• 한국공작기계학회논문집
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• 제16권3호
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• pp.81-87
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• 2007

It is important to investigate the relationship between weld process parameters and weld bead geometry for adaptive arc robot welding. However, it is difficult to predict an exact back-bead owing to gap in process of butt welding. In this paper, the quantitative prediction system to specify the relationship external weld conditions and weld bead geometry was developed to get suitable back-bead in butt welding which is widely applied on industrial field. Multiple regression analysis and artificial neural network were used as the research methods. And, the results of two prediction methods were compared and analyzed.

• 한국산학기술학회논문지
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• 제9권4호
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• pp.871-877
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• 2008

Adaptive 아크 로봇 용접을 위한 용접 공정 변수와 용접 부 형상 사이에 상관관계를 조사하는 것은 중요한 일이다. 하지만 맞대기 용접의 공정에 있어 갭으로 인해 정확한 이면비드를 예측하는 것은 어려운 일이다. 본 연구에서는, 먼저 맞대기 용접을 통해 외부 용접 조건과 용접 비드 형상사이 상관관계가 규명되었고, 이를 응용하여 적절한 이면비드를 얻기 위한 개발이 이루어졌고, 이 연구결과는 산업 전 분야에 폭넓게 사용될 수도 있다. 다중회귀분석법이 공정변수 예측을 위한 연구방법으로 적용되었다. 예측방법의 결과들 또한 비교 및 분석이 이루어졌다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2005년도 창립60주년 기념 추계 학술대회
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• pp.206.1-206.1
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• 2005

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1404-1407
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• 1996

A quality monitoring system in butt welding process is proposed to estimate weld pool sizes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to prove the integrity of the weld quality. The monitoring variables used are the surface temperatures measured at three points on the top surface of the weldment. The temperature profile is assumed that it has a gaussian distribution in vertical direction of torch movement and verify this assumption through temperature analysis. A neural network estimator is designed to estimate weld pool size from temperature informations. The experimental results show that the proposed neural network estimator which used gaussian distribution as temperature information can estimate the weld pool sizes accurately than used three point temperatures as temperature information. Considering the change of gap size in butt welding, the experiment were performed on various gap size.

• 한국레이저가공학회:학술대회논문집
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• 한국레이저가공학회 2006년도 추계학술발표대회 논문집
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• pp.17-20
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• 2006

In the remote welding system using $CO_2$ laser, laser beam is rapidly deflected by moving mirrors of scanner system and has focusable distance over 1000mm from workpiece. From such arrangement, various advantages and disadvantages arise. Remote welding is a highly efficient laser process. As the mirrors of the scanner system allow positioning speeds exceeding 700m/s, it becomes possible to reduce the welding cycle time. On the other hand, as there no the provision of shielding gas which is normally required for beam powers exceeding 3kW, may become difficult task. Therefore, In this study, the influence of the various penetration of back bead by the different laser welding speed on the weld seam formation without shielding gas was investigated.

• Journal of Welding and Joining
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• 제12권1호
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• pp.59-72
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• 1994

This paper presents an on-line quality monitoring and control method to obtain a uniform weld quality in gas metal arc welding (GMAW) processes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to assess the integrity of the weld quality. Since a good quality weld is characterized by a relatively high depth-to-width ratio in its dimensions, the second geometrical parameter is regulated to a desired one. The monitoring variables are the surface temperatures measured at various points on the top surface of the weldment which are strongly related to the formation of the weld pool The relationship between the measured temperatures and the weld pool size is implemented on the multilayer perceptrons which are powerful for realization of complex mapping characteristics through training by samples. For on-line quality monitoring and control, it is prerequisite to estimate the weld pool sizes in the region of transient states. For this purpose, the time history of the surface temperatures is used as the input to the neural estimator. The control purpose is to obtain a uniform weld quality. In this research, the weld pool size is directly regulated to a desired one. The proposed controller is composed of a neural pool size estimator, a neural feedforward controller and a conventional feedback controller. The pool size estimator predicts the weld pool size under growing. The feedforward controller compensates for the nonlinear characteristics of the welding process. A series of simulation studies shows that the proposed control method improves the overall system response in the presence of changes in torch travel speed during GMA welding and guarantees the uniform weld quality.