• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.553-558
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• 2003

The boundary estimation problem is used to estimate the shape of organic depend on the phase of the cardiac cycle or interested in the detection of the location and size of anomalies with resistivity values different from the background tissues such as nuclear reactor. And we can use the method to solve the optimal solution such as modified Newton raphson, kalman filter, extended kalman filter, etc. But, this method consumes much time and is sensitive to the initial value and noise in the estimation of the unknown shape. In the paper, we propose that multi-layer neural networks estimate the boundary of the unknown object using Fourier coefficient. This method can be used at the real time estimation and have strong characteristics at the noise and initial value. It uses voltage change; difference the homogeneous voltage to the non-homogeneous voltage, and change of Fourier coefficient change to train multi-layer neural network. After train, we can have real time estimation using this method.

• 대한임베디드공학회논문지
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• 제14권6호
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• pp.347-353
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• 2019

Electric-hydraulic sever cylinders are used in many offshore applications such as wind energy farms, solar farms and plants. Jack-up barges are often used for these offshore system operations. Jack-up barge control is up/down by hydraulic cylinder position control. Working in harsh environments can lead to changes in internal parameters. This nonlinearity makes precise control difficult. In order to overcome the problems, we proposed a method of unknown-parameter estimation algorithm based on measurements obtained by system. In this paper, we employee Unscented Kalman filter (UKF) to estimate states and unknown-parameter from augmented nonlinear equation. Performance of estimation results is verified in simulation on an environments of Matlab. The estimation results of the state and unknown-parameter show that the estimation error of unknown-parameter is reduced according to decreasing the state estimation error.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제2B권3호
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• pp.125-132
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• 2002

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

• 한국지하수토양환경학회지:지하수토양환경
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• 제8권2호
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• pp.70-77
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• 2003

유해유기물질의 미생물 분해시 일어나는 총괄반응을 이론적으로 예측하는 방법을 기술하였다. 열역학적 이론을 바탕으로 하는 반쪽반응 방법을 사용하,였고, 최근에 도입된 이론들인 중간체 생성 반응, oxygenation반응, 그룹이론에 의한 표준 자유생성에너지 예측기법 등을 적용하였다. 대표적인 유해유기물질인 phenanthrene과 함께 glucose, hexadecane의 미생물 분해 반응식을 실제로 계산하였다. 예측된 총괄반응식을 이용하여 미생물 수율, 산소 요구량, 질소 요구량, 무기화율 등의 정보를 얻을 수 있었으며, 이는 오염된 지하수/토양의 생물복원 공법 설계 및 자연정화평가 등에 유용하게 적용될 수 있을 것으로 기대한다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2019년도 추계학술대회
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• pp.70-72
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• 2019

For the safe and reliable operation of Lithium-ion batteries in Electric Vehicles (EVs) or Energy Storage Systems (ESSs), it is essential to have accurate information of the battery such as State of Charge (SOC). Many kinds of different techniques to estimate the SOC of the batteries have been developed so far such as the Kalman Filter. However, when it is applied to the multiple number of batteries it is difficult to maintain the accuracy of the estimation over all cells due to the difference in parameter value of each cell. Moreover the difference in the parameter of each cell may become larger as the operation time accumulates due to aging. In this paper a novel Deep Neural Network (DNN) based SOC estimation method for multi cell application is proposed. In the proposed method DNN is implemented to learn non-linear relationship of the voltage and current of the lithium-ion battery at different SOCs and different temperatures. In the training the voltage and current data of the Lithium battery at charge and discharge cycles obtained at different temperatures are used. After the comprehensive training with the data obtained with a cell resulting estimation algorithm is applied to the other cells. The experimental results show that the Mean Absolute Error (MAE) of the estimation is 0.56% at 25℃, and 3.16% at 60℃ with the proposed SOC estimation algorithm.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.702-708
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• 2019

