Productivity prediction method for roller press

Abstract

The invention discloses a productivity prediction method for a roller press, and the method comprises the following steps: taking an initial material with the weight of Q1, and carrying out the extrusion, so as to obtain a material cake; the material cake is scattered and then screened, the fine powder amount is T1, and the coarse powder amount m1 is equal to Q1-T1; wherein the particle size of the fine powder is not greater than Pi; the particle size of the coarse powder is greater than Pi; circularly extruding, scattering, screening and supplementing the materials for at least three times until the system reaches a balanced and stable state; and constructing a material characteristic parameter model, and inputting the handling capacity of the roller press in production into the material characteristic parameter model, so that predicted machine-hour yield data can be output. The reasonable and simple high-pressure material bed crushing test method for the roller press is established on the basis of the fragility research of the crushed material of the material bed, the test workload can be effectively reduced, reliable process parameters are provided, the problems of energy consumption prediction, equipment type selection, production regulation and control and the like of material bed crushing equipment such as the roller press are solved, and the high-pressure material bed crushing test method is suitable for the roller press. And a test method associated with actual production is established, so that the grinding efficiency is further improved.

Description

Technical Field

[0001] The invention relates to the technical field of roller presses, and in particular to a capacity prediction method for roller presses. Background Art

[0002] The laboratory-scale interlayer crushing test of material particle beds is a basic method for studying the theoretical basis of material bed crushing. At present, the methods for friability test research mainly use semi-industrial or small roller press crushing tests, particle bed ballast crushing tests, grindability and laboratory Bond work tests. Among them, the operation process of semi-industrial or small roller press crushing tests is complicated, requires a large amount of material, and is time-consuming and labor-intensive to apply; grindability and laboratory Bond work tests are a set of material grindability test analysis methods based on ball mills. For materials that are easy to grind but difficult to crush, the test error is large, and its application is limited in the basic research of material bed crushing. The particle bed piston ballast test can preliminarily simulate the material layer crushing process and predict the working parameters of equipment such as roller presses. It can be used for basic research on roller press selection and early exploratory evaluation of engineering projects.

[0003] The overall process of semi-industrial or small roller press crushing test of high-pressure roller mill is relatively complicated, with large amount of materials and long time consumption. At the same time, the test results still need certain corrections before they can be applied to industrial design, which is not suitable for the application and promotion of experimental research. The piston ballast test (fragility test) uses less materials and has a relatively simple operation process. The piston ballast test can predict the process performance of the high-pressure roller mill, but in the actual application process, it is necessary to fully demonstrate the applicability of the model and calculation empirical formula.

[0004] Although the piston ballast test is the basis for studying bed crushing, the traditional piston ballast test only completes the crushing process through one loading, which is somewhat different from the continuous crushing process of the high-pressure roller mill. Most scholars have only conducted predictive research on crushing energy consumption or product particle size through piston ballast tests, but have done little research on other key parameters required for high-pressure roller mill equipment selection and process design, and have not formed a set of intuitive and feasible test methods for bed crushing research. Summary of the invention

[0005] The purpose of the present invention is to provide a capacity prediction method for a roller press. Based on the study of the fragility of bed crushed materials, a reasonable and simple high-pressure bed crushing test method for a roller press is established, which can effectively reduce the test workload, provide reliable process parameters, and solve the problems of energy consumption prediction, equipment selection and production regulation of bed crushing equipment such as roller presses. Establishing a test method and device associated with actual production is conducive to further improving the grinding efficiency.

[0006] To achieve the above object, the present invention provides the following technical solutions: The first aspect of the present invention discloses a capacity prediction method for a roller press, comprising the following steps: S1, extrusion: take the initial material with a weight of Q1 and extrude it to obtain a cake; S2, sieving: breaking up the cake and sieving to obtain a fine powder amount of T1 and a coarse powder amount of m1=Q1-T1; wherein the particle size of the fine powder is not greater than Pi; and the particle size of the coarse powder is greater than Pi; S3, adding material: adding a raw material with a weight of T1 which is the same as the initial material to the coarse powder sieved out in step S2, and continuing extrusion; S4, cycle steps S2-S3 at least three times until the system reaches a stable equilibrium state; S5. Construct a material characteristic parameter model, input the processing volume of the roller press in production into the material characteristic parameter model, and output the predicted hourly production data.

