CN115845991A - Method for determining steel ball grading by predicting semi-autogenous grinding hard stone crushing effect based on Tavares crushing model - Google Patents
Method for determining steel ball grading by predicting semi-autogenous grinding hard stone crushing effect based on Tavares crushing model Download PDFInfo
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- 238000012669 compression test Methods 0.000 claims abstract description 7
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- 238000005457 optimization Methods 0.000 abstract description 2
- 238000004364 calculation method Methods 0.000 description 3
- 238000013467 fragmentation Methods 0.000 description 2
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- 229910052634 enstatite Inorganic materials 0.000 description 1
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Abstract
The invention relates to a method for determining steel ball gradation by predicting a semi-autogenous grinding hard stone crushing effect based on a Tavares crushing model, and belongs to the technical field of semi-autogenous grinding optimization. Carrying out a uniaxial compression test on the raw ore; calculating the fracture energy of ores with different size fractions through an integral force-displacement curve, fitting a lognormal distribution function of the fracture energy of the ore removal, fitting a damage accumulation constant calculated by a power function of damage variables and displacement, and counting the crushing particle size distribution under different stress energy and fitting a crushing distribution function; carrying out full-grain-size screening analysis on semi-autogenous grinding feeding ores, and determining distribution conditions of ore media, hard rocks and qualified grain sizes of the feeding ores; determining a semi-autogenous grinding steel ball grading comparison scheme; relevant parameters of a Tavares crushing model are calibrated in EDEM software; calculating and setting the number of the added steel balls and the number of ore particles with different size fractions, and calibrating material attribute parameters of the barrel lining plate, the steel balls and the ore and contact parameters among the particles; setting operation parameters to start simulation; and after the simulation is finished, predicting the optimal steel ball scheme for eliminating the hard stone accumulation of the industrial production semi-autogenous mill. The invention can realize the visual analysis of the motion state of the semi-autogenous mill in the ore grinding process.
Description
Technical Field
The invention relates to a method for determining steel ball gradation by predicting a semi-autogenous grinding hard stone crushing effect based on a Tavares crushing model, and belongs to the technical field of semi-autogenous grinding optimization.
Background
The semi-autogenous mill is used as a new ore grinding device, middle-fine and crushing operations in a conventional ore grinding process are omitted, the production process and the equipment investment cost are simplified, and the semi-autogenous mill mainly depends on large ores and a small amount of steel balls (generally 8% -16%) as grinding media, so that the large ores and the steel balls are thrown down to impact and crush the ores at a reasonable filling rate. The reasonable medium grading of the semi-autogenous grinding steel ball can effectively reduce the hard rock accumulation of semi-autogenous grinding ore discharge, improve the yield of qualified grade and ensure the continuous generation capability of large ore media. The laboratory mill can not realize visual analysis of the ore grinding process, can not quantitatively analyze the ore grinding effect from the angle of energy utilization rate, improves the ore grinding efficiency of the semi-autogenous mill, and provides a method for predicting the hard rock crushing effect of different steel ball grading schemes of the semi-autogenous mill based on an EDEM Tavares crushing model.
Disclosure of Invention
Aiming at the problems and the defects in the prior art, the invention provides a method for determining the grading of steel balls by predicting the semi-autogenous grinding hard stone crushing effect based on a Tavares crushing model. The invention is realized by the following technical scheme.
A method for determining steel ball grading by predicting a semi-autogenous grinding hard stone crushing effect based on a Tavares crushing model specifically comprises the following steps:
(1) Performing uniaxial compression test measurement on the raw ore to judge the mechanical properties of hardness, brittleness and toughness of the raw ore;
(2) Carrying out full-grain-size screening analysis on semi-autogenous grinding feeding ores, and determining distribution conditions of ore media, hard rocks and qualified grain sizes of the feeding ores;
(3) Determining a semi-autogenous grinding steel ball grading comparison scheme according to the existing semi-autogenous grinding steel ball medium diameter theoretical formula and the application experience of the semi-autogenous grinding production in mines at home and abroad;
(4) A YAW-600 type hydraulic servo test system is adopted to measure a force-displacement curve, a logarithmic normal distribution function of the fracture energy is fitted, and the function expression is as follows:
in the formula (II)>
Emax is therein the upper cut-off value of the distribution, E50, σ are the median and standard deviation, respectively, of the distribution, where->
E ∞, d0 and ∞>
Is the parameter of the test data, dp is the particle size of the ore particles, ks is the rigidity of the steel (230 GPa), and a power function is fitted through damage variables under different displacementsAnd obtaining a damage accumulation constant gamma of the raw ore, wherein the damage variable expression is as follows:
in the formula, eE k To specific stress energy, E f For fracture energy, t10 values of ores under different compression energies are fitted to obtain a t10 crushing distribution function, and the expression is as follows: />
Where A and b are fitting parameters for the experimental data.
