Optimum identifications of spectral emissivity and temperature for multi-wavelength pyrometry

被引：0

作者：

Yang, CL ^{[1
]}

Dai, JM ^{[1
]}

Hu, Y ^{[1
]}

机构：

[1] Harbin Inst Technol, Dept Elect Engn, Harbin 150001, Peoples R China

来源：

CHINESE PHYSICS LETTERS | 2003年 / 20卷 / 10期

关键词：

D O I：

暂无

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

The main problem of the traditional radiation pyrometry is that fatal errors will be caused by the unknown or varying emissivity. Based on the combined neural networks (CNNE model), we propose an improved method for emissivity modelling. The model structure and the optimum algorithm are described. This method being used, the spectral emissivity and temperature can be fast computed accurately from the spectral radiation measured.

引用

页码：1685 / 1688

页数：4

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