• Journal of Astronomy and Space Sciences
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• v.30 no.2
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• pp.107-112
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• 2013

Tissue equivalent proportional counter (TEPC) can measure the Linear Energy Transfer (LET) spectrum and calculate the equivalent dose for the complicated radiation field in space. In this paper, we developed and characterized a TEPC for radiation monitoring in International Space Station (ISS). The prototype TEPC which can simulate a 2 ${\mu}m$ of the site diameter for micro-dosimetry has been tested with a standard alpha source ($^{241}Am$, 5.5 MeV). Also, the calibration of the TEPC was performed by the $^{252}Cf$ neutron standard source in Korea Research Institute of Standards and Science (KRISS). The determined calibration factor was $k_f=3.59{\times}10^{-7}$ mSv/R.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.71.1-71.1
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• 2014

The black hole occupation fraction in dwarf galaxies can provide an important clue for understanding the black hole seed formation. As a pilot feasibility study, we performed a KVN radio monitoring campaign over 8 months for 4 dwarf galaxies. Two galaxies (IC10 and NGC1569) are detected at 22 GHz, respectively with 39 mJy, 83 mJy. The measured flux (rms) variability is 13% and 8%, respectively for IC10 and NGC1569, while the mean flux uncertainty is 25% and 12%. Thus, the detection of the radio flux variability is at best marginal. Detecting flux variability of faint sources (i.e., 22 GHz flux < 200 mJy) seems challenging with the KVN single dishes. Combining with the 1.4 GHz flux measurements from the NVSS, we find that these two galaxies have a steep spectrum, supporting that the radio sources are AGNs. Instead of a monitoring, single-epoch multi-band observations can be effective for identifying radio AGNs by providing the constraint of the radio continuum slope.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• v.4 no.1
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• pp.44-50
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• 2001

Existing surface defects in structural members often act as sites of fatigue crack initiation, and if undetected, these cracks may grow through the thickness of the member, leading to catastrophic failure of the structure. Thus, in-service monitoring of fatigue cracks through reliable and effective nondestructive techniques is an important ingredient in the leak-before-break (LBB) design and safe operation of defects critical structures. An advanced, waveform-based, acoustic emission (AE) technique has been used in this paper to study the characteristics of the signals emanating from the initiation, growth and through-the -thickness penetration of surface fatigue crack in a 6061 aluminum plate. The goal of this experimental study is to determine whether the evolution of the fatigue crocks could be identified from the properties of the waveforms produced during the tests. The AE waveform signals detected at different stages of crack growth was found to have different temporal and spectral characteristics. The data analysis technique presented here can be applied to real-time monitoring of the initiation and propagation of fatigue cracks in structural components.

• Structural Engineering and Mechanics
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• v.66 no.2
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• pp.185-193
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• 2018

In this study, low- and high-frequency structure behaviors were identified and a systematic analysis procedure was proposed using noisy GPS data from a 165-m-high tower in ${\dot{I}}stanbul$, Turkey. The raw GPS data contained long- and short-periodic position changes and noisy signals at different frequencies. To extract the significant results from this complex dataset, the general structure and components of the GPS signal were modeled and analyzed in the time and frequency domains. Uncontrolled jumps and deviations involving the signal in the time domain were pre-filtered. Then, the signal was converted to the frequency domain after applying low- and high-pass filters, and the frequency and periodic component values were calculated. The spectrum of the tower motion obtained from the filtered GPS data had dominant peaks at a low frequency of $1.15572{\times}10-4Hz$ and a high frequency of 0.16624 Hz, consistent with two equivalent GPS datasets. Then, the signal was reconstructed using inverse Fourier transform with the dominant low frequency values to obtain filtered and interpretable clean signals. With the proposed sequence, processing of noisy data collected from the GPS receivers mounted very close to the structure is effective in revealing the basic behaviors and features of buildings.

• Current Optics and Photonics
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• v.1 no.5
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• pp.433-439
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• 2017

The rodent model has been used frequently to understand stroke pathophysiology, due to its low cost and the large spectrum of genetic strains available. Here, we present a diffuse speckle contrast analysis system (DSCA) with a $1{\times}2$ optical switch that was used to non-invasively assess cerebral blood flow (CBF) changes in the rat during intraluminal suturing for middle cerebral artery occlusion (MCAO) surgery. The blood flow index (BFI) in the left hemisphere was lower than that in the right hemisphere because the left middle cerebral artery was occluded. Furthermore, the performance of the DSCA system was compared with that of commercial laser Doppler flowmetry. The changes in the BFI measured by the two systems were correlated strongly. The DSCA system was less sensitive to motion artifacts and able to measure relatively deep tissue flow in the rat's brain. In conclusion, the DSCA system secured CBF monitoring during surgery in a rodent model without craniotomy.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.28-33
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• 2016

