中国物理B ›› 2005, Vol. 14 ›› Issue (10): 2041-2045.doi: 10.1088/1009-1963/14/10/020

• • 上一篇    下一篇

The measuring of spectral emissivity of object using chaotic optimal algorithm

赵国良1, 杨春玲2, 王宇野3, 赵东阳3   

  1. (1)Harbin Engineering University, Harbin 150001, China; (2)Harbin Engineering University, Harbin 150001, China;Harbin Institute of Technology, Harbin 150001, China; (3)Harbin Institute of Technology, Harbin 150001, China
  • 收稿日期:2004-08-20 修回日期:2005-06-13 出版日期:2005-10-20 发布日期:2005-10-20

The measuring of spectral emissivity of object using chaotic optimal algorithm

Yang Chun-Ling (杨春玲)ab, Wang Yu-Ye (王宇野)b, Zhao Dong-Yang (赵东阳)b, Zhao Guo-Liang (赵国良)a   

  1. a Harbin Engineering University, Harbin 150001, China; b Harbin Institute of Technology, Harbin 150001, China
  • Received:2004-08-20 Revised:2005-06-13 Online:2005-10-20 Published:2005-10-20

PDF (PC)

509

赞

摘要： There exist a considerable variety of factors affecting the spectral emissivity of an object. The authors have designed an improved combined neural network emissivity model, which can identify the continuous spectral emissivity and true temperature of any object only based on the measured brightness temperature data. In order to improve the accuracy of approximate calculations, the local minimum problem in the algorithm must be solved.Therefore, the authors design an optimal algorithm, i.e. a hybrid chaotic optimal algorithm, in which the chaos is used to roughly seek for the parameters involved in the model, and then a second seek for them is performed using the steepest descent. The modelling of emissivity settles the problems in assumptive models in multi-spectral theory.

关键词: spectral emissivity, radiation thermometric, chaotic optimal algorithm

Abstract: There exist a considerable variety of factors affecting the spectral emissivity of an object. The authors have designed an improved combined neural network emissivity model, which can identify the continuous spectral emissivity and true temperature of any object only based on the measured brightness temperature data. In order to improve the accuracy of approximate calculations, the local minimum problem in the algorithm must be solved.Therefore, the authors design an optimal algorithm, i.e. a hybrid chaotic optimal algorithm, in which the chaos is used to roughly seek for the parameters involved in the model, and then a second seek for them is performed using the steepest descent. The modelling of emissivity settles the problems in assumptive models in multi-spectral theory.

Key words: spectral emissivity, radiation thermometric, chaotic optimal algorithm

中图分类号:  (Nonlinear dynamics and chaos)

  • 05.45.-a