A real-time neutron-gamma discriminator based on the support vector machine method for the time-of-flight neutron spectrometer  

作　　者：张伟 吴彤宇 郑博文 李世平 张轶泼 阴泽杰 

机构地区：[1]State Key Laboratory of Particle Detection and Electronics, University of Science and Technology ofChina, Hefei 230026, People's Republic of China [2]Department of Modem Physics, University of Science and Technology of China, Hefei 230026, People'sRepublic of China [3]Southwestern Institute of Physics, Chengdu 610041, People's Republic of China

出　　处：《Plasma Science and Technology》2018年第4期170-175,共6页等离子体科学和技术（英文版）

基　　金：partially supported by the National Science and Technology Major Project of Ministry of Science and Technology of China (Grant Nos. 2014GB109003 and 2015GB111002);National Natural Science Foundation of China (Grant Nos. 11375195, 11575184, 11375004 and 11775068)

摘　　要：A new neutron-gamma discriminator based on the support vector machine(SVM) method is proposed to improve the performance of the time-of-flight neutron spectrometer. The neutron detector is an EJ-299-33 plastic scintillator with pulse-shape discrimination(PSD) property. The SVM algorithm is implemented in field programmable gate array(FPGA) to carry out the real-time sifting of neutrons in neutron-gamma mixed radiation fields. This study compares the ability of the pulse gradient analysis method and the SVM method. The results show that this SVM discriminator can provide a better discrimination accuracy of 99.1%. The accuracy and performance of the SVM discriminator based on FPGA have been evaluated in the experiments. It can get a figure of merit of 1.30.A new neutron-gamma discriminator based on the support vector machine(SVM) method is proposed to improve the performance of the time-of-flight neutron spectrometer. The neutron detector is an EJ-299-33 plastic scintillator with pulse-shape discrimination(PSD) property. The SVM algorithm is implemented in field programmable gate array(FPGA) to carry out the real-time sifting of neutrons in neutron-gamma mixed radiation fields. This study compares the ability of the pulse gradient analysis method and the SVM method. The results show that this SVM discriminator can provide a better discrimination accuracy of 99.1%. The accuracy and performance of the SVM discriminator based on FPGA have been evaluated in the experiments. It can get a figure of merit of 1.30.

关 键 词：plasma diagnosis support vector machine pulse-shape discrimination TOF spectrometer 

分 类 号：O536[理学—等离子体物理]