August 9, 2022
Gholam Hossein Roshani

Gholam Hossein Roshani

Academic rank: Associate professor
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Education: Ph.D in Nuclear Engineering
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Faculty: Faculty of energy

Research

Title
Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter
Type Article
Keywords
GMDH model;Precision improvement;Gas volumetric percentage;Feature extraction;Oil-gas two phase flow
Researchers M. M. Roshani، mohammad amir satari، Peshawa Jammal Muhammad Ali، Gholam Hossein Roshani، Behrooz Nazemi، Enrico Corniani، Ehsan Nazemi

Abstract

Multiphase flowmeters have an important role to play in the industry and any attempts that lead to improvements in this field are of great interest. In the current study, group method of data handling (GMDH) technique was applied in order to increase measuring precision of a simple photon attenuation based two-phase flowmeter that has the ability to estimate the gas volumetric percentage in a two-phase flow without any dependency to flow regime pattern. The simple photon attenuation based system is comprised of a cobalt-60 radioisotope and only one 25.4 mm × 25.4 mm sodium iodide crystal detector. Four extracted features from recorded photon spectrum in sodium iodide crystal detector were used as the inputs of GMDH neural network. Equations related to the combination of the features and the error rate of each approximation is also reported in this paper. Applying the mentioned technique, the gas volumetric percentage in an oil-gas two phase flow was determined with the root mean square error of less than 2.71 without any dependency to the flow pattern. The obtained measuring precision in this study is at least 2.1 times better than reported in previous studies.