• Journal of the Korean earth science society
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• v.33 no.5
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• pp.395-400
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• 2012

One of the main problems concerning the shallow seismic survey is how to generate high frequency signals with large amplitudes using small seismic sources. If one could focus the seismic energy in the direction of the survey line, it will be much helpful in identifying the first break. In this research, we have used hammer as an impulsive source and compared the signal powers generated by different shapes of the hammer plates: circular, square, and rectangular. The experiment was conducted by calculating the power spectral density function to compare the frequency spectrum and signal power. In the direction perpendicular to the long side of the rectangular plate, the largest seismic energy with the highest frequency was achieved even with the same weights of hammer plates. Our conclusion is that it is more efficient to use a rectangular plate than a circular (or square) one when conducting a 2-D shallow seismic survey.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.195-200
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• 2013

Road loads data are indispensable in the evaluation of BSR (Buzz, Squeak, and Rattle) of automotive parts/modules. However, there are uncertainties on the best measurement locations for representative body motion and for seat systems. In the present study, we measure road loads at four different locations of a body. A-pillars on the driver and passenger sides and left and right frame fronts of the front passenger seat mountings are selected to study the acceleration behavior at different locations. The measurements are conducted with passenger cars driving local roads at 50km/hr. The measured time-acceleration data are then transformed into PSD (power spectral density) data to compare the characteristics of local accelerations. By defining the deviated acceleration components from rigid body motion, the stiffness of vehicle body could be simply expressed in a quantitative basis. Measured data from two different vehicles are presented to demonstrate their relative vehicle body stiffness.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1955-1962
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• 2017

Induction motors are a workhorse for the industry. The condition monitoring and fault analysis are the main concern for the engineers. The bearing is one of the vital segment of the induction machine and the condition of the whole machine is decided based on the condition of the bearing. In the present paper, the vibration signal of the bearing has been used for the analysis. The first line of action is to perform a statistical analysis of the vibration signal which gives trends in signal. To get the location of a fault in the bearing the second action is to develop an index based on Wavelet Packet Transform node energy named as Bearing Damage Index (BDI). Further, Teager-Kaiser Energy Operator (TKEO) has been calculated from higher index value to get the envelope and finally Power Spectral Density (PSD) has been applied to identify the fault frequencies. A performance index has also been developed to compare the usefulness of the proposed method with other existing methods. The result shows that the strong amplitude of fault characteristics and its side bands help to decide the type of fault present in the recorded signal obtained from the bearing.

• Corrosion Science and Technology
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• v.7 no.6
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• pp.319-323
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• 2008

The polarization resistance of mild steel in 0.5M hydrochloric acid has been evaluated by using impedance (Z) and linear polarization (LPR) techniques and compared to the noise resistance obtained from electrochemical noise data. The degree of localization of this general corrosion has also been discussed by evaluating localization index and power spectral density. Polarization resistance obtained by LPR technique ($28\Omega$) was higher than that obtained by impedance technique ($15\Omega$). Noise resistance ($11\Omega$) was much lower than polarization resistance measured by both of above techniques. Higher polarization resistance obtained by LPR technique is generally caused by passivation effect in the presence of scales or deposits which can introduce an increased resistance as can low conductivity electrolytes. The reason why noise resistance is lower than polarization resistance is the effect of background noise detected by using three platinum electrodes cell in 0.5M hydrochloric acid. Slope($-\beta$) of power spectral density (PSD) obtained from analysis of noise data ($-\beta$ = 3.3) was much higher than 2 which indicates mild steel corroded uniformly. Localization index (LI) calculated from statistical analysis (LI=0.08) is much lower than 1 which indicates that mild steel did not corroded locally. However, LI value is still higher than $1x10^{-3}$ and this indicates that mild steel corroded locally in microscopic point of view.

