scholarly journals Development and Validation of an Online Analyzer for Particle Size Distribution in Conveyor Belts

Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 581
Author(s):  
Claudio Leiva ◽  
Claudio Acuña ◽  
Diego Castillo
Keyword(s):  
Image Processing ◽  
Particle Size ◽  
Energy Consumption ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Large Particle ◽  
Equivalent Diameter ◽  
Online Measurement ◽  
Particle Detection ◽  
Detection Algorithms

Online measurement of particle size distribution in the crushing process is critical to reduce particle obstruction and to reduce energy consumption. Nevertheless, commercial systems to determine size distribution do not accurately identify large particles (20–250 mm), leading to particle obstruction, increasing energy consumption, and reducing equipment availability. To solve this problem, an online sensor prototype was designed, implemented, and validated in a copper ore plant. The sensor is based on 2D images and specific detection algorithms. The system consists of a camera (1024p) mounted on the conveyor belt and image processing software, which improves the detection of large particle edges. The algorithms determine the geometry of each particle, from a sequence of digital photographs. For the development of the software, noise reduction algorithms were evaluated and selected, and a routine was designed to incorporate morphological mathematics (erosion, dilation, opening, lock) and segmentation algorithms (Roberts, Prewitt, Sobel, Laplacian–Gaussian, Canny, watershed, geodesic transform). The software was implemented (in MatLab Image Processing Toolbox) based on the 3D equivalent diameter (using major and minor axes, assuming an oblate spheroid). The size distribution adjusted to the Rosin Rammler function in the major axis. To test the sensor capabilities, laboratory images were used, where the results show a precision of 5% in Rosin Rambler model fitting. To validate the large particle detection algorithms, a pilot test was implemented in a large mining company in Chile. The accuracy of large particle detection was 60% to 67% depending on the crushing stage. In conclusion, it is shown that the prototype and software allow online measurement of large particle sizes, which provides useful information for screening equipment maintenance and control of crushers’ open size setting, reducing the obstruction risk and increasing operational availability.

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.

scholarly journals Digital microscopic image application (DMIA), an automatic method for particle size distribution analysis in waste activated sludge

2021 ◽  
Author(s):  
S. Cazares ◽  
J. A. Barrios ◽  
C. Maya ◽  
G. Velásquez ◽  
M. Pérez ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Activated Sludge ◽  
Size Distribution ◽  
Particle Diameter ◽  
Diffraction Method ◽  
Laser Diffraction ◽  
Waste Activated Sludge ◽  
Equivalent Diameter ◽  
Distribution Analysis

Abstract An important physical property in environmental samples is particle size distribution. Several processes exist to measure particle diameter, including change in electrical resistance, blocking of light, the fractionation of field flow and laser diffraction (these being the most commonly used). However, their use requires expensive and complex equipment. Therefore, a Digital Microscopic Imaging Application (DMIA) method was developed adapting the algorithms used in the Helminth Egg Automatic Detector (HEAD) software coupled with a Neural Network (NN) and Bayesian algorithms. This allowed the determination of particle size distribution in samples of waste activated sludge (WAS), recirculated sludge (RCS), and pretreated sludge (PTS). The recirculation and electro-oxidation pre-treatment processes showed an effect in increasing the degree of solubilization (DS), decreasing particle size and breakage factor with ranges between 44.29%, and 31.89%. Together with a final NN calibration process, it was possible to compare results. For example, the 90th percentile of Equivalent Diameter (ED) value obtained by the DMIA with the corresponding result for the laser diffraction method. DMIA values: 228.76 μm (WAS), 111.18 μm (RCS), and 84.45 μm (PTS). DMIA processing has advantages in terms of reducing complexity, cost and time, and offers an alternative to the laser diffraction 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 Influence of grinding method and grinding intensity of corn on mill energy consumption and pellet quality

2016 ◽  
Vol 70 (1) ◽  
pp. 67-72 ◽  
Author(s):  
Djuro Vukmirovic ◽  
Jovanka Levic ◽  
Aleksandar Fistes ◽  
Radmilo Colovic ◽  
Tea Brlek ◽  
...  
Keyword(s):  
Particle Size ◽  
Energy Consumption ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Specific Energy ◽  
Specific Energy Consumption ◽  
Hammer Mill ◽  
Pellet Quality ◽  
Roller Mill ◽  
Grinding Method

In recent years there is an emerging trend of coarse grinding of cereals in production of poultry feed due to positive influence of coarse particles on poultry digestive system. Influence of grinding method (hammer mill vs. roller mill) and grinding intensity of corn (coarseness of grinding) on mill specific energy consumption and pellet quality was investigated. By decreasing grinding intensity of corn (coarser grinding), specific energy consumption of both hammer mill and roller mill was significantly decreased (p < 0.05). When comparing similar grinding intensities on hammer mill and roller mill (similar geometric mean diameter or similar particle size distribution), specific energy consumption was higher for the hammer mill. Pellet quality decreased with coarser grinding on hammer mill but, however, this effect was not observed for the roller mill. Generally, pellet quality was better when roller mill was used. It can be concluded that significant energy savings could be achieved by coarser grinding of corn before pelleting and by using roller mill instead of hammer mill. From the aspect of pellet quality, if coarser grinding is applied it is better to use roller mill, concerning that more uniform particle size distribution of corn ground on roller mill probably results in more uniform particle size distribution in pellets and this provides better pellet quality.

scholarly journals Influence of the Feed Moisture, Rotor Speed, and Blades Gap on the Performances of a Biomass Pulverization Technology

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Siyi Luo ◽  
Yangmin Zhou ◽  
Chuijie Yi ◽  
Yin Luo ◽  
Jie Fu
Keyword(s):  
Particle Size ◽  
Energy Consumption ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Specific Energy ◽  
Rotor Speed ◽  
Operational Parameters ◽  
Product Particle ◽  
Dry Conditions ◽  
Feed Moisture

Recently, a novel biomass pulverization technology was proposed by our group. In this paper, further detailed studies of this technology were carried out. The effects of feed moisture and crusher operational parameters (rotor speed and blades gap) on product particle size distribution and energy consumption were investigated. The results showed that higher rotor speed and smaller blades gap could improve the hit probability between blades and materials and enhance the impacting and grinding effects to generate finer products, however, resulting in the increase of energy consumption. Under dry conditions finer particles were much more easily achieved, and there was a tendency for the specific energy to increase with increasing feed moisture. Therefore, it is necessary for the raw biomass material to be dried before pulverization.

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