A method for capacity prediction for a roll press

Abstract

The application discloses a kind of productivity prediction methods for roller press, comprising the following steps: taking the weight Q1 initial material is extruded, and cake is obtained;After cake is scattered, screening is obtained, and the amount of fine powder T1, coarse powder amount m1=Q1-T1;Wherein, the particle size of fine powder is not more than Pi;The particle size of coarse powder is greater than Pi;Circulating extrusion, scattering, screening, at least three times, until system reaches balanced steady state;Material characteristic parameter model is constructed, and the throughput of roller press in production is input into the material characteristic parameter model, and the predicted hourly output data can be output.The present application is based on the friability of bed material crushing material, establishes a reasonable and simple high-pressure bed material crushing test method for roller press, which can effectively reduce the test workload, provide reliable process parameters, solve the energy consumption prediction, equipment selection and production control problems of bed material crushing equipment such as roller press, and establish the test method associated with actual production, which is beneficial to further improve the grinding efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of roller press, in particular to a production capacity prediction method for roller press. BACKGROUND

[0002] The inter-particle bed crushing test in laboratory scale is the basic method for studying the crushing theory of the material bed. At present, the methods for studying the friability mainly include semi-industrial or small-scale roller press crushing test, particle bed pressure loading crushing test, grindability and laboratory Bond work test. Among them, the semi-industrial or small-scale roller press crushing test has a complicated operation process, needs more material, and is time-consuming and laborious in application; the grindability and laboratory Bond work test is a set of material grindability test analysis method based on the ball mill, and has a large test error for materials that are easy to grind and difficult to crush, and is limited in application in the basic research of the material bed crushing. The particle bed piston pressure loading test can preliminarily simulate the material layer crushing process, predict the working parameters of the roller press and other equipment, and be used for the basic research and exploratory evaluation of the engineering project in the early stage.

[0003] The semi-industrial or small-scale roller press crushing test of the high-pressure roller mill has a complicated overall process, needs a large amount of material, and takes a long time, and at the same time, the test result still needs to be corrected before being applied to the industrial design, and is not suitable for the application and promotion of the test research. The particle bed piston pressure loading test (friability test) needs less material and has a relatively simple operation process, and the piston pressure loading test can predict the process performance of the high-pressure roller mill, but in the actual application process, the applicability of the model and the calculation empirical formula needs to be fully demonstrated.

[0004] Although the piston pressure loading test is the basis for studying the material bed crushing, the traditional piston pressure loading test only completes the crushing process through one loading, and still has some differences from the continuous crushing process of the high-pressure roller mill. Most scholars only predict the crushing energy consumption or product particle size through the piston pressure loading test, and few of them study other key parameters required for the selection and process design of the high-pressure roller mill, and a set of intuitive and feasible test method for the material bed crushing research has not been formed. SUMMARY

[0005] The present application aims to provide a production capacity prediction method for roller press, based on the friability research of the material bed crushing material, a reasonable and simple high-pressure material bed crushing test method for the roller press is established, which can effectively reduce the test workload, provide reliable process parameters, solve the problems of energy consumption prediction, equipment selection and production control of the material bed crushing equipment such as roller press, and establish the test method and device associated with the actual production, which is beneficial to further improve the grinding efficiency.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0007] The first aspect of the present application discloses a capacity prediction method for a roller press, comprising the following steps:

[0008] S1, extrusion: taking initial material with a weight of Q1 for extrusion to obtain a cake;

[0009] S2, sieve analysis: sieving the cake after being broken up 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; the particle size of the coarse powder is greater than Pi;

[0010] S3, supplementing: supplementing the coarse powder sieved in step S2 with raw material with a weight of T1 which is homologous to the initial material, and continuing to extrude;

[0011] S4, repeating steps S2-S3 at least three times until the system reaches a balanced stable state, and the judgment standard for the system reaching a stable state is that when the difference between the maximum value and the minimum value of the fine powder amount obtained continuously for three times is less than or equal to 1% of the average value of the fine powder amount for the three times, the system reaches a stable state;

[0012] S5, constructing a material characteristic parameter model, inputting the processing capacity of the roller press in production into the material characteristic parameter model, and outputting the predicted hourly output data, and the formula of the material characteristic parameter model is as follows:

[0013] ;

[0014] In the formula: Q is the initial material amount, the unit is t / h; T is the hourly output, the unit is t / h; S a is the specific surface area of the initial material, the unit is m 2 / kg; e a is the fine powder content of the initial material, the unit is %; S c is the average specific surface area of all materials before the balance of the circulating extrusion, the unit is m 2 / kg; e c is the average fine powder content of all materials before the balance of the circulating extrusion, the unit is %; S d is the average specific surface area of all materials after the balance of the circulating extrusion, the unit is m 2 / kg; e d is the average fine powder content of all materials after the balance of the circulating extrusion, the unit is %; S b is the specific surface area of the fine powder sieved after the balance of the circulating extrusion, the unit is m 2 / kg; e b is the fine powder content of the fine powder sieved after the balance of the circulating extrusion, the unit is %.