This paper deals with break size estimation of loss of coolant accidents (LOCA) using a nonlinear autoregressive with exogenous inputs (NARX) neural network. Previous studies used static approaches, requiring time-integrated parameters and independent firing algorithms. NARX neural network is able to directly deal with time-dependent signals for dynamic estimation of break sizes in real-time. The case studied is a LOCA in the primary system of Bushehr nuclear power plant (NPP). In this study, number of hidden layers, neurons, feedbacks, inputs, and training duration of transients are selected by performing parametric studies to determine the network architecture with minimum error. The developed NARX neural network is trained by error back propagation algorithm with different break sizes, covering 5% -100% of main coolant pipeline area. This database of LOCA scenarios is developed using RELAP5 thermal-hydraulic code. The results are satisfactory and indicate feasibility of implementing NARX neural network for break size estimation in NPPs. It is able to find a general solution for break size estimation problem in real-time, using a limited number of training data sets. This study has been performed in the framework of a research project, aiming to develop an appropriate accident management support tool for Bushehr NPP.

• 한국방사선학회논문지
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• 제3권3호
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• pp.23-25
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• 2009

Gd-157 material has very large neutron capture cross section in the thermal region. So it is very useful to shield material for thermal neutrons. Futhermore, in the neutron capture experiment and calculation, the neutron absorption and scattering are very important. Especially these effects are conspicuous in the resonance energy region and below the thermal energy region. In the case of very narrow resonance, the effect of scattering is to be more considerable factor. In the present study, we obtained energy dependent neutron absorption ratios of natural indium in energy region from 0.003 to 100 keV by MCNP-4B Code. The coefficients for neutron absorption was calculated for circular type and 1 mm thickness. In the lower energy region, neutron absorption is larger than higher region, because of large capture cross section (1/v). Furthermore it seems very different neutron absorption in the large resonance energy region. These results are very useful to decide the thickness of sample and shielding materials.

• 신재생에너지
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• 제7권3호
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• pp.36-45
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• 2011

Prediction of demand for workforce in new and renewable energy is precondition for sustainable growth of an industry. The purpose of this research is to review prediction methods and case studies of workforce in new and renewable energy industry. This research compares the three methods in the focused on possibility of applying in renewable energy industry; survey, input-output and labor function estimation methods. Also, three cases are reviewed in the focused on applied method; Korea, America and Australia. As a result, the survey method was wildly used in the new and renewable industry. Also the improvement rates of work force are difference depending on the methodology. This result can be applied to set up the policy of human resource development of renewable energy.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.263-263
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• 2007

In the future, self-contained sensors and processing units will need on-board, renewable power supplies to be truly autonomous. One way of supplying such power is through energy harvesting, processes by which ambient forms of energy are converted into electricity. One energy harvesting technique involves converting kinetic energy, in the form of vibrations, into electrical energy through the use of piezoelectric materials. Researchers are currently investigating how piezoelectric materials can be used to harvest power. This study examines the use of auxiliary structures, consisting of a mechanical fixture and a lead zirconate/lead titanate (PZT) piezoelectric element, which can be attached to any boundary conditions vibrating beam of the any boundary conditions. Adjusting various boundary conditions of these structures can maximize the strain induced in the attached PZT element and improve power output.

• 대한기계학회논문집A
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• 제29권8호
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• pp.1132-1138
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• 2005

Fatigue life of metal material can be predicted by the use of fracture theory and experimental database. Although prediction of fatigue life of rubber material uses the same way as metal, there are many reasons to make it almost impossible. One of the reasons is that there is not currently used fracture criteria for rubber material beacuse of non-standardization, various way of composition process of rubber and so on. Tearing energy is one of the fracture criteria which can be applied to a rubber. Even if tearing energy relaxes the restriction of rubber composition, it is also not currently used because of complication to apply in. Research material about failure process of rubber and tearing energy was reviewed to define the process of fatigue failure and the applicability of tearing energy in estimation of fatigue life for rubber. Also, 1file element formulation of tearing energy which can be used in FE analysis was developed.