• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.40-45
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• 2014

This paper suggests the optimal generation dispatch algorithm for ensuring voltage stability margin considering high wind energy injection. Generally, with wind generation being installed into the power system, we would have to consider several factors such as the voltage stability margin because wind turbine generators are mostly induction machines. If the proportion of wind generation increases in the power system increases this would affect the overall stability of the system including the voltage stability. This paper considers a specific system that is composed of two areas: area 1 and area 2. It is assumed that generation cost in area 1 is relatively higher than that in area 2. From an economic point of view generation in area 1 should be decreased, however, in the stability point of view the generation in area 2 should be decreased. Since the power system is a nonlinear system, it is very difficult to find the optimal solution and the genetic algorithm is adopted to solve the objective function that is composed of a cost function and a function concerned with voltage stability constraints. For the simulations, the New England system was selected. The algorithm is implemented and Python 2.5.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.502-502
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• 2007

A catenary system should be designed to have an uniform elasticity over a span in order to maintain the lowest possible loss of contact between a pantograph and a contact wire. A elasticity uniformity of a catenary can be regarded as a important design factor used for predicting the current collection performance for a catenary. There are a couple of formulas to calculate the degree of elasticity uniformity of a catenary according to the literature survey. The effectiveness of these formulas is reviewed by performing catenary elasticity and loss of contact analysis for various different configurations of catenary systems using a beam element based FEM program. The results reveals that these formulas are not suitable to predict the current collection performance for a catenary. Therefore, a new formula based on the standard deviation of the elasticity over a span is proposed in this study. The analysis results show that the new formula for an elasticity uniformity of a catenary is very effective in predicting the current collection performance for a catenary.

• Geophysics and Geophysical Exploration
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• v.23 no.4
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• pp.230-242
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• 2020

We performed a magnetotelluric (MT) survey to delineate the geological structures below the depth of 20 km in the Gyeongju area where an earthquake with a magnitude of 5.8 occurred in September 2016. The measured MT data were severely distorted by electrical noise caused by subways, power lines, factories, houses, and farmlands, and by vehicle noise from passing trains and large trucks. Using machine-learning methods, we classified the MT time series data obtained near the railway and highway into two groups according to the inclusion of traffic noise. We applied three schemes, stochastic gradient descent, support vector machine, and random forest, to the time series data for the highspeed train noise. We formulated three datasets, Hx, Hy, and Hx & Hy, for the time series data of the large truck noise and applied the random forest method to each dataset. To evaluate the effect of removing the traffic noise, we compared the time series data, amplitude spectra, and apparent resistivity curves before and after removing the traffic noise from the time series data. We also examined the frequency range affected by traffic noise and whether artifact noise occurred during the traffic noise removal process as a result of the residual difference.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.195-200
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• 2020

With the growing interest in fossil fuel depletion and environmental pollution, railroad cars operating in Korea are in progress as the conversion from diesel to electric vehicles expands. The photovoltaic system, which is applied as an example of the conversion of electric vehicles, is infinite and pollution-free, and can produce energy without generating hazards such as air pollution, noise, heat, and vibration, and maintain fuel transportation and power generation facilities. There is an advantage that is rarely needed. However, the amount of electricity produced depends on the amount of solar radiation by region, and the energy density is low due to the power generation of about 25㎡/ kWp, so a large installation area is required and the installation place has limited problems. In view of these problems, many studies have been applied to fuel cells in the railway field. In particular, the plan to link the fuel cell power generation system railroad power supply system must be linked to the power supply system that supplies power to the railroad, unlike solar and wind power. Therefore, it has a close relationship with railroad cars and the linkage method can vary greatly depending on the system topology. Therefore, in this paper, we study the validity through simulation modeling related to linkage analysis according to system topology.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.786-791
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• 2007

Korean high speed train(HSR-350x) has adopted a combined electrical and mechanical(friction) braking system. Brake blending control unit(BBCU) controls each brake system to fulfill the required brake performances such as braking distance, deceleration and jerk. Also the braking system should be designed considering the economical management, such as effective use of generated braking energy and the minimum wear of friction materials(a pad and a brake shoe). In this paper, we establish the disc braking force pattern that reduces the wear of pad in the disc braking system by minimizing the variance of the instantaneous disk baking energy during braking time, and compare the wear mass of pad between the conventional disc braking force pattern and the established results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.588-594
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• 2015

Although GPS technology for location positioning system has been widely used, it is difficult to be used in intelligent transport systems, due to the large positioning error and limited area for receiving radio signals. Thanks to the rapid development of LED technology, LED lights become popular in many applications. Especially, visible light communications (VLC) has raised a lot of interests because of the simultaneous functioning of LED illumination and communication. Recent studies on positioning system using VLC mainly focused on indoor environments and still difficult to satisfy positioning accuracy and simple implementation simultaneously. In this paper, we propose a positioning system based on VLC using the coordinate information of LEDs installed on the road infrastructure. Extracting the LED signal, obtained through VLC, from the easily accessible camera image, it is possible to estimate the position of the car on the road. Simulation results show that the proposed scheme can achieve a high positioning accuracy of 1 m when large number of pixels is utilized and the distance from the LED light is close.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.