• Structural Engineering and Mechanics
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• v.83 no.5
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• pp.693-707
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• 2022

Bonded joints have proven their performance against conventional joining processes such as welding, riveting and bolting. The single-lap joint is the most widely used to characterize adhesive joints in tensile-shear loadings. However, the high stress concentrations in the adhesive joint due to the non-linearity of the applied loads generate a bending moment in the joint, resulting in high stresses at the adhesive edges. Geometric optimization of the bonded joint to reduce this high stress concentration prompted various researchers to perform geometric modifications of the adhesive and adherends at their free edges. Modifying both edges of the adhesive (spew) and the adherends (bevel) has proven to be an effective solution to reduce stresses at both edges and improve stress transfer at the inner part of the adhesive layer. The majority of research aimed at improving the geometry of the plate and adhesive edges has not considered the effect of temperature and water absorption in evaluating the strength of the joint. The objective of this work is to analyze, by the finite element method, the stress distribution in an adhesive joint between two 2024-T3 aluminum plates. The effects of the adhesive fillet and adherend bevel on the bonded joint stresses were taken into account. On the other hand, degradation of the mechanical properties of the adhesive following its exposure to moisture and temperature was found. The results clearly showed that the modification of the edges of the adhesive and of the bonding agent have an important role in the durability of the bond. Although the modification of the adhesive and bonding edges significantly improves the joint strength, the simultaneous exposure of the joint to temperature and moisture generates high stress concentrations in the adhesive joint that, in most cases, can easily reach the failure point of the material even at low applied stresses.

• Journal of Welding and Joining
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• v.23 no.6
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• pp.67-71
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• 2005

This paper is concerned with a study on fracture strength of composites in an adhesive single lap joint. The tests were carried out on joint specimens made with hybrid stacked composites consisting of the polyester and bamboo natural fiber layer. The main objective of this work was to evaluate the fracture properties adjacent to adhesive bonded joint of natural fiber reinforced composite specimens. From the results, natural fiber reinforced composites have lower tensile strength than the original polyester. But tensile-shear strength of natural fiber reinforced composites with bamboo layer far from adhesive bond is as high as that of the original polyester adhesive bonded joints. Spew filet at the end of the overlap reduced the stress concentration at the bonded area. Spew fillet and position of bamboo natural fiber layer have a peat effect on the tensile-shear strength of natural fiber reinforced composites including adhesive bonded joints.

• Journal of Welding and Joining
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• v.19 no.2
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• pp.208-214
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• 2001

In this study, we constructed a visual sensor system for weld seam tracking in real time in GMA welding. A sensor part consists of a CCD camera, a band-pass filter, a diode laser system with a cylindrical lens, and a vision board for inter frame process. We used a commercialized robot system which includes a GMA welding machine. To extract the weld seam we used a inter frame process in vision board from that we could remove the noise due to the spatters and fume in the image. Since the image was very reasonable by using the inter frame p개cess, we could use the simplest way to extract the weld seam from the image, such as first differential and central difference method. Also we used a moving average method to the successive position data or weld seam for reducing the data fluctuation. In experiment the developed robot system with visual sensor could be able to track a most popular weld seam. such as a fillet-joint, a V-groove, and a lap-joint of which weld seam include planar and height directional variation.

• Journal of Welding and Joining
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• v.32 no.2
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• pp.43-47
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• 2014

Famous artificial neural network (ANN) is applied to predict proper process window of arc welding. Target weldment is variously combined lap joint fillet welding of automotive steel plates. ANN's system variable such as number of hidden layers, perceptrons and transfer function are carefully selected through case by case test. Input variables are welding condition and steel plate combination, for example, welding machine type, shield gas composition, current, speed and strength, thickness of base material. The number of each input variable referred in welding experiment is counted and provided to make it possible to presume the qualitative precision and limit of prediction. One of experimental process windows is excluded for predictability estimation and the rest are applied for neural network training. As expected from basic ANN theory, experimental condition composed of frequently referred input variables showed relatively more precise prediction while rarely referred set showed poorer result. As conclusion, application of ANN to arc welding process window derivation showed comparatively practical feasibility while it still needs more training for higher precision.

