Gas–Liquid Two-Phase Flow Pattern Identification of a Centrifugal Pump Based on SMOTE and Artificial Neural Network

The accurate identification of the gas–liquid two-phase flow pattern within the impeller of a centrifugal pump is critical to develop a reliable model for predicting the gas–liquid two-phase performance of the centrifugal pump. The influences of the inlet gas volume fraction, the liquid phase flow r...

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Vydané v:	Micromachines (Basel) Ročník 13; číslo 1; s. 2
Hlavní autori:	He, Denghui, Li, Ruilin, Zhang, Zhenduo, Sun, Shuaihui, Guo, Pengcheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 21.12.2021 MDPI
Predmet:	Algorithms Artificial neural networks Cameras centrifugal pump Centrifugal pumps Efficiency Experiments Flow characteristics Flow control Flow distribution Flow mapping flow pattern identification Flow velocity Fluid flow gas–liquid flow Identification Impellers Liquid phases Machine learning neural network Neural networks Oversampling Pattern recognition Polymethyl methacrylate Signal processing SMOTE algorithm Two phase flow SMOTE algorithm centrifugal pump flow pattern identification neural network gas–liquid flow
ISSN:	2072-666X, 2072-666X
On-line prístup:	Získať plný text
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