Identification of a new source of peak locking, analysis and its removal in conventional and super-resolution PIV techniques

Nogueira, J.; Lecuona, A.; Rodríguez, Pedro

doi:10.1007/s003480000179

Cited by 54 publications

(39 citation statements)

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“…It is well known that an additional error in the velocity estimation is present due to truncated particle images. The use of weighting functions and the removal of these truncated particle images can decrease this error significantly as shown by Nogueira et al (2001) and Liao and Cowen (2005). However, reducing the interrogation window size, only few and most likely truncated particle images are present, and thus, these techniques do not improve the results any further.…”

Section: Particle Tracking Velocimetry: Resolution Limitmentioning

confidence: 99%

On the resolution limit of digital particle image velocimetry

2012

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This work analyzes the spatial resolution that can be achieved by digital particle image velocimetry (DPIV) as a function of the tracer particles and the imaging and recording system. As the in-plane resolution for window-correlation evaluation is related by the interrogation window size, it was assumed in the past that single-pixel ensemble-correlation increases the spatial resolution up to the pixel limit. However, it is shown that the determining factor limiting the resolution of single-pixel ensemblecorrelation are the size of the particle images, which is dependent on the size of the particles, the magnification, the f-number of the imaging system, and the optical aberrations. Furthermore, since the minimum detectable particle image size is determined by the pixel size of the camera sensor in DPIV, this quantity is also considered in this analysis. It is shown that the optimal magnification that results in the best possible spatial resolution can be estimated from the particle size, the lens properties, and the pixel size of the camera. Thus, the information provided in this paper allows for the optimization of the camera and objective lens choices as well as the working distance for a given setup. Furthermore, the possibility of increasing the spatial resolution by means of particle tracking velocimetry (PTV) is discussed in detail. It is shown that this technique allows to increase the spatial resolution to the subpixel limit for averaged flow fields. In addition, PTV evaluation methods do not show bias errors that are typical for correlation-based approaches. Therefore, this technique is best suited for the estimation of velocity profiles.

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Section: Particle Tracking Velocimetry: Resolution Limitmentioning

confidence: 99%

On the resolution limit of digital particle image velocimetry

2012

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“…• Windowing functions, which become zero at the interrogation area boundaries (Gui et al 2000;Liao and Cowen 2005), reducing the effect of particle image truncation at the edges of the image sub-spaces (interrogation areas) to be correlated (Nogueira et al 2001).…”

Section: Introductionmentioning

confidence: 99%

“…• Direct correlation with a normalization, which so far has been realized in three ways: asymmetrically, with a small interrogation area from the first image correlated with a larger area in the second image (Huang et al 1993a;Fincham and Spedding 1997;Huang et al 1997;Rohály et al 2002), symmetrically, with two interrogation areas of the same size (Nogueira et al 1999;Nobach et al 2004) or bi-directional, combining an asymmetric direct correlation as above and a second direct correlation with a small interrogation area from the second image correlated with a larger area in the first image (Nogueira et al 2001), originally introduced as a ''symmetric'' method, but nonetheless using image sub-spaces of different sizes.…”

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confidence: 99%

Limitations of accuracy in PIV due to individual variations of particle image intensities

2009

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The effect of independent variations of the intensity of individual tracer particles between consecutive images on the accuracy of common displacement estimation methods in particle image velocimetry (PIV) is investigated. Such variations can be observed, e.g., in flows with components perpendicular to the illumination sheet, leading to out-of-plane displacements of the tracer particles. The achievable accuracy of PIV measurements is shown to be limited by this effect alone to be of the order of 0.1 pixel, yielding a basic limitation of the PIV technique.

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“…In many publications dealing with PIV subpixel interpolation, a so-called ''peak-locking'' effect is discussed, which is the tendency of peak position estimates to cluster around integer values (Keane and Adrian 1992;Westerweel 1998;Fincham and Delerce 2000;Forliti et al 2000;Nogueira et al 2001;Gui and Wereley 2002;Scarano (2002). The empirical finding is that a Gaussian peak fit performs better than linear or quadratic interpolation (see e.g.…”

Section: Peak Locking Interpreted As Interpolation Errormentioning

confidence: 91%

Optimal subpixel interpolation in particle image velocimetry

Roesgen

2003

Experiments in Fluids

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It is shown that among the different techniques for particle image velocimetry subpixel interpolation, only the ''sinc''-kernel creates an optimal result in that it completely suppresses spurious spectral sidelobes. An efficient method is introduced for the computation of the subpixel-accurate correlation peak position without any systematic errors. A connection is made with the kerneldependent observation of the peak-locking phenomenon.

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Identification of a new source of peak locking, analysis and its removal in conventional and super-resolution PIV techniques

Cited by 54 publications

References 0 publications

On the resolution limit of digital particle image velocimetry

On the resolution limit of digital particle image velocimetry

Limitations of accuracy in PIV due to individual variations of particle image intensities

Optimal subpixel interpolation in particle image velocimetry

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