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An investigation of the digital discrimination of neutrons and γ rays with organic scintillation detectors using an artificial neural network.

Liu, G. and Aspinall, M. D. and Ma, X. and Joyce, M. J. (2009) An investigation of the digital discrimination of neutrons and γ rays with organic scintillation detectors using an artificial neural network. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 607 (3). pp. 620-628. ISSN 0168-9002

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Abstract

The discrimination of neutron and γ-ray events in an organic scintillator has been investigated by using a method based on an artificial neural network (ANN). Voltage pulses arising from an EJ-301 organic liquid scintillation detector in a mixed radiation field have been recorded with a fast digital sampling oscilloscope. Piled-up events have been disentangled using a pile-up management unit based on a fitting method. Each individual pulse has subsequently been sent to a discrimination unit which discriminates neutron and γ-ray events with a method based on an artificial neural network. This discrimination technique has been verified by the corresponding mixed-field data assessed by time of flight (TOF). It is shown that the characterization of the neutrons and photons achieved by the discrimination method based on the ANN is consistent with that afforded by TOF. This approach enables events that are often as a result of scattering or pile-up to be identified and returned to the data set and affords digital discrimination of mixed radiation fields in a broad range of environments on the basis of training obtained with a single TOF dataset

Item Type: Article
Journal or Publication Title: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Uncontrolled Keywords: Digital discrimination ; Neutron ; γ rays ; Artificial neural network ; Pile-up ; Time of flight
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments: Faculty of Science and Technology > Lancaster Environment Centre
Faculty of Science and Technology > Engineering
ID Code: 34851
Deposited By: Dr Xiandong Ma
Deposited On: 13 Dec 2010 16:26
Refereed?: Yes
Published?: Published
Last Modified: 24 Jan 2014 05:19
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/34851

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