CN109482288B - Method for measuring particle size distribution of fine powder in material bed extrusion crushing material cake - Google Patents
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- CN109482288B CN109482288B CN201811433304.1A CN201811433304A CN109482288B CN 109482288 B CN109482288 B CN 109482288B CN 201811433304 A CN201811433304 A CN 201811433304A CN 109482288 B CN109482288 B CN 109482288B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
- B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
- B02C17/00—Disintegrating by tumbling mills, i.e. mills having a container charged with the material to be disintegrated with or without special disintegrating members such as pebbles or balls
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
- B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
- B02C17/00—Disintegrating by tumbling mills, i.e. mills having a container charged with the material to be disintegrated with or without special disintegrating members such as pebbles or balls
- B02C17/10—Disintegrating by tumbling mills, i.e. mills having a container charged with the material to be disintegrated with or without special disintegrating members such as pebbles or balls with one or a few disintegrating members arranged in the container
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Abstract
The invention discloses a method for measuring the particle size distribution of fine powder in a material bed extrusion crushing material cake, which comprises the steps of dispersing the material cake by a ball mill, detecting the particle size distribution by stages by utilizing the fitting rule of the particle size change of the material ground by the ball mill, and calculating the particle size distribution in the original material cake by fitting regression on the particle size distribution detection data.
Description
Technical Field
The invention relates to the technical field of material bed extrusion crushing, in particular to a method for measuring the particle size distribution of fine powder in a material bed extrusion crushed cake.
Background
The material bed extrusion crushing technology represented by a vertical mill and a roller press is widely applied to the field of grinding due to the characteristics of high efficiency and energy conservation, and becomes standard or common grinding equipment in various industries such as cement, raw materials, steel slag, slag and the like. The material bed extrusion crushing is characterized in that extrusion force is transmitted and acted between materials, and compared with a single-particle crushing technology, the material bed extrusion crushing has the advantages of remarkably higher crushing efficiency and the highest crushing technology in the field of large-scale crushing at present. However, in both laboratory and industrial applications, it has been a problem to accurately determine the crushing efficiency of the equipment, and the fundamental reason is that the materials are contacted with each other during the crushing process of the material bed, and are usually bonded together to form a cake after being crushed by high extrusion force, and the cake formed by some material varieties or materials with certain moisture even has high compressive strength. Therefore, it is very difficult to accurately detect the amount of fines in the cake, or more accurately determine the particle distribution.
Taking a typical roller press combined grinding system as an example, a material is fed into a roller press from a weighing bin, is crushed under the extrusion action of high pressure when passing through the roller press and is combined into a firm cake, the cake is subjected to procedures of scattering and grading by a scattering and grading machine and the like to separate the thickness of the material, fine powder with required particle size is selected and sent into a ball mill for ball milling, and un-crushed particles or larger particles after crushing are returned to the weighing bin and are mixed with fresh coming materials and then fed into the roller press for extrusion. The grinding efficiency of the roller press directly determines indexes such as the output and the power consumption of a grinding system, and the grinding efficiency of the roller press needs to be evaluated, and the discharged powder cake of the roller press and materials need to be taken to carry out particle size detection and comparison. In the actual production process, an indirect evaluation mode is always adopted, and the grinding efficiency of the roller press is evaluated according to the fineness or the ratio table of the fine powder selected under the system balance state. The indirect evaluation mode is unscientific and inaccurate, and essentially reflects the working effect of the whole extrusion and powder selection system, rather than the operation effect of single equipment of a roller press. The crushing efficiency of the roller press is not directly analyzed by detecting the fineness of the fine powder in the material II and the powder cake III, and the main reasons are as follows: 1) the materials II and the powder cakes III are inconvenient to sample, one part is a chute, the other part is a material pit, and the two parts are inconvenient to sample; 2) the powder cake is a strong material cake formed by extrusion, and the content of fine powder in the material cake is difficult to accurately detect. In conclusion, the existing indirect evaluation mode is difficult to directly guide the optimization of the operation parameters of the roller press, which is also the reason that the research work related to the optimization of the operation parameters of the roller press equipment in the years is slow.
The particle size determination of the dispersed materials is easy to realize, large particles can be screened by a combined screen, and small particles can be screened by a laser particle size analyzer. However, the particle size measurement of the cake is difficult because particles of different particle sizes are bound together and cannot be directly detected by technical means. Therefore, the particle size distribution of the cake is measured by dispersing the cake in advance to separate the particles. The conventional method is to adopt the mechanical scattering method, break up the cake through mechanical exogenic action promptly, make granule alternate segregation, and current technical means usually has a shortcoming, and mechanical exogenic action does not divide friend or foe, when breaking up the cake, and partial single granule also is broken into littleer granule, has changed original particle size distribution, and the result that detects from this is natural can not be accurate, has deviated from original intention. The difficulty in detecting the level of fines in the cake is therefore how to achieve adequate dispersion of the cake without altering the particle size distribution of the material.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method for measuring the particle size distribution of fine powder in a material bed extrusion crushing material cake, which reversely deduces the particle size distribution in an initial material cake according to the grinding characteristics and the particle size change of a ball mill, wherein the particle size distribution in the initial material cake is f0’Fitting a regression equation according to the particle size distribution obtained by reverse extrapolation to obtain the particle size distribution f0 in the original material cake’The accuracy is high.
