• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.132-139
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• 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 FL(fuzzy logic). The parameters of input membership functions and those of consequence functions in FL were tuned through the method of learning by backpropagation algorithm. Bead geometry could be reasoned from welding current, arc voltage, travel speed on FL using the results learned by neural networks. On the developed inference system of bead geometry using neuro-furzy 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 FL. Therefore the inference system of welding quality expects to be developed through proposed algorithm.

• Journal of Welding and Joining
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• v.27 no.1
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• pp.95-101
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• 2009

In case of manufacturing the high quality welds or pipeline, the full penetration weld has to be made along the weld joint. Thus the root pass welding is very important and has to be selected carefully. In this study, an experimental method for the selection of optimal welding condition was proposed in the root pass welding which was done along the V-grooved butt weld joint. This method uses the response surface analysis in which the width and height of back bead were chosen as the quality variables of the weld. The overall desirability function, which is the combined desirability function for the two quality variables, was used as the objective function for getting the optimal welding condition. In the experiments, the target values of the back bead width and the height are 6mm and zero respectively for the V-grooved butt weld joint of 8mm thickness mild steel. The optimal welding conditions could predict the back bead profile(bead width and height) as 6.003mm and -0.003mm. From a series of welding test, it was revealed that a uniform and full penetration weld bead can be obtained by adopting the optimal welding condition which was determined according to the method proposed.

• Journal of Welding and Joining
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• v.20 no.2
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• pp.65-70
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• 2002

This study was to evaluate GMA welding characteristics of the A15083-O aluminum alloy according to the shield gas mixing ratio and heat input change. The GMA welding of the base metal was carried out with flour different shield gas mixing ratios(Ar100%+He0%, Ar67%+He33%, Ar50%+He50%, and Ar33%+He67%). Regarding the if1uence on the bead shape of the shield gas mixing ratio and heat input, the bead width was greatest in Ar100%+He0% mixture. But the penetration depth and area were greatest in Ar33%+He67% mixture considering that the lower Ax gas ratio, the higher bead depth and area. Also, dilution was also best in the shield gas mixing ratio. The size and number of deflects were least in Ar33%+He67% mixture. Higher He gas ratio resulted in less deflects detected by the radiographic inspection.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.191-196
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• 2005

A full-bead of multi-layer-steel (MLS) engine head gasket is used to seal the combustion gas. Finite element analyses were conducted to assess the dependence of the sealing performance of full-bead on the forming process consisting of embossing and flatting operations. It is demonstrated that the sealing performance is enhanced with more severe deformation of the bead plate during the embossing, i.e., with the increase in the punching depth, the punch height, the punch width and the friction coefficient of the bead plate against the punch and die, and with the decrease in the width of die cavity. Meanwhile, the flatting process that is employed to adjust the height of the embossed full-bead has no influence on the sealing performance.

• Journal of Welding and Joining
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• v.22 no.1
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• pp.58-64
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• 2004

The control of the weld bead shape is important in laser welding of the small parts. The effects of laser welding parameters on the weld bead shape in the pulsed Nd:YAG laser welding of STS 304L material were investigated. Shielding gas type, flow rate, pumping voltage, pulse frequency, pulse width, focal position and overlap distance were selected as laser welding parameters. Experiments were designed and conducted using the Taguchi method which was a statistical experimental method. The weld bead width, penetration, area and aspect ratio were measured and analysed as the weld bead shape properties and the welding parameters were optimized to maximize the weld aspect ratio. Weld aspect ratio were greatly affected by the pulse width, pumping voltage and pulse frequency, and somewhat by the overlap distance, and little by the shielding gas type, flow rate and focal position. A confirmation experiment were conducted using the optimized welding parameters.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.30-35
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• 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 Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.189-194
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• 2007

Recently, as consumer's claim fur car safety is increased, quality inspection method fur welding zone is strengthened. Therefore, from the methods that depend on welding zone bead shape size of seat frame in macrography or passive examination, the quality control by whole recording inspection is required. In this study, the system that is measuring automatically if worker checks welding bead fur quality inspection of seat frame is developed using LabVIEW. If the quality standard for the bead width and length of welding zone is inputted, the system measures automatically whether welding zone is bead length or bead width. Measured data is preserved by points and quality recording of welding zone is stored. The car seat きme welding zone is applied and experimented. The results gave good influence o9 the quality control of work efficiency.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.301-306
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• 2002

This paper presents the use of the neural network technology to establish a mathematical model for predicting bead geometry (top-bead width, top-bead height, back-bead width and back-bead height) for multi-pass welding, and understand relationships between process parameters and bead geometry for robotic GMA welding process. Using a series of robotic arc welding, additional multi-pass butt welds were carried out in order to verify the performance of the developed neural network model. The results show that not only the proposed model can predict the bead geometry with reasonable accuracy and guarantee the uniform weld quality, but also the neural network model could be better than the linear and curvilin ear equations developed from Lee [8].

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

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.4
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• pp.113-117
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• 2007

The study was performed on the development of system in which the bead width can be controlled. In order to control the bead width, we designed the automatic seam tracking device by attaching the probe type strain gauge sensor, motor driving slide and encoder to check the moving distance, and interface card connected MCU(80Cl96KC) upside the speed controllable carriage. Seam tracking experiments were done by changing the bead width. We compared and analyzed the sampling data which were obtained by output voltage of strain gauge sensor and rotary encoder pulse every 50ms.