• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.616-619
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• 1995

This paper describes developement of on-line system for vibration signal analysis. In the power system, the main reason of transformer fault is due to a large amount of current by a short-circuit and a ground-fault. The electromagnetic force caused by fault-current deforms transformer windings and results in vibration pattern change. Therefore if the continuous on-line vibration monitoring on transformer is performed, an incipient failure can be detected. The developed system is composed of data acquisition devices, user interface program, signal processing program, diagnosis and trend analysis program, self diagnosis program and communication program.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.10
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• pp.126-133
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• 2008

Computer and communication of based IT technology use to das that remote control, monitoring, measuring automatic gas switch, recloser located far about $20{\sim}30[km]$. For increasing efficiency billing, metering of high voltage customer use to amr system. If between das and amr interface operate when generated fault in high voltage electric equipment of customer part, amr system serve to das quickly in fault information data, correct fault location.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.450-453
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• 1996

This research presents a new method of detecting and diagnosing faults of a power plant. Detection of characteristic wave patterns from multichannel instrumentation signals forms the basis of the proposed approach. The dynamics of 500MW drum-type boiler (Boryung coal-fired plant unit #1 and #2) and its control systems are modeled and simulated to generate diverse operation patterns and fault situations and to utilize them for the development of the fault detection algorithms. The results of the boiler system modeling and simulations show a fairly high agreement when compared with some of the actual plant performance test data.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.666-670
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• 2011

In this paper, a method for detecting broken rotor bar and stator winding fault in a low voltage squirrel-case induction motor using an air-gap flux variation analysis is proposed to develop a simple and low cost diagnosis technique. To measure the leakage flux in radial direction, a radial flux sensor is designed as a search coil and installed between stator slots. The proposed method is able to identify two kinds of motor faults by calculating load condition of motors and monitoring abnormal signals those are related with motor faults. Experimental results obtained on 7.5kW three-phase squirrel-cage induction motors are discussed to verify the performance of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.70-71
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• 2021

In this paper, we propose a new system that improves the management efficiency of aviation fault indication light of the wind power generator. By applying an LTE mobile communication network to the existing aviation fault indication light, the proposed system remotely checks the status, voltage, current, and temperature information of the light.

• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.5-9
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• 2019

Optical emission spectroscopy is used to identify chemical species and monitor the changes of process results during the plasma process. However, plasma process monitoring or fault detection by using emission signal variation monitoring is vulnerable to background signal fluctuations. IR heaters are used in semiconductor manufacturing chambers where high temperature uniformity and fast response are required. During the process, the IR lamp output fluctuates to maintain a stable process temperature. This IR signal fluctuation reacts as a background signal fluctuation to the spectrometer. In this research, we evaluate the effect of infrared background signal fluctuation on plasma process monitoring and improve the plasma process monitoring accuracy by using simple infrared background signal subtraction method. The effect of infrared background signal fluctuation on plasma process monitoring was evaluated on $SiO_2$ PECVD process. Comparing the $SiO_2$ film thickness and the measured emission line intensity from the by-product molecules, the effect of infrared background signal on plasma process monitoring and the necessity of background signal subtraction method were confirmed.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.3073-3078
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• 2011

Driverless Train Control System has been recently introduced and commercialized in Korea. It is expected that the vehicle with driverless operation system will be used in new lines such as Sinbundang line soon. Therefore it is necessary to change the system operation and conception of the existing train operation system and the necessity of driverless vehicle monitoring system meeting a new paradigm is rising. In order to dispel concerning about safety issues caused by driverless train operation, the importance to establish vehicle error detection, useful fault diagnosis and rapid action plans is higher than ever. For this, efficient and higher level of vehicle supervision & control system should be essentially supported. In this study, remote driverless vehicle monitoring system using by radio communication is suggested to be used for monitoring and controlling important parts of the vehicle and diagnose and take quick actions when vehicles are in trouble at control tower at real time.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.98-105
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• 2000

In this study, we developed rotating machine vibration condition monitoring system based upon Windows NT and DSP Board. Developed system includes signal analysis module, trend monitoring and simple diagnosis using threshold value. Trend analysis and report generation are offered with database management tool which was developed in MS-ACCESS environment. Post-processor, based upon Matlab, is developed for vibration signal analysis and fault detection using statistical pattern recognition scheme based upon Bayes discrimination rule and neural networks. Concerning to Bayes discrimination rule, the developed system contains the linear discrimination rule with common covariance matrices and the quadratic discrimination rule under different covariance matrices. Also the system contains k-nearest neighbor method to directly estimate a posterior probability of each class. The result of case studies with the data acquired from Pyung-tak LNG pump and experimental setup show that the system developed in this research is very effective and useful.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.950-955
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• 2003

This paper introduces an enhanced condition monitoring and diagnosis system recently developed for rotating machinery. In the system, the data aquisition/monitoring signal processing, machine condition classifier, case-based reasoning and demonstration modules are effectively integrated with user-friendliness so that machine operators can easily monitor and diagnose the status of rotating machinery in operation. Some of the new features include the directional spectrum, case-based reasoning and neural network techniques. And the demonstrator modules for fault diagnosis of a Bear driving system and for basic understanding of the rotor dynamics are provided to help the potential users better understand the system.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3184-3186
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• 2000

This paper describes the remote monitoring & diagnosis system of tower parking facilities. This system consists of central station, monitoring equipments and parking system control panel. The central station is developed under client/server architecture, and the monitoring systems are connected to central station by LAN using RAS constructed PSTN. This system offers real-time fault detection and data acquisition of tower parking system.