• 한국소음진동공학회논문집
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• 제22권10호
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• pp.985-993
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• 2012

In this paper, a new method is proposed to estimate the sound pressure generated from gasoline direct injection (GDI) engine. There are many noise sources as much as components in GDI engine. Among these components, fuel pump, fuel injector, fuel rail, pressure pump and intake/exhaust manifolds are major components generated from top of the engine. In order to estimate the contribution of these components to engine noise, the total sound pressure at the front of the engine is estimated by using airborne source quantification (ASQ) method. Airborne source quantification method requires the acoustic source volume velocity of each component. The volume velocity has been calculated by using the inverse method. The inverse method requires many tests and has ill-condition problem. This paper suggested a method to obtain volume velocity directly based on the direct measurement of sound intensity and particle velocity. The method is validated by using two known monopole sources installed at the anechoic chamber. Finally the proposed method is applied to the identification and contribution of noise sources caused by the GDI components of the test engine.

• 대한기계학회논문집A
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• 제27권9호
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• pp.1499-1507
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• 2003

Physical importance of cutting temperatures has long been recognized. Cutting temperatures have strongly influenced both the tool life and the metallurgical state of machined surfaces. Temperatures in drilling processes are particularly important, because chips remain in contact with the tool for a relatively long time in a hole. Tool temperatures tend to be higher in drilling processes than in other in machining processes. This paper concerns with modeling of thermal behaviors in drilling processes as well as estimation of the cutting temperature distribution based on remote temperature measurements. One- and two-dimensional estimation problems are proposed to analyze drilling temperatures. The proposed thermal models are compared with solutions of finite element methods. Observer algorithms are developed to solve inverse heat conduction problems. In order to apply the estimation of cutting temperatures, approximation methods are proposed by using the solution of the finite element method. In two-dimensional analysis, a moving heat source according to feedrate of the drilling process is regarded as a fixed heat source with respect to the drilling location. Simulation results confirm the application of the proposed methods.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.1044-1049
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• 2001

Classical deconvolution methods for source identification following linear filtering can only be used if the transfer function of the system is known. For many practical situations, however, this information is not accessible and/or is time varying. The problem addressed here is that of reconstruction of the original input from only the measured signal. This is known as 'blind deconvolution'. By using Higher Order Statistics (HOS), the restoration of the input signal is established through the maximisation of higher order moments (cumulants) with respect to the characteristics of the signals concerned. This restoration is achieved by constructing an inverse filter considering the choice of the initial inverse filter type. As a practical application, an experimental verification is carried out for the restoration of our impacting signal arising in the response of a cantilever beam with an end stop when randomly excited.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.385-389
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• 2003

In this paper, an improved technique for multiresolutive reconstruction of magnetoencephalography (MEG) source distribution is proposed. Using the proposed technique, focal solution with higher energy density can be reconstructed. Moreover, the proposed approach is very easy to implement compared to conventional ones. The usefulness of the proposed technique is verified by the application to a real brain model.

• 한국자동차공학회논문집
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• 제16권2호
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• pp.18-28
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• 2008

In inverse acoustic problem with nearfield sources, it is important to separate multiple acoustic sources and to measure the position of each target. This paper proposes a new algorithm by applying MUSIC(Multiple Signal Classification) to the outputs of discrete wavelet transformation with sub-band selection based on the entropy threshold, Some numerical experiments show that the proposed method can estimate the more precise positions than a conventional MUSIC algorithm under moderately correlated signal and relatively low signal-to-noise ratio case.

• ETRI Journal
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• 제34권5호
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• pp.684-689
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• 2012

A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

• ETRI Journal
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• 제42권6호
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• pp.932-942
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• 2020

To recover the neural activity from Magnetoencephalography (MEG) and Electroencephalography (EEG) measurements, we need to solve the inverse problem by utilizing the relation between dipole sources and the data generated by dipolar sources. In this study, we propose a new approach based on the implementation of a particle filter (PF) that uses minimum sampling variance resampling methodology to track the neural dipole sources of cerebral activity. We use this approach for the EEG data and demonstrate that it can naturally estimate the sources more precisely than the traditional systematic resampling scheme in PFs.

• 대한의용생체공학회:의공학회지
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• 제29권4호
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• pp.329-336
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• 2008

Recently, causality analysis of source time series extracted from EEG or MEG signals is becoming of great importance in human brain mapping studies and noninvasive diagnosis of various brain diseases. Two approaches have been widely used for the analyses: one is independent component analysis (ICA), and the other is multiple signal classification (MUSIC). To the best of our knowledge, however, any comparison studies to reveal the difference of the two approaches have not been reported. In the present study, we compared the performance of the two different techniques, ICA and MUSIC, especially focusing on how accurately they can estimate and separate various brain electrical signals such as linear, nonlinear, and chaotic signals without a priori knowledge. Results of the realistic simulation studies, adopting directed transfer function (DTF) and Granger causality (GC) as measures of the accurate extraction of source time series, demonstrated that the MUSIC-based approach is more reliable than the ICA-based approach.

• 한국컴퓨터정보학회논문지
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• 제17권8호
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• pp.51-60
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• 2012

역 RZ 부호로 코딩된 하향신호의 재변조를 이용한 5Gbps/1.25Gbps WDM/TDM 하이브리드 PON 구조를 제안하고, 매트랩을 이용한 모의실험을 통하여 성능을 분석한다. 모의실험을 통하여 OLT와 ONU간 거리가 10km이고 오차율이 $10^{-9}$일 경우OLT에서의 광송신출력이 각각 -3.8, -0.9dBm 이상이면 OLT에 있는 1개의 OLT가 각각 8, 16개의 ONU와 접속이 가능함을 알 수 있다. 제안된 WDM/TDM 하이브리드 PON 시스템은 일반적인 TDM PON에서 ONU 수에 비례하여 시분할로 다중된 상향채널의 속도가 증가하게 되어 가입자에서 송신하는 상향채널의 데이터 속도가 제한을 받을 수 있는 문제점을 해결할 수 있고, ONU에서 광원 및 OLT에서 광파장 제어회로를 제거할 수 있어 비대칭 광가입자망에 유용한 방식임을 알 수 있다.

• 한국초전도학회:학술대회논문집
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• 한국초전도학회 2003년도 High Temperature Superconductivity Vol.XIII
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• pp.59-59
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• 2003