• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.2
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• pp.310-316
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• 2003

One of the significant subject in the automatic arc welding is to establish control system of the welding parameters for controlling bead geometry as a criterion to evaluate the quality of arc welding. This paper proposes an inference algorithm for bead geometry in CMA Welding using Neuro-Fuzzy algorithm. The characteristic welding parameters are measured by the circuit composed of hall sensor, voltage divider tachometer, etc. and then the bead geometry of each weld pool is calculated and detected by an image processing with CCD camera and a measuring with microscope. The relationships between the characteristic welding parameters and the bead geometry have been arranged empirically. From the result of experiments, membership functions and fuzzy rules are tuned and determined by the learning of neural network, and then the relationship between actual bead geometry and inferred bead geometry are concluded by fuzzy logic controller. In the applied inference system of bead geometry using Neuro-Fuzzy algorithm, the inference error percent is within -5%∼+4% in case of bead width, -10%∼+10% in bead height, -5%∼+6% in bead area, -10%∼+10% in penetration. Use of the Neuro-Fuzzy algorithm allows the CMA Welding system to evaluate the quality in bead geometry in real time as the welding parameters change.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.2
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• pp.209-217
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• 2015

Generally welding is one of the most important processes to have a strong influence on the quality and productivity from a manufacture-based industry such as shipbuilding, automotive and machinery. The GMA(Gas Metal Arc) welding process involves large number of interdependent welding parameters which may affect product quality, productivity and cost effectiveness. To solve such problems, mathematical models are required to select the welding parameters for GMA welding process. In this study, the GMA welding process was studied using the information generated during the welding. The statistical analysis of a generalized regression approach was conducted by the following three methods: Firstly using the mathematical model (linear regression, 2nd regression); Secondly GA(Genetic Algorithm) with intelligent models; And finally using response surface analysis of models to develop the relationships between welding parameters and bead width as welding quality.

• Journal of Welding and Joining
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• v.26 no.2
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• pp.50-54
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• 2008

The wearplate with Cr-C has been used in condition of severe abrasion. Recently, the demand of wearplate made by hardfacing with Cr-C has increased in the world, but it is lack of supply and expensive due to low productivity. CMAW (Compound Metal Arc Welding) is very useful process of several welding methods to make wearplate. In this paper, twin torch CMAW to use twin torch at the same time was developed to improve productivity and to ensure quality of wear plate. When the distance between two touches was smaller than 30mm, arc blow was occurred. However when the distance was larger than 35mm, there was no arc blow any more. If the oscillation path of each torch was overlapped together, the melt through at the overlapped zone was occurred due to concentrated heat input in substrate. On the other hand, the turning point of each torch was open more than 5mm, separated bead was generated. Therefore twin torch CMAW which has adequate conditions was able to make wearplate having flatter surface at the bead connection than single torch.

• Journal of Welding and Joining
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• v.23 no.4
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• pp.41-47
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• 2005

Generally, the use of robots in manufacturing industry has been increased during the past decade. GMA(Gas Metal Arc) welding process is an actively Vowing area, and many new procedures have been developed for use with high strength alloys. One of the basic requirement for the automatic welding applications is to investigate relationships between process parameters and bead geometry. The objective of this paper is to develop a new approach involving the use of neural network and multiple regression methods in the prediction of bead geometry for GMA welding process and to develop an intelligent system that visualize bead geometry in order to employ the robotic GMA welding processes. Examples of the simulation for GMA welding process are supplied to demonstrate and verify the proposed system developed using MATLAB. The developed system could be effectively implemented not oかy for estimating bead geometry, but also employed to monitor and control the bead geometry in real time.

