Method and system for predicting particle size distribution of sintered mixture after granulation

Abstract

The invention provides a method and a system for predicting particle size distribution of a sintered mixture after granulation. According to the method, raw materials are divided into fine particles smaller than a preset threshold value and coarse particles larger than the threshold value; when the total weight percentage of the fine particles meets a preset condition, the method calculates the growth volume ratio of the particles based on the particle size distribution and proportion of the raw materials and a group of physical parameters including apparent density, bulk density and fine particle adhesion ratio. And finally, predicting the target particle size of the coarse particles based on the V%, and determining the final particle size distribution in combination with the amount of the non-adhered fine particles. According to the method, key parameters such as the adhesion ratio reflecting the internal balling performance of the raw materials are introduced, a simple and accurate prediction model is constructed, prospective regulation and control of the granulation granularity can be achieved in the batching stage without complex data training, and the method has important industrial application value.

Description

Technical Field

[0001] This invention relates to the field of sintering and pelletizing technology in iron and steel metallurgy, and in particular to a method and system for predicting the particle size distribution of sintered mixtures after a pelletizing process. Background Technology

[0002] Granulation of sintering mixes is a crucial step in the entire sintering process, as the particle size distribution of the granulated product affects the permeability of the bed and the yield and quality of the sinter. Predicting granulation particle size using raw material particle size and distribution, as well as operational parameters during granulation, is of great significance for the sustainable and efficient development of the sintering industry. Domestic and international models for predicting granulation particle size are divided into mathematical models and physical models.

[0003] The particle size distribution of the sintering mixture is a key factor affecting the permeability of the sintering process, thus determining the yield and quality of the sinter. To achieve effective control and optimization of the granulation process, various particle size prediction methods have been proposed in existing technologies, which can be broadly categorized as follows:

[0004] The first type of method is based on experimental empirical formulas combined with intelligent control algorithms. For example, the method disclosed by Guo Xiangjun et al. in the article "Particle Size Optimization of Sintering Mixtures Based on Fuzzy PID Control" (Automation Expo, 2017, 34(6)) predicts and optimizes the average particle size of the mixture by applying the principle of fuzzy control based on empirical formulas obtained from experimental research. Although this method can optimize the average particle size to a certain extent, it can only obtain a single index of average particle size and cannot provide complete particle size distribution information, while the particle size distribution has a more significant impact on the sintering permeability.

[0005] The second type of method is based on training a neural network model with a large amount of data. For example, Li Yong et al. published "PSO-BP Control Algorithm for Granulation Process Based on Particle Size Distribution Evaluation and Optimization" (Acta Automatica Sinica, 2012, 38(6)). They established a BP neural network evaluation model based on historical data of sintering production and experimental data of mixture screening, and then combined it with particle swarm optimization (PSO) to calculate the optimization value. Although this method can predict particle size distribution, it relies heavily on a large amount of high-quality historical data and sample training. Moreover, the algorithm structure is complex, the amount of computation is huge, and it requires high hardware computing power and professional level of operators. Similarly, Jiang Xiaoguang used neural network tools to train data in his research "Research on Prediction Model of Granulation Effect of Sintering Mixture" (Master's Thesis of Northeastern University, 2020) to predict the content of specific particle sizes (such as 3-8mm). However, his system for predicting particle size distribution is not yet perfect, and it also faces the problem of complex process and the need for strong computer professional skills.

[0006] The third type of method is based on physical models constructed from the granulation mechanism. For example, physical models centered on the granulation and pelletizing mechanism, such as the set equilibrium model discussed by Xing Bijun in "A Number Group Set Equilibrium Model for Predicting Particle Size Distribution" (Iron and Steel Research, 2007, 35(2)) and Yang Xiaoping in "Comparison of Particle Size Prediction Models for Iron-Bearing Raw Materials" (Chinese Journal of Materials and Metallurgy, 2007, 6(3)), simulate the particle growth process by simplifying the adhesion process into a mathematical model. Due to the significant simplification of the actual granulation process, the prediction accuracy of these models is often not high. At the same time, establishing and simulating such models requires high modeling expertise from the user, and the process is complex and inefficient.

[0007] Furthermore, the "Particle Size Distribution and Prediction Model of Granulation" proposed by Dai Shuhua et al. (Iron and Steel, 2010, 45(6)) has certain similarities with the concept of this invention. Its model is based on two major assumptions: (1) the growth mechanism of granulation is controlled by the stratification mechanism, that is, the finer particles adhere to the surface of the coarser core particles, and other growth mechanisms are ignored; (2) the thickness of the stratification layer is proportional to the particle size of the core particles. The model proposed in this literature considers the influence of moisture and original particle size, but fails to fully consider the influence of the differences in the granulation performance (adhesion ability) of different raw materials on the granulation effect, which limits the universality and accuracy of the prediction model.

[0008] In summary, existing technologies lack a method that is simple to operate, does not rely on large-scale data training, and can fully consider the inherent physical properties of raw materials, thereby accurately predicting the particle size distribution after granulation during the batching stage. Summary of the Invention

[0009] The present invention aims to solve the problems existing in the above-mentioned background technology, and provides a method, system and storage medium for predicting the particle size distribution of sintered mixture after granulation that is simple in model, convenient in operation and accurate in prediction.

[0010] To achieve the above objectives, in a first aspect, the present invention provides a method for predicting the particle size distribution of a sintered mixture after granulation, comprising the following steps: obtaining an initial particle size distribution of the sintered mixture composed of n single raw materials in their respective proportions, wherein the initial particle size distribution divides the raw material particles into fine particles smaller than a first preset particle size threshold and coarse particles larger than the first preset particle size threshold; determining whether the total weight percentage of all fine particles in the sintered mixture is not greater than a preset aggregation threshold; if the determination result is yes, calculating a particle growth volume ratio based on a set of physical parameters pre-determined for each single raw material; predicting the target particle size of the coarse particles after granulation based on the particle growth volume ratio and the initial particle size of the coarse particles; and determining the final particle size distribution of the sintered mixture after granulation based on the target particle size and the weight percentage of fine particles that are not adhered after granulation.

[0011] Preferably, the set of physical parameters includes at least: the apparent density of each individual raw material, the bulk density of the fine particles of each individual raw material in the densest state, and the adhesion ratio of the fine particles of each individual raw material during granulation.

[0012] Preferably, the calculated particle growth volume ratio V % The steps include:

[0013] Based on the respective proportions Pi of the n single raw materials and their corresponding physical parameters, the weighted average apparent density ρ, the weighted average densest bulk density Vm of the fine particles, and the weighted average adhesion ratio Ad of the fine particles are calculated.

[0014] The particle growth volume ratio V is determined based on the following logical relationship. % The particle growth volume ratio V % W, the total weight percentage of all fine particles in the sintered mixture fine The weighted average adhesion ratio Ad, the weighted average densest bulk density Vm, and the weighted average apparent density ρ are directly proportional to the product of these components and inversely proportional to the total weight percentage of all coarse particles in the sintered mixture.

[0015] Preferably, the particle growth volume ratio V % Calculate using the following formula: V % =W fine *Ad*Vm*ρ / (100-W fine ) / 100.

[0016] Preferably, the step of predicting the target particle size DL of coarse particles after granulation is calculated using the following formula: DL = (1 + V) / ( ... % )^(1 / 3)×D;where D is the initial particle size of the coarse particles.

[0017] Preferably, the step of determining the final particle size distribution further includes calculating the weight percentage of fine particles that were not adhered after granulation.

[0018] Preferably, the calculation steps for the weight percentage of the unadheded fine particles are as follows: for each individual raw material, multiply its fine particle weight percentage, blending ratio, and (100 - adhesion ratio) to obtain the contribution of the unadheded fine particles of that raw material; then sum the contribution of the unadheded fine particles of all individual raw materials.

[0019] Preferably, the first preset particle size threshold is 0.5 mm, and the preset aggregation threshold is 40%.

[0020] In a second aspect, the present invention provides a system for predicting the particle size distribution of sintered mixtures after granulation, comprising:

[0021] The data acquisition unit is used to acquire the initial particle size distribution of a sintering mixture composed of n kinds of single raw materials in their respective proportions, and a set of physical parameters pre-determined for each kind of single raw material; the initial particle size distribution divides the raw material particles into fine particles smaller than a first preset particle size threshold and coarse particles larger than the first preset particle size threshold.

[0022] The processing unit, connected to the data acquisition unit, is used to determine whether the total weight percentage of all fine particles in the sintering mixture is not greater than a preset aggregation threshold. If the determination result is yes, a particle growth volume ratio is calculated based on the set of physical parameters, and the target particle size of the coarse particles after granulation is predicted based on the particle growth volume ratio and the initial particle size of the coarse particles.

[0023] The prediction result generation unit, connected to the processing unit, is used to generate the final particle size distribution of the sintered mixture after granulation based on the target particle size and the weight percentage of fine particles that are not adhered after granulation.

[0024] Preferably, the set of physical parameters includes at least: the apparent density of each individual raw material, the bulk density of the fine particles of each individual raw material in the densest state, and the adhesion ratio of the fine particles of each individual raw material during granulation.

[0025] Preferably, the processing unit is configured as follows:

[0026] Based on the respective proportions and corresponding physical parameters of the n single raw materials, the weighted average apparent density, the weighted average densest bulk density of the fine particles, and the weighted average adhesion ratio of the fine particles are calculated.

[0027] The particle growth volume ratio is determined according to the following logical relationship: the particle growth volume ratio is directly proportional to the product of the total weight percentage of all fine particles in the sintered mixture, the weighted average adhesion ratio, the weighted average densest bulk density, and the weighted average apparent density, and is inversely proportional to the total weight percentage of all coarse particles in the sintered mixture.

[0028] Thirdly, the present invention provides a computer-readable storage medium storing a computer program therein, which, when executed by a processor, implements the method described in any one of the first aspects.

[0029] Fourthly, the present invention provides a computer program product, including computer program instructions, which are stored in a computer-readable storage medium. When a processor reads and executes the computer program instructions in the computer-readable storage medium, it implements the method described in any one of the first aspects.

[0030] Compared with the prior art, the present invention has the following advantages:

[0031] 1. Simple and easy to implement: This invention proposes a prediction method based on the detection of basic physical parameters of raw materials, avoiding the need for complex machine learning models trained on massive amounts of historical data or physical simulation models that require advanced professional knowledge. The required parameters can all be measured through conventional experimental methods, and the calculation process is clear, greatly reducing the application threshold and facilitating rapid promotion and application in industrial settings such as sintering plants.

[0032] 2. High prediction accuracy and clear mechanism: This invention creatively introduces the key physical parameter of "adhesion ratio," which characterizes the pelletizing ability of raw materials, and combines it with parameters such as bulk density and apparent density to construct the core concept of "particle growth volume ratio." This method more profoundly reflects the physical process of fine particles adhering to the surface of coarse particles and growing, and compared with existing technologies that ignore this key factor, it can more accurately predict the particle size distribution after granulation.

[0033] 3. Achieves forward-looking optimization with significant application value: This invention can predict the final particle size distribution based solely on the batching scheme before the mixture enters the pellet mill. This provides production operators with a powerful forward-looking control tool, allowing them to proactively control the particle size distribution of the pelleted product within an ideal range by adjusting the proportions of different raw materials (i.e., optimizing the ore blending). This provides solid technical support for improving the permeability of the material bed and increasing the yield and quality of sintered ore. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments disclosed in this invention, the accompanying drawings of the embodiments will be briefly described below. These drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention.

[0035] Figure 1 This is a flowchart of a method according to an embodiment of the present invention.

