• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1475-1480
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• 2013

In this paper, the basic design study of a water-cooling jacket, which have reported no cases for applying to railway traction motors so far, were conducted for applying to Interior Permanent Magnet Synchronous Motor (IPMSM) for railway vehicles. The basic thermal characteristics analysis of the 110kW-class IPMSM was performed by using 3-dimentional thermal equivalent network method. The necessary design requirements of the water-cooling jacket were derived by analyzing the results of the basic thermal properties. Next, the thermal characteristics analysis technique was established by using the equivalent model of the solenoid-typed pipe to be installed on the inside of the water-cooling jacket for 110kW-class IPMSM. Finally, a design model of 6kW-class water-cooling jacket was derived through the analysis of various design parameters.

• Journal of Power Electronics
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• v.17 no.4
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• pp.892-904
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• 2017

A design of a Class-E inverter with only one inductor and one capacitor is presented. It is operated at the optimal operation mode for domestic cooker. The design principle is based on the zero-voltage derivative switching (ZVDS) of the Class-E inverter with a parallel load network, which is a parallel resonant equivalent circuit. An induction load characterization is obtained from a large-signal excitation test bench, which is the key to an accurate design of the induction cooker system. Consequently, the proposed scheme provides a more systematic, simple, accurate, and feasible solution than the conventional quasi-resonant inverter analysis based on series load network methodology. The derivative of the switch voltage is zero at the turn-on transition, and its absolute value is relatively small at the turn-off transition. Switching losses and noise are reduced. The parameters of the ZVDS Class-E inverter for the domestic induction cooker must be selected properly, and details of the design of the components of this Class-E inverter need to be addressed. A 1,200 W prototype is designed and evaluated to verify the validation of the proposed topology.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.108-115
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• 2009

In metal forming technologies, the stamping process is one of the significant manufacturing processes to produce sheet metal components. It is important to design stamping process which can produce sound products without defect such as fracture and wrinkle. The objective of this study is to propose the feasible formability diagram which denotes the safe region without fracture and wrinkle for effective design of stamping process. To determine the feasible formability diagram, FE-analyses were firstly performed for the combinations of process parameters and then the characteristic values for fracture and wrinkle were estimated from the results of FE-analyses based on forming limit diagram. The characteristic values were extended through training of the artificial neural network. The feasible formability diagram was finally determined for various combinations of process parameters. The stamping process of turret suspension to support suspension module was taken as an example to verify the effectiveness of feasible formability diagram. The results of FE-analyses for process conditions within fracture and wrinkle as well as safe regions were in good agreement with experimental ones.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.21-25
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• 1999

Planning support systems(PSS) add more advanced spatial analysis functions than Geographic information systems(GIS) and intertemporal functions to the functions of spatial decision support systems(SDSS). This paper reports the continuing development of a PSS providing a framework that facilitates urban planners and civil engineers in conducting coherent deliberations about planning, design and operation & maintenance(O&M) of water-distribution networks for urban growth management. The PSS using dynamic optimization model, modeling-to-generate-alternatives, value engineering(VE) and life-cycle cost(LCC) can generate network alternatives in consideration of initial cost and O&H cost. Users can define alternatives by the direct manipulation of networks or by the manipulation of parameters in the models. The water-distribution network analysis model evaluates the performance of the user-defined alternatives. The PSS can be extended to include the functions of generating sewer network alternatives, combining water-distribution and sewer networks, eventually the function of planning, design and O&H of housing sites. Capacity expansion by the dynamic water-distribution network optimization model using MINLP includes three advantages over capacity expansion using optimal control theory(Kim and Hopkins 1996): 1) finds expansion alternatives including future capacity expansion times, sizes, locations, and pipe types of a water-distribution network provided, 2) has the capabilities to do the capacity expansion of each link spatially and intertemporally, and 3) requires less interaction between models. The modeling using MINLP is limited in addressing the relationship between cost, price, and demand, which the optimal control approach can consider. Strictly speaking, the construction and O&M costs of water-distribution networks influence the price charged for the served water, which in turn influence the. This limitation can be justified in rather small area because price per unit water in the area must be same as that of neighboring area, i.e., the price is determined administratively. Planners and engineers can put emphasis on capacity expansion without consideration of the relationship between cost, price, and demand.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.426-429
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• 2006

A distributed healthcare monitoring system prototype for clinical and trauma patients, was developed, using wireless sensor network node. The proposed system aimed to measure various vital physiological health parameters like ECG and body temperature of patients and elderly persons and transfer his/ her health status wirelessly in Ad-hoc network, to remote base station which was connected to doctor's PDA/PC or to a hospital's main Server using wireless sensor node. The system also aims to save the cost of healthcare facility for patients and the operating power of the system because sensor network is deployed widely and the distance from sensor to base station was shorter than in general centralized system. The wireless data communication will follow IEEE 802.15.4 frequency communication with ad-hoc routing thus enabling every motes attached to patients, to form a wireless data network to send data to base-station, providing mobility and convenience to the users in home environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1255-1262
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• 2012

