• New & Renewable Energy
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• v.4 no.1
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• pp.31-36
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• 2008

Stainless steels have been widely considered as metallic bipolar plates, due to their passive surface film, which is good for corrosion resistance. However, the high resistivity of the passive film increases interfacial contact resistance between the bipolar plates and the electrodes. Stainless steels thermal spray coated with a mixture of tungsten carbide and stainless steel powders showed that the coated layer safely combined with the matrix but they suffered many internal defects including voids and cracks. Many cracks were formed in the coated layer and the interface of the matrix and the coated layer during the rolling process. The coated and rolled stainless steels showed lower interfacial contact resistance and corrosion resistance than bare stainless steel because of low resistivity of tungsten carbide and numerous defects, which caused crevice corrosion, in the coated layer.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.1-5
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• 2008

Stainless steels have been widely considered as metallic separators, due to their passive surface film, which is good for corrosion resistance. However, the high resistivity of the passive film increases interfacial contact resistance between the separators and electrodes. Stainless steels thermal spray coated with a mixture of tungsten carbide and stainless steel powders showed that the coated layer safely combined with the matrix but they suffered many internal defects including voids and cracks. Many cracks were formed in the coated layer and the interface of the matrix and the coated layer during the rolling process. The coated and rolled stainless steels showed lower interfacial contact resistance and corrosion resistance than bare stainless steel because of low resistivity of tungsten carbide and numerous defects, which caused crevice corrosion, in the coated layer.

• Journal of the Korean Wood Science and Technology
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• v.51 no.6
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• pp.493-508
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• 2023

Round timber materials of 600 mm length, cut from large-cross-section round timber of red pine (Pinus densiflora S. et Z.) of 450 mm width and 4.2 m length, were prepared as the target of kiln drying in this study. After treating the target materials through end sealing (ES), end sealing - kerfing (ES-K), lateral sealing - end sealing - boring (LS-ES-B), or lateral sealing - partial end sealing (LS-PES), the effects of the treatment on the incidence of drying defects were determined. The target materials with exposed lateral surface and sealed cross surface were steamed at the initial temperature of 65℃ above the official pest control temperature of 56℃, followed by kiln drying toward the final temperature of 75℃. The target materials with sealed lateral surfaces, on the other hand, were dried at the initial temperature of 90℃ at almost the maximum temperature of conventional kiln drying, as there is no risk of early check formation caused by surface moisture evaporation. The final temperature was set at approximately 100℃. The drying time, taken for the target materials with initial moisture content of 70%-80% to reach the target moisture content of 19%, varied across treatment conditions. The measured drying time was 1,146 hours (approximately 48 days) for the timber with sealed cross surface and 745 hours (approximately 31 days) for the timber with sealed lateral surface, until the moisture content reached the target level. The formation of surface checks could not be prevented in the control and ES groups, but a definite preventive effect was obtained for the LS-ES-B and LS-PES groups.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.273-275
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• 2005

Active thermography is being used since several years for remote non-destructive testing. It provides thermal images for remote detection and imaging of damages. Also, it is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. For energy deposition, it use external heat sources (e.g., halogen lamp or convective heating) or internal heat generation (e.g., microwaves, eddy current, or elastic wave). Among the external heat sources, the ultrasound is generally used for energy deposition because of defect selective heating up. The heat source generating a thermal wave is provided by the defect itself due to the attenuation of amplitude modulated ultrasound. A defect causes locally enhanced losses and consequently selective heating up. Therefore amplitude modulation of the injected ultrasonic wave turns a defect into a thermal wave transmitter whose signal is detected at the surface by thermal infrared camera. This way ultrasound thermography(UT) allows for selective defect detection which enhances the probability of defect detection in the presence of complicated intact structures. In this paper the applicability of UT for fast defect detection is described. Examples are presented showing the detection of defects in PCB material. Measurements were performed on various kinds of typical defects in PCB materials (both Cu metal and non-metal epoxy). The obtained thermal image reveals area of defect in row of thick epoxy material and PCB.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.6
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• pp.989-995
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• 2013

Unlike fossil-or nuclear fuel-based power generation, wind power generation using inexhaustible wind energy is a pollution-free, hazardless power generation method. In this study, ultrasound thermography is used for fabricating specimens of wind power generator bearings and wind power generator supplement flanges, and an optimally designed ultrasound horn and ultrasound excitation system are used for detecting damage to part materials of a wind power generation setup. In addition, thermal flow analysis and ultrasonic thermography imaging are comparatively analyzed for improving the detection reliability in terms of surface and internal defects of part materials and for verifying the developed system's field applicability and reliability.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.3
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• pp.294-301
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• 2015

