Research on measurement method of emissivity of defective coating based on the infrared thermal imager

Boyu Wang; Huiqiang Tai; Jiaxing Gao; Anqi Zhang; Peng Zhang; Lin Lu

doi:10.1117/12.2648126

14 October 2022 Research on measurement method of emissivity of defective coating based on the infrared thermal imager

Boyu Wang, Huiqiang Tai, Jiaxing Gao, Anqi Zhang, Peng Zhang, Lin Lu

Proceedings Volume 12343, 2nd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2022); 123432U (2022) https://doi.org/10.1117/12.2648126
Event: 2nd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2022), 2022, Qingdao, China

Abstract

In this paper, an infrared thermal imager is used as a measuring instrument to build an emissivity test platform, and the system is used to measure the emissivity of defective coatings. By comparing the measured value with the true value, the effectiveness of the double temperature method and the reference volume method for the measurement of the emissivity of defective coatings is investigated. The results show that amid the use of the reference volume method, the radiation temperature of the defective coating is 317.93K, the ambient temperature is 303.07K, the emissivity of the reference coating is 0.3124, the radiation temperature of the reference coating is 311.21K, and the measurement error is not more than 0.23%; while in the use of the double temperature method, the ambient temperature is 299.15K and 300.62K, the radiation temperature of the defective coating is 307.09K and 310.22K, and the radiation temperature of the intact coating is 304.02K and 306.30K when the defective emissivity is closest to the standard value, but the error is still 9.2%.

Citation Download Citation

Boyu Wang, Huiqiang Tai, Jiaxing Gao, Anqi Zhang, Peng Zhang, and Lin Lu "Research on measurement method of emissivity of defective coating based on the infrared thermal imager", Proc. SPIE 12343, 2nd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2022), 123432U (14 October 2022); https://doi.org/10.1117/12.2648126

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