• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2004년도 춘계 학술발표대회 개요집
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• pp.18-20
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• 2004

This study is to find the optimal work plan of robot welding in the subassembly process of shipbuilding and to verify the found solution through 3-D simulation. The optimal work plan was established by evenly distributing the work amount to each stage and finding the shortest work sequence. The shortest work sequence was found by using the genetic algorithm. The result was compared with the practically adopted case and verified through the 3-D simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.206-210
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• 1989

In automobile glass fitting the stud is welded on the window seating panel in order to insert the plastic molding onto the stud. Since this type of process is in general manually done, almost 50% of the output turns out to be failure resulted from work inefficiency and weld inferiority. Therefore, it is required to improve this process for the productivity elevation through the application of the robot.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1114-1119
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• 1995

This paper presents the development of estimation model and control method based on the new computer vision. This proposed control method is accomplished using a sequential estimation scheme that permits placement of the rigid body in each of the two-dimensional image planes of monitoring cameras. Estimation model with six parameters is developed based on a model that generalizes known 4-axis scara robot kinematics to accommodate unknown relative camera position and orientation, etc. Based on the estimated parameters,depending on each camers the joint angle of robot is estimated by the iteration method. The method is tested experimentally in two ways, the estimation model test and a three-dimensional rigid body placement task. Three results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as assembly and welding.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.501-506
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• 2000

Many research in Robot control has effectively proceeded on the development of Aritficial Intelligence Robot which is able to apply to the uncertain and monotonous operations which are repeated continuously in the industrial field. In this study, the precise shape recognition of base metal for welding was gained by mono CCD camera, and the gained data was transformed into Decimal code through Image Board in computer. And the Fuzzy Logic control system designed by use of Fuzzy rule was built to judge whether the base metals were precisely matched or not with Decimal code. Machanically manipulated Robot syst em was linked to Fuzzy Control system through image information, and ultimately, these systems will be able to apply for production system.

• 대한기계학회논문집A
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• 제24권10호
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• pp.2581-2588
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• 2000

In previous studies, the dynamic resistance, which was calculated by the process variables measured at the electrode of the welding machine, and the electrode displacement were used for quality exa mination. However, in-process usage of such systems is not effective in systems that include a welding gun attached to a robot. In order to overcome such problems, we obtained and used the process variables from the welding machine timer. This would allow us to estimate real time in -process weld quality. For quality estimation, the features were extracted as factors from the primary dynamic resistance patterns, which were measured in t he welding machine timer. The relationship between the indexes and nugget size of the welds was observed through the regression analysis. Using the analyzed factors, a regression model that could estimate nugget diameter was developed. Two regression equations of the model were suggested depending on the factors, and it was showed that the model developed by stepwise method was effective one for weld quality estimation. The developed estimation model was in good linearity with the nugget diameter obtained through the experimentation.

• 한국공작기계학회논문집
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• 제17권6호
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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.

• Journal of Welding and Joining
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• 제17권5호
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• pp.40-46
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• 1999

The sensors employed in the robotic are welding system must detect the changes in weld characteristics and produce the output that is in some way related to the change being detected. Such adaptive systems, which synchronise the robot arm and eyes using a primitive brain will form the basis for the development of robotic GMA(Gas Metal Arc) welding which increasingly higher levels of artificial intelligence. The objective of this paper is to realize the mapping characteristics of bead height through learning. After learning, the neural estimation can estimate the bead height desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

• 대한조선학회 특별논문집
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• 대한조선학회 2008년도 특별논문집
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• pp.90-95
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• 2008

The letters and marks on the hull of vessels are marked by welding bead or steel plate to resist the corrosion environment. It has done by manual work. So, it cause deterioration of welding quality and process delay and so on. The automated welding device for draft mark has developed partially in the field of shipbuilding. But it can be used for draft mark only. And it has caused a few problems about that workablity and movablity are decreased owing to the size and weight of device. So we developed the automated welding device that can be used for most letters and marks on the hull. It designed to 3 axises mobile robot include to ratoation axis and stand alone type controller with multi GUI base on imbedded windows.

• Journal of Welding and Joining
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• 제31권5호
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• pp.35-40
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• 2013

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

• Journal of Welding and Joining
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• 제14권1호
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• pp.24-29
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• 1996

철도차량의 루프 판넬(Roof Panel)은 폭이 약 3m, 길이가 약 20m의 초대형 외판과 하부 골조간에 2000 - 3000개의 스폿 용접건을 조작해서 작업을 해야 하는 대표적인 작업기피 공정의 하나이다. 이제까지 철도차량 제조업체에서는 대부분 스폿 용접을 사진1에서 본 바와 같이 수동조작 메니퓨레이터 등의 전용장비를 사용하여 제품 생산을 하고 있었으나 이러한 장비는 고가일뿐 아니라 수동조작으로 위치 이동 하여 모든 스폿 용접을 하여야 하므로 작업시간이 크게 소요되어 생산성이 매우 낮았 다. 본고에서는 300kg 중량물 취급용 5축 구조의 대형 로봇을 개발하여 철도차량 루프 판넬 스폿용접 작업 공정을 자동화 함으로서 생산성 및 품질을 크게 향상시킨 사례에 대하여 소개하고자 한다.