Study on n/γ Discrimination Method Based on BP Neural Network

被引：0

作者：

Song H. ^{[1
]}

Lyu B. ^{[1
,2
]}

Li T. ^{[2
,3
]}

Niu D. ^{[1
,2
]}

Zhuang K. ^{[2
,3
]}

Liu P. ^{[2
]}

Yang X. ^{[2
]}

Qin X. ^{[2
]}

Yu B. ^{[1
,2
]}

Jiang J. ^{[2
,3
]}

机构：

[1] College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou

[2] Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing

[3] School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing

来源：

Yuanzineng Kexue Jishu/Atomic Energy Science and Technology | 2020年 / 54卷 / 01期

关键词：

BP neural network; Charge comparison method; Frequency gradient analysis method; N/γ discrimination; Pulse shape discrimination;

D O I：

10.7538/yzk.2019.youxian.0042

中图分类号：

学科分类号：

摘要：

The commonly used scintillator detectors are sensitive to neutrons and gamma rays, so it is necessary to eliminate or weaken the influence of gamma ray in neutron detection technology. BP neural network can realize the function of classifier. In this paper, BP neural network combining pulse shape discrimination technology was applied to particle discrimination in neutron and gamma ray mixed field. The purpose of memorizing and classifying test samples was achieved by training BP neural network. The accuracy of BP neural network in the discrimination of n/γ pulse waveform was verified and compared with the discrimination result of charge comparison method and frequency gradient analysis method. The results show that the discrimination method based on BP neural network can not only provide effective screening for mixed radiation field, but also improve the discrimination time compared with charge comparison method and frequency gradient analysis method. © 2020, Editorial Board of Atomic Energy Science and Technology. All right reserved.

引用

页码：187 / 192

页数：5

共 15 条

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