[0015] Further scheme: the value of Pi is 45-200µm.

[0016] Further solution: the value of Pi is 80 µm.

[0017] Further solution: the specific surface variation and the fine powder content variation are measured by the friability test, S a and e a Obtained by testing the material to be measured.

[0018] In another aspect, the present application discloses a computer readable storage medium, wherein a plurality of acquisition classification programs are stored on the computer readable storage medium, and the plurality of acquisition classification programs are used to be called by a processor and execute the method for predicting the capacity of a roller press as described above.

[0019] Compared with the prior art, the present application has the beneficial effects that:

[0020] 1. The present application provides a closed-circuit process test approach for a material bed crushing device (such as a simulated roller press), which particularly designs a friability test method for specific materials based on the material bed crushing mechanism, aiming to predict the capacity of a roller press. This method not only has high prediction accuracy, but also significantly reduces the complexity of test operation. By accurately providing key process parameters, it can effectively solve the problems of energy consumption estimation, equipment selection and production process control of the material bed crushing device such as a roller press. In addition, the present application also establishes a test method and device system closely related to actual production, which lays a solid foundation for further improving the grinding efficiency.

[0021] 2. The test analysis method introduced in the present application closely combines capacity prediction with production control and directly relates to production parameters such as throughput, specific surface area or fineness, making it extremely convenient to control according to this method in actual production process, thereby further enhancing the flexibility and efficiency of production management. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 Test principle diagram for capacity prediction of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0024] In the description of the present application, it should be noted that the terms "upper", "lower", "left", "right", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship commonly used when the product of the present application is used, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0025] Referring to Figure 1 The embodiment discloses a capacity prediction method of a roller press, comprising the following steps:

[0026] S1, extrusion: the initial material with a weight of Q1 is put into a bed crushing device to perform bed crushing and extrusion, and a cake is obtained;

[0027] S2, screening: the cake is put into a cake breaking device to break, and then is put into a vibrating screen device to perform screening, so that a fine powder amount T1 is obtained, and a coarse powder amount 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;

[0028] S3, supplementing: the coarse powder screened in step S2 is supplemented with raw material with a weight of T1 which is homologous to the initial material, so that the total weight of the material is kept unchanged, and then the bed crushing device is returned to continue extrusion;

[0029] S4, the steps S2-S3 are repeated at least three times, and the difference T between the maximum and minimum values of the fine powder amount (T n-2 , T n-1 , T n ) in the material after continuous extrusion and the average value T* of three times is ≤1%, so that the system reaches a balanced stable state;

[0030] S5, after the extrusion stable balance condition is reached, the test is ended, and the test data is processed: the material amount Q, the specific surface S a of the initial material, the fine powder content e a of the initial material, the average specific surface S c of all the materials before the cycle extrusion balance, the average fine powder content e c of all the materials before the cycle extrusion balance, the average specific surface S d of all the materials after the cycle extrusion balance, the average fine powder content e d of all the materials after the cycle extrusion balance, the specific surface S b of the fine powder screened after the cycle extrusion balance, the fine powder content e b of the fine powder screened after the cycle extrusion balance, the specific surface S e of the coarse powder screened after the cycle extrusion balance, and the fine powder content e e= 0%, the test model of the test amount, fineness, specific surface area, and finished product yield of the material is established, and the formula is as follows:

[0031] Q·S c = T·S a + (Q-T)·S e ; Q·e c = T·e a + (Q-T)·e e

[0032] Q·S d = T·S b + (Q-T)·S e ; Q·e d = T·e b + (Q-T)·e e

[0033] The upper and lower formulas are subtracted from each other to obtain:

[0034] ;

[0035] The processing capacity Q* of the roller press in production is substituted into the above model to obtain the production capacity prediction model associated with the production parameters of the roller press for the material based on the prediction model of the test. Among them, the specific surface area change ΔS = S d - S c and the fine powder change Δe = e d - e c S a and e a are obtained through the friability test. Through the test of the material to be tested, only the processing capacity Q* of the roller press in production and the required product fineness e a or S a are substituted into the model formula to perform prediction and control.

[0036] Further, in step S1, the material bed crushing device is a press, the loading speed is 6 mm / min, the final pressure is set to 900 kN, and the pressure is maintained for 5 s after reaching the final pressure. The pressure-loaded mold cavity is a cylinder with a diameter of 100 mm. The maximum particle size of the test material particles is 5 mm. The cake breaking device is a φ305*305 test ball mill equipped with a rubber ball grinder; the vibration screening device screens the material using a vibrating screen machine and a screen sleeve.

[0037] Further, the judgment standard for the system to reach a stable state is that when the difference between the maximum value and the minimum value of the fine powder obtained each time and the average value of the fine powder obtained by weighing multiple times is ≤1%, the system reaches a stable state.

