Open AccessMultibubbles Segmentation and Characteristic Measurement in Gas-Liquid Two-Phase Flow
Author(s) -
Tao Xue,
Yanlong Chen,
Penghui Ge
Publication year - 2013
Publication title -
advances in mechanical engineering/advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1155/2013/143939
Subject(s) - artificial intelligence , computer vision , segmentation , computer science , bubble , flow (mathematics) , optical flow , feature (linguistics) , vector field , optics , acoustics , mathematics , physics , image (mathematics) , geometry , philosophy , parallel computing , linguistics
Gas-liquid two-phase flow is a typical flow, and bubble characteristic measurement is of great importance to discover flow mechanism and guide the practical fluid mechanical engineering. In this paper, a virtual stereo vision measurement system mainly consists of a high-speed camera, and two optical reflector sets was established, and bubble images in gas-liquid two-phase flow were captured by the optimized virtual stereo vision sensor. Overlapping bubbles segmentation is indispensable for the images, and an effective multibubbles segmentation method was proposed. Firstly the convexities of the overlapped area were identified based on the chain code difference, and the pseudoconcave points were removed based on the concave length constraint. According to the matching principle of concave points, the segmentation area was clarified, and the overlapping bubbles were segmented effectively. Therefore, the modality and motion feature parameters of bubbles were estimated, and three-dimensional bubble trajectories and velocity vector field were reconstructed according to the measurement model of virtual stereo vision. The experimental results show that the segmentation and characteristic measurement method of multibubbles is valid and with high precision