• 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 the Korean Society for Aeronautical & Space Sciences
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• v.37 no.6
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• pp.556-561
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• 2009

The UAV(Unmanned Aerial Vehicle) that is remotely operating in various and long flight environments must have a very reliable propulsion system. Precise fault diagnosis of the turbo shaft engine for the Smart UAV that has the vertical take-off, landing and forward flight behaviors can promote reliability and availability. This work proposes a new diagnostic method that can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. The proposed diagnostic method can detect not only single fault but also multiple faults.

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.467-482
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• 2022

The Yeonghae basin is located at the northeastern part of the Yangsan fault (YSF; a potentially active fault). The study of the architecture of the Yeonghae basin is important to understand the activity of the Yangsan fault system (YSFS) as well as the basin formation mechanism and the activity of the YSFS. For this study, Digital Elevation Model (DEM) was used to highlight the marginal faults, and structural fieldwork was performed to understand the geometry of the intra-basinal structures and the nature of the bounding faults. DEM analysis reveals that the eastern margin is bounded by the northern extension of the YSF whereas the western margin is bounded by two curvilinear sub-parallel faults; Baekseokri fault (BSF) and Gakri fault (GF). The field data indicate that the YSF is striking in the N-S direction, steeply dipping to the east, and experienced both sinistral and dextral strike-slip movements. Both the BSF and GF are characterized dominantly by an oblique right-lateral strike-slip movement. The stress indicators show that the maximum horizontal compressional stress was in NNE to NE and NNW-SSE, which is consistent with right-lateral and left-lateral movements of the YSFS, respectively. The plotted structural data show that the NE-SW is the predominant direction of the structural elements. This indicates that the basin and marginal faults are mainly controlled by the right-lateral strike-slip movements of the YSFS. Based on the structural architecture of the Yeonghae basin, the study area represents a contractional zone rather than an extensional zone in the present time. We proposed two models to explain the opening and developing mechanism of the Yeonghae basin. The first model is that the basin developed as an extensional pull-apart basin during the left-lateral movement of the YSF, which has been reactivated by tectonic inversion. In the second model, the basin was developed as an extensional zone at a dilational quadrant of an old tip zone of the northern segment of the YSF during the right-lateral movement stage. Later on, the basin has undergone a shortening stage due to the closing of the East Sea. The second model is supported by the major trend of the collected structural data, indicating predominant right-lateral movement. This study enables us to classify the Yeonghae basin as an inverted strike-slip basin. Moreover, two opposite strike-slip movement senses along the eastern marginal fault indicate multiple deformation stages along the Yangsan fault system developed along the eastern margin of the Korean peninsula.

• Journal of Electrical Engineering and information Science
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• v.3 no.1
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• pp.8-13
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• 1998

Often ESOP(Exclusive Sum of Products) expressions provide more compact representations of logic functions and implemented circuits are known to be highly testable. Motivated by the merits of using XOR(Exclusive-OR) gates in circuit design, ESOP(Exclusive Sum of Products) expressions are considered s the input to the logic synthesis for random pattern testability. The problem of interest in this paper is whether ESOP expressions provide better random testability than corresponding SOP expressions of the given function. Since XOR gates are used to collect product terms of ESOP expression, fault propagation is not affected by any other product terms in the ESOP expression. Therefore the test set for a fault in ESOP expressions becomes larger than that of SOP expressions, thereby providing better random testability. Experimental results show that in many cases, ESOP expressions require much less random patterns compared to SOP expressions.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05c
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• pp.161-163
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• 2001

We present the basic properties of a superconducting current limiting fuse (SCLF) based on YBCO/Au films. The SCLFs consists of YBCO stripes covered with Au layers for current shunt. Under the source voltage of 100 $V_{rms}$, the longer the duration time of fault current was, the shorter its discharge time was. The duration time of fault current and its discharge time were reduced by increased voltages in the range of 200 - 300 $V_{rms}$. We thought that this was because the quench propagation was limited by local melting generated with higher voltage.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.819-821
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• 1998

This paper deals with a method or a residual generation for fault isolation in a centrifugal pump with a water circulation system, driven by a speed controlled dc motor. It is based on parity relations derived from the moving-average model of the system and is used to identify sensor faults and two possible brush and impeller faults, where the former is dealt with additive faults, while the latter characterized as discrepancies between the nominal and actual plant parameters of the system is modelled by multiplicative faults. We will represent the propagation of this uncertainty to the model matrices by the approximate handling of partial derivatives of polynomials. With multiplicative faults, the transformation matrix implemented in the residual generator are calculated on-line. The simulation studies demonstrate that small changes of the system can be detected and diagnosed by using the method.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.485-487
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• 1997

Schemes for detecting and diagnosing faults are presented. Faults are detected when residuals change significantly and thresholds are exceed. Two stage artificial neural networks are applied to diagnose faults. The idealized steady state patterns of residuals are defined and learned by ANNs using back propagation algorithm. The first stage ANN is trained to classify the subsystem in which the various faults are located. The first stage ANN could be also used to detect faults with threshold, checking. The second stage ANNs are trained to discriminate the specific cause of a fault at the subsystem level.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.121-126
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• 2002

We proposed the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gains of input-output variables of fuzzy logic controller(FLC) and weights of neural network using Tabu search. Neural network was used for adaptively tuning the output gain of FLC. The weights of neural network was learned from the back propagation algorithm in real-time. To evaluate the usefulness of AFLC, we applied the proposed method to single-machine infinite system. AFLC showed the better control performance than PD controller and GAFLC[8] for. three-phase fault in nominal load which had used when tuning AFLC. To show the robustness of AFLC, we applied the proposed method to disturbances such as three-phase fault in heavy and light load. AFLC showed the better robustness than PD controller and GAFLC[8].

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.689-696
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• 2003

Criticality prediction models that determine whether a design entity is fault-prone or non fault-prone are used for identifying trouble spots of software system in analysis or design phases. Many criticality prediction models for identifying fault-prone modules using complexity metrics have been suggested. But most of them need training data set. Unfortunately very few organizations have their own training data. To solve this problem, this paper builds a new prediction model, KSM, based on Kohonen SOM neural networks. KSM is implemented and compared with a well-known prediction model, BackPropagation neural network Model (BPM), considering internal characteristics, utilization cost and accuracy of prediction. As a result, this paper shows that KSM has comparative performance with BPM.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.2
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• pp.1-7
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• 2011

The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.