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Title
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Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products
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Type
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JournalPaper
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Keywords
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Petroleum by-products;Artificial intelligence;Online monitoring;Dual energy; source;Poly-pipelines
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Abstract
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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.
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Researchers
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Behrooz Nazemi (Not In First Six Researchers), Gholam Hossein Roshani (Fifth Researcher), Ehsan Nazemi (Not In First Six Researchers), Enrico Corniani (Not In First Six Researchers), Nhut-Huan Phan (Fourth Researcher), rezhna hassan faraj (Third Researcher), giang phan (Second Researcher), M. M. Roshani (First Researcher)
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