Bubble image segmentation and dynamic feature extraction in gas–liquid two-phase transient flow

Understanding the dynamics of bubble growth and collapse during gas–liquid two-phase transient flow is crucial for minimizing pipeline wear and maintaining the normal operation of the pipeline system. This paper focuses on obtaining the bubble trajectory, movement velocity, and volume change of gas bubbles. The bubble images during the transient flow are first denoised and enhanced, then the moving target detection algorithm and watershed segmentation algorithm are used to segment the bubbles, and the contour reconstruction of the bubbles is performed using fitting to extract the relevant parameters. The movement trajectories of the bubbles are then traced by analyzing the trajectories and velocities of growth and collapse of the first bubbles during the transient flow, specifically when the flow rate of the hydraulic pipeline is 0.75 m/s. Finally, the changes in gas content during the transient flow in the pipeline under different initial flow rates are compared between the algorithm proposed here and the simulation results.

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Publication Details

Journal
AIP Advances
Published
2024-08-01
DOI
https://doi.org/10.1063/5.0222299
Primary Topic
Fluid Dynamics and Mixing
Type
article
Field-Weighted Citation Impact
0.00

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article

Bubble image segmentation and dynamic feature extraction in gas–liquid two-phase transient flow

Qing Guo, Dan Jiang, Chen Zeng, Xin Yan et al.
AIP Advances
Fluid Dynamics and Mixing
article

Bubble image segmentation and dynamic feature extraction in gas–liquid two-phase transient flow

Qing Guo, Dan Jiang, Chen Zeng, Xin Yan, Wei Chen
article en

Abstract

Understanding the dynamics of bubble growth and collapse during gas–liquid two-phase transient flow is crucial for minimizing pipeline wear and maintaining the normal operation of the pipeline system. This paper focuses on obtaining the bubble trajectory, movement velocity, and volume change of gas bubbles. The bubble images during the transient flow are first denoised and enhanced, then the moving target detection algorithm and watershed segmentation algorithm are used to segment the bubbles, and the contour reconstruction of the bubbles is performed using fitting to extract the relevant parameters. The movement trajectories of the bubbles are then traced by analyzing the trajectories and velocities of growth and collapse of the first bubbles during the transient flow, specifically when the flow rate of the hydraulic pipeline is 0.75 m/s. Finally, the changes in gas content during the transient flow in the pipeline under different initial flow rates are compared between the algorithm proposed here and the simulation results.

AIP AdvancesVol. 14(8)
University of Electronic Science and Technology of China (CN), Nanjing University of Aeronautics and Astronautics (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
Fluid Dynamics and Mixing
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