• 한국정보과학회논문지:시스템및이론
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• 제30권3_4호
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• pp.186-193
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• 2003

최근 몇 년 동안 디지털 시스템이 복잡성은 아주 빠르게 증가하고 있다. 비록 반도체 제조업자들이 제품에 대한 신뢰성을 높이려고 노력하고 있지만 어느 때에 시스템이 어딘가에서 결함이 발생할 것이라는 것을 알기는 불가능하다. 이렇듯이 회로가 복잡화함에 따라 테스트 생성(test generation)에 대한 잘 정리되어 있고 자동화된 방법이 필요하게 되었다. 하지만 현재 광범위하게 사용하고 있는 방법중 대부분은 한번에 하나씩의 패턴만을 넣어서 처리하는 방식이다. 이는 각각의 결함에 대해서 탐색하는데 많은 시간을 낭비하게 된다. 본 논문에서는 Exhaustive 방법을 사용하는 테스트 패턴 생성 방법 중에서 분할 기법을 적용하여 테스트 패턴을 생성한다. 또한 이 패턴을 이용하여 병렬로 패턴을 삽입함으로써 더욱 빠르게 결함을 발견할 수 있는 방법을 설계 및 구현한다.

• 전기학회논문지
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• 제63권8호
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• pp.1085-1091
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• 2014

A model based SOC estimation scheme using parameter identification is described and applied to a Lithium-ion battery module that can be installed in electric vehicles. Simulation studies are performed to verify the effect of sensor faults on the SOC estimation results for terminal voltage sensor and load current sensor. The sensor faults should be detected and isolated as soon as possible because the SOC estimation error due to any sensor fault seriously affects the overall performance of the BMS. A new fault detection and isolation(FDI) scheme by which the fault of terminal voltage sensor and load current sensor can be detected and isolated is proposed to improve the reliability of the BMS. The proposed FDI scheme utilizes the parameter estimation of an input-output model and two fuzzy predictors for residual generation; one for terminal voltage and the other for load current. Recently developed dual polarization(DP) model is taken to develope and evaluate the performance of the proposed FDI scheme. Simulation results show the practical feasibility of the proposed FDI scheme.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2007년도 제29회 추계학술대회논문집
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• pp.345-349
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• 2007

본 연구에서는 계측 데이터의 성능 추이를 분석하여 엔진의 기계적 결함 여부를 탐지하기 위한 퍼지 경향감시 방법을 제안하였다. 경향감시 방법은 연료유량, 배기가스 온도, 로터회전수, 진동수와 같은 중요 엔진 파라미터를 모니터링하여 시간에 따른 변화를 분석하여 엔진 상태를 진단하는 것이다. 선형회귀분석을 통해 엔진 상태 변화를 수식화하고 퍼지 로직을 통해 진단 결과를 분석하여 예측되는 손상 원인을 제시한다.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.281-287
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• 2003

A Natural cavities were found at shallow depth during construction of a huge bridge in Moon-Kyung, Korea. The distribution patterns of cavities in the Moon-Kyung limestone were investigated carefully with a supplementary field job such as a structural geological survey, a geophysical survey, and a rock mechanical test in laboratory or field. A structural geological mapping produced a detail geological map on this area. It suggested that there were three faults in this area, and these faults had an influence on the mechanism of natural cavities. Among many kinds of geophysical surveys, an electrical resistivity prospecting was applied firstly on the specific area that was selected by results from the geological survey. Many evidences for cavities were disclosed from this geophysical data. Therefore, a seismic tomography was tested on the target area, which was focused by results from the electrical resistivity prospecting and was believed to have several large cavities. A distinct element numerical simulation using the UDEC was followed on the target area after completing all of field surveys. Data from field tests were directly dumped or extrapolated to numerical simulations as input data. It was verified from numerical analysis that several natural cavities underneath the foundation of the bridge should be reinforced. Based on the project result, finally, most of foundations for the bridge were re-examined and the cement grouting reinforcement was constructed on several foundations among them.

• 한국소음진동공학회논문집
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• 제13권9호
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• pp.703-712
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• 2003

This paper suggests a fuzzy expert system for fault diagnosis of rotating machinery, based on modulated databases. In the proposed system, alarm and trip levels are set based on ISO, considering operating condition, machinery type and maintenance history. Input signals for diagnosis, such as sub-and super-harmonic components of vibration and mean value, are normalized from 0 to 1 under the threshold level and otherwise equal to one so that chronic faults slightly below the threshold level can be monitored. The database for diagnosis consists of two modules: the well-known Sohre's chart module and if-then type rules. The Sohre's chart is utilized for the most common problems of high-speed turbomachinery, while the rule-based module, which was collected from many papers and reports, is for diagnosing peculiar faults according to the type of machinery. To infer the results from two modules, a fuzzy operation of Yager sum was adopted. Using a simulator constructed in laboratory, experimental verification was performed for the cases of unbalance and resonance which were intended. The experimental results show that the proposed fuzzy expert system has feasibility in practical diagnosis of rotating machinery.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.303-312
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• 2003

