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Image processing techniques for high-speed videometry in horizontal two-phase slug flows

机译:水平两相弹团流中高速测像的图像处理技术

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摘要

Two-phase flow measurements are very common in industrial applications especially in oil and gas areas. Although some works in image segmentation have analyzed gas-liquid slug flow along vertical pipes, few approaches have focused on horizontal experiments. In such conditions, the detection of the Taylor bubble is challenging due the great amount of small bubbles in the slug area and, thus, requires a special treatment in order to separate gas from liquid phases. This article describes a new technique that automatically estimates bubble parameters (e.g. frequency, dimension and velocity) through video analysis of high-speed camera measurements in horizontal pipes. Experimental data were obtained from a flow test section where slug flows were generated under controlled conditions. Image processing techniques such as watershed segmentation, top-hat filtering and H-minima transform were applied to detect and estimate bubble contour and velocities from the observed images. Finally, the estimated parameters were compared to theoretical predictions, showing good agreement and indicating that the proposed technique is a powerful tool in the investigation of two-phase flow.
机译:两相流测量在工业应用中非常普遍,尤其是在石油和天然气领域。尽管一些图像分割方面的工作已经分析了沿垂直管道的气液塞流,但很少有方法专注于水平实验。在这种情况下,由于段塞区域中存在大量小气泡,因此泰勒气泡的检测具有挑战性,因此需要进行特殊处理才能将气体与液相分离。本文介绍了一种新技术,该技术可以通过对水平管道中高速摄像头测量的视频分析来自动估算气泡参数(例如频率,尺寸和速度)。从流量测试部分获得了实验数据,在受控条件下产生了团状流。图像处理技术(例如分水岭分割,高顶滤波和H-minima变换)被用于从观察到的图像中检测和估计气泡轮廓和速度。最后,将估计的参数与理论预测值进行比较,显示出良好的一致性,并表明所提出的技术是研究两相流的有力工具。

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