A method and system for optimizing the amount of bentonite used in a pellet feed

Abstract

The application discloses a kind of pellet burdening bentonite dosage optimization method and system.The method determines iron concentrate cementation demand based on the specific surface area of air permeation method and geometric specific surface area and iron concentrate moisture, determines bentonite cementation capacity based on bentonite montmorillonite content, gum price and mixed material target moisture;Accordingly, the theoretical dry basis dosage of bentonite is determined, the candidate dry basis dosage of bentonite that meets the green ball performance range is generated and screened;Determine the mass of silicon dioxide and calcium oxide before flux addition, determine the candidate dry basis dosage of flux and predict the pellet composition, form the candidate burdening scheme;From it, the target burdening scheme is obtained, the burdening set value is determined and the feeding equipment is controlled.The application determines the candidate dry basis dosage of bentonite with the change of iron concentrate cementation demand and bentonite cementation capacity, and brings the change of candidate dry basis dosage of bentonite into the calculation of candidate dry basis dosage of flux and predicted pellet composition, to improve the correspondence of green ball performance and pellet composition control.

Description

Technical Field

[0001] This invention relates to the field of iron and steel metallurgy technology, specifically to a method and system for optimizing the amount of bentonite used in pellet batching. Background Technology

[0002] Pellet production is a process in which raw materials such as iron concentrate, binder, and flux are mixed, pelletized, dried, preheated, and calcined according to a set ratio to obtain finished pellets. The particle size distribution, specific surface area, moisture content, and chemical composition of the iron concentrate affect particle wetting, interparticle liquid bridge formation, and the internal pore structure of the green pellets. Bentonite, a commonly used binder in pellet production, affects the drop strength, compressive strength, and integrity of the green pellets during the drying process due to its mineral composition and colloidal properties. Simultaneously, both bentonite and flux introduce gangue components into the pellet mixture, thus affecting the silica content, basicity, and total iron content of the finished pellets. Therefore, the amount of bentonite added must not only meet the performance requirements for green pellet formation and subsequent transportation but also be coordinated with the requirements for controlling the chemical composition of the pellets.

[0003] In existing pelletizing processes, the bentonite addition ratio is typically set based on the source of iron concentrate, particle size analysis results, and historical production experience. This ratio is then adjusted based on test results such as green pellet drop strength and compressive strength. When the source or batch of iron concentrate changes, operators usually adjust the bentonite addition ratio based on changes in the proportion of undersized particles, moisture content, and green pellet quality. For the chemical composition of the pellets, the addition ratio of the corresponding raw materials is adjusted based on the test results of iron concentrate, bentonite, and flux, as well as production indicators such as target basicity and target silica content. Some production lines use particle size analysis equipment, component analysis equipment, and automatic batching systems to obtain raw material status and issue feed settings, thereby improving batching adjustment efficiency.

[0004] However, the pelletizing characteristics of iron concentrate are not only related to the proportion of undersized particles, but are also affected by factors such as particle morphology, surface condition, and moisture content. Even if iron concentrate from different sources or batches has similar particle size results, the binding requirements for forming green pellets may still differ. The mineral composition and colloidal properties of bentonite from different batches may also vary, resulting in different binding effects with the same dosage. Setting the bentonite dosage solely based on iron concentrate particle size indicators or historical experience is insufficient to adapt to the combined changes in iron concentrate pelletizing characteristics and bentonite binding properties, easily leading to insufficient or excessive bentonite dosage. Furthermore, when changing the bentonite dosage to meet green pellet performance requirements, the gangue composition introduced by the bentonite will also change accordingly, potentially causing the silica content, alkalinity, and total iron grade of the pellets to deviate from control requirements. This results in mutual influence between green pellet performance adjustment and pellet chemical composition adjustment, increasing the likelihood of repeated corrections to the batching parameters. Summary of the Invention

[0005] The main objective of this invention is to provide a method and system for optimizing the amount of bentonite used in pelleting, in order to solve the technical problem that existing pelleting methods are difficult to adapt to batch variations in the pelletizing characteristics of iron concentrate and the binding properties of bentonite, resulting in a mismatch between the amount of bentonite added and the actual pelletizing conditions of the current raw materials, and causing mutual interference between the control of green pellet performance and the control of pellet chemical composition.

