Yu Kun, Guo Huige, Zhang Kaihua, Liu Yanlei, Liu Yufang
Appl Opt. 2021 Mar 1;60(7):1916-1923. doi: 10.1364/AO.412269.
Multi-wavelength radiometric thermometry has a wide application prospect in many fields. However, due to unknown emissivity, the data processing algorithm remains a difficult problem. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is proposed to inverse true temperature and spectral emissivity without assuming the emissivity model. The BFGS algorithm can automatically identify the emissivity models of different trends. These simulation results show that given different initial emissivity has no significant influence on the inverse temperature and emissivity. Then, we select 0.5 as the initial emissivity and carry out the simulation experiments at 800 and 900 K, respectively. The maximum absolute error of temperature is less than 3.5 K and the computation time is less than 0.2 s. Thus, the algorithm has high precision and efficiency. Finally, the verification experiment indicates that the BFGS algorithm is effective and reliable. The proposed method can be applied to real-time temperature measurement in many industrial processes.
多波长辐射测温法在许多领域具有广阔的应用前景。然而，由于发射率未知，数据处理算法仍然是一个难题。提出了布罗伊登-弗莱彻-戈德法布-肖诺（BFGS）算法来反演真实温度和光谱发射率，而无需假设发射率模型。BFGS算法可以自动识别不同趋势的发射率模型。这些模拟结果表明，给定不同的初始发射率对反演温度和发射率没有显著影响。然后，我们选择0.5作为初始发射率，分别在800和900 K下进行模拟实验。温度的最大绝对误差小于3.5 K，计算时间小于0.2 s。因此，该算法具有高精度和高效率。最后，验证实验表明BFGS算法是有效且可靠的。所提出的方法可应用于许多工业过程中的实时温度测量。
