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Globally optimized cross-correlation for particle image velocimetry
Experiments in Fluids ( IF 2.4 ) Pub Date : 2020-10-10 , DOI: 10.1007/s00348-020-03062-x Hongping Wang , Guowei He , Shizhao Wang
Experiments in Fluids ( IF 2.4 ) Pub Date : 2020-10-10 , DOI: 10.1007/s00348-020-03062-x Hongping Wang , Guowei He , Shizhao Wang
We propose a global optimization method to automatically search for the correlation peak instead of computing the entire cross-correlation map throughout an interrogation window (IW) using a fast Fourier transform (FFT)-based method. The proposed method, named globally optimized cross-correlation for particle image velocimetry (GOCCPIV), minimizes an objective function consisting of a residual term for cross-correlation and a penalty term for smoothness to solve the optimal velocity field. A very small IW is adopted in GOCCPIV to obtain a dense velocity field with a high spatial resolution. The proposed method is quantitatively validated on synthetic particle image pairs with different flow patterns and is compared with the mainstream FFT-based cross-correlation method (FFTCCPIV) and physical-based optical flow (OpticalFlow). We consider the influences of the IW size, particle concentration, particle image diameter, large displacements and image noise on the velocity measurements. Error analysis indicates that GOCCPIV outperforms FFTCCPIV in resolving small-scale vortices and reducing the measurement error. Finally, the proposed method is applied to a real PIV experiment with an impinging jet. The results indicate that GOCCPIV is more suitable than FFTCCPIV for resolving high-velocity-gradient regions.
中文翻译:
粒子图像测速的全局优化互相关
我们提出了一种全局优化方法来自动搜索相关峰值,而不是使用基于快速傅立叶变换 (FFT) 的方法在整个询问窗口 (IW) 中计算整个互相关图。所提出的方法称为粒子图像测速全局优化互相关(GOCCPIV),它最小化由互相关残差项和平滑惩罚项组成的目标函数,以求解最佳速度场。GOCCPIV 中采用非常小的 IW 来获得具有高空间分辨率的密集速度场。该方法在具有不同流型的合成粒子图像对上进行了定量验证,并与主流的基于 FFT 的互相关方法 (FFTCCPIV) 和基于物理的光流 (OpticalFlow) 进行了比较。我们考虑了 IW 尺寸、粒子浓度、粒子图像直径、大位移和图像噪声对速度测量的影响。误差分析表明,GOCCPIV在解决小尺度涡旋和减少测量误差方面优于FFTCCPIV。最后,将所提出的方法应用于具有撞击射流的真实 PIV 实验。结果表明GOCCPIV比FFTCCPIV更适合解析高速梯度区域。
更新日期:2020-10-10
中文翻译:
粒子图像测速的全局优化互相关
我们提出了一种全局优化方法来自动搜索相关峰值,而不是使用基于快速傅立叶变换 (FFT) 的方法在整个询问窗口 (IW) 中计算整个互相关图。所提出的方法称为粒子图像测速全局优化互相关(GOCCPIV),它最小化由互相关残差项和平滑惩罚项组成的目标函数,以求解最佳速度场。GOCCPIV 中采用非常小的 IW 来获得具有高空间分辨率的密集速度场。该方法在具有不同流型的合成粒子图像对上进行了定量验证,并与主流的基于 FFT 的互相关方法 (FFTCCPIV) 和基于物理的光流 (OpticalFlow) 进行了比较。我们考虑了 IW 尺寸、粒子浓度、粒子图像直径、大位移和图像噪声对速度测量的影响。误差分析表明,GOCCPIV在解决小尺度涡旋和减少测量误差方面优于FFTCCPIV。最后,将所提出的方法应用于具有撞击射流的真实 PIV 实验。结果表明GOCCPIV比FFTCCPIV更适合解析高速梯度区域。