• Journal of Welding and Joining
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• v.32 no.1
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• pp.53-60
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• 2014

The automatic arc welding is generally accepted as the preferred joining technique and commonly chosen for assembly of large metal structures such as in areas of automotive, aircraft and shipbuilding due to its joint strength, reliability, and low cost compared to other joint processes. Recently, several mathematical models have been developed and studied for control and monitoring welding quality, productivity, microstructure and weld properties in arc welding processes. This study indicates the prediction of process parameters for the expected welding quality with accordance to the adaptive GTA welding process. Furthermore, the mathematical models is also develop to aid the selection of an optimal welding process as the generation of process controls to predict the bead geometry as a function output parameters in the GTA welding process. The developed models through this study showed comparatively excellent predicted results, and will extend to other welding processes to integrate an optimized system for the robotic welding process.

• Journal of Welding and Joining
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• v.29 no.4
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• pp.80-84
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• 2011

In the 5xxx series Al-Mg alloy, magnesium addition can increase the strength of aluminum alloy by solid solution strengthening but it has a relatively low melting and boiling temperature. During full -penetration laser welding of the Al-Mg alloys, its low boiling point and high vapor pressure brings about the spiky humping bead on the bottom side. Under back-side shielding, the spiking of back bead can be reduced but it restraints the process flexibility. In this study, a square pulse waveform modulation was employed to stabilize keyhole and back bead surface without back-side shielding. By using an experimental design, the bead shapes were evaluated for various process parameters such as the focal position, welding velocity and waveform parameters and the smooth back bead shape could be achieved.

• Journal of Welding and Joining
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• v.29 no.6
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• pp.77-81
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• 2011

In most industry, manual GTAW welding is preferred for formation of stable back bead in root weld of butt joint. However, manual GTAW welding has low productivity as compared with GMAW, also it has unstable bead quality which depend on skilled workers. So it is necessary to develop process of root pass welding by using automation GMAW that have stable back bead formation and high productivity. In this paper, the design of U-groove with 3mm root face was applied to extend the tolerance of misalignment in condition of standard root gap 1.5mm. Consequently, for the formation of stable back bead in root pass of butt welding, in case of the narrow root gap(0.5mm) the large arc force was applied by increasing the current and voltage. In case of the large root gap(2.5mm), the small arc force was applied by decreasing the current and voltage. Considering the various root gap, the required deposited metal was controlled by welding speed only.

• Journal of Welding and Joining
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• v.25 no.6
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• pp.64-70
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• 2007

Recently, several models to control weld quality, productivity and weld properties in arc welding process have been developed and applied. Also, the applied model to make effective use of the robotic GMA(Gas Metal Arc) welding process should be given a high degree of confidence in predicting the bead dimensions to accomplish the desired mechanical properties of the weldment. In this study, a development of the on-line learning neural network models that investigate interrelationships between welding parameters and bead width as well as apply for the on-line quality control system for the robotic GMA welding process has been carried out. The developed models showed an excellent predicted results comparing with the predicted ability using off-line learning neural network. Also, the system will extend to other welding process and the rule-based expert system which can be incorporated with integration of an optimized system for the robotic welding system.

• Journal of Korean Society of Steel Construction
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• v.16 no.4 s.71
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• pp.479-492
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• 2004

When U-ribs of steel deck plates are connected at the field, overhead welding should be done with backing strips. Misalignments may occur and lead to eccentric moments as well as high stress concentrations at welded joints. In this study, stress analyses and fatigue tests were carried out. Stress analyses for U-ribs' welded joints with backing strips were performed with different misalignments, root shapes, root gaps, and backing strip sizes. From the stress analyses, the stress concentration factors increased with increasing misalignments and root gaps. With the fixed misalignments and root gaps, the stress concentration factors obtained in the case of the semi-circle root shape were lower than those in the case of the right-angle root shape. It was verified that backing strip sizes have little influence on stress concentration factors. The fatigue tests for U-ribs' welded joints with backing strips indicated that increased misalignments shorten fatigue life drastically and cracks usually initiate at the root of the base metal and are propagated to the weld bead surface. Based on the results of the stress analyses, root-shape control methods were developed to mitigate stress concentration by changing welding condition control, radius curvature, and flank angle.