Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Discrimination of neutrons and gamma-rays in plastic scintillator based on spiking cortical model

  • Bing-Qi Liu (Chengdu University) ;
  • Hao-Ran Liu (State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology) ;
  • Lan Chang (The Engineering & Technical College of Chengdu University of Technology) ;
  • Yu-Xin Cheng (The Engineering & Technical College of Chengdu University of Technology) ;
  • Zhuo Zuo (State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology) ;
  • Peng Li (The Engineering & Technical College of Chengdu University of Technology)
  • Received : 2022.03.13
  • Accepted : 2023.04.20
  • Published : 2023.09.25
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Abstract

In this study, a spiking cortical model (SCM) based n-g discrimination method is proposed. The SCM-based algorithm is compared with three other methods, namely: (i) the pulse-coupled neural network (PCNN), (ii) the charge comparison, and (iii) the zero-crossing. The objective evaluation criteria used for the comparison are the FoM-value and the time consumption of discrimination. Experimental results demonstrated that our proposed method outperforms the other methods significantly with the highest FoM-value. Specifically, the proposed method exhibits a 34.81% improvement compared with the PCNN, a 50.29% improvement compared with the charge comparison, and a 110.02% improvement compared with the zero-crossing. Additionally, the proposed method features the second-fastest discrimination time, where it is 75.67% faster than the PCNN, 70.65% faster than the charge comparison and 38.4% slower than the zero-crossing. Our study also discusses the role and change pattern of each parameter of the SCM to guide the selection process. It concludes that the SCM's outstanding ability to recognize the dynamic information in the pulse signal, improved accuracy when compared to the PCNN, and better computational complexity enables the SCM to exhibit excellent n-γ discrimination performance while consuming less time.

Keywords

References

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