• Journal of the Korean Society for Precision Engineering
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• v.31 no.10
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• pp.905-911
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• 2014

A Loss-in-Weight (LIW) feeder, a type of automated measuring device, is a continuous feeder used in many mass production industries. Due to its versatility, there have been constant demands of LIW feeders in food production supply lines as well as chemical and pharmaceutical industries. In this paper, the process of designing a LIW feeder system with better performance will be examined and compared with commercial products. This system is characterized by low pass Butterworth filter and feed forward PI control. The filter is for noise disposal caused by dynamic condition of a LIW feeder. The feed forward PI control, based on linearity feature of feeders, is adequate for stable driving of the system. At the end, a possible evaluation method of LIW system will be proposed to verify the specific achievement of this paper.

• Journal of the Korean Society of Propulsion Engineers
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• v.10 no.4
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• pp.34-39
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• 2006

The flow forming has been used to produce long thin walled tube parts, with reduced forming force and enhanced mechanical for a good finished part, compared with other method formed parts. Especially, the flow forming is suitable for making high precision thin walled cylinders, such as rocket motor cases, combustion chamber, hydraulic cylinders and high-pressure vessels and so on. In this paper, finite element analysis of three-roller forward and backward flow forming for combustion chamber is carried out to study effects of forming depth and feed rate on forming force. The axial and radial forming forces of forward flow forming on several forming depth and feed rate conditions are compared with those of backward flow forming.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.94-101
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• 2008

In this paper, we introduce a real-time state-of-polarization(SOP) finding system. The system divides the optical wave into linear horizontal- and vertical-SOP components and measures two different beat-signals, which are produced by superposition with reference optical source, in time domain. From these measured beat signals we can get SOP information of the signal instantly. Since the proposed scheme is a feed-forward measurement system, comparing with conventional systems which require an optical feedback loop, the measurement time becomes reduced tremendously. We also introduced a novel calibration method for compensating birefringence-related errors which may occur during the measurement. We prove the operation and performance of the proposed system through computer simulation and actual experiments.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.671-674
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• 2004

We propose accurate classification method of EEG signals during mental tasks. In the experimental task, the tasks of subjects show 3 major measurements; there are mathematical tasks, color decision tasks, and Chinese phrase tasks. The classifier implemented for this work is a feed-forward neural network that trained with the error back-propagation algorithm. The new BCI system is proposed by using neural network. In this system, tr e architecture of the neural network is composed of three layers with a feed-forward network, which implements the error back propagation-learning algorithm. By applying this algorithm to 4 subjects, we achieved $95{\%}$ classification rates. The results for BCI mathematical task experiments show performance better than those of the Chinese phrase tasks. The selection time of each task depends on the mental task of subjects. We expect that the proposed detection method can be a basic technology for brain-computer interface by combining with left/right hand movement or yes/no discrimination methods.

• International Journal of Internet, Broadcasting and Communication
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• v.6 no.1
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• pp.9-12
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• 2014

We present a mathematical method for calculation of transmission zero locations, determining a filtering characteristics of two-port systems. By adjusting element values based on the zero locations, the frequency-selectivity is characterized. The characteristic polynomial of ladder networks in externally-loaded feed-forward systems is considered by adopting chain matrices for subsystems. This method can be extended to other types of lumped systems with cross-coupled sections. We find out the zeros by solving characteristics polynomials of closed-form expressions in terms of Laplace impedances of elements. The pairs of complex zeros are shown to be solely from the cross-coupled portion of the system.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.729-737
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• 2009

This paper introduces the machine tools feed system, which can be optimized the control's performance through simulation and the adjustment of the mechanical components. One method simulates the frequency response of the speed-loop with the design value using the MATLAB application, so that all of the interpolation axis can be equal to the response bandwidth, resulting in a high accuracy rate. The other method sees the mechanical component being adjusted by analyzing the results of various experiments. Lastly, this client's program is able to change the parameters that are related to the FFD, as well as the parameters in the friction compensation of the OPEN-CNC.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.3
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• pp.267-274
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• 2004

In this paper, a new on-line dead-time compensation method is proposed. The output voltage errors due to the dead-time effect is considered as disturbance voltages. The magnitude of the disturbance voltages is estimated using a time delay control technique and the disturbance voltages are calculated using the estimated values, measured currents, and position information. The calculated disturbance voltages are fed to voltage references in order to compensate the dead-time effect. The proposed method is applied to a PM synchronous motor drive system and implemented in a digital manner using a digital signal processor (DSP) TMS320C31. The experiments are carried out for this system to show the effectiveness of the proposed method and the results show the validity of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1972-1977
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• 2005

In this work, an inverse dynamic control method is developed to enhance tracking performance of industrial robots, which effectively deal with the nonlinear dynamic interferential forces. In general, the DFF (Dynamic Feed-Forward) controller and the CTM (Computed-Torque Method) controller are used for dynamic control for industrial robots. We study on the practical issues for implementing these inverse dynamic controllers via simulations and experiments. We develop the dynamic models in two different ways. One is a model designed through Newton-Euler method for real time computation and the other is a model designed through SimMechanics for evaluating the developed controller via simulations. We evaluate the nominal performance and robustness of the controller via simulations and experiments using serial 4-DOF HyRoHILS (Hyundai Robot Hardware-In-the-Loop Simulation) system. The results show that the inverse dynamic controller is effective and practically useful for a real control structure.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.641-649
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• 2021

Fuel oil consumption (FOC) must be minimized to determine the economic route of a ship; hence, the ship power must be predicted prior to route planning. For this purpose, a numerical method using test results of a model has been widely used. However, predicting ship power using this method is challenging owing to the uncertainty of the model test. An onboard test should be conducted to solve this problem; however, it requires considerable resources and time. Therefore, in this study, a deep feed-forward neural network (DFN) is used to predict ship power using deep learning methods that involve data pattern recognition. To use data in the DFN, the input data and a label (output of prediction) should be configured. In this study, the input data are configured using ocean environmental data (wave height, wave period, wave direction, wind speed, wind direction, and sea surface temperature) and the ship's operational data (draft, speed, and heading). The ship power is selected as the label. In addition, various treatments have been used to improve the prediction accuracy. First, ocean environmental data related to wind and waves are preprocessed using values relative to the ship's velocity. Second, the structure of the DFN is changed based on the characteristics of the input data. Third, the prediction accuracy is analyzed using a combination comprising five hyperparameters (number of hidden layers, number of hidden nodes, learning rate, dropout, and gradient optimizer). Finally, k-means clustering is performed to analyze the effect of the sea state and ship operational status by categorizing it into several models. The performances of various prediction models are compared and analyzed using the DFN in this study.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.387-392
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• 2007

The paper presents control performance of a magnetorheological (MR) fluid-based haptic knob which is applicable to invehicle comfort functions. As a first step, MR fluid-based haptic knob is devised to be capable of both rotary and push motions with a single device. Under consideration of spatial limitation, design parameters are optimally determined to minimize a reciprocal of control torque using finite element analysis. The proposed haptic knob is then manufactured and its fielddependent torque is experimentally evaluated. Subsequently, in-vehicle comfort functions are constructed in virtual environment and make them communicate with the haptic knob. Control performances such as reflection force are experimentally evaluated via simple feed-forward control strategy.