This study presents an event-data-enhanced particle streak velocimetry (EE-PSV) technique, which integrates data from a high-frequency event-based camera and a low-frequency frame-based camera (125 FPS), as well as the fusion of their respective imaging information. The proposed EE-PSV approach is built around the frame-based camera, with an extended exposure time to capture all laser pulses, while the final velocity measurements are derived from grayscale frame-based images. Event-based data are utilized for defining particle track direction, guiding tracking, and separating overlapping particle tracks. The accuracy of particle-center positioning was validated using a jet flow experiment under two Reynolds numbers (Re) and three particle densities, confirming the measurement reliability of the EE-PSV technique. The event-based data serve two key purposes: (1) resolving the directional ambiguity inherent in traditional PSV methods that rely solely on grayscale images and (2) separating either point-like trajectories or continuous streaks encountered in conventional PSV, thereby enabling accurate particle localization and tracking even in cases of overlapping streaks. EE-PSV achieves enhanced positioning and tracking accuracy by tracing particles directly on grayscale images from the frame-based camera, rather than relying on event-based particle localization. EE-PSV achieves high-precision particle positioning and velocity tracking by tracing particles on frame-camera grayscale images, the percentage increase in precision is 22.97% (for point-like trajectories) and 16.87% (for streak-like trajectories) when compared with the event-based data tracking. Finally, the EE-PSV technique offers valuable guidance for future system design, indicating that event-based cameras may be better utilized as complementary tools to enhance traditional frame-based cameras—whether operating at low or high frequencies—in PSV/PIV/PTV systems, rather than serving as the primary sensing modality for flow measurement.
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