Abstract
Gas-liquid two-phase bubbly flow widely exists in the field of natural gas extraction. The identification and feature extraction of bubbles are becoming more and more important to the pipe system. This study develops a detection method based on Faster R-CNN for real-time bubble recognition, feature extraction, and void fraction calculation. The method detects ellipsoidal large bubbles in gas–liquid two-phase bubbly flow in a vertical closed pipeline with a high void fraction. The uncertainty of the method is 10 %. Then compared to the gas volume holdup from standard flowmeter, average error of this method is 7.07 %, which has high accuracy. This new detection method finds a new way for feature extraction of two-phase flow.
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