• Journal of Advanced Marine Engineering and Technology
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• v.36 no.8
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• pp.1076-1082
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• 2012

Today the welding for LNG carrier is known to be possible using arc and plasma arc welding process. But because of the lower energy density, arc welding is inevitable to multi-pass welding for thick plate and has a limit of welding speed compared to laser which is high energy density heat source. When thick plate is welded, weld defect by multi-pass welding and heat-affected zone by high heat-input were formed. Therefore one-pass welding by key-hole has been considered to work out the problems. It is possible for Laser, electron beam, plasma process to do key-hole welding. Nowadays, plasma process has been used for welding membrane of cargo tank for LNG carrier instead of arc process. Recently, many studies have examined to apply laser process to welding of membrane. In this paper, weldability, microstructure and mechanical properties of stainless steel for LNG carrier welded by fiber laser were compared to those by plasma. As a result, although the laser welding has several times faster speed, similar properties and smaller weld and heat affected zone were obtained. Consequently, this study proves the superiority of fiber laser welding for LNG carrier.

• Proceedings of the KWS Conference
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• 1994.10a
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• pp.127-129
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• 1994

• Proceedings of the KWS Conference
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• 1997.05a
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• pp.133-136
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• 1997

• Journal of Welding and Joining
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• v.16 no.3
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• pp.85-94
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• 1998

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.26-26
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• 2009

TIG 용접은 고품질이고 용접인자의 제어가 쉽고 정확하다는 장점이 있지만, 얕은 용입과 낮은 생산성과 같은 단점이 있다. TIG 오비탈 용접에서는 용입의 한계 때문에 작은 루트면과 넓은 그루브를 가공하여 다층 용접을 하며, 루트패스에서는 파이프 진원도에 의한 핏업 시 단차의 문제가 자주 발생하여 많은 현장에서 루트갭을 만들어 수동 용접하는 실정이다. 따라서 생산성이 낮으며 생산 단가가 높고 용접 품질이 작업자에 따라 다르게 된다. 이러한 문제점을 해결하여 자동 오비탈 용접을 위해 단차를 흡수 할 수 있는 용접 공정 개발이 필요하다. 본 연구의 목적은 TIG 용접에서 단차에 따른 용접성을 검토하여 이를 맞대기 용접에 적용했을 때 균일한 이면비드를 얻는 공정을 개발하는 것이다. 따라서 본 연구는 아래보기 자세에서 단차에 따른 용입 특성을 이면비드 및 단면으로 비교 분석하였다. 단차 없이 아크길이만 1mm, 2mm, 3mm로 변경하여 실험한 결과 아크길이가 짧아질수록 표면비드 폭은 좁아졌고 이면비드 폭은 증가하는 경향을 나타내어 아크길이가 짧아질수록 용융효율이 증가하는 것을 확인하였다. 단차 1mm에서 아크길이 3mm를 제외하고 표면비드 및 이면비드가 미려하였다. 하지만 단차 2mm에서는 아크길이 1mm, 2mm, 3mm 전부 이면비드가 생성되지 않았다. 이는 단차로 인해 아크길이가 증가하여 용융효율이 낮아졌기 때문이라 판단된다. 이면비드가 생성되지 못한 시험편을 백 베벨링(0.5mm, 1.0mm, 1.5mm, 2.0mm)하여 실험한 결과 단차 2mm, 아크길이 1-3mm 백 베벨링 2.0mm 적용한 시험편에서 양호한 이면비드를 얻을 수 있었다.

• Journal of Welding and Joining
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• v.13 no.4
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• pp.122-131
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• 1995

An automatic welding equipment for thick plates requires the capability of the seam tracking of the weld line which often includes misalignment of the workpiece and variation of groove width. In this study, an automatic welding equipment and control algorithms based on the arc sensor were proposed for the GMA welding of thick plates which had misalignment and gap variation. The developed system being constituted with 5 axis can be automatically controlled by computer and also automnatically set the welding conditions such as welding current, and voltage. The proposed algorithms for the seam tracking in multi-pass welding of the thick plates were constituted as follows : the detection of weaving-end point for findng the variation of groove width, the control of welding velocity for acquiring a constant thickness deposition of weld metal, and the calculation of groove width and height of an arbitrary pass in the multi-pass weld. As results of the application of the system, it was revealed that the system had a good capability in seam tracking and made an excellent weld quality in V groove butt joint.

