Non-iterative double-frame 2D/3D particle tracking velocimetry
Non-iterative double-frame 2D/3D particle tracking velocimetry
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DOI：
10.1007/s00348-017-2404-0
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发表时间：
2017-09-01
影响因子：
2.4
通讯作者：
Kaehler, Christian J.
中科院分区：
文献类型：
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作者：
Fuchs, Thomas;Hain, Rainer;Kaehler, Christian J.
近年来，检测单个粒子图像并随时间跟踪以确定局部流速已成为平面和体积测量中非常流行的方法。与粒子图像测速等通过相互关联方法对粒子图像集合进行统计分析相比，粒子跟踪测速具有很强的优势。跟踪单个粒子不受空间平均的影响，因此可以避免偏差误差。此外，平均场的空间分辨率可以提高到亚像素级。为了使瞬时测量的空间分辨率最大化，需要高的播种浓度。然而，如果没有可用的时间序列，在高播种浓度下跟踪颗粒仍然具有挑战性。在这些条件下使用的跟踪方法通常是非常复杂的迭代算法，由于大量可调参数，需要专家知识。为了克服这些缺点，本文介绍了一种新的非迭代跟踪方法，该方法不需要指定除位移限制外的任何参数，即可自动分析邻近粒子的运动。这使得算法非常用户友好，也提供了没有经验的用户使用和执行粒子跟踪。此外，该算法可以使用标准双脉冲设备测量高速流动，并且即使在大颗粒图像密度下也能可靠地估计流速。
In recent years, the detection of individual particle images and their tracking over time to determine the local flow velocity has become quite popular for planar and volumetric measurements. Particle tracking velocimetry has strong advantages compared to the statistical analysis of an ensemble of particle images by means of cross-correlation approaches, such as particle image velocimetry. Tracking individual particles does not suffer from spatial averaging and therefore bias errors can be avoided. Furthermore, the spatial resolution can be increased up to the sub-pixel level for mean fields. A maximization of the spatial resolution for instantaneous measurements requires high seeding concentrations. However, it is still challenging to track particles at high seeding concentrations, if no time series is available. Tracking methods used under these conditions are typically very complex iterative algorithms, which require expert knowledge due to the large number of adjustable parameters. To overcome these drawbacks, a new non-iterative tracking approach is introduced in this letter, which automatically analyzes the motion of the neighboring particles without requiring to specify any parameters, except for the displacement limits. This makes the algorithm very user friendly and also offers unexperienced users to use and implement particle tracking. In addition, the algorithm enables measurements of high speed flows using standard double-pulse equipment and estimates the flow velocity reliably even at large particle image densities.