• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.370-375
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• 2004

This paper proposes an algorithm that estimates three dimensional array shape calibration about the bottom-mounted sensor array. under the assumption that the active sources are in the far-field with unknown positions. Under some assumptions. we calculate the sensor positions via an algebraic solutions of a least squares problem that the linear equations are related to the sensor positions and directions or arrival. We give examples of algorithm performance from both computer simulations and sea test. We also illustrate the performance of sensor positions estimation as a function of time delay estimation variance and the distribution of the localizing sources.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• v.10 no.1
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• pp.103-107
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• 2005

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.11a
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• pp.94-95
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• 2011

선박 엔진 크랭크 케이스 내부의 기계 결함으로 발생하는 윤활 오일 미스트 발생은 폭발뿐만 아니라 급격한 온도와 압력상승으로 2차 폭발을 야기하는 등 큰 피해를 가져와 현재 선박용 엔진의 크랭크 케이스에 오일미스트 검출장치의 설치를 의무화 하고 있는 추세이다. 본 논문에서는 이러한 피해를 줄이기 위하여 광 산란 방식을 이용한 오일 미스트 검출장치를 구현하였으며, 구현된 오일미스트 검출 장치의 오일미스검출 센서 센싱 성능은 전기적, 광학적 그 외 환경적 요인으로 인하여 출력값이 일정하지 못해 각각의 오일미스트 검출 센서를 보정해야 한다. 본 논문에서는 크랭크케이스마다 장착되는 오일미스트 검출 센서의 오차를 최소화하기 위하여 정밀하게 Calibration된 Reference Data를 기반으로 최소자승법을 적용하여 센서를 Calibration하였으며, 그 결과 각각의 오일미스 검출센서의 오차를 기존 방법과 비교하여 최소화할 수 있었다.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1773-1774
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• 2006

나노 기술의 급격한 발달에 따라 나노미터 수준의 정밀도를 갖는 초정밀 측정 기술이 여러 분야에서 요구되고 있다. 헤테로다인 레이저 간섭계를 이용하여 초정밀 위치 측정을 하려고 할 때, 광학기기 자체의 불완전함에서 발생하는 비선형성 오차는 주요한 요소로 작용한다. 본 논문에서는 헤테로다인 레이저 간섭계 시스템에서의 비선형성을 보정해주기 위해 적응형 알고리즘을 제안한다. 기준 입력인 정전용량센서와 최소자승법을 이용하여 보정변수를 구한 후, 반복 최소자승법을 이용하여 비선형성에 따른 타원 위상을 비선형성이 보정된 원 위의 위상으로 사상시킨다.

• Journal of KSNVE
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• v.4 no.1
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• pp.59-69
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• 1994

A new LMS algorithm titled constrained LMS' is proposed for problems with constrained structure. The conventional LMS algorithm can not be used because it destroys the constrained structures of the weights or parameters. Proposed method uses error-back propagation, which is popular in training neural networks, for error minimization. The illustrative examplesare shown to demonstrate the applicability of the proposed algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1B
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• pp.9-20
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• 2012

Recently to overcome limitations of conceptual, hydrological and physics based models for flood stage forecasting, multiple linear regression model as one of data-driven models have been widely adopted for forecasting flood streamflow(stage). The objectives of this study are to compare performance of different multiple linear regression models according to regression coefficient estimation methods and determine most effective multiple linear regression flood stage forecasting models. To do this, the time scale was determined through the autocorrelation analysis of input data and different flood stage forecasting models developed using regression coefficient estimation methods such as LS(least square), WLS(weighted least square), SPW(stepwise) was applied to flood events in Jungrang stream. To evaluate performance of established models, fours statistical indices were used, namely; Root mean square error(RMSE), Nash Sutcliffe efficiency coefficient (NSEC), mean absolute error (MAE), adjusted coefficient of determination($R^{*2}$). The results show that the flood stage forecasting model using SPW(stepwise) parameter estimation can carry out the river flood stage prediction better in comparison with others, and the flood stage forecasting model using LS(least square) parameter estimation is also found to be slightly better than the flood stage forecasting model using WLS(weighted least square) parameter estimation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.1
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• pp.29-39
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• 1989

In this work, a numerical and experimental study was done to get an optimum cam profile considering dynamic characteristics of a cam-valve system. First of all, a four degree of freedom dynamic model was set up for an OHV type cam-valve acceleration while not modifying original cam shape greatly. Also another optimization which aims to enlarge the valve displacement area while reducing the peak valve acceleration, was tried. The optimized cam profile was tested experimentally and found that the measured valve displacement and pushrod force show only very small error from the analytically predicted model simulation results.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.314-323
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• 2016

Overhead line voltage of DC railway traction substations has rising or falling characteristics depending on the acceleration and regenerative braking of the subway train loads. The suppression of this irregular fluctuation of the line voltage gives rise to improved energy efficiency of both the railway substation and the trains. This paper presents parameter estimation schemes using the RC circuit model for an overhead line voltage at a 1500V DC electric railway traction substation. A linear artificial neural network with a back-propagation learning algorithm was trained using the measurement data for an overhead line voltage and four feeder currents. The least square estimation method was configured to implement batch processing of these measurement data. These estimation results have been presented and performance analysis has been achieved through raw data simulation.

• Journal of Radiation Protection and Research
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• v.29 no.3
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• pp.157-163
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• 2004

Atmospheric dispersion modelling has been widely used to predict the fate and transport of radioactive or toxic materials released from nuclear facilities which is an unlikely accidental event. To improve the forecasting performance of the dispersion model, it is required that source rate and dispersion characteristics must be defined appropriately. Generally, source term of the radioactive materials is much uncertain at the early phase of an accidental event. In this study, we computed the source rate with the experimental field data monitored at the Yeoung-Kwang nuclear site and obtained the optimal source rate to minimize the errors between the measured concentrations and the computed ones by the Gaussian plume model. Computed source term showed a good result within 24% of the artificially released source rate.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.56-67
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• 2012

In this thesis, to compensate the sweep nonlinearity occurring in the high resolution radar system using FMICW or FMCW, the method of the estimation of the nonlinearity is proposed. The nonlinear phase component caused by the nonlinear characteristic of the radar system is modelled as a linear combination of the sinusoidal functions consisting of various magnitudes and phases(systematic nonlinear phase error) and a random component(stochastic nonlinear phase error). From two IF signals that are measured respectively independently for two reference point targets lying in different distances which are known, a sparse linear equation is made and solved by least squares method to estimate the nonlinear phase component. The estimated component can be used for predistortion method to compensate the sweep nonlinearity.