• Journal of Welding and Joining
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• v.8 no.1
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• pp.23-30
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• 1990

The robotic welding has been adapted positively in many welding shops forthe purpose of improving the welding efficiency and liberating operators from the severe working atmosphere. But for a large-size structure with thick plates like ship-building and every kind of plants manufacturing, the application of the arc welding robots is not established yet. The reason is assumed that the conventional arc welding robots are not adaptive for multi-pass welding of thick plates whose grooves are not so accurate. As one solution to this problem, a guidance system which uses the welding arc itself as a sensor is largely used. In this study the velocity controller which changes the tip to workpiece distance for regulating the weld proposed. The proportional and integral gain of velocity controller were determined by using the computer simulation of the control system, and the simulation results compared with the experimental ones. It was revealed that the developed control system using the arc sensor principle has a good capability of tracking the weld joint, although some more studies will be needed to refine the model of arc current.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.7-7
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• 2009

TIG 용접에서는 후판 용접의 경우 용입의 한계 때문에 깊고 넓은 그루브 가공을 하여 다층 용접을 한다. 이 때, 그루브를 채우는 용착금속에 의한 응고 수축과 과대한 입열로 인한 변형이 문제시 되고 있다. 변형을 줄이기 위해서는 용착금속의 양과 입열량을 줄여야 한다. 이러한 문제를 해결하기 위해 그루브의 루트패이스를 두껍게 하고 그루브각을 줄여서 용착량을 줄인다. 이때, 좁은 그루브에서 두꺼운 루트패이스를 완전 용입할 수 있는 용접 프로세스가 필요하다. 비드가 좁고 깊은 용입 특성을 가지는 Plasma welding(PAW) 경우에는 좁은 그루브 속에 토치가 접근하기 어려워 적용하기 어렵다. 따라서 접근성이 용이한 TIG 용접에서 높은 용입형상비를 가지는 용접공정 개발이 필요하다. 선행연구로 높은 용입 형상비를 가지는 Active flux Tungsten Inert Gas(ATIG) 용접이 연구되었다. ATIG의 용입 증가 메커니즘으로는 Marangoni effect, 음이온들로 인한 아크 수축 효과, 절연 플럭스에 의한 아크 수축효과 등으로 알려져 있다. 또한 선행연구에서 ATIG에서 Ar가스에 He 또는 $H_2$ 가스를 첨가하면 용입이 더욱 증가하는 것을 확인하였다. 본 연구에서는 A-TIG에 He 가스를 적용하고 아크길이 0.5mm, 1.0mm, 2.0mm와 전극 선단각 30도, 60도, 90도에 따른 용입 형상비와 변형량을 검토하기 위해 실험을 하였다. 실험 결과는 아크길이가 감소할수록 전극 선단각이 증가할수록 용입 형상비는 증가하였고, 변형량은 감소하였다.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.14-23
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. However, in this paper, multipass tracking more than single pass tracking is performed by conventional seam tracking algorithm and developed one. And tracking performances of two algorithm are compared in multipass tracking. As the result, tracking performance in multi-pass welding shows superior conventional seam tracking algorithm to developed one.

• Journal of Welding and Joining
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• v.17 no.5
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• pp.98-106
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• 1999

In GMAW, the spatters are generated according to the variation of the arc. Of the arc is stable, Few spatters are generated. But if unstable, too many spatters are generated. So, this means the spatters are dependent on the arc state. The aim of this study is to accurately estimate the arc state. To do this, the generated spatters were captured under the some welding conditions, and the waveforms of the arc voltage and welding current were collected. From the collected signals, the waveform factors and their standard deviations were extracted. Using these factors as input parameters of multi-layer artificial neural network, the learning for the weight of the generated spatters is performed and the estimation results to the real spatter are assessed. Obtained results are as follow: the linear correlation coefficient between the estimated result and the real spatters was 0.9986. And although the average convergence error was set 0.002, the estimated error to the real spatter was within 0.1 gr/min at each welding condition. In the estimation for the weight generated spatters, the result with multi-layer neural network was far better than with multiple regression analysis. Especially, even though under the welding condition which the arc state is unstable (the spatter is generated much more), very excellent estimation performance was shown.