Computer methods of recognition and analysis of X-ray and gamma radiation parameters
Abstract
The rapid development of computer technologies makes it possible to use computer methods for spectral analysis of X-ray and gamma radiation, where analog electronics have been traditionally used. One of the difficulties in obtaining data from radiation detectors is the very high frequency of signal registration. However, the use of special devices called digitizers allows us to acquire, digitize and send data to a computer system at a sufficient speed. Large data arrays obtained during experiments reflect the characteristics of spectrometric signals. It is possible to recognize the registration of radiation quanta in the detector, as well as to draw conclusions about the quantitative characteristics of radiation with the help of computer methods, mathematical calculations and special algorithms.
The overview of the main methods of obtaining data in digital form for further computer analysis, namely by conducting real experiments on special equipment and by means of computer modeling (simulation) is presented in the article. Several existing methods for recognition and analysis of individual radiation particles based on the shape of the signal are described, also the methods and the software algorithms for analyzing the parameters of X-ray and gamma radiation are implemented. The computer program, that is capable of simulating data with given characteristics and can perform recognition and analysis of gamma quanta based on the loaded data, has been developed as a part of the research. The program also allows visualizing the results and checking the efficiency of the methods. The conclusions about potential directions for further research have been made.
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W. Wolszczak, P. Dorenbos. Time-resolved gamma spectroscopy of single events. Nuclear Instruments and Methods in Physics Research. Section A: Accelerators Spectrometers Detectors and Associated Equipment. Volume 886. P. 30–55. 2018. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900217315036 (Last accessed: 25.12.2022)
G. T. Wright. Scintillation decay times of organic crystals. Proceedings of the Physical Society. Section B, Volume 69, Number 3. P. 358-372. 1956. URL: https://iopscience.iop.org/article/10.1088/0370-1301/69/3/311 (Last accessed: 25.12.2022)
L. Dinca, P. Dorenbos, J. de Haas, V. Bom, and C. V. Eijk. Alphagamma pulse shape discrimination in CsI:Tl, CsI:Na and BaF2 scintillators. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. Volume 486. P. 141-145. 2002. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900202006915 (Last accessed: 25.12.2022)
M. Kobayashi, Y. Tamagawa, S. Tomita, A. Yamamoto, I. Ogawa, Y. Usuki. Significantly different pulse shapes for γ- and α-rays in Gd3Al2Ga3O12:Ce3+ scintillating crystals. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. Volume 694. P. 91–94. 2012. URL: https://www.researchgate.net/publication/257024093_Significantly_different_pulse_shapes_for_g-_and_a-rays_in_Gd3Al2Ga3O12Ce3_scintillating_crystals (Last accessed: 26.12.2022)
Spectrum Instrumentation Official Website. URL: https://spectrum-instrumentation.com/products/digitizer/index.php (Last accessed: 26.12.2022)
E.M. Khilkevitch, A.E. Shevelev, I.N. Chugunov, M.V. Iliasova, D.N. Doinikov, D.B. Gin, V.O. Naidenov, I.A. Polunovsky, Advanced algorithms for signal processing scintillation gamma ray detectors at high counting rates. Nuclear Instruments and Methods in Physics Research. Section A: Accelerators Spectrometers Detectors and Associated Equipment. Volume 997. 2020. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900220307051 (Last accessed: 26.12.2022)
A.E. Shevelev, et al., High performance gamma-ray spectrometer for runaway electron studies on the FT-2 tokamak, Nuclear Instruments and Methods in Physics Research. Section A: Accelerators Spectrometers Detectors and Associated Equipment. Volume 830. P. 102–108. 2016. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900216304685 (Last accessed: 25.12.2022)
D.B. Gin, I.N. Chugunov, A.E. Shevelev, Development of a technique for high-speed gamma-ray spectrometry. Instruments and Experimental Techniques. Volume 51. P. 240–245. 2008. URL: https://link.springer.com/article/10.1134/S0020441208020152 (Last accessed: 27.12.2022)
M. Lopatin, N. Moskovitch, Tom Trigano, Yann Sepulcre. Pileup attenuation for spectroscopic signals using a sparse reconstruction. Conference: Electrical & Electronics Engineers in Israel (IEEEI). 2012. URL: https://www.researchgate.net/publication/261199932_Pileup_attenuation_for_spectroscopic_signals_using_a_sparse_reconstruction (Last accessed: 27.12.2022)
Averill M. Law, W. David Kelton. Simulation Modeling and Analysis. Third edition. McGraw-Hill. 760 pages. 2000.
