• 전기학회논문지
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• 제58권9호
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• pp.1802-1808
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• 2009

A fault detection observer with finite time convergence characteristics(FT_FDO) is proposed and applied to a fault detection isolation system for a dynamic control system. The FT_FDO is a kind of dual state-observer scheme that provides with the state estimates insensitive to a specified fault and the corresponding fault estimate. The state estimates are processed to get the residual that will be logically compared with other residuals to detect and isolate the fault of interest, and the fault estimate may be used for fault compensation. The FDIS employing the FT_FDOs can be considered to be a multiple observer schemes(MOS) in which FT_FDOs are parallelly driven to generate a set of residuals to be compared each other. Due to the finite time convergence characteristics of the FT_FDO, the predetermined detection delay can be considered in the design stage of FDIS so that any fault of interest can be detected and identified in that time. It evidently resolves a well known difficulty of threshold selection owing to the transient responses of the fault detection observers(FDO) employed in FDIS. An FDIS is constructed for instruments(2-sensor, 1-actuator) in an inverted pendulum control system, and simulations are performed to show the performance of the FDIS and fault tolerant control system.

• 한국방사선학회논문지
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• 제17권6호
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• pp.897-902
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• 2023

본 논문에서는 휴대용 X-ray 검출기의 방사선 고감도 검출에 대한 실현 가능 여부를 확인하기 위한 SiPM의 특성 분석을 목적으로 한다. 휴대용 X-ray 검출기는 환자의 위치에 빠르게 접근하여 실시간 이미지를 획득함으로써 의사들은 신속하게 진단을 수행할 수 있는 장점이 있지만 이러한 이동성은 선량 감지의 어려움을 동반한다. 기존 검출기에서는 SiPM을 X-ray Trigger를 판별하는 단순한 용도로 사용하고 있다. SiPM을 통한 X-ray의 고감도 검출 가능 여부를 확인하기 위해 7종의 SiPM Sensor를 비교 선정하고 특성 분석을 진행하였다. 최종 시험에 사용한 SiPM은 10 nGy 수준의 극저선량 조사 조건에서 Signal 구분이 가능하며, 관전압에 따라 Signal 상승곡선의 기울기가 변하는 것이 확인되었다. X-ray 선량에 따라 SiPM의 signal level 및 지속시간이 변화되는 특성을 이용한 고감도 측정이 가능할 것으로 보인다.

• 한국입자에어로졸학회지
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• 제13권1호
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• pp.25-31
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• 2017

This paper offer the characteristics for the detection and classification of biological and non-biological aerosol particles in the air by using laser-induced-fluorescence (LIF) based Bio-aerosol Detection System (BDS). The BDS is mainly consist of an optical chamber, in-outlet nozzle system, 405 nm diode laser, an avalanche photo detector (APD) for scattering signal and photomultiplier tubes (PMT) for fluorescence signals in two different wavelength range ; F1, 510-600 nm and F2, 435-470 nm. The detection characteristics, especially ratio of fluorescence signal intensity were examined using well-known components : polystylene latex (PSL), fluorescence PSL, $2{\mu}m$ of SiO2 micro sphere, dried yeast, NADH, ovalbumin, fungicide powder and standard dust. The results indicated that the 405 nm diode laser-based LIF instrument can be a useful bio-aerosol detection system for unexpected biological threaten alter in real-time to apply for dual-use technology in military and civilian fields.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.192-198
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• 2020

The 3D point cloud is a key technology of object detection for virtual reality and augmented reality. In order to apply various areas of object detection, it is necessary to obtain 3D information and even color information more easily. In general, to generate a 3D point cloud, it is acquired using an expensive scanner device. However, 3D and characteristic information such as RGB and depth can be easily obtained in a mobile device. GNN (Graph Neural Network) can be used for object detection based on these characteristics. In this paper, we have generated RGB and RGBD by detecting basic information and characteristic information from the KITTI dataset, which is often used in 3D point cloud object detection. We have generated RGB-GNN with i-GNN, which is the most widely used LiDAR characteristic information, and color information characteristics that can be obtained from mobile devices. We compared and analyzed object detection accuracy using RGBD-GNN, which characterizes color and depth information.

