کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8209400 | 1532088 | 2016 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Real-time radionuclide identification in γ-emitter mixtures based on spiking neural network
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
تشعشع
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Portal radiation monitors dedicated to the prevention of illegal traffic of nuclear materials at international borders need to deliver as fast as possible a radionuclide identification of a potential radiological threat. Spectrometry techniques applied to identify the radionuclides contributing to γ-emitter mixtures are usually performed using off-line spectrum analysis. As an alternative to these usual methods, a real-time processing based on an artificial neural network and Bayes' rule is proposed for fast radionuclide identification. The validation of this real-time approach was carried out using γ-emitter spectra (241Am, 133Ba, 207Bi, 60Co, 137Cs) obtained with a high-efficiency well-type NaI(Tl). The first tests showed that the proposed algorithm enables a fast identification of each γ-emitting radionuclide using the information given by the whole spectrum. Based on an iterative process, the on-line analysis only needs low-statistics spectra without energy calibration to identify the nature of a radiological threat.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Radiation and Isotopes - Volume 109, March 2016, Pages 405-409
Journal: Applied Radiation and Isotopes - Volume 109, March 2016, Pages 405-409
نویسندگان
C. Bobin, O. Bichler, V. Lourenço, C. Thiam, M. Thévenin,