• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 하계학술대회 논문집 Vol.9
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• pp.289-289
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• 2008

We investigated the operational characteristics of the separated three-phase flux-lock type superconducting fault current limiter (SFCL). The single-phase lock type SFCL consist of two coils, which are wound in parallel through an iron core. The high-$T_c$ superconducting(HSTC) thin film connected in series with secondary coil. The separated three-phase flux-lock type SFCL consist of three single-phase flux-lock type SFCL. In a normal condition, the SFCL is not operate. When a fault occurs, the current of a HSTC thin film exceeds its critical current by fault current, the resistance of the HSTC thin film generated. Therefore fault current was limited by SFCL. The separated three-phase flux-lock type SFCL are operated in fault condition such as the the single line-to-ground fault, the double line-to-ground fault and the triple line-to-ground fault. The experimental results, the SFCL operational characteristics was dependent on fault condition.

• 전기학회논문지
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• 제60권3호
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• pp.524-530
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• 2011

This paper analyzes fault tolerance under a stator turn fault, according to the winding configuration. Improvement of torque characteristics and fault tolerance can be achieved by winding configuration without additional methods. And, torque characteristics and fault tolerance according to the winding configuration can be usually analyzed by analytical method. But, when the stator turn fault generates, compare to the steady-state, analysis of torque characteristics and fault tolerance using the analytical method is not accurate because it does not reflect influence in mutual inductance and magnetic non-linearity. Therefore, analysis of torque characteristics and fault tolerance has to be performed by using the numerical method under fault condition. This paper develops fault characteristics according to the winding configuration using the FEM-base model considered magnetic non-linearity. And, this paper suggests fault tolerance improvement according to the winding configuration, by the comparison of 8/12 and 10/12 models, under fault condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• Journal of Positioning, Navigation, and Timing
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• 제10권4호
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• pp.263-269
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• 2021

The carrier-based differential global navigation satellite system (CD-GNSS) has been garnering significant attention as a promising technology for unmanned vehicles for its high accuracy. The CD-GNSS systems to be used for safety-critical applications should provide a certain level of integrity. The integrity of these systems must be analyzed under various conditions, including fault-free and satellite fault conditions. The systems should be able to detect the faults that can cause large biases on the user position errors and quantify the integrity risk by computing the protection level (PL) to protect the user against the faults that are left undetected. Prior work has derived and investigated the PL for the fault-free condition. In this study, the integrity of the CD-GNSS system under the fault condition is analyzed. The position errors caused by the satellite's fault are compared with the fault-free PL (PL_H0) to verify whether the integrity requirement can be met without computing the PLs for the fault conditions. The simulations are conducted by assuming the ephemeris fault, and the position errors are evaluated by changing the size of the ephemeris faults that missed detection. It was confirmed that the existing fault monitors do not guarantee that the position error under the fault condition does not exceed the PL_H0. Further, the impact of the faults on the position errors is discussed.

• Journal of Electrical Engineering and Technology
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• 제3권2호
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• pp.213-217
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• 2008

The flux-lock type superconducting fault current limiter(SFCL) can apply the magnetic field into the high-$T_C$ superconducting(HTSC) element by adopting the magnetic field coil in its third winding. To apply the magnetic field into the HTSC element effectively, the capacitor for LC resonance is connected in series with the magnetic field coil. However, the current waveform of third winding for the application of the magnetic field is affected by the LC resonance condition for the frequency of the source voltage and can affect the waveform of the limited fault current. In this paper, the current waveform of the third winding in the flux-lock type SFCL according to LC resonance condition during a fault period was analyzed. From the differential equation for its electrical circuit, the current equation of the third winding was derived and described with the natural frequency and the damping ratio as design parameters. Through the analysis according to the design parameters of the third winding, the waveform of the limited fault current was confirmed to be influenced by the current waveform of the third winding and the design condition for the stable fault current limiting operation of this SFCL was obtained.

