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.

中文翻译：

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提出一种基于伽马辐射的智能系统，用于同时分析和检测石油副产品的类型和数量

摘要 对于石油工业多管道的运营商来说，持续监测输送流体的类型和数量等特性非常重要。为了实现这一目标，在本研究中，提出了一种结合人工神经网络 (ANN) 的双能量伽马衰减技术，以同时确定四种不同石油副产品的类型和数量。检测系统由双能伽马源（包括镅241 和钡133 放射性同位素）和一个用于记录透射光子的2.54 cm × 2.54 cm 碘化钠探测器组成。透射检测器中记录的两个信号，即能量为 59.5 keV 的 Americium-241 的光峰下计数和能量为 356 keV 的 Barium-133 的光峰下计数，