• 한국방재학회:학술대회논문집
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• 한국방재학회 2009년도 정기 학술발표대회
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• pp.146.2-146.2
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• 2009

• The Journal of the Acoustical Society of Korea
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• 제15권1E호
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• pp.5-19
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• 1996

This paper proposes a loose part monitoring system (LPMS) design with a signal processing method based on fuzzy logic. Considering fuzzy characteristics of metallic impact waveform due to not only interferences from various types of noises in an operating nuclear power plant but also complex wave propagation paths within a monitored mechanical structure, the proposed LPMS design incorporates the comprehensive relation among impact signal features in the fuzzy rule bases for the purposes of alarm discrimination and impact diagnosis improvement. The impact signal features for the fuzzy rule bases include the rising time, the falling time, and the peak voltage values of the impact signal envelopes. Fuzzy inference results based on the fuzzy membership values of these impact signal features determine the confidence level data for each signal feature. The total integrated confidence level data is used for alarm discrimination and impact diagnosis purposes. Through the perpormance test of the proposed LPMS with mock-up structures and instrumentation facility, test results show that the system is effective in diagnosis of the loose part impact event(i.e., the evaluation of possible impacted area and degree of impact magnitude) as well as in suppressing false alarm generation.

• ETRI Journal
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• 제37권3호
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• pp.502-511
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• 2015

Intrusion detection plays a key role in detecting attacks over networks, and due to the increasing usage of Internet services, several security threats arise. Though an intrusion detection system (IDS) detects attacks efficiently, it also generates a large number of false alerts, which makes it difficult for a system administrator to identify attacks. This paper proposes automatic fuzzy rule generation combined with a Wiener filter to identify attacks. Further, to optimize the results, simplified swarm optimization is used. After training a large dataset, various fuzzy rules are generated automatically for testing, and a Wiener filter is used to filter out attacks that act as noisy data, which improves the accuracy of the detection. By combining automatic fuzzy rule generation with a Wiener filter, an IDS can handle intrusion detection more efficiently. Experimental results, which are based on collected live network data, are discussed and show that the proposed method provides a competitively high detection rate and a reduced false alarm rate in comparison with other existing machine learning techniques.

• 전기학회논문지
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• 제58권7호
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• pp.1276-1280
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• 2009

This paper presents a fault diagnosis expert system for 765kV substation. The proposed system includes the topology processor and intelligent alarm processing subsystems. This expert system estimates the fault section through the inference process using heuristic knowledge and the output of topology processor and intelligent alarm processing system. The rule-base of this expert system is composed of basic rules suggested by Korea Electric Power Corporation and heuristic rules. This expert system is developed using PROLOG language. Also, user friendly Graphic User Interface is developed using visual basic programming in the windows XP environment. The proposed expert system showed a promising performance through the several case studies.

• 인터넷정보학회논문지
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• 제7권3호
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• pp.119-132
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• 2006

지금까지 잘 알려진 네트워크 기반 보안 기법들은 공격에 수동적이고 우회한 공격이 가능하다는 취약점을 가지고 있어 인라인(in_line) 모드의 공격에 능동적 대응이 가능한 오용탐지 기반의 침입방지시스템의 출현이 불가피하다. 하지만 오용탐지 기반의 침입방지시스템은 탐지 규칙에 비례하여 과도한 오경보(False Alarm)를 발생시켜 정상적인 네트워크 흐름을 방해하는 잘못된 대응으로 이어질 수 있어 기존 침입탐지시스템보다 더 위험한 문제점을 갖고 있으며, 새로운 변형 공격에 대한 탐지가 미흡하다는 단점이 있다. 본 논문에서는 이러한 문제를 보완하기 위해 오용탐지 기반의 침입방지시스템과 Anomaly System 중의 하나인 서포트 벡터 머신(Support Vector Machines; 이하 SVM)을 이용한 침입방지시스템 기술을 제안한다. 침입 방지시스템의 탐지 패턴을 SVM을 이용하여 진성경보만을 처리하는 기법으로 실험결과 기존 침입방지시스템과 비교하여, 약 20% 개선된 성능결과를 보였으며, 제안한 침입방지시스템 기법을 통하여 오탐지를 최소화하고 새로운 변종 공격에 대해서도 효과적으로 탐지 가능함을 보였다.

