Application of Multivariate Data Analysis Techniques for the Portable Isotopic Neutron Spectroscopy System
| Autor: | Brian Bucher, Edward H. Seabury, C. J. Wharton, Dongwon Lee, Kenneth M Krebs, A. J. Caffrey |
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| Rok vydání: | 2017 |
| Předmět: |
Idaho National Laboratory
Computer science Astrophysics::High Energy Astrophysical Phenomena Nuclear engineering Probabilistic logic Decision tree Prompt gamma neutron activation analysis 010403 inorganic & nuclear chemistry 01 natural sciences 030218 nuclear medicine & medical imaging 0104 chemical sciences Semiconductor detector Neutron spectroscopy 03 medical and health sciences 0302 clinical medicine Principal component analysis Neutron |
| Zdroj: | 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). |
| DOI: | 10.1109/nssmic.2017.8533106 |
| Popis: | The Portable Isotopic Neutron Spectroscopy (PINS) is a commercialized system developed by Idaho National Laboratory to examine chemical compounds in munitions and containers non-destructively, utilizing the Prompt Gamma Neutron Activation Analysis (PGNAA) technique. The PINS system takes advantage of a germanium detector’s high energy resolution, and gamma-ray peak analysis provides input to its chemical identification logic using a probabilistic decision tree. Multivariate analysis (MVA) techniques were contemplated with the expectation that they could supplement the current PINS algorithm. Principal Component Analysis (PCA) was selected to project gamma-ray spectra into the principal component domain. A PCA-based chemical identification algorithm was tested, and the results are presented in this study. |
| Databáze: | OpenAIRE |
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