• Proceedings of the KWS Conference
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• 2005.06a
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• pp.97-99
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• 2005

Laser arc hybrid process is actively researched as a new welding method since it has several advantages by the combination of laser beam and electric arc. By the coupling of two different heat sources, laser and arc mutually assist and influence. High power laser can make the deep keyhole and arc plasma can form the large bead shape. In this paper the effect of two different heat sources to weld bead are investigated and as a result of analysis, it is shown that the lower part of keyhole is heated by laser and the upper part of weld pool is dominantly heated by arc.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.379-386
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• 1996

This paper describes an approach for classifying myoelectric patterns using a multilayer perceptrons (MLP's) and hidden Markov models (HMM's) hybrid classifier. The dynamic aspects of EMG are important for tasks such as continuous prosthetic control or vari- ous time length EMG signal recognition, which have not been successfully mastered by the most neural approaches. It is known that the hidden Markov model (HMM) is suitable for modeling temporal patterns. In contrasts the multilayer feedforward networks are suitable for static patterns. Ank a lot of investigators have shown that the HMM's to be an excellent tool for handling the dynamical problems. Considering these facts, we suggest the combination of MLP and HMM algorithms that might lead to further improved EMG recognition systems.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.105-107
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• 2018

This paper presents a new hybrid multilevel converter topology, which consists of a combination of the series connected switched capacitor units with boost ability, and an H-bridge with T-type bidirectional switches. The proposed converter boosts the input voltage without any bulky inductors, and has the small number of components, which can make the size and cost of a power converter greatly reduced. The output filter size and harmonics are also reduced by the high quality multilevel output. In addition, there is no need for complicated methods to balance the capacitor voltage. Simulation and experimental results with a nine-level converter system are presented to validate the proposed topology and modulation method.

• Proceedings of the KIPE Conference
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• 2019.11a
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• pp.144-145
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• 2019

This paper proposes a design and analysis for a PI-IP hybrid voltage controller with a combination of PI and IP voltage controller for stable voltage control of DC bus voltage, Transient characteristic of DC bus voltage is improved by designed setting variable value and control method in the variable load and power generation conditions.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.2
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• pp.73-79
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• 2005

This paper is proposed hybrid artificial intelligent (HAI) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using a closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.686-691
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• 2011

This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1307-1309
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• 1996

This paper presents hybrid active noise control (HANC) systems which is based on the combination of feedforward and feedback ANC controllers. HANC systems use FIR filters and is based on primary noise regeneration principle and filtered-X LMS algorithms. HANC systems show better attenuation characteristics and residual spectrum. The order of adaptive filters used in HANC systems is lower than that of conventional feedforward and feedback ANC systems. A proposed HANC algorithm was implemented using a Taxas Instruments TMS320C31 digital signal processor for experimental verification.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.37-39
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• 1998

The hybrid step motor has found applications in a wide range of mechanical systems as a low cost, open-loop positioning device. The step motor provides good stiffness at rest against disturbing load influences, a combination of moderate speed fine resolution, high reliability and simplicity. In recent years, considerable competition has arisen over the technological issue of wheather the device should be applied as a 2-Phase or 5-Phase machine. In this paper, to compare two systems, we have atempted to derive the mathematical. model, and analysed operating detent torque with this model. The analysis shows that a fundamental component of the permeance distribution produces the average torque and that harmonic components produce the ripple torque.

• Geosystem Engineering
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• v.21 no.6
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• pp.309-317
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• 2018

We employ a three-dimensional indirect boundary element method (BEM) to simulate temperature change around an underground liquefied natural gas storage cavern. The indirect BEM (IBEM) uses fictitious heat source strength on boundary elements as basic variables which are solved from equations of boundary conditions and then used to compute the temperature change at other points in the considered problem domain. The IBEM requires evaluation of singular integration for temperature change due to heat conduction from a constant heat source on a planar (triangular) region. The singularity can be eliminated by a semi-analytical integration scheme. However, it is found that the semi-analytical integration scheme yields sharp temperature gradient for points close to vertices of triangle. This affects the accuracy of heat flux, if they are evaluated by finite difference method at these points. This difficulty can be overcome by a combination of using a direct numerical integration for these points and the semi-analytical scheme for other points distance away from the vertices. The IBEM and the hybrid integration scheme have been verified with an analytic solution and then used to the application of the underground storage.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.146-158
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• 2022

With the success of the digital economy and the rapid development of its technology, network security has received increasing attention. Intrusion detection technology has always been a focus and hotspot of research. A hybrid model that combines particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is presented in this work. Continuous-valued PSO and binary PSO (BPSO) are adopted together to determine the parameter combination and the feature subset. A fitness function based on the detection rate and the number of selected features is proposed. The results show that the method can simultaneously determine the parameter values and select features. Furthermore, competitive or better accuracy can be obtained using approximately one quarter of the raw input features. Experiments proved that our method is slightly better than the genetic algorithm-based KELM model.