Classification of flow regimes using a neural network and a non-invasive ultrasonic sensor in an S-shaped pipeline-riser system

Classification of flow regimes using a neural network and a non-invasive ultrasonic sensor in an S-shaped pipeline-riser system

A method for classifying flow regimes is proposed that employs a neural network with inputs of extracted features from Doppler ultrasonic signals of flows using either the Discrete Wavelet Transform (DWT) or the Power Spectral Density (PSD). The flow regimes are classified into four types: annular,...

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Bibliographic Details
Main Authors: Somtochukwu Godfrey Nnabuife, Boyu Kuang, Zeeshan A. Rana, James Whidborne
Format: Article
Language:English
Published: Elsevier 2022-03-01
Series:Chemical Engineering Journal Advances
Subjects:
Ultrasonic sensor
Artificial Neural Network (ANN)
S-shaped riser
Discrete Wavelet Transforms (DWTs)
Power Spectral Density (PSD)
Online Access:http://www.sciencedirect.com/science/article/pii/S2666821121001307

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http://www.sciencedirect.com/science/article/pii/S2666821121001307

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