• Geomechanics and Engineering
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• 제24권5호
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• pp.443-456
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• 2021

Structural design of the vertical displacements and shear strains in the earth fill (EF) dams has great importance in the structural engineering problems. Moreover, far fault earthquakes have significant seismic effects on seismic damage performance of EF dams like the near fault earthquakes. For this reason, three dimensional (3D) earthquake damage performance of Oroville dam is assessed considering different far-fault ground motions in this study. Oroville Dam was built in United States of America-California and its height is 234.7 m (770 ft.). 3D model of Oroville dam is modelled using FLAC3D software based on finite difference approach. In order to represent interaction condition between discrete surfaces, special interface elements are used between dam body and foundation. Non-reflecting seismic boundary conditions (free field and quiet) are defined to the main surfaces of the dam for the nonlinear seismic analyses. 6 different far-fault ground motions are taken into account for the full reservoir condition of Oroville dam. According to nonlinear seismic analysis results, the effects of far-fault ground motions on the nonlinear seismic settlement and shear strain behaviour of Oroville EF dam are determined and evaluated in detail. It is clearly seen that far-fault earthquakes have very significant seismic effects on the settlement-shear strain behaviour of EF dams and these earthquakes create vital important seismic damages on the swelling behaviour of dam body surface. Moreover, it is proposed that far-fault ground motions should not be ignored while modelling EF dams.

• Journal of Power Electronics
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• 제13권4호
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• pp.552-557
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• 2013

This paper proposed an analytical model for the distributed magnetic field analysis of interior permanent magnet-type blush-less direct current motors under the stator-turn fault condition using the winding function theory. Stator-turn faults cause significant changes in electric and magnetic characteristic. Therefore, many studies on stator-turn faults have been performed by simulation of the finite element method because of its non-linear characteristic. However, this is difficult to apply to on-line fault detection systems because the processing time of the finite element method is very long. Fault-tolerant control systems require diagnostic methods that have simple processing systems and can produce accurate information. Thus analytical modeling of a stator-turn fault has been performed using the winding function theory, and the distributed magnetic characteristics have been analyzed under the fault condition. The proposed analytical model was verified using the finite element method.

• 항공우주기술
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• 제6권2호
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• pp.21-28
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• 2007

본 논문의 목표는 고장허용제어시스템에 대한 기반 연구로서 무인비행기 안전성 향상을 위하여 조종면 작동불능과 같은 고장에 대해 검출 방법을 제시하는 것이다. 조종면 고장검출을 위한 실시간 시스템식별 알고리듬은 퓨리에 변환기법을 사용하였으며 프로그램 성능 및 검증을 위해 HILS 시험과 비행시험을 수행하였다. 엘리베이터 조종면 고장은 피칭모멘트에 대한 조종면 효과를 나타내는 조종미계수를 실시간 추정하여 정상상태의 값과 비교함으로써 검출된다. 비행시험 결과를 통해 고장상태의 조종미계수 값은 정상상태의 값보다 작다는 것을 확인하였다.

• 한국신뢰성학회지:신뢰성응용연구
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• 제14권4호
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• pp.208-212
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• 2014

An experimental gear-box was set-up to simulate the real situation of the wind-turbine. Artificial cracks of different sizes were machined into the gear. Vibration signals were acquired to diagnose the different crack fault conditions. Time-domain features such as root mean square, variance, kurtosis, normalized 6th central moments were used to capture the characteristics of different crack conditions. Normal condition, 1 mm crack condition, 2mm crack condition, 6mm crack condition, and tooth fault condition were compared using ANFIS and DAG-SVM methods, and three different DAG-SVM models were compared. High-pass filtering improved the success rates remarkably in the case of DAG-SVM.

• Tribology and Lubricants
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• 제14권3호
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• pp.74-80
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• 1998

The morphologies of the wear particles are directly indicative of wear process occuring in the machine. The analysis of wear particle morphology can therefore provide very early detection of a fault and can also ofen facilitate a dignosis. For this work, the neural network was applied to identify friction coefficient through four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris generated from the machine. The averages of these parameters were used as inputs to the network. It is shown that collect identification of friction coefficient depends on the ranges of these shape parameters learned. The various kinds of the wear debris had a different pattern characteristics and recognized relation between the friction condition and materials very well by neural network. We discuss how the network determines difference in wear debris feature, and this approach can be applied for machine condition monitoring and fault diagnosis.