• Journal of the Korean Society for Nondestructive Testing
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• v.12 no.1
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• pp.9-15
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• 1992

Ultrasonic spectroscopy is likely to become a very powerful NDE method for detection of microfects and thickness measurement of thin film below the limit of ultrasonic distance resolution in the opaque materials, provides a useful information that cannot be obtained by a conventional ultrasonic measuring system. In this paper, we considered a thin film below the limit of ultrasonic distance resolution sandwitched between two substances as acoustical analysis model, demonstrated the usefulness of ultrasonic spectroscopic analysis technique using information of ultrasonic frequency for measurements of thin film thickness, regardless of interference phenomenon and phase reversion of ultrasonic waveform. By using frequency intervals(${\triangle}f$) of periodic minima from the ratio of reference power spectrum of reflective waveform obtained a sample to power spectrum of multiple reflective waves obtained interference phenomenon caused by ultrasonic waves reflected at the upper and lower surfaces of a thin layer, can measured even dimensions of interest are smaller than the ultrasonic wave length with simplicity and accuracy.

• Journal of Power Electronics
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• v.8 no.1
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• pp.101-107
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• 2008

In this paper, the features extracted from vibration time signals are used to detect the bearing fault condition. The decision tree is applied to diagnose the bearing status, which has the benefits of being an expert system that is based on knowledge history and is simple to understand. This paper also suggests a genetic algorithm (GA) as a method to reduce the number of features. In order to show the potentials of this method in both aspects of accuracy and simplicity, the reduced-feature decision tree is compared with the non reduced-feature decision tree and the PCA-based decision tree.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.934-937
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• 1992

The partial discharge signal can be used as the detection signal of the deterioration of the power transformer insulation. Detecting this signal, the insulation failure and the point, in which the partial discharge is generated, could be predicted. In this paper, we study to predict the point, and find that the cross correlation method could predict the point accurately. Also, experimental system and the results are presented here.

• 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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• 1999.07a
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• pp.274-277
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• 1999

The paper describes a implementation of space vector pulse-width modulation (SVPWM) voltage source inverter using Field Programmable Gate Array(FPGA) for a induction motor control system. The implemented chip is included logic circuits for SVPWM, dead time compensation and speed detection using Quick Logic, QL16X24B. The maximum operating frequency and delay time can be set to 110MHz and 6 nsec. The designed FPGA for SVPWM can be incorporated with a digital signal processing to provide a simple and effective solution for high performance voltage source inverter drives. Simulation and Implementation results are shown to verify the usefulness of FPGA as a Application Specific Integrated Circuit(ASIC) in power electronics applications

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.217-224
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• 2002

The performance demonstration round robin test was conducted to quantify the capability of ultrasonic inspection for in-service and to address some aspects of reliability for nondestructive evaluation. The fifteen inspection teams who employed procedures that met or exceeded ASME Sec. XI code requirements detected the piping of nuclear power plant with various cracks to evaluate the capability of detection. With data from PD-RR test, the performance of ultrasonic nondestructive inspection could be assessed using probability of length and depth sizing of cracks.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.5
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• pp.427-434
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• 2003

This paper describes a new method of detecting rotor position in switched reluctance motor(SRM), Some strategies of position sensorless control methods for the motor include the measurement of phase current and applied pulse voltage in an unexcited phase. The principle of the estimation of a rotor position is based on the detection of inductance by pulse currents. This sensorless method is very simple to compute rotor position estimation and gives efficient control of drive system. Suggested method is verified by some experimental tests.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.621-628
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• 1998

In order to develop an inspection algorithm for an automatic eggshell inspection system, acoustic impulse response with neural network method was studied. An improved error backpropagation algorithm was selected as a loaming rule of neural network, and three layer network was chosen for the neural network architecture. Acoustic signals in time domain and theirs power spectrum were studied as the input to the neural network. The classification feasibility and success rate were investigated in terms of statistical analysis and neural network approach. As a result, the success rate was 95% with the statistical model having five independent variables. Among the neural network models studied, the power spectrum of acoustic signal as the input with 64 input neurons and the two impact data showed the success rate of 95.5% which was slightly higher than of statistical analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.445-446
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• 2006

This paper is concerned with a substantial speed up of image processing methods and less power consumption on 2D images making use of modern FPGA (Field Programmable Gate Array) technology. We implemented 2D FFT and edge detection algorithms based on FPGA and examined processing time and power consumption compared with C/C++ and Alti-Vec technologies.