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.
Authors
- Qing Guo (ORCID: https://orcid.org/0000-0003-0522-1243)
- Dan Jiang (ORCID: https://orcid.org/0000-0001-7982-7542)
- Chen Zeng
- Xin Yan (ORCID: https://orcid.org/0000-0002-0537-5288)
- Wei Chen (ORCID: https://orcid.org/0000-0002-4807-205X)
Institutions
- University of Electronic Science and Technology of China (CN)
- Nanjing University of Aeronautics and Astronautics (CN)
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
Funders
- National Natural Science Foundation of China