Uncertainty Analysis of a Particle Tracking Algorithm Developed for Super-Resolution Particle Image Velocimetry
The spatial resolution is an important parameter of this measuring system since it determines its ability to resolve features of interest in the flow. The super-resolution technique maximises the spatial resolution by augmenting the PIV analysis with a second pass that identifies specific particles and measures the distance between them.
The accuracy of the procedure depends on both the success with which the proper pairings are identified and the accuracy with which their centre-to-centre distance can be measured. This study presents an analysis of both the systematic uncertainty and random uncertainty associated with this process. The uncertainty is analysed as a function of several key parameters that define the quality of the image. The uncertainty analysis is performed by preparing 4000 member ensembles of simulated images with specific setpoints of each parameter.
It is shown that the systematic uncertainty is negligible compared to the random uncertainty for all conditions tested. Also, the image contrast and the selection of a threshold for the particle search are the most critical parameters influencing both success rate and uncertainty. It is also shown that high image intensities still yield accurate results. The search radius used by the super-resolution algorithm is shown to be a critical parameter also. By increasing the search radius, the success rate can be increased although this is accompanied by an increase in random uncertainty.
Advisor:Bugg, James D.; Burton, Richard T.; Evitts, Richard W.; Habibi, Saeid R.; Sumner, David
School:University of Saskatchewan
School Location:Canada - Saskatchewan
Source Type:Master's Thesis
Keywords:high resolution piv simulated images ldv whole field velocity measurements error in uncertainty analysis of algorithm super particle image velocimetry spiv hot wire
Date of Publication:08/11/2003