Novel streak-resolving algorithm for particle streak velocimetry

Abstract

In this paper, a novel streak-resolving algorithm is proposed for particle streak velocimetry (PSV) to resolve velocity fields for a single image frame with multiple particle streaks. A model streak function, which was based on the temporal integral of the particle image intensity moving along its trajectory during the exposure period, was approximated using a multivariable least-square fit procedure to reconstruct the streak information and the corresponding particle trajectory. Lagrangian tracking was achieved, and the velocities were evaluated by differentiating the resolved particle trajectory with respect to time. Two types of flows, accelerating parallel flow and the rotational flow of Hill’s vortex, were used to generate synthetic streaks for the performance tests. Three types of relative error were defined and used to evaluate the performance of the algorithm in terms of statistical mean and standard deviation (SD) errors. The accuracy of the fitted streak parameters, such as particle image intensity and diameter, were also evaluated and compared. The results reveal that the error and SD were low if the image noise is below 1.0%; for noise levels of 5.0%, the error was up to 10% with an SD of up to 12%. The error and SD of the particle image intensity and particle image diameter for both flow types were also 0%–7% for clean and up to 12% for noisy images. The processing results for experimental streak images of flow past a cylinder reveal that these images can be resolved using the proposed algorithm with a residual mean error of 4.38 and an SD of 9.48. These results suggest that the proposed novel approach can be used to resolve velocity fields with only a single image frame and without expensive hardware for high-speed imaging and thus is suitable for diverse applications.