• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.513-520
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• 2010

The degradation phenomenon caused by noises significantly corrupts digitalized data. Therefore, a variety of methods to preserve the edge component of signals and remove noise simultaneously have been used in time domain and frequency domain. In this paper, we have proposed a new noise reduction algorithm using wavelet approximation coefficients to reduce the mixed noise overlapping the signal. The proposed algorithm adopts the distribution characteristics of the error function which is obtained by accumulating the wavelet approximation coefficients, in order to improve the capability to separate edges of the signal and noises.

• Tribology and Lubricants
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• v.35 no.5
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• pp.317-322
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• 2019

In spite of progress in tribological research, machine component failure due to friction and wear has been reported frequently. This failure may lead to secondary damage that can cause huge expense for maintenance and repair. To prevent economic loss, it is important to detect and predict the initial failure point. In this sense, various researchers have been tried to develop Condition Monitoring (CM) method using Acoustic Emission (AE) generated while the materials undergo failure. In this study, effect of particles on friction and wear was investigated using the pin-on-plate friction test and AE signal was recorded with a band-width type AE sensor. The experiments were performed in dry and lubricant conditions using steel and glass as specimens. After the experiment, 3D laser microscope image was captured to evaluate the wear behavior quantitatively. The AE signal was analyzed in time-domain and frequency-domain. The amplitude was compared with the frictional results. The results of this study showed that particle generation accelerate wear, generate high magnitude AE signal and change the frequency characteristics of the signal. Also, lubricant condition test results showed low coefficient of friction, low wear rate, and low magnitude of AE signal compared to the dry condition. It is expected that the results of this study will aid in better assessment of wear in CM technology

• Smart Structures and Systems
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• v.33 no.1
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• pp.41-53
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• 2024

Grouting sleeves are an essential connecting component of prefabricated components, and the quality of grouting has a significant influence on structural integrity and seismic performance. The embedded grouting sleeve (EGS)'s grouting defects are highly undetectable and random, and no effective monitoring method exists. This paper proposes an ultrasonic guided wave method and provides a set of guidelines for selecting the optimal frequency and suitable period for the EGS. The optimal frequency was determined by considering the group velocity, wave structure, and wave attenuation of the selected mode. Guided waves are prone to multi-modality, modal conversion, energy leakage, and dispersion in the EGS, which is a multi-layer structure. Therefore, a time-reversal (TR)-based multi-mode focusing and dispersion automatic compensation technology is introduced to eliminate the multi-mode phase difference in the EGS. First, the influence of defects on guided waves is analyzed according to the TR coefficient. Second, two major types of damage indicators, namely, the time domain and the wavelet packet energy, are constructed according to the influence method. The constructed wavelet packet energy indicator is more sensitive to the changes of defecting than the conventional time-domain similarity indicator. Both numerical and experimental results show that the proposed method is feasible and beneficial for the detection and quantitative estimation of the grouting defects of the EGS.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.406-413
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• 2024

The proposed method uses Generalized Cross Correlation - Phase Transform (GCC-PHAT) method with nonlinear preprocessing and a frequency domain low-pass filter. In this paper, by reinterpreting the calculation process of GCC-PHAT as DFT, we derive that there is an effective frequency band used for time delay estimation in GCC-PHAT, and by using only the effective band using a low-pass filter, the noise component is reduced and it improvesthe time delay performance in impulsive noise environments. By comparing the proposed method with the traditional GCC-PHAT in an impulsive noise environment, we show that the GCC-PHAT becomes more robust to the impulsive noise.

• Journal for History of Mathematics
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• v.18 no.2
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• pp.75-94
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• 2005

This study is intended to develop the criterion for evaluating the creative products that mathematically gifted students produce in their education program to enhance the development of creative productive ability. 1 distinguish the mathematical creativity with the creativity in the general domain, and make the production model of the creative mathematical product grounded on the mathematicians' work through the mathematical history. The model has the following components; the mathematical knowledge, the mathematical thinking and the mathematical inquiry skill, surrounding the resultive creative product. The students products are focused on one component of the model. Thus the criterion for the creative products is grounded on the each component of the model. According to it, teachers could evaluate the students'work, which got the validity and the reliability.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.278-282
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• 2001

