• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.525-530
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• 2004

A classifier was constructed by using a generalized regression neural network (GRU) and random generator (RG), which was applied to classify DNA sequences. Three data sets evaluated are eukaryotic and prokaryotic sequences (Data-I), eukaryotic sequences (Data-II), and prokaryotic sequences (Data-III). For each data set, the classifier performance was examined in terms of the total classification sensitivity (TCS), individual classification sensitivity (ICS), total prediction accuracy (TPA), and individual prediction accuracy (IPA). For a given spread, the RG played a role of generating a number of sets of spreads for gaussian functions in the pattern layer Compared to the GRNN, the RG-GRNN significantly improved the TCS by more than 50%, 60%, and 40% for Data-I, Data-II, and Data-III, respectively. The RG-GRNN also demonstrated improved TPA for all data types. In conclusion, the proposed RG-GRNN can effectively be used to classify a large, multivariable promoter sequences.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.271-273
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• 1999

In this paper 30 kVA Super-Conducting Generator's test and analysis results of OCC and SCC are presented. Also the test and FE analysis results of the generator under 1.2, 2.4, and 3.6[kW] load are described. For FE analysis of the generator's performance, the external circuit is coupled with the FE region. The generator's end winding reactance is obtained based on the design data, actual dimension, preliminary FE analysis, and empirical formulas. The comparison of FE analysis coupled with external circuit to the test results shows a good agreement.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.501-510
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• 1996

The gas-turbine generator of Seo-Incheon combined-cycle plant was tested for derivation of a model for dynamic analysis. Load rejection and AVR step test was performed to get the dynamic response of generator. The parameters of generator/control system model were determined by these measured data. No-load saturation test was performed for the saturation characteristics of the generator under steady state. V-curve test was also performed so as to find exact generator parameters. Q-axis parameters of generator was derived by measuring power angle. AVR and governor constants have been tuned by their oscillatory period and setting time characteristics. The derived parameters of generator control system is verified by one-machine infinite bus system simulation. (author). 7 refs., 20 figs., 5 tabs.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.802-807
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• 2007

Elastic-plastic structural analysis for regenerative cooling chamber of gas generator was performed. Uniaxial tension test was also conducted for STS316L at room and high temperature conditions to get the material data necessary for the structural analysis of the chamber which is operated under thermal load and high internal pressure. Physical properties including thermal conductivity, specific heat and thermal expansion data were also measured. The structural analysis for four different types of regenerative cooling chamber of gas generator revealed that increased cooling performance decreases the thermal load and strain of the cooling channel. The results propose that in order for the regenerative cooling gas generator chamber to have high structural stability with endurance to high mechanical and thermal loads, it is important for the chamber to be designed to have high cooling performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.1
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• pp.123-128
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• 2006

The proposed mathematical model of the starter-generator system incorporates the motor speed, battery voltage and the desired current to estimate the moment generation capabilities of the starter-generator and the actual current of the battery system. The fundamentals for this mathematical modeling are the simulated results of the experimental data. These pertinent data are used in establishing the governing equations for the determination of motor moments, actual battery currents and efficiencies of the system's operation at different loading characteristics and speed regions. The derived equations will be used into simulation programs to predict the fuel efficiency, vehicle characteristics of a hybrid electric vehicle equipped with a transmission starter-generator which will be developed.

• Journal of the Korean Solar Energy Society
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• v.32 no.3
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• pp.146-152
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• 2012

To install a wind power generator, the survey on the wind environment resources must be conducted in advance. The survey on the wind environment resources is to collect and analyze data regarding the wind speed and direction on a data logger. The data logger consists of a sensor, signal processing circuit and storage device. According to the analysis of the stored data, the amount of power generation by the types of generators can be predicted and the most optimal generator including safety grade can be selected, and in case of installing a generator in the future, it can be utilized as basic data regarding supporting base and foundation construction method of survey points. Data logger was developed for a small wind power generator that is suitable for the international standard(IEC 61400) by using DSP-F28335 micro controller in this paper. It was developed to measure the wind speed of 1 [m/s]~17 [m/s], the wind direction of 0 [$^{\circ}$]~359 [$^{\circ}$], and temperature of -30 [$^{\circ}C$]~50 [$^{\circ}C$], and the comparative experiment with other companies' data loggers was conducted, and an error was measured to be less than ${\pm}0.1$ [m/s] for wind speed and less than +1 [$^{\circ}$] for wind direction.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1309-1317
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• 2012

Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is veri ed that the addition of these covariates does not distort the performance of the weather generator in other respects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8753-8759
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• 2015

Establishment of analysis procedures and validated performance measurements for generator output is required to maintain stable management of generator output in turbine power generation cycle. We developed turbine expansion model and measurement validation model for the performance calculation of generator using turbine output based on ASME (American Society of Mechanical Engineers) PTC (Performance Test Code). We also developed verification model for uncertain measurement data related to the turbine and generator output. Although the model in previous researches was developed using artificial neural network and kernel regression, the verification model in this paper was based on algorithms through Support Vector Machine (SVM) model to overcome the problems of unmeasured data. The selection procedures of related variables and data window for verification learning was also developed. The model reveals suitability in the estimation procss as the learning error was in the range of about 1%. The learning model can provide validated estimations for corrective performance analysis of turbine cycle output using the predictions of measurement data loss.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.148-153
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• 2004

This paper represents that parts of a large generator operating in 1000 MW are affected by centrifugal forces due to high-speed rotation in 3600 rpm and 3D FEM Analyses are required to obtained the structural reliability of the generator. From these results, one would know the weakest locations and the stress distributions. The fatigue life is calculated in order to grasp the remaining life of generator. 2D and 3D analyses are performed to calculate stresses of the generator rotor and the retaining ring. From 2D results, we find the SCF at the slot and sub-slot of the rotor. 3D analysis is applied at the end part of generator rotor, which represents complex geometry, and rotor and retaining ring shrink thermally. With these results, designers of rotor and retaining ring can compare with the results of design code and verify the stress distributions of generator rotor and retaining ring, and then calculate the remaining life from the low-cycle fatigue data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.434-441
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• 2003

This paper presents a generator for stand-alone vibration monitoring system of bridge structure based on ambient vibration of bridge. In this paper, a novel electric power generator which has minimum effect of armature reaction is proposed. The related mechanical and electrical design equations are obtained and a pilot generator has been implemented. In addition, the charging system for extremely low generator current is discussed, and some improvements are identified for the system. This investigation reveals that diode characteristics of rectifier is dominant factor in the charging process. Finally, both the simulation, which uses real measurement data of the Namhae bridge as input of the pilot generator, and indoor test are carried out. The results showed the applicability and effectiveness of the stand-alone vibration powered generator.