• 제목/요약/키워드: Thermal Cameras

검색결과 83건 처리시간 0.028초

태양 복사와 열화상이미지의 관계에 대한 기초 연구 (A Basic Study to Reveal the Relationships between Solar Thermal Radiation and Thermographic Images)

  • 김정배
    • 융복합기술연구소 논문집
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    • 제10권1호
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    • pp.13-17
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    • 2020
  • Among the factors that must be taken into account when using thermal imaging cameras that are expanding their application to various fields, a basic study was conducted focusing on temperature on the effect of solar radiation on the photographed thermal image. Through all experiments, in order to use an image taken with a thermal imaging camera for an object installed or located outdoors, a separate temperature correction according to the size of solar radiation or a separate device to block the effect of solar radiation must be additionally installed. Since the temperature of the same object may vary in the thermal image taken indoors or outdoors, it is necessary to calibrate it through comparison with other temperatures as a reference point. In the case of measuring the temperature of a glossy surface such as metal indoors with a thermal imaging camera, it was confirmed that an environment that can remove the light reflection effect by the glossy surface must be constructed and photographed.

알루미늄 스퍼터링 처리 의류소재의 스텔스 특성과 전자파 차단 및 전기적 특성에 관한 연구 - 밀도 변화를 중심으로 - (Stealth, electromagnetic interception, and electrical properties of aluminum sputtered clothing materials - Focusing on the density change -)

  • 한혜리
    • 복식문화연구
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    • 제30권4호
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    • pp.579-593
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    • 2022
  • This study examines the surface characteristics, electrical conductivity, electromagnetic wave blocking characteristics, infrared (IR) transmittance, stealth function, thermal characteristics, and moisture characteristics of IR thermal imaging cameras. Nylon film (NFi), nylon fabric (NFa), and 5 types of nylon mesh were selected as the base materials for aluminum sputtering, and aluminum sputtering was performed to study IR thermal imaging, color difference, temperature change, and so on, and the relationship with infrared transmittance was assessed. The electrical conductivity was measured and the aluminum-sputtered nylon film demonstrated 25.6kΩ of surface resistance and high electrical conductivity. In addition, the electromagnetic wave shielding characteristics of the sputtering-treated nylon film samples were noticeably increased as a result of aluminum sputtering treatment as measured by the electromagnetic wave blocking characteristics. When NFi and NFa samples with single-sided sputtering were placed on the human body (sputtering layer faced the outside air) and imaged using IR thermographic cameras, the sputtering layer displayed a color similar to the surroundings, showing a stealth effect. Moreover, the tighter the sample density, the better the stealth function. According to the L, a, b measurements, when the sputtering layer of NFi and NFa samples faced the outside air, the value of a was generally high, thereby demonstrating a concealing effect, and the △E value was also high at 124.2 and 93.9, revealing a significant difference between the treated and untreated samples. This research may be applicable to various fields, such as the military wear, conductive sensors, electromagnetic wave shielding film, and others.

멀티모달 방식을 통한 가스 종류 인식 딥러닝 모델 개발 (Development of Gas Type Identification Deep-learning Model through Multimodal Method)

  • 안서희;김경영;김동주
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제12권12호
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    • pp.525-534
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    • 2023
  • 가스 누출 감지 시스템은 가스의 폭발성과 독성으로 인한 인명 피해를 최소화할 핵심적인 장치이다. 누출 감지 시스템은 대부분 단일 센서를 활용한 방식으로, 가스 센서나 열화상 카메라를 통한 검출 방식으로 진행되고 있다. 이러한 단일 센서 활용의 가스 누출감지 시스템 성능을 고도화하기 위하여, 본 연구에서는 가스 센서와 열화상 이미지 데이터에 멀티모달형 딥러닝을 적용한 연구를 소개한다. 멀티모달 공인 데이터셋인 MultimodalGasData를 통해 기존 논문과의 성능을 비교하였고, 가스 센서와 열화상 카메라의 단일모달 모델을 기반하여 네 가지 멀티모달 모델을 설계 및 학습하였다. 이를 통해 가스 센서와 열화상 카메라는 각각 1D CNN, GasNet 모델이 96.3%와 96.4%의 가장 높은 성능을 보였다. 앞선 두 단일모달 모델을 기반한 Early Fusion 형식의 멀티모달 모델 성능은 99.3%로 가장 높았으며, 또한 기존 논문의 멀티모달 모델 대비 3.3% 높았다. 본 연구의 높은 신뢰성을 갖춘 가스 누출 감지 시스템을 통해 가스 누출로 인한 추가적인 피해가 최소화되길 기대한다.

NCM-CV 주철 제동디스크와 다양한 패드의 적합성 평가 (Compatibility Evaluation between NCM-CV Cast Iron Brake Disk and Various Pads)

  • 길형균;고태환;조동현;한성호;서승일
    • 한국철도학회논문집
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    • 제10권3호
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    • pp.251-256
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    • 2007
  • The research analyzed dynamo test results to evaluate compatibility between brake disk made of NCM-CV cast iron and various pads. The dynamo test was executed with one kind of resin pad and three kinds of sintered pads suitable for 200 km/h trains according to a program which refers to UIC 541-3. The thermocouples were established in specific location in order to measure the temperature of disk and pads. In addition, the thermal imaging camera was used for capturing the instantaneous thermal characteristic of disk. The research results may be utilized to use as basis data of pad development for NCM-CV brake disk hereafter.

