CN108918356B - Method and system for predicting particle size of mixed material after extrusion and crushing - Google Patents
Method and system for predicting particle size of mixed material after extrusion and crushing Download PDFInfo
- Publication number
- CN108918356B CN108918356B CN201810485320.9A CN201810485320A CN108918356B CN 108918356 B CN108918356 B CN 108918356B CN 201810485320 A CN201810485320 A CN 201810485320A CN 108918356 B CN108918356 B CN 108918356B
- Authority
- CN
- China
- Prior art keywords
- particle size
- size distribution
- extrusion
- crushing
- single material
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000000463 material Substances 0.000 title claims abstract description 322
- 239000002245 particle Substances 0.000 title claims abstract description 172
- 238000001125 extrusion Methods 0.000 title claims abstract description 118
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000009826 distribution Methods 0.000 claims abstract description 119
- 238000004519 manufacturing process Methods 0.000 claims abstract description 19
- 238000001514 detection method Methods 0.000 claims abstract description 11
- 239000000203 mixture Substances 0.000 claims description 11
- 238000000926 separation method Methods 0.000 claims 1
- 238000005457 optimization Methods 0.000 abstract description 3
- 239000004568 cement Substances 0.000 description 12
- 235000019738 Limestone Nutrition 0.000 description 11
- 239000006028 limestone Substances 0.000 description 11
- 238000000227 grinding Methods 0.000 description 7
- 239000002994 raw material Substances 0.000 description 6
- 239000000843 powder Substances 0.000 description 5
- 238000002474 experimental method Methods 0.000 description 3
- -1 mines Substances 0.000 description 3
- 238000010298 pulverizing process Methods 0.000 description 3
- 239000002893 slag Substances 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000010419 fine particle Substances 0.000 description 2
- 239000010440 gypsum Substances 0.000 description 2
- 229910052602 gypsum Inorganic materials 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 229910001141 Ductile iron Inorganic materials 0.000 description 1
- 229910000831 Steel Inorganic materials 0.000 description 1
- 239000011362 coarse particle Substances 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000008188 pellet Substances 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/02—Investigating particle size or size distribution
Landscapes
- Chemical & Material Sciences (AREA)
- Dispersion Chemistry (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Disintegrating Or Milling (AREA)
Abstract
The invention discloses a method and a system for predicting the particle size of a mixed material after extrusion crushing, which belong to the technical field of material crushing detection and comprise the steps of obtaining the particle size distribution of each single material in the mixed material after extrusion crushing; and predicting the particle size distribution of the extruded and crushed mixed materials according to the mass ratio of each single material in the mixed materials and the particle size distribution of each single material after extrusion crushing. The particle size distribution of the mixed material after extrusion crushing is predicted by independently detecting the particle size distribution of the single material after extrusion crushing in the mixed material and combining the formula proportion parameters of the mixed material, namely the mass percentage of each single material in the mixed material and the particle size distribution of each single material after crushing, so that a basis is provided for the operation optimization of production.
Description
Technical Field
The invention relates to the technical field of material crushing detection, in particular to a method and a system for predicting the particle size of a mixed material after extrusion crushing.
Background
The material bed crushing technology comprises a roller press, a vertical mill, a barrel roller mill, a beta mill and the like, and is widely applied to crushing procedures in the industries of cement, mines, steel slag, sintered pellets and the like with the characteristics of high efficiency and energy conservation. The particle size of the powder material processed by the method is less than 200mm, the material processed by the material bed crushing equipment generates a large amount of fine particles and is classified and selected by the powder selecting equipment, wherein the fine particles enter the next process such as the grinding of a ductile iron, and the coarse particles return to the material bed crushing equipment and are mixed with the newly fed material for further grinding. Because of the energy-saving characteristic of the material bed crushing technology, the material bed crushed products are required to be as thin as possible, so that the whole equipment is more energy-saving, the system circulation energy is required to be increased, the material returned to the equipment is thinner, the particle distribution of the mixed material entering the equipment is wider, and the average particle size is also thinner.
