• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1664-1666
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• 2001

This paper presents the development of electromagnetic wave detecting equipment for diagnosis of enclosed switchboard. High voltage power equipments are very important equipment of the key industries and the private enterprise. Power line accidents are national plans because of those set off casualties lose of power equipments and communication networks. Therefore the necessity of the development of detecting for power equipment diagnosis is demand for prevention of high voltage equipment accidents. This paper is the development of electromagnetic wave detecting equipment for diagnosis of high voltage equipment. This paper establishes the diagnosis method for high voltage power equipments, that secures original technique and possesses detecting technique for electromagnetic wave. By the study we developed electromagnetic wave detector, and we applied this equipment application tests at the place constructed high voltage equipments.

• Journal of Mechanical Science and Technology
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• v.16 no.2
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• pp.255-261
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• 2002

A newly designed mass-detecting capillary viscometer uses a novel concept to continuously measure non-Newtonian fluids viscosity over a range of shear rates. A single measurement of liquid-mass variation with time replaces the now rate and pressure drop measurements that are usually required by capillary tube viscometers. Using a load cell and a capillary, we measured change in the mass flow rate through a capillary tube with respect to the time, m(t), from which viscosity and shear rate were mathematically calculated. For aqueous polymer solutions, excellent agreement was found between the results from the mass-detecting capillary viscometer and those from a commercially available rotating viscometer. This new method overcomes the drawbacks of conventional capillary viscometers meassuring non-Newtonian fluid viscosity. First, the mass-detecting capillary viscometer can accurately and consistently measure non -Newtonian viscosity over a wide range of shear rate extending as low as 1 s$\^$-1/. Second, this design provides simplicity (i. e., ease of operation, no moving parts), and low cost.

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.174-176
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• 2007

Because of accident or leak of electricity, high voltage electricity can be conducted to vehicle chassis and damage human. Therefore the unit for detecting ground fault is necessary to minimize loss of life or equipment damage. Isolation resistance must be monitored for detecting ground fault. GFD(Ground Fault Detection) unit continually generate the pulse voltage between high voltage network and chassis. This will be sensing the returned current, calculate the isolation resistance and make decision the ground fault. This paper describes the method detecting ground fault.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.211-214
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• 2002

Under a continuous manufacturing process, two dimension inspection system causes problems as blurring effect and low resolution and requires position calibration between frames. One dimension inspection system is, therefore, being researched as a substitution. In this paper, we implement mechanism of switching memory and processing data for reasonable one dimension inspection system. Redundant weft image and noise was suggested to be reduced by new method using modified morphological process and masked erosion process. From resulting image, line data and possible error information were obtained and constructed as a structure. Finally, error detecting algorithm was performed with this data structure. Processing time of error detecting was 0.625ms per line in applied system and experiment showed 94.7% of error detecting ability. This method is 20% faster in speed and 2.7% higher in error detecting ability comparing with the present method.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.210-213
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• 2003

Short-circuited can have significant effects on a generator and its performance. One of effective method detecting inter-turn short circuits on round rotor winding is a method using sensor detecting. But the method needs duplicate design of sensor for characteristic change according to types and forms of generator. Thus rotor shorted-turn diagnosis method without sensor is needed for detecting short turn when generator is driven. Diagnosis method without sensor depend on change of electric property in generator For the reason, this paper presents characteristic analysis of shorted-turns in generator by detecting the output voltage of generator.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05c
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• pp.178-181
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• 2001

This paper presents the development of electromagnetic wave detecting equipment for diagnosis of enclosed switchboard. High voltage power equipments are very important equipment of the key industries and the private enterprise. Power line accidents are national plans because of those set off casualties lose of power equipments and communication networks. Therefore the necessity of the development of detecting for power equipment diagnosis is demand for prevention of high voltage equipment accidents. This paper is the development of electromagnetic wave detecting equipment for diagnosis of high voltage equipment. This paper establishes the diagnosis method for high voltage power equipments, that secures original technique and possesses detecting technique for electromagnetic wave. By the study we developed electromagnetic wave detector, and we applied this equipment application tests at the place constructed high voltage equipments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1410-1416
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• 2011

A corrosion detecting system for 22.9 kV distribution power line insulation cable, which can travel autonomously along the live line, is proposed. Eddy current test method is employed to detect the corrosion, and the system developed here is capable of detecting internal corrosion of a ACSR-OC. Somewhat details of the electrical and mechanical mechanism of the system and traveling algorithm are introduced. Experimental results applied to the sample cables having artificial corrosion and the operating distribution lines are provided. From the result, we confirmed that the system is useful for detecting internal corrosion of a ACSR, and is expected to be a new non-destructive testing equipment in the area of diagnosis for the distribution power line.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1332-1341
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• 1999

Rapid expansion of network and increment of computer system access cause computer security to be an important issue. Hence, the researches in intrusion detection system(IDS)are active to reduce the risk from hackers. Considering IDS, we propose a new IDS model(DABIDS : Distributed Agent Based Intelligent intrusion Detection System) based on distributed intrusion detecting agents. The DABIDS dynamically collects intrusion behavior knowledge from each agents when some doubtable behaviors of users are detected and make new agents codes using intrusion scenario data base, and broadcast the detector codes to the distributed intrusion detecting agent of all node. This DABIDS can efficiently solve the problem to reduce the overhead for training detecting agent for intrusion behavior patterns.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.159-168
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• 2021

Detecting cyber-attacks using machine learning or deep learning is being studied and applied widely in network intrusion detection systems. We noticed that the application of deep learning algorithms yielded many good results. However, because each deep learning model has different architecture and characteristics with certain advantages and disadvantages, so those deep learning models are only suitable for specific datasets or features. In this paper, in order to optimize the process of detecting cyber-attacks, we propose the idea of building a new deep learning network model based on the association and combination of individual deep learning models. In particular, based on the architecture of 2 deep learning models: Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM), we combine them into a combined deep learning network for detecting cyber-attacks based on network traffic. The experimental results in Section IV.D have demonstrated that our proposal using the CNN-LSTM deep learning model for detecting cyber-attacks based on network traffic is completely correct because the results of this model are much better than some individual deep learning models on all measures.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.31-40
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• 2022

YOLOv4 can be used for detecting parking vehicles in order to check a vehicle in out-door parking space. YOLOv4 has 9 anchor boxes in each of 13x13 grid cells for detecting a bounding box of object. Because anchor boxes are allocated based on each cell, there can be existed small observational error for detecting real objects due to the distance between neighboring cells. In this paper, we proposed YOLOv4 grid cell shift algorithm for improving the out-door parking vehicle detection accuracy. In order to get more chance for trying to object detection by reducing the errors between anchor boxes and real objects, grid cells over image can be shifted to vertical, horizontal or diagonal directions after YOLOv4 basic detection process. The experimental results show that a combined algorithm of a custom trained YOLOv4 and a cell shift algorithm has 96.6% detection accuracy compare to 94.6% of a custom trained YOLOv4 only for out door parking vehicle images.