• 한국의류산업학회지
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• 제12권6호
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• pp.843-850
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• 2010

To evaluate the heating performance of commercial heated vests, we investigated the thermal images and the temperature between body and vest for three heated vests. We captured infrared thermography by FT-IR Spectrometer to analyzed the heating temperature of the heating elements taken from the vests, and the maximum heating temperature of the vests was compared with thermal image in the room temperature($18^{\circ}C$). In outdoor experiment($-4.7^{\circ}C$), we measured the inner temperature as well as the thermal image of heated vests. Four healthy men participated in this experiment, and the ANOVA and Duncan test was performed for statistical analysis. As the results, the heating temperature range of the heated vests used in this experiment was $32{\sim}42^{\circ}C$, much lower than the displayed temperature range in their specifications, so the exact specification for heating performance of heated clothing was required. In comparisons of the heating performance among the heated vests, we found out that the insulation of clothing is very important to design the heated clothing, because the inner temperature of the vest had good insulation by itself was higher than that of the vest shown higher temperature over $7^{\circ}$ than another vests at the heating temperature.

• 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.

• Smart Structures and Systems
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• 제32권2호
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• pp.123-133
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• 2023

This paper proposes a thermography-based coating thickness estimation method for steel structures using model-agnostic meta-learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured using an infrared (IR) camera. The measured heat responses are then analyzed using model-agnostic meta-learning to estimate the coating thickness, which is visualized throughout the inspection surface of the steel structure. Current coating thickness estimation methods rely on point measurement and their inspection area is limited to a single point, whereas the proposed method can inspect a larger area with higher accuracy. In contrast to previous ANN-based methods, which require a large amount of data for training and validation, the proposed method can estimate the coating thickness using only 10- pixel points for each material. In addition, the proposed model has broader applicability than previous methods, allowing it to be applied to various materials after meta-training. The performance of the proposed method was validated using laboratory-scale and field tests with different coating materials; the results demonstrated that the error of the proposed method was less than 5% when estimating coating thicknesses ranging from 40 to 500 ㎛.

• Smart Structures and Systems
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• 제24권6호
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• pp.803-812
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• 2019

Triplex composite is an epoxy-bonded joint structure, which constitutes the secondary barrier in a liquefied natural gas (LNG) carrier. Defects in the triplex composite weaken its shear strength and may cause leakage of the LNG, thus compromising the structural integrity of the LNG carrier. This paper proposes an autonomous triplex composite inspection (ATCI) system for visualizing and classifying hidden defects in the triplex composite installed inside an LNG carrier. First, heat energy is generated on the surface of the triplex composite using halogen lamps, and the corresponding heat response is measured by an infrared (IR) camera. Next, the region of interest (ROI) is traced and noise components are removed to minimize false indications of defects. After a defect is identified, it is classified as internal void or uncured adhesive and its size and shape are quantified and visualized, respectively. The proposed ATCI system allows the fully automated and contactless detection, classification, and quantification of hidden defects inside the triplex composite. The effectiveness of the proposed ATCI system is validated using the data obtained from actual triplex composite installed in an LNG carrier membrane system.

• Journal of Animal Science and Technology
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• 제59권10호
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• pp.21.1-21.6
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• 2017

Background: The aim of the study is to evaluate the effectiveness of thermographic monitoring, using the temperature changes of perianal and perivulvar areas for the determination of estrus in Anatolian Shepherd bitches. Fifteen bitches were used in the study. Blood and vaginal smear samples were collected and thermographic monitoring of perianal and perivulvar areas were carried out starting from proestrus to early diestrus. Also, external signs of estrus were investigated. Smear samples were evaluated by light microscopy after Diff-Quik staining method and superficial and keratinized superficial cells were determined as percentage (S + KS%). Progesterone and luteinizing hormone measurements were done by radioimmunoassay. The difference in temperature between perianal and perivulvar areas was evaluated through thermographic images by FLIR ResearchIR Software. Results: According to the results obtained from the study, differences between progesterone and S + KS% were statistically significant (P < 0,05). Although temperature showed increase and decrease with progesterone and S + KS%, the differences were not important statistically (P > 0,05). Serum luteinizing hormone levels did not sign any difference (P > 0,05). Conclusions: As a result, thermographic monitoring alone is not enough for estrus detection in Anatolian Shepherd bitches. However, it can be used to assist the actual estrus detection technique in terms of providing some foreknowledge by evaluating the differences in temperature.

• Smart Structures and Systems
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• 제33권1호
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.

