Investigation of cloud droplets velocity extraction based on depth expansion and self-fusion of reconstructed hologram

Abstract

The velocity of cloud droplets has a significant effect on the investigation of the turbulence-cloud microphysics interaction mechanism. The paper proposes an in-line digital holographic interferometry (DHI) technique based on depth expansion and self-fusion algorithm to simultaneously extract particle velocity from eight holograms. In comparison to the two-frame exposure method, the extraction efficiency of velocity is raised by threefold, and the number of reference particles used for particle registration is increased to eight. The experimental results obtained in the cloud chamber show that the velocity of cloud droplets increases fourfold from the stabilization phase to the dissipation phase. The measurement deviations of two phases are 1.138 and 1.153 mm/s, respectively. Additionally, this method provides a rapid solution for three-dimensional particle velocimetry investigation of turbulent field stacking and cloud droplets collisions.