[0036] Figure 2 This is a system structure block diagram of one embodiment of the present invention. Detailed Implementation

[0037] The technical solutions (including preferred technical solutions) of the present invention will be further described in detail below with reference to the accompanying drawings and by way of listing some optional embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0038] Example 1

[0039] like Figure 1 As shown in the figure, this embodiment details a method for predicting the particle size distribution of sintered mixtures after granulation, and the specific steps are as follows:

[0040] Step S101: Obtain initial data.

[0041] First, determine the types of n individual raw materials participating in the batching and their proportion Pi in the mixture. Simultaneously, characterize the physical properties of each individual raw material independently. This characterization step includes drying a sample of each raw material (e.g., at least 3 kg) in an oven to constant weight (e.g., moisture content less than 0.1 wt%), and then sieving it using a set of standard sieves.

[0042] Step S102: Applicability judgment.

[0043] This method is based on the layered growth of fine particles on the surface of coarse particles, and it dominates when the content of fine particles is relatively low. Therefore, applicability assessment is necessary. Based on experience and experimental data, a preset aggregation threshold is set, for example, 40%.

[0044] First, based on the particle size distribution (Wi) and proportion (Pi) of each individual raw material, the total weight percentage (W) of fine particles in the mixture is calculated. fine The calculation logic is: W fine = Σ(Wi fine * Pi) / 100, where Wi fine It is the weight percentage of fine particles in the i-th raw material.

[0045] Then, determine W. fine Is it not greater than the aggregation threshold? If W fine If W ≤ 40%, then this method is deemed applicable, and the process continues; if W fine If the result is >40%, it means that significant multinucleus aggregation may occur during the granulation process, and the prediction accuracy of this method will decrease. In this case, the user should be advised that the method is not applicable or to refer to the prediction results with caution.

[0046] Step S103: Obtain key physical parameters.

[0047] For each individual raw material, a set of pre-defined physical parameters characterizing its granulation performance were determined through experiments.

[0048] Apparent density ρi (g / cm³): determined using conventional density measurement methods such as the specific gravity bottle method.

[0049] The bulk density Vmi (cm³ / g) of fine particles in their densest state: Here, fine particles refer to particles obtained through sieving with a particle size smaller than a first preset particle size threshold. A certain weight of this fine particle sample is weighed and compacted to its densest state using a sample compactor under a specific pressure (e.g., 7–12 MPa). The density is calculated by measuring the relationship between its volume and mass.

[0050] Adhesion ratio Adi (%) during fine particle granulation: A certain weight of fine particle sample is taken for granulation test, and then the granulated product is dried and sieved again. The weight of particles that failed to adhere and grow successfully and are still fine particles is measured. The adhesion ratio Adi is the percentage of the weight of fine particles that successfully adhere and grow to the total weight of the initial fine particles.

[0051] Step S104: Calculate the weighted average parameter and the particle growth volume ratio V % .

[0052] Based on the data obtained in steps S101 to S103, the weighted average physical parameters of the mixture are calculated, and then the core particle growth volume ratio V is calculated. % .

[0053] First, calculate the weighted average apparent density ρ of the mixture, the weighted average densest bulk density Vm of the fine particles, and the weighted average adhesion ratio Ad of the fine particles.

[0054] Then, according to formula V % =W fine *Ad*Vm*ρ / (100-W fine ) / 100 Calculate the particle growth volume ratio V % The V % The physical meaning of the parameter is that it quantifies the proportion of the total volume of all the fine particles that can successfully adhere, after compaction into layers, to the total volume of all the coarse particles that serve as growth cores.

[0055] Step S105: Predict the target particle size and final particle size distribution.

[0056] Based on particle growth volume ratio V % To predict the particle size distribution after granulation.

[0057] Predicting the target particle size DL for coarse particles: Assuming particle growth is uniform isotropic stratification, the relationship of volume increase can be converted into a relationship of particle size increase. The formula DL = (1 + V) / ( ... % )^(1 / 3)×D,For each coarse particle's initial particle size D, calculate its target particle size DL after growth.

[0058] Calculate the amount of non-adhering fine particles: For each individual raw material, multiply its fine particle weight percentage, blending ratio, and (100 - adhesion ratio) to obtain the contribution of non-adhering fine particles for that raw material; then sum the contributions of non-adhering fine particles for all individual raw materials. Calculate the percentage of particles that failed to adhere after granulation and remain in fine particle form as a percentage of the total weight of the mixture.

[0059] The final particle size distribution is determined as follows: It consists of two parts: the non-adherent fine particles calculated above, and the larger, coarser particles. The weight percentage of each initial coarse particle size remains constant, but its corresponding particle size range is shifted and expanded based on the calculation results from step S105. Integrating these two parts yields the complete predicted particle size distribution after granulation.

[0060] Example 2

[0061] like Figure 2 As shown, this embodiment provides a system for implementing the above method. This system can be embedded in the batching control system of a factory or run as independent prediction software.

[0062] The system includes a data acquisition unit 100, a processing unit 200, and a prediction result generation unit 300.

[0063] Data acquisition unit 100: Responsible for data input and management. It has a human-machine interface or data interface, allowing the operator to input or import from the database the particle size distribution, blending ratio Pi, and key physical parameters (ρi, Vmi, Adi) of each individual raw material obtained in steps S101 and S103 of Example 1.

[0064] Processing Unit 200: This is the core of the system, performing the main calculations and logical judgments. It can be further divided into several functional modules:

[0065] Applicability determination module: After receiving the data, it first calculates W according to the method in step S102 of embodiment 1. fine The result is then compared with a clustering threshold (e.g., 40%) stored in the system. If the threshold is exceeded, an "inapplicable" instruction is sent to the prediction result generation unit 300; if the condition is met, subsequent modules are activated.

[0066] Parameter Calculation Module: This module is activated after the applicability judgment is passed. It performs the calculation in step S104 of Example 1, that is, calculates the weighted average parameters ρ, Vm, and Ad, and finally calculates the particle growth volume ratio V. % .

[0067] Particle size prediction module: This module receives the particle growth volume ratio V % Then, the calculation in step S105 of Example 1 is performed. It calculates the weight percentage of unadhered fine particles and the target particle size DL and new particle size range after all coarse particle sizes have grown.

[0068] Prediction result generation unit 300: Responsible for displaying prediction results in a user-friendly manner. It receives calculation results from processing unit 200. If it receives an "Inapplicable" instruction, it displays a warning message. If it receives complete calculation results, it presents the final particle size distribution to the user in the form of a data table or graph (such as a particle size distribution curve), providing a basis for the user's mineral blending decisions.

[0069] This system automates complex calculation processes, allowing users to quickly obtain accurate prediction results simply by inputting basic data, greatly improving work efficiency and the practicality of the method.

[0070] Example 3

[0071] This embodiment provides a method for predicting the particle size distribution of sintered mixtures after granulation, and the implementation steps are as follows:

[0072] 1) Test the particle size distribution of all individual raw materials (n kinds of raw materials) used in the mixture: Take no less than 3 kg of each individual raw material and dry them until the moisture content is less than 0.1 wt%, and set aside for later use; put all the dried individual raw materials into a sieve and sieve to separate particles of -0.5 mm, 0.5-1 mm, 1-2 mm, 2-3.15 mm, 3.15-5 mm, 5-6.3 mm, and +6.3 mm (the +0.5 mm particle size is not limited to the sieve size listed here, and can be selected arbitrarily as needed), and record its particle size distribution, and express the weight percentage of each particle size as Wi. -0.5 Wi 0.5-1 Wi 1-2 Wi 2-3.15 Wi 3.15-5 Wi 5-6.3 Wi +6.3 (i is the code for a single raw material, where i is an integer from 1 to n).

[0073] 2) Calculate the particle size distribution of the mixture: Based on the proportion Pi of all individual raw materials (i is the number of the individual raw material, i is an integer from 1 to n), calculate the content of particle sizes -0.5mm, 0.5-1mm, 1-2mm, 2-3.15mm, 3.15-5mm, 5-6.3mm, and +6.3mm in the mixture, and express the weight percentage of each particle size as W. -0.5 W 0.5-1 W 1-2 W 2-3.15 W 3.15-5 W 5-6.3 W +6.3 The calculation method for each particle size fraction of the mixture is the same; the following calculation will use W as an example. -0.5 and W 0.5-1 Taking the calculation as an example, the calculation formulas are as follows:

[0074]

[0075]

[0076] 3) Determine whether the particle size distribution of the granulated mixture can be predicted using this method: If W -0.5 If the probability is no greater than 40%, this method can be used for prediction.

[0077] 4) Detect the apparent density ρi (g / cm³) of all individual raw material particles used in the mixture. 3 Take a 25ml specific gravity bottle, weigh it, and record its weight as mi; after filling it with water, weigh the total weight of the bottle and water, and record it as mi. 总 After draining and drying the water from the specific gravity bottle, fill it with the dried mixed particles, filling it to about one-third full. Weigh the bottle and the sample, and record the weight as Mi. Then fill the specific gravity bottle with water and weigh the total weight of the bottle, the sample, and the water, and record the weight as Mi. 总 ; Calculate the apparent density of all individual raw materials ρi = (Mm) / (mi) 总 -Mi 总 +Mi-mi).

[0078] 5) Calculate the apparent density ρ (g / cm³) of the mixture. 3 The calculation formula is:

[0079]

[0080] 6) Detect the bulk density Vmi (cm³) of all single raw materials used in the mixture in the 0.5mm particle size fraction under the densest state. 3 / g): Weigh a certain amount of -0.5mm particles, denoted as Gi; load the weighed -0.5mm particles into a mold with a known bottom area, denoted as S; extrude the -0.5mm particles in the mold, with the extrusion parameters set as follows: extrusion pressure of 7-12MPa, extrusion time of not less than 300min; take out the extruded -0.5mm particles for testing, measure their thickness, denoted as Hi; calculate the bulk density Vmi=S*Hi / Gi in its densest state.

[0081] 7) Calculate the bulk density Vm (cm³) of the mixture with 0.5mm particles in its densest state. 3 / g): The calculation formula is:

[0082]

[0083] 8) Test the adhesion ratio (Adi) (%) of all single raw materials used in the mixture during granulation of -0.5mm particle size: A certain amount of all single raw materials' -0.5mm particle size was taken (the amount was determined according to the size of the granulation test equipment, and the weight taken was recorded as Zi) for granulation; after granulation, the particles were dried until the moisture content was no more than 2wt%; the dried particles were sieved to separate the -0.5mm particle size, and dried again until the moisture content was no more than 0.1wt%; the weight of the dried -0.5mm particle size was recorded as Zi. -0.5 ; Calculate the granulation adhesion ratio Adi for all single raw materials -0.5mm particle size: Adi = 100 * (Zi - Zi) -0.5 ) / Zi.

[0084] 9) Calculate the adhesion ratio Ad (%) of -0.5mm particles in the mixture during granulation: The calculation formula is as follows:

[0085]

[0086] 10) Calculate the percentage of non-adhered -0.5mm particles in the mixture (WDL). -0.5mm The calculation formula is:

[0087]

[0088] 11) Calculate the volume ratio V of the densest packing volume of -0.5mm particles to the volume of +0.5mm particles in the mixture. % = W -0.5 *Ad*Vm*ρ / (100-W -0.5 ) / 100.

