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

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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.; Aspinall, Michael; Ma, X. et al.
In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 607, No. 3, 21.08.2009, p. 620-628.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Liu, G, Aspinall, M, Ma, X & Joyce, MJ 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, vol. 607, no. 3, pp. 620-628. https://doi.org/10.1016/j.nima.2009.06.027

APA

Liu, G., Aspinall, M., Ma, X., & 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), 620-628. https://doi.org/10.1016/j.nima.2009.06.027

Vancouver

Liu G, Aspinall M, Ma X, Joyce MJ. 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. 2009 Aug 21;607(3):620-628. doi: 10.1016/j.nima.2009.06.027

Author

Liu, G. ; Aspinall, Michael ; Ma, X. et al. / An investigation of the digital discrimination of neutrons and γ rays with organic scintillation detectors using an artificial neural network. In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2009 ; Vol. 607, No. 3. pp. 620-628.

Bibtex

@article{9d3b6870c21e453f80aa09e0e45def1c,
title = "An investigation of the digital discrimination of neutrons and γ rays with organic scintillation detectors using an artificial neural network.",
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",
keywords = "Digital discrimination, Neutron, γ rays, Artificial neural network, Pile-up, Time of flight",
author = "G. Liu and Michael Aspinall and X. Ma and Joyce, {M. J.}",
year = "2009",
month = aug,
day = "21",
doi = "10.1016/j.nima.2009.06.027",
language = "English",
volume = "607",
pages = "620--628",
journal = "Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment",
issn = "0168-9002",
publisher = "ELSEVIER SCIENCE BV",
number = "3",

}

RIS

TY - JOUR

T1 - An investigation of the digital discrimination of neutrons and γ rays with organic scintillation detectors using an artificial neural network.

AU - Liu, G.

AU - Aspinall, Michael

AU - Ma, X.

AU - Joyce, M. J.

PY - 2009/8/21

Y1 - 2009/8/21

N2 - 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

AB - 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

KW - Digital discrimination

KW - Neutron

KW - γ rays

KW - Artificial neural network

KW - Pile-up

KW - Time of flight

U2 - 10.1016/j.nima.2009.06.027

DO - 10.1016/j.nima.2009.06.027

M3 - Journal article

VL - 607

SP - 620

EP - 628

JO - Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

JF - Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

SN - 0168-9002

IS - 3

ER -