• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1727-1731
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• 2003

In this paper we proposed backward fuzzy Petri-net to diagnoses faults in power systems by using the time sequence information of protection system. As the complexity of power systems increases, especially in the case of multiple faults or incorrect operation of protective devices, fault diagnosis requires new and systematic methods to the reasoning process, which improves both its accuracy and its efficiency. The fuzzy Petri-net models of protection system are composed of the operating process of protective devices and the fault diagnosis process. Fault diagnosis model, which makes use of the nature of fuzzy Petri-net, is developed to overcome the drawbacks of methods that depend on operator knowledge. The proposed method can reduce processing time and increase accuracy when compared with the traditional methods. And also this method covers online processing of real-time data from SCADA (Supervisory Control and Data Acquisition)

• 한국통신학회논문지
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• 제31권8B호
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• pp.701-706
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• 2006

System-level diagnosis plays an important technique for fault detection in multi-processor systems. Efficient diagnosis is very important for real time systems as well as multiprocessor systems. Feng(1) proposed two adaptive diagnosis algorithms HADA and IHADA for hypercube system. The diagnosis cost, measured by diagnosis time and the number of test links, depends on the number and location of the faults. In this paper, we propose an adaptive diagnosis algorithm using the syndrome analysis. This removes unnecessary overhead generated in HADA and IHADA algorithm sand give a better performance compared to Feng's Method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 춘계학술대회 논문집 전기설비전문위원
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• pp.4-6
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• 2005

This paper deals with the technical map of diagnosis for power cable systems. For this purpose, failure status, failure and degradation causes, and newly suggested diagnostic techniques were investigated and analyzed. From the analysis, the technical map of diagnosis for power cable systems was proposed.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(1)
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• pp.340-345
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• 1996

Because of limited resources of time and information processing capability during abnormal situation, diagnosis is difficult tasks in nuclear power plant (NPP) operators. Moreover since minimizing of adverse consequences according to process abnormalities is vital for the safety of NPP, introducing of diagnosis support systems have particularly emphasized. However, considerable works to develop effective diagnostic support system are not sufficiently fulfilled because of the complexity of NPP is one of the major problems. To cope with this complexity, a lot of model-based diagnosis support systems have considered and implemented worldwide. In this paper, as a prior step to development of model-based diagnosis support systems, primary side of pressurized water reactor is functionally modeled by multilevel flow modeling (MFM) concept. MFM is suitable for complex system modeling and for diagnosis of abnormalities. Furthermore, knowledge-based diagnosis process, of NPP operator could be supported because this diagnosis strategy can represent operator's one.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.597-600
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• 2002

This paper has been studied expert system using fuzzy theory for fault diagnosis of HDD test systems by detecting systems fault and presenting the way of repair using test history and rule base built via interview from exports. The rules of fault diagnosis of HDD test systems are classified into 2 types, fuzzy and crisp, and these have been serialized to decide whether fault diagnosis be done or not by fuzzy rules and to present the way of repair by crisp rules. And then this paper has designed expert system using fuzzy theory for fault diagnosis.

• 한국시스템다이내믹스연구
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• 제17권3호
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• pp.145-173
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• 2016

This study aims to develop strategic diagnosis framework of performance by identifying and analysing the dynamics of the technology commercialization ecosystem in innovative region. To achieve the purpose of this study, the systems thinking approach is used. The systems thinking approach connects feedback structure and behavior more explicitly to diagnosis vicious feedback loop in the regional technology commercialization ecosystem. In terms of an ecological point of view, it will be possible to explore dominant feedback structure and find leverages to overcome the limitations of regional technology commercialization performance. The diagnosis of reenforcing and balancing feedback structure is based on the statistical analysis of the survey data which has been collected in a cluster random sampling method, targeting on the 200 firm located in the Pangyo and Daeduk region. The results from this research showed that the regional technology commercialization ecosystem was immature and faced limit to the growth. An important finding of this study was that regional technology commercialization ecosystem need to activation of startups and reinforcement of virtuous feedback structures of technology commercialization market systems.

• Clinical Endoscopy
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• 제57권3호
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• pp.283-292
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• 2024

We developed three e-learning systems for endoscopists to acquire the necessary skills to improve the diagnosis of early gastric cancer (EGC) and demonstrated their usefulness using randomized controlled trials. The subjects of the three e-learning systems were "detection", "characterization", and "preoperative assessment". The contents of each e-learning system included "technique", "knowledge", and "obtaining experience". All e-learning systems proved useful for endoscopists to learn how to diagnose EGC. Lecture videos describing "the technique" and "the knowledge" can be beneficial. In addition, repeating 100 self-study cases allows learners to gain "experience" and improve their diagnostic skills further. Web-based e-learning systems have more advantages than other teaching methods because the number of participants is unlimited. Histopathological diagnosis is the gold standard for the diagnosis of gastric cancer. Therefore, we developed a comprehensive diagnostic algorithm to standardize the histopathological diagnosis of gastric cancer. Once we have successfully shown that this algorithm is helpful for the accurate histopathological diagnosis of cancer, we will complete a series of e-learning systems designed to assess EGC accurately.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 춘계학술대회 논문집 전기설비전문위원
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• pp.10-12
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• 2005

This paper describes MV switchgear technology trends and diagnosis technology. MV switchgear has been rapidly changed into compact, reliability and safety situation. And suggested road-map to implement condition assessment or condition based maintenance. On-line diagnosis technology, life evaluation technology and system technology are suggested.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.116.1-116
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• 2001

In the near future, drive-by-wire systems will replace mechanical systems of vehicles. Since there would be no mechanical redundancy in the x-by-wire subsystem, it needs to improve the reliability of the system using fault diagnosis of sensors and actuators. This paper proposes a Kalman filter based fault diagnosis method for the vehicle with the drive-by-wire system, which includes steer-by-wire, brake-by-wire and throttle-by-wire systems. We will show that the proposed method is successful in fault detection and isolation for single sensor/actuator faults of the vehicle system.

• 지능정보연구
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• 제4권1호
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• pp.115-131
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• 1998

Customer service process is one of the most important processes in today's competitive business environment. Among the various activities of customer service process, equipment malfunction diagnosis activity should be performed fast and accurately. When a customer calls the service center and reports the observed symptoms, he/she describes them in layman's terms. Therefore, the customer-reported symptoms have not been considered helpful information for service representatives. However, in order to perform diagnosis activity fast and accurately, we need to make use of the customer-reported symptoms actively. In this research, we developed three systems called R-EMD (Rule-based Equipment Malfunction Diagnostic system), C-EMD (Case-based Equipment Malfunction Diagnostic system) and R&C-EMD (Rule & Case-based Equipment Malfunction Diagnostic system), each of which diagnoses equipment malfunctions using the customer-reported symptoms. R&C-EMD is a hybrid system that utilizes both rule-based and case-based technologies. The diagnosis rules used in R&C-EMD and R-EMD were not acquired from service manuals or interviews with service representatives. Rater, we extracted them directly from the past diagnosis cases based on symptoms' frequencies. By this way, we were able to overcome the knowledge acquisition bottleneck. Using the real 100 malfunction diagnosis cases, we evaluated the performances of R&C-EMC, R-EMD and C-EMD in terms of speed and accuracy. In diagnosis time, R&C-EMD took longer than R-EMD and shorter than C-EMD. However, R&C-EMC was the best in accuracy.