Bubble identification based on high speed videometry data: Algorithm and validation

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Abstract

The simultaneous flow of gas and liquid in a pipe is commonly found in several industrial activities, such as crude oil extraction and processing. In order to analyze this (two-phase) flow, many measurement techniques have been proposed, including X-ray, ultrasound, impedance and optical measurement. In this context, although the high speed videometry use is limited in practical cases, it is an important tool to validate other methods in experimental essays. Approaches based on image segmentation have already been considered to analyze gas-liquid flows along vertical pipes, but just a few have focused horizontal experiments, which are also widely found in many applications. This article describes a new technique developed to automatically measure the bubble volume through video analysis. The tests carried out considering horizontal air-water flow images yielded results with good correlation with known volume data, thus showing that the measurements are accurate enough to be considered for the validation of other technologies. © 2012 Springer-Verlag.

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Do Amaral, C. E. F., Alves, R. F., Da Silva, M. J., Arruda, L. V. R., Dorini, L. B., & Morales, R. E. M. (2012). Bubble identification based on high speed videometry data: Algorithm and validation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7441 LNCS, pp. 870–876). https://doi.org/10.1007/978-3-642-33275-3_107

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