Detection and Tracking of Bubbles in Two Phase Flow

Abstract

Bubble detection and tracking is an important and complex part of motion analysis of two phase air-water flow in non linear wavy channels in which bubble speed and size varies and sometimes bubble occludes with the boundaries of the other bubbles. Due to optical noise bubbles boundaries are not recorded completely in a camera and then need to be filled intelligently to recognize them as single entity in a non-convergent sinusoidal channel. To solve this problem non linear sinusoidal curved channel is transformed to a linear straightened horizontal channel and then trail and error method of segmented morphological operations are applied to identify each bubble as a single entity and should not be occluded with the other bubbles. The detected bubbles are associated across different frames based on motion, estimated by Kalman filter to predict frame by frame detections and the likelihood of every detections assigned to each track. Since a Kalman filter is a good estimator for linear motion so path based approach to the sinusoidal channel is more robust, as it linearizes the motion of the sinusoidal channel to study a non linear motion model. Finally the result shown that our path based straightened channel gives more accurate results for both bubble count and computational velocities than non-convergent sinusoidal channel.