• 비파괴검사학회지
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• 제26권4호
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• pp.211-219
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• 2006

초음파 서모그라피는 초음파 진동 에너지 여기에 의한 물체의 표면 및 표면 아래에 존재하는 결함부위의 선택적 발열 특성을 적외선 열영상 카메라로 관측하는 것이다. 결함(균열, 박리, 공극 등) 이 존재하는 구조물에 초음파 진동 에너지를 입사시킬 경우 결함 부근에서의 국부적인 발열로 인해 건전 부위와의 급격한 온도차를 드러내는 핫 스폿이 관측된다. 초음파 진동 에너지 여기에 의한 핫 스폿 관측 및 분석을 통해 결함을 진단하는 것이 초음파 서모그라피를 이용한 비파괴 결함 진단 방법이다. 이를 이용한 결함 검출을 위해서는 초음파의 진동에너지를 검사 구조물에 효율적으로 전달하는 것이 중요하다 본 논문에서는 초음파 서모그라피를 이용한 실시간 결함검출에 대해 기술한다. 초음파 진동에너지의 입사 방향에 따른 결함 검출 특성을 평가하기 위해 진동에너지의 전달 방향을 시편과 수직 또는 수평방향으로 각각 입사시켰다. 각각의 입사 방향에 따른 초음파 트랜스듀서 양단에 인가되는 전압을 디지털 오실로스코우프로 계측 비교하였다. 결함 검출에 사용한 시편은 14 mm 두께의 SUS 균열(crack) 시편, PCB 기판(1.8 mm), 인코넬 600 판(1.0 mm) 및 CFRP 판(3.0 mm)의 4종류이다. 4종류의 시편에 대해 280ms 펄스폭의 초음파에너지를 수직 수평으로 각각 입사시켰다. 4종류 모두 수직방향으로 초음파 진동에너지를 입사시켰을 때 수평방향에 비해 전달 손실이 적었다. 복합재료인 PCB, CFRP 판은 수직방향으로 초음파 진동에너지를 입사시켰을 때 수평방향에 비해 결함 위치에서 열이 크게 발생하였으며 선택적 발열 현상도 3배 이상 지속되었다. 금속재료인 인코넬 600판과 SUS 시편은 수평방향이 수직방향보다 핫 스폿이 빨리 관측되었다.

• Restorative Dentistry and Endodontics
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• 제27권4호
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• pp.370-381
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• 2002

This study was performed to evaluate the temperature rise on various position of the Buchanan plugger, the peak temperature of plugger's type and the temperature change by its touching time of heat control spling. The heat carrier system 'System B' (Model 1005, Analytic Technologies, USA) and the Buchanan's plug-gers of F, FM, M and ML sizes are used for this study. The temperature was set to 20$0^{\circ}C$ which Dr. Buchanan's "continuous wave of condensation" technique recommended on digital display and the power level on it was set to 10. In order to apply heat on the Buchanan's pluggers, the heat control spring was touched for 1, 2, 3, 4 and 5 seconds respectively. The temperature rise on the surface of the pluggers were measured at 0.5 mm intervals from tip to 20 mm length of shank using the infrared thermography (Radiation Thermometer-IR Temper, NEC San-ei Instruments, Ltd, Japan) and TH31-702 Data capture software program (NEC San-ei Instruments, Ltd, Japan). Data were analyzed using a one way ANOVA followed by Duncan's multiple range test and linear regression test. The results as follows. 1. The position at which temperature peaked was approximately at 0.5 mm to 1.5 mm far from the tip of Buchanan's pluggers (p<0.001). The temperature was constantly decreased toward the shank from the tip of it (p<0.001). 2. When the pluggerss were heated over 5 seconds, the peak temperature by time of measurement revealed from 253.3$\pm$10.5$^{\circ}C$ to 192.1$\pm$3.3$^{\circ}C$ in a touch for 1 sec, from 218.6$\pm$5.$0^{\circ}C$ to 179.5$\pm$4.2$^{\circ}C$ in a touch for 2 sec, from 197.5$\pm$3.$0^{\circ}C$ to 167.5$\pm$3.7$^{\circ}C$ in a touch for 3 sec, from 183.7$\pm$2.5$^{\circ}C$ to 159.8$\pm$3.6$^{\circ}C$ in a touch for 4 sec and from 164.9$\pm$2.$0^{\circ}C$ to 158.4$\pm$1.8$^{\circ}C$ in a touch for 5 sec. A touch for 1 sec showed the highest peak temperature, followed by, in descending order, 2 sec, 3 sec, 4 sec. A touch for 5 sec showed the lowest peak temperature (p<0.001). 3. A each type of pluggers showed different peak temperatures. The peak temperature was the highest in F type and followed by, in descending order, M type, ML type. FM type revealed the lowest peak temperature (p<0.001). The results of this study indicated that pluggers are designed to concentrate heat at around its tip, its actual temperature does not correlate well with the temperature which Buchanan's "continuous wave of condensation" technique recommend, and finally a quick touch of heat control spring for 1sec reveals the highest temperature rise.