• Journal of Welding and Joining
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• v.23 no.4
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• pp.66-72
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• 2005

An electromagnetic inductive sensor consisted of one exciter and three separated (triple) detectors has been developed for both tracking the weld seam of a workpiece and controlling the sensor-to-workpiece distance (height) simultaneously. The left and right detectors are used to track the seam, while the fore and the other two detectors allow the sensor to determine the height and the gap width by being coupled their outputs together. A series of experiments with the proposed sensor located above a mild steel plate containing a weld seam of gap are carried out to examine the feasibility of the sensor. The results revealed that the proposed sensor could fairly well track the desired seam and also well control the height to be constant even when the gap width of the seam varied. The gap width can be also determined during the seam tracking by using the sensor outputs. As a consequence, these can provide the developed sensor with substantial improvement for industrial uses with respect to the previous electromagnetic sensors being used for the weld seam tracking.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1506-1511
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• 2003

This paper describes an automatic weld seam tracking method of plasma arc welding system designed for the corrugation panel that consists of a linear section and a curved section with various curvatures. Due to the complexity of the panel shape, it is difficult to find a seam and operate a torch manually in the welding process. So, the laser vision sensor for seam tracking is designed for sensing the seam position and controlling a torch automatically. To achieve precise seam tracking, the design of sensor head, image simulation, and calibration are carried out. Through a series of experiment result, compensation algorithm is added and real time error compensation is achieved. The experiment result shows that this vision sensor works effectively. It will provide more precise welding performance and convenience to the operator.

• 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.16 no.3
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• pp.44-54
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• 1998

In this study a new arc sensor algorithm for automatic weld seam tracking was proposed, which uses the relative welding current variation according to the tip-to-workpiece distance in GMA welding. Since the new developed arc sensor algorithm is not sensitive to unstable factors of arc signal, the system is expected to get rid of the problems of already existing arc sensor system which include the difficulty of modeling the process for various welding conditions and limitation of application to thick plate welding. Thus the system is applicable not only to thick plate welding but also to thin plate welding. To implement the new arc sensor algorithm the system parameters which include sampling time, averaging range, weighting factor of moving averaging, basic compensation time, and basic compensation distance were determined by experimental analysis. Consequently this system has shown the successful tracking capability for the various welding conditions.

• Journal of Welding and Joining
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• v.13 no.4
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• pp.65-74
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• 1995

The weld seam tracking sensor is indispensable to improve the flexibility of automatic arc welding systems. Among the position sensing methods available, a laser displacement sensor is one of the most prevailing methods. In this study, a laser displacement sensor was examined on detecting the weld seam of lap joints in sheet metal arc welding. The output signal of the laser displacement sensor may ontain severe fluctuation from the effect of arc light, spatters, fume, etc. So a variety of signal processing methods was applied to smooth the output signal of the sensor. And then the weld joint was determined by using the central difference method. It was revealed that the quadratic mean method plays an important role in detecting the weld seam during welding especially.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.499-503
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• 2004

This application-oriented paper describes an automated welding carriage system to weld a thin corrugated workpiece with welding seam tracking function. Hyundai Heavy Industries Corporation has developed an automatic welding carriage system, which utilizes pulsed plasma arc welding process for corrugated sheets. It can obtain high speed welding more than 2 times faster than traditional TIG based welding system. The aim of this development is to increase the productivity by using automatic plasma welding carriage systems, to track weld seam line using vision sensor automatically, and finally to provide a convenience to operator in order to carry out welding. In this paper a robust image processing and a distance based tracking algorithms are introduced for corrugated workpiece welding. The automatic welding carriage system is controlled by the programmable logic controller(PLC), and the automatic welding seam tracking system is controlled by the industrial personal computer(IPC) equipped with embedded OS. The system was tested at actual workpiece to show the feasibility and performance of proposed algorithm and to confirm the reliability of developed controller.

• Proceedings of the KWS Conference
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• 1996.10a
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2701-2706
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• 2003

This paper describes weld seam tracking and error compensation methods of automatic plasma arc welding system designed for the corrugation panel that consists of a linear section and a curved section with various curvatures. Realizing automatic welding system, we are faced with two problems. One is a precise seam tracking and the other is an arc length control. Due to the complexity of the panel shape, it is difficult to find a seam and operate a torch manually in the welding process. So, laser vision sensor for seam tracking is equipped for sensing the seam position and controlling the height of a torch automatically. To attain more precise measurement of an arc length, we measure the 3D shape of the panel and analyze error factors according to the various panel states and caused errors are predicted through the welding process. Using that result, compensation algorithm is added to that of arc length control and real time error compensation is achieved. The result shows that these two methods work effectively.

• Journal of Welding and Joining
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• v.9 no.2
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• pp.20-28
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• 1991

The main subject of this study is the construction of an automatic welding system that has the capability to trace the weld seam in GMA welding of lap joints. The system was composed of a vision sensor, moving torch, and personal computer(IBM-PC). In the developed vision sensor, an image was captured by the frame grabber at the time of short circuit during welding. The threshold method was adopted for determining the structured light and the central difference method for detecting the weld joint. And the seam tracing of the torch was performed by using the data regeneration algorithm. In this system using the image at the time of short circuit, weld seam tracking was performed without any relations to arc light and spatters.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.775-778
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• 1996

In this research, the robustness of a seam tracking for the automatic welding system is studied. The laser displacement sensor is used as a seam finder. X-Y moving table drived by ac servo motor controls the position and velocity of the torch-and-sensor part. However, dc servo motor is used to control the position and velocity of the torch. The sensor locates ahead of torch to preview the weld line, and brings about the inaccuracy on the torch tracking. To enhance the robustness on this system against the influence of disturbances and model uncertainty, H$\_$.inf./ control is applied to the angular motion of torch. The simulation shows that the tracking accuracy improved significantly. Also, experimental results give a good performance of H$\_$.inf./ control strategy to the automatic seam tracking system for the welding.