• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.491-499
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• 2018

Runway visual range (RVR), one of the important indicators of aircraft takeoff and landing, is affected by meteorological conditions such as temperature, humidity, etc. It is important to estimate the RVR at the time of arrival in advance. This study estimated the RVR of the local airport after 1 hour by upgrading the RVR estimation model using the proposed deep learning network. To this end, the advancement of the estimation model was carried out by changing the time interval of the meteorological data (temperature, humidity, wind speed, RVR) as input value and the linear conversion of the results. The proposed method generates estimation model based on the past measured meteorological data and estimates the RVR after 1 hour and confirms its validity by comparing with measured RVR after 1 hour. The proposed estimation model could be used for the RVR after 1 hour as reference in small airports in regions which do not forecast the RVR.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.5
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• pp.313-322
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• 2024

To ensure the stable flight of aerospace electric propulsion systems, it is necessary to measure the supplied flow rate and control it to an appropriate level. However, conventional flow sensors are costly and face limitations in space environments, making heat-based flow estimation a promising alternative. In this study, the Taguchi method, one of the experimental design techniques, was applied to perform thermal analysis simulations using Ansys under various variables and conditions. The Taguchi method was used to set heat supply and the positioning of inlet and outlet temperature sensors as key variables, and the optimal distance conditions were derived. Thermal analysis was conducted through Ansys to analyze the flow estimation results under each experimental condition. Therefore, this study demonstrates the practicality of the heat-based flow estimation method for fuel management systems in electric propulsion systems, presenting a new approach for the efficient and economical operation of electric propulsion. Additionally, this research contributes to the development of fuel management technologies that can be effectively utilized in the constrained environment of space.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.47-48
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• 2005

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• Journal of Power Electronics
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• v.18 no.3
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• pp.910-922
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• 2018

Conventional battery state-of-charge (SoC) estimation methods either involve sophisticated models or consume considerable computational resource. This study constructs an enhanced coulomb counting method (Ah method) for the SoC estimation of lithium-ion batteries (LiBs) by expanding the Peukert equation for the discharging process and incorporating the Coulombic efficiency for the charging process. Both the rate- and temperature-dependence of battery capacity are encompassed. An SoC mapping approach is also devised for initial SoC determination and Ah method correction. The charge counting performance at different sampling frequencies is analyzed experimentally and theoretically. To achieve a favorable compromise between sampling frequency and accumulation accuracy, a frequency-adjustable current sampling solution is developed. Experiments under the augmented urban dynamometer driving schedule cycles at different temperatures are conducted on two LiBs of different chemistries. Results verify the effectiveness and generalization ability of the proposed SoC estimation method.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.600-608
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• 2014

This paper presents estimation of d-axis and q-axis inductance of an interior permanent magnet synchronous motor (IPMSM) by using an extended Kalman filter (EKF). The EKF is widely used for control applications including the motor sensorless control and parameter estimation. The motor parameters can be changed by temperature and air-gap flux. In particular, the variation of the inductance affects torque characteristics like the maximum torque per ampere (MTPA) control. Therefore, by estimating the parameters, it is possible to improve the torque characteristics of the motor. The performance of the proposed estimator is verified by simulations and experimental results based on an 11kW PMSM drive system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1404-1407
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• 1996

A quality monitoring system in butt welding process is proposed to estimate weld pool sizes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to prove the integrity of the weld quality. The monitoring variables used are the surface temperatures measured at three points on the top surface of the weldment. The temperature profile is assumed that it has a gaussian distribution in vertical direction of torch movement and verify this assumption through temperature analysis. A neural network estimator is designed to estimate weld pool size from temperature informations. The experimental results show that the proposed neural network estimator which used gaussian distribution as temperature information can estimate the weld pool sizes accurately than used three point temperatures as temperature information. Considering the change of gap size in butt welding, the experiment were performed on various gap size.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.6
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• pp.817-823
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• 2011

This paper proposes a cooling stop temperature control(CST) and a phase transformation control(PTR) which aim at obtaining the uniform temperature and quality along the longitudinal direction of the high strength steel on the run-out table(ROT) process. The problems of the temperature control are analyzed for the conventional steel and the new control concepts are derived from a time-temperature transformation(TTT) diagram. The proposed control technologies are verified from the simulation results under the temperature prediction model by the heat transfer governing equation, and the temperature estimation simulator. It is shown through the field test of the hot strip mills that the phase transformation ratio of the high strength steel is considerably improved by the proposed temperature controls.

• Journal of the Korean Society of Safety
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• v.13 no.2
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• pp.76-87
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• 1998

This study was carried out to investigate the effect of on temperature control from actuating method, recycling ratio and the position (top, middle and bottom) of set and controlled temperature within the reactor in adiabatic ebullated recycling condition, when the disturbance was occurred. Estimation of the solution were performed numerically using the finite difference method. It was assumed that the reaction is in constant with heat of reaction and the physical properties(density, heat capacity and viscosity, etc) of the reactants are same condition within the reactor.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.798-800
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• 2003

The time shift processing of ground measured surface temperature with the meteorological variables has no evaluated function. We introduce new evaluating function. To use this evaluating function, the algorithm of time-shift processing will be able to be reliable and get error-bar for all moving measured point's data. We will finally obtain the area averaged surface temperature by land observation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.197-198
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• 2021

The temperature and humidity inside concrete affects the depth of carbonation. In this study, the temperature and humidity inside concrete were predicted by the numerical method under the boundary conditions of ambient temperature, humidity, solar radiation, and wind. Using the results of the thermal humidity analysis, diffusion of carbon dioxide and the reaction of cement hydration products were calculated for carbonation depth.