Oil filters for vehicular parts are used under high and low temperatures as the engine is cooled, and defects can be generated with repeated changes in the operating environment and with changes in the shape, such as very high internal losses for the bolts. Visually checking for defects inside a bolt is impossible. Nondestructive evaluation methods such as eddy current testing (ECT) are recommended as a more effective way to examine inside a bolt and detect surface defects in a short amount of time. In this study, the fit bobbin coil eddy current probe was applied to checking the bolts. The bolt parameters were calculated by using a COMSOL analysis program to obtain parameters for professional interior design and fault diagnosis.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.1
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• pp.48-55
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• 2012

Pressure vessels in vehicle industries, power plants, and chemical industries are often affected by flaw and defect generated inside the pressure vessels due to production processes or being used. It is very important to detect such internal defects of pressure vessel because they sometimes bring out serious problems. In this paper, an optical defect detection method using digital shearography is used. This method has advantages that the inspection can be performed at a real time measurement and is less sensitive to environmental noise. Shearography is a laser-based technique for full-field, non-contacting measurement of surface deformation (displacement or strain). The ultimate goal of this paper is to detect flaws in pressure vessels and to measure the lengths of the flaws by using unwrapping, phase images which are only obtained by Phase map. Through this method, we could decrease post-processing (next processing). Real length of a pixel can be calculated by comparing minimum and maximum unwrapping images with shearing angle. Through measuring several specimen defects which have different lengths and depths of defect, it can be possible to interpret quantitatively by calculating gray level.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.18-23
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• 2016

Self-assembly of organic molecules is formed spontaneously on surfaces by electrostatic interaction with substrate. This research has shown that the self-assembly improves safety and handling tractability of high-energetic materials (HEMs). According to the recent study, control of the specific crystal size for reducing the internal defects is mightily important, because the internal defects are a factor in unstability of HEMs. In turn, we performed self-assembly of organic molecules and HEMs by using nano-sized HEMs, which were produced by drowing-out or milling/crystallization. Surface modification efficiency was decided by size distribution, zeta-potential, friction sensitivity and electrostatic charge.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.511-516
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• 2024

The recently enacted detailed guidelines on the performance evaluation of track facilities presented the necessary requirements regarding the evaluation procedures and implementation methods of track performance evaluation. However, the grade of rail surface damage is determined by external inspection (visual inspection), and there is no choice but to rely only on qualitative evaluation based on the subjective judgment of the inspector. Therefore, in this study, we attempted to develop a diagnostic application that can diagnose rail internal defects using rail surface damage. In the field investigation, rail surface damage was investigated and patterns were analyzed. Additionally, in the indoor test, SEM testing was used to construct image data of rail internal damage, and crack length, depth, and angle were quantified. In this study, a deep learning model (Fast R-CNN) using image data constructed from field surveys and indoor tests was applied to the application. A rail surface damage diagnosis application (App) using a deep learning model that can be used on smart devices was developed. We developed a smart diagnosis system for rail surface damage that can be used in future track diagnosis and performance evaluation work.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.297-314
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• 2016

As the study of internal corrosion of pipeline need a large number of experiments as well as long time, so there is a need for new computational technique to expand the spectrum of the results and to save time. The present work represents a new non-destructive evaluation (NDE) technique for detecting the internal corrosion inside pipeline by evaluating the dielectric properties of steel pipe at room temperature by using electrical capacitance sensor (ECS), then predict the effect of pipeline environment temperature (${\theta}$) on the corrosion rates by designing an efficient artificial neural network (ANN) architecture. ECS consists of number of electrodes mounted on the outer surface of pipeline, the sensor shape, electrode configuration, and the number of electrodes that comprise three key elements of two dimensional capacitance sensors are illustrated. The variation in the dielectric signatures was employed to design electrical capacitance sensor (ECS) with high sensitivity to detect such defects. The rules of 24-electrode sensor parameters such as capacitance, capacitance change, and change rate of capacitance are discussed by ANSYS and MATLAB, which are combined to simulate sensor characteristic. A feed-forward neural network (FFNN) structure are applied, trained and tested to predict the finite element (FE) results of corrosion rates under room temperature, and then used the trained FFNN to predict corrosion rates at different temperature using MATLAB neural network toolbox. The FE results are in excellent agreement with an FFNN results, thus validating the accuracy and reliability of the proposed technique and leads to better understanding of the corrosion mechanism under different pipeline environmental temperature.