• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.469-475
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• 2009

Accident dangerousness of domestic hydro power generators which are operated in Korea is on the increase because of use at the long term. On this, the Off-line diagnosis techniques developed to the On-line by continued domestic technical development since 2000. Especially, On-line insulation diagnosis of domestic hydro power generator is possible by localization of partial electric discharge sensor and On-line insulation diagnosis system. This paper shows the diagnosis result that is applied localized Ceramic Coupler and PDMS-HG(Partial Discharge Monitoring System for Hydro Generator) at four Chung-ju hydro Generator used for 25 years. Particularly, the confidence of insulation diagnosis is improved by using high frequency filter and sampling the partial discharge signals which occur in site. For reviewing the confidence of On-Line insulation diagnosis system, we measured the outside noises and partial discharge signals during practical operation by using the partial discharge diagnosis system of the Full A/D process. And we reviewed the confidence of the On-Line insulation diagnosis system by comparing and analyzing these data.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.975-977
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• 2005

The generator on-line diagnosis system has been developed. This system monitor the insulation condition of stator winding by on-line measurements of partial discharge and the shorted-turn condition of rotor winding by on-line measurements of slot leakage flux. Sensor, such as SSC(Stator Slot Coupler) and flux probe are used for generator on-line diagnosis.

• Nuclear Engineering and Technology
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• v.32 no.3
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• pp.261-273
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• 2000

During an extensive review made as part of the Integrated Diagnosis System project of the Maiden Reactor Project, MOAS (Maryland Operator Advisory System) was identified as one of the most thorough systems developed thus far. MOAS is an integrated on-line diagnosis system that encompasses diverse functional aspects that are required for an effective process disturbance management: (1) intelligent process monitoring and alarming, (2) on-line sensor data validation and sensor failure diagnosis, (3) on-line hardware (besides sensors) failure diagnosis, and (4) real-time corrective measure synthesis. The MOAS methodology was used at the Maiden Man-Machine Laboratory HAMMLAB of the OECD Maiden Reactor Project. The performance of MOAS, developed in G2 real-time expert system shell for the high-pressure preheaters of the NORS process in the HAMMLAB, was tested against a variety of transient scenarios, including failures of the control valves and sensors, and tube leakage of the preheaters. These tests showed that MOAS successfully carried out its intended functions, i.e., quickly recognizing an occurring disturbance, correctly diagnosing its cause, and presenting advice on its control to the operator. The lessons learned and insights gained during the implementation and performance tests also are discussed.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2003.11a
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• pp.224-228
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• 2003

The basic Principles and methods of the on-line monitoring of tribology parameters (friction coefficient and wear allowance) and fault diagnosis for the hoist disc brake system were introduced, the method were based on the spring force and oil pressure of the brake system and the hoist kinematics parameters. The experiment on the monitoring and diagnosis of hoist brake system were carried out. The research results showed: the monitoring and diagnosis methods are feasible.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.279-284
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• 2007

Nowadays, due to development of automatic control devices and various sensors, one operator can freely handle several remote plants and processes. Automatic diagnosis and warning systems have been adopted in various fields, in order to prepare an operator's absence for patrolling plants. In this paper, a Bayesian networks based on-line diagnosis system is proposed for a wastewater treatment process. Especially, the suggested system is included learning structure, which can continuosly update conditional probabilities in the networks. To evaluate performance of proposed model, we made a lab-scale five-stage step-feed enhanced biological phosphorous removal process plant and applied on-line diagnosis system to this plant in the summer.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.813-823
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• 2013

On-line monitoring system is important for high voltage vacuum circuit breakers (HVCBs) in operation condition assessment and fault diagnosis. A distributed multilayer system with client/server architecture is developed on rated voltage 10kV HVCB with spring operating mechanism. It can collect data when HVCB switches, calculate the necessary parameters, show the operation conditions and provide abundant information for fault diagnosis. Ensemble empirical mode decomposition (EEMD) is used to detect the singular point which is regarded as the contact moment. This method has been applied to on-line monitoring system successfully and its satisfactory effect has been proved through experiments. SVM and FCM are both effective methods for fault diagnosis. A combinative algorithm is designed to judge the faults of HVCB's operating mechanism. The system's precision and stability are confirmed by field tests.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.5
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• pp.206-212
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• 2005

In this paper, criterion and algorithm for on-line dissolved gas of a Power transformer are studied. For the initial diagnosis of a power transformer, the on-line dissolved gas analysis is one of the most important and acceptable item to preventively diagnose a power transformer. But the criterion and algorithm of this item are not established yet in korea. In this paper, criterion and alarm level of the on-line dissolved gas analysis are based on the analysis of on-line data of operating transformers, Korea industrial standard and operation manual for a power transformer as well as accumulated data of the preventive diagnosis systems which have been operated at nine substations of Korea Electric Power Co.(KEPCO) since 1997, Therefore, the criterion and alarm level proposed in this paper are to be well suitable and are adaptable for the domestic operational environments and conditions of the power transformer. Considering that the conventional diagnosis system is capable only of accumulating and monitoring data of the power transformer operation, the criteria and the algorithms make it possible to accomplish an ultimate goal of the preventive diagnosis system. It is expected, therefore, that they will have a beneficial effect on broad applications of the preventive diagnosis system and the achievement of manless substation system in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11C
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• pp.75-84
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• 2001

In this paper, we propose an on-line FDD(Fault Detection and Diagnosis) system based on the three layer feed-forward neural network which is trained by the back-propagation teaming algorithm. We implement the on-line fault detection and diagnosis system by Visual C++ and Visual Basic. The proposed FDD system is applied to an air handling unit in operation. Experimental results show the high performance of our system in the task of fault detection and diagnosis.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.4
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• pp.168-172
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• 2007

The global environment deteriorating which originated from using of fossil fuel is an serious problem for human being to solve. The photovoltaic energy has been considered as a solution. In advanced countries, research and development for photovoltaic(PV) energy system is carrying on. Once installed, a PV array requires maintenance and fault diagnosis other than an occasional cleaning. In this research, the proposed system monitor and diagnosis the output of PV array by on-line for maintenance of PV power plant. The validity of proposed system is verified using sample system.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.228-232
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• 1993

This paper describes a on-line monitoring and fault diagnosis system designed for the automation of a medium-size concrete plant. The system is based on the structure of a hardware system of data acquisition and a personal computer. Simulation results are presented to illustrate the system operation. It applies the preconstructed rules to the plant data for the diagnosis of weighing processes.