The technical scheme of the invention is as follows:
the method for measuring the particle size distribution of the fine powder in the material bed extrusion crushing material cake specifically comprises the following steps:
(1) firstly, carrying out primary dispersion on a material cake obtained after extrusion and crushing of a material bed by adopting a light external force;
(2) screening the primarily dispersed materials, and weighing the weight of each particle size section to obtain the particle size distribution f 0;
(3) putting the grinding body into a ball mill, then putting all materials into the ball mill, starting the ball mill, stopping the ball mill after running for a fixed time T, taking the materials out of the ball mill, screening the materials, weighing the weight of each particle size section, and recording the particle size distribution f1 of the materials;
(4) repeating the step (3) n-1 times, and recording the particle size distribution of all materials every time to obtain a particle size distribution f2-fn, wherein n is an integer greater than 2;
(5) taking out the particle size distribution data of the materials with the same particle size in the f1-fn, performing fitting regression, obtaining a corresponding particle size distribution fitting regression equation for each particle size material, and calculating the particle size distribution f0 of the materials with the corresponding particle size in the original material cake according to the particle size distribution fitting regression equation’。
In the step (1), the material cake is primarily dispersed by adopting a light external force, and the method comprises the following specific steps: firstly, lightly hammering the material cake to disperse the material cake into a plurality of large blocks of materials, and then rolling and lightly rolling the large blocks of materials back and forth by using a cylindrical object until large particles with the size of more than 1mm are exposed.
In the step (5), the particle size distribution data of the materials with the same particle size in the f1-fn are taken out and subjected to linear fitting regression, each particle size material obtains a corresponding particle size distribution linear fitting regression equation, and the particle size distribution f0 of the corresponding particle size material in the original material cake is calculated according to the particle size distribution linear fitting regression equation’。
N in the step (4) is 2, namely the particle size distribution f2 of all the materials after the materials are subjected to secondary ball milling and screening is recorded; the step (5) directly takes out the particle size distribution data of the materials with the same particle size in the f1 and the f2 and carries out fitting regression, each particle size material obtains a corresponding particle size distribution linear fitting regression equation, and the particle size distribution f0 of the materials with the corresponding particle size in the original material cake is calculated according to the particle size distribution linear fitting regression equation’。
The principle on which the invention is based:
the grinding industry often adopts the ball mill to grind the material, and the grinding of unit duration shows better linear relation to the specific table increase of material. Experiments show that the ball mill grinding in unit time has better linear relation to the increase of the content of fine powder, and the linear fitting degree R2Most often above 0.995. If the material cake is put into a ball mill for grinding, the grinding process has two stages:
1. breaking up and grinding. When the grinding body in the ball mill moves, the material cake is broken up, and simultaneously, the material particles are crushed and ground. The level of fines measurable in the material at this stage increased rapidly.
2. And (4) grinding the mixture simply. When the material cake in the material is fully broken up, the grinding body only plays a role in grinding and grinding single particles, and the increasing speed of fine powder in the material shows the linear rising law.
In stage 1, under the combined action of scattering and grinding, the content of fine powder in the material is rapidly increased, so that the content of fine powder in the original material can be obtained by deducting the fine powder in which the grinding action is increased. The increment of the fine powder under the grinding action of the ball mill accords with a fitting regression equation, so that the particle size distribution in the initial cake can be reversely deduced according to the grinding characteristics and the particle size change of the ball mill.
The invention has the advantages that:
the invention adopts the ball mill to disperse the material cake, utilizes the fitting rule of the particle size change of the grinding material of the ball mill to detect the particle size distribution by stages, and then carries out fitting regression on the particle size distribution detection data to calculate the particle size distribution in the original material cake.
