A stochastic approach for measuring bubble size distribution via image analysis

Kracht, Willy; Emery, Xavier; Paredes, Camila

doi:10.1016/j.minpro.2013.02.016

Cited by 33 publications

(25 citation statements)

References 13 publications

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“…From a classical image analysis point of view, it is assumed that bubble clusters occur as a non-selective process and ignoring these clusters would not bias the measurement. However, recently Kracht et al (2013) showed through a stochastic approach that even if the bubble clusters are non-selective, large bubbles are more likely to be present as clusters. Thus, ignoring these clusters in the measurement would bias the estimations.…”

Section: Proposed Methodsmentioning

confidence: 99%

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An integrative image measurement technique for dense bubbly flows with a wide size distribution

Karn

Ellis

Arndt

et al. 2015

Chemical Engineering Science

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A robust image analysis approach for highly turbulent bubbly flows is proposed. It can resolve both in-focus and out-of focus bubbles over a wide size range. It can segment individual bubble from large clusters in high void fraction images. The approach was validated using both synthetic bubble images and experimental data. It allows real time analysis of two-phase flows in many industrial applications. a b s t r a c tThe measurements of bubble size distribution are ubiquitous in many industrial applications in chemical engineering. The conventional methods using image analysis to measure bubble size are limited in their robustness and applicability in highly turbulent bubbly flows. These flows usually impose significant challenges for image processing such as a wide range of bubble size distribution, spatial and temporal inhomogeneity of image background including in-focus and out-of-focus bubbles, as well as the excessive presence of bubble clusters. This article introduces a multi-level image analysis approach to detect a wide size range of bubbles and resolve bubble clusters from images obtained in a turbulent bubbly wake of a ventilated hydrofoil. The proposed approach was implemented to derive bubble size and air ventilation rate from the synthetic images and the experiments, respectively. The results show a great promise in its applicability for online monitoring of bubbly flows in a number of industrial applications.

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Section: Proposed Methodsmentioning

confidence: 99%

“…Honkanen et al, 2010;Ferreira et al, 2012;do Amaral et al, 2013;Kracht et al, 2013;Lau et al, 2013). Generally, due to the excessive coalescence and breakup of bubbles, most of the proposed techniques for bubble image processing produce considerable errors when applied to flows with high superficial gas and liquid velocities.…”

Section: Introductionmentioning

confidence: 99%

An integrative image measurement technique for dense bubbly flows with a wide size distribution

Karn

Ellis

Arndt

et al. 2015

Chemical Engineering Science

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“…Also, simple clusters of bubbles can be automatically segmented and processed using either the Watershed or the Hough Transform. Kratch et al (2013) reported that skipping bubble clusters, the BSD estimation may be biased. Therefore, complex clusters of bubbles and large bubbles must be manually processed.…”

Section: Experimental Procedures and Data Processingmentioning

confidence: 99%

Indirect estimation of bubble size using visual techniques and superficial gas rate

Vinnett

Álvarez-Silva

2015

Minerals Engineering

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“…Here, the data are assumed to be 2D binarized images, also called silhouette images (Descombes, 2011;Zafari et al, 2015), where the digitized set is composed of 0 while 1 is assigned to the image's background. A stochastic modeling approach has already been used by Kracht et al (2013) to characterize bubble images. The authors proposed a planar Boolean model of disks with a specific inference technique to retrieve the bubble size distribution.…”

Section: Introductionmentioning

confidence: 99%

A 3d Stochastic Model for Geometrical Characterization of Particles in Two-Phase Flow Applications

Langlard

Lamadie²,

Charton³

et al. 2018

Image Anal Stereol

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In this paper a new approach to geometrically model and characterize 2D silhouette images of two-phase flows is proposed. The method consists of a 3D modeling of the particles population based on some morphological and interaction assumptions. It includes the following steps. First, the main analytical properties of the proposed model – which is an adaptation of the Matérn type II model – are assessed, namely the effect of the thinning procedures on the population’s fundamental properties. Then, orthogonal projections of the model realizations are made to obtain 2D modeled images. The inference technique we propose and implement to determine the model parameters is a two-step numerical procedure: after a first guess of the parameters is defined, an optimization procedure is achieved to find the local minimum closest to the constructed initial solution. The method was validated on synthetic images, which has highlighted the efficiency of the proposed calibration procedure. Finally, the model was used to analyze real, i.e., experimentally acquired, silhouette images of calibrated polymethyl methacrylate (PMMA) particles. The population properties are correctly evaluated, even when suspensions of concentrated monodispersed and bidispersed particles are considered, hence highlighting the method’s relevance to describe the typical configurations encountered in bubbly flows and emulsions.

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A stochastic approach for measuring bubble size distribution via image analysis

Cited by 33 publications

References 13 publications

An integrative image measurement technique for dense bubbly flows with a wide size distribution

An integrative image measurement technique for dense bubbly flows with a wide size distribution

Indirect estimation of bubble size using visual techniques and superficial gas rate

A 3d Stochastic Model for Geometrical Characterization of Particles in Two-Phase Flow Applications

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