27 November 2007 BP neural network application on surface temperature measurement system based on colorimetry
Author Affiliations +
Proceedings Volume 6723, 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment; 672326 (2007) https://doi.org/10.1117/12.783220
Event: 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes, 2007, Chengdu, China
Abstract
Measurement of the features of infrared radiation is very important for the precaution and discrimination of missiles, and relevant research is worthy in military application. The measurement of target's surface temperature is the foundation of infrared radiation characteristics measurement. The principle and configuration of target's surface temperature measurement system based on colorimetry is introduced, the measurement model is deduced and the processes of temperature measurement are presented. Least-square method and back-propagation neural network method are both used to deal with the demarcating data. Compared with the least-square method, Back-propagation neural network has more advantages, such as high precision, good applicability and so on.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhi-yuan Sun, Sheng Cai, Yan-feng Qiao, Wei Zhu, "BP neural network application on surface temperature measurement system based on colorimetry", Proc. SPIE 6723, 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, 672326 (27 November 2007); doi: 10.1117/12.783220; https://doi.org/10.1117/12.783220
PROCEEDINGS
5 PAGES


SHARE
Back to Top