• Journal of Communications and Networks
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• v.9 no.4
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• pp.482-489
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• 2007

In this paper, two frequency domain signal processing techniques for pulse shape modulation(PSM) ultra wideband(UWB) systems are presented. Firstly, orthogonal detection of UWB PSM Hermite pulses in frequency domain is addressed. It is important because time domain detection by correlation-based receivers is severely degraded by many sources of distortion. Pulse-shape, the information conveying signal characteristic, is deformed by AWGN and shape-destructive addition of multiple paths from the propagation channel. Additionally, because of the short nature of UWB pulses, timing mismatches and synchronism degrade the performance of PSM UWB communication systems. In this paper, frequency domain orthogonality of the Hermite pulses is exploited to propose an alternative detection method, which makes possible efficient detection of PSM in dense multipath channel environments. Secondly, a ranging method employing the Cepstrum algorithm is proposed. This method is partly processed in the frequency domain and can be implemented without additional hardware complexity in the terminal.

• The Journal of the Acoustical Society of Korea
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• v.30 no.2
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• pp.73-79
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• 2011

This paper presents a new impulsive noise detection algorithm in speech signal. The proposed method employs the frequency domain characteristic of the impulsive noise to improve the detection accuracy while avoiding the false-alarm problem by the pitch of the speech signal. Furthermore, we proposed time-frequency domain impulsive noise detector that utilizes both the time and frequency domain parameters which minimizes the false-alarm problem by mutually complementing each other. As the result, the proposed time-frequency domain detector shows the best performance with 99.33 % of detection accuracy and 1.49 % of false-alarm rate.

• Journal of Mechanical Science and Technology
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• v.15 no.2
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• pp.232-238
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• 2001

Fast Fourier Transformation is employed to convert the head variation of a pipeline in the time domain to the amplitude of the frequency domain. Applying method of characteristics to a pipeline provides a significant frequency range for a surge introduced from the valve modulation. Inverse Fast Fourier Transformation and a Finite Impulse Response Filter can be used to remove any possible noise existing from the significant frequency range of an unsteady condition. A filtered signal shows higher potential for the inverse calculation of leakage detection than the noise-added signal does. The respective performances of Inverse Fast Fourier Transformation and a Finite Impulse Response Filter are compared in terms of leakage detection capability. Characteristics of the frequency range for multiple leakages were investigated to validate the effectiveness of the noise control method in the frequency domain.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1127-1130
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• 1999

In this paper, using one method of Additive Synthesis, Analysis-by-synthesis/Overlap-Add (ABS/OLA) method, analysis and synthesis of musical tones is processed. But peak detection of frequency domain is processed by proposed method considering the view of acoustics. It is that that harmonics frequency is times of main frequency. Using this fact, peak detection of frequency domain is useful for detection of tonal component identified musical note. It is possible to realize high-quality lour bit rate audio.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.10
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• pp.1079-1088
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• 2003

In this paper, we propose a high-resolution time-frequency domain reflectometry technique as a methodology of detection and estimation of faults on a wire. This method adopts the time-frequency cross correlation characteristics of the observed signal in both time and frequency domains simultaneously. The accuracy of the proposed method is verified with experiments using a RG type coaxial cable and comparing it with traditional time domain as well as frequency domain reflectometry methods. It is clearly shown here that the proposed algorithm produces excellent results compared to the conventional methods for single as well as multiple fault cables.

• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.12-18
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• 1991

Detecting the fundamental frequency(Fo) of the speech signal is a problem in many speech applications. A problem of the pitch detection method in the frequency domain is occurred by the first formant and the background noise. Thus, in this paper, we proposed a pitch detection algorithm in the frequency domain that reduces the effects of the first formant and the background noise by the spectral AMDF function. Several computer simulation results showed that the proposed algorithm was very effective for fundamental frequency detection.

