• 산업경영시스템학회지
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• 제44권3호
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• pp.86-97
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• 2021

As mechatronic systems have various, complex functions and require high performance, automatic fault detection is necessary for secure operation in manufacturing processes. For conducting automatic and real-time fault detection in modern mechatronic systems, multiple sensor signals are collected by internet of things technologies. Since traditional statistical control charts or machine learning approaches show significant results with unified and solid density models under normal operating states but they have limitations with scattered signal models under normal states, many pattern extraction and matching approaches have been paid attention. Signal discretization-based pattern extraction methods are one of popular signal analyses, which reduce the size of the given datasets as much as possible as well as highlight significant and inherent signal behaviors. Since general pattern extraction methods are usually conducted with a fixed size of time segmentation, they can easily cut off significant behaviors, and consequently the performance of the extracted fault patterns will be reduced. In this regard, adjustable time segmentation is proposed to extract much meaningful fault patterns in multiple sensor signals. By considering inflection points of signals, we determine the optimal cut-points of time segments in each sensor signal. In addition, to clarify the inflection points, we apply Savitzky-golay filter to the original datasets. To validate and verify the performance of the proposed segmentation, the dataset collected from an aircraft engine (provided by NASA prognostics center) is used to fault pattern extraction. As a result, the proposed adjustable time segmentation shows better performance in fault pattern extraction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권6호
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• pp.1496-1521
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• 2012

Uncertainty is ubiquitous in target tracking wireless sensor networks due to environmental noise, randomness of target mobility and other factors. Sensing results are always unreliable. This paper considers unreliability as it occurs in wireless sensor networks and its impact on target-tracking accuracy. Firstly, we map intersection pairwise sensors' uncertain boundaries, which divides the monitor area into faces. Each face has a unique signature vector. For each target localization, a sampling vector is built after multiple grouping samplings determine whether the RSS (Received Signal Strength) for a pairwise nodes' is ordinal or flipped. A Fault-Tolerant Target-Tracking (FTTT) strategy is proposed, which transforms the tracking problem into a vector matching process that increases the tracking flexibility and accuracy while reducing the influence of in-the-filed factors. In addition, a heuristic matching algorithm is introduced to reduce the computational complexity. The fault tolerance of FTTT is also discussed. An extension of FTTT is then proposed by quantifying the pairwise uncertainty to further enhance robustness. Results show FTTT is more flexible, more robust and more accurate than parallel approaches.

• 한국지구과학회지
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• 제45권3호
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• pp.224-238
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• 2024

역사지진 및 계기지진이 보고되어 앞으로 지진이 발생할 가능성이 있는 한반도 중부지역 중, 충청남도 서부지역에 분포하는 선형구조와 단층지형을 분석하였다. 단층지형을 기반으로 총 151개의 선형구조가 추출하였다. 당진단층과 예산단층이 위치하는 지역에 단층과 주향이 일치하는 선형구조가 밀집하여 분포하는 반면, 홍성단층이 위치한 지역에는 선형구조의 수가 적으며 단층과 유사한 주향을 갖는 선형구조 또한 잘 인지되지 않는다. 이러한 특징은 넓은 충적층과, 오랜 기간의 풍화와 침식, 그리고 경작으로 인한 지표의 변형 등에 의해 단층을 지시하는 지형증거를 인지하기 어렵기 때문으로 판단된다. 단층으로 판명된 5개의 주요지점에서는 단층안부, 제4기 충적층에 나타나는 경사급변점, 선형곡 등의 단층지형이 선형구조를 따라 인지되었으며 단층지형이 실제 단층을 잘 지시하는 것으로 나타났다. 한편 선형구조 내에서 감지된 제4기층의 변위는 단층운동에 의해 직접적으로 형성된 것이 아닌 농경지 정리와 같은 인위적 교란이나 하천 침식의 영향과 같은 외부요인에 의해 형성되었을 가능성이 있는 것으로 파악되었다. 연구지역에서 인지되는 단층지형의 유형과 한반도 남동부 지역에서 인지되는 단층지형의 유형에 차이가 나타나는데 이는 단층지형의 유형이 단층종류에 따라 변화되는 한 예를 보여준다.

• Earthquakes and Structures
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• 제5권2호
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• pp.129-142
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• 2013

Linear and nonlinear time history analyses have been becoming more common in seismic analysis and design of structures with advances in computer technology and earthquake engineering. One of the most important issues for such analyses is the selection of appropriate acceleration time histories and matching these histories to a code design acceleration spectrum. In literature, there are three sources of acceleration time histories: artificial records, synthetic records obtained from seismological models and accelerograms recorded in real earthquakes. Because of the increase of the number of strong ground motion database, using and scaling real earthquake records for seismic analysis has been becoming one of the most popular research issues in earthquake engineering. In general, two methods are used for scaling actual earthquake records: scaling in time domain and frequency domain. The objective of this study is twofold: the first is to discuss and summarize basic methodologies and criteria for selecting and scaling ground motion time histories. The second is to analyze scaling results of time domain method according to ASCE 7-05 and Eurocode 8 (1998-1:2004) criteria. Differences between time domain method and frequency domain method are mentioned briefly. The time domain scaling procedure is utilized to scale the available real records obtained from near fault motions and far fault motions to match the proposed elastic design acceleration spectrum given in the Eurocode 8. Why the time domain method is preferred in this study is stated. The best fitted ground motion time histories are selected and these histories are analyzed according to Eurocode 8 (1998-1:2004) and ASCE 7-05 criteria. Also, characteristics of both near fault ground motions and far fault ground motions are presented by the help of figures. Hence, we can compare the effects of near fault ground motions on structures with far fault ground motions' effects.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.187-194
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• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1348-1351
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• 1997