In practical application, the raw materials are not single varieties generally, for example, in the process of producing cement, besides cement clinker as a main raw material, materials such as limestone, gypsum, sandstone, slag and the like are required to be blended as a mixed material. Thus, the production feedstock is typically a mixture of materials, with the physical properties of the different materials varying. The particle size distribution of a single material after extrusion crushing can be easily determined through experiments, but the particle size distribution of the material after extrusion crushing can not be measured through experiments for mixed materials, particularly mixed materials with constantly adjusted and changed mixture ratio.
Disclosure of Invention
The invention aims to provide a method and a system for predicting the granularity of a mixed material after extrusion crushing, so as to predict and evaluate the granularity of the material after extrusion crushing.
In order to achieve the purpose, the invention adopts a particle size prediction method after extrusion and crushing of mixed materials, which comprises the following steps:
obtaining the particle size distribution of each single material in the mixed material after extrusion and crushing;
and predicting the particle size distribution of the extruded and crushed mixed materials according to the mass ratio of each single material in the mixed materials and the particle size distribution of each single material after extrusion crushing.
Preferably, the obtaining of the particle size distribution of each crushed material after each single material in the mixed material is crushed by extrusion includes:
respectively putting each single material in the mixed material into extrusion crushing equipment, and carrying out extrusion crushing treatment on each single material;
scattering and separating the materials obtained after extrusion and crushing;
detecting the granularity level of the scattered and separated materials through granularity detection equipment;
and (4) counting the mass of the crushed materials with different granularity levels, and calculating the mass fractions with different granularity levels.
Preferably, the extrusion force of each single material in the mixed material in the extrusion crushing equipment is the same as all extrusion forces of the mixed material in production.
Preferably, the method further comprises the following steps:
when a single material is newly added to the mixed material, acquiring the mass ratio of the newly added single material to the new mixed material;
carrying out extrusion crushing treatment on the newly added single material to obtain the particle size distribution of the crushed newly added single material;
and predicting the particle size distribution of the new mixed material after extrusion crushing according to the mass ratio of each single material in the new mixed material and the particle size distribution of each single material.
Preferably, according to the mass ratio of each single material in the mixed material and the particle size distribution of each single material after extrusion crushing, the particle size distribution of the mixed material after extrusion crushing is predicted by adopting a prediction formula, wherein the prediction formula is as follows:
wherein, PiRepresents the mass percent of the particles of the ith fraction after the extrusion crushing of the mixed material, PijRepresents the mass percent of particles of the ith fraction when the jth single material is extruded and crushed independently, SjRepresents the mass percentage of the jth single material in the mixed material, and n represents the variety number of the single material in the mixed material
On the other hand, the particle size prediction system after the mixed material is extruded and crushed comprises a particle size distribution acquisition unit and a particle size distribution prediction unit, wherein the output of the particle size distribution acquisition unit is connected with the input of the particle size distribution prediction unit;
the particle size distribution acquisition unit is used for acquiring the particle size distribution of each single material in the mixed material after extrusion and crushing;
and the particle size distribution prediction unit is used for predicting the particle size distribution of the extruded and crushed mixed materials according to the mass ratio of each single material in the mixed materials and the particle size distribution of each single material after extrusion crushing.
Preferably, the particle size distribution obtaining unit comprises an extrusion crushing device, a material scattering device, a particle size detection device and a particle size distribution statistical unit which are connected in sequence;
the extrusion crushing equipment is used for carrying out extrusion crushing treatment on each single material in the mixed material;
the material scattering equipment is used for scattering and separating the materials obtained after extrusion and crushing;
the granularity detection equipment is used for detecting the granularity level of the scattered and separated materials;
and the particle size distribution counting unit is used for counting the mass of the crushed materials with different particle size grades and calculating the mass fraction of the crushed materials with different particle size grades.
Preferably, the extrusion force of each single material in the mixed material in the extrusion crushing equipment is the same as the extrusion force of the mixed material in the production.
Preferably, when a single material is newly added to the mixed material, the particle size distribution obtaining unit is executed, and the particle size distribution obtaining unit sends the particle size distribution of the newly added single material after being crushed to the particle size distribution predicting unit;
and the particle size distribution prediction unit is used for predicting the particle size distribution of the new mixed material after extrusion crushing according to the mass ratio of each single material in the new mixed material and the particle size distribution of each single material after extrusion crushing.
