• Journal of Welding and Joining
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• v.22 no.6
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• pp.43-49
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• 2004

In this study, a visual sensor system which can detect I-butt weld joint with height variation and includes a seam tracking algorithm was investigated. Three-dimensional position of an object can be acquired by using the method of distance measurement, i.e., an optical trigonometry which results from the spatial relations between the camera, the object and the structured light by a visible laser. Effects of laser intensity and iris number for the image quality as well as object material were investigated for the optical system design. For the image processing, a region of interest is defined from the whole image and a line image of laser is drew by using the gray level difference in the image. From the drew laser line, the weld joint can be recognized in searching the biggest point position calculated from the central difference method. Through a series of welding experiments, a good tracking performance was confirmed under GMA welding.

• 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.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.59-66
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• 2006

In laser welding, automatic seam tracking is important to adjust the laser head position in real time as it moves along the seam. Also if the joint gap is occurred, filling the missing material into the joint gap is necessary to prevent welding defects and bad welding quality. In general, the joint gap width is not constant along the seam due to a variety of reason. So it is essential to control the filler wire speed into the joint gap to acquire good welding quality. This paper describes an intelligent filler wire feeding device which can control 3-dimensional seam tracking and the filler wire speed by measuring the gap position and the joint gap width in laser welding. We call this device as Smart Micro Control system(SMC). To achieve this objective, we assessed weld quality in 2mm sheets of A16061 which had various gap width by using the developed device. From the experimental results, It was found the possibility that the developed device could be used in welding various 3-dimensional structures.

• Journal of Welding and Joining
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• v.14 no.6
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• pp.131-139
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• 1996

The response of the arc sensor using the welding current and/or welding voltage as its outputs has been obtained by the analysis and/or experiments of the static characteristics of arc sensor. But in order to improve the reliability of arc sensor, it is necessary to know its dynamic characteristics. So in this paper, it is presented the dynamic model of arc sensor including the power source, arc voltage, electrode burnoff rate, and wire feed rate. A numerical simulation of the dynamic model of arc sensor was implemented, computing the welding current with input of CTWD. The results of computer simulations and experiments of $CO_2$arc welding showed that a linear relationship between weaving center - weld line distance and current area difference was established. Additionally, a real-time weld seam tracking system interfaced with industrial welding robot was constructed, the result of the weld seam tracking experiment for weld line with an initial offset error of 5$^{\circ}$was good.

• Journal of Welding and Joining
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• v.13 no.4
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• pp.122-131
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• 1995

An automatic welding equipment for thick plates requires the capability of the seam tracking of the weld line which often includes misalignment of the workpiece and variation of groove width. In this study, an automatic welding equipment and control algorithms based on the arc sensor were proposed for the GMA welding of thick plates which had misalignment and gap variation. The developed system being constituted with 5 axis can be automatically controlled by computer and also automnatically set the welding conditions such as welding current, and voltage. The proposed algorithms for the seam tracking in multi-pass welding of the thick plates were constituted as follows : the detection of weaving-end point for findng the variation of groove width, the control of welding velocity for acquiring a constant thickness deposition of weld metal, and the calculation of groove width and height of an arbitrary pass in the multi-pass weld. As results of the application of the system, it was revealed that the system had a good capability in seam tracking and made an excellent weld quality in V groove butt joint.

• 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.

• Journal of Welding and Joining
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• v.16 no.5
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• pp.119-133
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• 1998

To implement full automation in pipe welding, it si most important to develop special sensors and their related systems which act like human operator when detecting irregular groove conditions. In this study, an automatic pipe Gas Metal Arc Welding (GMAW) system was proposed to full control pipe welding procedure with intelligent sensor systems. A five-axes manipulator was proposed for welding torch to automatically access to exact welding position when pipe size and welding angle were given. Pool status and torch position were measured by using a weld-pool image monitoring and processing technique in root-pass welding for weld seam tracking and weld pool control. To overcome the intensive arc light, pool image was captured at the instance of short circuit of welding power loop. Captured image was processed to determine weld pool shape. For weld seam tracking, the relative distance of a torch position from the pool center was calculated in the extracted pool shape to move torch just onto the groove center. To control penetration of root pas, gap was calculated in the extracted pool image, and then weld conditions were controlled for obtaining appropriate penetration. welding speed was determined with a fuzzy logic, and welding current and voltage were determined from a data base to correspond to the gap. For automatic fill-pass welding, the function of human operator of real time weld seam control can be substituted by a sensor system. In this study, an arc sensor system was proposed based on a fuzzy control logic. Using the proposed automatic system, root-pass welding of pipe which had gap variation was assured to be appropriately controlled in welding conditions and in torch position by showing sound welding result and good seam tracking capability. Fill-pass welding by the proposed system also showed very successful result by tracking along the offset welding line without any control of human operator.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.14-23
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. However, in this paper, multipass tracking more than single pass tracking is performed by conventional seam tracking algorithm and developed one. And tracking performances of two algorithm are compared in multipass tracking. As the result, tracking performance in multi-pass welding shows superior conventional seam tracking algorithm to developed one.