• Journal of Welding and Joining
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• v.26 no.2
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• pp.62-68
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• 2008

Effects of gravitational orientation on gas tungsten arc welding (GTAW) for 304 stainless steel were studied to determine the critical factors for weld pool formation, such as weld surface deformation and weld pool shape. This study was accomplished through an analytical study of weld pool stability as a function of primary welding parameters (arc current and arc holding time), material properties (surface tension and density), and melting efficiency (cross-sectional area). The stability of weld pool shape and weld surface deformation was confirmed experimentally by changing the welding position. The arc current and translational velocity were the major factors in determining the weld pool stability as a function of the gravitational orientation. A 200A spot GTAW showed a significant variation of the weld pool formation as the arc held longer than 3 seconds, however the weld pool shape and surface morphology for a 165A spot GTAW were 'stable', i.e., constant regardless of the gravitational orientation. The cross-sectional area of the weld (CSA) was one of the critical factors in determining the weld pool stability. The measured CSA ($13.5mm^2$) for the 200A spot GTAW showed a good agreement with the calculated CSA ($14.9mm^2$).

• 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.

• 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 Welding and Joining
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• v.16 no.2
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• pp.40-47
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• 1998

In the present study, depressions of the GMA weld pool due to the impact of droplet are numerically investigated. The numerical simulation is conducted on the basis of the Navier-Stokes equation and the volume of fluid(VOF) functions. The kinetic energy of transferring droplet makes a depression of the weld pool surface. The surface active element affects the depression of the weld pool. The droplets transferred efficiently to the bottom of the weld pool, along with electromagnetic force make the finger shape penetration at the high current GMAW.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.307-313
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• 2002

This paper describes a weld pool monitoring technique, which is based on the weld pool image analysis. The proposed image analysis algorithm uses machine vision techniques to extract geometrical information from the weld pool image such as maximum weld pool width, gap width and misalignment between the joint longitudinal axis and the welding wire. These can be related to the welding parameters (welding voltage and current, wire feed speed and standoff) to produce control actions necessary to ensure that the required weld quality will be achieved. The experiments have shown that the algorithm is able to produce good estimates of the weld pool geometry; however, the adjustment of the camera parameters affects the image quality and, consequently, has a great influence over the estimation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.2
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• pp.575-583
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• 1991

The weld pool convection problem that occurs during the stationary GTA welding has been studied, considering the four driving forces for weld pool convection, i.e., the electromagnetic force, the buoyancy force, the aerodynamic drag force, and the surface tension force at the weld pool surface. In the numerical simulation, the difficulties associated with the irregular moving liquid-solid interface have been successfully overcome by adopting a Boundary-Fitted Coordinate system. In the experiments to show the validity of the numerical analysis, a deep periphery and shallow centerpentrated weld pool shape was observed from the etched specimen. It could be revealed that this type of weld pool shape could be simulated, only when some of aerodynamic drag force distributions are considered. Although slight disagreement arose, the calculated and the observed weld pool shapes were in a reasonable agreement.

• 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.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.23-30
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• 2001

Among the various welding conditions, the welding current that is inversely proportional to the tip-to-work-piece distance is an essential parameter as to monitor the GMAW process and to implement the welding automation. Considering the weld pool surface geometry including weld defects, it should modify the signal processing method for automatic seam tracking in horizontal fillet welding. To meet the above necessities, a mathematical model related with the weld pool geometry was proposed as in a conjunction with the two-dimensional heat flow analysis of the horizontal fillet welding. The signal processing method based on the artificial neural network (Adaptive Resonance Theory) was proposed for discriminating the sound weld pool surface from that with the weld defects. The reliability of the numerical model and the signal processing method proposed were evaluated through the experiments of which showed that they are effective for predicting the weld bead shape with or without the weld defects in a horizontal fillet welding.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.89-95
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• 1997

Welding technique is widely applied to general industry such as pressure vessel for chemical plant, pipe system, heavy industry, and automobile. There are some points which must be considered when robot system is used in welding automation process for productivity improvement. Welding quality is governed by heat input, and this quantity can be different according to shape, property, and thick of material . For desired heat input , weld input parameters such as welding voltage, current, and welding velocity must be determined with those consideration. Until now these parameters have been determined mainly by experience of operator. In this study, the size of welding zone was predicted by fuzzy rules were constructed from the relation between welding variables and weld pool size. Inverse model method which welding control input for welder is determined with optimum voltage and current by fuzzy controller is validatied by computer simulation.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1294-1298
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• 2007

Welding process monitoring is advantageous for maintaining weld quality and numerous sensing techniques have been developed for laser welding. Coaxial image monitoring enables direct monitoring of the weld pool shape and keyhole behavior, but requires the complex optical system and the image processing technique. In this study, we coaxially acquired the weld pool images during laser lap welding by using the camera and special illumination. The welding characteristics - pool width and length, keyhole shape, etc - were extracted by using image processing and the relationship between these characteristics and the penetration depth were investigated.