(5) Introducing a Tavares fragmentation model in EDEM software and marking relevant parameters in the model: introducing a Tavares crushing model, and setting the minimum crushing grain size of the crushing model by combining the grain size distribution of semi-autogenous grinding ore discharge in the step (2);
(6) Drawing a semi-autogenous mill cylinder liner model and an irregular ore particle model by using SOLIDWORKS software, introducing the models into EDEM software, calculating and setting the number of steel balls to be added according to the required steel ball filling rate and the bulk density of the steel balls with different sizes; calculating and setting the number of ore particles with different size fractions according to the measured granularity composition of the semi-autogenous grinding feeding ore according to the required ore filling rate and the ore specific gravity, converting the smaller size fractions into the minimum size fraction of the ore particles set by the EDEM software to reduce the calculation cost, and calibrating the material attribute parameters of the barrel lining plate, the steel ball and the ore and the contact parameters among the particles;
(7) Except for the setting in the step (6), setting a rotation speed rate, a time step, running time, a fixed-axis rotation direction and Cell-Size parameters, setting a particle factory, and starting simulation; and after the simulation is finished, comparing the particle motion states of different steel ball schemes, deriving inter-particle collision energy data and particle size distribution of a crushed product in the ore grinding process of different steel ball grading schemes, analyzing a collision energy spectrum of the hard rock and an energy ratio of impact on the hard rock, comparing the yield of the crushed product hard rock, comprehensively determining the crushing effect of the semi-autogenous grinding different steel ball grading schemes on the hard rock, and predicting the optimal steel ball scheme for eliminating hard rock accumulation of the industrial production semi-autogenous grinding machine.
And (2) measuring the uniaxial compressive strength, the elastic modulus and the Poisson ratio of the raw ore by using a uniaxial compression test in the step (1) so as to judge the hardness, the brittleness and the toughness mechanical properties of the raw ore.
And (4) determining the damage accumulation constant of the raw ore by adopting a YAW-600 type hydraulic servo test system, wherein the YAW-600 type hydraulic servo test system provides the maximum axial pressure of 600kN, the test force test range is 24 kN-600 kN, the indication precision of the test force is +/-1%, the maximum moving speed of the piston in no-load is 80mm/min, and the maximum compression space is 500mm.
And (5) using SOLIDWORKS software to draw a semi-autogenous mill cylinder liner model with a semi-autogenous mill cylinder liner model of 0.3m in the step (6).
The indices of the above formula are well known to those skilled in the art unless otherwise explained.
The invention has the beneficial effects that:
the invention can realize the visual analysis of the motion state of the semi-autogenous mill in the ore grinding process, quantitatively analyze the effect of crushing hard rocks by different steel ball grading schemes from the utilization rate of collision energy and the particle size distribution of crushed products, predict the optimal steel ball grading of the industrial production semi-autogenous mill, improve the working efficiency of the semi-autogenous mill and improve the economic benefit.
Drawings
FIG. 1 is a process flow diagram of the present invention.
Detailed Description
The invention is further described with reference to the following drawings and detailed description.
Example 1
As shown in fig. 1, the method for determining the grading of the steel balls based on the prediction of the semi-autogenous grinding hard stone crushing effect of the Tavares crushing model specifically comprises the following steps:
(1) Performing a uniaxial compression test on the raw ore to determine the uniaxial compressive strength, the elastic modulus and the Poisson ratio so as to judge the mechanical properties of hardness, brittleness and toughness of the raw ore; the uniaxial compressive strength, elastic modulus and poisson ratio obtained by specific measurement are shown in table 1:
TABLE 1 mechanical Properties of the ores
As can be seen from table 1, the average ordinary hardness of the raw ore of the present invention is 9.64 (ordinary hardness coefficient f = σ pressure/10), and the hardness is relatively high, but the soft and hard distribution is not uniform, and the whole ore belongs to medium-grade and hard ore; the average value of the elastic modulus is 8.44 multiplied by 104MPa, the ore brittleness is high, the average Poisson ratio is 0.27, and the overall toughness of the ore is also high; the ore is not easy to deform under the action of external force, and the impact crushing effect and the grinding stripping effect need to be comprehensively considered so as to improve the grinding effect.
