• 한국안전학회지
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• 제21권4호
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• pp.42-48
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• 2006

The strategies of maintenance and operation are usually established based on the number of flaws and their size distribution obtained from nondestructive inspection in order to preserve safety of the plant. But non destructive inspection results are different from the physical flaws which really exist in the equipments. In case of a single inspection, it is easy to estimate the number of physical flaws using the POD curve. However, we may be faced with some difficulties in obtaining the number of physical flaws from the periodic in-service non destructive inspection data. In this study a simple method for estimating the number of physical flaws from periodic in-service nondestructive inspection data was proposed. In order to obtain the flaw growth history, the flaw growth was simulated using the Monte Carlo method and the flaw size and the corresponding POD value were obtained for each flaw at each periodic inspection time. The flaw growth rate used in the simulation was statistically calculated from the in-service inspection data. By repeating the simulation numerous flaw growth data could be generated and the effective POD curve was obtained as a function of flaw size. From the effective POD curve the number of physical flaws was obtained. The usefulness and convenience of the proposed method was evaluated from several applications and satisfactory results were obtained.

• Smart Structures and Systems
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• 제5권4호
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• pp.317-328
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• 2009

Current maintenance operations and integrity checks on a wide array of structures require personnel entry into normally-inaccessible or hazardous areas to perform necessary nondestructive inspections. To gain access for these inspections, structure must be disassembled and removed or personnel must be transported to remote locations. The use of in-situ sensors, coupled with remote interrogation, can be employed to overcome a myriad of inspection impediments stemming from accessibility limitations, complex geometries, the location and depth of hidden damage, and the isolated location of the structure. Furthermore, prevention of unexpected flaw growth and structural failure could be improved if on-board health monitoring systems were used to more regularly assess structural integrity. A research program has been completed to develop and validate Comparative Vacuum Monitoring (CVM) Sensors for surface crack detection. Statistical methods using one-sided tolerance intervals were employed to derive Probability of Detection (POD) levels for a wide array of application scenarios. Multi-year field tests were also conducted to study the deployment and long-term operation of CVM sensors on aircraft. This paper presents the quantitative crack detection capabilities of the CVM sensor, its performance in actual flight environments, and the prospects for structural health monitoring applications on aircraft and other civil structures.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.246-251
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• 2001

The performance demonstration round robin test was conducted to quantify the capability of ultrasonic inspection for in-service and to address some aspects of reliability for nondestructive evaluation. The fifteen inspection teams who employed procedures that met or exceeded ASME Sec. XI code requirements detected the pinping of nuclear power plant with various cracks to evaluate the capability of detection. With data from PD-RR test, the performance of ultrasonic nondestructive inspection could be assessed using probability of detection and length and depth sizing of cracks.

• 한국멀티미디어학회논문지
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• 제22권11호
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• pp.1300-1312
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• 2019

BSTRACT In this paper, PM10 forecast model using DNN(Deep Neural Network) is developed for Seoul region. The previous Julian forecast model has been developed using weather and air quality data of Seoul region only. This model gives excellent results for accuracy and false alarm rates, but poor result for POD(Probability of Detection). To solve this problem, an WA(Wide Area) forecasting model that uses Chinese data is developed. The data is highly correlated with the emergence of high concentrations of PM10 in Korea. As a result, the WA model shows better accuracy, and POD improving of 3%(D+0), 21%(D+1), and 36%(D+2) for each forecast period compared with the Julian model.

• 대한원격탐사학회지
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• 제34권6_1호
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• pp.1025-1032
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• 2018

적설은 강수의 한 형태로 지표면에 쌓인 눈으로 정의되며 빙권의 가장 큰 단일 구성 요소로서 지구 표면과 대기 사이의 열 교환이나 전 지구 또는 지역적인 측면에서 지구의 에너지 수지 균형을 유지하는 중요한 역할을 하는 등 지구 표면 온도를 조절하는데 영향을 미친다. 그러나 적설은 인간의 접근이 어려운 지역에 주로 분포하기 때문에 위성을 활용한 적설 탐지가 활발히 수행되고 있으며 산림 지역의 적설 탐지는 구름과 적설의 구분 다음으로 중요한 과정이다. 따라서 본 연구는 기존 극 궤도 위성에서 산림 지역 적설 탐지에 활용하는 Normalized Difference Snow Index(NDSI) 및 Normalized Difference Vegetation Index(NDVI)를 정지궤도 위성에 적용하였으며, 산림 지역 외 영역은 적설의 분광 특징을 활용한 $R_{1.61{\mu}m}$ anomaly 기법 및 NDSI를 활용하여 적설 탐지를 수행하였다. 본 연구에서 산출한 Snow Cover 자료와 Visible Infrared Imaging Radiometer(VIIRS) Snow Cover 자료를 활용해 간접 검증을 수행한 결과, Probability of Detection(POD)는 99.95%, False Alarm Ratio(FAR)는 16.63 %로 나타났다. Himawari-8 Advanced Himawari Imager(AHI) RGB 영상을 추가로 활용해 정성적 검증 또한 수행하였으며 수행 결과, VIIRS Snow Cover가 미탐지한 영역과 본 연구가 오탐지한 영역이 혼합되어 나타났다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.240-245
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• 2001

