Comparative analysis of the possibilities of X-ray, neutron and muon tomography of goods and vehicles for the purposes of customs control

  • В. В. Пантелеева St. Petersburg Branch of the Russian Customs Academy
  • Д. Н. Афонин St. Petersburg Branch of the Russian Customs Academy https://orcid.org/0000-0002-1390-838X
Keywords: X-ray tomography, neutron tomography, muon tomography, non-intrusive inspection, customs control

Abstract

This article discusses the possibilities of applying X-ray, neutron and muon tomography for customs control purposes, as well as the achievements of recent research in this area.

References

Andreeva N.S., Budnik S.V., Bryazgin A. A. and others. Radiation technologies: view from Russia // Radiation technologies, RVC, Moscow, 2015. pp. 26-27.

Min H. Challenges and opportunities for implementing X-ray scanning technology at the Korean hub ports // Int. J. Logistics Systems and Management. 2016. Vol. 25, № 4. pp. 513-531.

Jaccarda N., Rogersa T.W., Morton E.J. Tackling the X-ray cargo inspection challenge using machine learning // Anomaly Detection and Imaging with X-Rays (ADIX). 2016. Vol. 9847, № 98470. pp. 1-13.

Yifan Z. Research on material discrimination method by cosmic ray muon tomography // Master thesis, dual diploma program advanced level, School of Science Tsinghua University, Stockholm – Beijing. 2018. pp. 25.

Приказ Федеральной таможенной службы России от 09.12.2010 № 2354 (ред. от 05.09.2014) «Об утверждении Инструкции о действиях должностных лиц таможенных органов при таможенном контроле товаров и транспортных средств с использованием инспекционно-досмотровых комплексов» // СПС «Консультант Плюс».

Guidelines for the procurement and deployment of scanning/NII equipment // World customs organization.

Eberhardt J., Liu Y. Fast Neutron and Gamma-Ray Interrogation of Air Cargo Containers // Proceeding or science. 2006. pp. 1-11.

Hartmann J., Yazdanpanah A., Barzilov A. and others. 3D imaging using combined neutron-photon fan-beam tomography: A Monte Carlo study // Applied Radiation and Isotopes, Elsevier, ScienceDirect. 2016. pp. 110-116.

Yang G., Ireland D., Kaiser R. and others. Machine Learning for Muon Imaging // Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences. 2018. № 377. pp. 808-817.

Morishima K., Nishio A., Kuno M. and others. Discovery of a big void in Khufu’s Pyramid by observation of cosmic-ray muons // Nature. 2017. № 552. pp. 386-390.

Афонин Д.Н. Перспективы применения мюонной томографии при таможенном контроле // Бюллетень инновационных технологий. 2018. Т. 2, № 2(6). С. 18-20.

Borozdin K., Asaki T., Chartrand R. and others. Cosmic-ray muon tomography and its application to the detection of high-z materials // Los Alamos National Laboratory, University of South Carolina. 2014. pp. 1-8.

Bendahan J. Vehicle and Cargo Scanning for Contraband // Physics Procedia 2017. № 90. pp. 242-255.

Сравнительный анализ возможностей рентгеновской, нейтронной и мюонной томографии товаров и транспортных средств для целей таможенного контроля
Published
2019-02-12
How to Cite
Пантелеева, В. and Афонин, Д. (2019) “Comparative analysis of the possibilities of X-ray, neutron and muon tomography of goods and vehicles for the purposes of customs control”, Bulletin of innovative technologies, 3(1(9), pp. 42-44. Available at: https://www.bitjournal.ru/index.php/BIT/article/view/92 (Accessed: 21June2026).
Section
Economics science