• 제목/요약/키워드: on-line diagnosis system

검색결과 262건 처리시간 0.042초

수력발전기 On-line 부분방전 측정 시스템을 이용한 절연상태 진단의 신뢰성 향상 (Reliability Improvement of Insulation Diagnosis Using the Hydro-Generator On-Line Partial Discharge Monitoring System)

  • 옥연호;이은웅;임재일;박지군;곽원구;이재흥;신재필;신병철
    • 전기학회논문지P
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    • 제58권4호
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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.

발전기 운전중 종합 진단시스템 개발 (Development of On line Diagnosis System for Generator)

  • 이영준;공태식;김희동;주영호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 제36회 하계학술대회 논문집 B
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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.

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An Integrated On-Line Diagnostic System for the NORS Process of Maiden Reactor Project: The Design Concept and Lessons Learned

  • Kim, Inn-Seock
    • Nuclear Engineering and Technology
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    • 제32권3호
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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.

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On-line Monitoring of Tribology Parameters and Fault Diagnosis for Disc Brake System

  • Yang Zhao-Jian;Kim Seock-Sam
    • 한국윤활학회:학술대회논문집
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    • 한국윤활학회 2003년도 학술대회지
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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.

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On-line Diagnosis System with Learning Bayesian Networks for fsEBPR

  • Cheon, Seong-Pyo;Kim, Sung-Shin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제7권4호
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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.

Development and Application of Distributed Multilayer On-line Monitoring System for High Voltage Vacuum Circuit Breaker

  • Mei, Fei;Mei, Jun;Zheng, Jianyong;Wang, Yiping
    • Journal of Electrical Engineering and Technology
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    • 제8권4호
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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.

전력용 변압기 온라인 유중가스 진단기준치 및 알고리즘에 관한 연구 (Study on the Criterion and Algorithm for On-line Dissolved Gas of a Power Transformer)

  • 권동진;곽주식;곽희로;김재철;진상범
    • 대한전기학회논문지:전기물성ㆍ응용부문C
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    • 제54권5호
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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.

신경망을 이용한 실시간 고장 진단 시스템 (On-Line Fault Diagnosis System using Neural Network)

  • 김문성;유승선;소정훈;곽훈성
    • 한국통신학회논문지
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    • 제26권11C호
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    • pp.75-84
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    • 2001
  • 본 논문에서는 신경망을 이용한 실시간 고장 검출 및 진단(FDD : Fault Detection and Diagnosis) 시스템을 제안한다. 제안된 시스템은 공조 시스템(FDD : Air Handling Unit)에서 발생 가능한 여러 고장들을 검출하고 진단할 수 있다. 고장 검출 및 진단 기법으로 3층 구조의 전방향(feed-forward) 신경망을 사용하였고, 여기에 사용된 학습 방법은 역전파(back-propagation) 학습 알고리즘이다. 공조 시스템에 적용된 실시간 고장 검출 및 진단 시스템은 비주얼 C++와 비주얼 베이직을 사용하여 구현하였다. 제안된 고장 검출 및 진단 시스템을 실제 운전 중인 공조 시스템에 적용하여 실험하였고, 정확한 고장 검출 및 진단이 수행됨을 실험 결과로서 입증하였다.

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태양광 발전시스템 전지모듈의 온라인 감시 진단 시스템 개발 (On Line Monitoring and Diagnosis Technique for the Array of Photovoltaic Energy System)

  • 이종필;지평식;변상준;임재윤
    • 전기학회논문지P
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    • 제56권4호
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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.

콘크리트 플랜트의 온-라인 감시 및 고장진단을 위한 시스템 개발에 대한 연구 (A study of system development for on-line monitoring and fault diagnosis of a concrete plant)

  • 공영준;장태규;양원영
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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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.

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