[0089] 12) Predicting the particle size DL of a +0.5mm particle after granulation: Let the particle size before granulation be D. The formula for calculating the particle size DL after granulation is:

[0090]

[0091] 13) Calculate the particle size after granulation for particles with diameters of 0.5mm, 1mm, 2mm, 3.15mm, 5mm, and 6.3mm before granulation: Calculate according to the formula in step 11), and denote them as DL. 0.5mm DL 1mm DL 2mm DL 3.15mm DL 5mm DL 6.3mm

[0092] 14) Obtain the particle size distribution of the granulated mixture: WDL -0.5mm (Calculated in step 10), WDL 0.5-1mm =W 0.5-1 *(1+V % / (Vm*ρ)), WDL 1-2mm =W 1-2 *(1+V % / (Vm*ρ)), WDL 2-3.15mm =W 2-3.15 *(1+V % / (Vm*ρ)), WDL 3.15-5mm =W 3.15-5 *(1+V % / (Vm*ρ)), WDL 5-6.3mm =W 5-6.3 *(1+V % / (Vm*ρ)), WDL +6.3mm =W +6.3 *(1+V % / (Vm*ρ)).

[0093] Example 4

[0094] This embodiment uses a specific ingredient formula as an example to fully demonstrate the application process and results of the method of the present invention.

[0095] 1) Test the particle size distribution of all individual raw materials (a total of 10 raw materials) used in the mixture: Take no less than 3 kg of each individual raw material and dry them until the moisture content is less than 0.1 wt%, and set aside for later use; put all the dried individual raw materials into a sieve and sieve to separate particles of -0.5 mm, 0.5-1 mm, 1-2 mm, 2-3.15 mm, 3.15-5 mm, 5-6.3 mm, and +6.3 mm (the +0.5 mm particle size is not limited to the sieve size listed here and can be selected arbitrarily as needed), and record its particle size distribution, and express the weight percentage of each particle size as Wi. -0.5 Wi 0.5-1 Wi 1-2 Wi 2-3.15 Wi 3.15-5 Wi 5-6.3 Wi +6.3 The particle size distribution of the 10 raw materials is shown in Table 4.1.

[0096] Table 4.1 Particle size distribution and blending ratio of individual raw materials, wt%

[0097] Raw material name Number i <![CDATA[Wi +6.3 ]]> <![CDATA[Wi 5-6.3 ]]> <![CDATA[Wi 3.15-5 ]]> <![CDATA[Wi 2-3.15 ]]> <![CDATA[Wi 1-2 ]]> <![CDATA[Wi 0.5-1 ]]> <![CDATA[Wi -0.5 ]]> Pi Iron ore K 1 17.77 5.16 17.16 4.34 12.00 11.08 32.49 7.32 Iron ore N 2 12.36 6.31 16.8 5.51 15.30 13.00 30.72 4.51 Iron Ore M 3 9.32 3.96 13.77 4.61 13.44 13.66 41.24 8.45 Iron ore Y 4 30.13 3.54 15.36 6.18 16.17 14.29 14.33 22.54 Iron Ore NF 5 13.18 13.54 32.13 9.11 20.44 8.44 3.16 7.89 Iron ore J 6 0 0 0 0 0 4.25 95.75 5.63 Flux SH1 7 0 0.23 21.07 12.35 23.8 14.95 27.6 10.71 Flux BY1 8 0.00 0.38 15.31 8.16 18.95 15.46 41.74 4.48 Fuel J1 9 1.33 8.11 21.25 8.91 17.94 13.97 28.49 3.31 Return to mining 1 10 2.90 4.10 16.50 9.70 20.30 19.10 27.40 25.16

[0098] 2) Calculate the particle size distribution of the mixture: Based on the proportions Pi of all individual raw materials (i is the number of the individual raw material, i is an integer from 1 to n) shown in Table 4.1, calculate the content of particle sizes -0.5mm, 0.5-1mm, 1-2mm, 2-3.15mm, 3.15-5mm, 5-6.3mm, and +6.3mm in the mixture, and quantify the weight percentage of each particle size as W. -0.5 W 0.5-1 W 1-2 W 2-3.15 W 3.15-5 W 5-6.3 W +6.3 (Calculation results are shown in Table 4.2). The calculation method is the same for all particle sizes of the mixture. The following calculations are for W-0.5 and W0.5-1 as examples, with the following formulas:

[0099]

[0100]

[0101] Table 4.2 Calculated weight percentage of each particle size in the mixture, wt%

[0102] <![CDATA[W +6.3 ]]> <![CDATA[W 5-6.3 ]]> <![CDATA[W 3.15-5 ]]> <![CDATA[W 2-3.15 ]]> <![CDATA[W 1-2 ]]> <![CDATA[W 0.5-1 ]]> <![CDATA[W -0.5 ]]> Mixture 11.25 4.20 16.97 7.49 17.06 14.24 28.79

[0103] 3) To determine whether the particle size distribution of the granulated mixture can be predicted using this method: Table 4.2 shows that the particle size distribution of the mixture W -0.5 Since the percentage is 28.79% (less than 40%), this method can be used for prediction.

[0104] 4) Detect the apparent density ρi (g / cm³) of all individual raw material particles used in the mixture. 3 Take a 25ml specific gravity bottle, weigh it, and record its weight as mi; after filling it with water, weigh the total weight of the bottle and water, and record it as mi. 总 After draining and drying the water from the specific gravity bottle, fill it with the dried mixed particles, filling it to about one-third full. Weigh the bottle and the sample, and record the weight as Mi. Then fill the specific gravity bottle with water and weigh the total weight of the bottle, the sample, and the water, and record the weight as Mi. 总 ; Calculate the apparent density of all individual raw materials ρi = (Mi - mi) / (mi) 总 -Mi 总 +Mi-mi). The apparent density test results of the 10 raw materials are shown in Table 4.3.

[0105] Table 4.3 Record of Apparent Density Test Results for Single Raw Materials

[0106] Raw material name Number i mi, g <![CDATA[mi 总 ,g]]> Mi, g <![CDATA[Mi 总 ,g]]> <![CDATA[ρi,g / cm 3 ]]> Iron ore K 1 16.4249 41.6899 43.4268 62.4610 4.3336 Iron ore N 2 16.6424 42.112 40.5583 60.3428 4.2068 Iron Ore M 3 16.3418 42.2488 40.8510 60.244 3.7625 Iron ore Y 4 15.6800 41.5296 37.3215 56.8172 3.4060 Iron Ore NF 5 15.8693 40.9172 50.5266 68.4152 4.8409 Iron ore J 6 15.8762 41.3164 52.3547 70.8706 5.2682 Flux SH1 7 16.1354 41.7892 38.7125 54.6179 2.3160 Flux BY1 8 16.0731 41.0915 37.9246 53.4571 2.3036 Fuel J1 9 15.9268 40.9706 33.5798 49.2763 1.8886 Return to mining 1 10 16.0139 41.7534 46.1512 64.2162 3.9269

[0107] 5) Calculate the apparent density ρ (g / cm³) of the mixture. 3 The calculation formula is: ρ = 3.6729.

[0108]

[0109] 6) Detect the bulk density Vmi (cm³) of all single raw materials used in the mixture in the 0.5mm particle size fraction under the densest state. 3 / g): Weigh a certain amount of -0.5mm particle size, denoted as Gi; load the weighed -0.5mm particle size into a mold with a known bottom area, denoted as S; extrude the -0.5mm particle size into the mold, with the extrusion parameters set as follows: extrusion pressure 7-12MPa, extrusion time not less than 300min; remove the extruded -0.5mm particle size for testing, measure its thickness, denoted as Hi; calculate its bulk density Vmi = S*Hi / Gi in its densest state. The bulk density test results of 10 raw materials are shown in Table 4.4.

[0110] Table 4.4 Record of Bulk Density Test Results for Single Raw Materials

[0111] Raw material name Number i Gi, g <![CDATA[S,cm 2 ]]> Hi, cm <![CDATA[Vmi,cm 3 / g <!-- 8 -->]]> Iron ore K 1 30 4.8735 2.13 0.3460 Iron ore N 2 30 4.8735 2.25 0.3655 Iron Ore M 3 25 4.8735 2.14 0.4172 Iron ore Y 4 25 4.8735 2.50 0.4874 Iron Ore NF 5 30 4.8735 1.95 0.3168 Iron ore J 6 30 4.8735 1.84 0.2989 Flux SH1 7 20 4.8735 2.45 0.5970 Flux BY1 8 20 4.8735 2.49 0.6068 Fuel J1 9 15 4.8735 2.37 0.7700 Return to mining 1 10 30 4.8735 2.43 0.3948

[0112] 7) Calculate the bulk density Vm (cm3 / g) of the 0.5mm particle size of the mixture in the densest state: The calculation formula is: Vm = 0.4306.

[0113]

[0114] 8) Test the adhesion ratio (Adi) (%) of all single raw materials used in the mixture during granulation of -0.5mm particle size: A certain amount of all single raw materials' -0.5mm particle size was taken (the amount was determined according to the size of the granulation test equipment, and the weight taken was recorded as Zi) for granulation; after granulation, the particles were dried until the moisture content was no more than 2wt%; the dried particles were sieved to separate the -0.5mm particle size, and dried again until the moisture content was no more than 0.1wt%; the weight of the dried -0.5mm particle size was recorded as Zi. -0.5 ; Calculate the granulation adhesion ratio Adi for all single raw materials -0.5mm particle size: Adi = 100 * (Zi - Zi) -0.5 The adhesion ratios of the 10 raw materials during granulation are shown in Table 4.5.

[0115] Table 4.5 Adhesion ratio results during granulation of single raw materials

[0116] Raw material name Number i Zi,g <![CDATA[Zi -0.5 ,g]]> Adi, % Iron ore K 1 1000 26.7 97.33 Iron ore N 2 1000 25.1 97.49 Iron Ore M 3 1000 11.2 98.88 Iron ore Y 4 1000 12.8 98.72 Iron Ore NF 5 1000 25.7 97.43 Iron ore J 6 1000 848.5 15.15 Flux SH1 7 1000 23.4 97.66 Flux BY1 8 1000 24.2 97.58 Fuel J1 9 1000 35.7 96.43 Return to mining 1 10 1000 26.3 97.37

[0117] 9) Calculate the adhesion ratio Ad (%) of -0.5mm particles in the mixture during granulation: The calculation formula is: Ad = 82.32.

[0118]

[0119] 10) Calculate the percentage of non-adhered -0.5mm particles in the mixture (WDL). -0.5mm The calculation formula is as follows: WDL is calculated. -0.5mm =5.09.

[0120]

[0121] 11) Calculate the volume ratio V of the densest packing volume of -0.5mm particles to the volume of +0.5mm particles in the mixture. % =W -0.5 *Ad*Vm*ρ / (100-W -0.5 ) / 100=28.79*82.32*0.4306*3.6729 / (100-28.79) / 100=0.5264.

[0122] 12) Predicting the particle size DL of a +0.5mm particle after granulation: Let the particle size before granulation be D. The formula for calculating the particle size DL after granulation is:

[0123]

[0124] 13) Calculate the particle size after granulation for particles with diameters of 0.5mm, 1mm, 2mm, 3.15mm, 5mm, and 6.3mm before granulation: Calculate according to the formula in step 12), and denote them as DL. 0.5mm =0.58, DL 1mm =1.15、DL 2mm =2.30、DL 3.15mm =3.63、DL 5mm =5.76、DL 6.3mm =7.25.

