Particle size plays an important role in evaluating the quality and performance of a mineral processing plant (Horiba 2014, 1). It also influences many of the properties of a particulate such as its reaction rate with some reagents.
Particle size analysis is significant in determining the quality of ore grind and in establishing the degree of liberation of the valuable materials from the gangue (Haldar 2013, 227). This is done by mineral processing plants to ensure that the desired particle size is always achieved throughout the project. It is also used to describe the efficiency of crushing and grinding processes used in mineral processing. Techniques in particle size analysis. Some techniques for particle size analysis are microscopy, sieving, …show more content…
Particle Size Analysis of Fine and Coarse Ore Samples
A standard set of sieves were cleaned by wiping the walls on the oversize side, and by brushing the screen from the undersize side. Seven sieves with meshes of: 8, 16, 30, 35, 70, 80, and 200, and an improvised pan made up of paper coated with tape and another sieve were stacked, with the pan at the bottom and sieves increasing in aperture size going up the stack. An improvised pan was made to address lack of additional pan.
The coarse sample were poured onto the top-most sieve and then covered. The stack was placed onto the Ro-Tap machine and the timer was set for 20 minutes.
After the time had elapsed, the stack of sieves was removed from the Ro-Tap machine. The weights of the ore samples retained in each sieves and pan were obtained. To ensure that the particles were fully removed from the sieves, the walls of the sieves were tapped and the undersize side of the screen was brushed to collect near-size particles. Near size particles were included in the material retained on the sieve. The materials left were weighed on the bottom-most …show more content…
Following are the GGS, RR, and 7-range histogram plots of each trial for fine and coarse ore samples.
The GGS and RR plot for fine ore sample in trial 1 give linear fits of y=0.4416x + 0.5908 and y= 1.4381x +2.6191 and an r-squared of 0.9175 and 0.9768, respectively. One can clearly say that the RR plot for the ore sample is more linear than the GGS plot. Both GGS plot and RR plot relates the cumulative undersize to the nominal aperture size while the histogram relates the frequency of the particle to nominal aperture size. A more linear plot means that it can approximate an 80% cumulative passing size better, thus using RR of fine ores to approximate is better.
The particle size distribution of the fine ore sample is wider or more spread out as one can see on the histogram
Particle size analysis is significant in determining the quality of ore grind and in establishing the degree of liberation of the valuable materials from the gangue (Haldar 2013, 227). This is done by mineral processing plants to ensure that the desired particle size is always achieved throughout the project. It is also used to describe the efficiency of crushing and grinding processes used in mineral processing. Techniques in particle size analysis. Some techniques for particle size analysis are microscopy, sieving, …show more content…
Particle Size Analysis of Fine and Coarse Ore Samples
A standard set of sieves were cleaned by wiping the walls on the oversize side, and by brushing the screen from the undersize side. Seven sieves with meshes of: 8, 16, 30, 35, 70, 80, and 200, and an improvised pan made up of paper coated with tape and another sieve were stacked, with the pan at the bottom and sieves increasing in aperture size going up the stack. An improvised pan was made to address lack of additional pan.
The coarse sample were poured onto the top-most sieve and then covered. The stack was placed onto the Ro-Tap machine and the timer was set for 20 minutes.
After the time had elapsed, the stack of sieves was removed from the Ro-Tap machine. The weights of the ore samples retained in each sieves and pan were obtained. To ensure that the particles were fully removed from the sieves, the walls of the sieves were tapped and the undersize side of the screen was brushed to collect near-size particles. Near size particles were included in the material retained on the sieve. The materials left were weighed on the bottom-most …show more content…
Following are the GGS, RR, and 7-range histogram plots of each trial for fine and coarse ore samples.
The GGS and RR plot for fine ore sample in trial 1 give linear fits of y=0.4416x + 0.5908 and y= 1.4381x +2.6191 and an r-squared of 0.9175 and 0.9768, respectively. One can clearly say that the RR plot for the ore sample is more linear than the GGS plot. Both GGS plot and RR plot relates the cumulative undersize to the nominal aperture size while the histogram relates the frequency of the particle to nominal aperture size. A more linear plot means that it can approximate an 80% cumulative passing size better, thus using RR of fine ores to approximate is better.
The particle size distribution of the fine ore sample is wider or more spread out as one can see on the histogram