Three-dimensional feature parameters measurement of bubbles in gas–liquid two-phase flow based on virtual stereo vision

Abstract

In this paper, three-dimensional (3D) feature parameters reconstruction and measurement methods of bubbles in gas–liquid two-phase flow based on virtual stereo vision have been developed. A mathematical model of virtual stereo vision is established, and the optimized design method of structure parameters is discussed in detail. In addition, the key technologies for the 3D measurement of bubbles, including the camera calibration, the virtual stereo vision sensor calibration, image processing, feature extraction and 3D reconstruction of bubble trajectories are introduced. All the intrinsic and extrinsic parameters of two virtual cameras, as well as coefficients of lens distortion, can be estimated by the complete mathematical model of the camera. With the sensor calibration, the relative position and orientation of two virtual cameras are determined. Several improved image processing algorithms are used to extract the primary modality parameters of bubbles, and then the 3D trajectories of bubbles can be reconstructed based on the measurement model of virtual stereo vision. The experiment is tested on the upstream bubble-producing appliance. It shows that the method is valid, and the 3D trajectories of bubbles can be reconstructed with high precision. The measured absolute error of bubble 3D displacement is smaller than 0.13 mm, and the relative error is smaller than 0.49%.