A Flowrate Estimation Method for Gas–Water Two-Phase Flow Based on Multimodal Sensors and Hybrid LSTM-CNN Model-Reference-Cited by-同舟云学术

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A Flowrate Estimation Method for Gas–Water Two-Phase Flow Based on Multimodal Sensors and Hybrid LSTM-CNN Model

Published:2024 Issue: Volume:73 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Jiang Yuxiao¹^ORCID,Liu Yinyan²^ORCID,Mao Baijin¹^ORCID,Lu Xing³^ORCID,Li Yi¹^ORCID,Peng Lihui⁴^ORCID

Affiliation:

1. Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

2. School of Photovoltaic and Renewable Energy Engineering, University of New South Wales, Sydney, NSW, Australia

3. Xinjiang Oilfield Company of PetroChina, Karamay, China

4. Department of Automation, Tsinghua University, Beijing, China

Funder

Shenzhen Science and Technology Innovation Committee

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10367905/10599331.pdf?arnumber=10599331

Reference40 articles.

1. Developments of leak detection, diagnostics, and prediction algorithms in multiphase flows

2. Effects of flow patterns and salinity on water holdup measurement of oil-water two-phase flow using a conductance method

3. Sparse Local Fisher Discriminant Analysis for Gas-Water Two-Phase Flow Status Monitoring With Multisensor Signals

4. Shale gas: Will it become a new type of clean energy in China? — A perspective of development potential

5. Actively Exploring Informative Data for Smart Modeling of Industrial Multiphase Flow Processes

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