• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.1
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• pp.154-162
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• 2019

Large scale damage has been globally increased due to natural disasters such as earthquake. Although a variety of studies secured seismic performance of buildings, casualties and economic loss have occurred because of poor security of seismic performance in non-structural components. Structure's location on which non-structural components are installed and characteristics of vibration occurring on each position of structures are varied, so a response spectrum is required for each position of structures. In addition, a response spectrum occurring in a structure is different, depending on the form of it and positions on which it is installed. Therefore, selection of a response spectrum is important, so a definite method for calculating the response spectrum which acts on non-structural components is necessary. A method for choosing a response spectrum is suggested in this paper, and a structural analysis was conducted with the suggested method, by selecting a ground response spectrum and a structural system, which may occur in Korea. Moreover, it helps create a response spectrum necessary for a seismic test of non-structural components, by suggesting the method for deduction it, with a simple formula.

• Journal of electromagnetic engineering and science
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• v.10 no.3
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• pp.190-198
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• 2010

This paper evaluates the performance of two methods of spectrum sensing: the linear combining method and the selection combining method which is based on maximum SNR of sensing channel. We proposed a rule for global detection for the purpose of combating hidden terminal problems in spectrum sensing. Our analysis considers a situation when sensing channels experience the non-identically, independently distributed(n.i.d) Rayleigh fading. The average probabilities of global detection in these methods are derived and compared. In the scope of this paper, the reporting channels are assumed to be the AWGN channel with invariant and identical gain during the system's operation.

• Journal of KSNVE
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• v.11 no.3
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• pp.449-454
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• 2001

The shock performance of hard disk drives has been a serious issue for portable computers and AV application HDD. Focusing on the motion of an actuator, we investigated non-operational shock mechanism and studied several parameters that affect the shock performance by experimental analysis. It was found that there are two important factors fort the actuator to endure high shock revel. One is a shock transmissibility and the other is a beating between the arm blade and the suspension. To generalize the shock transmissibility, the concept of shock response spectrum was introduced. The shock response spectrum of the actuator system was obtained experimentally and compared with that of an analytical single degree of freedom model. It was found that there was a good agreement. The first bending natural frequency of the arm blade was found to be the most important factor for the low shock transmissibility. By applying the shock response spectrum and avoiding the beating, we could design an actuator of high shock performance.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1850-1851
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• 2011

The faults of a electric motor cause to rise the maintenance and repair cost and to reduce the reliability of the electric power system. In this paper, the auto fault detection system for a induction motor is developed using the torque signal spectrum analysis. The spectrum of motor torque signal is used for finding a bearing fault feature frequency. A threshold value, for detecting the motor bearing fault is set by the difference of torque signal spectrum(FFT signal) between normal condition and faulted condition of the motor.

• Structural Engineering and Mechanics
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• v.28 no.2
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• pp.153-166
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• 2008

This paper suggests the use of wavelet multiresolution analysis (WMRA) and neural network for generation of artificial earthquake accelerograms from target spectrum. This procedure uses the learning capabilities of radial basis function (RBF) neural network to expand the knowledge of the inverse mapping from response spectrum to earthquake accelerogram. In the first step, WMRA is used to decompose earthquake accelerograms to several levels that each level covers a special range of frequencies, and then for every level a RBF neural network is trained to learn to relate the response spectrum to wavelet coefficients. Finally the generated accelerogram using inverse discrete wavelet transform is obtained. An example is presented to demonstrate the effectiveness of the method.

• Progress in Medical Physics
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• v.4 no.2
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• pp.37-47
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• 1993

The quality of radiation for a high energy x-ray beam can be specified by its attenuation curve in a selected material. The inverse Laplace transform of the attenuation curve can be used as an approximate indication of the energy spectrum of the beam. We have made a comparative investigation of the estimated spectrum obtained by the Laplace transform analysis of the transmitted exposure data measured in an absorption study of a 6MV x-ray beam. Two of existing transform pair models have been investicated and discussed.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.311-319
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• 2001

Recently, the number of seismically isolated bridges increased suddenly since the occurrence of strong earthquakes. However, because isolator lies between pier and girder, the response of the superstructure of seismically isolated bridge may be magnified and induce risk of unseating girder Consequently, the response of girder constitutes a crucial factor in designing bridge. In the case of frictional bearing, the inherent nonlinearity makes the use of former linear response spectrum unable to estimate the maximum response of the bearing, and nonlinear tlme history analysis shall be applied. In this paper, nonlinear response spectrum considering frictional element is established, and simple analysis method using such nonlinear spectrum is proposed to estimate the maximum response of the superstructure.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.22 no.1
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• pp.41-47
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• 1989

Using computer simulated irregular waves, variations of ocean wave statistics according to sea state are analyzed, and the reasonable conditions that transform the energy spectrum to individual wave statistics are discussed. Ocean wave statistics varying with sea state are found to respond linearly to the spectral peakedness parameter $Q_p$ and spectrum moments $m_n$ (n = 0, 1, 2${\cdots}{\cdots}\;\infty$ ). It is clarified that the 2nd-order spectrum moment is a reasonable parameter which represents the wave statistics including wave periods, and that the spectrum analysis should be carried out under the conditions of minimum data length of 10 times of peak period $T_p$ with time lag of $7T_p$ to satisfy the stable condition of wave statistics.

• Proceedings of the KIEE Conference
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• 1998.07e
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• pp.1656-1658
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• 1998

This paper deals with a measurement system of a distance between lightning strokes and observatory station and spectrum analysis of electric fields radiated from lightning discharges. The distance measurement system, which consists of a loop type magnetic field sensor, a microphone and one chip microprocessor, is connected to a personal computer through RS232 port to acquire and process the data. This system is to use a difference of propagation velocity between an electromagnetic wave and a sonic wave produced by lightning discharge. Also, an electric field waveform and a frequency spectrum were investigated by an electric field measurement system with a hemisphere antenna and a spectrum analyzer with a biconical antenna and a log-periodic antenna, respectively. The results would be used as a basic reference to protect the power systems and electric circuits from lightning overvoltages.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.879-880
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• 2006

The subject of this paper is to recognize the stable state of EEG using wavelet transform and power spectrum analysis. An alpha wave, showed in stable state, is dominant wave for a human EEG and a beta wave displayed excited state. We decomposed EEG signal into an alpha wave and a beta wave in the process of wavelet transform. And we calculated each power spectrum of EEG signal, an alpha wave and a beta wave using Fast Fourier Transform. We recognized the stable state by making a comparison between power spectrum ratios respectively.