• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1584-1590
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• 2017

This paper presents a implementation method of reliable speed limitation controller considering motor parameter variation in high speed operation. In spinning process of drum washing machine, speed increase has to be limited when unallowable imbalance mass is detected. Otherwise, severe noise and vibration can happen because noise and vibration are proportional to imbalance mass. To detect imbalance mass, d-axis current magnitude is used. However, we have to compensate for back-emf and power supply variation by means of detecting them because d-axis current is affected by both of them. On the other hand, we have to carefully estimate back-emf because back-emf is affected by stator resistance variation and inverter voltage error. Stator resistance variation can happen by manufacturing process for mass production or temperature variation in running. And there are inverter voltage errors between command voltage from micro-computer to inverter and real voltage from inverter to motor because of rising and falling time delay and turn-on resistance of power semiconductor switch. To solve this problem, we propose 2-step align current injection method which is to inject step-wise current right before starting. By this method, we can simply obtain stator resistance by ratio of voltage without inverter voltage error and current, and we can measure inverter voltage error. So we can obtain more exact model current, and then by simple calculation with compensation gain, we can estimate more accurate motor back-emf. We show that this method works well. It is verified through experiments.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.117-131
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• 2009

When most drivers take to the freeway, they don't necessarily pay attention to the geometric design. They expect proper design by depending on their own senses and recognition. When they evaluate the features of traveling on the freeway, they can think differently than engineers. The design needs to predict the exact speed of the driver to satisfy the driver's expectation, safety, pleasure and so on. This study categorized the factors influencing the speed of six freeways considering geometric and operational features to make a prediction model of speed. The model used multiple regression with these factors and produced statically appropriate results. This study utilized the principle component analysis and the quantification II analysis based on the image data of the satisfaction of the traveling environment collected through individual interviews. As a result, this study found the factors of satisfaction in a traveling environment. It made a satisfaction model of the traveling environment on freeways considering the change of driver's actual recognition and societal recognition using structural equations and the quantification II theory. Through the model made in this study, This model can present not only qualitative factors like satisfaction of traveling environment on freeways, but also the quantitative elements like speed. What is important is the evaluation of features of traveling on freeways reflected in the recognition and traffic environment felt by drivers.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.236-244
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• 1998

When the capacity and traffic operation at signalized intersections are analyzed in Korea, the unprotected left-turn saturation flow rate, which is an important parameter for the analysis, is estimated form the USHCM model. thus, exact analysis of the left-turn is not possible because of the difference of traffic environments between two contries. In order to improve this problem, it is undertaken in this study to develop techniques for the estimation of unprotected left-turn saturation flows based on Korean drivers' data. As study intersections, signalized or unsignalized intersections on the 6, 4 and 2 lane streets are selected. the data for the saturation flow measurement and gap-acceptance behavior analysis are inputed in a notebook computer on the sites. The critical acceptance gaps of the 6, 4, and 2 lane streets are analyzed to be 6.0 secs, 4.6 secs, and 4.3 secs respectively. the average minimum headway of the left-turn vehicle was observed to be 2.6 secs. As the model to estimate unportected left-turn saturation flows, the drew model is recommended for 6 and 4 lane streets, and a graph is suggested for the 2-lane street. As the values of the parameters of the Drew model, the 2.6 secs of this study is recommended for the average minimum headway of the left-turn. But, the critical acceptance gap varies according to the approach speed of opposing traffic and driver population, it requires field survey to measure the gap of an intersection; however, the values of the gaps studied in this study may be used for the general intersections in urban area in Korean.

