Optimization of x-ray tube voltage to improve the precision of two phase flow meters used in petroleum industry

To the best knowledge of the authors, in all the former studies, a fixed value of X-ray tube voltage has been used for investigating gas–liquid two-phase flow characteristics, while the energy of emitted X-ray radiations that depends on the tube voltage can significantly affect the measurement precision of the system. The purpose of present study is to find the optimum tube voltage to increase the accuracy and efficiency of an intelligent X-ray radiation-based two-phase flow meter. The detection system consists of an industrial X-ray tube and one detector located on either side of a steel pipe. Tube voltages in the range of 125–300 kV with a step of 25 kV were investigated. For each tube voltage, different gas volume percentages (GVPs) in the range of 10–90% with a step of 5% were modeled. A feature extraction method was performed on the output signals of the detector in every case, and the obtained matrixes were applied to the designed radial basis function neural networks (RBFNNs). The desired output of the networks was GVP. The precision of the networks in every voltage and every number of neurons in the hidden layer were obtained. The results showed that 225 kV tube voltage is the optimum voltage for this purpose. The obtained mean absolute error (MAE) for this case is less than 0.05, which demonstrates the very high precision of the metering system with an optimum X-ray tube voltage. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Авторы
Alanazi A.K.1 , Alizadeh S.M.2 , Nurgalieva K.S.3 , Guerrero J.W.G.4 , Abo-Dief H.M.1 , Eftekhari-Zadeh E.5 , Nazemi E.6 , Narozhnyy I.M. 7
Издательство
MDPI AG
Номер выпуска
24
Язык
Английский
Статус
Опубликовано
Номер
13622
Том
13
Год
2021
Организации
  • 1 Department of Chemistry, Faculty of Science, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia
  • 2 Petroleum Engineering Department, Australian College of Kuwait, West Mishref, 13015, Kuwait
  • 3 Department of Development and Operation of Oil and Gas Fields, Saint-Petersburg Mining University, Saint-Petersburg, 199106, Russian Federation
  • 4 Department of Energy, Universidad de la Costa, Barranquilla, 080001, Colombia
  • 5 Institute of Optics and Quantum Electronics, Friedrich-Schiller-University Jena, Max-Wien-Platz 1, Jena, 07743, Germany
  • 6 Imec-Vision Laboratory, Department of Physics, University of Antwerp, Antwerp, 2610, Belgium
  • 7 Department of Commercialization of Intellectual Activity Resultse Center for Technology Transfer, Mining Oil and Gas Department, RUDN University, Moscow, 117198, Russian Federation
Ключевые слова
Artificial intelligence; GVP; Sustainable technology; Tube voltage optimization; Two-phase flow; X-ray
Дата создания
06.07.2022
Дата изменения
06.07.2022
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/84496/
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