• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2106-2117
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• 2017

An effective statistical feature extraction approach of data sampling of fault in the combined transmission system is presented in this paper. The proposed algorithm leads to high accuracy at minimum cost to predict fault location and fault type classification. This algorithm requires impedance measurement data from one end of the transmission line. Modal decomposition is used to extract positive sequence impedance. Then, the fault signal is decomposed by using discrete wavelet transform. Statistical sampling is used to extract appropriate fault features as benchmark of decomposed signal to train classifier. Support Vector Machine (SVM) is used to illustrate the performance of statistical sampling performance. The overall time of sampling is not exceeding 1 1/4 cycles, taking into account the interval time. The proposed method takes two steps of sampling. The first step takes 3/4 cycle of during-fault and the second step takes 1/4 cycle of post fault impedance. The interval time between the two steps is assumed to be 1/4 cycle. Extensive studies using MATLAB software show accurate fault location estimation and fault type classification of the proposed method. The classifier result is presented and compared with well-established travelling wave methods and the performance of the algorithms are analyzed and discussed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권2호
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• pp.99-104
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• 2009

The turn-to-turn short is one major fault of the motor faults of BLDC motors and can appear frequently. When the fault happens, the motor can be operated without breakdown, but it is necessary to maintain the motor for continuous working. In past research, several methods have been applied to detect winding faults. The representative approaches have been focusing on current signals, which can give important information to extract features and to detect faults. In this study, current sensors were installed to measure signals for fault detection of BLDC motors. In this study, the Park's vector method was used to extract the features and to isolate the faults from the current measured by sensors. Because this method can consider the three-phase current values, it is useful to detect features from one-phase and three-phase faults. After extracting two-dimensional features, the final feature was generated by using the two-dimensional values using the distance equation. The values were used in fuzzy similarity to isolate the faults. Fuzzy similarity is an available tool to diagnose the fault without model generation and the fault was converted to the percentage value that can be considered as possibility of the fault.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.1274-1279
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• 2004

This paper proposes technique to detect ground fault in railway high voltage distribution lines. Overcurrent relay technique is widely used for detecting one line ground fault that occurs most frequently in railway high voltage distribution lines. However, ground fault in distribution line is usually high impedance fault with arc. Because the fault current magnitude measured in substation is very small, the conventional overcurrent relay can't detect the high impedance ground fault. Therefore this paper proposes the advanced technique using wavelet transform. It extracts D1 component from fault signals and detects fault comparing magnitude of D1 component in each phase. To evaluate this proposed technique, we model distribution system using PSCAD/EMTDC and extract various fault data. In conclusion this technique can detect ground fault including high impedance fault regardless of fault distance, fault impedance etc.

• 정보보호학회논문지
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• 제20권6호
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• pp.59-65
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• 2010

오류 주입 공격은 비밀키가 내장된 암호 장치에서 연산을 수행 시 공격자가 오류를 주입하여 비밀키를 찾아내는 공격으로서 암호시스템의 안전성에 심각한 위협이 되고 있다. 본 논문에서는 AES 암호를 수행하는 동안 마지막 라운드의 키를 더하는 반복문(for statement)에 대한 오류 주입을 통해 비밀키 전체를 공격할 수 있음을 보이고자 한다. 상용 마이크로프로세서에 AES를 구현한 후 한 번의 레이저 오류 주입 공격을 시도하여 128비트의 비밀키가 노출됨을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.368-369
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• 2011

This article suggests an online-based remote fault current mode discrimination method in order to identify the causes of the power line faults with various causes. For that, it refers to existing cause identification methods and categorizes modes by fault causes based on statistical techniques beforehand and performs the pretreatment process of fault currents by each cause acquired from the fault recorder into a topological plane in order to extract the characteristics of fault currents by each cause. After that, for the fault mode categorization, it discriminates modes by each cause using data by each cause as leaning data through utilizing RBF network based on FCM allowing self-organization in deciding the middle layer. And then it tests the validity of the suggested method as applying it to the data of the actual fault currents acquired from the fault recorder in the electric power transmission center.

• International Journal of Safety
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• 제11권2호
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• pp.22-25
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• 2012

This paper deals with the problem of fault diagnosis for identifying a single fault when the number of assumed faults is larger than that of predictive variables. Principal component analysis (PCA) is employed to isolate and identify a single fault. PCA is a method to extract important information as reducing the number of large dimension in a process. The patterns of all assumed faults can be recognized by PCA and these can be employed whether a new fault is one of predefined faults or not. Through PCA, empirical models for analyzing patterns can be trained. When a single fault occurs, the pattern generated by PCA can be obtained and this is used to identify a fault. The performance of the proposed approach is illustrated in the actuator benchmark problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 전기설비전문위원
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• pp.86-88
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• 2009

This article suggests an online-based remote fault current mode discrimination method in order to identify the causes of the power line faults with various causes. For that, it refers to existing cause identification methods and categorizes modes by fault causes based on statistical techniques beforehand and performs the pre-treatment process of fault currents by each cause acquired from the fault recorder into a phase space in order to extract the characteristics of fault currents by each cause. After that, for the fault mode categorization, it discriminates modes by each cause using data by each cause as leaning data through utilizing RBF network. And then it tests the validity of the suggested method as applying it to the data of the actual fault currents acquired from the fault recorder in the electric power transmission center.

• JSTS:Journal of Semiconductor Technology and Science
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• 제2권3호
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• pp.226-232
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• 2002

This paper explains a technique to improve the fault coverage of oscillation-test [1-5] for linear analog circuits. The transient behavior of the virtual ground is monitored during oscillation to extract information of the circuit. The limitation of the oscillation-test is analyzed, and an efficient signature analysis technique is proposed to maximize the fault coverage. The experimental result proves that the parametric fault coverage can be significantly increased by the proposed technique.

• 정보보호학회논문지
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• 제19권3호
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• pp.51-59
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• 2009

중국인의 나머지 정리(Chinese Remainder Theorem, CRT)를 이용하는 RSA 암호시스템을 암호 칩에 구현 할 경우, 암호 칩에서 동작하는 과정 중에 한 번의 오류 주입으로 모듈러스 N의 비밀 소인수 p, q값이 노출될 수 있다. 본 논문에서는 상용 마이크로컨트롤러에 CRT-RSA 암호 시스템을 구현한 후, 레이저 빔과 플래시를 이용한 광학적 오류 주입 방법으로 공격을 시도하고 실험 결과를 분석하였다. 레이저 빔과 플래시를 이용한 오류 주입 공격 실험 결과, 일부 상용 마이크로 컨트롤러는 광학적 오류 주입 공격에 대해 취약한 특성으로 인해 CRT-RSA암호 시스템에 소인수 분해 공격이 적용됨을 확인하였다.

• 정보보호학회논문지
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• 제22권3호
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• pp.439-445
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• 2012

오류 주입 공격은 비밀 키를 내장하여 사용하는 암호 장치에서 연산 수행시 공격자가 오류를 주입하는 방법으로 비밀 키를 찾아낼 수 있어 암호시스템 운영의 심각한 위협이 되고 있다. 논문에서는 AES 암호 연산을 수행하는 동안 라운드 함수를 반복적으로 사용하는 경우, 반복하는 구문에 오류를 넣어 한 라운드를 생략하면 쉽게 비밀 키를 추출할 수 있음을 보이고자 한다. 제안하는 공격 방법을 상용 마이크로프로세서에서 실험한 결과, 두 개의 정상-오류 암호문 쌍만 있으면 128비트 AES 비밀 키가 노출됨을 확인하였다.