열화상 영상의 Image Translation을 통한 Pseudo-RGB 기반 장소 인식 시스템 (Pseudo-RGB-based Place Recognition through Thermal-to-RGB Image Translation)

  • 이승현;김태주;최유경
    • 로봇학회논문지
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    • 제18권1호
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    • pp.48-52
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    • 2023
  • Many studies have been conducted to ensure that Visual Place Recognition is reliable in various environments, including edge cases. However, existing approaches use visible imaging sensors, RGB cameras, which are greatly influenced by illumination changes, as is widely known. Thus, in this paper, we use an invisible imaging sensor, a long wave length infrared camera (LWIR) instead of RGB, that is shown to be more reliable in low-light and highly noisy conditions. In addition, although the camera sensor used to solve this problem is an LWIR camera, but since the thermal image is converted into RGB image the proposed method is highly compatible with existing algorithms and databases. We demonstrate that the proposed method outperforms the baseline method by about 0.19 for recall performance.

화재상황에서 적용가능한 열화상 카메라의 파노라마 촬영을 위한 동일점 추출 알고리즘 (Image Matching Algorithm for Thermal Panorama Image Construction Adaptable for Fire Disasters)

  • 곽동기;김동환
    • 제어로봇시스템학회논문지
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    • 제22권11호
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    • pp.895-903
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    • 2016
  • In a fire disaster in a tunnel, people should be rescued immediately using the information obtained from cameras or sensors. However, in heavy smoke from a fire, people cannot be clearly identified by a mounted CCTV, which is only effective in a clear environment. A thermal camera can be an alternative to this in smoky situations and is capable of detecting people from their emitted thermal energy. On the other hand, the thermal image camera has a smaller field of view than an ordinary camera due to its lens characteristics and temperature error, etc. In order to cover a relatively wide area, panoramic image construction needs to be implemented. In this work, a template-based similarity matching algorithm for constructing the panorama image is proposed and its performance is verified through experiments. This scheme provides guidelines for coping with difficulty in image construction, which requires an exact correspondence search for two images in cases of heavy smoke.

Thermal Strain Measurement of Austin Stainless Steel (SS304) during a Heating-cooling Process

  • Ha, Ngoc San;Le, Vinh Tung;Goo, Nam Seo;Kim, Jae Young
    • International Journal of Aeronautical and Space Sciences
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    • 제18권2호
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    • pp.206-214
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    • 2017
  • In this study, measurement of thermophysical properties of materials at high temperatures was performed. This experiment employed a heater device to heat the material to a high temperature. The images of the specimen surface due to thermal load at various temperatures were recorded using charge-coupled device (CCD) cameras. Afterwards, the full-field thermal deformation of the specimen was determined using the digital image correlation (DIC) method. The capability and accuracy of the proposed technique are verified by two experiments: (1) thermal deformation and strain measurement of a stainless steel specimen that was heated to $590^{\circ}C$ and (2) thermal expansion and thermal contraction measurements of specimen in the process of heating and cooling. This research focused on two goals: first, obtaining the temperature dependence of the coefficient of thermal expansion, which can be used as data input for finite element simulation; and second, investigating the capability of the DIC method in measuring full-field thermal deformation and strain. The results of the measured coefficient of thermal expansion were close to the values available in the handbook. The measurement results were in good agreement with finite element method simulation results. The results reveal that DIC is an effective and accurate technique for measuring full-field high-temperature thermal strain in engineering fields such as aerospace engineering.

Study on the Thermal and Electrical Conductivity Properties of Titanium-sputtered Materials

  • Han, Hye Ree
    • 한국의류학회지
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    • 제46권3호
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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.

Breast Cancer Detection with Thermal Images and using Deep Learning

  • Amit Sarode;Vibha Bora
    • International Journal of Computer Science & Network Security
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    • 제23권8호
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    • pp.91-94
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    • 2023
  • According to most experts and health workers, a living creature's body heat is little understood and crucial in the identification of disorders. Doctors in ancient medicine used wet mud or slurry clay to heal patients. When either of these progressed throughout the body, the area that dried up first was called the infected part. Today, thermal cameras that generate images with electromagnetic frequencies can be used to accomplish this. Thermography can detect swelling and clot areas that predict cancer without the need for harmful radiation and irritational touch. It has a significant benefit in medical testing because it can be utilized before any observable symptoms appear. In this work, machine learning (ML) is defined as statistical approaches that enable software systems to learn from data without having to be explicitly coded. By taking note of these heat scans of breasts and pinpointing suspected places where a doctor needs to conduct additional investigation, ML can assist in this endeavor. Thermal imaging is a more cost-effective alternative to other approaches that require specialized equipment, allowing machines to deliver a more convenient and effective approach to doctors.

Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras

  • Ik Jae Jin;Do Yeong Lim;In Cheol Bang
    • Nuclear Engineering and Technology
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    • 제55권2호
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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.