• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.917-923
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• 2002

KITECH and ODS performed a study of internal and external noise prediction of the KHST test train. The object of this study was 3 kind of cars; trailer car(TT2), motorized car(TM1) and power car(TP1) and the predicted noise was calculated for the two different driving speeds in free field and tunnel conditions. Data of carbody design and noise sources were delivered from each manufactures. Some of noise sources which were not available in project team, were chosen by experiences of ODS. Internal noise level of each car were predicted for two cases i.e, at 300 km/h and 350 km/h. In addition sound transmission path and dominant noise sources were also investigated of each section of car, which is circular shell typed part of whole carbody. In case of TT2, the dominating sound transmission path is floor in terms or structure-borne noise and air-borne noise. The main noise sources are structure-borne noise from the yaw-damper and air-borne noise from the wheel/rail contact, whereas the dominating sound transmission path of TM1 are floor and sidewall below the window in terms of structure-borne noise. The main noise sources of TM1 are structure-borne noise from motor/gear unit and the yaw-damper in the free field, and air-borne noise from the wheel/rail contact and structure-borne noise from motor/gear unit in the tunnel. Through the external noise prediction for the KHST test train formation, the noise form the wheel/rail contact is estimated as one of the major sources. In addition, the noise specification of sub-component was proposed for managing each sub-surpplier to reach the KHST noise requirement. The specification provide the sound power of machinery part and transmission loss of component of carbody structure. The predicted noise level in each case exceeded the required limit. Through this study, the noise characteristics of the test train were investigated by simulation, and then the actual test will be performed in near future. Both measured and calculated data will be compared and further work for noise reduction will be continued.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.703-709
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• 2023

It is most desirable to train with a real crane in an environment similar to that of a port for crane operation training in charge of loading and unloading in a port, but it has time and space limitations and cost problems. In order to overcome these limitations, VR(Virtual Reality) based crane training programs and related devices are receiving a lot of attention. In this paper, we designed and implemented a VR-based harbor crane simulator operating on an HMD. The simulator developed in this paper consists of a crane simulator program that operates on the HMD, an IoT driving terminal that processes trainees' crane operation input, and a training server that stores trainees' training information. The simulator program provides VR-based crane training scenarios implemented with Unity3D, and the IoT driving terminal developed based on Arduino is composed of two controllers and transmits the user's driving operation to the HMD. In particular, the crane simulator in this paper uses a training server to create a database of environment setting values for each educator, progress and training time, and information on driving warning situations. Through the use of such a server, trainees can use the simulator in a more convenient environment and can expect improved educational effects by providing training information.

• Journal of the Korean Society for Railway
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• v.13 no.2
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• pp.173-178
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• 2010

Electric railroad systems consist of supply system of electric power and electric locomotive. The electric locomotive is adapted to high speed driving and mass transportation due to obtaining high traction force. The electric locomotive is operated by motor blocks and traction motors. Train speed is controlled by suppling power from motor blocks to traction motors according to reference speed. Speed control of the electric locomotive is efficient by spending minimum energy between motor blocks and traction motors. Recently, induction motors have been used than DC and synchronized motors as traction motors. Speed control of induction motors are used by vector control techniques. In this paper, speed of the induction motor is controlled by using the vector control technique. Control system model is presented by using Simulink. Pulse is controlled by PI and hysteresis controller. IGBT inverter is used for real-time control and system performance is demonstrated by simulating the induction motor which has 210[kW] on the output power.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.68-72
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• 2015

The railway system has been recognized as one of the best eco-friendly advanced transportation systems. Furthermore, the improvement of the passenger transportation quality and the energy saving have been studied for being the most competitive transportation system. However, most of the studies have been mainly focused on the improvement of the transportation efficiency and energy saving because of the characteristics of the urban railway which serves the unspecified multiple passengers. In this paper, the 3-dimensional vibratory lateral acceleration has been measured in various environments for the automatic and manual operation modes of the general train and express train in the urban railway lines. In terms of the improvement of the passenger transportation quality, the comparison analysis of the ride quality is carried out based on the measured 3-dimensional vibratory lateral acceleration and the statistical techniques of UIC513R suggested by the International Union of Railways.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.1
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• pp.89-99
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• 2014

