scholarly journals Mathematical Model for Calculating the Particle Size Distribution Fractal Dimension Based on Image Processing Method and Its Application

2016 ◽  
Author(s):  
Lieshu Lin ◽  
Chengbao Wu ◽  
Chuansheng Liu ◽  
Zhenghua Chen
Keyword(s):  
Mathematical Model ◽  
Image Processing ◽  
Particle Size ◽  
Fractal Dimension ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Processing Method ◽  
Image Processing Method

Study on Soil Particle Size Distribution by Digital Image Processing

2013 ◽  
Vol 788 ◽  
pp. 627-630
Author(s):  
Jian Shu Hou
Keyword(s):  
Mechanical Property ◽  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image ◽  
Traditional Method ◽  
Processing Method ◽  
Distribution Analysis ◽  
Processing Technologies

The particle size distribution of soil is very importantto its physical and mechanical property. The ordinary method of the particlesize distribution analysis is based on shaking the soil through a set of sieves.But it will be difficult to use the method while there have particles largerthan the biggest aperture of the size sieves. Then the digital image processingwas used to solve the problem here. The processing technologies, such as imageanalysis and enhancement, deblurring, edge detection were studied to analyzethe image of soil particles. Then the image processing method was used to getthe particle size distribution accurately. Though some promotions need to becarried out in the further study, it is can be found that the image processingmethod is more efficiently than the traditional method.

scholarly journals Digital Image Processing Method for Characterization of Fractures, Fragments, and Particles of Soil/Rock-Like Materials

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 815
Author(s):  
Zizi Pi ◽  
Zilong Zhou ◽  
Xibing Li ◽  
Shaofeng Wang
Keyword(s):  
Image Processing ◽  
Fractal Dimension ◽  
Size Distribution ◽  
Digital Image Processing ◽  
Digital Image ◽  
Processing Method ◽  
Equivalent Diameter ◽  
Static Compression ◽  
Image Processing Method

Natural soil and rock materials and the associated artificial materials have cracks, fractures, or contacts and possibly produce rock fragments or particles during geological, environmental, and stress conditions. Based on color gradient distribution, a digital image processing method was proposed to automatically recognize the outlines of fractures, fragments, and particles. Then, the fracture network, block size distribution, and particle size distribution were quantitatively characterized by calculating the fractal dimension and equivalent diameter distribution curve. The proposed approach includes the following steps: production of an image matrix; calculation of the gradient magnitude matrix; recognition of the outlines of fractures, fragments, or particles; and characterization of the distribution of fractures, fragments, or particles. Case studies show that the fractal dimensions of cracks in the dry mud layer, ceramic panel, and natural rock mass are 1.4332, 1.3642, and 1.5991, respectively. The equivalent diameters of fragments of red sandstone, granite, and marble produced in quasi-static compression failures are mainly distributed in the ranges of 20–40 mm, 25–65 mm, and 10–35 mm, respectively. The fractal dimension of contacts between mineral particles and the distribution of the equivalent diameters of particles in rock are 1.6381 and 0.8–3.6 mm, respectively. The proposed approach provides a computerized method to characterize quantitatively and automatically the structure characteristics of soil/rock or soil/rock-like materials. By this approach, the remote sensing for characterization can be achieved.

scholarly journals Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Zhaolin Lu ◽  
Xiaojuan Hu ◽  
Yao Lu
Keyword(s):  
Image Processing ◽  
Particle Size ◽  
Particle Morphology ◽  
Processing Method ◽  
Image Resolution ◽  
Ultrasonic Dispersion ◽  
Image Processing Method ◽  
Size And Shape ◽  
Nominal Size ◽  
Particle Size And Shape

Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis.

Experimental Study of the Mixing and Segregation Behavior in Binary Particle Fluidized Bed with Wide Size Distributions

2018 ◽  
Vol 16 (12) ◽  
Author(s):  
Runjia Liu ◽  
Yong Zang ◽  
Rui Xiao
Keyword(s):  
Image Processing ◽  
Pressure Drop ◽  
Size Distribution ◽  
Fluidized Bed ◽  
Processing Method ◽  
Size Distributions ◽  
Mixing Index ◽  
Image Processing Method ◽  
Segregation Behavior ◽  
Wide Size Distribution

Abstract Detailed understanding the particle mixing and segregation dynamic is essential in successfully designing and reasonably operating multicomponent fluidized bed. In this work, a novel fluorescent tracer technique combining image processing method has been used to investigate the mixing and segregation behavior in a binary fluidized bed with wide size distributions. The particle number percentage in each layer for different gas velocities is obtained by an image processing method. Fluidization, mixing and segregation behavior has been discussed in terms of bed pressure drop, gas velocity and mixing index. Different types of binary particle systems, including the jetsam and the flotsam-rich system, are analyzed and compared. The mixing indexes at different minimum fluidization velocities are also analyzed and compared with other work. The results show that the theoretical minimum fluidization velocity calculated from the bed pressure drop cannot represent the whole fluidization for a wide size distribution binary particle system. The effect of a wide size distribution is an inflection point in the mixing index curve. There is also a dead region in the bottom of the bed that consists of particles with large size and a low degree of sphericity. The particles in the dead region are extraordinarily difficult to fluidize and should be considered in the design of fluidized beds in industrial applications.

scholarly journals Green Preparation, Spheroidal, and Superior Property of Nano-1,3,5,7-Tetranittro-1,3,5,7-Tetrazocane

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xinlei Jia ◽  
Jingyu Wang ◽  
Conghua Hou ◽  
Yingxin Tan
Keyword(s):  
Activation Energy ◽  
Particle Size ◽  
Fractal Dimension ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Fractal Theory ◽  
Crystal Form ◽  
Decomposition Temperature ◽  
Scanning Calorimetry ◽  
The Impact

Herein, a green process for preparing nano-HMX, mechanical demulsification shearing (MDS) technology, was developed. Nano-HMX was successfully fabricated via MDS technology without using any chemical reagents, and the fabrication mechanism was proposed. Based on the “fractal theory,” the optimal shearing time for mechanical emulsification was deduced by calculating the fractal dimension of the particle size distribution. The as-prepared nano-HMX was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC). And the impact sensitivities of HMX particles were contrastively investigated. The raw HMX had a lower fractal dimension of 1.9273. The ideal shearing time was 7 h. The resultant nano-HMX possessed a particle size distribution ranging from 203.3 nm to 509.1 nm as compared to raw HMX. Nano-HMX particles were dense spherical, maintaining β-HMX crystal form. In addition, they had much lower impact sensitivity. However, the apparent activation energy as well as thermal decomposition temperature of nano-HMX particles was decreased, attributing to the reduced probability for hotspot generation. Especially when the shearing time was 7 h, the activation energy was markedly decreased.

Development of Method of Rapid Analysis of Particle Size Distribution of the Coal Charge Based on Digital Image Processing

2015 ◽  
Vol 770 ◽  
pp. 512-517 ◽  
Author(s):  
O.V. Tailakov ◽  
M.P. Makeev ◽  
A.N. Kormin ◽  
A.I. Smyslov
Keyword(s):  
Image Processing ◽  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Digital Image Processing ◽  
Fractional Composition ◽  
Rapid Analysis ◽  
Optical Images ◽  
Coal Charge ◽  
Filtration Properties

Therein algorithms of application of digital models for evaluation of porosity and fractional composition of coals based on analysis of their optical images are offered. The models allow allocating significant informational objects and estimation of structural and filtration properties of coals. The results of algorithms application on recognition of the optical images of coals are presented, the particle size distribution of coal charge and porosity of coal is defined.

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