Denoising of time-resolved PIV for accurate measurement of turbulence spectra and reduced error in derivatives
Denoising of time-resolved PIV for accurate measurement of turbulence spectra and reduced error in derivatives
复制标题
对时间分辨 PIV 进行去噪，以精确测量湍流谱并减少导数误差
DOI：
10.1007/s00348-012-1375-4
复制
发表时间：
2012
影响因子：
2.4
通讯作者：
Oxlade A
中科院分区：
文献类型：
--
作者：
Oxlade A
时间分辨PIV（TRPIV）湍流测量的准确性受到白色噪声的限制，这降低了小尺度速度波动的信噪比（SNR）。本文介绍了一种新的能量滤波器，扩展了频谱噪声减法的概念到时域。该滤波器等效于白色噪声能量的谱减法，因此可以恢复信号的真实能量。通过比较在网格生成湍流（Reλ= 90）中进行的双组分（2C）TRPIV和恒温风速仪（CTA）测量来评估其有效性。去噪PIV测量结果显示出与高性能CTA系统相当的SNR。速度波动和导数的时间谱被精确地恢复，动态范围提高了$$\fancyscript{O}（10^3）$$。从频谱中得到的耗散估计的误差减少到约2%。直接计算的空间梯度和通过泰勒假设计算的空间梯度之间的相关系数从0.83提高到0.95。均方误差减少被发现是等效的频率和波数域，虽然我们观察到，频域滤波具有有限的能力，以提高在高波数的空间谱的SNR。的能量过滤器的性能被证明是敏感的测量光谱的收敛，因此，我们提供采样标准，以确保最佳的实施湍流测量。
The accuracy of time-resolved PIV (TRPIV) turbulence measurements is limited by white noise, which reduces the signal-to-noise ratio (SNR) of small-scale velocity fluctuations. This paper demonstrates a novel energy filter that extends the concept of spectral noise subtraction to the time domain. The filter is equivalent to the spectral subtraction of white noise energy, and therefore it can recover the true signal energy. Its effectiveness is evaluated by comparing two-component (2C) TRPIV and constant temperature anemometry (CTA) measurements performed in grid-generated turbulence (Reλ= 90). The denoised PIV measurements exhibit a SNR equivalent to those of a high-performance CTA system. The temporal spectra of velocity fluctuations and derivatives are accurately recovered, with an improvement in dynamic range by a factor of $$\fancyscript{O}(10^3)$$. The error in dissipation estimates derived from the frequency spectrum is reduced to approximately 2 %. The correlation coefficient between spatial gradients computed directly and those computed via Taylor’s hypothesis improves from 0.83 to 0.95. The mean-square error reduction is found to be equivalent in the frequency and wavenumber domains, although we observe that frequency domain filtering has a limited ability to improve the SNR of spatial spectra at high wavenumbers. The performance of the energy filter is shown to be sensitive to the convergence of the measured spectra; therefore, we provide sampling criteria to ensure optimal implementation in measurements of turbulent flows.