• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.725-730
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• 1996

In this work, the software behavior under memory faults in operation phase is modeled and simulated using the stochastic activity network, generalized stochastic Petri nets. This networks permit the representation of concurrency, timeliness, fault tolerance, and degradable performance of system and provide a means for determining the stochastic behavior of a complex system. We estimate the reliability of an application software in the digitized system in nuclear power plants and show the sensitivity of the software reliability to the major physical parameters which affect the software failure in normal operation phase. We found that the effects of the hardware faults on the software failure should be considered for predicting the software dependability accurately in operation phase.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2222-2224
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• 2002

Induction motors are critical components of many industrial machines and are frequently integrated in commercial equipment. The heavy economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motors supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the artificial neural network, and the diagnosis system is programmed by using LabVIEW and MATLAB.

• ETRI Journal
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• v.30 no.4
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• pp.546-554
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• 2008

Phase-locked loops (PLLs) are among the most important mixed-signal building blocks of modern communication and control circuits, where they are used for frequency and phase synchronization, modulation, and demodulation as well as frequency synthesis. The growing popularity of PLLs has increased the need to test these devices during prototyping and production. The problem of distinguishing and classifying the responses of analog integrated circuits containing catastrophic faults has aroused recent interest. This is because most analog and mixed signal circuits are tested by their functionality, which is both time consuming and expensive. The problem is made more difficult when parametric variations are taken into account. Hence, statistical methods and techniques can be employed to automate fault classification. As a possible solution, we use the back propagation neural network (BPNN) to classify the faults in the designed charge-pump PLL. In order to classify the faults, the BPNN was trained with various training algorithms and their performance for the test structure was analyzed. The proposed method of fault classification gave fault coverage of 99.58%.

• ETRI Journal
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• v.31 no.2
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• pp.209-214
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• 2009

In this paper, we propose a novel test methodology for the detection of catastrophic and parametric faults present in analog very large scale integration circuits. An automatic test pattern generation algorithm is proposed to generate piece-wise linear (PWL) stimulus using wavelets and a genetic algorithm. The PWL stimulus generated by the test algorithm is used as a test stimulus to the circuit under test. Faults are injected to the circuit under test and the wavelet coefficients obtained from the output response of the circuit. These coefficients are used to train the neural network for fault detection. The proposed method is validated with two IEEE benchmark circuits, namely, an operational amplifier and a state variable filter. This method gives 100% fault coverage for both catastrophic and parametric faults in these circuits.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2175-2177
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• 2001

This paper presents a faults diagnosis technique of induction motors based on a neural network. Only stator current is measured, transformed by using FFT and normalized for the training. Healthy, bearing fault, stator fault and rotor end-ring fault motors are prepared to obtain the learning data and diagnose the several faults. For more effective diagnosis, the load rate is changed by 100%, 60%, 30% of full load and the obtained are applied to the learning process. The experimental results show the proposed method is very detectable and applicable to the real diagnosis system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.459-462
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating. so it is well hon that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• Nuclear Engineering and Technology
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• v.33 no.1
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• pp.1-11
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• 2001

In contrast with conventional fieldbus researches which are focused merely on real-time performance, this study aims to evaluate the real-time performance of the communication system including fault-tolerant mechanisms Maintaining performance in presence of recoverable faults is very important in case that the communication network is applied to a highly reliable system such as next generation Nuclear. Power. Plant (NPP). If the tie characteristics meet the requirements of the system, the faults will be recovered by fieldbus recovery mechanisms and the system will be safe. If the time characteristics can not meet the requirements, the faults in the fieldbus can propagate to the system failure. In this study, for the purpose of investigating the time characteristics of fieldbus, the recoverable faults are classified and then the formulas that represent delays including recovery mechanisms are developed. In order to validate the proposed approach, we have developed a simulation model that represents the Korea Next Generation Reactor (KNGR) NSSS Process Control System (NPCS). The results of the simulation show us the reasonable delay characteristics of the fault cases with recovery mechanisms. Using the simulation results and the system requirements, we also can calculate the failure propagation probability from fieldbus to outer system.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.264-272
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• 1998

This paper proposes a fault detection and recovery mechanism for a fault-tolerant Mini-MAP system, and provides detailed techniques for its implementation. This paper considers the fault-tolerant Mini-MAP system which has dual layer structure from the LLC sublayer down to the physical layer to cope with the faults of those layers. For a good fault detection, a redundant and hierarchical fault supervision architecture is proposed and its implementation technique for a stable detection operation is provided. Information for the fault location is provided from data reported with a fault detection and obtained by an additional network diagnosis. The faults are recovered by the stand-by sparing method applied for a dual network composed of two equivalent networks. A network switch mechanism is proposed to achieve a reliable and stable network function. A fault-tolerant Mini-MAP system is implemented by applying the proposed fault detection and recovery mechanism.

• The Journal of Korean Association of Computer Education
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• v.3 no.2
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• pp.77-86
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• 2000

As the information technology is being rapidly developed, Korean government supplies various communication equipments to schools and therefore, it causes difficulties to cope with various faults from complicated school network communication equipments. These faults come from many reasons for wasting school budget and decreasing effectiveness in school administration. From this, it is necessary to figure out the problems of school communication equipments and cope with these problems quickly and preventing those faults in advance. In this paper, we present the school communication equipments analysis methodology not only quantitative but also qualitative aspects. We are sure that applying this methodology may improve the effectiveness of school network equipments management.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.43-50
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• 2003

This presents a fault detecting method for a power transformer based upon a neural network. To maintain a normal relay operating conditions, external winding faults of a power transformer and magnetic inrush have been tested under consideration of the EMTP/ATP software and internal faults of power transformer have been tested by the EMTP/BCTRAN software. The neural network has been evaluated by the proposed fault. Input variables of the neural network for the proposed model can be obtained from fundamental currents, restraining and operating currents. This algorithm uses back-propagation and the ratio of a restraining current and an operating current as relay input parameters. The ratio may enhance the fault detection since the restraining currents increase rapidly at external faults. The proposed detecting method has been applied to the practical relay systems for transformer protection. As a result, the proposed detecting method based on the neural network has been shown to have better characteristics.