16th Int Symp on Applications of Laser Techniques to Fluid Mechanics Lisbon, Portugal, 09-12 July, 2012 1 A super-resolution approach for uncertainty estimation of PIV measurements Andrea Sciacchitano 1,* , Bernhard Wieneke 2 , Fulvio Scarano 1 . 1: Faculty of Aerospace Engineering, Delft University of Technology, Delft, The Netherlands 2: LaVision GmbH, Göttingen, Germany *correspondent author: a.sciacchitano@tudelft.nl Abstract A super-resolution approach is proposed for the a posteriori uncertainty estimation of PIV measurements. The measured velocity field is employed to determine the displacement of individual particle images. A disparity set is built from the residual distance between paired particle images of successive recordings. Within each interrogation window, the disparity set is treated with a statistical analysis to infer the measurement uncertainty: the mean disparity is ascribed to bias errors due to poor particle image sampling or spatial modulation effect; the dispersion of the set is related to precision errors, mainly due to random noise in the recordings and to errors in the PIV interrogation. The performance of the estimator is first assessed via Monte Carlo simulation on a uniform flow field with varying out-of-plane displacement. The uncertainty is accurately estimated in optimal imaging condition, while it is underestimated when the imaging conditions are suboptimal. The experimental assessment is conducted on a water jet experiment. For evaluating the performance of the estimator, the actual measurement error is computed as the difference between measured and a reference displacement field; the latter is built with an advanced processing algorithm that exploits the time redundancy of highly oversampled data to reduce the error of one order of magnitude. The capability of the super-resolution technique to quantify the uncertainty within 0.1 px accuracy is proven. 1. Introduction Digital particle image velocimetry (PIV) is nowadays an established and reliable flow diagnostic tool capable of measuring velocity fields in two- and three-dimensional domains. Several works have been focused on PIV measurement errors. Huang et al. (1997) distinguished two major forms of errors in digital PIV, namely the mean-bias and the RMS (or precision) errors. The bias errors are mainly related to spatial modulation effects and to the particle image size. Modulation effects are dominant when the interrogation is conducted at low spatial resolution; furthermore, for particle image diameter of the order of 1 pixel, the measured displacement is biased towards the closest integer value, producing the effect commonly referred to as peak locking (Westerweel, 1997, among others). Precision errors are random errors mainly due to noise introduced during the recording process and numerical errors associated to the interrogation of PIV images. The noise in the recording process causes uncertainty of the pixel values describing the particles, resulting in uncertainty of the particle locations and displacements. The typical magnitude of precision errors is of the order of a fraction of a pixel. A further source of uncertainty in PIV data is the insufficient number of particle image pairs due to low seeding density or out-of-plane motion, which is responsible of spurious vectors. The error associated to spurious vectors is typically orders of magnitude larger than the typical precision error; recognizing incorrect vectors is referred to as data validation (Westerweel, 1994, Westerweel and Scarano, 2005).