• 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.

• Laser Solutions
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• v.13 no.2
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• pp.17-23
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• 2010

It is very important to track a complicate weld seam for the welding automation. Very recently, laser vision sensor becomes a useful sensing tool to find the seams. Until now, however studies of welding automation using a laser vision sensor, focused on either image processing or feature recognition from CCD camera. Even though it is possible to use a simple algorithm for tracking a simple seam, it is extremely difficult to develop a seam-tracking algorithm when the seam is more complex. To overcome these difficulties, this study introduces a simulation system to develop the seam tracking algorithm. This method was verified experimentally to reduce the time and effort to develop the seam tracking algorithm, and to implement the sensing device.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.3
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• pp.243-251
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• 2015

In order to develop an automatic system for welding thin steel plates with curvature such as the corrugated membranes of an LNG storage tank, a rotating mechanism should be firstly designed for the torch to easily follow the weld seam with a constant distance and angle. In this study, a torch rotating mechanism consisting of three circular links, two square-type links and a torch link was proposed for automation of the welding process. A weld-seam tracking system with two axis slides and the proposed rotating mechanism was successfully simulated with a dynamic simulation software. A prototype tracking system was manufactured and a tracking test with the system was then carried out. The test results with tracking system showed that the rotating mechanism could be implemented and it was feasible to be used in automatic tracking of weld seam with curvature.

• Special Issue of the Society of Naval Architects of Korea
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• 2013.12a
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• pp.73-80
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• 2013

From broad point of view, seam tracking has been one of main issues with respect to welding automation. Several attempts have been successful for seam tracking of fixed weaving width. As a solution of the seam tracking methods for varying groove width, the visual sensors such as CCD cameras have been adopted. Although the vision sensing techniques can achieve high accuracy, the weak point is that well-prepared vision sensor environment should be required to obtain high-quality visual measurements which can be easily affected by significant noises in industrial areas. This paper proposed an alternative seam tracking algorithm for narrow groove. A special measurement device for arc voltage, in this study, is developed to enhance the reliability of the measured welding signals. Based on the developed arc sensor algorithm, an automatic weld-width tracking algorithm is also proposed, which is able to predict the weld-position more accurately. The usefulness of the automatic weld-width tracking algorithm was well verified by applying it to gas tungsten arc welding (GTAW).

• Journal of Welding and Joining
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• v.8 no.3
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• pp.70-78
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• 1990

The harsh nature of welding environments makes welding a prime candidate for process automation. Among the variety of welding processes available, gas metal arc welding is one of the most frequently used methods, primarily because it is highly suited to a wide range of applications, and also to automation. Automatic seam tracking method is one of the most demanded techniques for automatic control of arc welding. In this study a seam tracking system has been developed by using the welding arc itself as a sensor. This paper described the principle and experimental result of the arc sensor system, as well as the development and application of the automatic CO_2$ welding for the horizontal fillet welding. A basic problem in horizontal fillet welding is the prevention of hanging bead formation such as undercut at the vertical plate and overlap at the horizontal plate. To produce the symmetric bead shape, the relationship of bead shape to welding parameters(welding velocity, weaving width, weaving speed, tip to workpiece distance) was also investigated.

• International Journal of Korean Welding Society
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• v.4 no.1
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• pp.30-37
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• 2004

There have been continuous efforts on automating welding processes. This automation process could be said to fall into two categories, weld seam tracking and weld quality evaluation. Recently, the attempts to achieve these two functions simultaneously are on the increase. For the study presented in this paper, a vision sensor is made, a vision system is constructed and using this, the 3 dimensional geometry of the bead is measured on-line. For the application as in welding, which is the characteristic of nonlinear process, a fuzzy controller is designed. And with this, an adaptive control system is proposed which acquires the bead height and the coordinates of the point on the bead along the horizontal fillet joint, performs seam tracking with those data, and also at the same time, controls the bead geometry to a uniform shape. A communication system, which enables the communication with the industrial robot, is designed to control the bead geometry and to track the weld seam. Experiments are made with varied offset angles from the pre-taught weld path, and they showed the adaptive system works favorable results.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.102-110
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• 1998

The horizontal fillet welding is prevalently used in heavy and ship building industries to fabricate the large scale structures. A deep understanding of the horizontal fillet welding process is restricted, because the phenomena occurring in welding are very complex and highly non-linear characteristics. To achieve the satisfactory weld bead geometry in robot welding system, the seam tracking algorithm should be reliable. The number of seam tracker was developed for arc welding automation by now. Among these seam tracker, the arc sensor is prevalently used in industrial robot welding system because of its low cost and flexibility. However, the accuracy of arc sensor would be decreased due to the electrical noise and metal transfer. In this study, the signal processing algorithm based on the neural network was implemented to enhance the reliability of measured welding current signals. Moreover, the seam tracking algorithm in conjunction with the signal processing algorithm was implemented to trace the center of weld line. It was revealed that the neural network could be effectively used to predict the welding current signal at the end of weaving.

• 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.

• Laser Solutions
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• v.12 no.1
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• pp.19-24
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• 2009

Because of its fast and precise welding performance, laser welding is becoming a new excellent welding method. However, the precise focusing and robust seam tracking are required to apply laser welding to the practical fields. In order to laser weld a type of T joint like a circular pipe on a square pipe, which could be met in the three dimensional structure such as an aluminum space frame, a visual sensor system was developed for automation of focusing and seam tracking. The developed sensor system consists of a digital CCD camera, a structured laser, and a vision processor. It is moved and positioned by a 2-axis motorized stage, which is attached to a 6 axis robot manipulator with a laser welding head. After stripe-type structured laser illuminates a target surface, images are captured through the digital CCD camera. From the image, seam error and defocusing error are calculated using image processing algorithms which includes efficient techniques handling continuously changed image patterns. These errors are corrected by the stage off-line during welding or teaching. Laser welding of a circular pipe on a square pipe was successful with the vision tracking system by reducing the path positioning and de focusing errors due to the robot teaching or a geometrical variation of specimens and jig holding.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.706-713
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• 2002

In the multi-pass welding of pressure vessels or ships, the mechanical touch sensor system is generally used together with a manipulator to measure the gap and depth of the narrow gap to perform seam tracking. Unfortunately, such mechanical touch sensors may commit measuring errors caused by the eterioration of the measuring device. An automation system of narrow gap multi-pass welding using a laser vision system which can track the seam line of narrow gap and which can control welding power has been developed. The joint profile of the narrow gap, with 250mm depth and 28mm width, can be captured by laser vision camera. The image is then processed for defining tracking positions of the torch during welding. Then, the real-time correction of lateral and vertical position of the torch can be done by the laser vision system. The adaptive control of welding conditions like welding Currents and welding speeds, can also be performed by the laser vision system, which cannot be done by conventional mechanical touch systems. The developed automation system will be adopted to reduce the idle time of welders, which happens frequently in conventional long welding processes, and to improve the reliability of the weld quality as well.