• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.532-538
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• 2002

This study was performed to classify the fatigue crack opening and closure for three kinds of aluminum alloy using principal component analysis (PCA). Fatigue cycle loading test was conducted to acquire AE signals which come from different source mechanisms such as crack opening and closure, rubbing, fretting etc. To extract the significant feature from AE signal, correlation analysis was performed. Over 94% of the variance of AE parameters could accounted for the first two principal components. The results of the PCA on AE parameters showed that the first principal component was associated with the size of AE signals and the second principal component was associated with the shape of AE signals. An artificial neural network (ANN) an analysis was successfully used to classify AE signals into six classes. The ANN classifier based on PCA appeared to be a promising tool to classify AE signals for fatigue crack opening and closure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.5
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• pp.775-786
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• 2017

Monitoring sediment flux is crucial especially for maintaining river systems to understand morphological behaviors. Recently, hydroacoustic backscatter (or SNR) as a surrogate to empirically estimate suspended sediment concentration has been increasingly highlighted for more efficient acquisition of sediment dataset, which is difficult throughout direct sediment sampling. However, relevant contemporary researches have focused on wide range solution applicable for large natural rivers where H-ADCPs with relatively low acoustic frequency have been widely utilized to seamlessly measure streamflow discharge. In this regard, this study aimed at investigating hydroacoustical characteristics based on a very recently released H-ADCP (SonTek SL-3000) with high acoustic frequency of 3 MHz in order to capitalize its capacity to be applied for suspended sediment monitoring in laboratory conditions. SL-3000 was tested in a laboratory flume to collect SNR in conjunction with LISST-100X for actual sediment concentration and particle distribution in both sand and silt sediment injection in various amount. Conventional algorithms to correct signal attenuations for water and sediment were carefully tested to validate whether they can be applied for SL-3000. As result of analyzing the SNR-SSC correlation trand, through further study in the future, it is confirmed that SSC can be observed indirectly by using the SNR.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.491-499
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• 2023

Scattering by Sea surface roughness occurs due to sea level roughness, communication performance deteriorates by causing frequency spread in communication signals and time variation in communication channels. In order to compare the difference in time variation of underwater acoustic communication channel according to the surface roughness, an experiment was performed in a tank owned by Hanyang University Ocean Acoustics Lab. Artificial surface roughness was created in the tank and communication signals with three bandwidths were used (8 kHz, 16 kHz, 32 kHz). The measured surface roughness was converted into a Rayleigh parameter and used as a roughness parameter, and statistical analysis was performed on the time-varying channel characteristics of the surface path using Doppler spread and correlation time. For the Doppler spread of the surface path, the Weighted Root Mean Square Doppler spread (w_fσ_ν) that corrected the effect of the carrier frequency and bandwidth of the communication signal was used. Using the correlation time of the surface path and the energy ratio of the direct path and the surface path, the correlation of total channels was simulated and compared with the measured correlation time of total channels. In this study, we propose a method for efficient communication signal design in an arbitrary marine environment by using the time-varying characteristics of the sea surface path according to the sea surface roughness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.22-29
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• 2016

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target detection technique has been considered as a difficult technique. In this paper, we describe the basic concept of Fractional Fourier transform and optimal transform order. Then we analyze the relationship between time-frequency characteristics of an LFM signal and its spectrum using Fractional Fourier transform. Based on the analysis results, we present active sonar target detection method. To verify the performance of proposed methods, we compared the results with conventional FFT-based matched filter. The experimental results demonstrate the superiority of the proposed method compared to the conventional method in the aspect of AUC(Area Under the ROC Curve).

• 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.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.59-65
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• 2008

Nowadays, implantable hearing aids have been developed to solve the problems of conventional hearing aids. In case of fully implantable hearing aids, an implantable microphone is necessary to receive sound signal beneath the skin. Normally, an implantable microphone has poor frequency response characteristics in high frequency bands of acoustic signal due to the high frequency attenuation effect of skin after implantation to human body. In this paper, the implantable microphone is designed to reduce the high frequency attenuation effect of a skin by putting its resonance frequency at the attenuated range through a finite element analysis (FEA) simulation. The designed implantable microphone through the simulated results has been fabricated by manufacturing process using bio-compatible materials. By the several in-vitro experiments with pig skin, it has been verified that the designed implantable microphone has a resonance frequency around the starting part of the attenuated range and reduces the attenuation effect.