Since defects in the wheels of railway vehicles, which occur due to wears with the rail, cause serious damage to the running device, the diagnostic monitoring system for condition-based maintenance is required to secure the driving safety. In this paper, we studied to apply a useful Cepstrum analysis to detect periodic structure in spectrum among the vibration signal processing techniques for the fault diagnosis of a rotating body such as wheel. In order to analyze in variations of train velocity, the Cepstrum analysis was performed after a domain change of the vibration signal from time domain to rotation angle domain. When domains change, it is important to use a interpolation for a uniform interval of the rotation angle. Finally, the Cepstrum analysis for wheel flat detection was verified by using the vibration signal including the disturbance resulting from the rail irregularities and the vibration of bogie components.

• Smart Structures and Systems
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• v.29 no.3
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• pp.475-484
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• 2022

The loss of cable tension for civil infrastructure reduces structural bearing capacity and causes harmful deformation of structures. Currently, most of the structural health monitoring (SHM) approaches for cables rely on contact transducers. This paper proposes a cable tension identification technology using percussion sound, which provides a fast determination of steel cable tension without physical contact between cables and sensors. Notably, inspired by the concept of tensioning strings for piano tuning, this proposed technology predicts cable tension value by deep learning assisted classification of "percussion" sound from tapping a steel cable. To simulate the non-linear mapping of human ears to sound and to better quantify the minor changes in the high-frequency bands of the sound spectrum generated by percussions, Mel-frequency cepstral coefficients (MFCCs) were extracted as acoustic features to train the deep learning network. A convolutional neural network (CNN) with four convolutional layers and two global pooling layers was employed to identify the cable tension in a certain designed range. Moreover, theoretical and finite element methods (FEM) were conducted to prove the feasibility of the proposed technology. Finally, the identification performance of the proposed technology was experimentally investigated. Overall, results show that the proposed percussion-based technology has great potentials for estimating cable tension for in-situ structural safety assessment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.607-610
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• 2009

The abnormal combustion in the running engine results to knocking which increases the pressure and temperature in the cylinder, thereby decreasing the generated power by reducing the thermal efficiency. When the temperature and pressure in the cylinder increased rapidly by knocking, abnormal combustion takes place and the engine power is decreased. To investigate the knocking phenomenon, accelerometers are installed in the cylinder head to monitor and diagnose the vibration signal. As method of signal analysis, the time-frequency analysis method was adapted for acquisition of vibration signal and analyzes engine combustion in the short time. In this experiment, after analyzing time data which is stored in the signal recorder in one unit work (4 strokes: 2 revolutions), the signal with frequency and Wavelet methods with extracted one engine combustion data was also analyzed. Then, normal condition with no knocking signal is analyzed at this time. Hereafter, the experiments made a standard for distinguishing normal and abnormal condition to be carried out in acquisition of vibration signal at all cylinders and extracting knocking signal. In addition, analyzing methods can be diverse with Symmetry Dot Patterns (SDP), Time Synchronous Average (TSA), Wigner-Ville Distribution (WVD), Wigner-Ville Spectrum (WVS) and Mean Instantaneous Power (MIP) in the cold test [2]. With signal processing of vibration from engine knocking sensor, the authors adapted a part of engine /rotor vibration analysis and monitoring system for marine vessels to prevent several problems due to engine knocking

• Composites Research
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• v.15 no.3
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• pp.30-38
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• 2002

Fiber Bragg grating(FBG) like other optical fiber sensors also has the merit of embedding capability. To increase their actual value related to embedding capability, this paper reported the reliability and signal characteristics of FBGS embedded in composite laminates. The microphotographs of embedded optical fibers visualized the embedding environments of stripped optical fibers and coated optical fibers. Based on these microphotographs and cure monitoring performed using FBGs, we could understand that the main cause breaking the unique Bragg condition of low-birefrigence FBG were residual stress artier curing and reported the stale of stress/strain of optical fiber quantitatively. The cure monitoring also showed the history of splitting peak of a stripped FBG along cure processing. In addition, we could obtain a transverse insensitive grating(TIG) with ease by recoating a stripped FBG. TIG has good advantage for real-time signal processing.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.675-680
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• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around the world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance. CMS(Condition Monitoring System) can be used to aid plant operator in achieving these goals. Its aim is to provide operators with information regarding th e health of their machine, which in turn, can help them improve operation efficiency. In this work, wind turbine fault diagnostic algorithm which can diagnose the mass unbalance and aerodynamic asymmetry of the blades is proposed. Proposed diagnostic algorithm utilizes both FFT(Fast Feurier Transform) of the signal from accelerometers installed inside of nacelle and simple diagnostic logic. Furthermore, to verify the applicability of the proposed system, 3W small sized wind turbine system is tested and physical experiments are carried out.