• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.395-396
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• 2017

차세대 고속 이동수단에 필요한 고전력 전동기에 대한 관심이 꾸준히 증가하는 추세이다. 본 논문에서는 고전력 동기전동기(PMSM) 구동에 필요한 전력 인버터의 제어 및 센서리스 제어기법을 적용한 자속 기준 제어(Field-oriented control)를 시뮬레이션을 통해 입증하였다. 고전력에서 인버터 스위치의 전력부담을 줄이기 위해 3-레벨 인버터를 설계하고, 벡터 제어 SVPWM 방식을 적용하였으며 고전력 및 고속 PMSM의 파라미터에 맞추어 센서리스(sensorless) 제어기를 설계하였다. 센서리스 제어에는 모델 기준 적응 시스템(MRAS)을 통해 속도 및 위치를 예측하여 모터를 제어하는 방식을 적용하였다. 가속시 5초간 가가속도 값을 적용하여 필요 토크 및 속도제어를 Matlab/Simulink에서 설계 및 구현하고, 예측속도와 실제 모터속도는 최대 0.01 rad의 오차를 나타났고, 67초 동안 목표 속도 500 rad/s까지 가속함을 확인하였다.

• Tunnel and Underground Space
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• v.16 no.2 s.61
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• pp.166-178
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• 2006

Recently, the frequency of occurring dynamic events such as earthquakes, explosives blasting and other types of vibration has been increasing. Besides, the chances of exposure for rock discontinuities to free faces get higher as the scale of rock mass structures become larger. For that reason, the frictional behavior of rock joints under dynamic conditions needs to be investigated. In this study, artificially fractured rock joint specimens were prepared in order to examine the dynamic frictional behavior of rough rock joint. Roughness of each specimen was characterized by measuring surface topography using a laser profilometer and a series of shaking table tests was carried out. For mated joints, the static friction angle back-calculated ken the yield acceleration was $2.7^{\circ}$ lower than the tilt angle on average. The averaged dynamic friction angle for unmated joints was $1.8^{\circ}$ lower than the tilt angle. Displacement patterns of sliding block were classified into 4 types and proved to be related to the first order asperity of rock joint. The tilt angle and the static friction angle for mated joints seem to be correlated to micro average inclination angle which represents the second order asperity. The tilt angle and the dynamic friction angle for unmated Joints, however, have no correlation with roughness parameters. Friction angles obtained by shaking table test were lower than those by direct shear test.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1221-1229
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• 2014

This paper proposes an approach for predicting the fatigue life of a propeller shaft of a forklift truck by an accelerated life test method. The accelerated life test method adopted in this study is the calibrated accelerated life test, which is highly effective in the prediction of the lifetime and enables significant reduction of the test time as well as a quantification of reliability in the case of small sample sizes. First, the fatigue test was performed under two high stress levels, and then, it was performed by setting low stress levels in consideration of the available test time and extrapolation. Major reliability parameters such as the lifetime, accelerated power index, and shape parameter were obtained experimentally, and the experimentally predicted lifetime of the propeller shaft was verified through comparison with results of an analysis of load spectrum data under actual operating conditions.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.2
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• pp.42-50
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• 2012

The goal of heat transfer studies is the accurate prediction of temperature and heat flux distribution on material boundaries. To this purpose, general-purpose computational fluid dynamics(CFD) code is used : FLUENT. Mass fluxes and pressure ratio are calculated for two types of nozzle. The comparative studies reveal that the computational results are in agreement with the experimental data. Also, heat transfer coefficients from FLUENT for one type of nozzle are very similar and agree well with the experimental data in the diverging part of the nozzle, but the calculated results are large in the converging part. The heat transfer coefficients from Bartz equation are over-predicted. We can consider various reasons for these differences, i.e., laminarization by the highly accelerated flow in the nozzle, turbulent flow model and grid generation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.3
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• pp.266-272
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• 2004

