Holographic Astigmatic Particle Tracking Velocimetry

TL;DR

This paper introduces holographic astigmatic PTV (HAPTV), a novel method that enhances digital inline holography particle tracking by resolving twin image issues, enabling accurate flow measurements in large-scale or field environments.

Contribution

HAPTV employs a cylindrical lens and a customized reconstruction algorithm to distinguish tracer particles on different sides of the focal plane, improving depth resolution in DIH-PTV.

Findings

HAPTV achieves a calibration error standard deviation of 4.2 um at high magnification.

HAPTV extends the depth of field compared to conventional astigmatic PTV.

HAPTV accurately measures flow velocity in a laminar jet flow.

Abstract

The formation of twin images in digital inline holography (DIH) prevents the placement of the focal plane in the center of a sample volume for DIH-based particle tracking velocimetry (DIH-PTV) with a single camera. As a result, it is challenging to apply DIH-PTV for flow measurements in large-scale laboratory facilities or many field applications where it would otherwise be desirable due to the low cost and compact setup. Here we introduce holographic astigmatic PTV (HAPTV) by inserting a cylindrical lens in the optical setup of DIH-PTV, generating distorted holograms. Such distortion is subsequently utilized in a customized reconstruction algorithm to distinguish tracers positioned on different sides of the focal plane which can in turn be placed in the middle of a sample volume. Our HAPTV approach is calibrated under high (1 um/pixel) and low (10 um/pixel) magnifications with an error standard deviation of 4.2 um (one particle diameter) and 120.7 um (~5 times the particle diameter), respectively. We compare the velocity field of a laminar jet flow obtained using HAPTV and conventional PIV to illustrate the accuracy of the technique when applied to practical flow measurement applications. The work demonstrates that HAPTV improves upon the depth of field of conventional astigmatic PTV and enables the implementation of DIH-based PTV for in situ applications.