Computer vision techniques for Taylor bubble detection and velocity measurement using YOLO v8 and optical flow

IF 2.3 3区工程技术 Q2 ENGINEERING, MECHANICAL

Flow Measurement and Instrumentation Pub Date : 2025-03-18 DOI:10.1016/j.flowmeasinst.2025.102885

Leonardo Fadel Metzker, Cáio César Silva Araújo, Maurício de Melo Freire Figueiredo, Ana Maria Frattini Fileti

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引用次数: 0

Abstract

This study focuses on measuring the velocity and length of Taylor bubbles in vertical liquid–gas two-phase slug flows using a non-intrusive image-based methodology. High-resolution video footage of the flow was analyzed through the YOLO v8 object detection algorithm, combined with the optical flow technique for motion analysis. The proposed method achieved an average detection precision of 84.3% and a velocity measurement accuracy of 88%. Measurements of bubble lengths showed maximum deviations of 1.1% when compared to manual measurements, with larger discrepancies occurring primarily in cases involving elongated or deformed bubbles. Velocity measurements demonstrated strong agreement with mechanistic model predictions, with deviations not exceeding 6%. These results highlight the robustness and reliability of the proposed method for analyzing bubble dynamics, offering valuable insights into flow behavior for multiphase flow applications and facilitating improved process optimization.

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使用YOLO v8和光流进行泰勒气泡检测和速度测量的计算机视觉技术

本研究的重点是使用非侵入式成像方法测量垂直液气两相段塞流中泰勒气泡的速度和长度。通过YOLO v8目标检测算法对流场的高分辨率视频片段进行分析，并结合光流技术进行运动分析。该方法的平均检测精度为84.3%，速度测量精度为88%。与人工测量相比，气泡长度测量的最大偏差为1.1%，较大的差异主要发生在涉及伸长或变形气泡的情况下。速度测量结果与机械模型预测结果非常吻合，误差不超过6%。这些结果突出了所提出的气泡动力学分析方法的鲁棒性和可靠性，为多相流应用的流动行为提供了有价值的见解，并促进了改进的过程优化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Flow Measurement and Instrumentation 工程技术-工程：机械

CiteScore

4.30

自引率

13.60%

发文量

123

审稿时长

6 months

期刊介绍： Flow Measurement and Instrumentation is dedicated to disseminating the latest research results on all aspects of flow measurement, in both closed conduits and open channels. The design of flow measurement systems involves a wide variety of multidisciplinary activities including modelling the flow sensor, the fluid flow and the sensor/fluid interactions through the use of computation techniques; the development of advanced transducer systems and their associated signal processing and the laboratory and field assessment of the overall system under ideal and disturbed conditions. FMI is the essential forum for critical information exchange, and contributions are particularly encouraged in the following areas of interest: Modelling: the application of mathematical and computational modelling to the interaction of fluid dynamics with flowmeters, including flowmeter behaviour, improved flowmeter design and installation problems. Application of CAD/CAE techniques to flowmeter modelling are eligible. Design and development: the detailed design of the flowmeter head and/or signal processing aspects of novel flowmeters. Emphasis is given to papers identifying new sensor configurations, multisensor flow measurement systems, non-intrusive flow metering techniques and the application of microelectronic techniques in smart or intelligent systems. Calibration techniques: including descriptions of new or existing calibration facilities and techniques, calibration data from different flowmeter types, and calibration intercomparison data from different laboratories. Installation effect data: dealing with the effects of non-ideal flow conditions on flowmeters. Papers combining a theoretical understanding of flowmeter behaviour with experimental work are particularly welcome.