• Tribology and Lubricants
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• 제15권1호
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• pp.83-89
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• 1999

The fretting wear behaviour of Zircaloy-4 tube used as the fuel rod cladding in PWR nuclear power plants has been investigated at the different test environment, in light water and in air as a function of slip amplitude, normal load, test duration and frequency. Zircaloy-4 tubes were used for both of oscillating and stationary specimens. A fretting wear tester was designed to be suitable for this fretting test. The wear volume and specific wear rate of Zircaloy-4 tube in water was greater than those in air under various slip amplitude. Delaminates and surface cracks were observed at low slip amplitude and high load of fretting test in water, but the traces of adhesion and plowing were observed at and above 200 Um. The water accelerates the wear of Zircaloy-4 tube at lower slip amplitude in fretting.

• 한국표면공학회지
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• 제29권6호
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• pp.745-752
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• 1996

Wear property of plasma spray coating in $Cr_2O_3$ powder manufatured of spray dry method on the aluminum substrate was inspected for the application of piston-ring of automotive enginel. The plama spray coatings were varied with feed rate and particle size. Used the ball-on disc type tribometer, wear volume, friction, surface rougness were investigated. The delamination of the coating layer were observed with SEM. Also the cross-section of wear track were investigated, using optical microscopy. As a result of experiment, wear mechanism was addressed in the various coating process.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.345-350
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• 2002

In this study, researchers classifying the artificial flaws in semiconductor packages are performed by pattern recognition technology. For this purposes, image pattern recognition package including the user made software was developed and total procedure including ultrasonic image acquisition, equalization filtration, binary process, edge detection and classifier design is treated by Backpropagation Neural Network. Specially, it is compared with various weights of Backpropagation Neural Network and it is compared with threshold level of edge detection in preprocessing method fur entrance into Multi-Layer Perceptron(Backpropagation Neural network). Also, the pattern recognition techniques is applied to the classification problem of defects in semiconductor packages as normal, crack, delamination. According to this results, it is possible to acquire the recognition rate of 100% for Backpropagation Neural Network.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 춘계학술대회 논문요약집
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• pp.116-116
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• 2004

편마비 환자의 보행운동 개선을 위한 보조기구로 족부보장구(Ankle Foot Orthosis, A.F.O.)가 활용되고 있다 족부보장구는 Fig. 1에 제시한 바와 같이 보행특성상 무수히 반복되는 충격과 굽힘하중을 받는다. 따라서 족부보장구용 재료는 피로특성이 우수한 탄소섬유 강화재(Carbon Fiber Reinforced Plastic, 이하 CFRP)를 주로 사용한다. 그러나 CFRP의 상용재인 프리프레그(prepreg)는 강한 이방성의 단방향 섬유이므로 섬유방향과 하중작용방향의 관계에 매우 민감하다.(중략)

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 춘계학술대회 논문요약집
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• pp.74-74
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• 2004

탄소섬유강화 적층재(Carbon Fiber Reinforced Plastic, 이하 CFRP)는 강성도는 뛰어나지만 충격특성에는 취약한 단점이 있다. 따라서 충격저항과 충격에너지 흡수율이 상대적으로 우수한 유리섬유강화 적층재(Glass Fiber Reinforced Plastic, GFRP) 및 아라미드섬유강화 적층재(Aramid Fbier Reinforced Plastic, 이하 AFRP)를 CFRP 적용분야에 대체하고 점차적으로 피로특성을 개선시켜 나간다면 특성이 더욱 개선된 제품을 사용할 수 있을 것으로 판단된다.(중략)

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.721-726
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• 2005

In this study, researchers classifying the artificial flaws in semiconductor. packages are performed by pattern recognition technology. For this purposes, image pattern recognition package including the user made software was developed and total procedure including ultrasonic image acquisition, equalization filtration, binary process, edge detection and classifier design is treated by Backpropagation Neural Network. Specially, it is compared with various weights of Backpropagation Neural Network and it is compared with threshold level of edge detection in preprocessing method for entrance into Multi-Layer Perceptron(Backpropagation Neural network). Also, the pattern recognition techniques is applied to the classification problem of defects in semiconductor packages as normal, crack, delamination. According to this results, it is possible to acquire the recognition rate of 100% for Backpropagation Neural Network.

• 대한기계학회논문집A
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• 제20권4호
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• pp.1216-1224
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• 1996

In the use of glass fiber reinforced plastics it is often necessary to cutting the components, but the cutting GFRP is often made difficult by the delamination of composites and the short tool life. In this paper, the machinability of GFRP by mean of tool materials and type was experimentally investigated. By proper selection of cutting tool material and type excellent machining of this workpiece is achieved. The surface quality relate closely with the feed rate and cutting tools.

• 대한금속재료학회지
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• 제50권9호
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• pp.637-643
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• 2012

Recently, because of safety and environmental concerns, there has been a tendency to introduce solid self-lubricating composites for bearing materials. In this paper, we developed Fe-Cr-C-Mn-Cu cast composite alloys as a self-lubricating composite and investigated the effect of carbon on the formation of protective tribofilms during sliding. The wear resistance of these materials was mainly affected by carbon concentrations due to the fact that in particular wear passed from delamination to tribo-oxidation, reducing the wear rate. The improved wear resistance likely resulted from protective tribofilms that formed on the surface during sliding.

• 한국정밀공학회지
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• 제12권8호
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• pp.27-38
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• 1995

For solving troubles happened during the drilling process with carbon fiber epoxy composite materials(CFRP) by using HSS drill, a few types of diamond gift electroplated drills are manufactured, and machinability of these drills is experimented with a variety of cutting speed and feed rate. These drills have some advantages of good wear resistant and the conception of grinding process. As a result, using of these drills improves both troubles being caused by tool wear and damage of exit surface depending on fiber stacking angle. It is desirable that cutting conditions for the cutting thickness per revolution must be set under 0.01mm when the size of a diamond grit is # 60 .approx. 80.

• Journal of information and communication convergence engineering
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• 제22권3호
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• pp.231-236
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• 2024

This paper presents a method used to identify partial discharge defects in cast-resin power transformers using a back-propagation algorithm. The Rogowski-type partial discharge (PD) sensor was designed with a planar and thin structure based on a printed circuit board to detect PD signals. PD electrode systems, such as metal protrusions, particle-on-insulators, delamination, and void defects, were fabricated to simulate the PD defects that occur in service. PD characteristics, such as rising time, falling time, pulse width, skewness, and kurtosis without phase-resolved partial discharge patterns, were extracted to intuitively analyze each PD pulse according to the type of PD defect. A backpropagation algorithm was designed to identify PD defects using a virtual instrument (VI) based on the LabVIEW program. The results show that the accuracy rate of back-propagation (BP) algorithm reaches over 92.75% in identifying four types of PD defects.