• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.9
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• pp.2760-2769
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• 1996

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 the light intensity of welding arc is much stronger than that of the 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 a long wavelength pass filter was used to get a better weld pool image. Subsequently, an image analysis technique has been developed to measure the weld pool width. Using this weld pool width measurement, a colsed loop control system adjusted welding speed to maintain a constant weld pool width.

• Journal of Welding and Joining
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• v.19 no.2
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• pp.208-214
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• 2001

In this study, we constructed a visual sensor system for weld seam tracking in real time in GMA welding. A sensor part consists of a CCD camera, a band-pass filter, a diode laser system with a cylindrical lens, and a vision board for inter frame process. We used a commercialized robot system which includes a GMA welding machine. To extract the weld seam we used a inter frame process in vision board from that we could remove the noise due to the spatters and fume in the image. Since the image was very reasonable by using the inter frame p개cess, we could use the simplest way to extract the weld seam from the image, such as first differential and central difference method. Also we used a moving average method to the successive position data or weld seam for reducing the data fluctuation. In experiment the developed robot system with visual sensor could be able to track a most popular weld seam. such as a fillet-joint, a V-groove, and a lap-joint of which weld seam include planar and height directional variation.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.1
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• pp.150-157
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• 1997

Uniform weld pool shape is important in determining the weld quality. And weld pool width is one of the most dominant factors of the seld pool shape. In order to control the weld pool width, the fuzzy logic controller, which is well adapted to the complicated nonlinear systems such as welding, was used in this study. The weld pool image was obtained through CCD camera, and the weld pool width was calculated by processing the image. Uaing the calculated width, welding speed, as a control input, was inferred by the fuzzy logic controller. An uniform weld pool width can be successfully obtained regardless of the disturbances in the system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.103-110
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• 2008

A reliable extraction of welded area is the precedent task before the detection of weld defects in industrial radiography. This paper describes an attempt to detect and extract the welded features of steel tubes from the computed radiography(CR) images. The statistical properties are first analyzed on over 160 sample radiographic images which represent either weld or non-weld area to identify the differences between them. The analysis is then proceeded by pattern classification to determine the clustering parameters. These parameters are the width, the functional match, and continuity. The observed weld image is processed line by line to calculate these parameters for each flexible moving window in line image pixel set. The local statistic line-clustering method is used as the classifier to recognize each window data as weld or non-weld cluster. The sequential procedure is to track the edge lines between two distinct regions by iterative calculation of threshold, and it results in extracting the weld feature. Our methodology is concluded to be effective after experiment with CR weld images.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.527-529
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• 1986

Measurement and control system of weld pool is comprised of optical devices, image processor, personal computer and welding machine. Combinations of ND and Infrared filters were used to block the intense arc light and to get the clearer image of weld pool. Smoothing operation and conversion to binary data were performed to eliminate the noises and to decrease the processing time. A simple algorithm for feedback control was developed and weld pool size is controlled by welding current which is adjusted automatically with personal computer.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.643-646
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• 2000

In this study, we constructed a preview-sensing visual sensor system for weld seam tracking in real time in GMA welding. A sensor part consists of a CCD camera, a band-pass filter, a diode laser system with a cylindrical lens, and a vision board for inter frame process. We used a commercialized robot system which includes a GMA welding machine. To extract the weld seam we used a inter frame process in vision board from that we could remove the noise due to the spatters and fume in the image. Since the image was very reasonable by using the inter frame process, we could use the simplest way to extract the weld seam from the image, such as first differential and central difference method. Also we used a moving average method to the successive position data of weld seam for reducing the data fluctuation. In experiment the developed robot system with visual sensor could be able to track a most popular weld seam, such as a fillet-joint, a V-groove, and a lap-joint of which weld seam include planar and height directional variation.

• 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 the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.38-46
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• 1996

This paper discusses the feasibility of Ultrasonic Nondestructive Evaluation (UNDE) technique for sport weld quality. Ultrasonic c-scan image assisted by image processing technique was used for Nondestructive Evaluation(NDE) of spot weld quality. Ultrasonic testing results obtained were confirmed and compared by Optical Microscope and SAM(Scanning Acoustic Mircroscope) observation of the spot-weld cross section, The results show that the nugget dinameter can be successfully measured with the accuracy of 0.5mm. It was ascertained that ultrasonic c-scan technique is very effective method for the sake of the approach to the quantitative measurement of nugget diameter and the discrimination of the corona bond from nugget. Additional support for the above conclusions is provided by the results for galvanized steel. The ultrasonic results for galvanized welds generally correspond to the results for uncoated steel. Finally, it was found that the above-mentioned technique can be sufficiently applied to NDE method for securing the Quality Assurance(QA) of spot welded products in production line.

• 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.