• Fire Science and Engineering
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• v.30 no.4
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• pp.27-38
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• 2016

The paper reports the development of a distributed temperature sensing (DTS) system, which is a fire detection system using optical sensor linear detectors that depends on foreign and domestic technologies. This study accordingly analyzed the electrical signal patterns of Raman scattering light mainly used for temperature sensing among back-scattered light generated in optical fiber by using an oscilloscope. Through the measurement results, it could be verified that the Stokes signal patterns had little change by the temperature increase, but the temperature-sensitive anti-Stokes patterns had relative increase of the changes. This study developed a K-DTS system, which is an optical sensor linear fire detection system composed of an optical repeater and a receiver that can detect fires using Raman scattering light. It could be verified that the developed K-DTS system satisfied the type approval standards through the sensitivity tests using the rate of rise type and fixed temperature type sensitivity testers. In addition, performance experiments have been performed for performance evaluation of the K-DTS system developed in comparison with S-DTS system which has been imported from abroad and widely used in Korea. It can be confirmed from the results of the performance experiments using model tunnels that comparable performances can be obtained in fire detection locations and the measurements of fire temperatures.

• Korean Journal of Optics and Photonics
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• v.30 no.6
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• pp.249-254
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• 2019

An optical current sensor device that measures electric current by the principle of the Faraday effect was designed and fabricated. The polarization-rotated reflection interferometer and the quadrature phase interferometer were introduced so as to improve the operational stability. Complex structures containing diverse optical components were integrated in a polymeric optical integrated circuit and manufactured in a small size. This structure allows sensing operation without extra bias feedback control, and reduces the phase change due to environmental temperature changes and vibration. However, the Verdet constant, which determines the Faraday effect, still exhibits an inherent temperature dependence. In this work, we tried to eliminate the residual temperature dependence of the optical current sensor based on polarization-rotated reflection interferometry. By varying the length of the fiber-optic wave plate, which is one of the optical components of the interferometer, we could compensate for the temperature dependence of the Verdet constant. The proposed optical current sensor exhibited measurement errors maintained within 0.2% over a temperature range, from 25℃ to 85℃.

• Composites Research
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• v.29 no.1
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• pp.1-6
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• 2016

Low-speed impact was localized on a stiffened composite structure, using 4 FBG sensors with 100 kHz-sampling rate interrogator and devised localization algorithm. The composite specimen consists of a main spar and several stringers, and the overall size of the specimen's surface is about $0.8{\times}1.2m$. Pre-stored reference data for 247 grid locations and 36 stiffener locations are gathered and used as comparison target for a random impact signal. The proposed algorithm uses the normalized cross-correlation method to compare the similarities of the two signals; the correlation results for each sensor's signal are multiplied by others, enabling mutual compensation. 20 verification points were successfully localized with a maximum error of 43.4 mm and an average error of 17.0 mm. For the same experimental setup, the performance of the proposed method is evaluated by reducing the number of sensors. It is revealed that the mutual compensation between the sensors is most effective in the case of a two sensor combination. For the sensor combination of FBG #1 and #2, the maximum localization error was 42.5 mm, with average error of 17.4 mm.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.84-89
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• 2019

This is a pilot study of machine learning based structural health monitoring system using flight data of composite aircraft. In this study, the most suitable machine learning algorithm for structural health monitoring was selected and dimensionality reduction method for application on the actual flight data was conducted. For these tasks, impact test on the cantilever beam with added mass, which is the simulation of damage in the aircraft wing structure was conducted and classification model for damage states (damage location and level) was trained. Through vibration test of cantilever beam with fiber bragg grating (FBG) sensor, data of normal and 12 damaged states were acquired, and the most suitable algorithm was selected through comparison between algorithms like tree, discriminant, support vector machine (SVM), kNN, ensemble. Besides, through neighborhood component analysis (NCA) feature selection, dimensionality reduction which is necessary to deal with high dimensional flight data was conducted. As a result, quadratic SVMs performed best with 98.7% for without NCA and 95.9% for with NCA. It is also shown that the application of NCA improved prediction speed, training time, and model memory.

• Composites Research
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• v.36 no.3
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• pp.186-192
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• 2023

Recently, in the field of railway vehicles, interest in the use of composite materials for weight reduction and transportation efficiency is increasing. Accordingly, research and commercialization development to apply composite materials to various vehicle parts are being actively conducted, and evaluation is conducted centering on post-measurement such as mechanical performance evaluation of finished products to verify quality when composite materials are applied. However, the analysis of heat and stress generated during the molding process of composite materials, which are factors that greatly affect manufacturing quality, is insufficient. Therefore, in this study, in order to verify the molding quality of composite parts for railway vehicles, the molding quality analysis was conducted for the two types of composite interior panels (laminate panel and sandwich panel) that are most actively used. To this end, temperature and strain changes were monitored during the molding process by using an FBG fiber optic sensor, which is easy to apply to the inside of the composite, and the residual strain value generated after molding was completed was measured. As a result, it was confirmed that overheating and excessive residual stress did not occur, thereby verifying the excellent molding quality of the composite interior panel for railway vehicles.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.345-351
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• 2018