The discovery of tacit knowledge from domain experts is one of the most exciting challenges in today\`s knowledge management. The nature of decision knowledge in determining the quality a firm\`s short-term liquidity is full of abstraction, ambiguity, and incompleteness, and presents a typical tacit knowledge extraction problem. In dealing with knowledge discovery of this nature, we propose a scheme that integrates both knowledge elicitation and knowledge discovery in the knowledge engineering processes. The knowledge elicitation component applies the Verbal Protocol Analysis to establish industrial cases as the basic knowledge data set. The knowledge discovery component then applies fuzzy clustering to the data set to build a fuzzy knowledge based system, which consists of a set of fuzzy rules representing the decision knowledge, and membership functions of each decision factor for verifying linguistic expression in the rules. The experimental results confirm that the proposed scheme can effectively discover the expert\`s tacit knowledge, and works as a feedback mechanism for human experts to fine-tune the conversion processes of converting tacit knowledge into implicit knowledge.

• Wind and Structures
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• v.30 no.1
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• pp.99-117
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• 2020

This paper focuses on the processes of wind flow in atmospheric boundary layer, to produce realistic full scale pressures for design of low-rise buildings. CFD with LES turbulence closure is implemented on a scale 1:1 prototype building. A proximity study was executed computationally in CFD with LES that suggests new recommendations on the computational domain size, in front of a building model, apart from common RANS-based guidelines (e.g., COST and AIJ). Our findings suggest a location of the test building, different from existing guidelines, and the inflow boundary proximity influences pressure correlation and reproduction of peak loads. The CFD LES results are compared to corresponding pressures from open jet, full scale, wind tunnel, and the ASCE 7-10 standard for roof Component & Cladding design. The CFD LES shows its adequacy to produce peak pressures/loads on buildings, in agreement with field pressures, due to its capabilities of reproducing the spectral contents of the inflow at 1:1 scale.

• Wind and Structures
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• v.20 no.2
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• pp.169-189
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• 2015

To investigate the effects of "sudden change" of wind fluctuations on vehicle running performance, which is caused by the artificial discrete simulation of wind field, a three-dimensional vehicle model is set up with multi-body dynamics theory and the vehicle dynamic responses in crosswind conditions are obtained in time domain. Based on Hilbert Huang Transform, the effects of simulation separations on time-frequency characteristics of wind field are discussed. In addition, the probability density distribution of "sudden change" of wind fluctuations is displayed, addressing the effects of simulation separation, mean wind speed and vehicle speed on the "sudden change" of wind fluctuations. The "sudden change" of vehicle dynamic responses, which is due to the discontinuity of wind fluctuations on moving vehicle, is also analyzed. With Principal Component Analysis, the comprehensive evaluation of vehicle running performance in crosswind conditions at different simulation separations of wind field is investigated. The results demonstrate that the artificial discrete simulation of wind field often causes "sudden change" in the wind fluctuations and the corresponding vehicle dynamic responses are noticeably affected. It provides a theoretical foundation for the choice of a suitable simulation separation of wind field in engineering application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1599-1605
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• 2012

We introduced an approach of modeling of a sound absorbing medium that had different absorbing coefficient according to frequency. To obtain the time domain result of the frequency characteristics of a sound absorbing medium, transmission line matrix modeling was used. To input sound absorbing effect in TLM modeling, we added a FIR filter at a node instead of absorbing component using resistance component. There were simulated the characteristics of time-shift, low pass filter, high pass filter using the FIR filter with 7-tap coefficients, then compared with theoretical results. From various simulation results, we could find that added FIR filter coefficient in TLM modeling was an useful way to model a sound absorbing medium.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.24-29
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• 2012

The sounds of exhaust emissions of automobiles are independent sound sources which are nothing to do with voices. We have no information for the sources of voices and exhaust sounds. Accordingly, Independent Component Analysis which is one of the Blind Source Separaton methods was used to segregate two source signals from each mixed signals. Maximum Likelyhood Estimation was applied to the signals came through the stereo microphone to segregate the two source signals toward the maximization of independence. Since there is no clue to find whether it is speech signal or not, the coefficients of the slope was calculated by the autocovariances of the signals in frequcency domain. Noise remover for speech signals was implemented by coupling the two algorithms.