• Journal of the Korean Institute of Gas
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• v.23 no.3
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• pp.27-32
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• 2019

In this study, the vorticity distribution and the temperature distribution change around a circular cylinder were compared and analyzed with time for constant inlet velocity and periodic inlet velocity. Also, the frequency characteristics of the flow were analyzed by analyzing the time variation of lift and drag and their PSD(power spectral density). In the case of constant inlet velocity, the well known Karman vorticity distribution was shown, and vortices were alternately generated at the upper and lower sides of the circular cylinder. In case of periodic inlet velocity, it was observed that vortex occurred simultaneously in the upper and lower sides of the circular cylinder. In both cases, it was confirmed that the time dependent temperature distribution changes almost the same behavior as the vorticity distribution. For the constant inlet velocity, the vortex flow frequency is 31.15 Hz, and for the periodic inlet velocity, the vortex flow frequency is equal to the preriodic inlet velocity at 15.57 Hz. The mean surface Nusselt number was 99.6 for the constant inlet velocity and 110.7 for the periodic inlet velocity, which showed 11.1% increase in surface heat transfer.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.433-442
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• 2003

The performance of communication systems should be tested against a set of requirements. To this end, noise generation systems are used to generate noise signals with specified characteristics. In recent study, noise generation system using DCT outperforms the conventional noise generation system when a noise model requires complicated PSD(Power Spectral Density) specifications. In this paper low area/power structures of non-DCT block in DCT-based noise generation system are proposed. Simulation results show that the low area structure results in area reduction by 61-64% and the low power structure achieves power reduction by 88-89% except DCT blocks.

• Earthquakes and Structures
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• v.7 no.6
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• pp.895-908
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• 2014

The main objective of critical excitation methods is to reveal the worst possible response of structures. This goal is accomplished by considering the uncertainties of ground motion, which is subjected to the appropriate constraints, such as earthquake power and intensity limit. The concentration of this current study is on the theoretical optimization aspect, as is the case with the majority of conventional critical excitation methods. However, these previous studies on critical excitation lead to a discontinuous power spectral density (PSD). This paper introduces some critical excitations which contain proper continuity in frequency domain. The main idea for generating such continuous excitations stems from the combination of two continuous functions. On the other hand, in order to provide a non-stationary model, this paper attempts to present an appropriate envelope function, which unlike the previous envelope functions, can properly cover the natural earthquakes' accelerograms based on multi-peak conditions. Finally, the proposed method is developed into the multiple-degree-of-freedom (M.D.O.F) structures.

• Journal of Biomedical Engineering Research
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• v.30 no.4
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• pp.327-332
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• 2009

In this paper, new index was developed to estimate the depth of anesthesia during general anesthesia using EEG. Analysis of the power spectral density(PSD) of EEG was used to develop new parameters because EEG signal tends to have slow wave during anesthesia. Classifier for index creator was developed by using SEF, BDR and BTR parameters, which are calculated by power spectral density. EEG data were obtained from 7 patients (ASA I, II) during general anesthesia with Sevoflurane. The anesthetic depth evaluation indexes ranged from 0 to 100. The average were $86.05{\pm}10.1$, $36.98{\pm}20.2$, $15.33{\pm}13.6$, $50.87{\pm}16.5$ and $87.72{\pm}11.7$ for the states of pre-operation, induction of anesthesia, operation, awaked and post-operation, respectively. The results show that while the depth of anesthesia was evaluated, more accurate information can be provided for anesthetician.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.8 s.113
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• pp.806-813
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• 2006

An important factor of vibration test using MAST(multi axial simulation table) system is the reliance of input excitation source. Generally the generation of input excitation source is obtained by the measured data on special road in proving ground. The measured data on special road have more exciting energy than the data of real fields, therefore the time and expense for test can be reduced. But the magnitude of input excitation source must be defined by comparison with the excited energy on real field. The object of this paper makes the data base of domestic roads for the definition of input excitation source which is obtained by the measured data on special road in proving ground. These real field data on domestic roads are analyzed by the power spectral density and interrelationship index.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.