We employed an unprecedented technique to synthesize porous $WO_3@SnO_2$ nanofibers exhibiting core-shell and fiber-in-tube configurations. Firstly, 2-methylimidazole was uniformly incorporated in as-spun nanofibers containing ammonium metatungstate hydrate and the sacrificial polymer (polyacrylonitrile). Secondly, the 2-methylimidazole on the surfaces of nanofibers was complexed with tin(II) chloride ($SnCl_2$) via simple impregnation of the as-spun nanofibers in ethanol containing tin(II) chloride dihydrate ($SnCl_2{\cdot}2H_2O$). The presence of vacant p-orbitals in tin (Sn) and the nucleophilic nitrogen on the imidazole ring allowed for the reaction between $SnCl_2$ and 2-methylimidazole, forming adducts on the surfaces of the as-spun nanofibers. The calcination of these nanofibers resulted in porous $WO_3@SnO_2$ nanofibers with a higher surface area ($55.3m^2{\cdot}g^{-1}$) and a better response to 1-5 ppm of acetone than pristine $SnO_2$ NFs synthesized using a similar method. An improved response to acetone was achieved upon functionalization of the $WO_3@SnO_2$ nanofibers with catalytic palladium nanoparticles. This work demonstrates the potential application of $WO_3@SnO_2$ nanofibers as sensing layers for chemiresistive sensory devices for the detection of acetone in exhaled breath.

• Journal of Microbiology and Biotechnology
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• v.11 no.6
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• pp.979-985
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• 2001

A fluorometric detection technique for HDL (High Density Lipoprotein) and LDL (Low Density Lipoprotein) was developed for application in a fiber-optic immunosensor using a protein A Langmuir-Blodgget (LB) film. For the fluorescence immunoassay, antibodies specific to HDL or LDL were imobilied on the protein A LB film, and a fluorescence amplification method was developed to overcome their weak fluorescence. The deposition of protein A using the LB technique was monitored using a surface pressure-are $({\pi}-A)$ curve, and the antibody immobilization of the protein A LB film was experimentally verified. The immobilized antibody was used to separate only HDL and LDL from a sample, then the fluorescence of he separated HDL or LDL was amplified. The amount of LDL or HDL was measured using the developed fiber optic fluorescence detection system. The optical properties resulting from the reaction of HDL or LDL with o-phtaldialdehyde, detection range, response time, and stability of the immunoassay were all investigated. The respective detection ranges for HDL and LDL were sufficient to diagnose the risk of coronary heart disease. The amplification step increased the sensitivity, while selective separation using the immobilized antibody led to linearity in the sensor signal. The regeneration of the antibody-immobilized substrate could produce a stable and reproducible immunosensor.

• Journal of Adhesion and Interface
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• v.21 no.2
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• pp.51-57
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• 2020

Recently, there has been growing interest in the study of removal of harmful and hazardous pollutants emitted by industrial activities. In this study, we have developed porous activated carbon fibers prepared by a water vapor activation method and analyzed the adsorptions of the harmful gases with electrochemical responses of activated carbon fibers. To control the uniformity of pore structures, active reaction areas, and active sites, the reaction conditions of activation temperatures were varied from 750 to 850 ℃ with the predetermined reaction time intervals (30 to 240 min). The SO₂ and NO gas adsorptions of activated carbon fibers prepared by various reaction conditions were analyzed and monitored by electrochemical sensor responses. In particular, the activated carbon fibers prepared at the reaction temperature of 850 ℃ and time of 45 min showed the highest specific surface area (1,041.9 ㎡/g) and pore characteristics (0.42 ㎤/g), and excellent adsorption capabilities of SO₂ (1.061 mg/g) and NO (1.210 mg/g) gases, respectively.

• Smart Structures and Systems
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• v.19 no.3
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• pp.335-340
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• 2017

Fiber Bragg grating (FBG) sensors are applied to structural health monitoring (SHM) in many areas due to their unique advantages such as ease of multiplexing and capability of absolute measurement. However, they are exposed to cyclic thermal load, generally in the temperature range of $-20^{\circ}C$ to $60^{\circ}C$, in railways during a long-term SHM and the cyclic thermal load can affect the mechanical strength of FBGs. In this paper, the effects of both cyclic thermal load and the reflectivity of FBGs on the mechanical strength are investigated though tension tests of FBG specimens after they are aged in a thermal chamber with temperature changes in a range from $-20^{\circ}C$ to $60^{\circ}C$ for 300 cycles. Results from tension tests reveal that the mechanical strength of FBGs decreases about 8% as the thermal cycle increases to 100 cycles; the mechanical strength then remains steady until 300 cycles. Otherwise, the mechanical strength of FBGs with reflectivity of 6dB (70%) and 10dB (90%) exhibits degradation values of about 6% and 12%, respectively, compared to that with reflectivity of 3dB (50%) at 300 cycles. SEM photos of the Bragg grating parts also show defects that cause their strength degradation. Consequently, it should be considered that mechanical strength of FBGs can be degraded by both thermal cycles and the reflectivity if the FBGs are exposed to repetitive thermal load during a long-term SHM.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.3
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• pp.281-287
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• 2001

For the conventional two-dimensional source location of acoustic emission (AE) based on the threshold crossing, wave velocity has to be measured in the actual structure to calculate the arrival-time difference and thus to form the two hyperbolae. Velocity is dependent on the fiber orientation, however, due to the dependence of elastic modulus on fiber orientation in anisotropic materials such as compost#e plates. This tan affect the accuracy of AE source location and make the source location procedure complicated. In this study, we propose a method to reduce the location error in anisotropic plates by using the numerical solution of nonlinear equations, where the velocity term has been removed by employing the fourth sensor. The efficiency and validity of the proposed method has also been experimentally verified.