The federated Kaman filter(FKF) is being widely used in many multisensor navigatiion systems. It is know that the FKF has advantages of simplicity and fault-tolerance over other decentralized filter techniques. In this paper, optimal and suboptimal FKF configuratiions are mentioned and a covariance analysis technique for the suboptimal FKF is newly presented. The suboptimal FKF configuration, known as No-reset(NR) mode, has better fault tolerance capability than the optimal FKF coniguratioin. In the suggested technique, a suboptimal fusion process of FKF is considered a swell as suboptimal gains of local filters. An upper boun of error covariance for suboptimal FKF is derived. Also, it is mathematically shown that this bound is smaller thanexisting bound in the literatrue. A vehicle-navigaion system is designed using the FKF. In thissystem, a map constraing equation is introduced and used as a measurement equatioin of Kalman filter. Performance analysis is done by the suggested covariance analysis techniques.

• Journal of Power Electronics
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• 제16권4호
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• pp.1612-1620
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• 2016

This paper presents the dynamic excitation control of a siphon-turbine coupled pico-hydro powered cage rotor induction generator and load matching for off-grid electricity generation. Through the proposed dual-role of the current-controlled voltage source converter (VSC), acting as static synchronous compensator and load controller, real and reactive power are dynamically controlled in a decoupled manner with a self supported DC-bus. The proposed scheme entails minimal computation for ensuring the rated (set) capacity of real power. The scheme also exhibits fault immunity for protection, thus enabling the effective handling of constant power electrical loads presented by base telecom station towers in remote locations. The performance of the system is evaluated under MATLAB/Simulink and is experimented through a developed hardware prototype. Simulation and experimental results show close conformity and validate the effectiveness of the proposed scheme.

• 대한전기학회논문지:전력기술부문A
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• 제55권10호
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• pp.410-417
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• 2006

Generally, the training set of maximum $m{\times}L(m+f)$ patterns in the pattern recognition method is required for the real-time bus reconfiguration strategy when a main transformer fault occurs in the distribution substation. Accordingly, to make the application of pattern recognition method possible, the size of the training set must be reduced as efficient level. This Paper proposes a methodology which obtains the minimized training set by applying the pattern clustering method to load patterns of the main transformers and feeders during selected period and to obtain bus reconfiguration strategy based on it. The MaxMin distance clustering algorithm is adopted as the pattern clustering method. The proposed method reduces greatly the number of load patterns to be trained and obtain the satisfactory pattern matching success rate because that it generates the typical pattern clusters by appling the pattern clustering method to load patterns of the main transformers and feeders during selected period. The proposed strategy is designed and implemented in Visual C++ MFC. Finally, availability and accuracy of the proposed methodology and the design is verified from diversity simulation reviews for typical distribution substation.

• 지질공학
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• 제31권3호
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• pp.239-255
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• 2021

Kinematic analyses of magmatic intrusions and faults can provide useful information on stress conditions and chronological relationships between dike emplacement and brittle deformation events. We studied structures in rocks exposed on a coastal platform in Geoje Island off the southern Korean Peninsula because of its well-developed dikes and faults. The geology of the study area includes the Cretaceous Seongpo-ri Formation, which is composed mostly of shale, sandstone, and hornfels intruded by magmatic dikes. Most of the dikes are developed along pre-existing structural features (faults and fractures), indicating that their emplacements were structurally controlled. Because dikes commonly open along the direction of the minimum principal stress, the direction of this stress can be obtained from dike geometry and orientation through the matching of piercing points on either side of a dike. In addition, the deformed dikes can give information regarding later deformation. On the basis of the kinematic analyses, we identified five deformation events in the study area, which are kinematically related to changes of the regional maximum principal stress. Results indicate that the structures in the study area have been controlled predominantly by episodes of reactivation of the NNE-trending Yangsan strike-slip fault, located to the northeast of the study area, under different stress regimes. In a wider tectonic context, the brittle deformation of the rocks of Geoje Island was probably induced by interactions among the Philippine Sea, Pacific, and Eurasian plates, including changes in subduction parameters with respect to the latter two plates over time.

• 대한전자공학회논문지SD
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• 제43권9호
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• pp.59-63
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• 2006

VLSI의 복잡도가 증가함에 따라, 보다 복잡한 고장이 나타나게 되었다. 단일 고장 진단을 위한 많은 방법들이 연구되어 왔다. 때로는 오류가 존재하는 칩에 대한 다중 결함이 실제 현상을 보다 더 정확하게 반영한다. 따라서 다중 고착 고장을 위한 효율적인 고장 진단 알고리듬을 제한하겠다. 제안하는 매칭 알고리듬은 완전일치공통부분을 고장 진단의 중요한 기준으로 사용함으로써 단일 고착 고장 시뮬레이터 환경에서도 다중 고착 고장을 진단할 수 있다. 또한 각 고장간의 식별성을 높여 다중 고착 고장을 진단함에도 불구하고, 고장 후보의 수를 획기적으로 줄일 수 있었다. 이를 위하여 출력단의 수에 따른 가중치 개념과 가산, 감산 연산을 사용하였다. 제안한 매칭 알고리듬은 ISCAS85회로와 완전 주사 스캔이 삽입된 ISCAS89회로에서 실험하여 성능을 입증하였다.