An image processing algorithm for the measurement of multiphase bubbly flow using predictor-corrector method. (July 2020)

• Record Type: Journal Article
• Authors: Zhou, Haojie; Niu, Xiaojing
• Is Part Of: International journal of multiphase flow. Volume 128(2020)
• Publication Date: 2020-07
• Subjects: Multi-frame -- Image processing -- Bubbly flow -- Particle tracking velocimetry -- Predictor-corrector method; Multiphase flow -- Periodicals; Écoulement polyphasique -- Périodiques; Multiphase flow; Periodicals; 620.1064
• DOI: 10.1016/j.ijmultiphaseflow.2020.103277
• Languages: English
• ISSNs: 0301-9322

Abstract

Highlights: An image processing algorithm based on the concept of predictor-corrector is proposed to deal with the shadow images of bubbly flow. Totally obscured or overlapped bubbles can be detected. Experiment of bubbly plume can be well measured. Abstract: Optical photography and image analysis technology provide a non-intrusive and efficient research tool for the experimental research of multiphase bubbly flow. This paper presented a multi-frame image processing algorithm for measuring size and velocity of bubbles more accurately with bubble shadow images, especially in bubbly plume with serious overlapping in the bubble image. The raw images are the accurate recording of bubble shadow by high frequency CCD camera. In the shadow image, some of bubbles are isolated and others may overlap resulting in a complex geometric shape. It is easy to obtain the shape and centroid of isolated bubbles. But for the overlapping bubbles, additional effort should be made to detect each one from a cluster. And some of them are highly and completely overlapped, and may be lost during tracking. The main conception of the algorithm is based on the continuity of bubble movement to retrieve those bubbles. In one frame, a bubble which is highly or completely overlapped by others may appear alone in another frame. With the information of previous frames, the centroid and size of highly overlapping bubbles are predicted and then corrected according internal cores and edge information of bubble shadow. The algorithm is tested by artificial bubble images and further applied to the experiment of bubbly plume. It is proved that the algorithm performs well in recognition of bubbles and especially in determination of the size and velocity of bubbles in a cluster. For the artificial bubble images, the proposed algorithm successfully captures all bubbles including an inner bubble which cannot be detected in a single frame. For the experiment of bubbly plume, which is conducted in a tank with a 1 cm diameter nozzle at bottom and with the superficial gas velocity ranging from 31.8 to 53.1 mm/s, the effectiveness of the proposed method also reaches 95% by random sampling. For the case that more than half of bubbles are overlapped, the new algorithm can improve the recognition rate from 4% to 6% comparing with the primary algorithm without predictor-corrector method.