• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.571-579
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• 2010

This paper reviews and analyzes converters for SRM(Switched Reluctance Motor) drive. Conventional classification focuses on the number of power switches and diodes. It is easy to find the number of semiconductors and the cost by counting the number of active components, but it does not show the important characteristics of a power converter. The voltage ratings for the power switches and diodes are also difficult to identify. This paper proposes a switched reluctance (SR) converter configuration that is classified based on the commutation type and magnetic energy path. The converter has three parts: utility interface, front-end circuit, and power converter. Based on the overview on the conventional SR drive, the most important characteristic of the converter is determined by the topology of front-end in conjunction with the power converter. An SR converter has two parts: front-end and power converter. Inasmuch as the capacitive front-end is widely used for voltage source converters, this paper focuses on topologies for the front-end.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.11-12
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• 2010

This paper reviewed and analyzed converters for SRM drive. SR converter has two parts, front ends and power converter. Since the capacitive front-end is widely used in voltage source converter, this paper focuses on topologies with the front-end. A novel classification of power converters for SR drives based on the commutation type is also introduced and analyzed.

• Journal of Power Electronics
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• v.11 no.5
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• pp.767-777
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• 2011

Power electronic systems such as switching power supplies are accounted as noise sources for other sensitive circuits. EMI caused by power converters can disturb the normal operation of the converter and other adjacent systems. Major research is concentrated on EMI mitigation for power converters in which the main concern is compliance with EMC standards to ensure proper operation of converters and nearby systems. This paper reviews EMI reduction techniques related to switching power converters with emphasis on the conducted EMI. A comprehensive review of significant research works is performed and various methods are thoroughly discussed and compared. Also, a classification of methods is presented. Moreover, converter prototypes are realized which contain several EMI mitigation techniques and their effects are presented via experimental results.

• Advances in Energy Research
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• v.6 no.2
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• pp.103-129
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• 2019

While global demand for energy increases annually, at the same time the demand for carbon-free, sulphur-free and NO_x-free energy sources grows considerably. This state poses a challenge in the research for newer sources like biomass and shale gas as well as renewable energy resources such as solar, wind, geothermal and hydraulic energy. Although wave energy also is a form of renewable energy it has not fully been exploited technically and economically so far. This study tries to explain those reasons in which it is beyond doubt that the demand for wave energy will soon increase as fossil energy resources are depleted and environmental concerns gain more importance. The electrical energy supplied to the grid shall be produced from wave energy whose conversion devices can basically work according to three different systems. i. Systems that exploit the motions or shape deformations of their mechanisms involved, being driven by the energy of passing waves. ii. Systems that exploit the weight of the seawater stored in a reservoir or the changes of water pressure by the oscillations of wave height, iii. Systems that convert the wave motions into air flow. One of the aims of this study is to present the classification deficits of the wave energy converters (WECs) of the "wave developers" prepared by the European Marine Energy Center, which were to be reclassified. Furthermore, a new classification of all WECs listed by the European Marine Energy Center was arranged independently. The other aim of the study is to assess the technological state of the art of these WECs designed and/or produced, to obtain an overview on them.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.100-107
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• 1994

This article describes the hardware design scheme of Hamming MAXNET algorithm which is appropriate for binary pattern classification with minimum HD measurement between stimulus vector and storage vector. Circuit integration is profitable to Hamming MAXNET because the structure of hamming network have a few connection nodes over the similar neuro-algorithms. Designed hardware is the two-layered structure composed of hamming network and MAXNET which enable the characteristics of low power consumption and fast operation with biline volgate sensing scheme. Proposed Hamming MAXNET hardware was designed as quantize-level converter for simulation, resulting in the expected binary pattern convergence property.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.11a
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• pp.409-412
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• 2000

A high performance EEG signal measurement system is fabricated. It consists of high precision pre-amplifier and auto identification bandwidth unit. High precision pre-amplifier is composed of signal generator, signal amplifier with a impedance converter, body driver and isolation amplifier. The pre-amplifier is designed for low noise characteristics, high CMRR, high input impedance, high IMRR and safety, Auto identification bandwidth unit is composed of AD-converter and PIC micro-controller for real time processing EEG signal. The performance of EEG signal measurement system has been shown the classified bandwidth through the clinical demonstrations.

• Proceedings of the Safety Management and Science Conference
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• 2002.05a
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• pp.31-36
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• 2002

In this paper, we developed a working adaptation evaluation system using finger force measurement which interact between material and biological system. The system consists of a finger force transducer, a signal conditioner, an A/D converter, a computer, and a software system for data processing. The finger force transducer is made by a load cell and a special mechanism. The data processing software controls the A/D converter, data monitoring, and data analysis for group classification. The developed system were tested by 4 different materials in left hand and the finger forte transducer in the other hand's thumb and index finger with 16 persons. As the results of experiments, the developed system could measure the finger force quantitatively and classify the measured values into four groups.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.69-71
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• 2005

This paper presents a wavelet-based neural network technology for the detection and classification of the short durations type of power quality disturbances. Transients happen during very short durations to the nano- and microsecond. Thus, a method for detecting and classifying transient signals at the same time and in an automatic combines the properties of the wavelet transform and the advantages of neural networks. Especially, the additional feature extraction to improve the recognition rate is considered. The configuration of the hardware of TMS320C6711 DSP based with 16 channel 20Mhz sampling rate A/D(Analog to Digital) converter and some case studies are described.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.487-489
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• 2005

This paper presents a wavelet-based neural network technology for the detection and classification of the short durations type of power quality disturbances. Transients happen during very short durations to the nano- and microsecond. Thus, a method for detecting and classifying transient signals at the same time and In an automatic combines the properties of the wavelet transform and the advantages of neural networks. Especially, the additional feature extraction to improve the recognition rate is considered. The configuration of the hardware of TMS320C6711 DSP based with 16 channel 20Mhz sampling rate A/D(Analog to Digital) converter and some case studies are described.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.131-133
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• 1999

This paper proposed the technique of the fault-types classification using Adaptive Network Fuzzy Inference System in the distribution system. Fault and fault-like data in the linear RL load, arc furnace load and converter load were extracted by EMTP. These were characterized into 5 input variables and fuzzified automatically by learning. This technique was tested using another fault data unused learning.