哈尔滨商业大学学报（自然科学版）2025，Vol.41Issue(2)：161-168,8.
基于特征融合Swin-Tiny Transformer的γ能谱识别方法
γ-ray spectrum recognition method based on feature fusion Swin-Tiny Transformer
摘要
Abstract
The nuclide identification,as the focus of the current nuclear security research direction,was considered of great significance for security protection.In order to solve the problem of slow speed and low accuracy of radionuclide identification,a nuclide identification method based on feature fusion Swin-Tiny Transformer lightweight model was proposed.The energy spectrum data of four individual radionuclides,such as 133 Ba,60 Co,152 Eu,and 137 Cs,were measured by the NaI detector to produce the training dataset;in the preprocessing stage,Gram's angle field method,Hilbert's curve method,and Chirplet transform method were used to transform the γ spectrum information into a two-dimensional image,and the feature fusion method was applied to highlight the characteristics of the γ spectrum information more.The design of the residual grouping convolution module was designed to extract the local and global features of the image through two branches,and the branch information was effectively aggregated using the residual connection.The mixed γ energy spectra of the above four radionuclides were collected using the NaI detector as a test dataset for the identification and verification.The experimental results showed that the average recognition accuracy of the model reached 99.87%,and the F1 score was 99.88%.Meanwhile,compared with other algorithms,the comparison results showed that the algorithm not only effectively improved the security of the radioactive sources and avoided the radiation threat,but also further improved the recognition accuracy while ensuring the recognition speed.关键词
核素识别/特征融合/残差分组卷积/格拉姆角场法/Swin-Tiny Transformer/ChirpletKey words
nuclide identification/feature fusion/residual grouping and convolution module/Gram's angle field method/Swin-Tiny Transformer/Chirplet分类
计算机与自动化引用本文复制引用
顾威,孟献才,洪兵..基于特征融合Swin-Tiny Transformer的γ能谱识别方法[J].哈尔滨商业大学学报（自然科学版）,2025,41(2):161-168,8.基金项目
国家自然科学基金(12105135) （12105135）
国家自然科学基金青年项目(12305200) （12305200）
合肥综合性国家科学中心能源研究院(安徽省能源实验室)项目(21KZS202、21KZS208) （安徽省能源实验室）
安徽省住房城乡建设科学技术计划项目(2023-RK043) （2023-RK043）
高校协同创新项目(GXXT-2022-003) （GXXT-2022-003）