[0038] In this example, the initial material weight is 500 g, and Pi is 80 pm. The particle size distribution of the initial material is according to Table 1, the material is mixed uniformly and placed in the device, and the device is placed on the pressure testing machine for bed crushing test. After the test, the moving pressure head is removed, the extruded material (cake) is taken out from the outer mold part, scattered and sieved with a nested sieve, the fine powder ≤80 pm is taken out for sample, and the same weight of raw material as the removed fine powder is added to the coarse powder >80 pm, that is, the measured material is added to the extruded coarse powder to keep the total weight of the material to be extruded unchanged, and then the cycle extrusion is repeated until the test balance stable condition is reached. Finally, the fine powder ≤80 pm in the material after three balance stable extrusions is mixed uniformly and sieved with a nested sieve, and the sieving results are shown in Table 2.

[0039] Table 1 Particle size distribution of the material to be tested

[0040]

[0041] Table 2 Fragility test data

[0042]

[0043] When the cycle is the 7th time, T*=(98.3+99.1+99.0) / 3=98.8; AT=(99.1-98.3) / 98.8=0.81%, which meets the system stable balance condition, and the following characteristic parameters are calculated (the subscript number represents the cycle extrusion number):

[0044] Q=500;e a =m1 / Q=e c1 =13.5%; S a =S c1 =27.4;

[0045] T=(T5+T6+T7) / 3=T*=98.8; S b =(S b5 + S b6 + S b7 ) / 3=235.1;e b =100%;

[0046] 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;

[0047] e d =(T5 / Q + T6 / Q + T7 / Q) / 3=(e d5 + e d6 + e d7 ) / 3 = 19.8%; S d =(S d5 + S d6 + S d7 ) / 3 = 56.7;

[0048] Substituting the relevant parameters into the prediction model formula will allow you to calculate the predicted hourly output:

[0049] ;

[0050]

[0051] The predicted fine powder yield T is in excellent agreement with the experimental data T*. However, if applied to production, the processing capacity Q* of the roller press and the required product fineness e need to be considered. a or S a Substitute into the model formula:

[0052] A factory's roller press has a throughput of Q* = 1200 t / h. If a ratio table is used as the control method, that is, the roller press's finished product ratio table is controlled at S... b =240m 2 If the weight is / kg, then the predicted hourly output for producing this material is T = 1200 * (56.7 - 14.4) / (230 - 27.4) = 250.54 t / h. If fineness is used as the control method, the fineness control e of the finished product from the roller press... b =96.4% (i.e., 3.6% residue on the 80µm sieve), then the predicted hourly output for producing this material is T = 1200 * (19.8% - 2.7) / (96.4 - 13.5%) = 247.53 t / h. This predicted result is in good agreement with the stable output of 250 t / h for producing this material.

[0053] Although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

[0054] Therefore, the above description is only a preferred embodiment of this application and is not intended to limit the scope of this application; that is, all equivalent modifications made in accordance with the scope of the claims of this application shall be within the protection scope of the claims of this application.

Claims

1. A capacity prediction method for a roll press, characterized by, The method comprises the following steps: S1, extrusion: taking initial material with a weight of Q1 to perform extrusion to obtain a cake; S2, screening: screening the cake after being broken to obtain fine powder with a quantity of T1 and coarse powder with a quantity of m1=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; S3, supplementing: supplementing the coarse powder screened in step S2 with raw material with a weight of T1 which is homologous to the initial material, and continuing to extrude; S4, repeating steps S2-S3 for at least three times until the system reaches a stable state, and the judgment standard for the system reaching the stable state is that when the difference between the maximum value and the minimum value of the fine powder quantity obtained for three times is less than or equal to 1% of the average value of the fine powder quantity for the three times, the system reaches the stable state; S5, constructing a material characteristic parameter model, inputting the processing capacity of the roller press in production into the material characteristic parameter model to output predicted hourly output data, and the formula of the material characteristic parameter model is as follows: ； wherein: Q is the initial material quantity, in t / h; T is the hourly production, in t / h; S a is the initial material specific surface, in m 2 / kg; e a is the initial material fine content, in %; S c is the average specific surface of the total material before the extrusion cycle balance, in m 2 / kg; e c is the average fine content of the total material before the extrusion cycle balance, in %; S d is the average specific surface of the total material after the extrusion cycle balance, in m 2 / kg; e d is the average fine content of the total material after the extrusion cycle balance, in %; S b is the specific surface of the fine powder screened after the extrusion cycle balance, in m 2 / kg; e b is the fine content in the fine powder screened after the extrusion cycle balance, in %.

2. The capacity prediction method for a roll press according to claim 1, characterized by, The value of Pi is 45-200µm.

3. The capacity prediction method for a roll press according to claim 2, characterized by, The value of Pi is 80µm.

4. The capacity prediction method for a roll press according to claim 1, characterized by, Specific surface change ΔS = S d -S c and fine powder content change Δe = e d -e c S a and e a are obtained by testing the material under test.

5. A computer readable storage medium, characterized in that, The computer readable storage medium stores a plurality of acquisition classification programs, and the plurality of acquisition classification programs are used to be called and executed by the processor to perform the production capacity prediction method for the roller press according to any one of claims 1-4.

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