Drawings
FIG. 1 is a graph showing the variation of particle size distribution of various particle size materials at different stages of milling in examples of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for measuring the particle size distribution of the fine powder in the material bed extrusion crushing material cake specifically comprises the following steps:
(1) firstly, placing a material cake obtained after extrusion and crushing of a material bed in a clean iron disc, lightly hammering the material cake to disperse the material cake into a plurality of large materials, and then, rolling and lightly rolling the large materials back and forth by using a cylinder until large particles with the size of more than 1mm are exposed;
(2) screening the primarily dispersed materials, and weighing the weight of each particle size section to obtain the particle size distribution f 0;
(3) putting the grinding body into a ball mill, then putting all materials into the ball mill, starting the ball mill, stopping the ball mill after running for 10 turns, taking the materials out of the ball mill, screening the materials, weighing the weight of each particle size section, and recording the particle size distribution f1 of the materials; wherein the specification of the ball mill is as followsThe rated power is 4.75kw, the rotating speed of the cylinder body is 70r/min, the grinding body is made of high-chromium cast iron, and the specification and the quantity are shown in table 1;
TABLE 1 ball mill grinding body ratio
(4) Repeating the step (3) for 4 times, and recording the particle size distribution of all materials every time to obtain particle size distribution f2-f 5; wherein the particle size distribution of f1-f5 is shown in Table 2:
TABLE 2 particle size distribution of the material ground in the ball mill (percent under sieve)
(5) Taking out the particle size distribution data of the materials with the same particle size in the f1-f5 and performing fitting regression, as shown in figure 1, giving variation lines of undersize proportion particle size distribution of the materials with the particle sizes of 0.12mm, 0.5mm and 3mm, taking undersize proportion data of the materials with the particle size of 0.5mm as an example, performing linear fitting regression on the data of f1-f5 to obtain a particle size distribution linear fitting regression equation:
y=0.5059x+55.726,R2=0.9983;
r in the above formula2For linear fitness, the content of fines in the raw cake obtained from the above, which was less than 0.5mm, was 55.726%, which is 5.636% higher than 50.09% obtained directly by sieving%。
Here we use five sets of screened data from f1-f5 to regressively calculate the data in the raw cake, and in practice we would like to be the easier and the better. We also performed linear regression using the two sets of sieve analysis data f1-f2 to obtain a fine content of 56.418% for the raw cake of less than 0.5mm, which is 0.692% different from 55.726% when fitting the five sets of data. The calculated fines contents of less than 0.12mm and less than 3mm in the raw cake differed by 0.475% and 0.185%, respectively, under two different regression approaches. From the perspective of experimental analysis, repeated experiments for many times and increased experiment duration can reduce errors, but the workload also increases by a wide margin, and two sets of data regression can be adopted to realize very small experimental errors, and the workload is reduced by a wide margin.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (4)
1. The method for measuring the particle size distribution of the fine powder in the material bed extrusion crushing material cake is characterized by comprising the following steps: the method specifically comprises the following steps:
(1) firstly, carrying out primary dispersion on a material cake obtained after extrusion and crushing of a material bed by adopting a light external force;
(2) screening the primarily dispersed materials, and weighing the weight of each particle size section to obtain the particle size distribution f 0;
(3) putting the grinding body into a ball mill, then putting all materials into the ball mill, starting the ball mill, stopping the ball mill after running for a fixed time T, taking the materials out of the ball mill, screening the materials, weighing the weight of each particle size section, and recording the particle size distribution f1 of the materials;
(4) repeating the step (3) n-1 times, and recording the particle size distribution of all materials every time to obtain a particle size distribution f2-fn, wherein n is an integer greater than 2;
(5) taking out the particle size distribution data of the material with the same particle size in the f1-fnPerforming fitting regression to obtain corresponding particle size distribution fitting regression equation for each particle size material, and calculating the particle size distribution f0 of the corresponding particle size material in the original material cake according to the particle size distribution fitting regression equation’。
2. The method for determining the particle size distribution of fine powder in a bed extrusion-pulverized cake as set forth in claim 1, wherein: in the step (1), the material cake is primarily dispersed by adopting a light external force, and the method comprises the following specific steps: firstly, lightly hammering the material cake to disperse the material cake into a plurality of large blocks of materials, and then rolling and lightly rolling the large blocks of materials back and forth by using a cylindrical object until large particles with the size of more than 1mm are exposed.
3. The method for determining the particle size distribution of fine powder in a bed extrusion-pulverized cake as set forth in claim 1, wherein: in the step (5), the particle size distribution data of the materials with the same particle size in the f1-fn are taken out and subjected to linear fitting regression, each particle size material obtains a corresponding particle size distribution linear fitting regression equation, and the particle size distribution f0 of the corresponding particle size material in the original material cake is calculated according to the particle size distribution linear fitting regression equation’。
4. The method for determining the particle size distribution of fine powder in a bed extrusion-pulverized cake as set forth in claim 1, wherein: n in the step (4) is 2, namely the particle size distribution f2 of all the materials after the materials are subjected to secondary ball milling and screening is recorded; the step (5) directly takes out the particle size distribution data of the materials with the same particle size in the f1 and the f2 and carries out fitting regression, each particle size material obtains a corresponding particle size distribution linear fitting regression equation, and the particle size distribution f0 of the materials with the corresponding particle size in the original material cake is calculated according to the particle size distribution linear fitting regression equation’。
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