This paper presents the experimental torque disturbance analysis of a missile hatch system by spline backlash. The missile hatch system uses a spline and gear train for vertical elevation of the heavy hatch. The spline used for the rotation shaft of the hatch is generally used for automotive driving parts that transmit high amounts of power. It has an angular backlash, which results in jerks. Backlash of the hatch spline influences hatch swinging. The spline backlash and hatch swing are experimentally analyzed by measuring the hatch's rotation angle and acceleration. Hatch swing is visually observable for a short period, and it is measured by measuring the rotation angle variation and hatch acceleration. The shape of fluctuation and duration time of hatch angle variation are similar to those of torque. This shows that the hatch swing due to spline backlash generates torque disturbances.

• Transactions of the KSME C: Technology and Education
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• v.5 no.2
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• pp.115-126
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• 2017

This paper proposes an accelerated life evaluation of drive shaft for the power train parts of special purpose vehicle. It is necessary the real load data of usage level driving load condition for life evaluation of power train parts, but we can't get the load spectrum data for evaluation in many case of special purpose vehicle. So, in this paper, the road load spectrum data for evaluation is created by modeling and simulation based on vehicle data and special road condition. The inverse power model is used for accelerated life test. The equivalent torque of load spectrum is achieved using the Miner's Rule. This paper also proposes the calibrated acceleration life test method for drive shaft. The fatigue test is performed through three stress levels. The lifetime at normal stress level is predicted by extrapolation, and is verified through comparison of experimental results and load spectrum data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.632-638
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• 2019

This paper presents the conceptual design and reaction force analysis of a bogie structure for an inter-modal automated transportation system, including road and rail transportation. The proposed system was based on a train with rotation-aligning bogie mechanism that can save significant time and cost. One of the critical issues in conceptual design is the lateral forces applied to the rail caused by the characteristic shapes and structure of the rails and bogie. In particular, the lateral forces are significant in the transition section between the driving and platform sections. This paper provides design guidance for the transition section through reaction force analysis. Based on the analysis result, it was confirmed that the proposed concept can be a valid design candidate of a practical system, and the radius of the rail and the distance between rails are major factors for reaction force generation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• Structural Engineering and Mechanics
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• v.82 no.1
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• pp.1-16
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• 2022

This work elaborately investigates the influences of the guideway geometry parameters and track irregularity on the dynamic performances of the suspended monorail vehicle-guideway system (SMVGS). Firstly, a spatial dynamic analysis model of the SMVGS is established by adopting ANSYS parameter design language. Then, the dynamic interaction between a vehicle with maximum design load and guideway is investigated by numerical simulation and field tests, revealing the vehicle-guideway dynamic features. Subsequently, the influences of the guideway geometry parameters and track irregularity on the dynamic performances of the SMVGS are analyzed and discussed in detail, and the reasonable ranges of several key geometry parameters of the guideway are also obtained. Results show that the vehicle-guideway dynamic responses change nonlinearly with an increase of the guideway span, and especially the guideway dynamic performances can be effectively improved by reducing the guideway span; based on a comprehensive consideration of all performance indices of the SMVGS, the deflection-span ratio of the suspended monorail guideway is finally recommended to be 1/1054~1/868. The train load could cause a large bending deformation of the pier, which would intensify the car-body lateral displacement and decrease the vehicle riding comfort; to well limit the bending deformation of the pier, its cross-section dimension is suggested to be more than 0.8 m×0.8 m. The addition of the track irregularity amplitude has small influences on the displacements and stress of the guideway; however, it would significantly increase the vehicle-guideway vibrations and rate of load reduction of the driving tyre.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.