Particle shape characterisation and classification using automated microscopy and shape descriptors in batch manufacture of particulate solids

Zhang, Yang; Liu, Jing J.; Zhang, Lei; Anda, J. Calderon De; Wang, Xue Z.

doi:10.1016/j.partic.2014.12.012

Cited by 13 publications

(10 citation statements)

References 20 publications

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“…Although the application of µ-CT in the geosciences was previously introduced by Ketcham and Carlson (2001) and Ketcham (2005), many investigations that analyze irregular particle shapes are still performed with 2-D approaches (Buller et al, 1990;Zhang et al, 2016;Petrak et al, 2015). So far, µ-CT studies of 3-D features have mostly been related to the characterization of volcanic rocks (Eiríksson et al, 1994;Riley et al, 2003;Shea et al, 2010;Vonlanthen et al, 2015) or spheroidal objects (Robin and Charles, 2015), and these features are usually described by means of equivalent size or shape parameters, such as roundness or aspect ratio (Little et al, 2015;Saraji and Piri, 2015).…”

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confidence: 99%

Classification and quantification of pore shapes in sandstone reservoir rocks with 3-D X-ray micro-computed tomography

et al. 2016

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Abstract. Recent years have seen a growing interest in the characterization of the pore morphologies of reservoir rocks and how the spatial organization of pore traits affects the macro behavior of rock-fluid systems. With the availability of 3-D high-resolution imaging, such as x-ray microcomputed tomography (µ-CT), the detailed quantification of particle shapes has been facilitated by progress in computer science. Here, we show how the shapes of irregular rock particles (pores) can be classified and quantified based on binary 3-D images. The methodology requires the measurement of basic 3-D particle descriptors (length, width, and thickness) and a shape classification that involves the similarity of artificial objects, which is based on main pore network detachments and 3-D sample sizes. Two main pore components were identified from the analyzed volumes: pore networks and residual pore ganglia. A watershed algorithm was applied to preserve the pore morphology after separating the main pore networks, which is essential for the pore shape characterization. The results were validated for three sandstones (S 1 , S 2 , and S 3 ) from distinct reservoirs, and most of the pore shapes were found to be plate-and cube-like, ranging from 39.49 to 50.94 % and from 58.80 to 45.18 % when the Feret caliper descriptor was investigated in a 1000 3 voxel volume. Furthermore, this study generalizes a practical way to correlate specific particle shapes, such as rods, blades, cuboids, plates, and cubes to characterize asymmetric particles of any material type with 3-D image analysis.

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confidence: 99%

Classification and quantification of pore shapes in sandstone reservoir rocks with 3-D X-ray micro-computed tomography

et al. 2016

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“…It is being used through a broad range of applications (e.g., image processing, signal analysis, data compression and optimal control [40]), for which the common objective is to extract the dominant features out of a set of data, and to build a reduced model. As shown in [22], this method is also efficient for particle shape classification.…”

Section: Introductionmentioning

confidence: 91%

“…Such simple descriptors (e.g., elongation or roundness), while providing global shape information, fail to capture the complex morphology of ballast grains (faces,edges, angularity,etc.). More advanced shape descriptors have been introduced in the last years in order to both quantify and represent the realistic geometric characteristics of granular particles before incorporating them in DEM simulations [17][18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

3D particle shape modelling and optimization through proper orthogonal decomposition

et al. 2017

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Based on Proper Orthogonal Decomposition (POD), a new method is presented in order to statistically characterize arbitrary particle shapes using an optimal choice of shape functions identified on a set of 1000 digitized railway ballast particles obtained through 3D Scan. The coefficients of the POD expansion enable a description of ballast grains with varying levels of accuracy. On exploiting the knowledge of their statistical distribution we are able, implementing an appropriate Multivariate Kernel Density Estimation (Multivariate KDE) method, to generate irregular particles with similar morphological features. The description and generation methods are validated by comparing statistical distributions of basic characteristics: surface area, volume, average radius, elongation, flatness, and aspect ratio. Using suitable geometric descriptors defining local curvatures, we identify which surface points might be regarded as forming faces. This shows that the proposed particle generation method is well suited for irregularly shaped granular materials, as a first geometric definition step, before numerical simulations of their collective mechanical properties are carried out by a Discrete Element code dealing with

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“…Signature of a 2D Projection Shape descriptors are often used to capture the shape characteristics of an object, some types have physical meanings such as aspect ratio and roundness, some are latent such as principal component analysis (PCA) based shape descriptors (Zhang and Lu, 2004;Zhang et al, 2016).…”

Section: Shape Descriptorsmentioning

confidence: 99%

Stereo imaging camera model for 3D shape reconstruction of complex crystals and estimation of facet growth kinetics

Zhang

Cai

Liu

et al. 2017

Chemical Engineering Science

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The principle that the 3D shape of crystals that grow from a solution can be characterised in real-time using stereo imaging has been demonstrated previously. It uses the 2D images of a crystal that are obtained from two or more cameras arranged in defined angles as well as a mathematical reconstruction algorithm. Here attention is given to the development of a new and more robust 3D shape reconstruction method for complicated crystal structures. The proposed stereo imaging camera model for 3D crystal shape reconstruction firstly rotates a digitised crystal in the three-dimensional space and varies the size dimensions in all face directions. At each size and orientation, 2D projections of the crystal, according to the angles between the 2D cameras, are recorded. The contour information of the 2D images is processed to calculate Fourier descriptors and radius-based signature that are stored in a database. When the stereo imaging instrument mounted on a crystalliser captures 2D images, the images are segmented to obtain the contour information and processed to obtain Fourier descriptors and radius-based information. The calculated Fourier descriptors and radius-based signature are used to find the best matching in the database. The corresponding 3D crystal shape is thus found. Potash alum crystals that each has 26 habit faces were used as a case study. The result shows that the new approach for 3D shape reconstruction is more accurate and significantly robust than previous methods. In addition, the growth rates of {111}, {110} and {100} faces were correlated with relative supersaturation to derive models of facet growth kinetics.

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Particle shape characterisation and classification using automated microscopy and shape descriptors in batch manufacture of particulate solids

Cited by 13 publications

References 20 publications

Classification and quantification of pore shapes in sandstone reservoir rocks with 3-D X-ray micro-computed tomography

Classification and quantification of pore shapes in sandstone reservoir rocks with 3-D X-ray micro-computed tomography

3D particle shape modelling and optimization through proper orthogonal decomposition

Stereo imaging camera model for 3D shape reconstruction of complex crystals and estimation of facet growth kinetics

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