• Journal of Welding and Joining
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• v.14 no.6
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• pp.58-67
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• 1996

The horizontal filet welding is prevalently used in heavy and ship building industries to join the parts. The phenomena occurring in the horizonal fillet welding process are very complex and highly non-linear, so that its analysis is relatively difficult. Furthermore, various kinds of weld defect such as undercut, overlap, porosity. excess weld metal and incomplete penetration can be induced due to improper welding conditions. Among these defects, undercut, overlap and excess weld metal appear frequently in horizontal filet welding. To achieve a satisfactory weld bead geometry without weld defects, it is necessary to study the effect of welding conditions in the weld bead geometry. For analyzing the weld bead geometry with and without weld defects in horizontal fillet welding, a mathematical model was proposed in conjunction with a two-dimensional heat flow analysis adopted for computing the melting tone in . base metal. The reliability of the proposed model was evaluated through experiments. which showed that the proposed model was very effective for predicting the weld bead shape with or without weld defects in horizontal fillet welding.

• Journal of the Korean Institute of Navigation
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• v.23 no.4
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• pp.105-114
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• 1999

Generally, though we use the vision sensor or arc sensor in welding process, it is difficult to define the welding parameters which can be applied to the weld quality control. Especially, the important Parameters is Arc Voltage, Welding Current, Welding Speed in arc welding process and they affect the decision of weld bead shape, the stability of welding process and the decision of weld quality. Therefore, it is difficult to determine the unique relationship between the weld bead geometry and the combination of various welding condition. Due to the various difficulties as mentioned, we intend to use Fuzzy Logic and Neural Network to solve these problems. Therefore, the combination of Fuzzy Logic and Neural network has an effect on removing the weld defects, improving the weld quality and turning the desired weld bead shape. Finally, this system can be used under what kind of welding recess adequately and help us make an estimate of the weld bead shape and remove the weld defects.

• Journal of Welding and Joining
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• v.17 no.2
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• pp.53-60
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• 1999

Conventionally, CCD camera and vision sensor using the projected pattern of light is generally used to inspect the weld bead defects. But with this method, a lot of time is needed for image preprocessing, stripe extraction and thinning, etc. In this study, laser vision sensor using the scanning beam of light is used to shorten the time required for image preprocessing. The software for deciding whether the weld bead is in proper shape or not in real time is developed. The criteria are based upon the classification of imperfections in metallic fusion welds(ISO 6520) and limits for imperfections(ISO 5817).

• International Journal of Korean Welding Society
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• v.1 no.2
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• pp.36-44
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• 2001

To get the appropriate welding process variables, mathematical modeling in conjunction with many experiments is necessary to predict the magnitude of weld bead shape. Even though the experimental results are reliable, it has a difficulty in accurately predicting welding process variables for the desired weld bead shape because of nonlinear and complex characteristics of welding processes. The welding condition determined for the desired weld bead shape may cause the weld defect if the welding current/voltage/speed combination is improperly selected. In this study, the $2^{n-1}$ fractional factorial design method and correlation parameter were used to investigate the effect of the welding process variables on the fillet joint shape, and the multiple non-linear regression analysis was used for modeling the gas metal arc welding(GMAW）parameters of the fillet joint. Finally, a fuzzy rule-based method and a neural network method were proposed so that the complexity and non-linearity of arc welding phenomena could be effectively overcome. The performance of the proposed neuro-fuzzy system was evaluated through various experiments. The experimental results showed that the proposed neuro-fuzzy system could effectively check the welding conditions as to whether or not weld defects would occur, and also adjust the welding conditions to avoid these weld defects.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.87-92
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• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.189-193
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• 1997

Generally, though we use the vision sensor or arc sensor in welding process, it is difficult to define the welding parameters which can be applied to the weld quality control. Especially, the important parameters is Arc Voltage, Welding Current, Welding Speed in arc welding process and they affect the decision of weld bead shape, the stability of welding process and the decision of weld quality. Therefore, it is difficult to determine the unique relationship between the weld bead geometry and the combination of various welding condition. Due to the various difficulties as mentioned, we intend to use Fuzzy Logic and Neural Network to solve these problems. Therefore, the combination of Fuzzy Logic and Neural network has an effect on removing the weld defects, improving the weld quality and turning the desired weld bead shape. Finally, this system can be used under what kind of welding process adequately and help us make an estimate of the weld bead shape and remove the weld defects.

• Journal of Welding and Joining
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• v.15 no.3
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• pp.88-98
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• 1997

Welding defects, such as porosity and spike, have sometimes occurred in deep penetration electron beam welds. These defects are known to be one of the serious problem in electron beam welds. So, effects of active parameters ($a_b$) on bead shape and occurrence of defects in electron beam welds of heavy section 9%Ni steel plates were investigated. Partial penetration welding in flat position, and deep penetration welding of 10 ~ 28mm depth were investigated in this study. It is desirable to select low accelerating voltage and above the surface focus position $a_b$$\geq$1.2 at which a wine-cup shaped bead is obtained to avoid the welding defects such as spike and root porosity. When the accelerating voltage of electron beam was low (90kV), active parameter ($a_b$) did not influence on the bead width, penetration depth and weld defects significantly. However, in case of high voltage ($\geq$120kV), active parameter ($a_b$) was sensitively associated with penetraton depth and weld defects, i.e. when the active parameter (($a_b$) was in the range of 0.6 to 1.0, the depth of penetration was always over the target (23mm), while the depth of penetration was dramatically decreased with further increase of active parameter ($a_b$). The weld defects were decreased with the increase of active parameter $a_b$ resulting in the decrease of energy density of the focused beam in the root part of fusion zone.

• Journal of Ocean Engineering and Technology
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• v.24 no.4
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• pp.38-46
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• 2010

The wall thinning phenomenon of pipes was simulated as metal loss due to erosion and corrosion. Such wall thinning defects in the pipes of power plants are a very important safety consideration. In this study, we analyzed wall thinning defects that occurred by weld bead of weld zone of boost pump recirculation pipe. From the results of the analysis of pipe failures, numerical analysis was performed by Fluent v6.3.26 using the standard k-$\varepsilon$ model of the weld bead shape, such as an elliptical or a spherical shape, on the inner wall of the pipe. Using the results obtained, we showed the overlap effect by cavitations corrosion and erosion-corrosion at the bottom of the wall-thinning defect.

• Journal of Welding and Joining
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• v.34 no.6
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• pp.62-68
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• 2016

Laser welding has superior characteristic such as low distortion, high welding speed, easy automation and real time control. But it is easy to occur weld defects such as porosity, crater, humping bead in the area of welding start and end. These weld defects can be suppressed by applying the wave shape control. In this study CW fiber laser was used for welding of $0.5mm^t$ pure titanium. Penetration properties were evaluated with the time of slope up and down. After then the bead shape was observed, and the maximum depth and the area of crater were measured. The bead shape of welding start area changed to be sharp with increase of slope up time and non-weld area of welding start increased. The crater and humping bead were suppressed with slope down time. The cooling rate of crater area was understood through measure of the hardness. Also, The distribution tendency of alloying elements was observed by EPMA and EDS. When wave shape control didn't applied to weld, the hardness of end weld increased due to rapid cooling rate and the hardness of rear part in the crater was higher than that of fore part. On the other hand, when the wave shape control was used for end weld, the increase of hardness in the end weld couldn't be found due to gradual cooling rate.

• 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.