• Smart Structures and Systems
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• v.21 no.5
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• pp.705-713
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• 2018

High-speed rail (HSR) has been in operation and development in many countries worldwide. The explosive growth of HSR has posed great challenges for operation safety and ride comfort. Among various technological demands on high-speed trains, vibration is an inevitable problem caused by rail/wheel imperfections, vehicle dynamics, and aerodynamic instability. Ride comfort is a key factor in evaluating the operational performance of high-speed trains. In this study, online monitoring data have been acquired from an in-service high-speed train for condition assessment. The measured dynamic response signals at the floor level of a train cabin are processed by the Sperling operator, in which the ride comfort index sequence is used to identify the train's operation condition. In addition, a novel technique that incorporates salient features of Bayesian inference and time series analysis is proposed for outlier detection and change detection. The Bayesian forecasting approach enables the prediction of conditional probabilities. By integrating the Bayesian forecasting approach with time series analysis, one-step forecasting probability density functions (PDFs) can be obtained before proceeding to the next observation. The change detection is conducted by comparing the current model and the alternative model (whose mean value is shifted by a prescribed offset) to determine which one can well fit the actual observation. When the comparison results indicate that the alternative model performs better, then a potential change is detected. If the current observation is a potential outlier or change, Bayes factor and cumulative Bayes factor are derived for further identification. A significant change, if identified, implies that there is a great alteration in the train operation performance due to defects. In this study, two illustrative cases are provided to demonstrate the performance of the proposed method for condition assessment of high-speed trains.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1997-2004
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• 1994

A model analysis method has been developed in the paper. The method estimates the modal parameters of multiple input-output systems, assesses their quality, and seperates structural modes form computation ones. The modal parameter extraction algorithm is the least squares method with a finite difference model relating input and output time data. The quality of the estimated system model can be assessed in narrow frequency bands by comparing the measured and model predicted responses in time domain with the aid of digital filters. Structural modes can be effectively separated from computational ones using the convergence factor which represents the pole convergence rate. The modal analysis method has been applied to simulated and experimental vibration data to evaluate its utility and limitations.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.29-36
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• 2004

This paper deals with a fractional model reduction for linear systems with time varying delayed states. A contractive coprime factorization of linear time delayed systems is defined and obtained by solving linear matrix inequalities. Using generalize controllability and observability gramians of tile contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is illustrated.

• Journal of the Ergonomics Society of Korea
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• v.30 no.2
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• pp.365-373
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• 2011

The existing GOMS model overestimates the performance time of mouse activities because it describes them in a serial sequence. However, parallel movements of eye and hand(eye-hand coordination) have been dominant in mouse activities and this eye-hand coordination is the main factor for the overestimation of performance time. In this study, therefore, the revised CGOMSL model was developed to implement eye-hand coordination to the mouse activity to overcome one of the limitations of GOMS model, the lack of capability for parallel processing. The suggested revised CGOMSL model for drag activity, as an example for one of mouse activities in this study, begins visual search processing before a hand movement but ends the visual search processing with the hand movement in the same time. The results show that the revised CGOMSL model made the prediction of human performance more accurately than the existing GOMS model. In other words, one of the limitations of GOMS model, the incapability of parallel processing, could be overcome with the revised CGOMSL model so that the performance time should be more accurately predicted.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.663-671
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• 2008

This paper presents a real-time haptic rendering method for multi-contact interaction with virtual environments. Haptic systems often employ physics-based deformation models such as finite-element models and mass-spring models which demand heavy computational overhead. The haptic system can be designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. A multi-rate output-estimation with an exponential forgetting factor is proposed to implement real-time haptic rendering for the haptic systems with two sampling rates. The computational burden of the output-estimation increases rapidly as the number of contact points increases. To reduce the computation of the estimation, the multi-rate output-estimation with reduced parameters is developed in this paper. Performance of the new output-estimation with reduced parameters is compared with the original output-estimation with full parameters and an exponential forgetting factor. Estimated outputs are computed from the estimated input-output model at a high rate, and trace the analytical outputs computed from the deformation model. The performance is demonstrated by simulation with a linear tensor-mass model.

