• Proceedings of the KIEE Conference
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• 2008.05a
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• pp.145-146
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• 2008

초고압 케이블에서 발생하는 부분방전을 측정하기 위해 다양한 방법들이 연구 개발되어왔다. 최근에는 초고압 케이블의 설치 후 시행하는 준공시험에 있어 부분방전 측정을 필수적으로 할 만큼 부분방전 진단기술의 중요성이 부각되고 있는 실정이며, 디지털 측정기술을 통한 부분방전자동측정 기술이 많이 제안되고 있다. 특히, 비전문가들만으로도 진단 및 감시가 가능하도록 하는 자동 패턴 분류에 대한 다양한 연구에 활발히 보고되고 있다. 본 논문에서는 초고압 케이블에서 발생되는 결함을 내부, 외부, 노이즈의 세 가지로 분류하고 PRPD(Phase Resolved Partial Discharge) 형태로 모의된 실험데이터와 현장에서 축적된 데이터를 선별하여 다양한 통계치를 추출하였고, 결함별 구분이 용이하지 않은 통계치를 제외한 값들을 Neural Network 방법으로 학습시켰다. 학습된 가중치 값을 LabView로 작성된 프로그램에 사용하여 변전소 내 EBG에서 검출한 부분방전 측정 결과에 적용하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1401-1409
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• 2007

This paper presents a detecting technique for the improvement in quality by appling the various vibrational characteristics theory. The object of this study is to objectively point out faulty gear by developing the program which can be used to analyze and predict the vibrational characteristics caused by gear wear, deformation and nick of auto-transmission. The fault detection methods by vibrational signal analysis of gear have been progressed in the various fields of industry. These methods have the advantage of being easy to attach the accelerometer without discontinuance of the structure. But not all the methods are efficient for finding early faults. So in the thesis, we completed development of the inspection system of vibration by appling the most efficient detecting methods and verified the system's reliability through experiments.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.1
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• pp.47-56
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• 2008

This paper presents a detecting technique for the improvement in quality by appling the various vibrational characteristics theory. The object of this study is to objectively point out faulty gear by developing the program which can be used to analyze and predict the vibrational characteristics caused by gear wear, deformation and nick of auto-transmission. The fault detection methods by vibrational signal analysis of gear have been progressed in the various fields of industry. These methods have the advantage of being easy to attach the accelerometer without discontinuance of the structure. But not all the methods are efficient for finding early faults. So in the thesis, we completed development of the inspection system of vibration by appling the most efficient detecting methods and verified the system's reliability through experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1353-1358
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• 2010

In this paper, we propose a detection method that automatically detects concrete surface cracks using fuzzy method in the image of concrete surface cracks. First, the proposed method detecting concrete surface cracks detects the candidate crack areas by applying R, G, B channel values of the concrete crack image to fuzzy method. We finally detect cracks by the density information about the detected candidate areas after we remove the detailed noises on the image of the concrete surface cracks. The experiments using real concrete images showed that the proposed method is greatly improved of crack detection compared with the conventional methods.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.12
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• pp.24-30
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• 2003

In this paper, we proposed an adaptive ATC(Automatic Threshold Control) circuit with more decreased settling time by improving the structure of the peak detector. We showed that it could reduce a good deal of the settling time because it showed less than half the error voltage ratio that the ATC circuit with conventional structure showed in analysis. We also designed a burst-mode ATC circuit for the 1.25Gbps EPON system using a commercial foundry. It produced the reference levels in very short time, 6㎱ in 40 ㏈ input dynamic range.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.213-225
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• 2018

For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

• Convergence Security Journal
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• v.19 no.5
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• pp.75-84
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• 2019

Recently, the value of video as an important data of medical information technology is increasing due to the feature of rich clinical information. On the other hand, video is also required to be de-identified as a medical image, but the existing methods are mainly specialized in the stereotyped data and still images, which makes it difficult to apply the existing methods to the video data. In this paper, we propose an automated system to index candidate elements of personal identification information on a frame basis to solve this problem. The proposed system performs indexing process using text and person detection after preprocessing by scene segmentation and color knowledge based method. The generated index information is provided as metadata according to the purpose of use. In order to verify the effectiveness of the proposed system, the indexing speed was measured using prototype implementation and real surgical video. As a result, the work speed was more than twice as fast as the playing time of the input video, and it was confirmed that the decision making was possible through the case of the production of surgical education contents.

• Smart Media Journal
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• v.12 no.10
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• pp.19-28
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• 2023

In the fruit harvesting field, interest in automatic robot harvesting is increasing due to various seasonality and rising harvesting costs. Accurate apple detection is a difficult problem in complex orchard environments with changes in light, vibrations caused by wind, and occlusion of leaves and branches. In this paper, we introduce a dataset and an adaptive heatmap regression model that are advantageous for robot automatic apple harvesting. The apple dataset was labeled with not only the apple location but also the visibility. We propose a method to detect the center point of an apple using an adaptive heatmap regression model that adjusts the Gaussian shape according to visibility. The experimental results showed that the performance of the proposed method was applicable to apple harvesting robots, with MAP@K of 0.9809 and 0.9801 when K=5 and K=10, respectively.

• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.127-134
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• 2003

This paper is intended to develop an algorithm for automatic detection of traffic accidents using image sequences. This algorithm is designed for detecting stopped vehicles traffic accidents, break down, illegal stop in the road shoulder - on the range of camera view. Virtual traps are set on accident-prone spots. We analyze the changes in gray levels of pixels on the virtual traps which represent the motion of vehicles on the corresponding spots. We verify the proposed algorithm by simulating some situations and checking if it detect them correctly.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.5
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• pp.398-405
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• 2014

Recently the embedded software has been widely applied to the safety-critical systems in aviation and defense industries, therefore, the higher level of reliability, availability and fault tolerance has become a key factor for its implementation into the systems. The integrity of the software can be verified using the static analysis tools. And recent developed static analysis tool can evaluate code integrity through the mathematical analysis method. In this paper we detect the autocode error and violation of coding rules using the formal verification tool, Polyspace(R). And the fundamental errors on the flight control law model have been detected and corrected using the formal verification results. As a result of verification process, FBW helicopter control law autocode can ensure code integrity.