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Application of Soft Computing Techniques to Multiphase Flow Measurement: A Review

Yan, Yong, Wang, Lijuan, Wang, Tao, Wang, Xue, Hu, Yonghui, Duan, Quansheng (2018) Application of Soft Computing Techniques to Multiphase Flow Measurement: A Review. Flow Measurement and Instrumentation, 60 . pp. 30-43. ISSN 0955-5986. (doi:10.1016/j.flowmeasinst.2018.02.017) (KAR id:66012)

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After extensive research and development over the past three decades, a range of techniques have been proposed and developed for online continuous measurement of multiphase flow. In recent years, with the rapid development of computer hardware and machine learning, soft computing techniques have been applied in many engineering disciplines, including indirect measurement of multiphase flow. This paper presents a comprehensive review of the soft computing techniques for multiphase flow metering with a particular focus on the measurement of individual phase flowrates and phase fractions. The paper describes the sensors used and the working principle, modelling and example applications of various soft computing techniques in addition to their merits and limitations. Trends and future developments of soft computing techniques in the field of multiphase flow measurement are also discussed.

Item Type: Article
DOI/Identification number: 10.1016/j.flowmeasinst.2018.02.017
Uncontrolled keywords: Multiphase flow measurement; Soft computing; Machine learning; Computational intelligence; Sensor fusion; Data-driven model
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Yong Yan
Date Deposited: 13 Feb 2018 12:11 UTC
Last Modified: 06 Feb 2020 04:17 UTC
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