Abstract
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.
Highlights
Gas-liquid two-phase flow is a typical flow, and bubble characteristic measurement is of great importance to discover the flow mechanism and guide the practical fluid mechanical engineering [1]
It consists of three main steps, identification of candidate concave points referring to chain code difference, removal of the pseudoconcave points based on the concave length, and matching real concave points according to axial constraint
The experimental results show that the segmentation and characteristic measurement method of multibubbles is valid and with high precision
Summary
Gas-liquid two-phase flow is a typical flow, and bubble characteristic measurement is of great importance to discover the flow mechanism and guide the practical fluid mechanical engineering [1]. Zhang et al [10] proposed polygonal approximation method to find dominant points and segmented ellipse fitting bubbles based on average distance deviation criterion and two constraint conditions. It was not accurate for ellipselike bubbles shape, and false connection points could not be recognized and removed. Considering the real outline of bubbles and taking the irregular bubble shapes into account, a multibubbles segmentation method based on virtual stereo vision and chain code information is proposed It consists of three main steps, identification of candidate concave points referring to chain code difference, removal of the pseudoconcave points based on the concave length, and matching real concave points according to axial constraint. The experimental results show that the segmentation and characteristic measurement method of multibubbles is valid and with high precision
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