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A data processing algorithm for multispectral radiation thermometry based on multi-segment linear model and secondary inversion
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DOI：10.1016/j.measurement.2022.111753.png)
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摘要
En 中文
Multispectral radiation thermometry is a branch of infrared temperature measurement technology with wide application in many industries. Although this technology has been developed for decades, there is still a problem in its data processing, that is, how to accurately solve the radiation equations without the information of object's emissivity. The traditional fixed emissivity model method cannot adapt to all objects. Therefore, this study proposes a data processing algorithm for multispectral radiation thermometry based on multi-segment linear model and secondary inversion. The algorithm can automatically select the multi-segment linear model suitable for the measured object, and realize the accurate calculation of temperature and emissivity through the sec-ondary inversion. The efficiency and accuracy of the algorithm are verified through simulations. The experi-mental results of temperature measurement of aviation alloy prove the effectiveness of this algorithm in practical application.
Keyword:
Multispectral radiation thermometry
Emissivity
Linear model
DFP
Optimization
期刊
IF:
5.6
论文数:
2.1W
被引数:
5.4W
机构
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