[0125] 14) Obtain the particle size distribution of the granulated mixture:

[0126] -0.58mm particle size percentage by mass: WDL -0.5mm =5.09 (calculated in step 10);

[0127] Mass percentage of 0.58-1.15mm particles: WDL 0.5-1mm =W 0.5-1 *(1+V % / (Vm*ρ))=18.98;

[0128] 1.15-2.30mm particle size percentage (WDL) 1-2mm =W 1-2 *(1+V % / (Vm*ρ))=22.74;

[0129] Mass percentage of 2.30-3.63mm particles: WDL 2-3.15mm =W 2-3.15 *(1+V % / (Vm*ρ))=9.98;

[0130] Mass percentage of 3.63-5.76mm particles: WDL 3.15-5mm =W 3.15-5 *(1+V % / (Vm*ρ))=22.62;

[0131] Mass percentage of 5.76-7.25mm particles: WDL 5-6.3mm =W 5-6.3 *(1+V % / (Vm*ρ))=5.60;

[0132] +7.25mm particle size percentage by mass: WDL +6.3mm =W +6.3 *(1+V% / (Vm*ρ))=14.99.

[0133] 15) Verify the particle size distribution of the mixture after granulation (since the size of the standard sieve is fixed, 0.5 mm and 7.1 mm sieves are used for verification): The mixture is prepared according to the proportion of all single raw materials Pi, and the granulated sample is sieved. The particle size distribution after granulation is shown in Table 4.6.

[0134] Table 4.6 Measured weight percentage of each particle size in the granulated mixture, wt%.

[0135] <![CDATA[W +7.1 ]]> <![CDATA[W 0.5-7.1 ]]> <![CDATA[W -0.5 ]]> Granulated mixture 15.01 80.01 4.98

[0136] Example 5

[0137] This embodiment uses a specific ingredient formula as an example to fully demonstrate the application process and results of the method of the present invention.

[0138] 1) Test the particle size distribution of all individual raw materials (a total of 10 raw materials) used in the mixture: Take no less than 3 kg of each individual raw material and dry them until the moisture content is less than 0.1 wt%, and set aside for later use; put all the dried individual raw materials into a sieve and sieve to separate particles of -0.5 mm, 0.5-1 mm, 1-2 mm, 2-3.15 mm, 3.15-5 mm, 5-6.3 mm, and +6.3 mm (the +0.5 mm particle size is not limited to the sieve size listed here and can be selected arbitrarily as needed), and record its particle size distribution, and express the weight percentage of each particle size as Wi. -0.5 Wi 0.5-1 Wi 1-2 Wi 2-3.15 Wi 3.15-5 Wi 5-6.3 Wi +6.3 The particle size distribution of the 10 raw materials is shown in Table 5.1.

[0139] Table 5.1 Particle size distribution and blending ratio of individual raw materials, wt%

[0140] Raw material name Number i <![CDATA[Wi +6.3 ]]> <![CDATA[Wi 5-6.3 ]]> <![CDATA[Wi 3.15-5 ]]> <![CDATA[Wi 2-3.15 ]]> <![CDATA[Wi 1-2 ]]> <![CDATA[Wi 0.5-1 ]]> <![CDATA[Wi -0.5 ]]> Pi Iron ore K 1 17.77 5.16 17.16 4.34 12.00 11.08 32.49 7.32 Iron ore N 2 12.36 6.31 16.8 5.51 15.30 13.00 30.72 4.51 Iron Ore M 3 9.32 3.96 13.77 4.61 13.44 13.66 41.24 8.45 Iron ore Y 4 30.13 3.54 15.36 6.18 16.17 14.29 14.33 22.54 Iron Ore NF 5 13.18 13.54 32.13 9.11 20.44 8.44 3.16 7.89 Iron ore J 6 0 0 0 0 0 4.25 95.75 5.63 Flux SH2 7 2.85 5.12 28.35 8.9 23.43 14.82 16.53 10.71 Flux BY1 8 0.00 0.38 15.31 8.16 18.95 15.46 41.74 4.48 Fuel J1 9 1.33 8.11 21.25 8.91 17.94 13.97 28.49 3.31 Return to mining 1 10 2.90 4.10 16.50 9.70 20.30 19.10 27.40 25.16

[0141] 2) Calculate the particle size distribution of the mixture: Based on the proportions Pi of all individual raw materials (i is the number of the individual raw material, i is an integer from 1 to n) as shown in Table 5.1, calculate the content of particle sizes -0.5mm, 0.5-1mm, 1-2mm, 2-3.15mm, 3.15-5mm, 5-6.3mm, and +6.3mm in the mixture, and quantify the weight percentage of each particle size as W. -0.5 W 0.5-1 W 1-2 W 2-3.15 W 3.15-5 W 5-6.3 W +6.3(Calculation results are shown in Table 5.2). The calculation method is the same for each particle size of the mixture. The following calculation uses W as an example. -0.5 and W 0.5-1 Taking the calculation as an example, the calculation formulas are as follows:

[0142]

[0143]

[0144] Table 5.2 Calculated weight percentage of each particle size in the mixture, wt%

[0145] <![CDATA[W +6.3 ]]> <![CDATA[W 5-6.3 ]]> <![CDATA[W 3.15-5 ]]> <![CDATA[W 2-3.15 ]]> <![CDATA[W 1-2 ]]> <![CDATA[W 0.5-1 ]]> <![CDATA[W -0.5 ]]> Mixture 11.55 4.73 17.75 7.12 17.02 14.23 27.60

[0146] 3) Determine whether the particle size distribution of the granulated mixture can be predicted using this method: Table 5.2 shows that the particle size distribution of the mixture W -0.5 Since the percentage is 27.60% < 40%, this method can be used for prediction.

[0147] 4) Detect the apparent density ρi (g / cm³) of all individual raw material particles used in the mixture. 3 Take a 25ml specific gravity bottle, weigh it, and record its weight as mi; after filling it with water, weigh the total weight of the bottle and water, and record it as mi. 总 After draining and drying the water from the specific gravity bottle, fill it with the dried mixed particles, filling it to about one-third full. Weigh the bottle and the sample, and record the weight as Mi. Then fill the specific gravity bottle with water and weigh the total weight of the bottle, the sample, and the water, and record the weight as Mi. 总 ; Calculate the apparent density of all individual raw materials ρi = (Mi - mi) / (mi) 总 -Mi 总 +Mi-mi). The apparent density test results of the 10 raw materials are shown in Table 5.3.

[0148] Table 5.3 Record of Apparent Density Test Results for Single Raw Materials

[0149] Raw material name Number i mi, g <![CDATA[mi 总 ,g]]> Mi, g <![CDATA[Mi 总 ,g]]> <![CDATA[ρi,g / cm 3 ]]> Iron ore K 1 16.4249 41.6899 43.4268 62.4610 4.3336 Iron ore N 2 16.6424 42.112 40.5583 60.3428 4.2068 Iron Ore M 3 16.3418 42.2488 40.8510 60.244 3.7625 Iron ore Y 4 15.6800 41.5296 37.3215 56.8172 3.4060 Iron Ore NF 5 15.8693 40.9172 50.5266 68.4152 4.8409 Iron ore J 6 15.8762 41.3164 52.3547 70.8706 5.2682 Flux SH2 7 15.1769 40.9752 38.1054 53.7123 2.2498 Flux BY1 8 16.0731 41.0915 37.9246 53.4571 2.3036 Fuel J1 9 15.9268 40.9706 33.5798 49.2763 1.8886 Return to mining 1 10 16.0139 41.7534 46.1512 64.2162 3.9269

[0150] 5) Calculate the apparent density ρ (g / cm³) of the mixture. 3 The calculation formula is: ρ = 3.6658.

[0151]

[0152] 6) Detect the bulk density Vmi (cm³) of all single raw materials used in the mixture in the 0.5mm particle size fraction under the densest state. 3 / g): Weigh a certain amount of -0.5mm particle size, denoted as Gi; load the weighed -0.5mm particle size into a mold with a known bottom area, denoted as S; extrude the -0.5mm particle size into the mold, with the extrusion parameters set as follows: extrusion pressure 7-12MPa, extrusion time not less than 300min; remove the extruded -0.5mm particle size for testing, measure its thickness, denoted as Hi; calculate its bulk density Vmi = S*Hi / Gi in its densest state. The bulk density test results of 10 raw materials are shown in Table 5.4.

[0153] Table 5.4 Record of Bulk Density Test Results for Single Raw Materials

[0154] Raw material name Number i Gi, g <![CDATA[S,cm 2 ]]> Hi, cm <![CDATA[Vmi,cm 3 / g]]> Iron ore K 1 30 4.8735 2.13 0.3460 Iron ore N 2 30 4.8735 2.25 0.3655 Iron Ore M 3 25 4.8735 2.14 0.4172 Iron ore Y 4 25 4.8735 2.50 0.4874 Iron Ore NF 5 30 4.8735 1.95 0.3168 Iron ore J 6 30 4.8735 1.84 0.2989 Flux SH2 7 20 4.8735 2.57 0.6262 Flux BY1 8 20 4.8735 2.49 0.6068 Fuel J1 9 15 4.8735 2.37 0.7700 Return to mining 1 10 30 4.8735 2.43 0.3948

[0155] 7) Calculate the bulk density Vm (cm³) of the mixture with 0.5mm particles in its densest state. 3 / g): The calculation formula is: Vm = 0.4254.

[0156]

[0157] 8) Test the adhesion ratio (Adi) (%) of all single raw materials used in the mixture during granulation of -0.5mm particle size: A certain amount of all single raw materials' -0.5mm particle size was taken (the amount was determined according to the size of the granulation test equipment, and the weight taken was recorded as Zi) for granulation; after granulation, the particles were dried until the moisture content was no more than 2wt%; the dried particles were sieved to separate the -0.5mm particle size, and dried again until the moisture content was no more than 0.1wt%; the weight of the dried -0.5mm particle size was recorded as Zi. -0.5 ; Calculate the granulation adhesion ratio Adi for all single raw materials -0.5mm particle size: Adi = 100 * (Zi - Zi) -0.5 The adhesion ratios of the 10 raw materials during granulation are shown in Table 5.5.

[0158] Table 5.5 Adhesion ratio results during granulation of a single raw material

[0159] Raw material name Number i Zi,g <![CDATA[Zi -0.5 ,g]]> Adi, % Iron ore K 1 1000 26.7 97.33 Iron ore N 2 1000 25.1 97.49 Iron Ore M 3 1000 11.2 98.88 Iron ore Y 4 1000 12.8 98.72 Iron Ore NF 5 1000 25.7 97.43 Iron ore J 6 1000 848.5 15.15 Flux SH2 7 1000 36.8 96.32 Flux BY1 8 1000 24.2 97.58 Fuel J1 9 1000 35.7 96.43 Return to mining 1 10 1000 26.3 97.37

[0160] 9) Calculate the adhesion ratio Ad (%) of -0.5mm particles in the mixture during granulation: The calculation formula is: Ad = 81.58.

[0161]

[0162] 10) Calculate the percentage of non-adhered -0.5mm particles in the mixture (WDL). -0.5mmThe calculation formula is as follows: WDL is calculated. -0.5mm =5.08.

[0163]

[0164] 11) Calculate the volume ratio V of the densest packing volume of -0.5mm particles to the volume of +0.5mm particles in the mixture. % = W -0.5 * Ad * Vm * ρ / (100-W) -0.5 ) / 100 = 27.60 * 81.58 * 0.4254 * 3.6658 / (100-27.60) / 100 = 0.4849.

[0165] 12) Predicting the particle size DL of a +0.5mm particle after granulation: Let the particle size before granulation be D. The formula for calculating the particle size DL after granulation is:

[0166]

[0167] 13) Calculate the particle size after granulation for particles with diameters of 0.5mm, 1mm, 2mm, 3.15mm, 5mm, and 6.3mm before granulation: Calculate according to the formula in step 12), and denote them as DL. 0.5mm =0.57, DL 1mm =1.14、DL 2mm =2.28、DL 3.15mm =3.59、DL 5mm =5.70, DL 6.3mm =7.19.

