• Journal of Welding and Joining
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• v.15 no.4
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• pp.31-35
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• 1997

• Journal of Welding and Joining
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• v.21 no.1
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• pp.14-20
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• 2003

• Journal of Welding and Joining
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• v.20 no.1
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• pp.23-25
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• 2002

• Journal of Welding and Joining
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• v.21 no.1
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• pp.60-65
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• 2003

At present. welding of most pipes with large diameter is carried out by the manual process. Automation of the welding process is necessary f3r the sake of consistent weld quality and improvement in productivity. In this study, two vision sensors, based on the optical triangulation, were used to obtain the information for seam tracking and detecting the weld defects. Through utilization of the vision sensors, noises were removed, images and 3D information obtained and positions of the feature points detected. The aforementioned process provided the seam and leg position data, calculated the magnitude of the gap, fillet area and leg length and judged the weld defects by ISO 5817. Noises in the images were removed by using the gradient values of the laser stripe's coordinates and various feature points were detected by using an algorithm based on the iterative polygon approximation method. Since the process time is very important, all the aforementioned processes should be conducted during welding.

• Journal of Welding and Joining
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• v.33 no.3
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• pp.4-11
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• 2015

The offshore wind power plants are watched as a new market to accomplish the needed energy, bringing technical and economical challenges. Advanced countries in the field of wind industry are now appling the 600 MPa, 150~200 mm thick high strength steel to offshore wind power plants. Moreover, the high efficient welding methods which is weldable ultra tick high strength steel with 1 pass welding are developed and applied in manufacturing the offshore wind tower. This article deals with the present world wide status of offshore power plants and the tendency of the development of high efficient welding technology for constructing the offshore wind tower. This article intends to offer the materials for development and raising of the domestic offshore wind power technology.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.499-503
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• 1994

The feedback control systems of welding process using visual information can improve weld qualities. However, it is very difficult to get the visual information of weld pool since welding are is much stronger than light from weld pool. To explore the possibility of extending the capability of automatic welding machines a study of a closed loop controlled welding system consisted of a GTA welding machine, a vision system, a stepping motor system and a digital computer was undertaken. Particularly, in this system, a CCD camera with 850nm long pass filter was focused on the weld pool to give a weld pool image. Subsequently, image analysis technique has been developed to measure a weld pool width. Using this weld pool width measurement, a colsed loop control system adjusted welding speed to maintain constant weld pool width.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.885-893
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• 2000

The use of neural-fuzzy system to model mesh seam welding is described in this paper. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current, torch travel speed and the pressure and so on. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other. The effectiveness of the proposed neuro-fuzzy algorithms is demonstrated by computer simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.195-199
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• 2005

Semi automatic welding method to use carriage for welding at large size block manufacture welding process of present shipbuilding industry is used much. Carriage is device that transfer welding torch in horizontal fillet weld here, but because it is no function that chase welding like robot welding method, use can be impossible in curved line welding, and simply use in straight line welding. Also, because it is no function that chase welding, though welding mistake corrects this happening often in straight line welding, much times and expense are cost. Added welding chase sensor and 80C196KC microcontroller that use strain gauge to carriage that is using present in paper that see hereupon and manufacture a private line model and container box model welding because developing system that can chase welding automatically straight line and curved line welding establishing and investigate about chase phenomenon.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.25-31
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• 2014

Gas metal arc welding (GMAW) is currently the most widely used arc welding processes in the industry because of its high metal deposition rate, flexibility and low cost. It is attractive for high-productivity manufacturing applications and is well suited to automatic or robotic welding. Welding voltage and current have a significant impact on the weld bead. However, welding voltage and current are changed variously according to welding condition and user environment, and prediction is impossible. To determine the welding conditions, the welding current and voltage are applied to the appropriate data analysis techniques. In this paper, we used the moving average filter to the welding voltage and current data, and normal and abnormal welding waves were distinguished.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.595-599
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• 2002

Edge welding of thin sheets is very difficult because of the fit-up problem and small weld area In laser welding, joint fit-up and penetration are critical for sound weld quality, which can be monitored by appropriate methods. Among the various monitoring systems, visual monitoring method is attractive because various kinds of weld pool information can be extracted directly. In this study, a vision sensor was adopted for the weld pool monitoring in pulsed Nd:YAG laser edge welding to monitor whether the penetration is enough and the joint fit-up is within the requirement. Pulsed Nd:YAG laser provides a series of periodic laser pulses, while the shape and brightness of the weld pool change temporally even in one pulse duration. The shutter-triggered and non-interlaced CCD camera was used to acquire a temporally changed weld pool image at the moment representing the weld status well. The information for quality monitoring can be extracted from the monitored weld pool image by an image processing algorithm. Weld pool image contains not only the information about the joint fit-up, but the penetration. The information about the joint fit-up can be extracted from the weld pool shape, and that about a penetration from the brightness. Weld pool parameters that represent the characteristics of the weld pool were selected based on the geometrical appearance and brightness profile. In order to achieve accurate prediction of the weld penetration, which is nonlinear model, neural network with the selected weld pool parameters was applied.