Preferably, the particle size distribution prediction unit predicts the particle size distribution of the mixture after extrusion and crushing by using the following prediction formula:
wherein, PiRepresents the mass percent of the particles of the ith fraction after the extrusion crushing of the mixed material, PijRepresents the mass percent of particles of the ith fraction when the jth single material is extruded and crushed independently, SjThe mass percentage of the j-th single material in the mixed material is shown, and n represents the number of the single materials in the mixed material.
Compared with the prior art, the invention has the following technical effects: the particle size distribution of the mixed material after extrusion crushing is predicted by independently detecting the particle size distribution of the single material after extrusion crushing in the mixed material and then combining the formula proportion parameters of the mixed material, namely the mass percentage of each single material in the mixed material and the particle size distribution of each single material after crushing. Meanwhile, in the production process, when the proportion of a single material in the mixed material changes or the variety or the quantity of the single material in the mixed material changes, the particle size distribution of the material after the mixed material is extruded and crushed can be conveniently predicted, and a basis is provided for the operation optimization of production.
Drawings
The following detailed description of embodiments of the invention refers to the accompanying drawings in which:
FIG. 1 is a schematic flow chart of a method for predicting the particle size of a mixture after extrusion crushing;
FIG. 2 is a graphical representation of particle size prediction for a mixed material containing cement clinker and limestone;
FIG. 3 is a schematic diagram of a particle size prediction system after extrusion and pulverization of a mixture.
Detailed Description
To further illustrate the features of the present invention, refer to the following detailed description of the invention and the accompanying drawings. The drawings are for reference and illustration purposes only and are not intended to limit the scope of the present disclosure.
As shown in fig. 1, the embodiment discloses a method for predicting particle size of a mixture after extrusion and pulverization, which includes the following steps S1 to S2:
s1, obtaining the particle size distribution of each single material in the mixed material after extrusion and crushing;
it should be noted that, each single material in the mixed material is extruded and crushed respectively, and the particle size distribution of the extruded and crushed material of each single material and the mass percentages of the particles with different particle size levels are detected independently.
And S2, predicting the particle size distribution of the mixture after extrusion crushing according to the mass ratio of each single material in the mixture and the particle size distribution of each single material after extrusion crushing.
According to the proportion of the mixed materials and the particle size distribution of each single material after extrusion crushing in the mixed materials, the particle size distribution of the mixed materials after extrusion crushing can be predicted, the change of the particle size of the materials after crushing the mixed materials can be accurately predicted for the change of the material proportion and the type in production, and the optimization of production operation parameters is effectively guided.
More preferably, in step S1: and obtaining the particle size distribution of each crushed material after each single material of the mixed material is extruded and crushed. The method specifically comprises the following steps (1) to (4):
(1) respectively putting each single material in the mixed material into extrusion crushing equipment, and carrying out extrusion crushing treatment on each single material;
it should be noted that the extrusion crushing apparatus is a material bed type crushing apparatus, including but not limited to a roller press, a vertical mill, a roller mill, a beta mill, a pressure tester, etc.
(2) Scattering and separating each crushed material obtained after extrusion crushing;
and (4) scattering and separating each crushed material through material scattering equipment so as to facilitate material granularity classification.
(3) Detecting the granularity level of the scattered and separated materials through granularity detection equipment;
in this embodiment, the crushed materials are classified by screening through a combination screen and a top-impact type vibrating screen machine.
(4) And counting the mass of the crushed materials with different granularity levels, and calculating the mass percentage of the crushed materials with different granularity levels in the single material.
It should be noted that the mass percentages of the pulverized materials with different particle size levels are obtained by counting the mass of the pulverized materials with different particle size levels and according to the mass of the pulverized material with different particle size levels and the mass of the single material.
As a further preferred solution, the extrusion force applied to each individual material in the mixed material in the extrusion crushing apparatus is the same as all extrusion forces applied to the mixed material during production. In practical application, experimental parameters of the extrusion crushing equipment are set in advance, so that the extrusion force applied to each single material in the extrusion crushing process is the same as the extrusion force applied to the mixed material in the actual production process. The method reduces the error between the particle size distribution of each crushed material after crushing the single material and the particle size distribution of each single material in the actual production of the mixed material as much as possible, and improves the accuracy of predicting the particle size distribution of the crushed material after extruding the mixed material.