[0168] 14) Obtain the particle size distribution of the granulated mixture:

[0169] -0.57mm particle size percentage WDL -0.5mm =5.08 (calculated in step 10);

[0170] Mass percentage of 0.57-1.14mm particles: WDL 0.5-1mm =W 0.5-1 *(1+V % / (Vm*ρ))=18.66;

[0171] Mass percentage of 1.14-2.28mm particles: WDL 1-2mm =W 1-2 *(1+V % / (Vm*ρ))=22.31;

[0172] Mass percentage of 2.28-3.59mm particles: WDL 2-3.15mm =W 2-3.15 *(1+V % / (Vm*ρ))=9.33;

[0173] Mass percentage of 3.59-5.70mm particles: WDL 3.15-5mm =W 3.15-5 *(1+V % / (Vm*ρ))=23.27;

[0174] Mass percentage of 5.70-7.19mm particles: WDL 5-6.3mm =W 5-6.3 *(1+V % / (Vm*ρ))=6.20;

[0175] +7.19mm particle size percentage by mass: WDL +6.3mm =W +6.3 *(1+V% / (Vm*ρ))=15.15.

[0176] 15) Verify the particle size distribution of the mixture after granulation (since the size of the standard sieve is fixed, 0.5 mm and 7.1 mm sieves are used for verification): The mixture is prepared according to the proportion of all single raw materials Pi, and the granulated sample is sieved. The particle size distribution after granulation is shown in Table 5.6.

[0177] Table 5.6 Measured weight percentage of each particle size in the granulated mixture, wt%.

[0178] <![CDATA[W +7.1 ]]> <![CDATA[W 0.5-7.1 ]]> <![CDATA[W -0.5 ]]> Granulated mixture 15.16 79.85 4.99

[0179] Example 6

[0180] This embodiment uses a specific ingredient formula as an example to fully demonstrate the application process and results of the method of the present invention.

[0181] 1) Test the particle size distribution of all individual raw materials (a total of 10 raw materials) used in the mixture: Take no less than 3 kg of each individual raw material and dry them until the moisture content is less than 0.1 wt%, and set aside for later use; put all the dried individual raw materials into a sieve and sieve to separate particles of -0.5 mm, 0.5-1 mm, 1-2 mm, 2-3.15 mm, 3.15-5 mm, 5-6.3 mm, and +6.3 mm (the +0.5 mm particle size is not limited to the sieve size listed here and can be selected arbitrarily as needed), and record its particle size distribution, and express the weight percentage of each particle size as Wi. -0.5 Wi 0.5-1 Wi 1-2 Wi 2-3.15Wi 3.15-5 Wi 5-6.3 Wi +6.3 The particle size distribution of the 10 raw materials is shown in Table 6.1.

[0182] Table 6.1 Particle size distribution and blending ratio of individual raw materials, wt%

[0183] Raw material name Number i <![CDATA[Wi +6.3 ]]> <![CDATA[Wi 5-6.3 ]]> <![CDATA[Wi 3.15-5 ]]> <![CDATA[Wi 2-3.15 ]]> <![CDATA[Wi 1-2 ]]> <![CDATA[Wi 0.5-1 ]]> <![CDATA[Wi -0.5 ]]> Pi Iron ore K 1 17.77 5.16 17.16 4.34 12.00 11.08 32.49 7.32 Iron ore N 2 12.36 6.31 16.8 5.51 15.30 13.00 30.72 4.51 Iron Ore M 3 9.32 3.96 13.77 4.61 13.44 13.66 41.24 8.45 Iron ore Y 4 30.13 3.54 15.36 6.18 16.17 14.29 14.33 22.54 Iron Ore NF 5 13.18 13.54 32.13 9.11 20.44 8.44 3.16 7.89 Iron ore J 6 0 0 0 0 0 4.25 95.75 5.63 Flux SH1 7 0 0.23 21.07 12.35 23.8 14.95 27.6 10.71 Flux BY1 8 0.00 0.38 15.31 8.16 18.95 15.46 41.74 4.48 Fuel M1 9 16.04 11.16 21.95 5.59 14.32 9.8 21.14 3.31 Return to mining 1 10 2.90 4.10 16.50 9.70 20.30 19.10 27.40 25.16

[0184] 2) Calculate the particle size distribution of the mixture: Based on the proportions Pi of all individual raw materials (i is the number of the individual raw material, i is an integer from 1 to n) as shown in Table 6.1, calculate the content of particle sizes -0.5mm, 0.5-1mm, 1-2mm, 2-3.15mm, 3.15-5mm, 5-6.3mm, and +6.3mm in the mixture, and quantify the weight percentage of each particle size as W. -0.5 W 0.5-1 W 1-2 W 2-3.15 W 3.15-5 W 5-6.3 W +6.3 (Calculation results are shown in Table 6.2). The calculation method is the same for each particle size of the mixture. The following calculation uses W as an example. -0.5 and W 0.5-1 Taking the calculation as an example, the calculation formulas are as follows:

[0185]

[0186]

[0187] Table 6.2 Calculated weight percentage of each particle size in the mixture, wt%

[0188] <![CDATA[W +6.3 ]]> <![CDATA[W 5-6.3 ]]> <![CDATA[W 3.15-5 ]]> <![CDATA[W 2-3.15 ]]> <![CDATA[W 1-2 ]]> <![CDATA[W 0.5-1 ]]> <![CDATA[W -0.5 ]]> Mixture 11.74 4.31 16.99 7.38 16.94 14.10 28.54

[0189] 3) Determine whether the particle size distribution of the granulated mixture can be predicted using this method: Table 6.2 shows that the particle size distribution of the mixture W -0.5 Since the percentage is 28.54% (less than 40%), this method can be used for prediction.

[0190] 4) Detect the apparent density ρi (g / cm³) of all individual raw material particles used in the mixture. 3 Take a 25ml specific gravity bottle, weigh it, and record its weight as mi; after filling it with water, weigh the total weight of the bottle and water, and record it as mi. 总 After draining and drying the water from the specific gravity bottle, fill it with the dried mixed particles, filling it to about one-third full. Weigh the bottle and the sample, and record the weight as Mi. Then fill the specific gravity bottle with water and weigh the total weight of the bottle, the sample, and the water, and record the weight as Mi. 总 ; Calculate the apparent density of all individual raw materials ρi = (Mi - mi) / (mi)总 -Mi 总 +Mi-mi). The apparent density test results of the 10 raw materials are shown in Table 6.3.

[0191] Table 6.3 Results of Apparent Density Test for Single Raw Materials

[0192] Raw material name Number i mi, g <![CDATA[mi 总 ,g]]> Mi, g <![CDATA[Mi 总 ,g]]> <![CDATA[ρi,g / cm 3 ]]> Iron ore K 1 16.4249 41.6899 43.4268 62.4610 4.3336 Iron ore N 2 16.6424 42.112 40.5583 60.3428 4.2068 Iron Ore M 3 16.3418 42.2488 40.8510 60.244 3.7625 Iron ore Y 4 15.6800 41.5296 37.3215 56.8172 3.4060 Iron Ore NF 5 15.8693 40.9172 50.5266 68.4152 4.8409 Iron ore J 6 15.8762 41.3164 52.3547 70.8706 5.2682 Flux SH1 7 16.1354 41.7892 38.7125 54.6179 2.3160 Flux BY1 8 16.0731 41.0915 37.9246 53.4571 2.3036 Fuel M1 9 15.9172 40.7218 32.7903 48.1426 1.7851 Return to mining 1 10 16.0139 41.7534 46.1512 64.2162 3.9269

[0193] 5) Calculate the apparent density ρ (g / cm³) of the mixture. 3 The calculation formula is: ρ = 3.6695.

[0194]

[0195] 6) Detect the bulk density Vmi (cm³) of all single raw materials used in the mixture in the 0.5mm particle size fraction under the densest state. 3 / g): Weigh a certain amount of -0.5mm particle size, denoted as Gi; load the weighed -0.5mm particle size into a mold with a known bottom area, denoted as S; extrude the -0.5mm particle size into the mold, with the extrusion parameters set as follows: extrusion pressure 7-12MPa, extrusion time not less than 300min; remove the extruded -0.5mm particle size for testing, measure its thickness, denoted as Hi; calculate its bulk density Vmi = S*Hi / Gi in its densest state. The bulk density test results of 10 raw materials are shown in Table 6.4.

[0196] Table 6.4 Record of Bulk Density Test Results for Single Raw Materials

[0197] Raw material name Number i Gi, g <![CDATA[S,cm 2 ]]> Hi, cm <![CDATA[Vmi,cm 3 / g]]> Iron ore K 1 30 4.8735 2.13 0.3460 Iron ore N 2 30 4.8735 2.25 0.3655 Iron Ore M 3 25 4.8735 2.14 0.4172 Iron ore Y 4 25 4.8735 2.50 0.4874 Iron Ore NF 5 30 4.8735 1.95 0.3168 Iron ore J 6 30 4.8735 1.84 0.2989 Flux SH1 7 20 4.8735 2.45 0.5970 Flux BY1 8 20 4.8735 2.49 0.6068 Fuel M1 9 15 4.8735 2.39 0.7765 Return to mining 1 10 30 4.8735 2.43 0.3948

[0198] 7) Calculate the bulk density Vm (cm³) of the mixture with 0.5mm particles in its densest state. 3 / g): The calculation formula is: Vm = 0.4279.

[0199]

[0200] 8) Test the adhesion ratio (Adi) (%) of all single raw materials used in the mixture during granulation of -0.5mm particle size: A certain amount of all single raw materials' -0.5mm particle size was taken (the amount was determined according to the size of the granulation test equipment, and the weight taken was recorded as Zi) for granulation; after granulation, the particles were dried until the moisture content was no more than 2wt%; the dried particles were sieved to separate the -0.5mm particle size, and dried again until the moisture content was no more than 0.1wt%; the weight of the dried -0.5mm particle size was recorded as Zi. -0.5; Calculate the granulation adhesion ratio Adi for all single raw materials -0.5mm particle size: Adi = 100 * (Zi - Zi) -0.5 The adhesion ratios of the 10 raw materials during granulation are shown in Table 6.5.

[0201] Table 6.5 Adhesion ratio results during granulation of a single raw material

[0202] Raw material name Number i Zi,g <![CDATA[Zi -0.5 ,g]]> Adi, % Iron ore K 1 1000 26.7 97.33 Iron ore N 2 1000 25.1 97.49 Iron Ore M 3 1000 11.2 98.88 Iron ore Y 4 1000 12.8 98.72 Iron Ore NF 5 1000 25.7 97.43 Iron ore J 6 1000 848.5 15.15 Flux SH1 7 1000 23.4 97.66 Flux BY1 8 1000 24.2 97.58 Fuel M1 9 1000 47.9 95.21 Return to mining 1 10 1000 26.3 97.37

[0203] 9) Calculate the adhesion ratio Ad (%) of -0.5mm particles in the mixture during granulation: The calculation formula is: Ad = 82.17.

[0204]

[0205] 10) Calculate the percentage of non-adhered -0.5mm particles in the mixture (WDL). -0.5mm The calculation formula is as follows: WDL is calculated. -0.5mm =5.09.

[0206]

[0207] 11) Calculate the volume ratio V of the densest packing volume of -0.5mm particles to the volume of +0.5mm particles in the mixture. % = W -0.5 * Ad * Vm * ρ / (100-W) -0.5 ) / 100 = 28.54 * 82.17 * 0.4279 * 3.6695 / (100-28.54) / 100 = 0.5153.

