Hybrid digital holographic imaging system for three-dimensional dense particle field measurement

Cao, Lujie; Pan, Gang; Jong, Jeremy de; Woodward, Scott H.; Meng, Hui

doi:10.1364/ao.47.004501

Cited by 26 publications

(16 citation statements)

References 16 publications

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“…For holograms that cover a larger volume at a lower magnification, Meng and colleagues (Cao et al 2008, Salazar et al 2008 reduce the DOF by using a hybrid setup, which still involves in-line holography, but records 90 • side scattering from particles (Figure 4c). Ooms et al (2006) have introduced another approach, which inserts a ring-shaped circular aperture between a pair of identical lenses, which are separated by twice their focal length.…”

Section: Tracking and Measurements Of Particle Displacement From Digimentioning

confidence: 99%

“…Results supported the view that the generation of hairpins was governed by the base-flow shear strain and the existence of a sufficiently large initial disturbance. Recently, Cao et al (2008) and Salazar et al (2008) used the setup shown in Figure 4c to measure the spatial distribution of particles in isotropic turbulence and compared the results with DNS predictions. The experiments were performed in a special isotropic turbulence facility containing air, and consisted of measuring the location of several hundred 6-μm hollow glass spheres in a 1-cm 3 volume.…”

Section: Applications Related To Turbulence Researchmentioning

confidence: 99%

“…The red line in the sample volume represents a phase object, e.g., a cell. (c) Optical layout of the hybrid digital holography with 90 • side scattering from particles(Cao et al 2008). The red dashed line indicates the image plane.…”

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confidence: 99%

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Applications of Holography in Fluid Mechanics and Particle Dynamics

Katz

Sheng

2010

Annu. Rev. Fluid Mech.

404

188

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The quantification of three-dimensional (3D) flow structures and particle dynamics is crucial for unveiling complex interactions in turbulent flows. This review summarizes recent advances in volumetric particle detection and 3D flow velocimetry involving holography. We introduce the fundamental principle of holography and discuss the debilitating depth-of-focus problem, along with methods that have been implemented to circumvent it. The focus of this review is on recent advances in the development of in-line digital holography in general, and digital holographic microscopy in particular. A mathematical background for the numerical reconstruction of digital holograms is followed by a summary of recently introduced 3D particle tracking and velocity measurement techniques. The review concludes with sample applications, including 3D velocity measurements that fully resolve the flow in the inner part of a turbulent boundary layer, the diffusion of oil droplets in high-Reynolds number turbulence, and predator-prey interactions among swimming microorganisms in dense suspensions, as well as oceanic and atmospheric field experiments.

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Section: Tracking and Measurements Of Particle Displacement From Digimentioning

confidence: 99%

Section: Applications Related To Turbulence Researchmentioning

confidence: 99%

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Applications of Holography in Fluid Mechanics and Particle Dynamics

Katz

Sheng

2010

Annu. Rev. Fluid Mech.

404

188

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“…Due to the extended DOF, DH is now gaining as an emerging and promising characterization tool in many scientific and engineering fields. DH has been successfully applied in the numerous fields such as micro-structure testing [27], investigation of red blood cell [28], in spray analysis [29], microscopy [30][31][32], bubble characterization [33], particle characterization [34][35][36][37], particle image velocimetry (PIV) [38], and biological applications [39][40]. In spite of these advantages, DH has inferior qualities in terms of pixel resolution and image dimension [25].…”

Section: Background and Motivationmentioning

confidence: 99%

“…As a result, DH will take off as a widely embraced tool for particle characterization at the time of its transition from transmission to the reflection mode. So far, some literature has been found out in which 90 0 scattering of the object wave front was captured by the digital sensors [25,36]. No literature is reported about the reflection based digital particle holography.…”

Section: Directions For Future Researchmentioning

confidence: 99%

Digital holographic systems for particulate processes

Rahman¹

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List of Figures 2.1 Limitations of photographic imaging technique. (a) out of focused particle on a photographic image plane; (b) aggregated particles on the image plane. 12 2.2 Geometry of DIH 14 2.3 Schematic representation showing step-wise implementation of DH for micro-objects analysis. 2.4 Diffraction pattern of a particle onto the CCD array. 2.5 Maximum spatial frequency resolved by a CCD array. 2.6 Particle with diverging illumination. 3.1 Materials used for particle concentration and turbidity effects. (a) for concentration effect; (b) for turbidity effect. 3.2 Optical setup of the digital inline holographic microscopy. 3.3 Schematic for the calculation of sample volume imaged onto the camera. 3.4 Effect of particle concentration on detection efficiency. 3.5 Reconstructed images for 10 mm depth. (a) 0.01 v/v% particle concentration; (b) 0.05 v/v% particle concentration showing particle-particle interaction; (c) 0.05 v/v% particle concentration showing size reduction due to the noise (particle outlines at both lower and higher concentrations are shown in the inset for comparison). The green region is the area identified as the particle by the image processing algorithm. 3.6 Holograms and reconstructed images at 0.01 v/v% particle concentration. (a) hologram for 5 mm depth; (b) hologram for 10 mm depth; (c) reconstructed image at 25.55 mm for the hologram shown at (a); (d) reconstructed image at 29.95 mm for the hologram shown at (b). 30 3.7 PSDs and particle sizes at different concentrations. (a) PSDs for 10 mm depth; (b) Errorbar plot of the particle sizes for 10 mm depth; (c) PSDs for 5 mm depth; (d) Errorbar plot of the particle sizes for 5 mm depth. Errorbar plots are drawn based on the means and standard deviations of the distributions.

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