• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.

• Journal of Sensor Science and Technology
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• v.9 no.1
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• pp.44-50
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• 2000

Every object emits some energy from its surface. The emission energy forms surface heat distribution which we can capture by using an infrared thermal imager. The infrared thermal image may include valuable information regarding to the subsurface anomaly of the object. Since a thermal image reflects surface clutter and subsurface anomaly, we have difficulty in extracting the information on the subsurface anomaly only with thermal images taken under a wavelength. Thus, we use visible wavelength images of the object surface to remove exterior clutter. We, therefore in this paper, visualize the infrared image for overlaying it with a visible wavelength image. First, we make an interpolated image from two ordinary images taken from both sides of an infrared sensor. Next, we overlay the intermediate image with an infrared image taken from the infrared camera. The technique suggested in this paper can be utilized for analyzing the infrared images on non-destructive inspection against disaster and for safety.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.797-807
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• 2014

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of $1^{\circ}C$.

• Journal of Sensor Science and Technology
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• v.14 no.5
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• pp.337-342
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• 2005

A silicon-based micro-reactor to amplify small amount of deoxyribonucleic acid (DNA) has been fabricated using micro-electro-mechanical systems (MEMS) technology. Polymerase chain reaction (PCR) of DNA requires a precise and rapid temperature control. A Pt sensor is integrated directly in the chamber for real-time temperature measurement and an infrared lamp is used as external heating source for non-contact and rapid heating. In addition to the real-time temperature sensing, PCR needs a rapid thermocycling for effective PCR. For a fast thermal response, the thermal mass of the reactor chamber is minimized by removal of bulk silicon volume around the reactor using double-side KOH etching. The transparent optical property of silicon in the infrared wavelength range provides an efficient absorption of thermal energy into the reacting sample without being absorbed by silicon reactor chamber. It is confirmed that the fabricated micro-reactor could be heated up in less than 30 sec to the denaturation temperature by the external infrared lamp and cooled down in 30 sec to the annealing temperature by passive cooling.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.112-119
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• 2000

A die-casting junction method is usually used to manufacture the tub of an IH(induction heating) jar. If there is a very small air bubble in the junction area, the thermal conductivity is deteriorated and local overheat occurs. Such problem brings serious inferiority of the IH jar. In this paper, we propose a new method to detect such defect with simply measured thermal data. Thermal distribution of preheated tubs is obtained by scanning with infrared thermal sensors and analyzed with the statistic pattern recognition method. By defining the characteristic feature as the temperature difference between sensors and using ellipsoid function as decision boundary, a supervised learning method of genetic algorithm is proposed to obtain the required parpameters. After applying the proposed method to experiment, we have proved that the rate of recognition is high even for a small number of data set.

• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.237-247
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• 2018

In this paper, we describe a sensor module that monitors fire environment by analyzing fire characteristics. We analyzed the smoke characteristics of indoor fire. Six different environments were defined according to the type of smoke and the flame, and the sensors available for each environment were combined. Based on this analysis, the sensors were selected from the perspective of firefighter. The sensor module consists of an RGB camera, an infrared camera and a radar. It is designed with minimum weight to fit on the robot. the enclosure of sensor is designed to protect against the radiant heat of the fire scene. We propose a single camera mode, thermal stereo mode, data fusion mode, and radar mode that can be used depending on the fire scene. Thermal stereo was effectively refined using an image segmentation algorithm, SLIC (Simple Linear Iterative Clustering). In order to reproduce the fire scene, three fire test environments were built and each sensor was verified.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.5
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• pp.366-371
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• 2012

In this paper, fabricated by MEMS uncooled micro-bolometer detector for the study in the infrared sensitivity enhancement. Absorption layer SiOx-Metal series MDTF (metal-dielectric thin film) by high absorption rate and has a high thermal coefficient of resistance, low noise characteristics were implemented. Then MDTF were made in a vacuum deposition method. And MDTF for the analysis of the physical properties of silicon wafers were fabricated, TCR (temperature coefficient of resistance) value was made in order to measure the glass wafer and FT-IR (Fourier Transform Infrared spectroscopy) values were made in order to measure the germanium window. The analyzed results of MDTF -3 [%/K] has more characteristics of the TCR. And 8~12 um wavelength region close to 70% in the absorption characteristic.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.3
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• pp.530-544
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• 2022

Titanium exhibits substantial corrosion resistance, strength, and ductility, with a specific gravity of approximately 4.5 and a melting point of approximately 1800℃. It is currently used in aircraft parts and space development. This study considered the thermal characteristics, stealth effects of infrared thermal imaging cameras, electromagnetic shielding, and electrical conductivity of Ti-sputtered materials. Base materials of different densities and types were treated using titanium sputtering. Infrared thermal imaging showed a better stealth effect when the titanium layer was directed toward the outside. The film sample presented a better stealth effect than the fabrics did. In each of the samples subjected to titanium sputtering, when the titanium layer was directed outward, the untreated sample or exposed titanium layer showed surface temperatures lower than those of the samples with the titanium layer oriented toward the heat source. Additionally, after the titanium sputtering treatment, the films conducted electricity (low resistance) better than the fabrics did. All titanium-sputtered specimens presented reduced electromagnetic wave transmission and significantly reduced infrared transmission. These results are expected to apply to military uniforms (soldiers' protective clothing to gain the upper hand on the battlefield), medical sensors, multifunctional intelligent textiles and etc.

• 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 Sensor Science and Technology
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• v.8 no.3
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• pp.226-231
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• 1999

Pyroelectric infrared sensors have been fabricated using P(VDF/TrFE) film with pyroelectric effect. The weight percent and thickness of the poled P(VDF/TrFE) film are 75/25 percent and $25\;{\mu}m$ respectively. For easier fabrication and connection method new top and bottom electrodes design was adapted for human body detecting pyroelectric infrared sensor. An aluminum infrared absorption electrode and bottom electrode were deposited by thermal evaporator. And the device was mounted in TO-5 housing to detect infrared light of $5.5{\sim}14\;{\mu}m$ wavelength. The responsibility, NEP (noise equivalent power) and specific detectivity $D^*$ of the device were $9.62{\times}10^5\;V/W$, $3.95{\times}10^{-7}\;W$ and $5.06{\times}10^5\;cm/W$ under emission energy of $13\;{\mu}W/cm^2$ respectively.