• Journal of Advanced Navigation Technology
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• v.7 no.1
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• pp.38-50
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• 2003

In this paper, a new high resolution reflectometry scheme, time-frequency domain reflectometry (TFDR), is proposed to detect and locate fault in wiring. Traditional reflectometry methods have been achieved in either the time domain or frequency domain only. However, time-frequency domain reflectometry utilizes time and frequency information of a transient signal to detect and locate the fault. The time-frequency domain reflectometry approach described in this paper is characterized by time-frequency reference signal design and post-processing of the reference and reflected signals to detect and locate the fault. Design of the reference signal in time-frequency domain reflectometry is based on the determination of the frequency bandwidth of the physical properties of cable under test. The detection and estimation of the fault on the time-frequency domain reflectometry relies on the time-frequency domain reflectometry is compared with commercial time domain reflectomtery (TDR) instrument. In these experiments provided in this paper, TFDR locates the fault with smaller error than TDR. Knowledge of time and frequency localized information for the reference and reflected signal gained via time-frequency analysis, allows one to detect the fault and estimate the location accurately.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.522-523
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• 2014

Analysis of faults in induction motors has become a major field of research due to importance of loss and damage reduction and maximum online performance of motors. There are several methods to analyze the faults in an induction motor from conventional Fourier transform to modern decision-making neural networks. Considering detectability of fault among all methods, a new fault detection solution has been proposed; it is called as frequency-domain Discrete Wavelet Transform (FD-DWT). In this method, the stator current is decomposed through series of low- and high-pass filters and consequently, the fault characteristics are more visible, because additional components have been reduced. The objective of this paper is early detection of input voltage unbalance in induction motor using wavelet transform in frequency domain. Experimental results show the effectiveness of the proposed method in early detection of faults.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.22-27
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• 2012

Correct and fast detection of a micro-grid (MG) islanding is essential to the MG since operation, control and protection of the MG depend on an operating mode i.e., an interconnected mode or an islanding mode. When islanding occurs, the frequency of the point of common coupling (PCC) is not the nominal frequency during the transient state owing to the frequency rise or drop of generators in the MG. Thus, the active and reactive power calculated by the frequency domain based method such as Fourier Transform might contain some errors. This paper proposes an islanding detection algorithm for the MG based on the instantaneous active and reactive powers delivered to the dedicated line in the time domain. During the islanding mode, the instantaneous active and reactive powers delivered to the dedicated line are constants, which depend on the voltage of the PCC and the impedance of the dedicated line. In this paper, the instantaneous active and reactive powers are calculated in the time domain and used to detect islanding. The performance of the proposed algorithm is verified under various scenarios including islanding conditions, fault conditions and load variation using the PSCAD/EMTDC simulator. The results indicate that the algorithm successfully detects islanding for the MG.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.45-50
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• 2004

This paper describes a method of detecting formation boundaries, and permeable fractures, from frequency-domain Stoneley wave logs. Field data sets were collected between the depths of 330 and 360 m in well EE-4 in the Higashi-Hachimantai geothermal field, using a monopole acoustic logging tool with a source central frequency of 15 kHz. Stoneley wave amplitude spectra were calculated by performing a fast Fourier transform on the waveforms, and the spectra were then collected into a frequency-depth distribution of Stoneley wave amplitudes. The frequency-domain Stoneley wave log shows four main characteristic peaks at frequencies 6.5, 8.8, 12, and 13.3 kHz. The magnitudes of the Stoneley wave at these four frequencies are affected by formation properties. The Stoneley wave at higher frequencies (12 and 13.3 kHz) has higher amplitudes in hard formations than in soft formations, while the wave at lower frequencies (6.5 and 8.8 kHz) has higher amplitudes in soft formations than in hard formations. The correlation of the frequency-domain Stoneley wave log with the logs of lithology, degree of welding, and P-wave velocity is excellent, with all of them showing similar discontinuities at the depths of formation boundaries. It is obvious from these facts that the frequency-domain Stoneley wave log provides useful clues for detecting formation boundaries. The frequency-domain Stoneley wave logs are also applicable to the detection of a single permeable fracture. The procedure uses the Stoneley wave spectral amplitude logs at the four frequencies, and weighting functions. The optimally weighted sum of the four Stoneley wave spectral amplitudes becomes almost constant at all depths, except at the depth of a permeable fracture. The assumptions that underlie this procedure are that the energy of the Stoneley wave is conserved in continuous media, but that attenuation of the Stoneley wave may occur at a permeable fracture. This attenuation may take place at anyone of the four characteristic Stoneley wave frequencies. We think our multispectral approach is the only reliable method for the detection of permeable fractures.