하여 여러 종류의 센서들이 개발되어 왔다. 그 중 로보트나 자동용접장치에 장착이 용이한 아크센서에 대하여 원리들과 응용한 예들을 소개하였다. 용접이음부의 최소두께 제한, 용접중 용융지의 처침(Distortion) 등에 따른 아크신호의 불안정이 문제로 남아 있으므로 아크센서의 신뢰도를 향상시키기 위해서는 각 용접공정의 보다 정확한 해석이 요구되며, 이들을 적용하기 위한 제어 알고리즘의 개선 또한 요구된다. 아크센서가 개선되어 신뢰도가 높아질수록 더욱 광범위하게 적용될 것이며, 아크용접작업의 생산성 향상에 크게 기여하게 될 것이다.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.531-536
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• 1992

In GMA welding processes, monitoring and control of weld quality are extremely difficult problems. This paper describes a neural network-based method for monitoring and control of weld pool sizes. First, weld pool sizes are estimated via a neural estimator using multi-point surface temperatures, which are strongly related to the formation of weld pool, and then controlled using the estimated pool sizes. Two types of controllers using the pool size estimator are designed and tested. To evaluate the performance of the designed controllers, a series of simulation studies was performed.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.527-529
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• 1986

Measurement and control system of weld pool is comprised of optical devices, image processor, personal computer and welding machine. Combinations of ND and Infrared filters were used to block the intense arc light and to get the clearer image of weld pool. Smoothing operation and conversion to binary data were performed to eliminate the noises and to decrease the processing time. A simple algorithm for feedback control was developed and weld pool size is controlled by welding current which is adjusted automatically with personal computer.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1028-1033
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• 1991

This paper describes the design of a neural network estimator to estimate weld pool sizes for on-line use of quality monitoring and control in GMA welding processes. The estimator utilizes surface temperatures measured at various points on the top surface of the weldment as its input. The main task of the neural net is to realize the mapping characteristics from the point temperatures to the weld pool sizes through training, A series of bead-on plate welding experiments were performed to assess the performance of the neural estimator.

• 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 Welding and Joining
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• v.16 no.5
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• pp.119-133
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• 1998

To implement full automation in pipe welding, it si most important to develop special sensors and their related systems which act like human operator when detecting irregular groove conditions. In this study, an automatic pipe Gas Metal Arc Welding (GMAW) system was proposed to full control pipe welding procedure with intelligent sensor systems. A five-axes manipulator was proposed for welding torch to automatically access to exact welding position when pipe size and welding angle were given. Pool status and torch position were measured by using a weld-pool image monitoring and processing technique in root-pass welding for weld seam tracking and weld pool control. To overcome the intensive arc light, pool image was captured at the instance of short circuit of welding power loop. Captured image was processed to determine weld pool shape. For weld seam tracking, the relative distance of a torch position from the pool center was calculated in the extracted pool shape to move torch just onto the groove center. To control penetration of root pas, gap was calculated in the extracted pool image, and then weld conditions were controlled for obtaining appropriate penetration. welding speed was determined with a fuzzy logic, and welding current and voltage were determined from a data base to correspond to the gap. For automatic fill-pass welding, the function of human operator of real time weld seam control can be substituted by a sensor system. In this study, an arc sensor system was proposed based on a fuzzy control logic. Using the proposed automatic system, root-pass welding of pipe which had gap variation was assured to be appropriately controlled in welding conditions and in torch position by showing sound welding result and good seam tracking capability. Fill-pass welding by the proposed system also showed very successful result by tracking along the offset welding line without any control of human operator.