• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.6
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• pp.158-163
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• 2012

This study investigates numerical analysis for robot welder fume flow and gantry structure. The solvers are STAR-CCM+ and ANSYS workbench used on flow and structural analysis. The results show that fume is diffused in factory when the welding fume is remove at dust collector. But dust collector intercepts the fume diffusion into workroom by removing most of welding fume. Structure analysis result shows that the reinforcement rod is evaluated to main the safety by supporting sufficient structure.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.314-319
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• 2002

The Automation and Control Group at the University of Brasilia is developing an automatic welding station based on an industrial robot and a controllable welding machine. Several techniques were applied in order to improve the quality of the welding joints. This paper deals with the implementation of a laser-based computer vision system to guide the robotic manipulator during the welding process. Currently the robot is taught to follow a prescribed trajectory which is recorded a repeated over and over relying on the repeatability specification from the robot manufacturer. The objective of the computer vision system is monitoring the actual trajectory followed by the welding torch and to evaluate deviations from the desired trajectory. The position errors then being transfer to a control algorithm in order to actuate the robotic manipulator and cancel the trajectory errors. The computer vision systems consists of a CCD camera attached to the welding torch, a laser emitting diode circuit, a PC computer-based frame grabber card, and a computer vision algorithm. The laser circuit establishes a sharp luminous reference line which images are captured through the video camera. The raw image data is then digitized and stored in the frame grabber card for further processing using specifically written algorithms. These image-processing algorithms give the actual welding path, the relative position between the pieces and the required corrections. Two case studies are considered: the first is the joining of two flat metal pieces; and the second is concerned with joining a cylindrical-shape piece to a flat surface. An implementation of this computer vision system using parallel computer processing is being studied.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.37-42
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• 2007

The purpose of this research is stability estimation of plant structure through classification and recognition about welding flaw in SWP(Spiral Welding Pipe). And, In this research, we used nondestructive test based on ultrasonic test as inspection method, and made up 2-axes inspection robot in order to control of ultrasonic probe on the SWP surface, and programmed to image processing and probabilistic neural network(PNN) classifying code by MATLAB programming. Through this process, we proved efficiency on the system of SWP stability Estimation.

• 대한공업교육학회지
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• v.33 no.1
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• pp.282-296
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• 2008

Present automobile robot welding use $CO_2$ inert gas as a shielding fluid. The inert gas is spreading out and consumable. This present welding mechanism interfered with the welding nozzle. After welding several places have welding defects. Therefore, to reduce the $CO_2$ inert gas and to avoid interference with the material and to increase production modified nozzle which composed of cap and tip are needed. Suggested modified nozzle assembly composed of two stages i.e. $1^{st}$ and $2^{nd}$ stage. At the second stage it has 8 holes which is 3mm of diameter around the circumference. On the base of experimental results the inert $CO_2$ gas discharge reduced to 47% and welding defects decreased also. Modified two stage welding cap can be applied to the present robot welding machine and save the prime cost.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.5
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• pp.110-117
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• 2004

In automatic welding process using a robot, seam tracking is one of the important parts. Sensor for seam tracking is divided broadly into two categories as non contact sensor and contact sensor. The arc sensor is one of the non contact sensors, and it can be applied in weaving arc and rotating arc welding process. In such the arc sensors, rotating arc sensor can be applied to high speed welding over tens of Hz. The decrease of self regulation by high rotating speed causes to improve accuracy and response of sensor. In this study, fuzzy controller was used to track the seam for the $CO_2$ arc welding which had unstable arc. It could be shown that the rotating arc sensor was better than the weaving arc sensor.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1116-1120
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• 2004

In the nuclear power plant, there are several cylindrical vessels such as reactor vessel, pressuriser and so on. The vessels are usually constructed by welding large rolled plates, forged sections or nozzle pipes together. In order to assure the integrity of the vessel, these welds should be periodically inspected using sensors such as ultrasonic transducer or visual cameras. This inspection is usually conducted under water to minimize exposure to the radioactively contaminated vessel walls. The inspections have been performed by using a conventional inspection machine with a big structural sturdy column, however, it is so huge and heavy that maintenance and handling of the machine are extremely difficult. It requires much effort to transport the system to the site and also requires continuous use of the utility's polar crane to move the manipulator into the building and then onto the vessel. Setup beside the vessel requires a large volume of work preparation area and several shifts to complete. In order to resolve these problems, we have developed an underwater mobile robot guided by the laser pointer, and performed a series of experiments both in the mockup and in the real reactor vessel. This paper introduces our robotic inspection system and the laser guidance of the mobile robot as well as the results of the functional test.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.87-92
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• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.