• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.174.3-174
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• 2001

Electric power collection is one of the most important factors for the high-speed trains' operation. For the stable current collection, the contact wire of a catenary and the panhead of a pantograph should maintain a constant contact each other. In this paper, the catenary was modeled as a spring with time-varying stiffness from the point of a pantograph moving along the catenary, and the pantograph was modeled as a 3-D.O.F. mass-spring-damper system. Using the adaptive control method, the desired control performance could be obtained with the modeling errors and the time varying parameters. Also the state estimator was used considering the difficulty of applying the sensors obtaining feedback signals. Simulations were accomplished in various ...

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.123-131
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• 1996

This paper presents the development of an algorithm for the reliability and life of a hypoid gear axle system (located in the last section of power train) in heavy vehicles. The algorithm is developed about expecting the reliability and service-life for applied loads on each component in the system using the Weibull's probabilistic distribution and the extended Palmgren's model. The probabilistic method is used to results. Also this model is involved in predicting the failure which is related to the number of load cycles with the approaching load. Then the precious evaluation of the reliability and life in the axle system can be effectively carried out. Thus the general procedures of a reliability and life design, including the mathematical formulation and numerical examples, are illustrated for a hypoid gear axle system.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.53.4-53.4
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• 2019

We reconstruct the underlying dark matter (DM) density distribution of the local universe within 20Mpc/h cubic box by using the galaxy position and peculiar velocity. About 1,000 subboxes in the Illustris-TNG cosmological simulation are used to train the relation between DM density distribution and galaxy properties by using UNet-like convolutional neural network (CNN). The estimated DM density distributions have a good agreement with their truth values in terms of pixel-to-pixel correlation, the probability distribution of DM density, and matter power spectrum. We apply the trained CNN architecture to the galaxy properties from the Cosmicflows-3 catalogue to reconstruct the DM density distribution of the local universe. The reconstructed DM density distribution can be used to understand the evolution and fate of our local environment.

• Journal of Drive and Control
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• v.17 no.1
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• pp.1-12
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• 2020

This study was to develop a simulation model of a compound planetary gear reducer for the final driving shaft using a gear analysis software (KISSsoft, Version 2017, KISSsoft AG, Switzerland). The aim of this study is to analyze transmission error and the tooth load distribution through micro-geometry using the simulation model. The tip and root relief were modified with Micro-geometry in the profile direction, and crowning was modified with Micro-geometry in the lead direction. The transmission error was analyzed using the PPTE (Peak to Peak Transmission Error) value, and the tooth load distribution was analyzed for the concentrated stress on the tooth surface. As a result of modifying tip and relief in the profile direction, the transmission error was reduced up to 40.7%. In the case of modifying crowning in the lead direction, the tooth load was more evenly distributed than before and decreased the stress on the tooth surface. After modifying the profile direction for the 1st and 2nd planetary gear train, the bending and contact safety factors were increased by 31.7% and 17%, and 18.3% and 12.5% respectively. Moreover, the bending and safety factors after modifying lead direction were increased by 59.5% and 32.7%, respectively for the 1st planetary gear train, and 59.6% and 43.6%, respectively for the 2nd planetary gear train. In future studies, the optimal design of a compound planetary gear reducer for the final driving shaft is needed considering both the transmission error and tooth load distribution.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.303-311
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• 2017

Safety accidents in railway work continue to increase every year; Engineer's negligence, trackside worker's sensory deprivation and signalman's mistake are the main reasons of such incidents. We consider this problem by far the most urgent matter in railway work because of its steady increase and risk of taking a person's life. Based on that account, a new alarm system has developed, that is called Railway Access Alarm System, to allow railway workers to sense the access of trains with not only vision, but also hearing. The detector device of this system is installed on both sides of the track locating 1.5km from the workplace. When the train enters the place, the detector device can sense the entering, sending the detect sign of train to the alarm unit, then the alarm unit warns the workers by the LED lighting and sirens. This system has several advantages compared to previous systems. First, it recognizes the train at a long distance. Secondly, there is no need for wiring work since it is a wireless system. At last, the system works by rechargeable batteries and solar charger so that it is installed in the work places where there is no external power supply. Moreover, it is proven that the system is 100% reliable by the successful on-the spot inspection evaluating the capability.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.47-53
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• 2011

The Electric Multiple Unit (EMU) has many types of door system such as sliding door, plug door etc.al. according to customer's requirements. The sliding door is widely used in Korea but has weak point in the noise problem. In the low operation speed, the noise coming from outer side of the EMU is not an important factor. As the speed is higher than before, noise is increased and make a problem. The main cause of noise is the imperfect air tightness in the EMU. The plug door system has advantages for the noise reduction characteristic in the high speed area. We have been developing electric plug-in door. The door is controlled by Door Control Unit(DCU) following the order of Automatic Train Protection (ATP) that is a kind of train signalling system. DCU has to simultaneously open and close the doors and the operation of it is related to the passengers safety. So DCU is a safety device that is important to reliability and safety. DCU is composed of several devices of control, motor driving, Input/Output, communication and power. In this paper, we will describe the functions, characteristic, requirement, subsystem and test results of DCU used for the electric plug-in door.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.293-302
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• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.150-158
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• 2016

This paper is on a design of a new balise system which has a new functional part of a micro-power inductive wireless loop vehicle detector. The field test has processed and the data has analyzed for check the solar energy operable ability of the detect data interconnect sub-system which includes repeaters and field controllers. Instead of a railroad environment, 12 individual parking-lots are used for field test environment. As a result, in the condition of the designed system and the test environment, it is assumed that under 200 passing vehicles(train or tram) per day can be processed only with solar energy.

• The KSFM Journal of Fluid Machinery
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• v.19 no.3
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• pp.14-18
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• 2016

The power generation system using cold energy, which evolves in a large amount during the vaporization process of the liquefied natural gas, was designed in favor of the Rankine cycle with a mixed refrigerant as the working fluid. In this study it is intended to identify the allowable limits of the working fluid composition in respect of equipment safety in the Rankine cycle-type power generation system driven by the cold energy. The thermodynamic properties of the working fluid, which is a hydrocarbon mixture, were calculated with the Peng-Robinson model. In the steady state simulation of the power generation system by using a commercial tool Aspen HYSYS, the feed conditions of LNG Test Bed Train No.1 along with some necessary assumptions were incorporated. The results indicated that deterioration of the mechanical performance of the equipment as well as its safety would be brought about if contents of $C_2H_6$ and $C_3H_8$ in the mixture become, respectively, too high or too low.