[0007] Further solution: The material characteristic parameter model formula is as follows: ;

[0008] Where: Q is the initial material quantity, unit is t / h; T is the hourly output, unit is t / h; S a is the initial material ratio table, unit is m 2 / kg;e a is the fine powder content of the initial material, unit is %; S c It is the average ratio of all materials before the cycle extrusion balance, in m 2 / kg;e c It is the average fine powder content of all materials before the cycle extrusion equilibrium, the unit is %; S d It is the average ratio of all materials after cyclic extrusion balance, in m 2 / kg;e d It is the average fine powder content of all materials after cyclic extrusion equilibrium, in units of %; S b It is the ratio of fine powder screened out after cyclic extrusion balance, in m 2 / kg;e b It is the content of fine powder screened out after cyclic extrusion equilibrium, in %.

[0009] Further solutions: Pi values ​​are 45-200µm.

[0010] Further solution: The value of Pi is 80µm.

[0011] Further solution: In step S4, the judgment standard for the system to reach a stable state is: when the ratio of the difference between the maximum and minimum values ​​of the fine powder amount obtained three times in succession to the average value of the fine powder amount of the three times is ≤1%, the system reaches a stable state.

[0012] Further solution: The change in the specific surface area and the change in the fine powder content are measured by a fragility test, S a and e a Obtained by testing the material to be tested.

[0013] On the other hand, the present invention discloses a computer-readable storage medium, on which a plurality of acquisition classification programs are stored, and the plurality of acquisition classification programs are used to be called by a processor and execute the above-mentioned capacity prediction method for a roller press.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention innovatively provides a closed-loop process test approach for bed crushing equipment (such as a simulated roller press), which specifically designs a friability test method for specific materials based on the bed crushing mechanism, aiming to predict the production capacity of the roller press. This method not only has high prediction accuracy, but also significantly reduces the complexity of the test operation. By accurately providing key process parameters, it can effectively solve the problems of energy consumption estimation, equipment selection and regulation in the production process of bed crushing equipment such as roller presses. In addition, the present invention also establishes a test method and device system that is closely related to actual production, laying a solid foundation for further improving the grinding efficiency.

[0015] 2. The experimental analysis method introduced in the present invention closely combines production capacity prediction with production control, and is directly related to production parameters such as throughput, specific surface area or fineness, making it extremely convenient to control according to this method in the actual production process, thereby further enhancing the flexibility and efficiency of production management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the test principle for capacity prediction of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper", "lower", "left", "right", "inside", "outside", etc. are based on the directions or positional relationships shown in the accompanying drawings, or are the directions or positional relationships in which the product of the invention is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention.