• Journal of Welding and Joining
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• v.31 no.3
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• pp.44-48
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• 2013

Artificial neural network (ANN) model is applied to predict arc welding process window for automotive steel plate. Target weldment was various automotive steel plate combination with lap fillet joint. The accuracy of prediction was evaluated through comparison experimental result to ANN simulation. The effect of ANN variables on the accuracy is investigated such as number of hidden layers, perceptrons and transfer function type. A static back propagation model is established and tested. The result shows comparatively accurate predictability of the suggested ANN model. However, it restricts to use nonlinear transfer function instead of linear type and suggests only one single hidden layer rather than multiple ones to get better accuracy. In addition to this, obvious fact is affirmed again that the more perceptrons guarantee the better accuracy under the precondition that there are enough experimental database to train the neural network.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.2
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• pp.89-93
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• 2014

Variable polarity (VP) arc welding is known as an effective solution for aluminum thanks to the cleaning effect, which means oxide removal, during the DCEP (direct current electrode positive) period. In this research, VP GTAW (gas tungsten arc welding) is adopted for lap joint fillet welding of 3mm thickness 5052 aluminum alloy. Various welding currents and DCEP duty cycles are applied as welding conditions with a fixed welding speed to investigate the influence of DCEP characteristics on weld bead formation. Results show a tendency of higher heat input for higher DCEP duty cycle, which result does not follow conventional arc theory because it is known that DCEN (DC electrode negative) polarity is more efficient for heat input than is DCEP. This phenomenonhas recently been reported by several VP-GTA researchers and is still controversial because the mechanism of oxide removal is not yet clear except for the previous, well-known idea of "ion bombardment", which cannot explain the situation. Finally, proper usage conditions for VP-GTAW are suggested; then, further, related theoretical topics in the field of cathode physics are brieflyintroduced.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.643-646
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• 2000

In this study, we constructed a preview-sensing visual sensor system for weld seam tracking in real time in GMA welding. A sensor part consists of a CCD camera, a band-pass filter, a diode laser system with a cylindrical lens, and a vision board for inter frame process. We used a commercialized robot system which includes a GMA welding machine. To extract the weld seam we used a inter frame process in vision board from that we could remove the noise due to the spatters and fume in the image. Since the image was very reasonable by using the inter frame process, we could use the simplest way to extract the weld seam from the image, such as first differential and central difference method. Also we used a moving average method to the successive position data of weld seam for reducing the data fluctuation. In experiment the developed robot system with visual sensor could be able to track a most popular weld seam, such as a fillet-joint, a V-groove, and a lap-joint of which weld seam include planar and height directional variation.

• Journal of Welding and Joining
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• v.30 no.2
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• pp.59-64
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• 2012

Welding is an essential process in the automotive industry. Most welding processes that are used for auto body are spot welding and $CO_2$ welding are used in a small part. In production field, $CO_2$ welding process is decreased and spot welding process is increased due to welding quality is poor and defects are occurred in $CO_2$ welding process frequently. But $CO_2$ welding process should be used at robot interference parts and closed parts where spot welding couldn't. Because of the 0.65mm ~ 2.0mm thickness steel sheet were used in the automotive industry, poor quality of welding area such as burn through and under fill were happened frequently in $CO_2$ process. In this paper, we will study about the penetration depth which gives a huge impact on burn through changing a degree of base metal, welding position and torch angle. Voltage, current and welding speed were fixed but degree of base metal, welding position and torch angle were changed. And Cold- Rolled(CR) steel sheet was used. Penetration depth was analysed by multiple regression analysis to derive approximate calculations. And reliability of approximate calculations were confirmed through additional experiments. As the results of this research, we confirmed the effect of torch and plate angle to bead shape. And we present a possibility that can simulate more accurate to weld geometry, as deduced the verification equations that has tolerance of less than 21.69%.