QT Framework Official Website. URL: https://www.qt.io/product/framework (Last accessed: 27.12.2022)
Ronald Wurtz. Consistent principles for particle identification by pulse shape discriminating systems. SPIE Proceedings, Hard X-Ray, Gamma-Ray, and Neutron Detector Physics XXI. Volume 11114. P. 1–14. 2019. URL: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11114/111140X/Consistent-principles-for-particle-identification-by-pulse-shape-discriminating-systems/10.1117/12.2528898.full?SSO=1 (Last accessed: 27.12.2022)
C. Fu, A. Di Fulvio, S.D. Clarke, D. Wentzloff, S.A. Pozzi, H.S. Kim, Artificial neural network algorithms for pulse shape discrimination and recovery of piled-up pulses in organic scintillators. Annals of Nuclear Energy. Volume 120. P. 410-421. 2018. URL: https://doi.org/10.1016/j.anucene.2018.05.054 (Last accessed: 27.12.2022)
Fabio Pollastrone, Marco Riva, Daniele Marocco, Francesco Belli, Cristina Centioli. Automatic pattern recognition on electrical signals applied to neutron gamma discrimination. Fusion Engineering and Design. Volume 123. Pages 969-974. 2017. URL: https://doi.org/10.1016/j.fusengdes.2017.03.009 (Last accessed: 27.12.2022)
W. Wolszczak, P. Dorenbos. Time-resolved gamma spectroscopy of single events. Nuclear Instruments and Methods in Physics Research. Section A: Accelerators Spectrometers Detectors and Associated Equipment. 2018. Volume 886. P. 30–55. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900217315036 (дата звернення: 25.12.2022)
G. T. Wright. Scintillation decay times of organic crystals. Proceedings of the Physical Society. Section B. 1956. Volume 69, Number 3. P. 358-372. URL: https://iopscience.iop.org/article/10.1088/0370-1301/69/3/311 (дата звернення: 25.12.2022)
L. Dinca, P. Dorenbos, J. de Haas, V. Bom, and C. V. Eijk. Alphagamma pulse shape discrimination in CsI:Tl, CsI:Na and BaF2 scintillators. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment/ 2002. Volume 486. P. 141-145. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900202006915 (дата звернення: 25.12.2022)
M. Kobayashi, Y. Tamagawa, S. Tomita, A. Yamamoto, I. Ogawa, Y. Usuki. Significantly different pulse shapes for γ- and α-rays in Gd3Al2Ga3O12:Ce3+ scintillating crystals. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2012. Volume 694. P. 91–94. URL: https://www.researchgate.net/publication/257024093_Significantly_different_pulse_shapes_for_g-_and_a-rays_in_Gd3Al2Ga3O12Ce3_scintillating_crystals (дата звернення: 26.12.2022)
Spectrum Instrumentation Official Website. URL: https://spectrum-instrumentation.com/products/digitizer/index.php (дата звернення: 26.12.2022)
E.M. Khilkevitch, A.E. Shevelev, I.N. Chugunov, M.V. Iliasova, D.N. Doinikov, D.B. Gin, V.O. Naidenov, I.A. Polunovsky, Advanced algorithms for signal processing scintillation gamma ray detectors at high counting rates. Nuclear Instruments and Methods in Physics Research. Section A: Accelerators Spectrometers Detectors and Associated Equipment. 2020. Volume 997. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900220307051 (дата звернення: 26.12.2022)
A.E. Shevelev, et al., High performance gamma-ray spectrometer for runaway electron studies on the FT-2 tokamak, Nuclear Instruments and Methods in Physics Research. Section A: Accelerators Spectrometers Detectors and Associated Equipment. 2016. Volume 830. P. 102–108. URL: https://www.sciencedirect.com/science/article/abs/pii/S0168900216304685 (дата звернення: 25.12.2022)
D.B. Gin, I.N. Chugunov, A.E. Shevelev, Development of a technique for high-speed gamma-ray spectrometry. Instruments and Experimental Techniques. 2008. Volume 51. P. 240–245. URL: https://link.springer.com/article/10.1134/S0020441208020152 (дата звернення: 27.12.2022)
M. Lopatin, N. Moskovitch, Tom Trigano, Yann Sepulcre. Pileup attenuation for spectroscopic signals using a sparse reconstruction. Conference: Electrical & Electronics Engineers in Israel (IEEEI), 2012. URL: https://www.researchgate.net/publication/261199932_Pileup_attenuation_for_spectroscopic_signals_using_a_sparse_reconstruction (дата звернення: 27.12.2022)
Averill M. Law, W. David Kelton. Simulation Modeling and Analysis. Third edition. McGraw-Hill. 2000. 760 pages.
QT Framework Official Website. URL: https://www.qt.io/product/framework (дата звернення: 27.12.2022)
Ronald Wurtz. Consistent principles for particle identification by pulse shape discriminating systems. SPIE Proceedings, Hard X-Ray, Gamma-Ray, and Neutron Detector Physics XXI. 2019. Volume 11114. P. 1–14. URL: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11114/111140X/Consistent-principles-for-particle-identification-by-pulse-shape-discriminating-systems/10.1117/12.2528898.full?SSO=1 (дата звернення: 27.12.2022)
C. Fu, A. Di Fulvio, S.D. Clarke, D. Wentzloff, S.A. Pozzi, H.S. Kim, Artificial neural network algorithms for pulse shape discrimination and recovery of piled-up pulses in organic scintillators. Annals of Nuclear Energy. 2018. Volume 120. P. 410-421. URL: https://doi.org/10.1016/j.anucene.2018.05.054 (дата звернення: 27.12.2022)
Fabio Pollastrone, Marco Riva, Daniele Marocco, Francesco Belli, Cristina Centioli. Automatic pattern recognition on electrical signals applied to neutron gamma discrimination. Fusion Engineering and Design. 2017. Volume 123. Pages 969-974. URL: https://doi.org/10.1016/j.fusengdes.2017.03.009 (дата звернення: 27.12.2022)