DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Cho, Gyuseong | - |
dc.contributor.advisor | 조규성 | - |
dc.contributor.author | Song, Gyohyeok | - |
dc.date.accessioned | 2023-06-26T19:33:25Z | - |
dc.date.available | 2023-06-26T19:33:25Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1032832&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/309794 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 원자력및양자공학과, 2023.2,[v, 54 p. :] | - |
dc.description.abstract | The fast neutron radiography system is a type of non-destructive testing used in various fields such as homeland security, material classification, and neutron source location detection. There are two methods for measuring fast neutrons: a thermal neutron capture detection system and a recoil proton-based neutron scattering detection system. In particular, the recoil proton-based neutron detection system can be utilized as a fast neutron radiography system. In this thesis, we proposed a machine learning-based algorithm. The proposed algorithm automatically classifies neutron signals in the entire energy range from pulse shape discrimination results consisting of the multi-channel organic plastic scintillators and silicon photomultiplier (SiPM) for fast neutron radiography acquisition. Through the characteristics of the data distribution in the high-energy region, the PSD results in the low-energy region were effectively classified. As a result of applying the algorithm to the neutron and gamma-ray signals obtained by the time of flight measurement, the AUC of the ROC curve was 0.9987, which showed excellent classification performance. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Fast neutron measurement▼aOrganic scintillator▼aSilicon photomultiplier (SiPM)▼aPulse shape discrimination (PSD)▼aMachine learning▼aAutomatic classification▼aRadiography system | - |
dc.subject | 고속 중성자 측정▼a유기섬광체▼a실리콘광증배소자▼a파형 분별▼a기계 학습▼a자동 분류▼a영상 시스템 | - |
dc.title | Automatic classification of multi-channel pulse shape discrimination for fast neutron radiography acquisition | - |
dc.title.alternative | 고속 중성자 영상 획득을 위한 다채널 PSD 중성자 신호 자동 분류 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :원자력및양자공학과, | - |
dc.contributor.alternativeauthor | 송교혁 | - |
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