Assessment of advanced windowing techniques for digital particle image velocimetry (DPIV)
Assessment of advanced windowing techniques for digital particle image velocimetry (DPIV)
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DOI：
10.1088/0957-0233/20/7/075402
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发表时间：
2009-07-01
影响因子：
2.4
通讯作者：
Vlachos, Pavlos P.
中科院分区：
文献类型：
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作者：
Eckstein, Adric;Vlachos, Pavlos P.
基于傅立叶互相关的DPIV估计方法由于计算简单，是目前最常用的估计方法。然而，由于傅立叶变换是在离散的有限尺寸区域上进行的，因此由于输入信号的不正确滤波而引入了系统误差。这项研究探索了先进的加窗技术来减弱这些基于傅里叶变换的误差的潜力。窗口的选择对空间分辨率、测量精度和峰值检测过程都有影响。使用人工图像模拟的误差分析能够表征单个性能特性上的一组最优窗口。使用该分析，定义了用于最佳窗口的一组标准，从中分析集中于50%高斯窗口的使用。在剪切和涡旋模拟中，进一步将高斯窗口与标准评估技术进行了比较，这表明这一先进技术具有显著的性能优势。进一步的仿真表明，背景噪声大大放大了相关误差的损失，从而影响了峰值检测过程。然而，这些影响很容易通过使用图像预处理或稳健的相位相关来克服。2003年PIV挑战赛的图像被用来验证高斯窗口技术，与标准窗口相比，该技术能够几乎消除所有错误的矢量。
The Fourier-based cross-correlation is the most common evaluation technique for DPIV estimation, due to its computational simplicity. However, because Fourier transforms are taken over discrete finite size regions, systematic errors are introduced due to the improper filtering of the input signals. This study explores the potential of advanced windowing techniques to attenuate these Fourier-based errors. The choice of window is shown to impact the spatial resolution, the measurement accuracy and the peak detection process. Error analysis using artificial image simulations is able to characterize a set of optimal windows onto a single performance characteristic. Using this analysis, a set of criteria is defined for an optimal windowing from which the analysis focused on the use of the 50% Gaussian window. The Gaussian window is further compared against standard evaluation techniques in both shear and vortex simulations, which indicate substantial performance benefits with this advanced technique. Further simulations reveal that background noise greatly amplifies the loss of correlation errors, which affect the peak detection process. However, these effects are easily overcome through the use of image preprocessing or the robust phase correlation. Images from the 2003 PIV challenge are used to validate the Gaussian window technique, which is able to remove nearly all of the erroneous vectors in comparison to standard windows.