This paper suggests a fuzzy expert system for fault diagnosis of rotating machinery, based on modulated databases. In the proposed system, alarm and trip levels are set based on ISO, considering operating condition, machinery type and maintenance history. Input signals for diagnosis, such as sub- and super-harmonic components of vibration and mean value, are normalized from 0 to 1 under the threshold level and otherwise equal to one so that chronic faults slightly below the threshold level can be monitored. The database for diagnosis consists of two modules: the well-known Sohre's chart module and if-then type rules. The Sohre's chart is utilized for the most common problems of high-speed turbomachinery, while the rule-based module, which was collected from many papers and reports, is for diagnosing peculiar faults according to the type of machinery. To infer the results from two modules, a fuzzy operation of Yager sum was adopted. Using a simulator constructed in laboratory, experimental verification was performed for the cases of resonance and housing looseness which were intended. The experimental results show that the proposed fuzzy expert system has feasibility in practical diagnosis of rotating machinery.

• 대한전자공학회논문지SD
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• 제39권8호
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• pp.24-33
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• 2002

혼성 신호 회로의 설계에 있어 저비용의 고효율 테스트 효율을 보장하기 위해 테스트의 노력은 계속되어 왔다. 특히 테스트를 고려한 BIST(built-in-self-test)설계 방법으로 발전해가고 있는 추세인데, 회로상에서 전체적인 테스트 용이도와 분석에 있어 보다 향상된 방법으로 접근할 수 있고 이러한 시스템에 대해 분석하는데 수월하게 할 수도 있다. 이 논문에서는 효과적인 테스트를 위한 방법을 위해 DC전압과 전압 위상에 대한 BIST를 구현하는 것을 제안하였다. 즉 정상적인 회로와 고장회로에서의 동작에서 전압과 위상의 차이를 검출하는 회로를 하드웨어상으로 구성함으로써 비용과 시간 등을 효과적으로 줄이는 방법을 제안하였다. 실험 결과에서는 기존의 BIST와 비교하여 향상된 것을 나타낸다.

• 융합신호처리학회논문지
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• 제20권1호
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• pp.57-62
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• 2019

본 논문에서는 회전기기의 전압, 전류, 온도, 가속도, 진동 등을 측정 전송할 수 있는 oneM2M 기반의 실시간 회전기기 센싱 데이터 수집 및 모니터링 시스템을 설계하고 구현하였다. 구현된 시스템은 전기적 결함(과전류, 역상, 결상, 지락)과 기계적 결함(MC 카운터, 모터동작시간, 베어링 및 권선온도, 모터 회전수, 절연저항)의 전기 또는 물리적인 현상 측정이 가능하며, 센서데이터 수집, 웹서버, php, 데이터베이스에 데이터 저장, 웹 접속 통한 데이터 모니터링까지 가능하도록 시스템을 구성하였다. 회전기기에서의 기계적 결함을 실험한 결과, 절연저항 및 모터회전수 측정 결과 시험저항 값과 기준 입력값 각각에서 유사한 실험 결과를 보였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2013년도 추계학술대회 논문집
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• pp.338-345
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• 2013

Induction motors play an increasing importance in industrial manufacturing. Therefore, the state monitoring systems also have been considering as the key in dealing with their negative effect by absorbing faulty symptoms in motors. There are numerous proposed systems in literature, in which, several kinds of signals are utilized as the input. To solve the multiple faults problem of induction motors, like the proposed system, the vibration signals is good candidate. In this study, a new signal processing scheme was utilized, which transforms the time domain vibration signal into the spatial domain as an image. Then the spatial features of converted image then have been extracted by applying the dominant neighbourhood structure (DNS) algorithm. In addition, these feature vectors were evaluated to obtain the fruitful dimensions, which support to discriminate between states of motors. Because of reliability, the conventional one-against-all (OAA) multi-class support vector machines (MCSVM) have been utilized in the proposed system as classifier module. Even though examined in severity levels of signal-to-noise ratio (SNR), up to 15dB, the proposed system still reliable in term of two criteria: true positive (TF) and false positive (FP). Furthermore, it also offers better performance than five state-of-the-art systems.

• 한국산업정보학회논문지
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• 제25권6호
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• pp.1-13
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• 2020

본 논문에서는 원전 비상 상황 발생 시 다수의 신호 오류가 발생했을 때 어떤 신호에 오류가 발생했는지를 추정하는 신호 오류 식별 (Fault identification) 방법론을 개발하였다. 변분 오토인 코더 (Variational autoencoder; VAE) 기반 모델은 기존의 이상 탐지 방법론과 같이 정상 신호 데이터만을 이용하여 훈련이 진행되며, 이후 각 신호에 대한 복원 오차 (Reconstruction error)와 복원 오차를 입력의 특정 부분으로 미분한 값을 이용하여 어떤 부분에 오류가 포함되어 있는지를 예측한다. 데이터 취득을 위하여 시뮬레이션을 수행하였으며, 일련의 실험으로부터 제시한 신호 오류 식별 방법이 적절한 오차 범위 내에서 오류가 발생한 신호를 특정할 수 있음을 확인하였다.