(2) Carrying out full-grain-size screening analysis on semi-autogenous grinding feeding ores, and determining distribution conditions of ore media, hard rocks and qualified grain sizes of the feeding ores; the full size fraction size sieve analysis results are shown in table 2:
TABLE 2 semi-autogenous grinding feed grain size composition
As can be seen from Table 2, the medium yield of ore with +100mm is 35.91%, the yield of enstatite with-80 +25mm is 14.61%, and the yield of qualified fraction with-2 mm is 18.19%;
(3) Determining a semi-autogenous grinding steel ball grading comparison scheme according to the existing semi-autogenous grinding steel ball medium diameter theoretical formula and the application experience of the semi-autogenous grinding production in mines at home and abroad; the semi-autogenous grinding steel ball grading comparison scheme is determined as shown in table 3:
TABLE 3 semi-autogenous grinding steel ball grading comparison scheme
(4) Measuring a force-displacement curve by adopting a YAW-600 type hydraulic servo test system, obtaining fracture energy through integration, fitting a lognormal distribution function of the fracture energy, obtaining a t10 distribution function according to t10 values under different compression energies, and obtaining a damage accumulation constant through breakage fitting damage variables;
(5) And (3) introducing a Tavares crushing model into EDEM software, setting relevant fitting parameters of the Tavares crushing model obtained by measurement in the step (5) in the model, introducing the Tavares crushing model, and setting the minimum particle size after crushing the Tavares crushing model to be 25mm by combining the particle size distribution condition of semi-autogenous grinding ore discharge in the step (2) and reducing the calculation cost of a server. The relevant calibration parameters of the Tavares crushing model are shown in Table 4:
TABLE 4Tavares fragmentation model related calibration parameters
(6) Drawing a semi-autogenous mill cylinder liner model (the semi-autogenous mill cylinder liner model is a 0.3m semi-autogenous mill cylinder liner model) and an irregular ore particle model (drawing a simplified model of an irregular geometric body to represent various irregular ore particle models) by using SOLIDWORKS software, introducing the models into EDEM software, and calculating and setting the number of steel balls to be added according to the required steel ball filling rate (13 percent of the steel ball filling rate) and the pile densities of the steel balls with different sizes; calculating and setting the number of ore particles with different size fractions according to the measured granularity composition of the semi-autogenous grinding feeding ore according to the required ore filling rate (the ore filling rate is 17%) and the ore specific gravity (3.86 g/cm < 3 >), and converting the smaller size fractions into the minimum size fraction (-25 mm) of the ore particles set by the EDEM software to calibrate the material attribute parameters of the cylinder liner plate, the steel ball and the ore and the contact parameters among the particles in order to reduce the calculation cost;
the number of steel balls added and the number of ore particles of different size fractions are shown in Table 5.
TABLE 5 number of ore particles
The material property parameters and the particle-particle contact parameters of the shell liner, the steel ball and the ore are shown in table 6.
TABLE 6 particle contact parameters
(7) Except for the setting in the step (6), setting a rotation speed rate of 76%, a time step which is generally 1-5% of the calculated Rayleigh time step (set as 3.38 × e-8), a running time of 20s, a fixed-axis rotation direction (rotating around) and a Cell-Size parameter of 3Rmin, setting a particle factory, and starting simulation; and after the simulation is finished, comparing the particle motion states of different steel ball schemes, deriving inter-particle collision energy data and particle size distribution of a crushed product in the ore grinding process of different steel ball grading schemes, analyzing a collision energy spectrum of the hard rock and an energy ratio of impact on the hard rock, comparing the yield of the crushed product hard rock, comprehensively determining the crushing effect of the semi-autogenous grinding different steel ball grading schemes on the hard rock, and predicting the optimal steel ball scheme for eliminating hard rock accumulation of the industrial production semi-autogenous grinding machine.
In the embodiment, collision energy distribution of different steel ball grading schemes in the semi-autogenous mill grinding machine is shown in table 7, collision energy crushing percentage of different steel ball grading schemes in the semi-autogenous mill grinding machine is shown in table 8, and particle size composition after crushing of different steel ball grading schemes in the semi-autogenous mill grinding machine is shown in table 9.
TABLE 7 Collision energy distributions for different steel ball grading schemes
TABLE 8 Collision energy hard rock crushing ratio of different steel ball grading schemes
TABLE 9 composition of particle size after crushing according to different steel ball grading schemes
From tables 7 to 9, the highest collision energy and proportion of the scheme of semi-autogenous grinding of the steel ball with the diameter of 140mm to the hard rock can be seen, and the collision energy and the proportion of the scheme reach 20.93 percent; and the yield of the naughty stones of the ore grinding products after the simulated crushing is minimum and 12.94 percent, and the yield of the 25mm size fraction is maximum, so the effect of eliminating the naughty stones is best. Therefore, the optimal steel ball scheme for eliminating the hard rock accumulation of the semi-autogenous mill for the industrial production of raw ores in the embodiment is a phi 140mm steel ball scheme,
while the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes can be made without departing from the spirit and scope of the present invention.
