Spectral emissivity measurement based on radiation at multiple temperatures

Jingjing Zhou; Xia Wang; Xiaopeng Hao; Jian Song; Chenyu Xie; Zhao Xing

doi:10.1117/12.2606784

24 November 2021 Spectral emissivity measurement based on radiation at multiple temperatures

Jingjing Zhou, Xia Wang, Xiaopeng Hao, Jian Song, Chenyu Xie, Zhao Xing

Proceedings Volume 12061, AOPC 2021: Infrared Device and Infrared Technology; 120611J (2021) https://doi.org/10.1117/12.2606784
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

Radiation temperature measurement is a non-contact temperature measurement, which has important applications in quantitative remote sensing, industrial thermal monitoring, biomedical engineering and military field. The infrared radiation of an object is directly proportional to its emissivity, which is an important parameter that affects radiation temperature measurement. In order to obtain the spectral emissivity of an object, this paper proposes a method for measuring spectral emissivity based on the radiation at multiple temperatures. Based on Planck's law of radiation, the expression of spectral emissivity is theoretically given by deriving the relationship between spectral emissivity, contact temperature and radiation. The simulation is carried out based on theoretical derivation. The spectral emissivity of three samples is simulated. The waveband of the samples is 8-14μm, and the spectral emissivity does not change with temperature. Two algorithms are used to avoid the problem of singular values in direct calculation. Based on the constrained linear least-squares method, the average relative errors of the three samples are 7.0%, 7.2%, and 6.2%. The maximum relative errors are 22.1%, 18.9% and 15.0%. Based on the improved constrained linear least-squares method, the average relative errors of the three samples are 2.2%, 1.1%, and 3.0%, and the maximum relative errors are 6.7%, 3.2%, and 4.2%. The simulation results verify the feasibility of inversion of spectral emissivity at multiple temperatures. The results show that the improved constrained linear least-squares method has smaller average relative errors.

Citation Download Citation

Jingjing Zhou, Xia Wang, Xiaopeng Hao, Jian Song, Chenyu Xie, and Zhao Xing "Spectral emissivity measurement based on radiation at multiple temperatures", Proc. SPIE 12061, AOPC 2021: Infrared Device and Infrared Technology, 120611J (24 November 2021); https://doi.org/10.1117/12.2606784

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KEYWORDS

Black bodies

Infrared radiation

Computer simulations

Remote sensing

Radiometry

Spectroscopy

Emission spectroscopy

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