As a further preferable aspect, the method further includes:
when a single material is newly added to the mixed material, acquiring the mass ratio of the newly added single material to the new mixed material;
carrying out extrusion crushing treatment on the newly added single material to obtain the particle size distribution of the crushed newly added single material;
and predicting the particle size distribution of the new mixed material after extrusion crushing according to the mass ratio of each single material in the new mixed material and the particle size distribution of each single material.
In practical application, if a certain single material is newly added into the mixed material to form a new mixed material, the particle size distribution of the single material after extrusion crushing can be detected only by experiments, and then the particle size distribution of the new mixed material after extrusion crushing can be predicted according to the steps.
Similarly, when the proportion of a certain material in the mixed material changes, the particle size distribution of the mixed material after extrusion crushing can be predicted according to the steps only by the mass ratio of the changed single material in the mixed material.
As a further preferable scheme, in this embodiment, according to the mass ratio of each single material in the mixed material and the particle size distribution of each single material, a prediction formula is used to predict the particle size distribution of each crushed material after the mixed material is crushed by extrusion, and the prediction formula is:
wherein, PiRepresents the mass percent of the particles of the ith fraction after the extrusion crushing of the mixed material, PijRepresents the mass percent of particles of the ith fraction when the jth single material is extruded and crushed independently, SjRepresents the mass percentage of the jth single material in the mixed material, n represents the variety number of the single material in the mixed material,
representing a cumulative sum.
The embodiment is very suitable for the mixed extrusion crushing process of materials with various components, and is particularly suitable for cement grinding, wherein the cement grinding comprises various grinding raw materials, such as clinker, limestone, natural gypsum, sandstone, building waste residue, slag and the like. In the production process, the raw material formulas are different due to different product varieties; the proportions of the raw material formulations are also changing dynamically due to quality requirements or instability of the process system to produce the same product. In the embodiment, the particle size distribution of the single material during extrusion crushing is independently detected in a laboratory, and then the particle size distribution of the mixed material after extrusion crushing is calculated and predicted according to the proportion parameters of the formula. In the production process, when the proportion of the two materials in the formula changes or the varieties or the quantity of the raw materials changes, the formula can be conveniently used for calculating and predicting the particle size distribution of the extruded and crushed materials, and the production operation is optimally controlled.
The following will explain the prediction of the particle size distribution of cement powder consisting of clinker and limestone after crushing by extrusion as an example:
cement clinker and limestone are used in a factory to produce cement, and the two materials are fully mixed and then enter a roller press to be extruded and crushed. In order to analyze and predict the particle size of the extruded and crushed material, the particle size of the extruded and crushed material needs to be tested and detected firstly, and the specific process is as follows:
(1) collecting a representative clinker sample of a certain quality measuring tool;
(2) putting a clinker sample into an experimental roller press for extrusion and crushing, wherein the operation parameters of the experimental roller press are set in advance, and the pressure of a hydraulic system ensures that the pressure borne by the material is the same as the pressure borne by the material in production;
(3) breaking up the extruded and crushed material;
(4) screening and grading the materials by a combined screen and a top impact type vibrating screen machine;
(5) weighing the mass of the materials with different grain sizes, and calculating the mass fraction of the materials with different grain sizes to obtain the particle size distribution data of the cement clinker after extrusion and crushing;
(6) repeating the steps (1) to (5) on the limestone, and measuring the particle size distribution data of the limestone after extrusion and crushing;
(7) then using the formula
And calculating the particle size distribution of the mixed material. Assuming that the group 3 particle size range to be concerned in the production process is 0.5-1mm, the mass fraction P of the particle size after the extrusion and crushing of the clinker is3，10.15, the mass fraction P of the particle size after limestone is extruded and crushed3，2When the proportion of the clinker to the limestone is 75% to 25% at a certain time, the mass fraction of the materials with the granularity of 0.5-1mm after the mixed materials are extruded and crushed can be calculated and predicted by the following formula:
where denotes the multiplication number.
The particle size distribution results of the obtained cement powder consisting of clinker and limestone and cement powder consisting of clinker and limestone are shown in figure 2.