[0208] 12) Predicting the particle size DL of a +0.5mm particle after granulation: Let the particle size before granulation be D. The formula for calculating the particle size DL after granulation is:

[0209]

[0210] 13) Calculate the particle size after granulation for particles with diameters of 0.5mm, 1mm, 2mm, 3.15mm, 5mm, and 6.3mm before granulation: Calculate according to the formula in step 12), and denote them as DL. 0.5mm =0.57, DL 1mm =1.15、DL 2mm =2.30、DL 3.15mm =3.62、DL 5mm =5.74, DL 6.3mm =7.24.

[0211] 14) Obtain the particle size distribution of the granulated mixture:

[0212] -0.57mm particle size percentage by mass: WDL -0.5mm =5.09 (calculated in step 10);

[0213] Mass percentage of 0.57-1.15mm particles: WDL 0.5-1mm =W 0.5-1 *(1+V % / (Vm*ρ))=18.73;

[0214] 1.15-2.30mm particle size percentage (WDL) 1-2mm =W 1-2 *(1+V % / (Vm*ρ))=22.50;

[0215] Mass percentage of 2.30-3.62mm particles: WDL 2-3.15mm =W 2-3.15 *(1+V % / (Vm*ρ))=9.80;

[0216] Mass percentage of 3.62-5.74mm particles: WDL 3.15-5mm =W 3.15-5 *(1+V % / (Vm*ρ))=22.57;

[0217] Mass percentage of 5.74-7.24mm particle size: WDL 5-6.3mm =W 5-6.3 *(1+V % / (Vm*ρ))=5.72;

[0218] +7.24mm particle size percentage by mass: WDL +6.3mm =W +6.3 *(1+V% / (Vm*ρ))=15.59.

[0219] 15) Verify the particle size distribution of the mixture after granulation (since the size of the standard sieve is fixed, 0.5 mm and 7.1 mm sieves are used for verification): The mixture is prepared according to the proportion of all single raw materials Pi, and the granulated sample is sieved. The particle size distribution after granulation is shown in Table 6.6.

[0220] Table 6.6 Measured weight percentage of each particle size in the granulated mixture (wt%)

[0221] <![CDATA[W +7.1 ]]> <![CDATA[W 0.5-7.1 ]]> <![CDATA[W -0.5 ]]> Granulated mixture 15.36 79.62 5.02

[0222] Example 7

[0223] This embodiment uses a specific ingredient formula as an example to fully demonstrate the application process and results of the method of the present invention.

[0224] 1) Test the particle size distribution of all individual raw materials (a total of 10 raw materials) used in the mixture: Take no less than 3 kg of each individual raw material and dry them until the moisture content is less than 0.1 wt%, and set aside for later use; put all the dried individual raw materials into a sieve and sieve to separate particles of -0.5 mm, 0.5-1 mm, 1-2 mm, 2-3.15 mm, 3.15-5 mm, 5-6.3 mm, and +6.3 mm (the +0.5 mm particle size is not limited to the sieve size listed here and can be selected arbitrarily as needed), and record its particle size distribution, and express the weight percentage of each particle size as Wi. -0.5 Wi 0.5-1 Wi 1-2 Wi 2-3.15 Wi 3.15-5 Wi 5-6.3 Wi +6.3 The particle size distribution of the 10 raw materials is shown in Table 7.1.

[0225] Table 7.1 Particle size distribution and blending ratio of individual raw materials, wt

[0226] Raw material name Number i <![CDATA[Wi +6.3 ]]> <![CDATA[Wi 5-6.3 ]]> <![CDATA[Wi 3.15-5 ]]> <![CDATA[Wi 2-3.15 ]]> <![CDATA[Wi 1-2 ]]> <![CDATA[Wi 0.5-1 ]]> <![CDATA[Wi -0.5 ]]> Pi Iron ore K 1 17.77 5.16 17.16 4.34 12.00 11.08 32.49 6.42 Iron ore N 2 12.36 6.31 16.8 5.51 15.30 13.00 30.72 3.95 Iron Ore M 3 9.32 3.96 13.77 4.61 13.44 13.66 41.24 7.41 Iron ore Y 4 30.13 3.54 15.36 6.18 16.17 14.29 14.33 19.76 Iron Ore NF 5 13.18 13.54 32.13 9.11 20.44 8.44 3.16 6.92 Iron ore J 6 0 0 0 0 0 4.25 95.75 4.94 Flux SH1 7 0 0.23 21.07 12.35 23.8 14.95 27.6 10.71 Flux BY1 8 0.00 0.38 15.31 8.16 18.95 15.46 41.74 4.48 Fuel J1 9 1.33 8.11 21.25 8.91 17.94 13.97 28.49 3.31 Return to mining 1 10 2.90 4.10 16.50 9.70 20.30 19.10 27.40 32.10

[0227] 2) Calculate the particle size distribution of the mixture: Based on the proportions Pi of all individual raw materials (i is the number of the individual raw material, i is an integer from 1 to n) shown in Table 7.1, calculate the content of particle sizes -0.5mm, 0.5-1mm, 1-2mm, 2-3.15mm, 3.15-5mm, 5-6.3mm, and +6.3mm in the mixture, and quantify the weight percentage of each particle size as W. -0.5 W 0.5-1 W 1-2 W 2-3.15 W 3.15-5 W 5-6.3 W +6.3 (Calculation results are shown in Table 7.2). The calculation method is the same for each particle size of the mixture. The following calculation uses W as an example. -0.5 and W 0.5-1 Taking the calculation as an example, the calculation formulas are as follows:

[0228]

[0229]

[0230] Table 7.2 Calculated weight percentage of each particle size in the mixture, wt%

[0231] <![CDATA[W +6.3 ]]> <![CDATA[W 5-6.3 ]]> <![CDATA[W 3.15-5 ]]> <![CDATA[W 2-3.15 ]]> <![CDATA[W 1-2 ]]> <![CDATA[W 0.5-1 ]]> <![CDATA[W -0.5 ]]> Mixture 10.16 4.14 16.99 7.79 17.49 14.74 28.70

[0232] 3) Determine whether the particle size distribution of the granulated mixture can be predicted using this method: Table 7.2 shows that the particle size distribution of the mixture W -0.5 Since the percentage is 28.70% (less than 40%), this method can be used for prediction.

[0233] 4) Detect the apparent density ρi (g / cm³) of all individual raw material particles used in the mixture. 3 Take a 25ml specific gravity bottle, weigh it, and record its weight as mi; after filling it with water, weigh the total weight of the bottle and water, and record it as mi. 总 After draining and drying the water from the specific gravity bottle, fill it with the dried mixed particles, filling it to about one-third full. Weigh the bottle and the sample, and record the weight as Mi. Then fill the specific gravity bottle with water and weigh the total weight of the bottle, the sample, and the water, and record the weight as Mi. 总 ; Calculate the apparent density of all individual raw materials ρi = (Mi - mi) / (mi) 总 -Mi 总 +Mi-mi). The apparent density test results of the 10 raw materials are shown in Table 7.3.

[0234] Table 7.3 Record of Apparent Density Test Results for Single Raw Materials

[0235] Raw material name Number i mi, g <![CDATA[mi 总 ,g]]> Mi, g <![CDATA[Mi 总 ,g]]> <![CDATA[ρi,g / cm 3 ]]> Iron ore K 1 16.4249 41.6899 43.4268 62.4610 4.3336 Iron ore N 2 16.6424 42.112 40.5583 60.3428 4.2068 Iron Ore M 3 16.3418 42.2488 40.8510 60.244 3.7625 Iron ore Y 4 15.6800 41.5296 37.3215 56.8172 3.4060 Iron Ore NF 5 15.8693 40.9172 50.5266 68.4152 4.8409 Iron ore J 6 15.8762 41.3164 52.3547 70.8706 5.2682 Flux SH1 7 16.1354 41.7892 38.7125 54.6179 2.3160 Flux BY1 8 16.0731 41.0915 37.9246 53.4571 2.3036 Fuel J1 9 15.9268 40.9706 33.5798 49.2763 1.8886 Return to mining 1 10 16.0139 41.7534 46.1512 64.2162 3.9269

[0236] 5) Calculate the apparent density ρ (g / cm³) of the mixture. 3 The calculation formula is: ρ = 3.6657.

[0237]

[0238] 6) Detect the bulk density Vmi (cm³) of all single raw materials used in the mixture in the 0.5mm particle size fraction under the densest state. 3 / g): Weigh a certain amount of -0.5mm particle size, denoted as Gi; load the weighed -0.5mm particle size into a mold with a known bottom area, denoted as S; extrude the -0.5mm particle size into the mold, with the extrusion parameters set as follows: extrusion pressure 7-12MPa, extrusion time not less than 300min; remove the extruded -0.5mm particle size for testing, measure its thickness, denoted as Hi; calculate its bulk density Vmi = S*Hi / Gi in its densest state. The bulk density test results of 10 raw materials are shown in Table 7.4.

[0239] Table 7.4 Record of Bulk Density Test Results for Single Raw Materials

[0240] Raw material name Number i Gi, g <![CDATA[S,cm 2 ]]> Hi, cm <![CDATA[Vmi,cm 3 / g]]> Iron ore K 1 30 4.8735 2.13 0.3460 Iron ore N 2 30 4.8735 2.25 0.3655 Iron Ore M 3 25 4.8735 2.14 0.4172 Iron ore Y 4 25 4.8735 2.50 0.4874 Iron Ore NF 5 30 4.8735 1.95 0.3168 Iron ore J 6 30 4.8735 1.84 0.2989 Flux SH1 7 20 4.8735 2.45 0.5970 Flux BY1 8 20 4.8735 2.49 0.6068 Fuel J1 9 15 4.8735 2.37 0.7700 Return to mining 1 10 30 4.8735 2.43 0.3948

[0241] 7) Calculate the bulk density Vm (cm³) of the mixture with 0.5mm particles in its densest state. 3 / g): The calculation formula is: Vm = 0.4321 is obtained.

[0242]

[0243] 8) Test the adhesion ratio (Adi) (%) of all single raw materials used in the mixture during granulation of -0.5mm particle size: A certain amount of all single raw materials' -0.5mm particle size was taken (the amount was determined according to the size of the granulation test equipment, and the weight taken was recorded as Zi) for granulation; after granulation, the particles were dried until the moisture content was no more than 2wt%; the dried particles were sieved to separate the -0.5mm particle size, and dried again until the moisture content was no more than 0.1wt%; the weight of the dried -0.5mm particle size was recorded as Zi. -0.5 ; Calculate the granulation adhesion ratio Adi for all single raw materials -0.5mm particle size: Adi = 100 * (Zi - Zi) -0.5 The adhesion ratios of the 10 raw materials during granulation are shown in Table 7.5.

[0244] Table 7.5 Adhesion ratio results during granulation of a single raw material

[0245] Raw material name Number i Zi,g <![CDATA[Zi -0.5 ,g]]> Adi, % Iron ore K 1 1000 26.7 97.33 Iron ore N 2 1000 25.1 97.49 Iron Ore M 3 1000 11.2 98.88 Iron ore Y 4 1000 12.8 98.72 Iron Ore NF 5 1000 25.7 97.43 Iron ore J 6 1000 848.5 15.15 Flux SH1 7 1000 23.4 97.66 Flux BY1 8 1000 24.2 97.58 Fuel J1 9 1000 35.7 96.43 Return to mining 1 10 1000 26.3 97.37

[0246] 9) Calculate the adhesion ratio Ad (%) of -0.5mm particles in the mixture during granulation: The calculation formula is: Ad = 84.13.

[0247]

[0248] 10) Calculate the percentage of non-adhered -0.5mm particles in the mixture (WDL). -0.5mm The calculation formula is as follows: WDL is calculated. -0.5mm =4.56.

