• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1782-1787
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• 1997

A combined algorithm called APEXS(Alarm Processing and Diagnosis Expert System) for power plants has been developed on the time-based alarm processing with a proper alarm prioritization and a diagnosis with a qualitative model(QM), qualitative interpreter(QI), and a state-transition trees(STT).

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.133-138
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• 1997

For a long time, a number of alarm processing techniques have been researched to reduce the number of actuated alarms for operators to deal with effectively during the abnormal as well as the normal conditions. However, the strategy that the only systems with a few clear technologies should be used as a part of an alarm annunciation system has been adopted considering the effectiveness and the reliability in actual alarm processing systems. Therefore, alarm processing systems have difficult knowledge-base maintenance problems and limited expansion or enhancement defects. To solve these shortcomings, the integrated knowledge-base which can express the general information related to all the alarm processing techniques is proposed and its management tool, Knowledge Input Tool for Alarm (KIT-A) which can handle the data of the knowledge-base efficiently is developed. Since the integrated knowledge-base with KIT-A can manipulate all the alarm information without the modification of alarm processing system itself, it is expected to considerably advance the overall capability of maintenance and enhancement of the alarm processing systems.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.8
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• pp.1045-1056
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• 1995

The purpose of multiple alarm processing is to give the operator the correct information and perception of the malfunction present in the plant. In this thesis, an APS(Alarm Processing System) is studied for fossil power plants. This APS is based on a cause-consequence trees in the knowledge representation aspect for alarm and plant and adapts alarm filtering methods using fired time information in the decision aspect. Through the cause-consequence trees and filtering methods, the Alarm Processing System finds the cause alarm among the fired multiple alarms and calculates the cause degree which represents the possibility of a fault occurring in the instruments of the plant with the information of fired alarm. The knowledge base is built via interviews and questionaries with the expert operators on the Seoul power plant unit 4. Finally, the validity of the studied APS is shown via simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1804-1810
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• 2011

It is necessary to adopt some logical techniques and methods of alarm processing for a large complex plant such as nuclear power plants in order to present the occurred alarm messages properly and concisely. Among such alarm processing techniques, the alarm suppressing function is a strong tool to avoid alarm flooding during the sudden transients of plant output power such as turbine trips, reactor trips and other incidents. Unless any suppression or representation technologies are used in an alarm message listing system, it cannot provide quick assistance to plant operators or supervisors during plant upsets because too many alarm messages are presented in an alarm list window. This paper presents the key suppression methods and analysis processes developed for implementing a suppressed alarm message listing function of an integrated alarm system called LogACTs which has been applied to a CANDU nuclear power plant. A simulation testing of the suppressing function conducted with the real plant alarm message list data has demonstrated an effective performance of the developed logics with the high suppression rate.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.161-162
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• 2006

There are many alarms in Substation Automation System because of data types and quantities increasing, so it is very difficult for operators to know the actual situations. In order to help operators easily make decision, some unnecessary alarms should be removed or combined as one. In this paper, alarm processing is using the structure of substation system and the relation of measured data and events to make some rules. Conventional alarm processing just gives data, but proposed alarm processing gives the whole information. In a simulation model system, the data such as voltage, current and CB status are collected by HyperSim and saved in DB, then proposed alarm processing has been testified using those data based on real-time simulation.

• The Journal of the Korea Contents Association
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• v.2 no.1
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• pp.86-97
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• 2002

In this thesis, we propose a high-speed information network management mode based on layering and partitioning concepts of ITU-T G.805 We describe an information mood of the configuration of VP and VC networks and an information mode to manage faults in high-speed information networks. In order to efficient manage faults, us distinguish between an alarm with a fault that has negative effects on services and an alarm with an alert that barely affects services. Thus, we propose two types of computational models to treat all of these alarms, a fault alarm processing system and an alert alarm processing system. We also describe procedures of alarm processing and we describe the scope and processing course of NMS and SubNMS when rerouting a fault VP and VC fault connection. Lastly, we describe the implementation and analysis of the performance of the proposed fault alarm processing system. We compare the alarm processing tire of each priority according to the alarm occurrence ratio.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3716-3724
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• 2023