[0019] See also Figure 1 This embodiment discloses a method for predicting the production capacity of a roller press, comprising the following steps: S1, extrusion: taking the initial material with a weight of Q1 and putting it into the material bed crushing device for material bed crushing and extrusion to obtain a material cake; S2, sieving: the material cake is placed in a material cake breaking device to break it up, and then placed in a vibrating screening device for screening to obtain a fine powder amount of T1 and a coarse powder amount of m1=Q1-T1; wherein the particle size of the fine powder is not greater than Pi, and the particle size of the coarse powder is greater than Pi; S3, adding material: adding a raw material of the same source as the initial material with a weight of T1 to the coarse powder sieved out in step S2, keeping the total weight of the material unchanged, and then returning to the material bed crushing device to continue extrusion; S4, repeat steps S2-S3 at least three times, the amount of fine powder in the material after continuous extrusion (T n-2 、T n-1 、T n ) is less than or equal to 1% of the ratio of the difference between the maximum and minimum values ​​T and the average value T* of three times, then the system reaches a stable equilibrium state; S5. The test ends after reaching the extrusion stable equilibrium condition, and the test data is processed: the test material quantity Q, the initial material ratio table S a , initial material fine powder content e a , All materials before cycle extrusion balance table S c , Fine powder content in all materials before cycle extrusion equilibrium c , after the cycle extrusion balance, the total material ratio table S d , fine powder content in all materials after cyclic extrusion equilibrium d , the fine powder screened out after the cycle extrusion balance is S b , the fine powder content in the fine powder screened out after cyclic extrusion balance b =100%, the coarse powder screened out after cyclic extrusion balance is S e , the fine powder content in the coarse powder screened out after the cycle extrusion balance e =0%, establish a test model for the test material quantity, fineness, specific surface, and finished product output of this material. The formula is as follows: Q.S c =T·Sa +(QT)·S e ; Q·e c =T·e a +(QT)·e e Q.S d =T·S b +(QT)·S e ; Q·e d =T·e b +(QT)·e e Subtract the upper and lower formulas from each other to get: ;

[0020] Substituting the processing volume Q* of the roller press in production into the above model, we can obtain the capacity prediction model for this material associated with the roller press production parameters based on this experimental prediction model. Among them, the specific table change ΔS=S d -S c And the change of fine powder Δe=e d -e c The S was obtained by brittleness test a and e a It is obtained by testing the material to be tested. It is only necessary to calculate the processing capacity Q* of the roller press in production and the required product fineness e a or S a Substitute the model formula to perform predictive control.

[0021] Furthermore, in step S1, the material bed crushing device is a press machine, the loading speed is 6mm / min, the end pressure is set to 900kN, the pressure is maintained for 5s after reaching the end pressure, and the inner cavity of the ballast mold is a cylinder with a diameter of 100mm. The maximum particle size of the test material particles is 5mm. The material cake breaking device is a φ305*305 test small ball mill equipped with rubber ball grinding; the vibration screening device uses a vibrating screen and a set screen to screen the material.

[0022] Furthermore, the criterion for judging whether the system reaches a stable state is: when the ratio of the difference between the maximum and minimum values ​​of the fine powder amount obtained each time to the average value of the fine powder amount obtained by multiple weighings is ≤1%, the system reaches a stable state.

[0023] In this embodiment, the initial material weight is 500g, and the Pi value is 80µm. The particle grading of the initial material is carried out according to Table 1. After the materials are mixed evenly, they are placed in the device, and the device is placed on the pressure testing machine for the material bed crushing test. After the test, the mobile pressure head is removed, the extruded material (cake) is taken out from the outer mold component, and the material is broken up and sieved with a set sieve. The fine powder ≤80µm is taken out and kept for standby, and the raw material equivalent to the weight of the fine powder taken away is added to the coarse powder of >80µm, that is, the measured material is added to the coarse powder after extrusion, and the total weight of the material to be extruded is kept unchanged, and then the extrusion cycle is repeated until the test equilibrium stability condition is reached. Finally, the fine powder ≤80µm in the material after three balanced and stable extrusions is mixed and sieved with a set sieve. The sieving results are shown in Table 2.

[0024] Table 1 Particle size distribution of the tested materials

[0025] Table 2 Fragility test data

[0026] After the seventh cycle, T*=(98.3+99.1+99.0) / 3=98.8; △T=(99.1-98.3) / 98.8=0.81%, which meets the system stability and equilibrium conditions. The following characteristic parameters are calculated (the subscript numbers represent the number of cycle extrusion): Q=500;e a =m1 / Q=e c1 =13.5%; S a =S b1 =27.4; T=(T5+T6+T7) / 3=T*=98.8; S b =(S b5 + S b6 + S b7 ) / 3=235.1;e b =100%; e c =(m5 / Q + m6 / Q + m7 / Q) / 3=(e c5 + e c6 + e c7 ) / 3=2.7%;S c =(S c5 + S c6 + S c7 ) / 3=14.4; e d =(T5 / Q + T6 / Q + T7 / Q) / 3=(e d5 + e d6 + ed7 ) / 3=19.8%;S d =(S d5 + S d6 + S d7 ) / 3=56.7; Substituting the corresponding parameters into the prediction model formula can calculate the predicted hourly output: ;

