• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.7 s.361
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• pp.112-121
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• 2007

In this paper, we propose a new checkpointing strategy for dual modular redundancy real-time systems. For every checkpoints the execution results from two processors, and the result saved in the previous checkpoint are compared to detect faults. We devised an operation algorithm in chectpoints to recover from transient faults as well as permanent faults. We also develop a Markov model for the optimization of the proposed checkpointing strategy. The probability of successful task execution within its deadline is derived from the Markov model. The optimal number of checkpoints is the checkpoints which makes the successful probability maximum.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.595-596
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• 2016

열차의 진로를 변경시키는 선로전환기의 고장은 탈선 등과 같은 대형 사고를 유발시킬 수 있는 중요한 시설이다. 따라서 열차운행 안전 측면에서 해당 설비에 대한 모니터링은 필수적이다. 본 논문에서는 선로전환기의 구동 시 발생하는 소리 정보를 이용하여 선로전환기의 이상상황을 탐지하는 시스템을 제안한다. 먼저 제안한 시스템은 소리 센서에서 실시간으로 취득하는 소리 신호를 Power Spectral Density(PSD) 특징으로 변환한다. 추출된 PSD 특징은 이미 성능이 입증된 딥러닝의 대표적인 모델인 Convolutional Neural Network(CNN)에 적용하여 이상상황을 탐지한다. 실제 선로전환기의 전환 시 발생하는 소리 데이터를 취득하여 모의실험을 수행한 결과, 비정상 상황을 안정적으로 탐지함을 확인하였다.

• Journal of Aerospace System Engineering
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• v.13 no.2
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• pp.26-33
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• 2019

Control moment gyro (CMG) employed as satellite actuators, generates a large torque through the steering of its gimbals. Although each gimbal holds a high-speed rotating wheel, the wheel imbalances induces disturbance and degrades the satellite control quality. Therefore, the disturbances ought to be detected and identified as a precaution against actuator faults. Among the method used in detecting disturbances is the state observers. In this paper, we apply a continuous second order sliding mode observer to detect single disturbances/faults in CMGs. Verification of the algorithm is also done on the hardware satellite simulator where four CMGs are installed.

• The KIPS Transactions:PartA
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• v.16A no.4
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• pp.235-244
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• 2009

The mission-critical computer for air defense has to maintain its operation without any fault for a long mission time and is required to implement at low cost. Now the reliability of the mission critical-computer using Active Sparing Redundancy fault-tolerant technique is inferior to that of the computer using TMR technique. So in this paper are proposed Extended ASR(EASR) technique that provides higher reliability than that of the computer using TMR technique. The fault-tolerant performance of the implemented mission-critical computer is proven through reliability analysis and numbers of fault recovery test. Also, the reliability of the mission-critical computer using EASR technique is compared with those of computer using ASR and TMR techniques. EASR technique is very suitable to the mission-critical computer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.199-206
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• 2022

A malfunction or breakdown of a manufacturing facility leads to product defects and the suspension of production lines, resulting in huge financial losses for manufacturers. Due to the spread of smart factory services, a large amount of data is being collected in factories, and AI-based research is being conducted to predict and diagnose manufacturing facility breakdowns or manufacturing site efficiency. However, because of the characteristics of manufacturing data, such as a severe class imbalance about abnormalities and ambiguous label information that distinguishes abnormalities, developing classification or anomaly detection models is highly difficult. In this paper, we present an deep learning algorithm for anomaly detection of a manufacturing facility using reconstruction loss of CNN-based model and ananlyze its performance. The algorithm detects anomalies by relying solely on normal data from the facility's manufacturing data in the exclusion of abnormal data.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.426-430
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• 1987

The reliability is the critical issue in many computer applications, particularly in process control system. In this paper we describe how to achieve the reliability improvement in controller system based multiprocessor. The proposed method is accomplished by using the techniques of fault detection, fault isolation, safe action, and fault diagnosis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.449-455
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• 2015

Built-In-Test(hereafter: BIT) is necessary functionality for aircraft flight safety and it requires a high failure detection capacity of more than 95 % in the case of avionics equipment. The BIT coverage analysis is needed to make sure that BIT meets its fault diagnosis capability. FMECA is used a lot of for the BIT coverage analysis. However, in this paper, the BIT coverage analysis based on electronic components is introduced to minimize the analytical error. Further, by applying the failure mode of the electronic components and excluding electronic components that do not affect flight safety, the BIT coverage analysis can be more accurate. Finally, BIT demo was performed and it was confirmed that the performance of the actual BIT matches the analysis of BIT performance.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.37-46
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• 2008

Launch control system controls the sequence for launching missile in weapon systems. This system have to generate the engagement plan, input information and launch the missile in timeliness requirement. Such a system may fail to operate correctly either due to errors in hardware and software or due to violation of timing constraints. We presented fault-tolerant ethernet for embedded real-time system like launch control system. This approach is designed to handle network faults using dual commercial-off-the-shelf(COTS) network devices. To support fault-tolerant ethernet each node is composed dual channel ethernet and designed the communication middleware for network fault detect and recovery. Especially for time-critical system, the middleware is being developed to achieve that no point of network failure shall take down or cause loss of communication to network nodes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.167-169
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• 2018

2016 한국 전력 통계에 따르면 약 900 만개의 지지물과 130 만 킬로미터의 전력 분배용 전력선이 있으며 많은 인적 자원과 엄청난 양의 송전선에 대한 유지보수가 필요하다. 현재 전선 늘어짐에 대한 고장진단 기법 중 하나로 이동 중인 자동차에 부착된 비전 시스템을 이용한 방법이 있다. 이 방법에서 사용된 송전선 탐지 방법을 보완하여 송전선을 이미지상에서 추출한다. 본 논문에서는 인공지능을 사용하여 지지물 을 탐지하고, 지지물 사이의 거리가 멀다는 점을 극복하기 위하여 공통 특징점들이 있는 이미지들을 하나의 이미지로 붙이는 파노라마 기술을 사용하여 지지물 사이의 거리를 극복하며, 제안하는 방법으로 송전선을 탐지하고 늘어짐을 판단하는 시스템을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.1
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• pp.47-57
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• 1992

Subject of this work is the application of neural networks for the signal(motor noise)recognition systems which detects motor failures and employs different signal(noise). Charaoteristics that re-sult from damaghe part and measure of motor construction during working. The four layers neural networks is applied to this examination. And consists of one input layer, two hidden layers, and one output layer, and learns by the back propagation algorithm.The results of this examination show that it the construction and the output power of the testmotor and learning motor are compatible, the damaged part of the testmotor are detected correctly in the system on the other hand, if the motors have different constrcotion but similar output power each other, mislesding results are obtained in this system.