As shown in fig. 3, the embodiment discloses a particle size prediction system after extrusion and pulverization of a mixed material, which includes a particle size distribution obtaining unit 10 and a particle size distribution prediction unit 20, wherein an output of the particle size distribution obtaining unit 10 is connected with an input of the particle size distribution prediction unit 20;
a particle size distribution obtaining unit 10, configured to obtain a particle size distribution of each single material in the mixed material after extrusion and crushing;
and the particle size distribution predicting unit 20 is used for predicting the particle size distribution of the mixed material after extrusion crushing according to the mass ratio of each single material in the mixed material and the particle size distribution of each single material after extrusion crushing.
As a further preferred scheme, the particle size distribution obtaining unit 10 includes an extrusion crushing apparatus, a material scattering apparatus, a particle size detection apparatus, and a particle size distribution statistical apparatus, which are connected in sequence;
the extrusion crushing equipment is used for carrying out extrusion crushing treatment on each single material in the mixed material;
the material scattering equipment is used for scattering and separating the materials obtained after extrusion and crushing;
the granularity detection equipment is used for detecting the granularity level of the scattered and separated materials;
and the particle size distribution counting unit is used for counting the mass of the crushed materials with different particle size grades and calculating the mass fraction of the crushed materials with different particle size grades.
As a further preferred solution, the extrusion force applied to each single material in the mixed material in the extrusion crushing device is the same as all extrusion forces applied to the mixed material in the production.
As a further preferred scheme, when a single material is newly added to the mixed material, the particle size distribution obtaining unit 10 is executed, and the particle size distribution obtaining unit 10 sends the crushed particle size distribution of the newly added single material to the particle size distribution predicting unit 20;
and the particle size distribution predicting unit 20 is used for predicting the particle size distribution of each crushed material after the new mixed material is extruded and crushed according to the mass ratio of each single material in the new mixed material and the particle size distribution of each single material.
As a further preferable scheme, the particle size distribution prediction unit predicts the particle size distribution of each crushed material after the mixed material is crushed by extrusion by using the following prediction formula:
wherein, PiRepresents the mass percent of the particles of the ith fraction after the extrusion crushing of the mixed material, PijRepresents the mass percent of particles of the ith fraction when the jth single material is extruded and crushed independently, SjThe mass percentage of the j-th single material in the mixed material is shown, and n represents the number of the single materials in the mixed material.
It should be understood that the particle size distribution obtaining unit and the particle size distribution predicting unit in the particle size predicting system after extrusion-grinding of the mixed material according to the present embodiment are respectively used for executing the steps in fig. 1, and have the same effect as the particle size predicting method after extrusion-grinding of the mixed material. For simplicity, no further details are provided.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (6)
1. A particle size prediction method for a mixed material after extrusion and crushing is characterized by comprising the following steps:
obtaining the particle size distribution of each single material in the mixed material after extrusion and crushing;
predicting the particle size distribution of the extruded and crushed mixed materials according to the mass ratio of each single material in the mixed materials and the particle size distribution of each single material after extrusion crushing, wherein the prediction formula is as follows:
wherein, PiRepresents the mass percent of the particles of the ith fraction after the extrusion crushing of the mixed material, PijIndicating the ith fraction of j single material when being extruded and crushed separatelyMass percent of particles of (1), SjThe mass percentage of the jth single material in the mixed material is shown, and n is the variety number of the single material in the mixed material;
further comprising:
when a single material is newly added to the mixed material, acquiring the mass ratio of the newly added single material to the new mixed material;
carrying out extrusion crushing treatment on the newly added single material to obtain the particle size distribution of the crushed newly added single material;
and predicting the particle size distribution of the new mixed material after extrusion crushing according to the mass ratio of each single material in the new mixed material and the particle size distribution of each single material.
2. The method for predicting the particle size of the mixture after extrusion crushing according to claim 1, wherein the step of obtaining the particle size distribution of each single material in the mixture after extrusion crushing comprises the following steps:
respectively putting each single material in the mixed material into extrusion crushing equipment, and carrying out extrusion crushing treatment on each single material;
scattering and separating the materials obtained after extrusion and crushing;
detecting the granularity level of each crushed material after the crushing and separation through granularity detection equipment;
and counting the mass of the crushed materials with different granularity levels, and calculating the mass percentage of the crushed materials with different granularity levels in the single material.
