• 융합신호처리학회논문지
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• 제20권2호
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• pp.78-83
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• 2019

소리 기반 기계 고장 진단은 기계의 음향 방출 신호에서 비정상적인 소리를 자동으로 감지하는 것이다. 수학적 모델을 사용하는 기존의 방법은 기계 시스템의 복잡성과 잡음과 같은 비선형 요인이 존재하기 때문에 기계 고장 진단이 어려웠다. 따라서 기계 고장 진단의 문제를 패턴 인식 문제로 해결하고자 한다. 본 논문에서 DWT와 인공신경망 기반 패턴 인식 기법을 이용한 자동화 기계 고장 진단 기법을 제안한다. 기계의 결함을 효과적으로 탐지하기 위해 DWT를 이용해 대역별 분해 후 최상위 고주파 부대역과 최하위 저주파 부대역을 제외한 나머지 부대역의 PSD를 구하여 인공신경망 기반 분류기의 입력으로 사용한다. 그 결과 본 연구에서 제안한 방법은 효과적으로 결함을 탐지할 뿐만 아니라 소리 기반의 다양한 자동 진단 시스템에도 효과적으로 활용될 수 있음을 보여준다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 춘계학술대회 논문집 전기설비전문위원
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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.

• 한국초전도ㆍ저온공학회논문지
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• 제7권1호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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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.

• 산업경영시스템학회지
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• 제22권53호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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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.

• 한국정보처리학회논문지
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• 제5권11호
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• pp.2989-2996
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• 1998

집적회로의 집적도가 높아지고 성능이 향상됨에 따라 회로의 지연고장에 대한 관심이 날로 높아지고 있다. 회로의 지연고장은 게이트 지연고장과 경로지연고장으로 분류할 수 있는데, 이 논문에서는 경로지연고장 시뮬레이션에 대한 두 가지 동적 메모리 사용 방법을 제안하였다. 첫 번째 방법은 고착고장에 대한 동시 고장 시뮬레이션과 유사한 방식이며, 두 번째 방법은 고장기술자의 값이 X일 때 이를 고장리스트에 삽입하지 않는 묵시적-X 방식이다. 제안된 두 방식 중 묵시적-X 방식이 동적 메모리 사용과 시뮬레이션 시간 측면에서 효율적이었다.

• 조명전기설비학회논문지
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• 제13권2호
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• pp.80-87
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• 1999

본 논문은 신경회로망을 이용하여 배전선로상의 고저항 사고검출기법을 제안하였다. 다양한 토양에서 실시한 고저항 사고 데이터를 통해 $\upsilon-i$ 특성곡선을 얻고, 이 특성곡선으로 EMTP를 이용하여 고저항 사고를 모의하였다. 배전선로 고저항 사고검출을 위해 훈련 모델은 강자갈을 사용하였고, 토양의 조건을 달리하여 신경회로망의 사고검출 성능을 평가하였다. 신경회로망의 입력으로 사고 전류를 주파수 분석한 후, 이를 한 주기 평균하여 얻어진 짝.홀수 고조파, 기본파, 실효치 지수을 이용하였다. 신겨회로망의 검출성능을 테스트한 결과 제안된 방법이 뛰어남을 확인하였다.

• Journal of Information Processing Systems
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• 제16권3호
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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.