[0249]

[0250] 11) Calculate the volume ratio V of the densest packing volume of -0.5mm particles to the volume of +0.5mm particles in the mixture. % = W -0.5 * Ad * Vm * ρ / (100-W) -0.5 ) / 100 = 28.70 * 84.13 *0.4321 * 3.6657 / (100-28.70) / 100 = 0.5364.

[0251] 12) Predicting the particle size DL of a +0.5mm particle after granulation: Let the particle size before granulation be D. The formula for calculating the particle size DL after granulation is:

[0252]

[0253] 13) Calculate the particle size after granulation for particles with diameters of 0.5mm, 1mm, 2mm, 3.15mm, 5mm, and 6.3mm before granulation: Calculate according to the formula in step 12), and denote them as DL. 0.5mm =0.58, DL 1mm =1.15、DL 2mm =2.31、DL 3.15mm =3.63、DL 5mm =5.77、DL 6.3mm =7.27.

[0254] 14) Obtain the particle size distribution of the granulated mixture:

[0255] -0.58mm particle size percentage by mass: WDL -0.5mm =4.56 (calculated in step 10);

[0256] Mass percentage of 0.58-1.15mm particles: WDL 0.5-1mm =W 0.5-1 *(1+V % / (Vm*ρ))=19.73;

[0257] Mass percentage of 1.15-2.31mm particle size: WDL 1-2mm =W 1-2 *(1+V % / (Vm*ρ))=23.41;

[0258] Mass percentage of 2.31-3.63mm particles: WDL 2-3.15mm =W 2-3.15 *(1+V % / (Vm*ρ))=10.43;

[0259] Mass percentage of 3.63-5.77mm particles: WDL 3.15-5mm =W 3.15-5 *(1+V % / (Vm*ρ))=22.74;

[0260] Mass percentage of 5.77-7.27mm particles: WDL 5-6.3mm =W 5-6.3 *(1+V % / (Vm*ρ))=5.54;

[0261] +7.27mm particle size percentage by mass: WDL +6.3mm =W +6.3 *(1+V% / (Vm*ρ))=13.60.

[0262] 15) Verify the particle size distribution of the mixture after granulation (since the size of the standard sieve is fixed, 0.5 mm and 7.1 mm sieves are used for verification): The mixture is prepared according to the proportion of all single raw materials Pi, and the granulated sample is sieved. The particle size distribution after granulation is shown in Table 7.6.

[0263] Table 7.6 Measured weight percentage of each particle size in the granulated mixture, wt%.

[0264] <![CDATA[W +7.1 ]]> <![CDATA[W 0.5-7.1 ]]> <![CDATA[W -0.5 ]]> Granulated mixture 13.07 82.52 4.41

[0265] Example 8

[0266] This embodiment uses a specific ingredient formula as an example to fully demonstrate the application process and results of the method of the present invention.

[0267] 1) Test the particle size distribution of all individual raw materials (9 raw materials in total) used in the mixture: Take no less than 3 kg of each individual raw material and dry them until the moisture content is less than 0.1 wt%, and set aside for later use; put all the dried individual raw materials into a sieve and sieve to separate particles of -0.5 mm, 0.5-1 mm, 1-2 mm, 2-3.15 mm, 3.15-5 mm, 5-6.3 mm, and +6.3 mm (the +0.5 mm particle size is not limited to the sieve size listed here and can be selected arbitrarily as needed), and record its particle size distribution, and express the weight percentage of each particle size as Wi. -0.5 Wi 0.5-1 Wi 1-2 Wi 2-3.15 Wi 3.15-5 Wi 5-6.3 Wi +6.3 The particle size distribution of the nine raw materials is shown in Table 8.1.

[0268] Table 8.1 Particle size distribution and blending ratio of individual raw materials, wt%

[0269] Raw material name Number i <![CDATA[Wi +6.3 ]]> <![CDATA[Wi 5-6.3 ]]> <![CDATA[Wi 3.15-5 ]]> <![CDATA[Wi 2-3.15 ]]> <![CDATA[Wi 1-2 ]]> <![CDATA[Wi 0.5-1 ]]> <![CDATA[Wi -0.5 ]]> Pi Iron Ore B 1 9.64 3.77 15.72 4.98 14.26 10.22 41.41 10.14 Iron ore H 2 19.27 4.01 10.21 2.97 9.64 9.11 44.79 7.32 Iron ore F 3 37.35 18.17 26.43 4.78 7.59 2.98 2.7 10.70 Iron Ore G 4 24 6.67 16.76 7.71 16.35 13.4 15.11 22.54 Iron Ore M 5 14.93 4.12 8.98 2.77 7.67 8.82 52.71 5.63 Flux SH1 6 0 0.23 21.07 12.35 23.8 14.95 27.6 10.71 Flux BY1 7 0.00 0.38 15.31 8.16 18.95 15.46 41.74 4.48 Fuel J1 8 1.33 8.11 21.25 8.91 17.94 13.97 28.49 3.31 Return to mining 1 9 2.90 4.10 16.50 9.70 20.30 19.10 27.40 25.16

[0270] 2) Calculate the particle size distribution of the mixture: Based on the proportions Pi of all individual raw materials (i is the number of the individual raw material, i is an integer from 1 to n) shown in Table 8.1, calculate the content of particle sizes -0.5mm, 0.5-1mm, 1-2mm, 2-3.15mm, 3.15-5mm, 5-6.3mm, and +6.3mm in the mixture, and quantify the weight percentage of each particle size as W.-0.5 W 0.5-1 W 1-2 W 2-3.15 W 3.15-5 W 5-6.3 W +6.3 (Calculation results are shown in Table 8.2). The calculation method is the same for each particle size of the mixture. The following calculation uses W as an example. -0.5 and W 0.5-1 Taking the calculation as an example, the calculation formulas are as follows:

[0271]

[0272]

[0273] Table 8.2 Calculated weight percentage of each particle size in the mixture, wt%

[0274] <![CDATA[W +6.3 ]]> <![CDATA[W 5-6.3 ]]> <![CDATA[W 3.15-5 ]]> <![CDATA[W 2-3.15 ]]> <![CDATA[W 1-2 ]]> <![CDATA[W 0.5-1 ]]> <![CDATA[W -0.5 ]]> Mixture 13.41 5.70 17.25 7.55 16.18 13.10 26.81

[0275] 3) Determine whether the particle size distribution of the granulated mixture can be predicted using this method: Table 8.2 shows that the particle size distribution of the mixture W -0.5 Since the percentage is 26.81% (less than 40%), this method can be used for prediction.

[0276] 4) Detect the apparent density ρi (g / cm³) of all individual raw material particles used in the mixture. 3 Take a 25ml specific gravity bottle, weigh it, and record its weight as mi; after filling it with water, weigh the total weight of the bottle and water, and record it as mi. 总 After draining and drying the water from the specific gravity bottle, fill it with the dried mixed particles, filling it to about one-third full. Weigh the bottle and the sample, and record the weight as Mi. Then fill the specific gravity bottle with water and weigh the total weight of the bottle, the sample, and the water, and record the weight as Mi. 总 ; Calculate the apparent density of all individual raw materials ρi = (Mi - mi) / (mi) 总 -Mi 总 +Mi-mi). The apparent density test results of the nine raw materials are shown in Table 8.3.

[0277] Table 8.3 Record of Apparent Density Test Results for Single Raw Materials

[0278] Raw material name Number i mi, g <![CDATA[mi 总 ,g]]> Mi, g <![CDATA[Mi 总 ,g]]> <![CDATA[ρi,g / cm 3 ]]> Iron Ore B 1 16.2022 41.175 44.4155 62.6175 4.1669 Iron ore H 2 15.9099 41.7215 40.5911 59.1785 3.4165 Iron ore F 3 15.6326 42.2529 41.5669 61.3609 3.7992 Iron Ore G 4 12.9869 38.7158 37.8465 56.2057 3.3732 Iron Ore M 5 16.2699 42.0715 45.9133 64.5656 4.1463 Flux SH1 6 16.1354 41.7892 38.7125 54.6179 2.3160 Flux BY1 7 16.0731 41.0915 37.9246 53.4571 2.3036 Fuel J1 8 15.9268 40.9706 33.5798 49.2763 1.8886 Return to mining 1 9 16.0139 41.7534 46.1512 64.2162 3.9269

[0279] 5) Calculate the apparent density ρ (g / cm³) of the mixture. 3 The calculation formula is: ρ = 3.4747.

[0280]

[0281] 6) Detect the bulk density Vmi (cm³) of all single raw materials used in the mixture in the 0.5mm particle size fraction under the densest state. 3 / g): Weigh a certain amount of -0.5mm particle size, denoted as Gi; load the weighed -0.5mm particle size into a mold with a known bottom area, denoted as S; extrude the -0.5mm particle size into the mold, with the extrusion parameters set as follows: extrusion pressure 7-12MPa, extrusion time not less than 300min; remove the extruded -0.5mm particle size for testing, measure its thickness, denoted as Hi; calculate its bulk density Vmi = S*Hi / Gi in its densest state. The bulk density test results of the 9 raw materials are shown in Table 8.4.

[0282] Table 8.4 Record of Bulk Density Test Results for Single Raw Materials

[0283] Raw material name Number i Gi, g <![CDATA[S,cm 2 ]]> Hi, cm <![CDATA[Vmi,cm 3 / g]]> Iron Ore B 1 25 4.8735 1.83 0.3567 Iron ore H 2 25 4.8735 1.98 0.3860 Iron ore F 3 25 4.8735 2.05 0.3996 Iron Ore G 4 25 4.8735 2.19 0.4269 Iron Ore M 5 25 4.8735 1.68 0.3275 Flux SH1 6 20 4.8735 2.45 0.5970 Flux BY1 7 20 4.8735 2.49 0.6068 Fuel J1 8 15 4.8735 2.37 0.7700 Return to mining 1 9 30 4.8735 2.43 0.3948

[0284] 7) Calculate the bulk density Vm (cm³) of the mixture with 0.5mm particles in its densest state. 3 / g): The calculation formula is: Vm = 0.4347.

[0285]

[0286] 8) Test the adhesion ratio (Adi) (%) of all single raw materials used in the mixture during granulation of -0.5mm particle size: A certain amount of all single raw materials' -0.5mm particle size was taken (the amount was determined according to the size of the granulation test equipment, and the weight taken was recorded as Zi) for granulation; after granulation, the particles were dried until the moisture content was no more than 2wt%; the dried particles were sieved to separate the -0.5mm particle size, and dried again until the moisture content was no more than 0.1wt%; the weight of the dried -0.5mm particle size was recorded as Zi. -0.5 ; Calculate the granulation adhesion ratio Adi for all single raw materials -0.5mm particle size: Adi = 100 * (Zi - Zi) -0.5 The adhesion ratios of the nine raw materials during granulation are shown in Table 8.5.

[0287] Table 8.5 Adhesion ratio results during granulation of a single raw material

[0288] Raw material name Number i Zi,g <![CDATA[Zi -0.5 ,g]]> Adi, % Iron Ore B 1 1000 60.4 93.96 Iron ore H 2 1000 33.3 96.67 Iron ore F 3 1000 33.1 96.69 Iron Ore G 4 1000 82.4 91.76 Iron Ore M 5 1000 106.5 89.35 Flux SH1 6 1000 23.4 97.66 Flux BY1 7 1000 24.2 97.58 Fuel J1 8 1000 35.7 96.43 Return to mining 1 9 1000 26.3 97.37

[0289] 9) Calculate the adhesion ratio Ad (%) of -0.5mm particles in the mixture during granulation: The calculation formula is: Ad = 82.32.

[0290]

[0291] 10) Calculate the percentage of non-adhered -0.5mm particles in the mixture (WDL). -0.5mm The calculation formula is as follows: WDL is calculated. -0.5mm =1.30.

[0292]

[0293] 11) Calculate the volume ratio V of the densest packing volume of -0.5mm particles to the volume of +0.5mm particles in the mixture. % = W -0.5 * Ad * Vm * ρ / (100-W) -0.5 ) / 100 = 26.81 * 95.16 * 0.4347 * 3.4747 / (100 - 26.81) / 100 = 0.5265.

[0294] 12) Predicting the particle size DL of a +0.5mm particle after granulation: Let the particle size before granulation be D. The formula for calculating the particle size DL after granulation is:

[0295]

[0296] 13) Calculate the particle size after granulation for particles with diameters of 0.5mm, 1mm, 2mm, 3.15mm, 5mm, and 6.3mm before granulation: Calculate according to the formula in step 12), and denote them as DL. 0.5mm =0.58, DL 1mm =1.15、DL 2mm =2.30、DL 3.15mm =3.63、DL 5mm =5.76、DL 6.3mm =7.25.

[0297] 14) Obtain the particle size distribution of the granulated mixture:

[0298] -0.58mm particle size percentage by mass: WDL -0.5mm =1.30 (calculated in step 10)

[0299] Mass percentage of 0.58-1.15mm particles: WDL 0.5-1mm =W 0.5-1 *(1+V % / (Vm*ρ))=17.67;

[0300] 1.15-2.30mm particle size percentage (WDL) 1-2mm =W 1-2 *(1+V% / (Vm*ρ))=21.82;

[0301] Mass percentage of 2.30-3.63mm particles: WDL 2-3.15mm =W 2-3.15 *(1+V % / (Vm*ρ))=10.18;

[0302] Mass percentage of 3.63-5.76mm particles: WDL 3.15-5mm =W 3.15-5 *(1+V % / (Vm*ρ))=23.26;

[0303] Mass percentage of 5.76-7.25mm particles: WDL 5-6.3mm =W 5-6.3 *(1+V % / (Vm*ρ))=7.69;

[0304] +7.25mm particle size percentage by mass: WDL +6.3mm =W +6.3 *(1+V% / (Vm*ρ))=18.08.

[0305] 15) Verify the particle size distribution of the mixture after granulation (since the size of the standard sieve is fixed, 0.5 mm and 7.1 mm sieves are used for verification): The mixture is prepared according to the proportion of all single raw materials Pi, and the granulated sample is sieved. The particle size distribution after granulation is shown in Table 8.6.

[0306] Table 8.6 Measured weight percentage of each particle size in the granulated mixture, wt%.

[0307] <![CDATA[W +7.1 ]]> <![CDATA[W 0.5-7.1 ]]> <![CDATA[W -0.5 ]]> Granulated mixture 17.94 80.73 1.33

[0308] Example 9

[0309] This embodiment uses a specific ingredient formula as an example to fully demonstrate the application process and results of the method of the present invention.

[0310] 1) Test the particle size distribution of all individual raw materials (9 raw materials in total) used in the mixture: Take no less than 3 kg of each individual raw material and dry them until the moisture content is less than 0.1 wt%, and set aside for later use; put all the dried individual raw materials into a sieve and sieve to separate particles of -0.5 mm, 0.5-1 mm, 1-2 mm, 2-3.15 mm, 3.15-5 mm, 5-6.3 mm, and +6.3 mm (the +0.5 mm particle size is not limited to the sieve size listed here and can be selected arbitrarily as needed), and record its particle size distribution, and express the weight percentage of each particle size as Wi.-0.5 Wi 0.5-1 Wi 1-2 Wi 2-3.15 Wi 3.15-5 Wi 5-6.3 Wi +6.3 The particle size distribution of the nine raw materials is shown in Table 9.1.

[0311] Table 9.1 Particle size distribution and blending ratio of individual raw materials, wt%

[0312] Raw material name Number i <![CDATA[Wi +6.3 ]]> <![CDATA[Wi 5-6.3 ]]> <![CDATA[Wi 3.15-5 ]]> <![CDATA[Wi 2-3.15 ]]> <![CDATA[Wi 1-2 ]]> <![CDATA[Wi 0.5-1 ]]> <![CDATA[Wi -0.5 ]]> Pi Iron ore K 1 17.77 5.16 17.16 4.34 12.00 11.08 32.49 1.69 Iron Ore M 2 9.32 3.96 13.77 4.61 13.44 13.66 41.24 6.76 Iron ore Y 3 30.13 3.54 15.36 6.18 16.17 14.29 14.33 19.72 Iron Ore NF 4 13.18 13.54 32.13 9.11 20.44 8.44 3.16 5.63 Iron ore S 5 0 0 0 0 0 0 100 22.54 Flux SH1 6 0 0.23 21.07 12.35 23.8 14.95 27.6 10.71 Flux BY1 7 0.00 0.38 15.31 8.16 18.95 15.46 41.74 4.48 Fuel J1 8 1.33 8.11 21.25 8.91 17.94 13.97 28.49 3.31 Return to mining 1 9 2.90 4.10 16.50 9.70 20.30 19.10 27.40 25.16

[0313] 2) Calculate the particle size distribution of the mixture: Based on the proportions Pi of all individual raw materials (i is the raw material number, i is an integer from 1 to n) shown in Table 9.1, calculate the content of particle sizes -0.5mm, 0.5-1mm, 1-2mm, 2-3.15mm, 3.15-5mm, 5-6.3mm, and +6.3mm in the mixture, and quantify the weight percentage of each particle size as W. -0.5 W 0.5-1 W 1-2 W 2-3.15 W 3.15-5 W 5-6.3 W +6.3 (Calculation results are shown in Table 9.2). The calculation method is the same for each particle size of the mixture. The following calculation uses W as an example. -0.5 and W 0.5-1 Taking the calculation as an example, the calculation formulas are as follows:

[0314]

[0315]

[0316] Table 9.2 Calculated weight percentage of each particle size in the mixture, wt%

[0317] <![CDATA[W +6.3 ]]> <![CDATA[W 5-6.3 ]]> <![CDATA[W 3.15-5 ]]> <![CDATA[W 2-3.15 ]]> <![CDATA[W 1-2 ]]> <![CDATA[W 0.5-1 ]]> <![CDATA[W -0.5 ]]> Mixture 8.39 3.16 13.86 6.54 14.55 11.97 41.54

[0318] 3) Determine whether the particle size distribution of the granulated mixture can be predicted using this method: Table 9.2 shows that the particle size distribution of the mixture W -0.5 Since the percentage is 41.54% (>40%), this method cannot be used for prediction.

[0319] Example 10

[0320] The present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, provides a method for predicting the particle size distribution of sintered mixtures after granulation as described in Examples 1, 3, 4, 5, 6, 7, 8, or 9.

[0321] This invention can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented in whole or in part as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0322] It will be readily understood by those skilled in the art that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, combinations, substitutions, improvements, etc., made under the spirit and principles of the present invention are included within the protection scope of the present invention.

Claims

1. A method for predicting the particle size distribution of sintered mixtures after granulation, characterized in that, Includes the following steps: The initial particle size distribution of the sintering mixture, which is composed of n kinds of single raw materials in their respective proportions, is obtained. The initial particle size distribution divides the raw material particles into fine particles smaller than a first preset particle size threshold and coarse particles larger than the first preset particle size threshold. Determine whether the total weight percentage of all fine particles in the sintered mixture is not greater than a preset aggregation threshold; If the judgment result is yes, then a particle growth volume ratio is calculated based on a set of physical parameters pre-determined for each individual raw material. Based on the particle growth volume ratio and the initial particle size of the coarse particles, the target particle size of the coarse particles after granulation is predicted. The final particle size distribution of the sintered mixture after granulation is determined based on the target particle size and the weight percentage of fine particles that are not adhered after granulation.

2. The method according to claim 1, characterized in that, The set of physical parameters includes at least: the apparent density of each individual raw material, the bulk density of the fine particles of each individual raw material in the densest state, and the adhesion ratio of the fine particles of each individual raw material during granulation.

3. The method according to claim 2, characterized in that, The calculated particle growth volume ratio V % The steps include: Based on the respective proportions Pi of the n single raw materials and their corresponding physical parameters, the weighted average apparent density ρ, the weighted average densest bulk density Vm of the fine particles, and the weighted average adhesion ratio Ad of the fine particles are calculated. The particle growth volume ratio V is determined based on the following logical relationship. % The particle growth volume ratio V % W, the total weight percentage of all fine particles in the sintered mixture fine The weighted average adhesion ratio Ad, the weighted average densest bulk density Vm, and the weighted average apparent density ρ are directly proportional to the product of these components and inversely proportional to the total weight percentage of all coarse particles in the sintered mixture.

4. The method according to claim 3, characterized in that, The particle growth volume ratio V % Calculate using the following formula: V % =W fine *Ad*Vm*ρ / (100-W fine ) / 100.

5. The method according to claim 1 or 4, characterized in that, The step of predicting the target particle size DL of coarse particles after granulation is calculated using the following formula: DL = (1 + V) % )^(1 / 3)×D;where D is the initial particle size of the coarse particles.

6. The method according to claim 1, characterized in that, The step of determining the final particle size distribution further includes calculating the weight percentage of fine particles that are not adhered after granulation; the calculation steps for the weight percentage of fine particles that are not adhered are as follows: for each single raw material, multiply its fine particle weight percentage, blending ratio and (100 - adhesion ratio) to obtain the contribution of unadheded fine particles of that raw material; and then sum the contribution of unadheded fine particles of all single raw materials.

7. The method according to claim 1, characterized in that, The first preset particle size threshold is 0.5 mm, and the preset aggregation threshold is 40%.

8. A system for predicting the particle size distribution of sintered mixtures after granulation, characterized in that, include: The data acquisition unit is used to acquire the initial particle size distribution of a sintering mixture composed of n kinds of single raw materials in their respective proportions, and a set of physical parameters pre-determined for each kind of single raw material; the initial particle size distribution divides the raw material particles into fine particles smaller than a first preset particle size threshold and coarse particles larger than the first preset particle size threshold. The processing unit, connected to the data acquisition unit, is used to determine whether the total weight percentage of all fine particles in the sintering mixture is not greater than a preset aggregation threshold. If the determination result is yes, a particle growth volume ratio is calculated based on the set of physical parameters, and the target particle size of the coarse particles after granulation is predicted based on the particle growth volume ratio and the initial particle size of the coarse particles. The prediction result generation unit, connected to the processing unit, is used to generate the final particle size distribution of the sintered mixture after granulation based on the target particle size and the weight percentage of fine particles that are not adhered after granulation.

9. The system according to claim 8, characterized in that, The set of physical parameters includes at least: the apparent density of each individual raw material, the bulk density of the fine particles of each individual raw material in the densest state, and the adhesion ratio of the fine particles of each individual raw material during granulation.

10. The system according to claim 9, characterized in that, The processing unit is configured as follows: Based on the respective proportions and corresponding physical parameters of the n single raw materials, the weighted average apparent density, the weighted average densest bulk density of the fine particles, and the weighted average adhesion ratio of the fine particles are calculated. The particle growth volume ratio is determined according to the following logical relationship: the particle growth volume ratio is directly proportional to the product of the total weight percentage of all fine particles in the sintered mixture, the weighted average adhesion ratio, the weighted average densest bulk density, and the weighted average apparent density, and is inversely proportional to the total weight percentage of all coarse particles in the sintered mixture.

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