3. The method of predicting the particle size of a mixed material after extrusion crushing according to claim 2, wherein the extrusion force applied to each single material in the mixed material in the extrusion crushing apparatus is the same as all extrusion forces applied to the mixed material in production.
4. A particle size prediction system after mixed material extrusion crushing is characterized by comprising: the particle size distribution prediction device comprises a particle size distribution acquisition unit and a particle size distribution prediction unit, wherein the output of the particle size distribution acquisition unit is connected with the input of the particle size distribution prediction unit;
the particle size distribution acquisition unit is used for acquiring the particle size distribution of each single material in the mixed material after extrusion and crushing;
the particle size distribution prediction unit is used for predicting the particle size distribution of the extruded and crushed mixed materials according to the mass ratio of each single material in the mixed materials and the particle size distribution of each single material after extrusion crushing;
when a single material is newly added to the mixed material, the particle size distribution obtaining unit is executed, and the particle size distribution obtaining unit sends the particle size distribution of the newly added single material after being crushed to the particle size distribution predicting unit;
the particle size distribution prediction unit is used for predicting the particle size distribution of the new mixed material after extrusion crushing according to the mass ratio of each single material in the new mixed material and the particle size distribution of each single material, and the prediction formula is as follows:
wherein, PiRepresents the mass percent of the particles of the ith fraction after the extrusion crushing of the mixed material, PijRepresents the mass percent of particles of the ith fraction when the jth single material is extruded and crushed independently, SjThe mass percentage of the j-th single material in the mixed material is shown, and n represents the number of the single materials in the mixed material.
5. The system for predicting the particle size of the mixed material after extrusion crushing according to claim 4, wherein the particle size distribution obtaining unit comprises an extrusion crushing device, a material scattering device, a particle size detection device and a particle size distribution statistical unit which are sequentially connected;
the extrusion crushing equipment is used for carrying out extrusion crushing treatment on each single material in the mixed material;
the material scattering equipment is used for scattering and separating the materials obtained after extrusion and crushing;
the granularity detection equipment is used for detecting the granularity level of the scattered and separated materials;
and the particle size distribution counting unit is used for counting the mass of the crushed materials with different particle size grades and calculating the mass fraction of the crushed materials with different particle size grades.
6. The system for predicting the particle size of a mixed material after extrusion crushing as claimed in claim 5, wherein the extrusion force of each single material in the mixed material in the extrusion crushing device is the same as the extrusion force of the mixed material in production.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810485320.9A CN108918356B (en) | 2018-05-18 | 2018-05-18 | Method and system for predicting particle size of mixed material after extrusion and crushing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810485320.9A CN108918356B (en) | 2018-05-18 | 2018-05-18 | Method and system for predicting particle size of mixed material after extrusion and crushing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108918356A CN108918356A (en) | 2018-11-30 |
| CN108918356B true CN108918356B (en) | 2021-07-09 |
Family
ID=64403813
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810485320.9A Active CN108918356B (en) | 2018-05-18 | 2018-05-18 | Method and system for predicting particle size of mixed material after extrusion and crushing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108918356B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010236989A (en) * | 2009-03-31 | 2010-10-21 | Toyota Motor Corp | Method of creating particle size distribution model, method of predicting degradation of fuel cell catalyst using the method of creating particle size distribution model, and method of controlling fuel cell using the method of predicting degradation of fuel cell catalyst |
| CN101869860A (en) * | 2010-06-04 | 2010-10-27 | 中南大学 | Granularity distribution predicting method for ore milling product of ball mill |
