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Validation of Multi-Frame PIV Image Interrogation Algorithms in the Spectral Domain

机译:谱域中多帧PIV图像询问算法的验证

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Multi-frame correlation algorithms for time-resolved PIV have been shown in previous studies to reduce noise and error levels in comparison with conventional two-frame correlations. However, none of these prior efforts tested the accuracy of the algorithms in spectral space. Even should a multi-frame algorithm reduce the error of vector computations summed over an entire data set, this does not imply that these improvements are observed at all frequencies. The present study examines the accuracy of velocity spectra in comparison with simultaneous hot-wire data. Results indicate that the high-frequency content of the spectrum is very sensitive to choice of the interrogation algorithm and may not return an accurate response. A top-hat-weighted sliding sum-of-correlation is contaminated by high-frequency ringing whereas Gaussian weighting is indistinguishable from a low-pass filtering effect. Some evidence suggests the pyramid correlation modestly increases bandwidth of the measurement at high frequencies. The apparent benefits of multi-frame interrogation algorithms may be limited in their ability to reveal additional spectral content of the flow.
机译:与传统的双帧相关相比,以前的研究中已经显示了用于时间分辨PIV的多帧相关算法,以降低噪声和误差水平。然而,这些事先努力都没有测试谱空间中算法的准确性。甚至应该将多帧算法减少在整个数据集上求和的矢量计算错误,这并不意味着在所有频率下观察到这些改进。本研究研究了与同时热线数据相比的速度光谱的准确性。结果表明,光谱的高频含量对询问算法的选择非常敏感,并且可能不会返回准确的响应。通过高频振铃污染顶帽加权的滑动总和,而高斯加权与低通滤波效果无法区分。有些证据表明金字塔相关性适度地增加了高频测量的带宽。多帧询问算法的表观益处可以限制它们能够揭示流动的额外光谱含量的能力。

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