Aluminum material, which has excellent corrosion resistance, durability, and light weight, is widely used in the field of shipbuilding, and welding is an essential technology in shipbuilding. currently, welding is efficiently used to assemble structures of various sizes in the shipbuilding process, but aluminum is a very sensitive material at high temperatures and in a molten state, so appropriate process control is essential. research on aluminum welding has been continuously conducted, but most of the research is on the butt welding method. therefore, in this study fillet welding experiments, which are essentially applied to the internal structure of aluminum ships, were performed and the correlation between welding beads and process variables was identified. for the welding experiment GMA fillet welding was performed on Al5083 material used in the shipbuilding industry, and the influence of the process variable was confirmed by analyzing the correlation through the analysis of the etched fillet weld bead cross section for the test result according to the process variable.

In this study, experiments and simulations were performed for fillet joint friction stir welding according to tool shape and welding conditions. Conventional butt friction stir welding has good weldability because heat is generated by friction with the bottom of the tool shoulder. However, in the case of fillet friction stir welding, the frictional heat is not sufficiently generated at the bottom of the tool shoulder due to the shape of the tool and the shape of the joint. Therefore, it is important to sufficiently generate frictional heat by slowing the welding speed as compared to butt welding. In this study, experiments and simulations were carried out on an aluminum battery housing made by friction stir welding an extruded material with a fillet joint. The temperature of the structure was measured using a thermocouple during welding, and the heat source was calculated through correlation analysis. Thermal elasto-plastic analysis of the structure was carried out using the calculated heat source and geometric boundary conditions. It is confirmed that the experimental results and the simulation results are well matched. Based on the results of the study, the deformation of the structure can be calculated through simulation even if the tool shape and welding process conditions change.

The bead geometry according to the welding conditions was analyzed through the laser fillet welding experiment of 9% Ni steel, and the relationship between the shear strength and the five bead geometry measured by selecting the main bead geometry of the fillet weld was analyzed. Among the welding conditions, the welding conditions that directly affect the penetration depth are welding speed and laser power, and the working angle and beam position have a great influence on the formation of leg of vertical and horizontal members. The bead shape, which greatly affects the shear strength, is the horizontal member length, neck thickness, and weld length, and has a proportional relationship with the shear strength. As a result of confirming the relationship between shear strength and bead shape through the derivation of the trend line, it was confirmed that the length of the vertical member, whose R2 value was 0.92, was most closely related to the shear strength.

오스테나이트계 스테인리스강은 우수한 내식성, 내구성 및 내화성을 지닌다. 특히, 오스테나이트계 스테인리스강중의 대표인 STS304에 비해 저탄소를 함유하고 있는 STS304L은 현장용접 후 별도의 열처리 없이 높은 내입계부식성능을 지니고 있어 용접후 내입계 부식이 우려되는 부재접합에 적용할 수 있다. 본 연구에서는 티그(TIG)용접으로 필릿 용접된 STS304L 용접접합부의 용접재(용착금속부) 내력과 파단 메카니즘을 조사하고자 한다. 주요변수인 하중방향에 대한 용접선의 배치에 따라 TFW(하중직각방향 용접), LFW(하중방향용접), FW (하중방향용접과 하중직각방향 용접조합)시리즈의 실험체를 제작하여 인장실험을 실시하였고, 각각 인장파단,전단파단, 블록전단파단(인장 파단과 전단파단의 조합)이 발생하였다. 동일 용접길이에 대해 TFW 시리즈의 접합부가 가장 높은 내력을 나타났으며, 현행기준식( KBC2016/AISC2010)과 기존 연구자의 식에 의한 예측내력과 비교한 결과, TFW와 LFW접합부는 과소평가되었고 FW실험체는 과대평가되었다 .실제 파단 위험단면과 블록전단파단 메카니즘을 고려한 내력식을 제안하였다.

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.