• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.4
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• pp.18-23
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• 2011

Generally, the digital circuit card can be tested by automatic test equipment using LASAR(Logic Automated Stimulus and Response). This paper proposes the ROM data extracting algorithm which can test the digital circuit card that consists usually ROMs. We are implemented of the proposed fault detecting program by LabWindow/CVI 8.5 and the digital automatic test instrument with NI-VXI(National Instrument - Versa Bus Modular Europe eXtentions for Instrumentation) card. We also make an interface circuit board connecting the digital test instrument and the digital circuit card. It shows the good performance of getting the data from ROMs.

• Journal of Korea Foundry Society
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• v.42 no.6
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• pp.369-376
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• 2022

The die-casting process is an important process for various industries, but there are limitations in the profitability and productivity of related companies due to the high defect rate. In order to overcome this, this study has developed die-casting fault detection modules based on industrial AI technologies. The developed module is constructed from three-stage models depending on the characteristics of the dataset. The first-stage model conducts fault detection based on supervised learning from the dataset without labels. The second-stage model realizes one-class classification based on semi-supervised learning, where the dataset only has production success labels. The third-stage model corresponds to fault detection based on supervised learning, where the dataset includes a small amount of production failure cases. The developed fault detection module exhibited outstanding performance with roughly 96% accuracy for actual process data.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.245-250
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• 2002

The operational data of diesel generator engine is two kind of discrete signal and analog signal. We can find the fault information from analog data measured for every sampling time if it is invested the changing rate or direction of data. This paper propose the Malfunction Diagnosis Engine(MDE) using the commercial data mining tool and show the data Process and fault finding method with the data collected from generator engine of the ship.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1002-1008
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• 2009

We consider a double faults detection and isolation problem using modified extended parity space approach for inertial measurement unit which use redundant inertial sensors. A redundant IMU which has a hardware redundant is composed of the cone shape because it is good for fault detection and isolation. We analyze the type of double faults and the reason why fault isolation performance is low. We propose modified extended parity space approach method using EPSA and the difference of sensor data.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.268-277
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• 1999

Impulsive acoustic and vibration signals within gear are often induced by impacting of fault tooths in gear. Thus the detection of these impulses can be useful for fault diagnosis. Recently there is an increasing trend towards the use of higher order statistics for fault detection within mechanical systems based on the observation that impulsive signals then to increase the kurtosis values. We show that the fourth order Wigner Moment Spectrum, called the Wigner Trispectrum, has found superior detection performance to second order Wigner distribution for typical impulsive signals in a condition monitoring application. These methods are also applied to data sets measured within an industrial gear box.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.31-32
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• 2007

In this paper, a fault section detection method is proposed for ungrounded system in the case of a single line-to-ground fault. A conventional method is used for faulted feeder selection according to the angular relationship between zero-sequence currents of the feeders and zero-sequence voltage of the system. Fault section detection is based on the comparison of phase angle of zero-sequence current. Proposed method has been testified in a demo system by Matlab/Simulink simulations. Based on Distribution Automation System(DAS), Feeder Remote Terminal Unit(FRTU) is used to collect those necessary data, at present a demo system is under developing using Manufacturing Message Specification (MMS) in IEC61850 standard.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.1-10
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• 1995

In this paper, a fault-tolerant Mini-MAP system with high reliability is proposed. For fault-tolerance, the LLC sublayer, MAC sublayer, and physical layer of the Mini-MAP system are dualized. The detection of faults, the replacement of the failed network, and the management of the network are three major functions required for the dualization, and they are performed by ESM(Error Supervisory Machine), EMM(Error Management Machine), and NMM(Network Management Machine) of the proposed fault-tolerant Mini-MAP system, respectively. The ring maintenance function of the MAC sublayer is used for the detection of the faults. In the proposed fault-tolerant Mini-MAP system, the data are received from both of the dualized networks and transmitted to the selected one of the two. We analyze the reliability and the MTTF(Mean Time To Failure) of the proposed fault-tolerant Mini-MAP system and show that it has better performance compared to a general Mini-MAP system.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.212-212
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• 1999

This paper proposed a high impedance fault detection method using a neural network on distribution lines. The v-I characteristic curve was obtained by high impedance fault data tested in various soil conditions. High impedance fault was simulated using EMTP. The pattern of High Impedance Fault on high density pebbles was taken as the learning model, and the neural network was valuated on various soil conditions. The average values after analyzing fault current by FFT of evenr·odd harmonics and fundamental rms were used for the neural network input. Test results were verified the validity of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.538-544
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• 1999

In this paper, we propose a new fault detection algorithm for transmission line protection using ANFIS(Adaptive Network Fuzzy Inference System). The developed system consists of two subsystems: fault type classification, and fault location estimation. We use rms value, zero sequence component and positive sequence of current, and then using learning method of neural network, premise and consequent parameters are tuned properly. To prove the performance of the proposcd system, generated data by EMTP(Electr0- Magnetic Transient Program) sin~ulationi s used. It is shown that the proposed relaying classifies fault types accurately and advances fault location estimation.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.1
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• pp.65-69
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• 2020

The aim of this study is to improve the fault decision ability of FRTU (Feeder remote terminal unit) in DAS (Distribution automation system). FRTU uses the FI (Fault indicator) algorithm based on fault current pickup and operation of the protection device. Even if the inrush current flows or the protection device is sensitive to the transient current, FRTU may indicate incorrect fault information. To address these problems, we propose an improved fault recognition algorithm that can be applied to FRTU. We will detect a specific wave that is indicative of a fault, and use this information to identify a fault wave. The specific wave-detection algorithm is based on the duration and periodicity of the voltage, current, and harmonic variations. In addition, we propose fault recognition algorithms using voltage factor variation analysis and DWT (Discrete wavelet transform). All the wave data used in this study were actual data stored in FRTU.