• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.09a
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• pp.173-180
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• 2002

This paper presents a signal processing procedure to detect damage locations of frame structures by using continuous wavelet transform. Morlet wavelet is used as a mother wavelet in wavelet transform. Wavelet transform has the characteristics that allows the use of long time intervals at more precise low-frequency information, and shorter regions at high-frequency information. By this wavelet transform characteristics, Morlet wavelet may be used to identify the locations of damages in the structures. The numerical case studies show that this method can be applied to detect the damage location under a controlled sweeping load.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.161-167
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• 2012

It is known that big brown bats can distinguish echo of a prey at various angles. In this paper, we suggest a new object localization strategy using ultrasonic echolocation. We calculate the relative energy ratio between a high frequency component of ultrasound signal and a low frequency component of ultrasound signal for a target object. We found the measure depends on bearing angle of the object in space. We also tested energy ratio of echoed FM ultrasound signals depending on frequency, based on cross-correlation. It can determine the relative angular position of objects even though the reflected signals are congested form each object.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.898-902
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• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

• Journal of IKEEE
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• v.24 no.4
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• pp.1004-1010
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• 2020

This paper proposes an initial rotor magnetic pole detection method for single-phase permanent magnet synchronous motors. The target motor cannot obtain position information based on the back emf in the low speed and stop state. Therefore, an open loop starting process is required, and in this process, initial rotor position information for low current and soft start is need. The proposed initial rotor magnetic pole detection algorithm considers the effect of asymmetric air- gap and magnetic flux. In addition, the high-frequency voltage signal injection and the offset voltage for accurate detection is used. As a result, the permanent magnet poles are is determined by acquiring the maximum value of the induced current using the virtual dq-axis.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.221-224
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• 1995

In speech signal processing, it is necessary to detect exactly the pitch. The algorithms of pitch extraction with have been proposed until now are difficult to detect pitches over wide range speech signals. In this paper, thus, we proposed a new pitch detection algorithm that used a low pass filter with variable bandwidth. It is the method that preprosses to find the first formant of speech signals by the FFT at each frame and detects the pitches for signals LPFed with the cut off frequency according to the first formant. Applying the method, we obtained the pitch contours, improving the accuracy of pitch detection in some noise environments.

• Proceedings of the KIPE Conference
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• 2013.11a
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• pp.63-64
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• 2013

Induction motors' faults detection is almost a popular topic among researchers. Monitoring the output of motors is a key factor in detecting these faults. (Short-time) Fourier, (continuous, discrete) wavelet, and extended Park vector transformations are among the methods for fault detection. One major deficiency of these methods is not being able to detect the severity of faults that carry low energy information, e.g. in ball bearing system failure, there is absolutely no way to detect the severity of fault using Fourier or wavelet transformations. In this paper, the authors have applied the Discrete Wavelet Transform (DWT) frequency-domain analysis to detect bearing faults in an induction motor. In other words, in discrete transform which the output signal is decomposed in several steps and frequency resolution increases considerably, the frequency-band analysis is performed and it will be verified that first of all, fault sidebands become more recognizable for detection in higher levels of decomposition, and secondly, the inner race bearing faults turn out easier in these levels; and all these matter because of eliminating the not-required high energy components in lower levels of decomposing.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.7
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• pp.30-38
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• 2012

This paper presents packet detection, frequency offset estimation architecture and performance analysis for OFDM-based wireless personal area network (WPAN) systems. Packet detection structure is used to find the start point of a packet exactly in WPAN system as the correlation value passes the constant threshold value. The applied autocorrelation structure of the algorithm can be implemented simply compared to conventional packet detection algorithms. The proposed frequency offset estimation architecture is designed for phase rotation process structure, internal bit reduction to reduce hardware size and the frequency offset adjustment block to reduce look-up table size unlike the conventional structure. If the received signal can be compensated by estimated frequency offset through the correction block, it can reduce the impact on the frequency offset. Through the performance result, the proposed structure has lower hardware complexity and gate count compared to the conventional structure. Thus, the proposed structure for OFDM-based WPAN systems can be applied to the initial synchronization process and high-speed low-power WPAN chips.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.3
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• pp.243-250
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• 2009

The expression of signal to noise ratio (SNR) is derived for the individual echo sounder and for the general specifications of commercial echo sounder. The SNR is depicted by several factors on transmitting and receiving, sound propagation, scattering by fishes, and mainly self ship noise. The detection ranges of echo sounders in depth and breadth are derived by finding the border of an acceptable SNR. The detection ranges are computed for the echo sounders of individual and general specifications. Generally, the detection range is lager for low frequencies. Increasing an electrical power and a diameter of transducer is not as effective for high frequencies as for low frequencies to increase the detection range. The theoretical results of the detection range can be applied to design low electrical power echo sounder for coastal use, to select an appropriate echo sounder, to know the capability of a sounder, and to interpret echograms. A method for evaluating and designing low electrical power echo sounder is developed. A universal diagram for the basic design of the low electrical power echo sounder where SNR is plotted against frequency is developed. An appropriate frequency, transducer diameter, and beam width are easily determined by using the diagram.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.81-88
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• 2018

Spectrum sensing, the key technology of the cognitive radio networks, is used by a secondary user to determine the frequency state of a primary user. The energy detection in the spectrum sensing determines the presence or absence of a primary user according to the intensity of the allocated channel signal. Since this technique simply uses the strength of the signal for spectrum sensing, it is difficult to detect the signal of a primary user in the low SNR band. In this paper, we propose a way to combine spectrum sensing and support vector machine using wavelet packet decomposition to overcome performance degradation in low SNR band. In our proposed scheme, the sensing signals were extracted by wavelet packet decomposition and then used as training data and test data for support vector machine. The simulation results of the proposed scheme are compared with the energy detection using the AUC of the ROC curve and the accuracy according to the SNR band. With simulation results, we demonstrate that the proposed scheme show better determining performance than one of energy detection in the low SNR band.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.15-18
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• 2004

A high data rate Wireless Personal Area Networks (WPAN) system is a hot issue in wireless communication communities and being standardized. Multi-band Orthogonal Frequency Division Multiplexing (MB-OFDM) is one of the candidates for WPAN standard. In this paper, we discuss the PLCP (Physical Layer Convergence Protocol) structure for MB-OFDM. Also we evaluate the performance of two signal detection algorithms, which are the method of cross-correlation with the original preamble and the signed preamble. The latter has a low complexity with a little degradation.