• Proceedings of the Korea Information Processing Society Conference
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• 2001.04b
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• pp.751-754
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• 2001

열교환기(Heat Exchanger)는 원전 운영에 핵심적인 설비이다. 따라서 열교환기 전열관의 건전성 유무를 판단키 위해 정기적으로 비파괴검사의 일종인 와전류검사(ECT, Eddy Current Testing)를 수행하고 있다. 이러한 와전류검사 공정은 크게 3가지로 분류할 수 있다. 첫 번째는 전열관 상태검사를 위한 신호데이터 취득공정이고, 두 번째는 취득된 신호를 판독하여 전열관의 건전성 여부를 진단하는 평가공정, 마지막으로 평가공정에서 발생하는 방대한 데이터를 토대로 추이분석 자료를 제공할 수 있는 공정이 필요하다. 본 논문에서는 세 번째 공정에서 필요한 열교환기 Tubesheet를 사용자 정의에 따라 자동으로 구현할 수 있는 기능을 정의하고, 평가공정에서 발생한 데이터를 직접 Tubesheet상에 Mapping 처리하여 시각적으로 전열관 상태를 확인할 수 있는 프로그램 구현방법을 제시한다.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.9
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• pp.464-469
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• 2004

The leakage current of transmission insulators contaminated with salt, clay, and kaolin was examined in the Gochang's Long Periods Testing Center. The Insulators were artificially contaminated and estimated with the method of equivalent salt deposit density(ESDD). The artificially contaminated insulators were installed with the same condition as in the real transmission power line and applied with 154 (kV). The leakage current of the artificially contaminated insulators was measured with environment conditions, such as temperature and humidity by the a automatic leakage current detecting system. The leakage current of heavily contaminated insulator was abruptly increased above 72［%］ of humidity, even though the leakage current was similar between the contaminated and non-contaminated insulators below 72［%］ of humidity. Also, it was found that the humidity was much more important than the temperature in the leakage current of transmission insulators. The leakage current of contaminated insulator was decreased when it was plenty of rainfall, resulting from natural washing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.61-62
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• 2006

A new neural network classifier is proposed for the automatic real-time surface inspection of high-speed cold steel strips having 11 different types of defects. 46 geometrical and gray-level features are extracted for the defect classification. 3241 samples of Posco's Kwangyang steel factory are used for training and testing the neural network classifier. The developed classifier produces plausible 15% error rate which is much better than 20-30% error rate of human vision inspection adopted in most of domestic steel factories.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.76-83
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• 2007

A new neural network classifier is proposed for the automatic real-time surface inspection of high-speed cold steel strips having 11 different types of defects. 46 geometrical and gray-level features are extracted for the defect classification. 3241 samples of Posco's Kwangyang steel factory are used for training and testing the neural network classifier. The developed classifier produces plausible 15% error rate which is much better than 20-30% error rate of human vision inspection adopted in most of domestic steel factories.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.511-513
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• 2005

최근 산업계에서는 급변하는 사용자의 요구사항을 반영하면서, 경쟁력 있고, 경제적인 소프트웨어를 개발하기 위해서 EJB 컴포넌트 개발 방법을 채택하고 있다. 그러나 EJB 컴포넌트를 테스트하는 것이 기존의 자바 클래스의 테스트보다 더 많은 노력이 필요하고, 어려운 작업이기 때문에 많은 경우에 EJB 컴포넌트에 대한 테스트가 수행되지 않는다. 이에 본 논문에서 EJB 컴포넌트의 테스트 케이스 생성을 자동화 할 수 있는 방법을 제안한다. 이는 EJB 컴포넌트 개발 시 만들어지는 Deployment Descriptor로부터 컴포넌트에 대한 정보를 추출해내고, 이를 기반으로 테스트 케이스를 자동으로 생성하는 방법이다.

• Atmosphere
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• v.27 no.2
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• pp.251-258
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• 2017

The standard weighing raingauges have a capacity limit in measuring the amounts of precipitation. Exceptions are those using a siphon to drain the collected water during observations. To reduce the drain time of the siphon type or to overcome the hassles associated with the manual emptying of the bucket for measuring, the most of weighing gauges use a large bucket for storing of rainwater to be measured. To avoid the above-mentioned adverse requirements, we propose a paired barrel for a weighing raingauge. The paired barrel may improve the accuracy of the weighing raingauges by getting rid of their capacity limit and make the gauges smaller in size and lighter in weight than the conventional ones. We showed its proper function and the feasibility of realization by testing a prototype paired barrel.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.361-362
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• 2006

Magnetic Flux Leakage (MFL) inspection is a general non-destructive testing (NDT) method to detect the corrosion of natural gas pipelines. Currently, it is subjectively analyzed by trained analysts. In spite of investing much time and human resources, the inspection results may be different according to the analysts' expertise. So, many gas suppliers are keenly interested in the automation of the interpretation process. This paper presents a Gaussian variance filtering method of MFL signals, which is taken from MFL pigging of underground pipelines. In the proposed algorithm the original MFL signals are filtered by multiple Gaussians with different variance. Experimental results show that this approach does not need to align bias and to use explicit noise reduction algorithm.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.125-130
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• 2016

Automatic quality inspection by computer vision can be applied and give a solution to the pharmaceutical industry field. Pharmaceutical capsule can be easily affected by flaws like dents, cracks, holes, etc. In order to solve the quality inspection problem, it is required computationally efficient image processing technique like thresholding, boundary edge detection and segmentation and some automated systems are available but they are very expensive to use. In this paper, we have developed a dented capsule image processing technique using edge-based image segmentation, TLS(Total Least Squares) curve fitting technique and adopted low cost camera module for capsule image capturing. We have tested and evaluated the accuracy, training and testing time of the classification recognition algorithms like PCA(Principal Component Analysis), ICA(Independent Component Analysis) and SVM(Support Vector Machine) to show the performance. With the result, PCA, ICA has low accuracy, but SVM has good accuracy to use for classifying the dented capsule.

• Journal of the Speleological Society of Korea
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• no.87
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• pp.8-13
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• 2008

The automatic firewall block and fire alarm system was embodied by using gas circuit and wireless communication equipment, using a smoke sensor (ST-QA1A) and RF Module. OR-CAD was also used for testing circuit system and experiment circuit after assembling circuit. As a result in experiment, the gas sensor detected well an imaginary smoke and worked reliably for driving action of firewall block motor and wireless warning alarm. Through the smoke sensitive perception from the fire, the warning alarm and the preventing fire propagation from the specific closed region were verified reliably. The gas sensor and RF module for firewall and fire alarm system were actually available.

• ETRI Journal
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• v.34 no.3
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• pp.478-481
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• 2012

Testing memory and repairing faults have become increasingly important for improving yield. Redundancy analysis (RA) algorithms have been developed to repair memory faults. However, many RA algorithms have low analysis speeds and occupy memory space within automatic test equipment. A fast RA algorithm using simple calculations is proposed in this letter to minimize both the test and repair time. This analysis uses the grouped addresses in the faulty bitmap. Since the fault groups are independent of each other, the time needed to find solutions can be greatly reduced using these fault groups. Also, the proposed algorithm does not need to store searching trees, thereby minimizing the required memory space. Our experiments show that the proposed RA algorithm is very efficient in terms of speed and memory requirements.