• Journal of Advanced Navigation Technology
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• v.22 no.4
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• pp.271-278
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• 2018

For ionospheric correction of low earth orbiter (LEO) satellites using single frequency global navigation satellite system (GNSS) receiver, ionospheric scale factor should be applied to the ground-based ionosphere model. The ionospheric scale factor can be calculated by using a NeQuick model, which provides a three-dimensional ionospheric distribution. In this study, the ionospheric scale factor is calculated by using NeQuick G model during 2015, and it is compared with the scale factor computed from the combination of LEO satellite measurements and international GNSS service (IGS) global ionosphere map (GIM). The accuracy of the ionospheric delay calculated by the NeQuick G model and IGS GIM with NeQuick G scale factor is analyzed. In addition, ionospheric delay errors calculated by the NeQuick G model and IGS GIM with the NeQuick G scale factor are compared. The ionospheric delay error variations along to latitude and solar activity are also analyzed. The mean ionospheric scale factor from the NeQuick G model is 0.269 in 2015. The ionospheric delay error of IGS GIM with NeQuick G scale factor is 23.7% less than that of NeQuick G model.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4093-4097
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• 2021

This study presents a new dead-time measurement method using the gamma attenuation law and generalized dead-time models for nuclear gamma-ray detectors. The dead-time of the NaI(Tl) detection system was obtained to validate the new dead-time determination method using very thin lead and polyethylene absorbers. Non-paralyzing dead-time was found to be 8.39 ㎲, and paralyzing dead-time was found to be 8.35 ㎲ using lead absorber for NaI(Tl) scintillator detection system. These dead-time values are consistent with the previously reported dead-time values for scintillator detection systems. The gamma build-up factor's contribution to the dead-time was neglected because a very thin material was used.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.164.1-164.1
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• 2011

Previously, many researchers assessed nearshore wave energy in two ways. The first is a simulation with respect to the offshore wave time series to validate the wave buoy data and the wave model results, and the other is to simulate the representative waves of typical seasonal wave conditions. The former requires enormous computational time and effort. The latter yields inspection on the patterns for the spatial and temporal distribution of nearshore wave energy but tends to underestimates the amount of wave energy in the nearshore region owing to the correlation between the significant wave height and wave period. $\ddot{O}$zger et al. (2004) derived the stochastic wave energy formulation by introducing a correction factor explicitly in terms of the covariance of the wave energy and significant wave height. In this study, a correction factor was applied for the assessment of nearshore wave energy obtained by numerical simulation of wave transformation with respect to representative waves.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.12
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• pp.93-100
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• 2013

This paper propose a method to design the rotor of synchronous reluctance motors(SynRM) for maximum torque and power factor by using DOE(design of experiment) with the design variables which are parameters of barriers and segments. In this process, there are problems that require lots of simulation time and number of simulations when calculating the both torque and power factor using the finite element method in order to find load angle, core loss per speed. In order to improve this problem, we calculate only value of flux linkage by finite element method, and can decrease analysis and the number of analysis time by applying steady state expression of the power factor and torque. Finally, in order to verify the characteristics of optimal model, we make prototype motor and compare with the conventional SynRM. In this experiment, we use the DC current decay test for calculating d-and q-axis inductance.

• The Korea Journal of Herbology
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• v.23 no.4
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• pp.191-196
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• 2008

Objectives: This research was investigated to find out the effect of the anticoagulant Perillae folium extract. Methods: To examine an active effect of anticoagulation in Perillae folium extract, the study measured Prothrombin time(PT) and activated partial thromboplastin time(APTT) of human plasma in vitro and measured bleeding time and arterio-venous shunt model in rats in vivo. Results: Bleeding time of Perillae folium extract in vivo had a significant increase 1.6 times and thrombus weight of Perillae folium extract had a significant reduction of thrombus weight as 68%. Perillae folium extract had an effect of anticoagulation by operating on extrinsic pathway factor II, V, VII, X and intrinsic pathway factor VIII, IX, X, VI, VII in the coagulation system. Conclusions: Considering the above mentioned results, it is judged that a Perillae folium extract has a control effect of thrombus creation.