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Inspection of Heat Seal Packing Bag Integrity Using Thermal Images With YOLO Algorithm
(2025-01-01)
Chaishome, Jedsada
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Khannakum, Wirat
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Nunak, Navaphattra
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Suesut, Taweepol
This paper presents an inspection of heat seal packing bag integrity using thermal imaging with a deep learning technique. The performance was evaluated by comparing the object detection rates obtained from the YOLOv4-Tiny Algorithm and the Convolutional Neural Network (CNN) technique. Two sets of completely sealed and failure-sealed packaging bags were prepared for the training (100 bags) and testing (100 bags) of the models. Some sample bags containing tomato sauce inserted between the seals represent a failure-sealed condition. The integrity of the heat seal packaging bag was analyzed by examining the differences in color shade patterns of the thermal images. As a result, the YOLOv4-Tiny model achieved a detection accuracy of 98.80%, significantly outperforming the CNN technique, which detected only 78.40%, while using the same dataset; additionally, the time required for detection and training was faster.
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An investigation of oil residue on surface by infrared thermography
(2020-01-01)
Chaishome, Jedsada
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Nunak, Teerawat
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Tuppadung, Yutthapong
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Suesut, Taweepol
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Nunak, Navaphattra
This work aims to propose a visual inspection, infrared thermography technique, of oil residual mass on stainless steel surface (SS) (hydrophilic surface representative) and polytetrafluoroethylene (PTFE) surface (hydrophobic surface representative). An improved understanding of the oil fouling characteristic is a key point to develop this technique. The effect of surface roughness on the oil contact angle, oil residual mass, and the resulting average temperature of the residues on SS and PTFE surface was studied. For the infrared thermography technique, the mass of oil adhered to each interface using heating at a temperature of 80<sup>0</sup>C for 10 minutes. SS AISI 304 plaques with the average surface roughness of 0.4, 0.8, and 3.2 µm and PTFE with that of 0.4 and 0.8 µm were examined. All samples were snapped top view using a thermal image camera. The average temperatures were obtained from the color spectrum of the thermal images. It could be summarized that the proposed measurement is possible to detect the accumulation of oil on the SS whereas it was not clearly different that on the PTFE surface. A greater oil residual mass on both hydrophilic and hydrophobic surfaces is a result of an increase in surface roughness and sequential wettability from the contact angle as expected. Moreover, each liquid-solid interfacial material has its specific surface characteristic. Finally, each liquid-solid interfacial material has its specific surface characteristic and the new and used oil-SS interface could be detected by infrared thermography technique.
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Investigation of soy milk deposited on stainless steel by infrared thermography
(2018-01-01)
Suesut, Taweepol
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Songthai, Maethinee
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Nunak, Navaphattra
This paper proposes a real-time investigation of soy milk deposited on stainless steel surface (SS) during the heating process by considering the relationship between emissivity and mass of soils on the surface using a thermal image processing technique. The understanding on organic fouling behavior is an important step leading to the optimum cleaning operations. The mass of soy milk deposited on SS during heating process at the temperature of 75°C for 180 min was measured by the weighing method and compared to the emissivity values analyzed from the infrared thermography in real-time. Two different types of stainless steel grades (AISI 304 and 316) with various average surface roughness (R<inf>a</inf>) values (0.4, 0.8 and 3.2 µm) were carried out. Emissivity values of sample plates which soil deposited on the surface, were obtained from the real-time processing of a thermo-map of soil film compared to the temperature of a reference surface (known emissivity value). Applying this technique to all conditions, it was found that the increasing of emissivity values of sample plates as the amount of soil film on SS increased could be detected in real-time for both SS grades. The emissivity of SS having soil on the surface was higher than a clean SS since the soil film on the SS caused the roughness of surface changed. It could also detect that emissivity values of both SS grades had no significantly difference at the same R<inf>a</inf>. From the detection of soy milk deposited on SS using the real-time thermal image processing acquired from infrared camera during heating process, it could be concluded that the proposed technique was possible to investigate the accumulation of soy milk and other soil types on the surface.
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Emissivity measurements of reflective materials using infrared thermography
(2016-01-01)
Rakrueangdet, K.
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Nunak, N.
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Suesut, T.
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Sritham, E.
This paper proposes the technique to measure the band emissivity using the infrared detector with a band pass filter of 7.5 to 14 um. The experimental setup consists of an infrared camera, K-type contact thermocouples, a tripod, a water bath, aluminium plate, a black tape, and an environmental control chamber. Three types of reflective engineering materials including aluminium, stainless steel, and copper are tested using this technique. Results are in good agreement with the findings from other literatures. Therefore, the proposed technique, which is easy to operate, can be an alternative method for measuring the emissivity of reflective materials. However, care must be taken in selecting the location the infrared camera, the material for lining internal surface of an environmental control chamber, and the temperature of chamber surface.
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Surrounding effects on temperature and emissivity measurement of equipment in electrical distribution system
(2015-01-01)
Nunak, T.
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Nunak, N.
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Tipsuwanporn, V.
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Suesut, T.
This paper reports the effect of surrounding conditions, e.g. IR radiation through IR window and the reflectivity and temperature of internal surface of chamber on the temperature and emissivity measurement. The results show that the transmission percentage of IR window is about 50 for all IR temperatures, except when the target temperature was the same as the surrounding temperature (T,ur). At this condition (Ts = Tc), the temperature readings were almost the same for all percentage of IR window. The accurate temperature measurement can be achieved by adjustment of the transmission correction in the IR camera or in the software. Considering the effect of materials surface and temperature of chamber, it can be concluded that the surrounding conditions can affect to the accurate emissivity measurement only with the high reflectance object, whereas the high emissivity object has no effect from the surround.
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Emissivity estimation using thermographic camera
(2013-11-04)
Nunak, N.
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Roonprasang, K.
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Suesut, T.
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Nunak, T.
This paper proposes a method based on the spectra response of IR detectors mounted on thermographic camera for emissivity measurement at various target surface temperatures, while the reflected temperature istaken into account, and also studies on the effect of surface roughness on the emissivity value. The emissivity (ε8-14μm) of general engineering material such as iron, stainless steel, brass, copper and aluminum obtained in this paper are in agreement with other literatures. Finally, results found that the roughness and emissivity of equipment increases with increasing of the operating time. © (2013) Trans Tech Publications, Switzerland.

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