• 한국위성정보통신학회논문지
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• 제9권4호
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• pp.26-31
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• 2014

본 논문은 컬러 영상에서 색상과 움직임 정보를 이용하여 후보영역을 특정하고 연기의 특성들을 추출하여 신경망을 사용한 검출의 성능을 분석하여 제시한다. 기존 연기 검출 알고리즘에서는 연기의 움직임, 색상을 분석하여 후보영역으로 특정하고 그 영역 안에서 연기의 여러 특성을 분석 하는 방법을 이용한다. 하지만 대부분 처음 발생하는 연기의 색상조건을 고려하지 않았기 때문에 조기 검출에는 적절하지 못하다. 본 논문은 연기의 색상과 움직임의 특성을 분석하여 그에 알맞은 방법을 적용하여 후보영역을 폭넓게 결정하고 그 영역 내에서 연기의 확산과 투명성을 인공신경망에 적용시킴으로써 나오는 성능을 분석하였다. 모의실험 결과는 91.31%의 검출율과, 2.62%의 오검출율 성능을 확인할 수 있었다.

• 한국자동차공학회논문집
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• 제7권6호
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• pp.42-48
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• 1999

Engine misfire causes of the negative effect on exhaust emission such as HC, CO, and NOX . Moreover, it causes damage to the three-way-catalyst(TWC) system permanently. The crankshaft velocity fluctuation(CVF) method has been applied for the real cars as misfire detection system usually, which utilizes the crank angle sensor input to calculate the variation of the crankshaft rotational speed. But this approach has the limit due to the fact that three could be problem under certain engine condition like as deceleration or high speed condition . Therefore the development of new methods are requested today. This study introduced the new method of misfire detection using breakdown voltage(BDV) characteristics between spark plug electrouds.

• 전기학회논문지
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• 제62권5호
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• pp.612-619
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• 2013

This paper proposes an early diagnosis technique for the stator-turn fault (STF) in an interior permanent magnet (IPM)-type brushless DC (BLDC) motor using the impedance parameter. We have analyzed the varying characteristics owing to the STF through various experiments and the finite element method (FEM). As a result, we have presented a simple method for fault detection. This technique can be applied without requiring a fast Fourier transform (FFT) and the calculation of the negative-sequence impedance. The fault detection system works on the basis of the comparison the measured impedance with the database impedance. The variations in the characteristics owing to the STF as well as the proposed technique have been verified through the simulation and experiment.

• Journal of Mechanical Science and Technology
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• 제15권2호
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• pp.232-238
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• 2001

Fast Fourier Transformation is employed to convert the head variation of a pipeline in the time domain to the amplitude of the frequency domain. Applying method of characteristics to a pipeline provides a significant frequency range for a surge introduced from the valve modulation. Inverse Fast Fourier Transformation and a Finite Impulse Response Filter can be used to remove any possible noise existing from the significant frequency range of an unsteady condition. A filtered signal shows higher potential for the inverse calculation of leakage detection than the noise-added signal does. The respective performances of Inverse Fast Fourier Transformation and a Finite Impulse Response Filter are compared in terms of leakage detection capability. Characteristics of the frequency range for multiple leakages were investigated to validate the effectiveness of the noise control method in the frequency domain.

• 한국소음진동공학회논문집
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• 제25권11호
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• pp.731-738
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• 2015

This study proposed the method of the multi-crack detection using the sensitivity coefficient matrix which is calculated from the change of eigenvalues and eigenvectors before and after the crack. Each crack is modeled by a rotational springs. The method is applied to the cantilever beam with miulti-crack. The eigenvalues and eigenvectors are determined for different crack locations and depths. The prediction of multi-crack detection are in good agreement with the results of structural reanalysis.

• Smart Structures and Systems
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• 제16권1호
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• pp.213-222
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• 2015

Early detection and precise location of leakage is of great importance for life-cycle maintenance and management of municipal pipeline system. In the past few years, acoustic emission (AE) techniques have demonstrated to be an excellent tool for on-line leakage detection. Regarding the multi-mode and frequency dispersion characteristics of AE signals propagating along a pipeline, the direct cross-correlation technique that assumes the constant AE propagation velocity does not perform well in practice for acoustic leak location. This paper presents an improved cross-correlation method based on wavelet transform, with due consideration of the frequency dispersion characteristics of AE wave and the contribution of different mode. Laboratory experiments conducted to simulate pipeline gas leakage and investigate the frequency spectrum signatures of AE leak signals. By comparing with the other methods for leak location identification, the feasibility and superiority of the proposed method are verified.