• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.17 no.5
• /
• pp.30-35
• /
• 2008

As the quality of a weld feint is strongly influenced by process parameters during the welding process, an intelligent algorithms that can predict the bead geometry and shape to accomplish the desired mechanical properties of the weldment should be developed. This paper focuses on the development of mathematical models fur the selection of process parameters and the prediction of bead geometry(bead width, bead height and penetration) in robotic GMA(Gas Metal Arc) welding. Factorial design can be employed as a guide for optimization of process parameters. Three factors were incorporated into the factorial model: arc current, welding voltage and welding speed. 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. The results obtained show that developed mathematical models can be applied to estimate the effectiveness of process parameters for a given bead geometry, and a change of process parameters affects the bead width and bead height more strongly than penetration relatively.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.21 no.6
• /
• pp.8-14
• /
• 2022

In this study reports experiments were conducted to determine the quality of weld beads of different materials, Al and Cu. Among the lasers used to make battery cells for electric vehicles, non-destructive testing was performed using deep learning to determine the quality of beads welded with the ARM laser. Deep learning was performed using AlexNet algorithm with a convolutional neural network structure. The results of quality identification were divided into good and bad, and the result value was derived that all the results were in agreement with 94% or more. Overall, the best welding quality was obtained in the experiment for the fixed ring beam output/variable center beam output, in the case of the fixed beam (ring beam) 500W and variable beam (center beam) 1,050W; weld bead failure was seldom observed. The tensile force test to confirm the reliability of welding reported an average tensile force of 2.5kgf/mm or more in all sections.

• Proceedings of the KWS Conference
• /
• 2009.11a
• /
• pp.82-82
• /
• 2009

Although leakage at a low carbon steel pipe made by electrical resistance welding(ERW) was reported due to grooving corrosion, the cause for the corrosion has not yet been cleared. So lots of researches were carried out already about grooving corrosion mechanism of ERW carbon steel pipe but there is seldom study for water hammer happened by fluid phenomenon and corrosion rate by flow velocity. In this study, the corrosion test carried out using the ERW carbon steel pipe by changed the water speed and heat input in a month. The level of dissolved oxygen is maintained 5~5.5mg/l(amount of dissolved oxygen in tap water). The water speed for corrosion test is 1m/s, 2m/s, 3m/s. As the results, grooving corrosion rate is increased cause by water speed in the pipe. In the case of the ERW pipe with more heat input, grooving corrosion rate is decreased. It is therefore that welding heat input should be controlled based on the carbon content of the pipe in order to improve the corrosion reistance of the ERW pipe.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.4
• /
• pp.363-371
• /
• 2023

To construct a ship, blocks of various sizes must be moved and erected . In this process, lugs are used such that they match the block fastening method and various functions suitable for the characteristics of each shipyard facility. The sizes and shapes of the lugs vary depending on the weight and shape of the block structures. The structure is reinforced by welding the doubling pads to compensate for insufficient rigidity around the holes where the shackle is fastened. As for the method of designing lugs according to lifting loading conditions, a simple calculation based on the beam theory and structural analysis using numerical modeling are performed. In the case of the analytical method, a standardized evaluation method must be established because results may differ depending on the type of element and modeling method. The application of this ambiguous methodology may cause serious safety problems during the process of moving and turning-over blocks. In this study , the effects of various parameters are compared and analyzed through numerical structural analysis to determine the modeling conditions and evaluation method that can evaluate the actual structural response of the lug. The modeling technique that represents the plate part and weld bead around the lug hole provides the most realistic behavior results. The modeling results with the same conditions as those of the actual lug where only the weld bead is connected to the main body of the lug, showed a lower ulimated strength compared with the results obtained by applying the MPC load. The two-dimensional shell element is applied to reduce the modeling and analysis time, and a safety working load was verified to be predicted by reducing the thickness of the doubling pad by 85%. The results of the effects of various parameters reviewed in the study are expected to be used as good reference data for the lug design and safe working load prediction.

