• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.446-450
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• 2021

Non-dispersive infrared (NDIR) gas sensors typically use an optical filter that transmits a discriminating 4.26 ㎛ wavelength band to measure carbon dioxide (CO2), as CO2 absorbs 4.26 ㎛ infrared. The filter performance depends on the transmittance and full width at half maximum (FWHM). This paper presents the fabrication, sensitivity, and selectivity characteristics of a distributed Bragg reflector (DBR)-based Fabry-Perot filter with a simple structure for CO2 detection. Each Ge and SiO2 films were prepared using the RF magnetron sputtering technique. The transmittance characteristics were measured using Fourier-transform infrared spectroscopy (FT-IR). The fabricated filter had a peak transmittance of 59.1% at 4.26 ㎛ and a FWHM of 158 nm. In addition, sensitivity and selectivity experiments were conducted by mounting the sapphire substrate and the fabricated filter on an NDIR CO2 sensor measurement system. When measuring the sensitivity, the concentration of CO2 was observed in the range of 0-10000 ppm, and the selectivity was measured for environmental gases of 1000 ppm. The fabricated filter showed lower sensitivity to CO2 but showed higher selectivity with other gases.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.3
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• pp.185-193
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• 2013

The plume infrared signature effects at various flight conditions of aircraft were investigated for the purpose of reducing infrared signature level. The nozzle of a virtual subsonic unmanned combat aerial vehicle was designed through a performance analysis. Nozzle and associated plume flowfields were first analyzed using a density-based CFD code and plume IR signature was then calculated on the basis of the narrow-band model. Finally, qualitative information for the plume infrared signature characteristics was obtained through the analysis of the IR signature effects at various flight conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.559-568
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• 2016

For the economic management of photovoltaic power plants, it is necessary to regularly monitor the panels within the plants to detect malfunctions. Thermal infrared image cameras are generally used for monitoring, since malfunctioning panels emit higher temperatures compared to those that are functioning. Recently, technologies that observe photovoltaic arrays by mounting thermal infrared cameras on UAVs (Unmanned Aerial Vehicle) are being developed for the efficient monitoring of large-scale photovoltaic power plants. However, the technologies developed until now have had the shortcomings of having to analyze the images manually to detect malfunctioning panels, which is time-consuming. In this paper, we propose an automatic photovoltaic panel area extraction algorithm for thermal infrared images acquired via a UAV. In the thermal infrared images, panel boundaries are presented as obvious linear features, and the panels are regularly arranged. Therefore, we exaggerate the linear features with a vertical and horizontal filtering algorithm, and apply a modified hierarchical histogram clustering method to extract candidates of panel boundaries. Among the candidates, initial panel areas are extracted by exclusion editing with the results of the photovoltaic array area detection. In this step, thresholding and image morphological algorithms are applied. Finally, panel areas are refined with the geometry of the surrounding panels. The accuracy of the results is evaluated quantitatively by manually digitized data, and a mean completeness of 95.0%, a mean correctness of 96.9%, and mean quality of 92.1 percent are obtained with the proposed algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.4
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• pp.97-103
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• 2006

A synthetic infrared image can be effectively utilized in various fields such as the recognition and tracking of targets as long as its quality is good enough to reflect the real situations. One way to improve its quality is to use the reference atmosphere which best describes atmospheric properties of regional areas. The east asian reference atmosphere has been developed to represent atmospheric properties of the east asia including Korean peninsula. However, few research has been conducted to examine the effects of this east asian reference atmosphere on the modeling and simulation. In this regard, this paper analyzes the effects of the east asian reference atmosphere on a synthetic infrared image. The research compares the atmospheric transmittance, the surface temperature, and the radiance obtained by using the east asian reference atmosphere with those of the midlatitude reference atmosphere which has been widely applied in the east asia. The results show that the differences of the atmospheric transmittance, the surface temperature, and the radiance between the east asian reference atmosphere and the midlatitude reference atmosphere are significant especially during the daytime. Therefore, it is recommended to apply the east asian reference atmosphere for generating a synthetic infrared image with targets in the east asia.

• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.5-9
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• 2019

Optical emission spectroscopy is used to identify chemical species and monitor the changes of process results during the plasma process. However, plasma process monitoring or fault detection by using emission signal variation monitoring is vulnerable to background signal fluctuations. IR heaters are used in semiconductor manufacturing chambers where high temperature uniformity and fast response are required. During the process, the IR lamp output fluctuates to maintain a stable process temperature. This IR signal fluctuation reacts as a background signal fluctuation to the spectrometer. In this research, we evaluate the effect of infrared background signal fluctuation on plasma process monitoring and improve the plasma process monitoring accuracy by using simple infrared background signal subtraction method. The effect of infrared background signal fluctuation on plasma process monitoring was evaluated on $SiO_2$ PECVD process. Comparing the $SiO_2$ film thickness and the measured emission line intensity from the by-product molecules, the effect of infrared background signal on plasma process monitoring and the necessity of background signal subtraction method were confirmed.

• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.109-115
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• 2011

Drying characteristics of squids under two dry conditions were investigated using far infrared and heated air. Dry temperatures of 40, 50 and $60^{\circ}C$ with air speed of 0.6, 0.8 and 1.2 m/s were used for evaluating far infrared squid drying. Heated air squid drying at 40 and $50^{\circ}C$ with air speed of 0.8 m/s was used as a control treatment. The two drying were evaluated in terms of drying rate, color, TBA value, aerobic bacteria, cutting shear, penetration strength, and energy consumption. The drying rate of far infrared drying was relatively faster than that of heated air drying. The drying time of far infrared drying was reduced as the drying temperature increased. The color difference of far infrared dried squids was from 18.81 to 22.85, and heated air dried squid had the color different from 23.94 to 24.09. Far infrared dried squid had relatively smaller TBA values that indicate a level of rancidity. The aerobic bacteria of heated air dried squid increased from $970{\times}10^3$ to $40,000{\times}10^3$ CFU/g before and after drying, respectively. Far infrared dried squid had relatively smaller increase (from $970{\times}10^3$ to $40,000{\times}10^3$ CFU/g). The cutting shear and penetration strength for far infrared dried squids was relatively lower. In addition, far infrared squid drying consumed relatively less energy compared to heated air drying.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1125-1125
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• 2001

Micro-scale test methods are producing small-sample size where the conventional physical and chemical tests can not be used (high standard deviation, uncertain sampling conditions, low repeatability). Different small-scale test methods were developed recently for determination of physico-chemical, functional, rheological properties of wheat or wheat dough using miniaturized instruments with sophisticated sample preparation/handling and mechanics (RVA, 2 g mixograph, micro-Z-arm mixer, small-scale noodle maker, micro-baking method etc.). The small-scale methodologies can be used as basic research tools or as technology supported measurements and can be also essential in the early selection for quality traits in breeding programs. The milling as a sample preparation step is essential procedure providing good quality flour or semolina samples from small amount of grain (5-10 g) in a reproducible and reliable way. The aim of present study was to use NIR as quality control tool, and to evaluate the recently developed and manufactured micro-scale lab mill (FQC-2000) produced by Inter-Labor Co. Ltd., Hungary. The milling characteristics of the new instrument were compared to other laboratory mills and the effects of milling action on the chemical composition of fractions were analysed. The fractions were tested with both chemical and near infrared spectroscopic methods. The micro-scale milling resulted significantly different yields, particle size distributions and different fractions from compositional point of view. The near infrared spectra were sensitive enough to distinguish the fractions obtained by different milling procedures. Quantitative NIR calibration equations were developed and tested in order to measure the chemical composition of characteristic milling fractions. Special qualification procedure the PQS (Polar Qualification System) method was used for detecting the differences between fractions obtained by macro and micro-milling procedures. The results and the limitations of PQS method in this application will be discussed.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.82-89
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• 2014

The damage in germanium (Ge) optical window irradiated by a near-infrared continuous wave (CW) laser was studied. Laser-induced heating and melting process were surveyed, and the specific laser power and the irradiance time to melt were estimated by numerical simulation. The experiments were also carried out to investigate the macro and micro structure change on Ge window. Results showed that the surface deformation was formed by melting and resolidification process, the damaged surface had a polycrystalline phase, and the transmittance as an optical performance factor in mid-infrared region was decreased. We confirmed that an abnormal polycrystalline phase and surface deformation effect such as hillock formation and roughness increase reduced the transmittance of Ge window and were the damage mechanism of CW laser induced damage on Ge window.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.12
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• pp.1054-1061
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• 2016

Development of an accurate infrared signature (IR) measurement system is expected to contribute in the development of low observable technology and the spectroscopic analysis of electromagnetic radiation. Application of a spectroradiometer (SR) allows for the measurement of detailed infrared signature from the exhaust plume due to its own heat source. Establishment of a measurement system using a micro-turbo engine is intended to simulate the modelling of the aircraft plume. The engine was installed on a test stand to measure the engine performance. The IR signature was measured by placing the SR perpendicular to the axis line of the exhaust plume. Reference data from the blackbody were also measured to calibrate the raw data, and the infrared signature of the background was also measured for comparison with that of the plume. The calibrated spectral radiance was obtained through the data reduction process and the results were analyzed in specific bands. The experiments revealed that the measurement system established here showed sufficient performance for further comprehensive analysis.