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Gas–liquid two-phase flow pattern analysis based on multiscale symbolic transfer entropy

  • Chunling Fan EMAIL logo , Jiangfan Qin , Qihua Fan and Chuntang Zhang
Published/Copyright: August 23, 2021

Abstract

This paper presents a multiscale symbolic transfer entropy (MSTE) to extract the features of gas–liquid two-phase flow and distinguish flow patterns effectively. The role of the MSTE in typical chaotic time series is investigated. Then the characteristics of the flow patterns about three gas–liquid two-phase flows are analyzed from the perspective of causal analysis. The results show that the MSTE can identify different flow patterns and characterize the dynamic characteristics of flow patterns, providing a new method for identifying two-phase flow accurately. In addition, the MSTE reduces the influence of noise to a certain extent and preserves the dynamic characteristics based on simplifying the original sequence. Compared with traditional algorithm, the MSTE has fast calculation speed and anti-interference characteristics and can express the essential features well.


Corresponding author: Chunling Fan, College of Automation and Electronic Engineering, Qingdao University of Science & Technology, Qingdao 266061, China, E-mail:

Funding source: Natural Science Foundation of Shandong Province doi.org/10.13039/501100007129

Award Identifier / Grant number: ZR2019MEE071

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This project is supported by the Natural Science Foundation of Shandong (ZR2019MEE071) and the Taishan Scholar Project Fund of Shandong Province.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Received: 2021-04-23
Accepted: 2021-07-28
Published Online: 2021-08-23
Published in Print: 2021-10-26

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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