Toward real-time particle tracking using an event-based dynamic vision sensor
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Optically based measurements in high Reynolds number fluid flows often require high-speed imaging techniques. These cameras typically record data internally and thus are limited by the amount of onboard memory available. A novel camera technology for use in particle tracking velocimetry is presented in this paper. This technology consists of a dynamic vision sensor in which pixels operate in parallel, transmitting asynchronous events only when relative changes in intensity of approximately 10% are encountered with a temporal resolution of 1 μs. This results in a recording system whose data storage and bandwidth requirements are about 100 times smaller than a typical high-speed image sensor. Post-processing times of data collected from this sensor also increase to about 10 times faster than real time. We present a proof-of-concept study comparing this novel sensor with a high-speed CMOS camera capable of recording up to 2,000 fps at 1,024 × 1,024 pixels. Comparisons are made in the ability of each system to track dense (ρ >1 g/cm3) particles in a solid–liquid two-phase pipe flow. Reynolds numbers based on the bulk velocity and pipe diameter up to 100,000 are investigated.
KeywordsParticle Image Velocimetry Particle Tracking Light Sheet Particle Tracking Velocimetry Particle List
This work was partially funded by the Research Council of Norway via "Strategic Institute Project ES132014, Droplet Transport Modeling and Generation Enhancement in Hydrocarbon Multiphase Transport". Svein Vesterby provided invaluable help in setting up and maintaining the test apparatus in the Hydrodynamics laboratory at the University of Oslo.
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