• 한국군사과학기술학회지
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• 제13권1호
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• pp.9-21
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• 2010

In this paper, optimum design of distributed detection is considered for a parallel sensor network system consisting of a fusion center and multiple passive sonar nodes. Nonrandom fusion rules are employed as the fusion rules of the sensor network. For the nonrandom fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is investigated that maximizes the probability of detection under a constraint on energy consumption due to false alarms. It is also investigated through numerical experiments how signal strength, false alarm probability, and the distance between three sensor nodes affect the system detection performances.

• 한국압력기기공학회 논문집
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• 제19권1호
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• pp.44-51
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• 2023

The RCP is one of the main components in nuclear power plants and plays an important role in circulating coolant to the RCS system. Currently, nuclear plants are monitored using various monitoring systems. However, since they operate independently according to their functional purpose, it is not able to analyze vibration and operation/performance information comprehensively, and thus failure diagnosis accuracy is limited. In addition, these systems do not provide some important information (such as fault type, parts and cause) necessary for emergency actions, but provide only alarm information. To improve these technical problems, this study proposes a diagnosis technique (M/L, Rule-based model, Data-driven model, Narrow band model) and methodology for comprehensive analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권12호
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• pp.3061-3080
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• 2012

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.

• 한국통신학회논문지
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• 제39A권1호
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• pp.19-27
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• 2014

최근 주파수 자원의 중요성이 부각됨에 따라 이미 할당된 주파수 대역을 재사용하여 주파수 이용 효율을 향상시키는 인지 무선 기술(Cognitive Radio, CR)에 대한 연구가 활발히 이루어지고 있다. CR은 주파수 대역의 사용현황에 따라 기회적으로 사용자가 주파수 대역을 이용하므로 이를 위한 정보를 얻는 센싱 단계가 성능에 중요한 영향을 미친다. 따라서 센싱 성능을 향상시키는 것은 CR에서의 중요 이슈가 되며 이를 위해 다수의 단말이 협력하여 1차 사용자의 스펙트럼 점유 여부를 검출하는 협력 스펙트럼 센싱이 고려되고 있다. 본 논문에서는 협력 스펙트럼 센싱 환경에서 각 사용자의 센싱 정보가 융합 센터(Fusion Center, FC)로 보고되는 채널의 오류 확률을 고려하는 OR 규칙 기반의 협력 스펙트럼 센싱 기법을 제안한다. 제안 기법은 보고 오류 확률을 통해 협력 센싱에 참여하는 사용자 수를 제한함으로써 기존 기법에서 나타나는 오경보 확률의 제한을 완화시킨다.

• 대한인간공학회지
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• 제32권1호
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• pp.9-16
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• 2013

Objective: The aim of this study is to investigate a trend of human error types observed in a series of verification and validation experiments for an Advanced Control Room(ACR) equipped with Lager Display Panel(LDP), Work Station Flat Panel Display(WS FPD), list type Alarm System(AS), Soft Control(SC) and Computerized Procedure System(CPS). Background: Operator behaviors in a fully computerized control room are quite different from those in a traditional hard-wired control room. Operators in an ACR all together monitor plant status and variables through their own interface system such as LDP and WS FPD, are notified of abnormal plant status through their own list type AS, control the plant through their own SC, and follow the structured procedure through their own CPS whereas operators in a traditional control room only separately do their duty directed by their supervisor. Especially the secondary task such as manipulating the user interface of ACR can be an extra burden to all the operators including the supervisor. Method: The Reason's human error classification method was applied to operators' behavioral data collected from a series of verification and validation experiments where operators showed their plant operational behaviors under a couple of harsh scenarios using the ACR simulator. Results: As operators accustomed to the new ACR system, knowledge or rule based mistakes appearing frequently in the early series of experiments decreased drastically in the latest stage of the series. Slip and lapse types of errors were observed throughout the series of experiments. Conclusion: Education and training can be one of the most important factors for the operators accustomed to the traditional control room to be adapted to the new system and to run the ACR successfully. Application: The results of this study implied that knowledge or rule based mistakes can be reduced by training and education but that lapse type errors might be reduced only through innovative improvement in human-system interface design or teamwork culture design including a new leadership style suitable for ACR.