• Journal of Welding and Joining
• /
• v.34 no.1
• /
• pp.54-58
• /
• 2016

In this research paper, suggest method of generate same bead as an actual measurement data in virtual welding conditions, exploit morphology information of the bead that acquired through robot welding. It has many multiple risk factors to Beginners welding training, by we make possible to train welding in virtual reality, we can reduce welding training risk and welding material to exploit bead visualization algorithm that we suggest so it will be expected to achieve educational, environmental and economical effect. The proposed method is acquire data to each case performing robot welding by set the voltage, current, working angle, process angle, speed and arc length of welding condition value. As Welding condition value is most important thing in decide bead form, we would selected one of baseline each item and then acquired metal followed another factors change. Welding type is FCAW, SMAW and TIG. When welding trainee perform the training, it's difficult to save all of changed information into database likewise working angle, process angle, speed and arc length. So not saving data into database are applying the method to infer the form of bead using a neural network algorithm. The way of bead's visualization is applying the spline algorithm. To accurately represent Morphological information of the bead, requires much of morphological information, so it can occur problem to save into database that is why we using the spline algorithm. By applying the spline algorithm, it can make simplified data and generate accurate bead shape. Through the research paper, the shape of bead generated by the virtual reality was able to improve the accuracy when compared using the form of bead generated by the robot welding to using the morphological information of the bead generated through the robot welding. By express the accurate shape of bead and so can reduce the difference of the actual welding training and virtual welding, it was confirmed that it can be performed safety and high effective virtual welding education.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.25 no.1
• /
• pp.30-35
• /
• 2016

Tandem arc welding is a guarantor for high efficiency and cost saving since the quantity of wire which is deposited in the welding is approximated 30% greater that in conventional welding. The welding process is now being successfully applied in many industries. However, in the case of tandem arc welding, good quality and high productivity should depend on the welding parameters. Therefore, an intelligent algorithms for the automatic tandem arc welding process has been necessarily required. In this study, a predictive model based on the neural network by using the data acquired during tandem gas metal arc (GMA) welding process has been developed. To verify the reliability of the developed predictive model, a mutual comparison with the surface of the top-bead width obtained from actual experiments has been analyzed.

• Journal of the Korean Society of Industry Convergence
• /
• v.5 no.2
• /
• pp.111-118
• /
• 2002

In GMAW(Gas Metal Arc Welding) processes, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality, Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWD (contact-tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using neuro-fuzzy algorithm. Neural networks was applied to design FLC(fuzzy logic control), The parameters of input membership functions and those of consequence functions in FLC were tuned through the method of learning by backpropagation algorithm, Bead geometry could he reasoned from welding current, arc voltage, travel speed on FLC using the results learned by neural networks. On the developed inference system of bead geometry using neuo-fuzzy algorithm, the inference error percent of bead width was within ${\pm}4%$, that of bead height was within ${\pm}3%$, and that of penetration was within ${\pm}8%$, Neural networks came into effect to find the parameters of input membership functions and those of consequence in FLC. Therefore the inference system of welding quality expects to be developed through proposed algorithm.

• Journal of Welding and Joining
• /
• v.31 no.5
• /
• pp.35-40
• /
• 2013

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.11
• /
• pp.4732-4737
• /
• 2011

A standing grinder with a vacuum dust collection, which works grinding a surface and collecting dust occurred simultaneously, is needed to clean the surface before painting, or to remove a weld bead burr in the industrial field. In recent it trends to be compact and potable with high grinding and dust collection power, and low noise. As increasing these grinding and dust collection power, the noise and weight of standing grinder occurs an important problem. To solve these problem, an efficient cyclone separator was designed and developed by Ansys-CFX analysis and experiments. A weight of the developed grinder part was 5.9kg, which can be easily handled on standing by workers. and a noise level of the developed prototype was measured 69.9 dB(A).

• Korean Journal of Materials Research
• /
• v.8 no.7
• /
• pp.648-652
• /
• 1998

TIG remelting was performed to harden the surface of automobile earn shaft. Multipass remelting was conducted in longitudinal direction under argon gas atmosphere. The microstructure of as-east earn shaft was gray iron which consisted of flake graphite and pearlitic matrix. The remelted area had microstructue of both fine pearlite and ledeburite structure that consisted of globular austenite and $Fe_3C$. Hardness for as-cast earn shaft had HRc 25~28, however it increased at remelted area to HRc 53~55. Black line was found at heat affected zone next to the fusion line, that is remelt area of previous pass, during multipass remelting. Black line was identified as graphite, which was transformed from $Fe_3C$. in the ledeburite structure. It is observed that all graphites were nucleated at $Fe_3C$. and matrix interface. High density energy laser remelting process was also applied to verify whether black line could be eliminated. However, black line was still existed as observed in TIG remelting process. Regraphitization was simulated on the ledeburitic structure specimen using Gleeble 1500 with conditions of 1100 and 100$0^{\circ}C$ for 0.5, I, 3, 5 and 1Osee. From the fact that graphite was formed even at the simulation condition of 100$0^{\circ}C$ for 0.5sec, it is seen that regraphitization is an inevitable phenomenon generated whatever processes used during multipass overlap remelting.