• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.429-432
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• 2003

In this paper, a novel neural network approach is proposed for cleaning robot to complete coverage path planning with obstacle avoidance in stationary and dynamic environments. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley's membrane equation. There are only local lateral connections among neurons. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location without any prior knowledge of the dynamic environment.

• 전기학회논문지
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• 제68권1호
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• pp.98-101
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• 2019

In this paper, we propose the power-based pipelined-forwarding MAC protocol which can select relay nodes according to the residual power and energy harvesting rate in EH-WSN (energy-harvesting wireless sensor networks). The proposed MAC follows a pipelined-forwarding scheme in which nodes repeatedly sleep and wake up in an EH-WSN environment and data is continuously transmitted from a high-level node to a low-level node. The sleep interval is adaptively controlled so that nodes with low energy harvesting rate can be charged sufficiently, thereby minimizing the transmission delay and increasing the network lifetime. Simulation shows that the proposed MAC protocol improves the balance of residual power and network lifetime.

• Steel and Composite Structures
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• 제51권6호
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• pp.713-727
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• 2024

Damage detection in structures using the change of modal parameters (modal shapes and natural frequencies) has achieved satisfactory results. However, as modal shapes and natural frequencies alone may not provide enough information to accurately detect damages. Therefore, a hybrid singular value decomposition and deep belief network approach is developed to effectively identify damages in aluminum plate structures. Firstly, damage locations are determined using singular value decomposition (SVD) to reveal the singularities of measured displacement modal shapes. Secondly, using experimental modal analysis (EMA) to measure the natural frequencies of damaged aluminum plates as inputs, deep belief network (DBN) is employed to search damage severities from the damage evaluation database, which are calculated using finite element method (FEM). Both simulations and experimental investigations are performed to evaluate the performance of the presented hybrid method. Several damage cases in a simply supported aluminum plate show that the presented method is effective to identify multiple damages in aluminum plates with reasonable precision.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 B
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• pp.1309-1312
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• 2002

The electric power network paralleled with wind turbine generator may have the negative impacts on the protection, operation, and management caused by the operation of wind turbine generator. Therefore, it is necessary to investigate the operating characteristic of wind turbine generator. This paper describes model of a squirrel-cage type wind turbine induction generator and the soft cut-in connection method for reducing the transient state on power network, and simulates various cases of wind turbine operations. The radial distribution network of IEEE 13-bus are modeled and tested by PSCAD/EMTDC.

• Journal of information and communication convergence engineering
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• 제8권3호
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• pp.333-338
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• 2010

This paper derives a nominal state relationship (NSR) from the data of a nominal system. Through an example of a second order system, it is shown that the relationship can be derived only in the system with different real eigenvalues. In higher order system, the relationship is expressed by using neural network (NN). The derived NSR is used to design a noble sliding surface with a nominal system characteristic. By using the sliding surface, the robustness of the sliding mode control (SMC) is added to the pole-placement control.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.170-177
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• 2014

This paper presents a new method of classification of the induction machine faults using Time Frequency Representation, Particle Swarm Optimization and artificial neural network. The essence of the feature extraction is to project from faulty machine to a low size signal time-frequency representation (TFR), which is deliberately designed for maximizing the separability between classes, a distinct TFR is designed for each class. The feature vectors size is optimized using Particle Swarm Optimization method (PSO). The classifier is designed using an artificial neural network. This method allows an accurate classification independently of load level. The introduction of the PSO in the classification procedure has given good results using the reduced size of the feature vectors obtained by the optimization process. These results are validated on a 5.5-kW induction motor test bench.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.443-449
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• 2002

In this paper, we propose a programmable method that can connect the control network with the Internet by using an ordinary PC, which is operated by GNU/LINUX. We make a physical connection between an ordinary PC and control network. Then, a PC can be bound with a particular control network. Moreover, numerous PCs that are bound with particular control networks have addresses of there own on the Internet. So, these PCs are connected each other very well. Consequently, all control networks can be observed and controlled with data transfer between these PCs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.313-316
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• 2002

The need to protect a main information and control a personal access using Biometrics in the intelligent building system is extended with growing the information and communication technologies in recent years. The fingerprint recognition technology is one of the biometrics methods available that has been widely used in various applications. But the present architecture of fingerprint recognition system has many of the problems because of centralized control network architecture. But we can solve the problems with distributed control network architecture. In this paper, the fingerprint recognition system uses the merit of the LonWorks. it is able to easily modularize the system and make up for the weak points in the typical fingerprint recognition system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 C
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• pp.1405-1407
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• 1997

A microstructure of realistic ZnO varistor is constructed by Voronoi network and studied via computer simulation. In this network, the grain boundary condition is fitted from the experimental data. The effect of the variation of the uniformity of the varistor on the electrical characteristic of the varistor is simulated by using this boundary condition.

• KIEE International Transactions on Electrophysics and Applications
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• 제3C권1호
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• pp.5-9
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• 2003

The waveforms of partial discharges (PDs) imply physical and structural properties of PD sources, so analyzing them give us information on the kind of PD sources and the location. Waveforms of PD as a time series function have variable amplitudes but sustain a certain uniform shape, which shows well the characteristics of the waveforms and frequency region. They can also be used as parameters having time and frequency information of PD signals and applied to classification of multiple PDs sources via Artificial Neural Network with back propagation (BP) learning.