Ultrasonic inspection system is consisted of the operator, equipment and procedure. The reliability of results in ultrasonic inspection is affected by its ability. Furthermore, the reliability of nondestructive testing is influenced by the inspection environment, other materials and types of defect. Therefore, it is very difficult to estimate the reliability of NDT due to various factors. In this study, the probability of detection, used logistic probability model and Monte Carlo simulation, estimated the reliability of ultrasonic inspection. The utility of the NDT reliability assesment is verified by the analysis of the data from round robin test applied these models.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2002년도 정기학술대회
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• pp.217-224
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• 2002

The performance demonstration round robin test was conducted to quantify the capability of ultrasonic inspection for in-service and to address some aspects of reliability for nondestructive evaluation. The fifteen inspection teams who employed procedures that met or exceeded ASME Sec. XI code requirements detected the piping of nuclear power plant with various cracks to evaluate the capability of detection. With data from PD-RR test, the performance of ultrasonic nondestructive inspection could be assessed using probability of length and depth sizing of cracks.

• 대기
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• 제27권2호
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• pp.119-131
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• 2017

We present and discuss the Tropopause Folding Turbulence Detection (TFTD) algorithm for the Korean Communication, Ocean, Meteorological Satellite (COMS) which is originally developed for the Tropopause Folding Turbulence Product (TFTP) from the Geostationary Operational Environmental Satellite (GOES)-R. The TFTD algorithm assumes that the tropopause folding is linked to the Clear Air Turbulence (CAT), and thereby the tropopause folding areas are detected from the rapid spatial gradients of the upper tropospheric specific humidity. The Layer Averaged Specific Humidity (LASH) is used to represent the upper tropospheric specific humidity calculated using COMS $6.7{\mu}m$ water vapor channel and ERA-interim reanalysis temperature at 300, 400, and 500 hPa. The comparison of LASH with the numerical model specific humidity shows a strong negative correlation of 80% or more. We apply the single threshold, which is determined from sensitivity analysis, for cloud-clearing to overcome strong gradient of LASH at the edge of clouds. The tropopause break lines are detected from the location of strong LASH-gradient using the Canny edge detection based on the image processing technique. The tropopause folding area is defined by expanding the break lines by 2-degree positive gradient direction. The validations of COMS TFTD is performed with Pilot Reports (PIREPs) filtered out Convective Induced Turbulence (CIT) from Dec 2013 to Nov 2014 over the South Korea. The score test shows 0.49 PODy (Probability of Detection 'Yes') and 0.64 PODn (Probability of Detection 'No'). Low POD results from various kinds of CAT reported from PIREPs and the characteristics of high sensitivity in edge detection algorithm.

• Asia-Pacific Journal of Atmospheric Sciences
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• 제54권4호
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• pp.527-544
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• 2018

This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the $3.7{\mu}m$ and $10.8{\mu}m$ channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation-maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively.

• 비파괴검사학회지
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• 제28권5호
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• pp.436-442
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• 2008

최근 VHTR(very high temperature reactor)에 대한 연구에서 흑연이 노심내 구조재, 반사재, 감속재로서 가장 적절한 재료로 인식되고 있다. 운전온도는 약 $900^{\circ}C$로 원자로 내부에 유입되는 소량의 불순물에도 흑연은 산화되기 쉬우며 산화된 흑연은 공극률이 증가하며 구조재료로서 가져야 할 파괴인성이 낮아진다. 본 연구에서는 산화 전후의 흑연에 대하여 초음파특성을 측정하고, 이를 기반으로 흑연에 대한 초음파탐상검사의 유효성을 타진하였다. 흑연의 초음파특성 측정 결과 초음파속도는 탄소강의 약 1/2, 음파 감쇠는 5배 이상, 신호대잡음비는 약 1/3로 측정되었다. 산화 후, 초음파속도는 as-received 상태에 비하여 미소하게 감소되었으나 초음파감쇠는 200% 이상으로 그 차이가 두드러지게 나타났다. 신호대잡음비에 기반하여 POD (probability of detection)을 산출한 결과, 100 mm 미만의 깊이를 가지는 측면공(SDH; side drilled hole)는 산화 전후에 큰 차이를 나타내지 않으므로 해당 깊이를 가지는 결함에 대해서 초음파탐상검사는 비교적 신뢰성 있는 검사를 수행할 수 있다고 판단된다. 상용 자동초음파탐상 장비에서의 테스트 결과 80 mm이하의 깊이에서는 인적오류가 크지 않을 것으로 예상할 수 있었으며, 위상배열 초음파 기법을 통한 검사를 수행한 결과 역시 양호한 신호대잡음비로 측면공들을 모두 검출할 수 있었다.