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Author Ninh, Giang Nguyen ♦ Phongphaeth, Pengvanich ♦ Nares, Chankow ♦ Hao, Quang Nguyen
Source United States Department of Energy Office of Scientific and Technical Information
Content type Text
Language English
Subject Keyword CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS ♦ ALGORITHMS ♦ AMERICIUM 241 ♦ BARIUM 133 ♦ CESIUM 137 ♦ COBALT 57 ♦ COBALT 60 ♦ CONTROL ♦ DETECTION ♦ GAMMA RADIATION ♦ GAMMA SPECTRA ♦ NATURAL URANIUM ♦ NOISE ♦ RADIATION SOURCES ♦ SECURITY ♦ SHIELDING ♦ SIGNALS
Abstract Gamma-ray signal can be used as a fingerprint for radioisotope identification. In the context of radioactive and nuclear materials security at the border control point, the detection task can present a significant challenge due to various constraints such as the limited measurement time, the shielding conditions, and the noise interference. This study proposes a novel method to identify the signal of one or several radioisotopes from a poorly resolved gamma-ray spectrum. In this method, the noise component in the raw spectrum is reduced by the wavelet decomposition approach, and the removal of the continuum background is performed using the baseline determination algorithm. Finally, the identification of radioisotope is completed using the matrix linear regression method. The proposed method has been verified by experiments using the poorly resolved gamma-ray signals from various scenarios including single source, mixing of natural uranium with five of the most common industrial radioactive sources (57Co, 60Co, 133Ba, 137Cs, and 241Am). The preliminary results show that the proposed algorithm is comparable with the commercial method.
ISSN 0094243X
Educational Use Research
Learning Resource Type Article
Publisher Date 2016-01-22
Publisher Place United States
Volume Number 1704
Issue Number 1


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