Spectrometry analysis algorithm based on R-L deconvolution and fuzzy inference

Zeyu Wang; Pin Gong; Dajian Liang; Xiaobin Tang; Peng Wang; Jinzhao Zhang; Le Gao; Rui Zhang

doi:10.1016/j.apradiso.2019.108817

Spectrometry analysis algorithm based on R-L deconvolution and fuzzy inference

Appl Radiat Isot. 2019 Nov:153:108817. doi: 10.1016/j.apradiso.2019.108817. Epub 2019 Jul 23.

Authors

Zeyu Wang¹, Pin Gong², Dajian Liang¹, Xiaobin Tang³, Peng Wang⁴, Jinzhao Zhang⁵, Le Gao¹, Rui Zhang¹

Affiliations

¹ Department of Nuclear Science & Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
² Department of Nuclear Science & Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China; Jiangsu Key Laboratory of Nuclear Energy Equipment Materials Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
³ Department of Nuclear Science & Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China; Jiangsu Key Laboratory of Nuclear Energy Equipment Materials Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China. Electronic address: tangxiaobin@nuaa.edu.cn.
⁴ School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
⁵ National Ocean Technology Center, Tianjin, 300112, China.

PMID: 31357139
DOI: 10.1016/j.apradiso.2019.108817

Abstract

A spectrometry analysis algorithm based on Richardson-Lucy (R-L) deconvolution and fuzzy inference is developed to identify radionuclides of overlapping spectra obtained by a low-resolution detector. The effectiveness of the algorithm was experimentally verified. It is shown that the algorithm can be used for radionuclide analysis of low-resolution spectra in a marine environment with high accuracy of nuclide identification.

Keywords: Fuzzy inference; Peak-search; R-L deconvolution; Radionuclide identification; Spectrometry analysis.