A New Bubble Image Model Based on the Recognition of Bubble Flow

Abstract

In this study, a new ellipse-fitting algorithm is proposed to achieve the reconstruction of bubble shapes in bubbly flow captured by a high-speed camera in the gas–liquid two-phase column reactor. Bubble flow patterns and geometric parameters in the experimental images are recognized and identified successfully, represented by means of the topological parameters. Three logical steps are carried out in detail. First, the area threshold and the circularity factors are established to identify the bubbles whether belonging to a single bubble or not. The overlapping bubbles in images can be separated from single bubbles based on a watershed segmentation algorithm. Second, a single bubble image and an overlapping bubble image are combined into one image. After that, statistical analysis for the size distributions and ellipse area bubbles is performed for further analysis and discussion. The advantage of this algorithm is that it can make use of a set of major and minor axes of an ellipse to capture the ellipse parameters more effectively. Simulation results are well agreed with experimental measurements. Moreover, it can be used to detect many ellipse-like bubbles that are dispersed in high-speed camera images, indicating that it is a better strategy for the recognition and identification of bubbly turbulent flow accurately.