Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products

  • Roshani, Mohammadmehdi (Institute of Fundamental and Applied Sciences, Duy Tan University) ;
  • Phan, Giang (Institute of Fundamental and Applied Sciences, Duy Tan University) ;
  • Faraj, Rezhna Hassan (Department of Chemistry, Faculty of Science and Health, Koya University) ;
  • Phan, Nhut-Huan (Institute of Fundamental and Applied Sciences, Duy Tan University) ;
  • Roshani, Gholam Hossein (Electrical Engineering Department, Kermanshah University of Technology) ;
  • Nazemi, Behrooz (Faculty of Art and Architecture, Yazd University) ;
  • Corniani, Enrico (Division of Nuclear Physics, Advanced Institute of Materials Science, Ton Duc Thang University) ;
  • Nazemi, Ehsan (Imec-Vision Lab, Department of Physics, University of Antwerp)
  • Received : 2020.05.24
  • Accepted : 2020.09.14
  • Published : 2021.04.25
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Abstract

It is important for operators of poly-pipelines in petroleum industry to continuously monitor characteristics of transferred fluid such as its type and amount. To achieve this aim, in this study a dual energy gamma attenuation technique in combination with artificial neural network (ANN) is proposed to simultaneously determine type and amount of four different petroleum by-products. The detection system is composed of a dual energy gamma source, including americium-241 and barium-133 radioisotopes, and one 2.54 cm × 2.54 cm sodium iodide detector for recording the transmitted photons. Two signals recorded in transmission detector, namely the counts under photo peak of Americium-241 with energy of 59.5 keV and the counts under photo peak of Barium-133 with energy of 356 keV, were applied to the ANN as the two inputs and volume percentages of petroleum by-products were assigned as the outputs.

Keywords

References

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