• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2000.11a
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• pp.89-93
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• 2000

Recently many research activities on the diagnosis of stator winding insulation of large rotating machines have been reported. Capacitive couplers are widely used as sensors for on-line partial discharge (PD) measurement of high voltage rotating machines. This paper presents laboratory test to compare Stator Slot Coupler (SSC), Resistance Temperature Detector (RTD), 80 [pF] coupler and 500 [pF] coupler for on-line PD measurement of rotating machines. And a novel on-line monitoring system for an insulation diagnosis is proposed.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.518-523
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• 2008

In this paper, we present the development of an intelligent diagnosis system for detecting faults of the transmission line. Based on the TFDR (Time-Frequency Domain Reflectometry), the fault detecting performs to measure the location of fault line. We analyze the reflected signal which is sent from the wire detecting system and classify the fault type of the wires by using intelligent diagnosis system. In order to analyze effectively, we construct the intelligent diagnosis system which is based on the fuzzy-bayesian algorithm. Finally, we provide the simulation results which are performed at transmission line to evaluate the feasibility and generality of the proposed method in this paper.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.11
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• pp.742-747
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• 1999

On-line diagnosis system has been developed and is now applied the detection of shorted turns in the field winding of large generator. This system consists of data aquisition system and display PC. The data aquisition system detects voltage waveforms from flux probe sensor installed in the stator slot. The display PC shows theshorted-turn situation of generator rotor winding. A shorted-turn diagnosis test wasperformed on five gas turbine generators at the Seoinchon combined cycle power plant. The test was conducted using an new diagnosis system and digital oscilloscope which can identify the pole location, the slot number and the number of shorted turns within each slot. It is confirmed that results of two systems are very same in the field tests.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.4
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• pp.206-210
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• 2004

This paper deals with a parameter estimation of the DC-DC converter system for its diagnosis. Especially, we present the results of parameter estimation for the DC-DC converter model by the system identification method. The parameter estimation for the DC-DC converter system aims at the diagnosis of its operating status. For the operating status diagnosis of the DC-DC converter system, we assume that the DC-DC converter system is an equivalent model of the Buck converter and estimate the main parameter for on-line diagnosis. In addition, for verification of an estimated parameter, we compare a bode plot of the estimated system transfer function and measurement results of the HP4194 instrument. It is a control system analyzer for system transfer function measurement. Our results confirm that the main parameter for diagnosis of the DC-DC converter system can be estimated by the system identification method and that the aging status of the system can be predicted by these results on operating status.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.975-976
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• 2012

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.313-318
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• 2014

In the last couple of decades industrialization and technological development has not only increase in the scale of electrical facilities and it has become more and more complicated and diversified. Furthermore, fires in the electrical transformers, like those that have knocked out power in the country in the past years, are likely to become more common as utility systems begin to show their age. The importance of preventing electrical accidents can never be overemphasized and for this reason, supply of on-line diagnosis system combining information and communication technology(ICT) for the customer's electrical facilities has been increasing recently. The major advantage of on-line diagnosis system is that the device's potential problems could be detected early before a serious deterioration or breakdown occurs. In this paper, We estimated the benefit from the investment in the right of present value of sales, success rate of commercialization regarding R&D investment for development and commercialization of on-line diagnosis technology targeting customer electrical facilities. As a result, the net value added of 29.7 billion won and the increased profit by roughly 7.52 precent are expected.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.8
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• pp.787-795
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• 2001

An experimentation on the on-line fault detection and diagnosis(FDD) system has been performed with HVAC system in he experimental building constructed inside the large scale environmental chamber. Personal computer with a home-made FDD program by pattern recognition method utilizing artificial neural network was connected on-line via Ether-net TCP/IP to the supervisory control server for HVAC system. The FDD program monitored the HVAC system by 1 minuted interval. The results showed that he FDD program detected the sudden or abrupt faults such s those in fans, sensors and heater, etc.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1906-1908
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• 2000

The central monitoring system with on-line diagnosis of high-voltage generator/motor stator insulation is developed. The system is capable of remote diagnosis and monitoring partial discharges of high-voltage generator/motor stator insulation. GOMS(Generator On-line Monitoring System) with maximum of 9 input channels can measure and analyze the status of high-voltage motor stator insulation by on-line. The measured and analysis data are brought to the central monitoring system via modem to build database. The central monitoring system can diagnose and monitor the insulation status of several high-voltage generator/motor at any time. The insulation status of those machines can be enhanced by the database on partial discharges.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.331-338
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• 1992

The application of Connectionist expert system using neural network to fault diagnosis of power system is presented and compared with rule-based expert system. Also, the merits of Connectionist model using neural network is presented. In this paper, the neural network for fault diagnosis is hierarchically composed by 3 neural network classes. The whole power system is divided into subsystems, the neural networks (Class II) which take charge of each subsystem and the neural network (Class III) which connects subsystems are composed. Every section of power system is classified into one of the typical sections which can be applied with same diagnosis rules, as line-section, bus-section, transformer-section. For each typical section, only one neural network (Class I) is composed. As the proposed model has hierarchical structure, the great reduction of learning structure is achieved. With parallel distributed processing, we show the possibility of on-line fault diagnosis.

• Proceedings of the KIEE Conference
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• 1998.07e
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• pp.1734-1736
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• 1998

On-line partial discharge monitoring system for generator stator insulation is developed. This system consists of remote and host units. The remote unit detects partial discharge signals from SSC(Stator Slot Coupler) installed between wedge and stator windings. The host unit monitors the condition of winding insulation. This system will be used as a module of a generator on-line monitoring system utilizing global network.