Gas–Liquid Two-Phase Flow Measurement Based on Optical Flow Method with Machine Learning Optimization Model

Gas–Liquid two-phase flows are a common flow in industrial production processes. Since these flows inherently consist of discrete phases, it is challenging to accurately measure the flow parameters. In this context, a novel approach is proposed that combines the pyramidal Lucas-Kanade (L–K) optical...

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Bibliographic Details
Published in:	Applied sciences Vol. 14; no. 9; p. 3717
Main Authors:	Wang, Junxian, Huang, Zhenwei, Xu, Ya, Xie, Dailiang
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.05.2024
Subjects:	Accuracy Algorithms Classification Deep learning Fourier transforms Gases gas–liquid two-phase flow Lucas–Kanade optical flow detection Machine learning Measurement Methods Natural gas Neural networks Nuclear energy Pattern recognition Sensors Ultrasonic imaging
ISSN:	2076-3417, 2076-3417
Online Access:	Get full text
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