• Journal of the Korean Society for Railway
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• v.11 no.2
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• pp.203-210
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• 2008

Since hub wheel BLDC Motor consisted of wheel and BLDCM (Brushless DC Motor) without gear reducer has high efficiency and low operation noise, it can be utilized to a driving wheel at some light rail systems. However, installing sensors for speedometer on a Hub-Wheel motor is not easy, so it requires a different speed control mechanism method for speed measurement. This paper introduces a speed control method based on simple mathematical model which uses discrete Kalman Filter to estimate and control the speed of the motor.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.195-211
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• 2015

Flat plate friction lines have been used in the process to estimate speed performance of full-scale ships in model tests. The results of the previous studies showed considerable differences in determining form factors depending on changes in plate friction lines and Reynolds numbers. These differences had a great influence on estimation of speed performance of full-scale ships. This study was conducted in two parts. In the first part, the scale effect of the form factor depending on change in the Reynolds number was studied based on CFD, in connection with three kinds of friction resistance curves: the ITTC-1957, the curve proposed by Grigson (1993; 1996), and the curve developed by Katsui et al. (2005). In the second part, change in the form factor by three kinds of friction resistance curves was investtigated based on model tests, and then the brake power and the revolution that were finally determined by expansion processes of full-scale ships. When three kinds of friction resistance curves were applied to each kind of ships, these were investigated: differences between resistance and self-propulsion components induced in the expansion processes of full-scale ships, correlation of effects between these components, and tendency of each kind of ships. Finally, what friction resistance curve was well consistent with results of test operation was examined per each kind of ships.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1098_1099
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• 2009

In this paper, we present the estimation of wind turbine power generation using Cascade Architectures of Fuzzy Neural Networks(CAFNN). The proposed model uses the wind speed average, the standard deviation and the past output power as input data. The CAFNN identification process uses a 10-min average wind speed with its standard deviation. The method for rule-based fuzzy modeling uses Gaussian membership function. It has three fuzzy variables with three modifiable parameters. The CAFNN's configuration has three Logic Processors(LP) that are constructed cascade architecture and an effective optimization method uses two-level genetic algorithm. First, The CAFNN is trained with one-day average input variables. Once the CAFNN has been trained, test data are used without any update. The main advantage of using CAFNN is having simple structure of system with many input variables. Therefore, The proposed CAFNN technique is useful to predict the wind turbine(WT) power effectively and hence that information will be helpful to decide the control strategy for the WT system operation and application.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.73-78
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• 2002

This paper presents a neural network approach to estimate the surface roughness by considering the relationship between the polishing operation parameters and the surface roughness. The neural network model predicts the post-machining surface roughness by using several factors such as pre-machining surface roughness, pressure, feed rate, spindle speed, and the number of polishing as inputs. In this paper, the several neural network models are implemented to estimate the surface roughness by using actual experimental data. The experimental results show that the neural network approach is more appropriate to represent the polishing characteristics of mold and die compared with the results obtained by the approach using exponential function.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.1
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• pp.20-25
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• 2019

To prepare for the ever-increasing demand for air transport, airport operators should be well aware of the timing of the saturation of the facility and increase the capacity of the airport through extension or extension. The capacity of an airport is determined by the smallest value of the facilities that make up the airport, but it is generally customary to determine the capacity of the costly and time-consuming runway as a whole for the airport. For analyzing the capacity of the runway capacity, the study used the most accurate microscopic air traffic simulation, Simmod-PRO, to analyze the saturation time of three runways currently in Incheon International Airport's operation, and calculate the appropriate time for operation of the 4th runway. The study also calculate the relocation of Airport's high-speed exit taxiway for analyzing the increasing of capacity.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.397-402
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• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1456-1470
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• 2017

This paper presents sensorless vector control of induction motor drives with an improved model reference adaptive system observer for rotor speed estimation and parameters identification from measured stator currents, stator voltages and estimated rotor fluxes. The aim of the proposed sensorless control method is to compensate simultaneously stator resistance and rotor time constant variations which are subject of large changes during operation. PI controllers have been used in the model reference adaptive system adaptation mechanism and in the closed loops of speed and currents regulation. The stability of the proposed observer is proved by the Lyapunov's theorem and its feasibility is verified by experimentation. The experimental results are obtained with an 1 kW induction motor using Matlab/Simulink and a dSPACE system with DS1104 controller board showing the effectiveness of the proposed approach in terms of dynamic performance.