publication . Article . 2016

Non-invasive classification of gas–liquid two-phase horizontal flow regimes using an ultrasonic Doppler sensor and a neural network

Abbagoni, Baba Musa; Yeung, Hoi;
Open Access
  • Published: 23 Jun 2016 Journal: Measurement Science and Technology, volume 27, page 84,002 (issn: 0957-0233, eissn: 1361-6501, Copyright policy)
  • Publisher: IOP Publishing
  • Country: United Kingdom
Abstract
The identification of flow pattern is a key issue in multiphase flow which is encountered in the petrochemical industry. It is difficult to identify the gas–liquid flow regimes objectively with the gas–liquid two-phase flow. This paper presents the feasibility of a clamp-on instrument for an objective flow regime classification of two-phase flow using an ultrasonic Doppler sensor and an artificial neural network, which records and processes the ultrasonic signals reflected from the two-phase flow. Experimental data is obtained on a horizontal test rig with a total pipe length of 21 m and 5.08 cm internal diameter carrying air-water two-phase flow under slug, elo...
Subjects
free text keywords: Instrumentation, Applied Mathematics
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