[0027] The predicted fine powder output T is consistent with the test data T*. If it is applied to production, the processing capacity Q* of the roller press in production and the required product fineness e a or S a Substitute into the model formula: The throughput of a roller press in a factory is Q*=1200t / h. If the ratio table is used as the control method, that is, the ratio table of the finished product of the roller press is controlled at S b =240m 2 / kg, then the predicted hourly output of this material is T = 1200* (56.7-14.4) / (230-27.4) = 250.54t / h. If fineness is used as the control method, the fineness control of the finished product of the roller press is e b =96.4% (i.e. 80µm sieve residue is 3.6%), then the predicted hourly output of this material is T = 1200* (19.8%-2.7) / (96.4-13.5%) = 247.53t / h. This prediction result is consistent with the 250t / h output data of this material when it is produced stably.

[0028] Although this specification is described according to implementation modes, not every implementation mode includes only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

[0029] Therefore, the above description is only a preferred embodiment of the present application and is not intended to limit the scope of implementation of the present application; that is, all equivalent changes made according to the scope of the claims of the present application are within the protection scope of the claims of the present application.

Claims

1. A method for predicting the production capacity of a roller press, characterized in that: The following steps are involved: S1, extrusion: take the initial material with a weight of Q1 and extrude it to obtain a cake; S2, sieving: breaking up the cake and sieving to obtain a fine powder amount of T1 and a coarse powder amount of m1=Q1-T1; wherein the particle size of the fine powder is not greater than Pi; and the particle size of the coarse powder is greater than Pi; S3, adding material: adding a raw material with a weight of T1 which is the same as the initial material to the coarse powder sieved out in step S2, and continuing extrusion; S4, cycle steps S2-S3 at least three times until the system reaches a stable equilibrium state; S5. Construct a material characteristic parameter model, input the processing volume of the roller press in production into the material characteristic parameter model, and output the predicted hourly production data.

2. The capacity prediction method for a roller press according to claim 1, characterized in that: The material characteristic parameter model formula is as follows: ； Where: Q is the initial material quantity, unit is t / h; T is the hourly output, unit is t / h; S a is the initial material ratio table, unit is m 2 / kg;e a is the fine powder content of the initial material, unit is %; S c It is the average ratio of all materials before the cycle extrusion balance, in m 2 / kg;e c It is the average fine powder content of all materials before the cycle extrusion equilibrium, in units of %; S d It is the average ratio of all materials after cyclic extrusion balance, in m 2 / kg;e d It is the average fine powder content of all materials after cyclic extrusion equilibrium, in units of %; S b It is the ratio of fine powder screened out after cyclic extrusion balance, in m 2 / kg;e b It is the content of fine powder screened out after cyclic extrusion equilibrium, in %.

3. The capacity prediction method for a roller press according to claim 1, characterized in that: The value of Pi is 45-200µm.

4. The capacity prediction method for a roller press according to claim 2, characterized in that: The value of Pi is 80µm.

5. The capacity prediction method for a roller press according to claim 1, characterized in that: In step S4, the criterion for judging whether the system reaches a stable state is: when the ratio of the difference between the maximum and minimum values ​​of the fine powder amount obtained three times in succession to the average value of the fine powder amount of the three times is ≤1%, the system reaches a stable state.

6. The capacity prediction method for a roller press according to claim 1, characterized in that: The change in specific surface area and the change in fine powder content are measured by a fragility test, S a and e a Obtained by testing the material to be tested.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of acquisition and classification programs, and the plurality of acquisition and classification programs are used to be called by a processor and execute the capacity prediction method for a roller press as described in any one of claims 1-6.

Images