In this paper, an observer-based adaptive controller is proposed to control the longitudinal motion of vehicles. The standard gradient method will be used to estimate the vehicle parameters such as mass, time constant, etc. The nonlinear model between the driving force and the vehicle acceleration will be chosen to design the state observer for the vehicle velocity and acceleration. It will be shown that the proposed observer is exponentially stable, and that the adaptive controller proposed in this paper is stable by the Lyapunov function candidate. It will be proved that the errors of the relative distance, velocity and acceleration converge to zero asymptotically fast, and that the overall system is also asymptotically stable. The simulation results are presented to investigate the effectiveness of the proposed method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.529-536
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• 2019

In this paper, the signals of the sensor for extracting characteristic parameters of the rotor are collected and the performance of the extraction technique is analyzed. To this end, a vibration test league was developed for conducting model tests to analyze the signal characteristics under normal operation. As a result, it is judged that no change in the measured the raw data amplitude will occur in the acceleration sensor with the unbalanced mass measured from the acceleration sensor. Performing FFT showed a significant increase in amplitude of the rotational frequency of 20 Hz as the unbalanced mass increased. The analysis results according to the change in the unequal mass of the speed sensor also showed a significant increase in the 1X Harmonics component, such as the acceleration sensor. There was no change in the amplitude of the acceleration sensor data when the misalignment occurred, and for the Envelope data, the amplitude of 2X (40 Hz) was increased depending on the degree of misalignment. The velocity sensor at change of misalignment also showed similar results to the acceleration sensor, and the peak was reduced at 600 Hz as the load increased in the frequency spectrum.

• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.1
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• pp.37-45
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• 2012

In an effort to further exploit the peak ground-motion acceleration (PGA) information per second available in real time by the enacted law, bracketed summations of the PGA per second ($BSPGA_k$) for 30 seconds based on the records with a rate of 100 samples were compared with the cumulative absolute velocity (CAV) and earthquake intensities based on a worldwide database of records from small-to-large earthquakes. The CAV, currently in use as an earthquake damage indicator for nuclear power plants due to its strong correlation with the earthquake intensity, has the disadvantage of requiring a massive amount of digital data with a rate of more than 100 samples per second. The comparative study shows that the $BSPGA_k$ is well correlated with the CAV over the wide range of strong ground-motion levels, which suggests that the $BSPGA_k$ is one of the new promising ground-motion parameters especially useful for rapid earthquake alert notifications through an earthquake monitoring network. Based on the domestic database of records from small-to-moderate earthquakes with felt reports, it is also observed that the $BSPGA_k$ is comparable to the CAV and better than the PGA in predicting the intensity by using the correlation relation.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.76-83
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• 2022

With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.11
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• pp.1315-1321
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• 2013

This study presents a prognostic technique for the damage state of a ball bearing. A stochastic bearing fatigue defect-propagation model is applied to estimate the damage progression rate. The damage state and the time to failure are computed by using RMS data from noisy acceleration signals. The parameters of the stochastic defect-propagation model are identified by conducting a series of run-to-failure tests for ball bearings. A regularized particle filter is applied to predict the damage progression rate and update the degradation state based on the acceleration RMS data. The future damage state is predicted based on the most recently measured data and the previously predicted damage state. The developed method was validated by comparing the prognostic results and the test data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.516-518
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• 2022

In this paper, we introduce a dependence of number of nodes of hidden-layer in fall detection system using Long Short-Term Memory that can detect falls. Its training is carried out using the parameter theta(θ), which indicates the angle formed by the x, y, and z-axis data for the direction of gravity using a 3-axis acceleration sensor. In its learning, validation is performed and divided into training data and test data in a ratio of 8:2, and training is performed by changing the number of nodes in the hidden layer to increase efficiency. When the number of nodes is 128, the best accuracy is shown with Accuracy = 99.82%, Specificity = 99.58%, and Sensitivity = 100%.