• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.4
• /
• pp.871-877
• /
• 2008

It is important to investigate the relationship between weld process parameters and weld bead geometry for adaptive arc robot welding. Howeve, 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 for the prediction of process parameters was used as the research method. And, the results of the prediction method were compared and analyzed.

• Journal of Welding and Joining
• /
• v.28 no.6
• /
• pp.21-27
• /
• 2010

Due to excellent weld quality, orbital welding with TIG is widely applied to pipe welding. But concave back bead is formed easily in overhead and inclined-up position of butt orbital welding. It is difficult to find a paper to overcome this problem. In this study, in order to make convex back bead in overhead and inclined-up position of pipe 5G welding, control method of molten pool was actively investigated. Melt run welds were conducted on thickness 4.0mm SS400 with overhead and inclined-up position and was observed the variation of bead shape after welding with the bead former developed. The height of back bead showed the trend of increase as the distance from molten pool to the bead former was decreased. Also, there is no trend in the bead width of front and back as welding position was changed or the distance from molten pool to the bead former was decreased.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1845-1848
• /
• 2005

The automatic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. A sensitivity analysis has been conducted and compared the relative impact of three process parameters on bead geometry in order to verify the measurement errors on the values of the uncertainty in estimated parameters.

• International Journal of Korean Welding Society
• /
• v.3 no.2
• /
• pp.15-23
• /
• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Korean Journal of Materials Research
• /
• v.14 no.1
• /
• pp.1-8
• /
• 2004

Laser weldability of aluminized steels for deep drawing application has been investigated. Test coupons for Nd:YAG laser welding and $CO_2$ laser welding were prepared trom the commercial steels. According to the test results, total penetration and back bead width of aluminized steels were sensitive to the welding conditions. Bead width at the half thickness of the overlap joint, however, was rather constant. Laser weldability of aluminized steels was superior to that of zinc coated steel. Weld microstructure revealed that overlap zone adjacent to the fusion line was filled with coated materials, which was thought to be desirable to protect weld from crevice corrosion. The aluminum coated materials was also found in the weld metal. Practically no spattering was observed in the laser welding of aluminized steels even when the welding was performed without joint gap. In the welding of zinc coated steel, however, spattering was so severe that it was difficult to get the acceptable weld. Bead quality of aluminized steel laser weld was smooth and stable.

• Proceedings of the KWS Conference
• /
• 2009.11a
• /
• pp.23-23
• /
• 2009

우수한 용접부 품질 때문에 TIG를 이용한 오비탈 용접은 파이프 용접에 널리 사용되고 있다. 하지만 루트갭이 없고 루트페이스가 큰 맞대기 오비탈 용접의 위보기 및 경사상진자세에서는 오목한 이면비드가 형성되기 쉽지만, 이러한 문제를 극복하기 위한 연구는 희박한 실정이다. 본 연구에서는 위보기 및 경사상진자세에서 볼록한 이면비드의 형성을 연구하기위해서 용융지의 제어 방법을 적극적으로 검토하였다. 4mm 두께의 SS400 시편을 위보기 및 경사상진자세에서 각각 Bead-on-plate 용접하고, 이 때 비드성형기의 사용에 따른 비드 형상 변화를 관찰하였다. 텅스텐 전극과 비드 성형기간의 거리(Tip To Former Distance, 이하 TTFD)를 4.5mm에서 7.5mm로 1mm단위로 변경시켜 실험하였으며, TTFD가 증가할수록 위보기 및 경사상진자세에서 이면비드 높이가 감소하였으며 표면비드의 처짐이 증가하였다.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.596-599
• /
• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.

• International Journal of Korean Welding Society
• /
• v.1 no.1
• /
• pp.17-22
• /
• 2001

Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.21 no.2
• /
• pp.349-353
• /
• 2012

As the world wind energy market grows rapidly, the productions of wind power generation equipment have recently increased, but manufacturers are not able meet this requirement. Particularly offshore wind energy industry is one of the most popular renewable energy sectors. To generalize welding processes, the welding automation is considered for steel structure manufacturing in offshore wind energy to get high quality and productivity. Welding technology in construction of the wind towers is depended on progress productivity. In addition, the life of wind tower structures should be considered by taking account of the natural weathering and the load it endures. The root passes are typically deposited using Gas Tungsten Arc Welding(GTAW) with a specialized backing gas shield. Not only the validation consists of welders experienced in determining the welding productivity of the baseline welding procedure, but also the standard testing required by the ASME section IX and API1104 codes, toughness testing was performed on the completed field welds. This paper presents the welding characteristics of the root-pass welding of high tensile steel in manufacturing of offshore wind tower. Based on the result from welding experiments, optimal welding conditions were selected after analyzing correlation between welding parameters(peak current, background current and wire feed rate) and back-bead geometry such as back-bead width(mm) and back-bead height performing root-pass welding experiment under various conditions. Furthermore, a response surface approach has been applied to provide an algorithm to predict an optimal welding quality.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.289-294
• /
• 1988

This paper describes tbe design and implementation of the adaptive controller to maintain the glood weld quality in gas metal arc welding process. The weld torch travel speed and the surface temperature are taken, respectively, as an input and an output of the welding control system. Because of the very complex phenomena of the process, the input-output dynamic model was experimentally identified by AIC (Akiake Information Criterion). Based on the model structure, the explicit model reference adaptive controller is simulated in order to regulate the output tempernture to the desired level.