Study on Inversion of Temperature Distribution Based on Principal Components Analysis
HU Xin-yue1, GAO Ming-xi1, REN Yu1, TAN Jian-yao1, LI Wei2, JIN Kun3, SHI San-zhi1, CAI Hong-xing1*
1. Science School at Changchun University of Science and Technology, Changchun 130022, China 2. Research Institute of China Ordnance Equipment, Beijing 100089, China 3. PLA Air Force Aviation University, Changchun 130022, China
Abstract：Multispectral radiation thermometry(MRT) is one of the methods for non-contact temperature measurement. The present MRT could invert only one approximate temperature value, and the actual temperature distribution could not be given. In the present article principal component analysis(PCA) was applied to solve the problem based on Planck’s laws. For example, in the laser damage target experiments, input laser pulse energy is 34.2 J, the inversion temperature value is 2 700 K from the thermal radiation spectrum. The fitting relative deviation is 0.5%, and when the temperature distribution is from 2 600 to 2 800 K, the fitting relative deviation is reduced to 0.13%. Temperature distribution inversion was shown based on PCA for the first time, and the measurement accuracy of non-contact temperature was improved.
胡馨月1，高明希1，任 玉1，谭见瑶1，李 伟2，金 琨3，施三支1，蔡红星1* . 基于主成分回归的温度分布反演研究[J]. 光谱学与光谱分析, 2012, 32(10): 2789-2793.
HU Xin-yue1, GAO Ming-xi1, REN Yu1, TAN Jian-yao1, LI Wei2, JIN Kun3, SHI San-zhi1, CAI Hong-xing1* . Study on Inversion of Temperature Distribution Based on Principal Components Analysis. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(10): 2789-2793.
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