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.

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.

Prediction model to estimate the specific energy and product particle size distribution of semi-autogenous mill

2018 ◽  
Vol 233 (2) ◽  
pp. 306-313 ◽  
Author(s):  
Mohammad Razani ◽  
Abolfazl Masoumi ◽  
Masoud Rezaeizadeh ◽  
Mohammad Noaparast
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Specific Energy ◽  
Energy Levels ◽  
Operating Time ◽  
Operation Time ◽  
Specific Product ◽  
Product Particle ◽  
Drop Weight Test

The optimal use of energy for grinding of ores in mills is one of the key objectives of this study. An attempt has been made to present an experimental model for the specific energy and product particle size distribution of semi-autogenous mills for the simulating of real conditions of the particles collision. A novel semi-autogenous mill test has been suggested in order to measure the required energy for grinding. The effect of the mill’s operation time and various energy levels on the particle size distribution and feed ore hardness has been investigated with samples collected from the Sarcheshmeh Copper Complex, Kerman, Iran. The obtained results demonstrated that there is a high congruence between the experimental product particle size distribution and energy, which are predicted by the proposed novel method and ball-drop test. Using the proposed analytic relationships, the required comminution energy and semi-autogenous mill operating time to achieve the specific product particle size distribution can be estimated with high accuracy ( R2 = 0.96). Finally, the accuracy of the results was evaluated by a ball drop-weight test.

Predicting the product particle size distribution from a laboratory vertical stirred mill

2018 ◽  
Vol 129 ◽  
pp. 85-92 ◽  
Author(s):  
Danielle Rocha ◽  
Erik Spiller ◽  
Patrick Taylor ◽  
Hugh Miller
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Product Particle

Transport Methods of Determining Particle Size Distributions in Colloidal Systems

1981 ◽  
Vol 54 (4) ◽  
pp. 882-891 ◽  
Author(s):  
C. D. Shuster ◽  
J. R. Schroeder ◽  
D. McIntyre
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Size Range ◽  
Size Distributions ◽  
Rotor Speed ◽  
Colloidal Systems ◽  
Particle Size Distributions ◽  
Density Distributions ◽  
Yield Information

Abstract The two techniques examined in this work yield information about the particle size distribution of the latexes studied. The ease of measurement is improved over previous methods used on broadly distributed latexes. The TPC curves for both the natural and synthetic latexes correlate with the centrifuge curves. Both techniques show the Hevea to have larger particles than the guayule. The techniques also show SBR latex samples 1 and 2 to have larger particles than samples 3 and 4. The TPC is useful only for particles between 0.3 µm and 20 µm in size. The centrifuge can be used for any size range of particles by altering the rotor speed or eluant density. By employing the proper mathematics, these data could be easily converted from optical density distributions to particle size distributions.

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.

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