• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.437-438
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• 2006

Generally, the vertical roll process is used to achieve extensive width reduction in hot strip mill. However, it is difficult to avoid the defects such as dog-bone and seam-defect. The sizing press has been developed in response to the defects mentioned above. Especially, this study is carried out to investigate the deformation of slab by two-step sizing press. The deformation behavior in the width sizing process is more favorable than that in conventional vertical rolling edger. The objective of this study is to determine the optimal anvil shape parameters in the sizing press with two-step die from the viewpoint of edge-seam length. In general, the edge-seam defect occurs parallel to the rolling direction at both edges in horizontal rolling process after sizing press. The optimal combination of the parameters is determined by FE-simulation and Artificial Neural Network (ANN). The slab deformation in sizing press with convex anvil is analyzed by FE-simulation. The most suitable profile of the anvil is also discussed fur the improvement of trimming loss because of the side seam defect by FE-simulation and ANN.

• 소성∙가공
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• 제18권1호
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• pp.52-58
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• 2009

Generally, a vertical rolling process is used to achieve extensive width reduction in hot strip mill. However, it is impossible to avoid the defects such as dog-bone and edge-seam defect. The sizing press process has been developed in response to the defects mentioned above. Especially, this study is carried out to investigate the deformation of slab by two-step sizing press. The deformation behavior of slab in the sizing press process is more favorable than that in conventional vertical rolling edger. The FE-simulation is applied to predict the deformation behavior of the slab. In this paper, the several causes of the asymmetrical deformation are mentioned for the purpose of understanding of the anvil shape. Load, dog-bone and edge-seam defect are discussed in width sizing process considering the anvil shape. And to reduce the problems generated at rougher mill just after sizing press, these are studied in this paper. The deformation behavior of slabs and optimum anvil shape are obtained by rigid-plastic finite element analyses and neural network.

• International Journal of Precision Engineering and Manufacturing
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• 제6권3호
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• pp.19-23
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• 2005

To minimize the weld defect in manufacturing of the welded tube by using $CO_2$ laser, the monitoring of the welding quality and the seam tracking along the butt-joint lengthwise to the tube axis are studied. The longitudinal butt-joint is shaped from $60kgf/mm^2$ grade steel sheet by 2 roll bending method, and welded by the $CO_2$ laser welding system equipped with the seam tracker and plasma sensor. The laser welded tube has the thickness of 1.5mm, diameter of 105.4mm and length of 2000mm. The precise positioning of the laser beam on the butt-joint to be assembled is obtained within $200{\mu}m$ by the laser vision sensor. The artificial defects in the butt-joint are well observed by the signal of plasma intensity measured from the plasma sensor of UV wavelength range within 400nm. The developed $CO_2$ laser tube welding system has the function of the precision seam tracking and the real-time monitoring of the welding quality. In conclusion, the laser welded tube can be used for manufacturing of automobile chassis and components after hydro-forming.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1996년도 특별강연 및 추계학술발표 개요집
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• Journal of Welding and Joining
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• 제21권1호
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• pp.60-65
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• 2003

At present. welding of most pipes with large diameter is carried out by the manual process. Automation of the welding process is necessary f3r the sake of consistent weld quality and improvement in productivity. In this study, two vision sensors, based on the optical triangulation, were used to obtain the information for seam tracking and detecting the weld defects. Through utilization of the vision sensors, noises were removed, images and 3D information obtained and positions of the feature points detected. The aforementioned process provided the seam and leg position data, calculated the magnitude of the gap, fillet area and leg length and judged the weld defects by ISO 5817. Noises in the images were removed by using the gradient values of the laser stripe's coordinates and various feature points were detected by using an algorithm based on the iterative polygon approximation method. Since the process time is very important, all the aforementioned processes should be conducted during welding.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.222-227
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• 2004

The failure assessment for corroded pipeline has been considered with the full scale burst test and the finite element analysis. The burst tests were conducted on 762 mm diameter, 17.5 mm wall thickness and API 5L X65 pipe that contained specially manufactured rectangular corrosion defect. The failure pressure for corroded pipeline was measured by burst testing and classified with respect to corrosion sizes and corroded regions - the body, the girth weld and the seam weld of pipe. Finite element analysis was carried out to derive failure criteria of corrosion defect on the pipe. A series of finite element analyses were performed to obtain a limit load solution for corrosion defects on the basis of burst test. As a result, the criteria for failure assessment of corrosion defect within the body, the girth weld and the seam weld of API 5L X65 gas pipeline were proposed.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2006년도 춘계 학술대회 개요집
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• pp.148-150
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• 2006

In this paper, the applicability of an UET(ultrasound excited thermography) for a defect detection of the welded receptacle is described. An UET(ultrasound excited thermography) is a defect-selective and fast imaging tool for damage detection. A high power ultrasound-excited vibration energy with pulse durations of 280ms is injected into the outer surface of the welded receptacle made of Al material. An ultrasound vibration energy sent into the welded receptacle propagate inside the sample until they are converted into the heat in the vicinity of the defect. The injection of the ultrasound excited vibration energy results in heat generation so that the defect is turned into a local thermal wave transmitter. Its local heat emission is monitored by the thermal infrared camera. And they are processed by the image recording system. Measurement was performed on aluminum receptacle welded by using Nd:YAG laser. The observed thermal image revealed two area of defects along the welded seam.

• 한국정밀공학회지
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• 제23권10호
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• pp.7-13
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• 2006

• 한국레이저가공학회:학술대회논문집
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• 한국레이저가공학회 2006년도 추계학술발표대회 논문집
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• pp.3-7
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• 2006

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권8호
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• pp.2199-2213
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• 2024

To enhance the quality of defect detection for Printed Circuit Board Assembly (PCBA) during electronic product manufacturing, this study primarily focuses on optimizing the YOLOv7-based method for PCBA defect detection. In this method, the Mish, a smoother function, replaces the Leaky ReLU activation function of YOLOv7, effectively expanding the network's information processing capabilities. Concurrently, a Squeeze-and-Excitation attention mechanism (SEAM) has been integrated into the head of the model, significantly augmenting the precision of small target defect detection. Additionally, considering angular loss, compared to the CIoU loss function in YOLOv7, the SIoU loss function in the paper enhances robustness and training speed and optimizes inference accuracy. In terms of data preprocessing, this study has devised a brightness adjustment data enhancement technique based on split-filtering to enrich the dataset while minimizing the impact of noise and lighting on images. The experimental results under identical training conditions demonstrate that our model exhibits a 9.9% increase in mAP value and an FPS increase to 164 compared to the YOLOv7. These indicate that the method proposed has a superior performance in PCBA defect detection and has a specific application value.