Spectrometry analysis based on approximation coefficients and deep belief networks

  • Jian-Ping He
  • Xiao-Bin Tang
  • Pin Gong
  • Peng Wang
  • Zhen-Yang Han
  • Wen Yan
  • Le Gao
Article
  • 57 Downloads

Abstract

A method of spectrometry analysis based on approximation coefficients and deep belief networks was developed. Detection rate and accurate radionuclide identification distance were used to evaluate the performance of the proposed method in identifying radionuclides. Experimental results show that identification performance was not affected by detection time, number of radionuclides, or detection distance when the minimum detectable activity of a single radionuclide was satisfied. Moreover, the proposed method could accurately predict isotopic compositions from the spectra of moving radionuclides. Thus, the designed method can be used for radiation monitoring instruments that identify radionuclides.

Keywords

Approximation coefficient Deep belief network Spectrometry analysis Radionuclide identification Detection rate 

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Copyright information

© Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Chinese Nuclear Society, Science Press China and Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Jian-Ping He
    • 1
  • Xiao-Bin Tang
    • 1
    • 2
  • Pin Gong
    • 1
  • Peng Wang
    • 1
  • Zhen-Yang Han
    • 1
  • Wen Yan
    • 1
  • Le Gao
    • 1
  1. 1.Department of Nuclear Science and EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina
  2. 2.Jiangsu Key Laboratory of Nuclear Energy Equipment Materials EngineeringNanjingChina

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