• Nuclear Engineering and Technology
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• v.39 no.3
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• pp.193-206
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• 2007

The Korea Atomic Energy Research Institute has developed an advanced fast reactor concept, KALIMER-600, which satisfies the Generation IV reactor design goals of sustainability, economics, safety, and proliferation resistance. The concept enables an efficient utilization of uranium resources and a reduction of the radioactive waste. The core design has been developed with a strong emphasis on proliferation resistance by adopting a single enrichment fuel without blanket assemblies. In addition, a passive residual heat removal system, shortened intermediate heat-transport system piping and seismic isolation have been realized in the reactor system design as enhancements to its safety and economics. The inherent safety characteristics of the KALIMER-600 design have been confirmed by a safety analysis of its bounding events. Research on important thermal-hydraulic phenomena and sensing technologies were performed to support the design study. The integrity of the reactor head against creep fatigue was confirmed using a CFD method, and a model for density-wave instability in a helical-coiled steam generator was developed. Gas entrainment on an agitating pool surface was investigated and an experimental correlation on a critical entrainment condition was obtained. An experimental study on sodium-water reactions was also performed to validate the developed SELPSTA code, which predicts the data accurately. An acoustic leak detection method utilizing a neural network and signal processing units were developed and applied successfully for the detection of a signal up to a noise level of -20 dB. Waveguide sensor visualization technology is being developed to inspect the reactor internals and fuel subassemblies. These research and developmental efforts contribute significantly to enhance the safety, economics, and efficiency of the KALIMER-600 design concept.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.107-115
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• 2021

Purpose: This study aimed to demonstrate the presence of dental caries through a photoacoustic imaging system with visible and near-infrared wavelengths, highlighting the differences between the 2 spectral regions. The depth at which carious tissue could be detected was also verified. Materials and Methods: Fifteen permanent molars were selected and classified as being sound or having incipient or advanced caries by visual inspection, radiography, and optical coherence tomography analysis prior to photoacoustic scanning. A photoacoustic imaging system operating with a nanosecond pulsed laser as the light excitation source at either 532 nm or 1064 nm and an acoustic transducer at 5 MHz was developed, characterized, and used. En-face and lateral(depth) photoacoustic signals were detected. Results: The results confirmed the potential of the photoacoustic method to detect caries. At both wavelengths, photoacoustic imaging effectively detected incipient and advanced caries. The reconstructed photoacoustic images confirmed that a higher intensity of the photoacoustic signal could be observed in regions with lesions, while sound surfaces showed much less photoacoustic signal. Photoacoustic signals at depths up to 4 mm at both 532 nm and 1064 nm were measured. Conclusion: The results presented here are promising and corroborate that photoacoustic imaging can be applied as a diagnostic tool in caries research. New studies should focus on developing a clinical model of photoacoustic imaging applications in dentistry, including soft tissues. The use of inexpensive light-emitting diodes together with a miniaturized detector will make photoacoustic imaging systems more flexible, user-friendly, and technologically viable.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.221-225
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• 2008

In this paper, to avoid the frequency analysis requiring a high sampling rate, time-warped similarity measure algorithms, which are able to classify objects even with a low-rate sampling rate as time- series methods, are presented and proposed the DTW-Cosine algorithm, as the best classifier among them in wireless sensor networks. Two problems, local time shifting and spatial signal variation, should be solved to apply the time-warped similarity measure algorithms to wireless sensor networks. We find that our proposed algorithm can overcome those problems very efficiently and outperforms the other algorithms by at least 10.3% accuracy.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2E
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• pp.71-80
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• 2002

This paper suggests the Cardioid beamforming algorithm of the doublet sensors employing DIFAR (directional frequency analysis and recording) sensor signals in the frequency domain. The algorithm enables target bearing estimation using the signals from directional sensors. The algorithm verifies its applicability by successfully estimating bearings of a target projecting ten narrow-band signals in shallow water. The estimated bearings agree very well with those from GPS (global positioning system) data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1°∼ 6.7°and 13.3∼43.6°, respectively. Estimation errors are caused by SNR (signal to noise ratio) degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.