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Multi-wavelength radiometric thermometry data processing algorithm based on the BFGS algorithm.

Kun Yu, Huige Guo, Kaihua Zhang

|March 10, 2021

Summary

This summary is machine-generated.

This study introduces the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm for accurate multi-wavelength radiometric thermometry. The BFGS algorithm effectively determines true temperature and spectral emissivity without needing a predefined emissivity model.

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Area of Science:

* Physics and Engineering
* Thermometry and Radiometry

Background:

* Multi-wavelength radiometric thermometry offers broad industrial applications.
* Accurate temperature measurement is hindered by unknown spectral emissivity.
* Existing data processing algorithms struggle with unknown emissivity models.

Purpose of the Study:

* To develop a novel algorithm for accurate temperature and emissivity determination.
* To address the challenge of unknown emissivity in radiometric thermometry.
* To validate the effectiveness and efficiency of the proposed method.

Main Methods:

* Application of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm.
* Inverse modeling to determine true temperature and spectral emissivity.
* Simulation and verification experiments without assuming emissivity models.

Main Results:

* The BFGS algorithm successfully identifies emissivity models and inverts temperature and emissivity.
* Initial emissivity values have minimal impact on the inversion results.
* High precision (max absolute error < 3.5 K) and efficiency (computation time < 0.2 s) demonstrated.

Conclusions:

* The BFGS algorithm is a precise, efficient, and reliable method for radiometric thermometry.
* The approach accurately determines temperature and spectral emissivity without prior model assumptions.
* The method is suitable for real-time temperature measurement in industrial processes.