Increasing the Efficiency of a Control System for Detecting the Type and Amount of Oil Product Passing through Pipelines Based on Gamma-Ray Attenuation, Time Domain Feature Extraction, and Artificial Neural Networks

Increasing the Efficiency of a Control System for Detecting the Type and Amount of Oil Product Passing through Pipelines Based on Gamma-Ray Attenuation, Time Domain Feature Extraction, and Artificial Neural Networks

Instantaneously determining the type and amount of oil product passing through pipelines is one of the most critical operations in the oil, polymer and petrochemical industries. In this research, a detection system is proposed in order to monitor oil pipelines. The system uses a dual-energy gamma so...

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Bibliographic Details
Main Authors: Abdulilah Mohammad Mayet, Seyed Mehdi Alizadeh, Zana Azeez Kakarash, Ali Awadh Al-Qahtani, Abdullah K. Alanazi, John William Grimaldo Guerrero, Hala H. Alhashimi, Ehsan Eftekhari-Zadeh
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Polymers
Subjects:
detection system
feature extraction
RBF neural network
oil and polymeric fluids
dual-energy gamma source
Online Access:https://www.mdpi.com/2073-4360/14/14/2852

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