Theoretical analysis of the measurement precision in particle image velocimetry

By Jerry Westerweel. 2000

491 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/5f6c1f756869039008efc14fc0384e52032a67cd

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In Computer Vision and Pattern Recognition

Citations in the corpus

Measurement of laminar, transitional and turbulent pipe flow using Stereoscopic-PIV (2007, methodology): “This is related to the socalled one-quarter-rule (the second control parameter in Table 3). If the loss of particle pairs is less than 25%, then the correlation-noise (the RMS of the mean particle displacement) is of the order of 0.1 px (Foucaut et al. 2004; Westerweel 2000a ).”
Mind the gap: a new insight into the tip leakage vortex using stereo-PIV (2014, methodology): “1 pixel uncertainty on the measurement of particle displacements (Westerweel 2000).”
Large scale PIV-measurements at the surface of shallow water flows (2002, methodology): “A common technique to test the accuracy of PIV systems is given by Westerweel [20], where artificial particle clouds are generated with random spatial distribution to simulate a reproducable particle movement under well determined boundary conditions.”
Digital particle image velocimetry (DPIV) robust phase correlation (2009, methodology): “To simplify our model, we have chosen to approximate the intensity distribution by a discrete Gaussian [19, 20], where higher frequency components of the Gaussian are aliased, contributing to the Paliased noise signal.”
Limitations of accuracy in PIV due to individual variations of particle image intensities (2009, background): “the loss-of-pairs and from the degradation of the correlation peak due to the out-of-plane motion [3, 34, 35, 36], large scale illumination variations [21] or intensity variations only due to the different particle locations within the light sheet without relative changes between the exposures [36].”
Single-pixel resolution ensemble correlation for micro-PIV applications (2004, methodology): “For a typical domain size of 32·32 pixels for W the measurement precision for the displacement is better than 0.1 px (Willert 1996; Westerweel 2000a ).”
PIV uncertainty quantification by image matching (2013, background): “Westerweel (2000) reported a typical figure of 0.05 pixels from Monte Carlo simulations.”
Mixing and segregation in a bidisperse gas-solid fluidized bed: a numerical and experimental study (2004, unknown): “To apply PIV overlap should remain sufficiently rare ( N S b 1), while the number of particles must be sufficiently high [14]: where F I and F O are the relative number of particles that are lost because of in-plane and out-of-plane displacement, respectively.”
Momentum and scalar transport at the turbulent/non-turbulent interface of a jet (2009, background): “In the case of experimental PIV data, even for an irrotational flow finite values for 〈ω(2) z〉 are found as a result of the finite measurement error in the displacement (Adrian 1991; Westerweel 2000).”
On velocity gradients in PIV interrogation (2008, methodology): “In the interrogation analysis in particle image velocimetry (PIV) by means of a spatial correlation, it is generally assumed that the displacement field is uniform (Adrian 1988; Westerweel 1993, 1997; Olsen and Adrian 2001).”
Estimation of uncertainty bounds for individual particle image velocimetry measurements from cross-correlation peak ratio (2013, background): “The correlation of the fluctuating signals (RD) can further be divided into an ensemble average component, 〈RD| V 〉, which carries the information about the displacement field, V , within a pair of interrogation windows, and a fluctuating component, RD, corresponding to image noise and the correlati”