Claims (4)
1. A method for predicting semi-autogenous grinding hard stone crushing effect and determining steel ball grading based on a Tavares crushing model is characterized by comprising the following steps:
(1) A YAW-600 type hydraulic servo test system is adopted to carry out uniaxial compression test measurement on the raw ore so as to judge the mechanical properties of hardness, brittleness and toughness of the raw ore;
(2) Carrying out uniaxial compression test on raw ore by adopting a YAW-600 type hydraulic servo test system to determine a force-displacement curve of the ore and the crushed particle size distribution of the ore under different test forces, obtaining the fracture energy by integrating the force-displacement curve, fitting and calculating a lognormal distribution function of the fracture energy of the ore, obtaining a damage accumulation constant by fitting a damage variable and a displacement power-producing function, and fitting an ore t10 crushing distribution function;
(3) Carrying out full-grain-size screening analysis on semi-autogenous grinding feeding ores, and determining distribution conditions of ore media, hard rocks and qualified grain sizes of the feeding ores;
(4) Determining a grading comparison scheme of the semi-autogenous grinding steel balls according to a medium diameter theoretical formula of the existing semi-autogenous grinding steel balls and semi-autogenous grinding production application experience;
(5) Introducing a Tavares crushing model into EDEM software, and setting the damage accumulation constant, the fracture energy lognormal distribution function and t of the raw ore measured in the step (2) in the model 10 Setting the minimum crushing granularity according to the distribution condition of the qualified granularity of the semi-autogenous grinding ore discharge in the step (3) according to relevant parameters of the crushing distribution function;
(6) Drawing a cylinder liner model and an irregular ore particle model of the semi-autogenous mill, introducing the models into EDEM software, calculating and setting the number of steel balls to be added according to the required steel ball filling rate and the bulk densities of the steel balls with different sizes; calculating and setting the number of ore particles of different size grades according to the measured granularity composition of the semi-autogenous grinding feeding according to the required ore filling rate and the ore specific gravity, and calibrating the material property parameters of the barrel lining plate, the steel ball and the ore and the contact parameters among the particles;
(7) Except for the setting in the step (6), setting a rotation speed rate, a time step, running time, a fixed-axis rotation direction and Cell-Size parameters, setting a particle factory, and starting simulation; and after the simulation is finished, comparing the particle motion states of different steel ball schemes, deriving inter-particle collision energy data and particle size distribution of a crushed product in the ore grinding process of different steel ball grading schemes, analyzing a collision energy spectrum of the hard rock and an energy ratio of impact on the hard rock, comparing the yield of the crushed product hard rock, comprehensively determining the crushing effect of the semi-autogenous grinding different steel ball grading schemes on the hard rock, and predicting the optimal steel ball scheme for eliminating hard rock accumulation of the industrial production semi-autogenous grinding machine.
2. The method for determining the grading of the steel balls based on the Tavares crushing model to predict the semi-autogenous grinding hard stone crushing effect according to claim 1, wherein the method comprises the following steps: and (2) measuring the uniaxial compression strength, the elastic modulus and the Poisson ratio of the raw ore by using a uniaxial compression test in the step (1) so as to judge the hardness, the brittleness and the toughness mechanical properties of the raw ore.
3. The method for determining the grading of the steel balls based on the Tavares crushing model to predict the semi-autogenous grinding hard stone crushing effect according to claim 1, wherein the method comprises the following steps: in the step (2), a YAW-600 type hydraulic servo test system is adopted to measure a force-displacement curve of raw ore, fracture energy is calculated through force-displacement curve integration, a power function curve of damage variable and displacement is fitted, a damage accumulation constant is obtained, a t10 distribution function is fitted according to ore crushing granularity under different compression energy, the YAW-600 type hydraulic servo test system provides the maximum axial pressure of 600kN, the test force test range is 24 kN-600 kN, the test force indication precision is +/-1%, the piston no-load maximum moving speed is 80mm/min, and the maximum compression space is 500mm.
4. The method for determining the grading of the steel balls based on the Tavares crushing model to predict the semi-autogenous grinding hard stone crushing effect according to claim 1, wherein the method comprises the following steps: and (5) drawing a semi-autogenous mill cylinder liner model with the semi-autogenous mill cylinder liner model being 0.3m in the step (6).
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117920446A (en) * | 2024-03-21 | 2024-04-26 | 昆明理工大学 | Semi-autogenous mill running state optimization method based on digital twin |
| CN117920446B (en) * | 2024-03-21 | 2024-05-31 | 昆明理工大学 | Semi-autogenous mill running state optimization method based on digital twin |
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