Loose parts monitoring and detecting alarm type in real Nuclear Power Plant have challenges such as background noise, insufficient alarm data, and difficulty of distinction between alarm data that occur during start and stop. Although many signal processing methods and alarm determination algorithms have been developed, it is not easy to determine valid alarm and extract the meaning data from alarm signal including background noise. To address these issues, this paper proposes a denoising autoencoder-based majority vote classification. Training and test data are prepared by acquiring alarm data from real NPP and simulation facility for data augmentation, and noisy data is reproduced by adding Gaussian noise. Using DAEs with 3, 5, 7, and 9 layers, features are extracted for each model and classified into neural networks. Finally, the results obtained from each DAE are classified by majority voting. Also, through comparison with other methods, the accuracy and the false alarm rate are compared, and the excellence of the proposed method is confirmed.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.229-240
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• 2006

The advanced Alarm System (AS) employs modem digital technology to implement the alarm functions of the NPP(Nuclear Power Plant). The use of modem digital technology can provide advanced alarm processing in which new algorithms such as a signal validation, advanced alarm processing logic and other features are applied to improve the control room man-machine interfaces. This paper will describe the design process of the AS of NPP, improving the system reliability and availability using the reliability prediction tool, design strategies regarding the human performance topics associated with a computer-based AS and the results of the performance analysis using a prototype of the AS.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1096-1099
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• 2014

스마트폰의 보급률에 맞물려 스마트폰 사용으로 인한 보행자 교통사고가 증가함에 따라 전세계적으로 이에 관한 연구 또한 꾸준히 증가 추세임에도 불구하고 인구대비 스마트폰 보급률이 세계 최고인 국내에서는 이에 대한 연구가 아직 미흡한 실정이다. 본 연구에서는 보행 중 교통사고 중에서 큰 비중을 차지하고 있는 젊은층의 산만 보행에 관해 알아보고자 하였다. 본 연구는 정신과학 분야의 주의 네트워크 연구를 바탕으로 보행자의 안전도 향상은 물론, 스마트폰 이용자의 사용성을 고려한 depth-based alarming 서비스를 제안한다.-본 연구는 스마트폰 애플리케이션을 제작하여 국내 20대 스마트폰 이용자를 대상으로 피험자내 설계로 진행되었고, 보행자의 안전도에 관련한 무선조종 자동차에 대한 반응속도와 충돌여부를 측정하였고, 또한 앱 사용성에 관련한 방해도 및 만족도를 설문을 통해 측정하였다. 본 연구는 위험 상황을 알리는 alarm 을 제공하기 전에 미리 pre-alarm 을 제공하는 depth-based alarming 을 디자인 하였다. 본 연구는 실험을 통해 pre-alarm 제공시 alarm 에 대한 보행자의 반응 속도가 1.446 초 향상됨을 통계적 유의성을 통해 입증함으로써 pre-alarm 을 제공하는 depth-based alarming 서비스의 필요성을 제시한다.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.146-154
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• 2019

An improved principal component analysis (PCA) method is applied for sensor fault detection and isolation (FDI) in a nuclear power plant (NPP) in this paper. Data pre-processing and false alarm reducing methods are combined with general PCA method to improve the model performance in practice. In data pre-processing, singular points and random fluctuations in the original data are eliminated with various techniques respectively. In fault detecting, a statistics-based method is proposed to reduce the false alarms of $T^2$ and Q statistics. Finally, the effects of the proposed data pre-processing and false alarm reducing techniques are evaluated with sensor measurements from a real NPP. They are proved to be greatly beneficial to the improvement on the reliability and stability of PCA model. Meanwhile various sensor faults are imposed to normal measurements to test the FDI ability of the PCA model. Simulation results show that the proposed PCA model presents favorable performance on the FDI of sensors no matter with major or small failures.