Quantifying bubble size and 3D velocity in a vortex with digital holographic particle tracking velocimetry (DHPTV)

Wu, Yingchun; Zhang, Hongyu; Wu, Xuecheng; Cen, Kefa

doi:10.1016/j.flowmeasinst.2020.101826

Cited by 11 publications

(6 citation statements)

References 31 publications

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“…Li et al [163] developed a Hough-transform-based hologram processing algorithm, which was then applied to quantify the solid circulation rate, size distribution, 3D position and velocity of particles in a fluidized bed. In addition, Wu et al [19] measured the bubble size, 3D velocity, and acceleration in an electrolytic cell with digital holographic PTV. Considering the difference of optical path between the recording and the reconstruction, they corrected the bubble depth position by multiplying the refractive indices of all the surrounding media (i.e.…”

Section: Characterization Of Droplets and Spraymentioning

confidence: 99%

“…Therefore, as a computational imaging technique, DH has the capability to reconstructthe 3D distribution of particle fields and quantify the particle shape and size simultaneously [15][16][17][18]. Furthermore, combined with particle tracking velocimetry (PTV), DH is capable of measuring the rotation and translation of moving irregular particles [19][20][21]. Besides, DH enjoys other features, such as label-free measurement, simple and low-cost experimental configuration, extended DOF, and automatic image processing.…”

Section: Introductionmentioning

confidence: 99%

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Recent advances and applications of digital holography in multiphase reactive/nonreactive flows: a review

Huang

Cai

et al. 2021

Meas. Sci. Technol.

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In various multiphase flows, the characterization of particle dynamics is of great significance to understand the interaction between particles and the surrounding flows. Digital holography (DH) is a versatile 3D imaging technique, which has shown great advantages in quantitative analysis and non-intrusive diagnosis of various particle fields. This review focuses on the advances and applications of DH in multiphase reactive/non-reactive flows in the last two decades. The basic principles of DH are introduced firstly, including its mathematical background and representative experimental configurations. Then, the image processing algorithms for hologram reconstruction and automatic focusing are summarized, along with the methods for separating overlapping particles and tracking moving particles. As a prevailing and powerful tool, the recent applications of deep learning in processing holographic images is also included in this review. Furthermore, the applications of DH in the characterization of particle dynamics in multiphase reactive/non-reactive flows are surveyed in detail. Lastly, the review concludes with the discussion of the technical limits of DH and provides insights into its promising future research directions.

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Section: Characterization Of Droplets and Spraymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recent advances and applications of digital holography in multiphase reactive/nonreactive flows: a review

Huang

Cai

et al. 2021

Meas. Sci. Technol.

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“…Digital holography of particles is used to address various tasks both in laboratory and field conditions. These may include the study of particles of different nature in various media: plankton organisms [1][2][3][4][5][6][7][8], microplastic particles [9,10], gas bubbles in water [11][12][13], aerosol particles [14][15][16][17], defects in optical crystals [1], erythrocytes [18][19][20][21] and others. Particle holography typically uses an in-line hologram recording scheme [22][23][24][25][26], where the volume of the medium with particles is illuminated with a coherent radiation beam and a part of the radiation scattered on the particles represents an object wave, while the radiation that passed without scattering is a reference wave (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

“…The in-line lensless digital holography assumes that the geometric and spatial parameters of the reconstructed images of particles coincide with the parameters of the particles themselves. However, this condition is not always fulfilled; for example, when recording a hologram in situ, the divergence of the reference wave in the medium or the refractive index of the medium in which the particle is located may be unknown [13,28].…”

Section: Introductionmentioning

confidence: 99%

Geometric-Optical Model of Digital Holographic Particle Recording System and Features of Its Application

Dyomin,

Davydova,

Polovtsev

2024

Photonics

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The paper proposes an equivalent optical scheme of an in-line digital holographic system for particle recording and a mathematical model that establishes a one-to-one correspondence between the dimensional and spatial parameters of a digital holographic image of a particle and the imaged particle itself. The values of the model coefficients used to determine the real size and longitudinal coordinate of a particle according to its holographic image are found by calibration. The model was tested in field and laboratory conditions to calibrate a submersible digital holographic camera designed to study plankton in its habitat. It was shown that four calibration measurements are sufficient enough to determine the model coefficients, and the developed design of the submersible digital holographic camera makes it possible to perform these measurements during the recording of each hologram. In addition, this neither requires data on the refractive index of the medium with particles nor on the parameters of the optical elements of the scheme. The paper presents the results of marine experiments in the Kara Sea and the Laptev Sea, as well as in fresh water in laboratory conditions and in Lake Baikal. The error in measuring the particle size in seawater without the use of the model is 53.8%, while the error in determining their longitudinal coordinates is 79.3%. In fresh water, the same errors were 59% and 54.5%, respectively. The error in determining the position of a particle with the use of the designed mathematical model does not exceed 1.5%, and the error in determining the size is 4.8%. The model is sensitive to changes in the optical properties of the medium, so it is necessary to perform calibration in each water area, and one calibration is quite sufficient within the same water area. At the same time, the developed design of the submersible holographic camera allows, if necessary, calibration at each holographing of the medium volume with particles.

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“…Digital holography (DH) uses CCD or COMS to record holograms, and with the help of computer programming, both the amplitude and phase information of recorded objects can be reconstructed. 1,2) DH has emerged as a low-cost and compact tool for the acquisition of two or three-dimensional (3D) information in various applications, such as DH microscopy, 3,4) particle field measurements, [5][6][7][8][9][10][11] etc. One of the outstanding advantages of DH is that it can simulate the diffraction process of object waves from the hologram plane to the reconstructed image plane through numerical calculations, and achieve a digitally focused reconstructed image from a single recorded digital hologram.…”

Section: Introductionmentioning

confidence: 99%

Autofocusing in off-axis digital Fresnel holography using S-th power weighted neighborhood correlation coefficient

Zhang,

Song,

Qiu

2023

Jpn. J. Appl. Phys.

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Accurately determining the focus plane of the reconstructed image is crucial for obtaining high-quality reconstructed images in the process of digital hologram reconstruction. In this paper, a focusing evaluation function based on S-th power weighted neighborhood correlation coefficient (SPWNCC) is proposed to realize automatic focusing of the reconstructed image in off-axis digital Fresnel holography. The Fresnel transform method is utilized as the off-axis digital holographic reconstruction algorithm. Both the numerical simulation and optical experiment results are given to verify the validity of the proposed autofocusing method. The obtained focusing curve can maintain good unimodality and noise immunity performance over a large search range (approximately 800 mm). The proposed SPWNCC based focusing evaluation function has a certain guiding significance on the automatic focusing of off axis digital holographic reconstructed images of long distance recorded objects.

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Quantifying bubble size and 3D velocity in a vortex with digital holographic particle tracking velocimetry (DHPTV)

Cited by 11 publications

References 31 publications

Recent advances and applications of digital holography in multiphase reactive/nonreactive flows: a review

Recent advances and applications of digital holography in multiphase reactive/nonreactive flows: a review

Geometric-Optical Model of Digital Holographic Particle Recording System and Features of Its Application

Autofocusing in off-axis digital Fresnel holography using S-th power weighted neighborhood correlation coefficient

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