• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.241-248
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• 2011

In this paper we proposed and implemented a diagnosis system to control nuclear fuel handling machine. The proposed system consists of data acquisition system, diagnosis algorithm and faults simulator. Since the test on real operation of the fuel handling machine is impossible, we evaluated the proposed system by diagnosis experiments using the faults simulator, with which test signals on abnormal states of the bearing ball and the inner race of the bearing are generated. The experiments showed that resulting diagnosis analysis are consistent with the theoretical expectations.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1380-1381
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• 2008

By applying the digital sub-station, the change of various protect and measuring equipments has been applying. This paper is analyzed that the development of GIS partial discharge condition monitoring equipment is suited to the electricity IT technology and digital sub-station. It's constitution apply to be able to suit the data to high rank for GIS partial discharge condition monitoring equipment that is suited digital sub-station and Watch-dog module that be able to monitor the inner communication of the GIS partial discharge equipment. And then it also be able to apply of GIS partial discharge equipment when digital sub-station is applied.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.182-194
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• 2012

To develop a liquid rocket engine with high reliability and safety under constraints of limited time and budget an optimal diagnosis system for the engine needs to be developed in parallel with the development of the engine. This paper is intended to set a development direction of the diagnosis system for the liquid rocket engine through the literature survey and addresses possible engine defects, characteristics of parameters for diagnosis and diagnostic methods including real-time diagnosis, post-test/post-flight diagnosis, fault detection method, parameter circuit method and test diagnosis. In addition tasks to be performed in the design and operation phases of the engine and foreign application case of engine diagnosis are presented.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.814-826
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• 2023

Sensor faults in nuclear power plant instrumentation have the potential to spread negative effects from wrong signals that can cause an accident misdiagnosis by plant operators. To detect sensor faults and make accurate accident diagnoses, prior studies have developed a supervised learning-based sensor fault detection model and an accident diagnosis model with faulty sensor isolation. Even though the developed neural network models demonstrated satisfactory performance, their diagnosis performance should be reevaluated considering real-time connection. When operating in real-time, the diagnosis model is expected to indiscriminately accept fault data before receiving delayed fault information transferred from the previous fault detection model. The uncertainty of neural networks can also have a significant impact following the sensor fault features. In the present work, a pilot study was conducted to connect two models and observe actual outcomes from a real-time application with an integrated system. While the initial results showed an overall successful diagnosis, some issues were observed. To recover the diagnosis performance degradations, additive logics were applied to minimize the diagnosis failures that were not observed in the previous validations of the separate models. The results of a case study were then analyzed in terms of the real-time diagnosis outputs that plant operators would actually face in an emergency situation.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.625-628
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• 2003

This paper proposes a fuzzy expert system for the fault diagnosis of Hard Disk Drive(HDD) test systems. The purposes of this system are diagnosis of HDD test systems, detection of system faults using test history, and presentation of the way of repair. Proposed Expert system is designed with Fuzzy logic and Binary Logic to present the way of repair using HDD tort result, HDD test history. The proposed system is simulated with actual data from SAMSUNG HDD product line in KUMI, KOREA, and show effective results.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.243-247
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• 1999

An electrolytic capacitor is widely used in a motor drive system. Therefore, the deterioration diagnosis of an electrolytic capacitor is needed of preventive maintenance of the system. In this paper, we propose a new diagnosis method for the electrolytic capacitor by using the system identification method, which presents the information about the capacitor's interna parameters in on-line operation an use fuzzy algorithm for the deterioration decision. We demonstrated the effectiveness of the proposed control scheme by using computer simulation.

• Journal of Korean Medical classics
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• v.33 no.4
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• pp.83-105
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• 2020

Objectives : This paper aims to examine the system, principle, and fundamentals of the great principle of pulse diagnosis in the 『Nanjing』. Methods : The system, principle, and fundamentals of pulse diagnosis in the 『Nanjing』 were examined within the book's description framework and logical structure in light of its relationship to the 『Huangdineijing』. Previous studies that follow pulse diagnosis of 『Nanjing』 and 『Wangshuhe Maijue』 were referenced. Results & Conclusions : The structure of pulse diagnosis in the 『Nanjing』 is systematically organized under the principle of the three positions and nine indicators as the great principle to which the yinyang and five viscera pulse theories are included. The great principle of the three positions and nine indicators is consisted of a system that allows for a multiple and comprehensive interpretation wherein the theories of yinyang and five elements are interweaved within the pulse diagnosis system, which is comprised of a great principle and particular principles. The theory follows that of the three yin three yang theory of the five circuits and six qi, its principles manifesting as the three positions and nine indicators and integration of pulse and symptoms.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.9
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• pp.814-822
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• 2013

For the fault diagnosis of a mechanical system, pattern recognition methods have being used frequently in recent research. Hidden Markov model(HMM) and artificial neural network(ANN) are typical examples of pattern recognition methods employed for the fault diagnosis of a mechanical system. In this paper, a hybrid method that combines HMM and ANN for the fault diagnosis of a mechanical system is introduced. A rotating blade which is used for a wind turbine is employed for the fault diagnosis. Using the HMM/ANN hybrid model along with the numerical model of the rotating blade, the location and depth of a crack as well as its presence are identified. Also the effect of signal to noise ratio, crack location and crack size on the success rate of the identification is investigated.

• Journal of Power System Engineering
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• v.19 no.5
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• pp.67-72
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• 2015

The reliable operation of onsite emergency diesel generator(EDG) should be ensured by a conditioning monitoring system designed to maintain, monitor and forecast the reliability level of diesel generator. The purpose of this paper is to develop condition diagnosis algorithm(logic) and analysis program of engine for the accurate diagnosis in actual condition of emergency diesel generator engine. As a result of this study, we confirmed that developed engine condition diagnosis algorithm and analysis program could be efficiently applied for actual EDG engine in nuclear power plant.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.124-131
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• 2001

Fault diagnosis of an assembled small motor relies usually on human experts hearing ability. The quality of diagnosis depends, however, heavily on physical conditions of the human experts. A fault diagnosis system for assembled small motors is developed using artificial neural network (ANN) in this paper. It is consisted of sound sampling device and fault diagnosis software package. Six parameters are defined to characterize the sampled sound waves. The Levenberg-Marquardt Backpropagation (LMBP) Algorithm is used to diagnose the fault of assembled small motors. Experimental results for more than two hundred small motors verify the performance of the developed system.