Publications Details
Denoising 400-khz “postage-stamp piv” using uncertainty quantification
A new approach to denoising Time-Resolved Particle Image Velocimetry data is proposed by incorporating measurement uncertainties estimated using the correlation statistics method. The denoising algorithm of Oxlade et al (Experiments in Fluids, 2012) has been modified to add the frequency dependence of PIV noise by obtaining it from the uncertainty estimates, including the correlated term between velocity and uncertainty that is zero only if white noise is assumed. Although the present approach was only partially effective in denoising the 400-kHz “postage-stamp PIV” data, important and novel insights were obtained into the behavior of PIV uncertainty. The belief that PIV noise is white noise has been shown to be inaccurate, though it may serve as a reasonable approximation for measurements with a high dynamic range. Noise spectra take a similar shape to the velocity spectra because increased velocity fluctuations correspond to higher shear and therefore increased uncertainty. Coherence functions show that correlation between velocity fluctuations and uncertainty is strongest at low and mid frequencies, tapering to a much weaker correlation at high frequencies where turbulent scales are small with lower shear magnitudes.