• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.393-403
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• 1998

The advent of very large scale integration(VLSI) has had a tremendous impact on the design of fault-tolerant circuits and systems. The increasing density, decreasing power consumption, and decreasing costs of integrated circuits, due in part to VLSI, have made it possible and practical to implement the redundancy approaches used in fault-tolerant computing. The purpose of this paper is to study the many aspects of designing fault-tolerant systems in a VLSI environment. First, we expound upon the opportunities and problemes presented by VLSI technology. Second, we consider in detail the importance of design mistakes, common-mode failures, and transient faults in VLSI. Finally, we examine the techniques available to implement redundancy using VLSI and the problems associated with these techniques.

• Proceedings of the KIEE Conference
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• 2008.04b
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• pp.171-173
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• 2008

This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

• Progress in Superconductivity and Cryogenics
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• v.7 no.1
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• pp.25-31
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• 2005

Since the discovery of the high temperature superconductors many researches have been performed for the practical applications of superconductivity technologies in various fields. As results, significant progress has been achieved. Especially, Superconducting Fault Current Limiter (SFCL) offers an attractive means In limit fault current in power systems. HTS resistive type SFCL is based on the ultra fast transition from the superconducting (non resistive) state to the normal (resistive) state by overstepping the critical current density, In this study, the simulation method of resistive type superconducting fault current limiter using EMTDC is proposed and the developed EMTDC model of SFCL is applied to the modeled power network using the Parameters of real system.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1503-1504
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• 2008

This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.53
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• pp.111-120
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• 1999

The advent of very large scale integration(VLSI) has had a tremendous impact on the design of fault-tolerant circuits and systems. The increasing density, decreasing power consumption, and decreasing costs of integrated circuits, due in part to VLSI, have made it possible and practical to implement the redundancy approaches used in fault-tolerant computing. The purpose of this paper is to study the many aspects of designing fault-tolerant systems in a VLSI environment. First, we expound upon the opportunities and problems presented by VLSI technology. Second, we consider in detail the importance of design mistakes, common-mode failures, and transient faults in VLSI. Finally, we examine the techniques available to implement redundancy using VLSI and the promlems associated with these techniques.

• Proceedings of the KIEE Conference
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• summer
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• pp.427-429
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• 2004

As the load density of KEOCO system is higher, the fault current can be much higher than SCC(Short Circuit Capacity) of circuit breaker. Even though there are several alternatives to reduce fault current, as the superconductivity technology has been developed, the HTS-FCL (High Temperature Superconductivity Fault Current Limiter) can be one of the attractive alternatives to solve the fault current problem. This study presents the application of HTS-FCL in real customer system.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2989-2996
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• 1998

As the circuit density of VLSI grows and its performance improves, delay fault testing of VLSI becomes very important. Delay faults in a circuit can be categorized into two classes, gate delay faults and path delay faults. This paper proposed two methods in dynamic memory usage in the path delay fault simulation. The first method is similar to that used in concurrent fault simulation for stuck-at faults and the second method reduces dynamic memory usage by not inserting a fault descriptor into the fault list when its value is X. The second method, called Implicit-X method, showed superior performance in both dynamic memory usage and simulation time than the first method, called Concurrent-Simulation-Like method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.80-87
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• 1999

This paper proposed a high impedance fault detection method using a neural network on distribution lines. The $\upsilon-i$ 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 evaluated on various soil conditions. The average values after analyzing fault current by FFT of even.odd harmonics and fundamental rms were used for the neural network input. Test results were verified the validity of the proposed method .ethod .

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.530-540
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• 2020

In order to solve the problem of low tracking accuracy caused by complex noise in the fault diagnosis of complex nonlinear system, a fault diagnosis method of high precision cost reference particle filter (CRPF) is proposed. By optimizing the low confidence particles to replace the resampling process, this paper improved the problem of sample impoverishment caused by the sample updating based on risk and cost of CRPF algorithm. This paper attempts to improve the accuracy of state estimation from the essential level of obtaining samples. Then, we study the correlation between the current observation value and the prior state. By adjusting the density variance of state transitions adaptively, the adaptive ability of the algorithm to the complex noises can be enhanced, which is expected to improve the accuracy of fault state tracking. Through the simulation analysis of a fuel unit fault diagnosis, the results show that the accuracy of the algorithm has been improved obviously under the background of complex noise.