• Proceedings of the KWS Conference
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• 2002.05a
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• pp.46-48
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• 2002

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.3
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• pp.81-87
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• 2007

It is important to investigate the relationship between weld process parameters and weld bead geometry for adaptive arc robot welding. However, it is difficult to predict an exact back-bead owing to gap in process of butt welding. In this paper, the quantitative prediction system to specify the relationship external weld conditions and weld bead geometry was developed to get suitable back-bead in butt welding which is widely applied on industrial field. Multiple regression analysis and artificial neural network were used as the research methods. And, the results of two prediction methods were compared and analyzed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.9-18
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• 2007

There have been continuous efforts for automation of joint tracking system. This automation process is mainly used to do in root pass of gas metal arc welding in the field of heavy industry and shipbuilding etc. For automation, it is important using of vision sensor. Welding robot with vision sensor is used for weld seam tracking on welding fabrication. Recently, it is used to on post-weld inspection for weld quality evaluation. For real time seam tracking, it is very important role in vision process technique. Vision process is included in filtering and thinning, segmentation processing, feature extraction and recognition. In this paper, it has shown performance comparison results of seam tracking for real time root pass on gas metal arc welding. It can be concluded better segment splitting method than iterative averaging technique in the performance results of seam tracking.

• Proceedings of the KWS Conference
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• 1997.10a
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• pp.229-233
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• 1997

The demand to increase productivity and quality, the shortage of skilled labour and the strict health and safety requirements have led to the development of the automated welding process to deal with many of the present problems of welded fabrication. To make effective use of the automated arc welding process, it is imperative that a mathematical model, which can be programmed easily and fed to the robot, should be developed. The objectives of the paper are to develop the mathematical equations (linear and curvilinear) for study of the relationship between process variables and bead geometry by employing a standard statistical package program, SAS and to choose the best model for automation of the $CO_2$ gas arc welding process. Mathematical models developed from experimental results can be employed to control the process variables in order to achieve the desired bead geometry based on weld quality criteria. Also these equations may prove useful and applicable for automatic control system and expert systems.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.89-95
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• 1997

Welding technique is widely applied to general industry such as pressure vessel for chemical plant, pipe system, heavy industry, and automobile. There are some points which must be considered when robot system is used in welding automation process for productivity improvement. Welding quality is governed by heat input, and this quantity can be different according to shape, property, and thick of material . For desired heat input , weld input parameters such as welding voltage, current, and welding velocity must be determined with those consideration. Until now these parameters have been determined mainly by experience of operator. In this study, the size of welding zone was predicted by fuzzy rules were constructed from the relation between welding variables and weld pool size. Inverse model method which welding control input for welder is determined with optimum voltage and current by fuzzy controller is validatied by computer simulation.

• Proceedings of the KWS Conference
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• 2005.11a
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• pp.52-54
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• 2005

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.49-55
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• 2008

Arc welding process is one of the most important technologies to join metal plates. Robotic welding offers the reduced manufacturing cost sought, but its widespread use demands a means of sensing and correcting for inaccuracies in the part, the fixturing and the robot. A number of problems that need to be addressed in robotic arc welding processes include sensing, joint tracking, and lack of adequate models for process parameter prediction and quality control. Problems with parameter settings and quality control occur frequently in the GMA(Gas Metal Arc) welding process due to the large number of interactive process parameters that must be set and accurately controlled. The objectives of this paper are to realize the mapping characteristics of bead width using a sensitivity analysis and develop the neural network and multiple regression method, and finally select the most accurate model in order to control the weld quality(bead width) for fillet welding. The experimental results show that the proposed neural network estimator can predict bead width with reasonable accuracy, and guarantee the uniform weld quality.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.159-159
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• 2000

최근 조선분야의 경우 생산원가의 절감, 품질의 고급화, 단순작업에 대한 근로기피 등의 이유로 로봇시스템 적용에 대한 필요성이 크게 대두되고 있다. 그러나 기존의 로봇 시스템의 교시방식이 교시-재생(Teaching-Playback)방식이어서 작업부재의 형상 및 치수가 매번 변경되는 중공업 분야에서는 적용이 불가능하였다. 본 연구에서는 조선용 아크용접 로봇을 위한 오프라인 프로그램밍(OLP: Off-Line Programming) 시스템을 개발하였다. 오프라인 프로그램밍 시스템의 경우 작업중인 로봇과는 상관없이 다음 부재에 대한 형상 데이터만을 이용하여 컴퓨터상에서 다음 작업프로그램을 미리 생성할 수 있으므로 기존의 온라인 교시-재생 방식의 교시시간의 과다라는 문제를 극복할 수 있다. 본 연구에서는 강교 판넬 및 조선 소조립용으로 개발 중인 아크용접용 로봇 시스템을 위한 오프라인 프로그래밍 시스템을 개발하였다. CAD 데이터나 OLP의 모델링 기능으로 작업부재를 형상한 후 미리 데이터베이스화 되어 있는 자료를 검색하여 부위별 작업매크로 확보를 위하여 실제 로봇 시스템을 이용한 작업테스트를 수행하였다. 개발된 오프라인 프로그래밍 시스템은 기능보완 후 당사 아크용접용 로봇시스템에 적용될 계획이다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.248-248
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• 2000

본 연구는 조선 소조립, 판넬조립 등의 공정에서 발생되는 필렛 용접 부위의 용접 자동화를 위한 로봇 시스템 개발에 관한 연구이다. 조선등의 중공업 분야에서는 작업이 중량이고 대형임에 따라 로봇이 부재의 특정위치로 이동하여 작업해야 한다. 또한 작업대상의 형상이나 치수가 매번 변경됨에 따라 이에 능동적으로 대처할 수 있어야 한다. 본 연구에서는 두 대의 로봇(2대x6축=12축)이 다축 문형 캔트리(4축)에 장착된 조선용 필렛용접 로봇 시스템(16축)을 개발하였다. 필렛용접부재를 중심으로 두 대의 로봇이 양쪽을 동시에 용접하는 방식으로 고속회전토치를 적용하여 위빙동작없이 원하는 용접각장(Leg Length)을 생성할 수 있다. 캔트리 시스템은 PC 기반의 별도 제어기로 구성하여 두 대의 로봇 제어기와 신호 입출력에 의해 동시동작이 가능하도록 하였으며, 작업장에 놓인 부재의 위치오차를 보장하기 위하여 시각센서를 적용하였다. 용접시작점의 위치보정을 위한 시작점 검출을 위해접촉센서(Touch Sensor)를 적용하였으며, 용접선 추적을 위해서 아크센서(Arc Sensor)를 적용하였다. 본 시스템 2000년 1월 제작 설치가 완료되어 현재 성능 테스트가 완료된 상태로 향후 생산현장에 적용될 계획이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.460-464
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• 2001

Recently, the use of Robot increase little by little for the purpose of developing a welding quality and productivity in the arc welding part. It is more important to contact the seam for arc welding before moving a welding robot. There are two types of method to contact the seam namely contact and noncontact type largely In this paper, image processing sensor(a kind of non-contact sensor) is concerned to track the seam by using laser diode and CCD camera. A structured laser diode's light illuminated on the weld groove and the reflected shape is introduced by CCD camera. The image board captures this image and software analyzes this image. The robot is moved and welded exactly as acquired image X-Y data is changed with robot's X-Y value. Also, most of seam tracking are considered by changing the program simply in case of the different weld prove of plane surface.