• Journal of the Korean Geosynthetics Society
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• v.19 no.4
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• pp.41-50
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• 2020

Since cracks in concrete structures expedite corrosion of reinforced concrete over a long period of time, regular on-site inspections are essential to ensure structural usability and prevent degradation. Most of the safety inspections of facilities rely on visual inspection with naked eye, so cost and time consuming are severe, and the reliability of results differs depending on the inspector. In this study, a portable measuring device that can be used for safety diagnosis and maintenance was developed as a device that measures the width and length of concrete cracks through image analysis of cracks photographed with a camera. This device captures the cracks found within a close distance (3 m), and accurately calculates the unit pixel size by laser distance measurement, and automatically calculates the crack length and width with the image processing algorithm developed in this study. In measurement results using the crack image applied to the experiment, the measurement of the length of a 0.3 mm crack within a distance of 3 m was possible with a range of about 10% error. The crack width showed a tendency to be overestimated by detecting surrounding pixels due to vibration and blurring effect during the binarization process, but it could be effectively corrected by applying the crack width reduction function.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.555-567
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• 2023

The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1137-1142
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• 2013

FBG sensors are mainly used to measure strain and temperature of structures. In this paper, an interrogator of FBG sensors is developed and implemented to measure the crack of structures using FPGA and DSP. Developed interrogator consists of an optical source, an optical circulator, an optical grating and a CCD sensor and controller. The spectrum of the reflected light from the FBG sensor is analyzed and peak wavelength is detected. Next, strain of structure can be measured using shift of peak wavelength. Centroid algorithm and Gaussian fitting which are mainly applied to detect peak wavelength of the interrogator are compared in this paper. As a result of experiment, Gaussian fitting is suitable for a developed interrogator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.826-832
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• 2016

In this paper, we propose a tongue diagnosis system for determining the presence of specific taste crack area as a first step in the digital tongue diagnosis system that anyone can use easily without special equipment and expensive digital tongue diagnosis equipment. Training DB was developed by the Haar-like feature, Adaboost learning on the basis of 261 pictures which was collected in Oriental medicine. Tongue candidate regions were detected from the input image by the learning results and calculated the average value of the HUE component to separate only the tongue area in the detected candidate regions. A tongue area is separated through the Connected Component Labeling from the contour of tongue detected. The palate regions were divided by the relative width and height of the tongue regions separated. Image on the taste area is converted to gray image and binarized with each of the average brightness values. A crack in the presence or absence was determined via Connected Component Labeling with binary images.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.6
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• pp.426-432
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• 1999

A plus-point eddy current test(ECT) probe was developed to examine the defects on the welds of pumps, valves, and pipings which are the major components of the electric power plants, non-destructive evaluation (NDE) techniques for detecting and sizing the flaws were studied adapting this probe. Differential plus-point ECT probe is consists of two "I"-type coils crossed each other and has an advantage having a small influence on the sensitivity by lift-off variation to the conventional types of probe. The specimens with crack-like electro discharge machining(EDM) notches on the weld of type 304 stainless-steel were fabricated in order to evaluate the plus-point ECT probe response to the flaws. NDE techniques to detect and size the flaws and estimate the flaw type were established with this specimens.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.450-450
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• 2009

최근 전세계적으로 태양전지의 대량보급에 따라 실리콘 원료의 공급에 차질이 생겨 원자재 값이 상승하는 추세에 있다. 결정질 실리콘 태양전지의 제조비용중 실리콘 재료 및 웨이퍼가 차지하는 비율은 약 50~60%정도로 높기 때문에 실리콘 웨이퍼의 두께를 감소시키는 것이 비용절감을 위한 효과적인 방법으로 기대되고 있다. 그러나 실리콘 웨이퍼의 두께가 앓아질수록 제조공정중 균열이나 파손이 발생할 가능성이 높아지기 때문에 이에 따른 실리콘 웨이퍼의 기계적 물성에 대한 연구가 필수적이라 할 수 있다. 본 연구에서는 현재 상용으로 사용되고 있는 크기가 5 인치인 $200{\mu}m$ 두께의 실리콘웨이퍼 (As-saw)를 약 80여개의 시편으로 절단한 후 각각의 파단강도를 부위별로 측정하였다. 또한 표면절단결함을 제거하는 saw damage etching(SDE) 시간을 제어하여 두께가 $150{\mu}m$, $130{\mu}m$인 웨이퍼를 준비하였다. 이들 시험편에 대해서도 부위별 파단강도를 측정하여 as-saw상태의 시험편과 비교하였다. 파단강도 측정은 4 접 굽힘시험을 통하여 측정하였으며 파단면은 주사전자현미경을 통하여 관찰하였다. 또한 실리콘 웨이퍼의 미세균열을 비파괴적으로 검출하기 위하여 100MHz 고주파수를 이용하는 초음파현미경(SAM, scanning acoustic microscope)을 이용하여 균열의 분포를 영상화하였다.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.508-515
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• 2011

Bovine incisor was investigated using active infrared thermography(IRT) to visualize crack on bovine teeth. An artificial crack was carefully created in bovine incisor sample by compression load of universal tensile machine. While applying a sinusoidal heat wave to the cracked bovine incisor through halogen lamp, consecutive digital infrared images was captured from the sample surface at a frequency synchronized with heat excitation. Phase information of thermal image was calculated by four-point correlation method and processed to produce the phase image of bovine incisor. This phase image showed clearly the crack on the incisor, which was hardly detected in traditional passive thermography.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.105-111
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• 2010

In this paper the elasticity of fault-detection algorithm based on fuzzy logic is proposed through lots of experiments, justifying its validity. The four mathematical morpholgical operators was defined to detect the cracks. The cracks was detected via center of area method with ${\lambda}$-fuzzy measure of fuzzy sets. However generally favorable, the result owes to how adequate the lighting device is designed in case of the so far fine crack of pieces. In an attempt to improve the response of the system, It is designed to minimize the use of memory via LookUp table in software.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.4
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• pp.167-172
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• 2019

The strength (MPa), hardness (Hv), shrinkage (%) and biological properties of the HAp were measured by using an organic plasticizer which facilitates the molding and heat treatment. Mechanical properties such as compressive strength, bending strength and hardness were increased with increasing amount of plasticizer, but mechanical properties were decreased when plasticizer was added more than 7 %. This is because addition of the plasticizer above the allowable value causes cracking during molding, and such cracks promote the generation of microcracks and pores at the time of sintering, resulting in a decrease in mechanical properties. As a result of the antimicrobial activity test, no bacteria were detected regardless of the addition amount of plasticizer.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05b
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• pp.851-856
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• 1998

국내에서 상업운전중인 월성 원자로는 캐나다에서 개발한 CANDU형 원자로로 핵연료를 지지하는 핵연료 압력관이 사용되며, 핵연료 압력관은 원자로의 1차기기로 건전성확보가 매우 중요하다. 가동중 검사시 압력관에서 결함이 검출되면, 지속적인 사용을 위해서 결함의 건전성을 확보하여야하나, 그 평가절차가 매우 복잡하다. 본 연구에서는 핵연료 압력관 평가를 보다 신속하고 효율적으로 수행하기 위한 건전성 평가시스템을 개발하였다. 개발된 평가시스템은 예리한 결함 및 둔한 함에 대한 평가를 수행할 수 있으며, 피로균열평가, 지체수소균열평가, 불안정파괴평가, 파단전누설평가, 소성붕괴평가모듈을 수록하고 있다. 또한 개발된 시스템을 검증하기 위하여 캐나다 ECL에서 제시한 평가결과와 비교함으로서 본 시스템의 효용성을 검증하였다.