Look into the nuclear power plant of Wolsong currently, it is controlled in order to required operating pressure with PI controller. PI controller has a simple structure and satisfy design requirements to gain setting. However, It is difficult to control without changing the gain from produce changes in parameters such as loss of the valves and the pipes. To solve these problems, the dynamic change of the PI controller gain, or to compensate for the PI controller output is desirable to configure the controller. The aim of this research and development in the parameter variations can be controlled to a stable controller design which is reduced an error and a vibration. Proposed PI/NN control techniques is the PI controller and the neural network controller that combines a parallel and the neural network controller part is compensated output of the controller for changes in the parameters were designed to be robust. To directly evaluate the controller performance can be difficult to test in real processes to reflect the characteristics of the process. Therefore, we develope the simulator model using the real process data and simulation results when compared with the simulated process characteristics that showed changes in the parameters. As a result the PI/NN controller error and was confirmed to reduce vibrations.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.408-421
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• 2015

Because the wheel of V-belt continuously variable transmission (CVT) system driven by permanent magnet synchronous motor (PMSM) has much unknown nonlinear and time-varying characteristics, the better control performance design for the linear control design is a time consuming job. In order to overcome difficulties for design of the linear controllers, a hybrid recurrent Chebyshev neural network (NN) control system is proposed to control for a PMSM servo-driven V-belt CVT system under the occurrence of the lumped nonlinear load disturbances. The hybrid recurrent Chebyshev NN control system consists of an inspector control, a recurrent Chebyshev NN control with adaptive law and a recouped control. Moreover, the online parameters tuning methodology of adaptive law in the recurrent Chebyshev NN can be derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, the optimal learning rate of the parameters based on discrete-type Lyapunov function is derived to achieve fast convergence. The recurrent Chebyshev NN with fast convergence has the online learning ability to respond to the system's nonlinear and time-varying behaviors. Finally, to show the effectiveness of the proposed control scheme, comparative studies are demonstrated by experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.6 s.183
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• pp.44-51
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• 2006

This paper deals with the aspects of die design for the multistage fine tooth hub gear in the cold forging process. In order to manufacture the cold forged product for the precision hub gear used as the ARD 370 system of bicycle, it examines the influences of different designs on the metal flow through experiments and FE-simulation. To find the combination of design parameters which minimize the damage value, the low gear length, upper gear length and inner diameter as design parameters are considered. An orthogonal fraction factorial experiment is employed to study the influence of each parameter on the objective function or characteristics. The optimal punch shape of fine tooth hub gear is designed using the results of FE-simulation and the artificial neural network. To verify the optimal punch shape, the experiments of the cold forging of the hub gear are executed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.769-772
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• 2005

This paper deals with the aspects of die design for the multistage fine tooth hub gear in the cold forging process. In order to manufacture the cold forged product fur the precision hub gear used as the ARD 370 system of bicycle, it examines the influences of different designs on the metal flow through experiments and FE-simulation. To find the combination of design parameters which minimize the damage value, the low gear length, upper gear length and inner diameter as design parameters are considered. An orthogonal fraction factorial experiment is employed to study the influence of each parameter on the objective function or characteristics. The optimal punch shape of fine tooth hub gear is designed using the results of FE-simulation and the artificial neural network. To verify the optimal punch shape, the experiments of the cold forging of the hub gear are executed.

• Advances in nano research
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• v.14 no.2
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• pp.155-164
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• 2023

Grain size in sheet metals in one of the main parameters in determining formability. Grain size control in industry requires delicate process control and equipment. In the present study, effects of grain size on the formability of steel sheets is investigated. Experimental investigation of effect of grain size is a cumbersome method which due to existence of many other effective parameters are not conclusive in some cases. On the other hand, since the average grain size of a crystalline material is a statistical parameter, using traditional methods are not sufficient for find the optimum grain size to maximize formability. Therefore, design of experiment (DoE) and artificial intelligence (AI) methods are coupled together in this study to find the optimum conditions for formability in terms of grain size and to predict forming limits of sheet metals under bi-stretch loading conditions. In this regard, a set of experiment is conducted to provide initial data for training and testing DoE and AI. Afterwards, the using response surface method (RSM) optimum grain size is calculated. Moreover, trained neural network is used to predict formability in the calculated optimum condition and the results compared to the experimental results. The findings of the present study show that DoE and AI could be a great aid in the design, determination and prediction of optimum grain size for maximizing sheet formability.