• 건축구조
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• v.22 no.4
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• pp.25-34
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• 2015

• Proceedings of the KWS Conference
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• 1997.05a
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• pp.107-111
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• 1997

In this paper distribution of welding residual stress on the double fillet welded joint which exits and not exits root gap, i.e. full penetration and partial penetration is investigated by two dimensional cunduct and thermal elasto-plastic analysis. And stress distribution on notch-tip of the structure where welding residual stress regarded as initial stress and then external load is added is also investigated.

• Proceedings of the KWS Conference
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• 2005.11a
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• pp.88-90
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• 2005

• Journal of Welding and Joining
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• v.11 no.4
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• pp.44-56
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• 1993

The arc welding processes are substantially nonlinear, in addition to being highly coupled multivariable systems, Frequently, not all the variables affecting the welding quality are known, nor may they be easily quantified. From this point of view, decoupling between the welding parameters from the welding quality is very difficult, which makes it also difficult to control the welding parameters for obtaining the desired welding quality. In this study, a neural network based on the backpropagation algorithm was implemented and adopted for the selection of gas metal arc welding parameters of the fillet joint, that is, welding current, arc voltage and welding speed. The performance of the neural network for modeling the relationship between the welding quality and welding parameters was presented and evaluated by using the actual welding data. To obtain the optimal neural network structure, various types of the neural network structures were tested with the experimental data. It was revealed that the neural network can be effectively adopted to select the appropriate gas metal arc welding parameter of fillet joints for a given weld quality.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1054-1061
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• 2011

GMA welding process is a production process to improve productivity for the provision of higher quality of material, These includs numerous process variables that could affect welding quality, productivity and cost savings. Recently, the welding part of construction equipment had frequent failure of major components in the welding part of each subsidiary material due to shock which is very poor according to the welding part. Therefore, the implementation of sound welding procedure is the most decisive factor for the reliability of construction machinery. The data generated through experimens conducted in this study has validated its effectiveness for the optimization of bead geometry and process variables is presented. The criteria to control the process parameters, to achieve a healthy bead geometry. This study has developed mathematical models and algorithms to predict or control the bead geometry in GMA fillet welding process.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.7-13
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• 2001

This Study is to investigate the influence of weld residual stresses on the fatigue crack growth behaviors in pressure ves-sel reinforcement. In order to perform this study, the automatically welded specimens are prepared. The material is ASTM A516 grade 60 steel used in pressure vessel mainly. For pad-on-plate of skip welding continuous welding and PWHT specimen, fatigue crack initiation is generally initiat-ed at weld starting and end toe zone, and ruptured at weld starting toe zone, Fatigue life if pad-on-plate continuous speci-men is increased more than that of pad-on-plate skip fillet welding specimene about 85% under low load, about 20% under high load, and decreased than that of two-pad continuous welding specimen about 85%. In da/dN-$\Delta$ Κ curve under low load, pad-on-plate skip fillet welding specimen showed retardation on the initial crack, and the fatigue crack growth rate at the low region of $\Delta$Κ greater specimene E(3.8{\times}10^{-6}$mm/cycle). And the fatigue life of welding specimen was smaller than that of PWHT specimen.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.1
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• pp.26-33
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• 2014

In this study, Non-load-carrying EH Grade steels in fillet welded joints were evaluated with both the hot spot stress method and the 1mm stress method. The thickness effect criterion for fatigue strength evaluation of welded of welded steel structures recommendations of the IIW was used to evaluate the fatigue strength of EH40 and EH36 and Both EH40 and EH36 have been compared with FAT 125 curve recommended in the IIW. Furthermore, fatigue strength of the welded tow and the ground conditions for Non-load-carrying EH36 based on the 1mm stress method has been discussed.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.10-10
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• 2009

파이프 용접은 중력의 영향으로 인하여 위치에 따라 같은 용접변수라도 비드 형상이 매우 달라 지게 된다. 또한 지금까지 많은 용접 기술자들이 위험하고 까다로운 환경에서 수작업으로 용접을 실행하였다. 따라서 이러한 이유로 용접 자동화 공정이 반드시 필요하게 된다. 본 연구에서는 FCAW를 사용하여 파이프 모재 대신 필릿 평판을 아래보기, 위보기 자세를 포함하여 9개 자세에서 실행하였다. 용접 자세를 비롯한 용접 변수와 비드 형상 변수간의 관계를 비선형 회귀 분석과 구간적 3차 에르미트 보간법을 이용하여 주어진 용접 변수에서의 비드 단면의 형상을 예측하고, 비드의 결함 유무를 파악하였다. 이러한 방법을 통하여 자세에 따라서 용접 결함이 없는 용접 변수를 구할 수 있었다. 시각센서를 이용하여 용접 후 비드 형상에 대해 모니터링을 실시하였다. 모니터링의 알고리즘은 영상획득, 이진화, 세선화, 적응형 미디언 필터링, 적응형 허프 변환, 용접 결함 검출의 순서로 구성되어 있으며, 본 연구에서는 보다 빠른 영상처리를 위하여 적응형 미디언 필터링을 제시하였다. 모니터링을 통하여 2차원 비드 단면뿐만 아니라, 디루니 삼각법을 적용하여 3차원으로 비드 표면을 표현할 수 있다. 보간법을 사용하여 얻은 비드 형상과 시각 센서를 통하여 얻은 비드 형상간의 비교를 통하여 본 연구의 적합성 여부를 확인하였다.

• Journal of Welding and Joining
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• v.13 no.2
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• pp.68-81
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• 1995

This paper presents an analytical solution to predict the transient temperature distribution in fillet arc welding. The analytical solution is obtained by solving a transient three -dimensional heat conduction equation with convection boundary conditions on the surfaces of an infinite plate with finite thicknesses, and mapping an infinite plate onto the fillet weld geometry with energy equation. The electric arc heat input on fillet weld and on infinite plate is assumed to have a traveling bivariate Gaussian distribution. To check the validity of the solution, GTA and FCA welding experiments were performed under various welding conditions. The actual isotherms of the weldment cross - sections at various distances from the arc start point are compared with those of simulation result. As the result shows a satisfactory accuracy, this analytical solution can be used to predict the transient temperature distribution in the fiIIet weld of finite thickness under a moving bivariate Gaussian distributed heat source. The simplicity and short calculation time of the analytical solution provides rationales to use the analytical solution for modeling the welding control systems or for an optimization tool of welding process parameters.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.49-55
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• 2008

Arc welding process is one of the most important technologies to join metal plates. Robotic welding offers the reduced manufacturing cost sought, but its widespread use demands a means of sensing and correcting for inaccuracies in the part, the fixturing and the robot. A number of problems that need to be addressed in robotic arc welding processes include sensing, joint tracking, and lack of adequate models for process parameter prediction and quality control. Problems with parameter settings and quality control occur frequently in the GMA(Gas Metal Arc) welding process due to the large number of interactive process parameters that must be set and accurately controlled. The objectives of this paper are to realize the mapping characteristics of bead width using a sensitivity analysis and develop the neural network and multiple regression method, and finally select the most accurate model in order to control the weld quality(bead width) for fillet welding. The experimental results show that the proposed neural network estimator can predict bead width with reasonable accuracy, and guarantee the uniform weld quality.