| CN102443695A (en) * | 2010-10-15 | 2012-05-09 | 宝山钢铁股份有限公司 | Method for determining sinter mixture granularity |
| CN102688880A (en) * | 2012-06-18 | 2012-09-26 | 武汉市天沭科技发展有限公司 | Method for efficiently recovering and reselecting steel slag |
| CN103575625A (en) * | 2013-09-29 | 2014-02-12 | 重庆大学 | Method for measuring content and particle size distribution of magnetic iron in steel slag |
| WO2017179365A1 (en) * | 2016-04-13 | 2017-10-19 | Ｊｆｅスチール株式会社 | Method for analyzing slag, and method for smelting molten iron |
| CN107657128A (en) * | 2017-10-12 | 2018-02-02 | 东南大学 | The coarse aggregate granular discrete-element method of broken state |
-
2018
- 2018-05-18 CN CN201810485320.9A patent/CN108918356B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010236989A (en) * | 2009-03-31 | 2010-10-21 | Toyota Motor Corp | Method of creating particle size distribution model, method of predicting degradation of fuel cell catalyst using the method of creating particle size distribution model, and method of controlling fuel cell using the method of predicting degradation of fuel cell catalyst |
| CN101869860A (en) * | 2010-06-04 | 2010-10-27 | 中南大学 | Granularity distribution predicting method for ore milling product of ball mill |
| CN102443695A (en) * | 2010-10-15 | 2012-05-09 | 宝山钢铁股份有限公司 | Method for determining sinter mixture granularity |
| CN102688880A (en) * | 2012-06-18 | 2012-09-26 | 武汉市天沭科技发展有限公司 | Method for efficiently recovering and reselecting steel slag |
| CN103575625A (en) * | 2013-09-29 | 2014-02-12 | 重庆大学 | Method for measuring content and particle size distribution of magnetic iron in steel slag |
| WO2017179365A1 (en) * | 2016-04-13 | 2017-10-19 | Ｊｆｅスチール株式会社 | Method for analyzing slag, and method for smelting molten iron |
| CN107657128A (en) * | 2017-10-12 | 2018-02-02 | 东南大学 | The coarse aggregate granular discrete-element method of broken state |
Non-Patent Citations (2)
| Title |
|---|
| 吕永信.用较粗的原矿筛析方法预测浮选的磨矿粒度及磨矿方案.《有色金属（选矿部分）》.1984,(第5期), * |
| 用较粗的原矿筛析方法预测浮选的磨矿粒度及磨矿方案;吕永信;《有色金属（选矿部分）》;19841231(第5期);12-17 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108918356A (en) | 2018-11-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109676795B (en) | Concrete intelligent stirring control method and system | |
| Toprak et al. | The influences and selection of grinding chemicals in cement grinding circuits | |
| Little et al. | Auto-SEM particle shape characterisation: Investigating fine grinding of UG2 ore | |
| CN103575625B (en) | Method for measuring content and particle size distribution of magnetic iron in steel slag | |
| DE102014018489A1 (en) | Device and a method for producing and analyzing a plurality of sample materials | |
| Toprak et al. | Effects of grinding aids on model parameters of a cement ball mill and an air classifier | |
| Jensen et al. | Analysis of limestone micromechanical properties by optical microscopy | |
| CN104028364A (en) | Multi-metal ore-separating and ore-grinding grading optimization test method | |
| CN114985064A (en) | Medium grading optimization method based on crushing statistical mechanics | |
| CN108918356B (en) | Method and system for predicting particle size of mixed material after extrusion and crushing | |
| Wang et al. | Grinding process within vertical roller mills: experiment and simulation | |
| Pascoe et al. | Efficiency of automated sorter performance based on particle proximity information | |
| Casagrande et al. | Study of iron ore mixtures behavior in the grinding pelletizing process | |
| CN116871015A (en) | Ore grinding process parameter optimization method and system | |
| Zuo et al. | Modelling of high voltage pulse breakage of ores | |
| Guo et al. | Effect of operating conditions on the particle size distribution and specific energy input of fine grinding in a stirred mill: Modeling cumulative undersize distribution | |
| Shahgholi et al. | Application of perfect mixing model for simulation of vertical roller mills | |
| CN112547293B (en) | Method for intelligently controlling load of rod mill | |
| Assaad et al. | Use of Locked-Cycle Protocol to Assess Cement Fineness and Properties in Laboratory Grinding Mills. | |
| CN109482288B (en) | Method for measuring particle size distribution of fine powder in material bed extrusion crushing material cake | |
| Beggio et al. | A novel method to calculate the size of representative waste samples based on particles size | |
| CN109684773B (en) | Online rapid characterization method and device for ore impact crushing property | |
| EP1737575B1 (en) | Testing method for ball mills | |
| CN115290530B (en) | Method for determining permeability coefficient of discrete material | |
| Mclvor et al. | Ball mill classification system optimization through functional performance modeling. |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |