• Title/Summary/Keyword: fault rate

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Fault Current Limitation Characteristics of the Bi-2212 Bulk Coil for Distribution-class Superconducting Fault Current Limiters (배전급 초전도 한류기 개발을 위한 Bi-2212 초전도 한류소자의 사고전류 제한 특성)

  • Sim, Jung-Wook;Lee, Hai-Gun;Yim, Sung-Woo;Kim, Hye-Rim;Hyun, Ok-Bae;Park, Kwon-Bae;Lee, Bang-Wook;Oh, Il-Sung;Kim, Ho-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.2
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    • pp.277-281
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    • 2007
  • We investigated fault current limitation characteristics of the resistive superconducting fault current limiter (SFCL) which consisted of a Bi-2212 bulk coil and a shunt coil. The Bi-2212 bulk coil and the shunt coil were connected in parallel. The Bi-2212 bulk coil was placed inside the shunt coil to induce field-assisted quench. The fault test was conducted at an input voltage of $200V_{rms}$ and fault current of $12kA_{rms}\;and\;25kA_{rms}$. The fault conditions were asymmetric and symmetric, and the fault period was 5 cycles. The test results show that the SFCL successfully limited the fault current of $12kA_{rms}\;and\;25kA_{rms}$ to below $5.5{\sim}6.9kA_{peak}\;within\;0.64{\sim}2.17$ msec after the fault occurred. Limitation was faster under symmetric fault test condition due to the larger change rate of current. We concluded that the speed of fault current limitation was determined by the speed of current rise rather than the amplitude of a short circuit current. These results show that the Bi-2212 bulk coil is suitable for distribution-class SFCLS.

The Active Fault Topography of the Northern Partof the Bulguksa Fault System in Kyungju City, Southeastern Korea (한국 남동부 청주시 불국사단층선 북부의 활단층지형)

  • 윤순옥;황상일
    • Journal of the Korean Geographical Society
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    • v.34 no.3
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    • pp.231-246
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    • 1999
  • The geomorphic deformation of the alluvial fans by tectonic movement was investigated along the lineaments of the northern part of the Bulguksa fault system. Based on the aerial photographs interpretation and field surveys Bulguksa fault system was identified as an active reverse fault which has displaced the Quaternary fan deposits. Bulguksa fault system strikes for the direction of NW-SE and N-S. These two lineaments of active fault are crossing at Jinty village in Kyungju city and the fault plane forms here almost vertical dip. Thelateral pressures from the two directions have possibly influenced on the formation of the vertical dip at Jinty village. It should be resulted from that the two pressures responsible for the active reverse fault at which the one with the NW-SE strike thrusts the hanging wall of Tohamsan block southwestward and the other pressure with the N-S jstrike thrusts it westwrd over the foot wall of the fan deposits. The marine oxygen isotope stage 8(0.30-0.25 Ma. BP) and stage 6(0.20-0.14 Ma. BP) are presumed to be the ages of high and middle surfaces of the alluvial fan, repectively. The vertical dispiacements on the high surface along the Bulguksa fault system are about 10.5m at Ha-dong, 9.5-10.5m at Jinhyun-dong, and about 10m at Jinty village. And the vertical displacement on the middle surface was measured about 6m high at Ha-dong. The average slip rate of vertical displacements is calculated about 0.03-0.043mm/y.

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Machine Learning Process for the Prediction of the IT Asset Fault Recovery (IT자산 장애처리의 사전 예측을 위한 기계학습 프로세스)

  • Moon, Young-Joon;Rhew, Sung-Yul;Choi, Il-Woo
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.4
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    • pp.281-290
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    • 2013
  • The IT asset is a core part that supports the management objective of an organization, and the fast settlement of the IT asset fault is very important. In this study, a fault recovery prediction technique is proposed, which uses the existing fault data to address the IT asset fault. The proposed fault recovery prediction technique is as follows. First, the existing fault recovery data were pre-processed and classified by fault recovery type; second, a rule was established for the keyword mapping of the classified fault recovery types and reported data; and third, a machine learning process that allows the prediction of the fault recovery method based on the established rule was presented. To verify the effectiveness of the proposed machine learning process, company A's 33,000 computer fault data for the duration of six months were tested. The hit rate for fault recovery prediction was approximately 72%, and it increased to 81% via continuous machine learning.

The Designs for Prediction of Future Reliability Using the Stochastic Reliabilit

  • Oh, Chung-Hwan;Kim, Bok-Mahn
    • Journal of Korean Society for Quality Management
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    • v.21 no.2
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    • pp.131-139
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    • 1993
  • The newly proposed model of the future reliability results in earlier fault-fixes having a greater effect than the fault which make the greatest contribution to the overall failure rate tend to show themselves earlier, and so are fixed earlier. The suggested model allows a variety of reliability measures to be calculated. Predictions of total execution time(debugging time) is to achieve a target reliability. This model could also apply to computer-hardware reliability growth resulting from the elimination of design error and fault.

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Analysis of Switching Overvoltage on Operating Reclosing in Combined Transmission Systems (혼합송전계통에서 재폐로 시행시 개폐과전압 해석)

  • Lim, Kwang-Sik;Lee, Jong-Boem;Jung, Chae-Kyun;Kang, Ji-Won;Park, Hung-Sok
    • Proceedings of the KIEE Conference
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    • 2008.11a
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    • pp.391-393
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    • 2008
  • This paper is analysed by switching overvoltage on operating reclosing in 154 [kV] combined transmission systems. Combined transmission systems are modeled by EMTP/ATPDraw program. It is fault condition that simulate high resistance earth fault. The simulation is carried out considering variation of parameters such as resistance value of fault point and rate of underground line.

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An Efficient Fault-diagnosis of Digital Circuits Using Multilayer Neural Networks (다층신경망을 이용한 디지털회로의 효율적인 결함진단)

  • 조용현;박용수
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.1033-1036
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    • 1999
  • This paper proposes an efficient fault diagnosis for digital circuits using multilayer neural networks. The efficient learning algorithm is also proposed for the multilayer neural network, which is combined the steepest descent for high-speed optimization and the dynamic tunneling for global optimization. The fault-diagnosis system using the multilayer neural network of the proposed algorithm has been applied to the parity generator circuit. The simulation results shows that the proposed system is higher convergence speed and rate, in comparision with system using the backpropagation algorithm based on the gradient descent.

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Study on the Quantification of Failure Rate for Safety-critical Fault-tolerant USN System (안전필수 결함허용 USN시스템의 고장률정량화에 관한 연구)

  • Shin, Duc-Ko;Shin, Kyung-Ho;Jo, Hyun-Jeong;Song, Yong-Soo
    • Proceedings of the KSR Conference
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    • 2011.05a
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    • pp.1414-1419
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    • 2011
  • In this paper we study the modeling to quantitatively assess the failure rate of USN system designed for fault-tolerant architecture, aiming at applying the world's best domestic USN technology to safety-critical railways. In order to apply the USN system to the safety-critical field like a train control sector that the failures of controllers may cause severe railway accidents such as train collision and derailment, the quantitative reliability and safety evaluation recommended in IEC 62278 must be preceded. We also develop the evaluation model for overall system failure rate for the distributed network structure, which is the characteristics of USN system. Especially, we allocate reliability targets to component units, and present an availability evaluation plan through the plan on the quantitative achievement of failure rate for sensor nodes, gateways, radio-communication network and servers, along with the failure rate model of the overall system considering network operational features.

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Simulation and Evaluation of Redistribution Algorithms In Fault-Tolerant Distributed System (결함허용 분산시스템의 재분배 알고리즘의 시뮬레이션과 평가)

  • 최병갑;이천희
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.8
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    • pp.1-10
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    • 1994
  • In this paper load redistribution algorithm to allow fault-tolerance by redistributing the workload of n failure nodes to the remaining good nodes in distributed systems are investigated. To evaluate the efficiency of the algorithms a simulation model of algorithms is developed using SLAM II simulation language. The job arrival rate service rate failure and repair rate of nodes and communication delay time due to load migraion are used as parameters. The result of the simulation shows that the job arrival rate failure and repair rate of nodes do not affected on the relative efficiency of algorithms. If the communication delay time is greater than average job processing time algorithm B is better. Otherwise algorithm C is superior to the others.

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Practical Swarm Optimization based Fault-Tolerance Algorithm for the Internet of Things

  • Luo, Shiliang;Cheng, Lianglun;Ren, Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.3
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    • pp.735-748
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    • 2014
  • The fault-tolerance routing problem is one of the most important issues in the application of the Internet of Things, and has been attracting growing research interests. In order to maintain the communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which alternate paths are created once the previous routing is broken. Then, we propose an improved efficient and intelligent fault-tolerance algorithm (IEIFTA) to provide the fast routing recovery and reconstruct the network topology for path failure in the Internet of Things. In the IEIFTA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by the immune mechanism, which can improve the ability of global search and improve the converging rate of the algorithm. The simulation results indicate that the IEIFTA-based fault-tolerance algorithm outperforms the EARQ algorithm and the SPSOA algorithm due to its ability of fast routing recovery mechanism and prolonging the lifetime of the Internet of Things.

Fast Diagnosis Method for Submodule Failures in MMCs Based on Improved Incremental Predictive Model of Arm Current

  • Xu, Kunshan;Xie, Shaojun
    • Journal of Power Electronics
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    • v.18 no.5
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    • pp.1608-1617
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    • 2018
  • The rapid and correct isolation of faulty submodules (SMs) is of great importance for improving the reliability of modular multilevel converters (MMCs). Therefore, a fast diagnosis method containing fault detection and fault location determination was presented in this paper. An improved incremental predictive model of arm current was proposed to detect failures, and the multi-step prediction method was used to eliminate the negative impact of disturbances. Moreover, a control method was proposed to strengthen the fault characteristics to rapidly locate faulty arms and faulty SMs by detecting the variation rate of the SM capacitor voltage. The proposed method can rapidly and easily locate faulty SMs under different load conditions without the need for additional sensors. The experimental results have validated the effectiveness of the proposed method by using a single-phase MMC with four SMs per arm.