[0006] To achieve the above objectives, the present invention provides a method for optimizing the amount of bentonite used in pellet formulation, comprising the following steps: S1. Obtain the dry basis amount of the iron concentrate to be mixed, the dry basis amount range of the flux, raw material data, target moisture content of the mixture, green pellet performance range, and pellet composition range; wherein, the raw material data includes the particle size distribution, permeability specific surface area, moisture and dry basis composition data of the iron concentrate, the montmorillonite content, resin value, moisture and dry basis composition data of the bentonite, and the moisture and dry basis composition data of the flux. S2. Determine the geometric specific surface area based on the particle size distribution; determine the iron concentrate bonding requirement based on the pre-calibrated relationship between the air permeability specific surface area and the geometric specific surface area and the moisture content of the iron concentrate; and determine the bentonite bonding capacity based on the montmorillonite content, the colloid value, and the target moisture content of the mixture. S3. Determine the theoretical dry basis amount of bentonite based on the iron concentrate cementing requirements, the bentonite cementing capacity, and the dry basis amount of the iron concentrate to be prepared. Generate multiple candidate dry basis amounts of bentonite. Determine the predicted pelletizing performance of each candidate dry basis amount of bentonite and retain the candidate dry basis amounts of bentonite that meet the pelletizing performance range. S4. For each retained candidate bentonite dry basis dosage, based on the dry basis dosage of the iron concentrate to be prepared, the retained candidate bentonite dry basis dosage, and the dry basis composition data of the iron concentrate and bentonite, determine the silica and calcium oxide mass before flux addition; based on the silica mass, the calcium oxide mass, the dry basis composition data of the flux, the flux dry basis dosage range, and the pellet composition range, determine the candidate flux dry basis dosage, and based on the dry basis dosage of each raw material and the corresponding dry basis composition data, determine the predicted pellet composition to form a candidate batching scheme; S5. Obtain the target batching scheme from the candidate batching schemes whose predicted green pellet performance meets the green pellet performance range and whose predicted pellet composition meets the pellet composition range. Determine the batching set value according to the target batching scheme and the moisture content of each raw material, and control the feeding equipment to feed according to the batching set value.

[0007] Furthermore, in step S2, determining the bonding requirements of the iron concentrate specifically includes the following steps: Based on the particle size distribution, obtain the mass percentage and representative particle size corresponding to multiple particle size intervals; The surface area contribution of each particle size range is determined based on the mass percentage and representative particle size of each particle size range, and the geometric specific surface area is determined based on the surface area contribution of each particle size range. The surface condition correction amount is determined based on the pre-calibrated relationship between the air permeability specific surface area and the geometric specific surface area; The bonding requirements of the iron concentrate are determined based on the surface condition correction amount and the moisture content of the iron concentrate.

[0008] Further, in step S2, determining the bonding capacity of the bentonite specifically includes the following steps: The foundation bonding capacity of bentonite is determined based on the montmorillonite content. Based on the colloidal value, the cementing capacity of the bentonite foundation is corrected by the colloidal state to obtain the corrected cementing capacity. The bentonite activation correction amount is determined based on the target moisture content of the mixture; The bentonite cementing capacity is determined based on the modified cementing capacity and the bentonite activation correction amount.

[0009] Furthermore, in step S3, retaining the amount of bentonite candidate dry basis material that conforms to the aforementioned green pellet performance range specifically includes the following steps: Obtain the bentonite feeding accuracy, and generate multiple candidate bentonite dry basis amounts based on the theoretical dry basis amount of bentonite and the bentonite feeding accuracy. The predicted green pellet drop performance and predicted green pellet compressive strength are determined based on the dry basis amount of each candidate bentonite, the iron concentrate bonding requirement and the bentonite bonding capacity. The amount of bentonite candidate dry basis that meets both the predicted green ball drop performance and the predicted green ball compressive strength within the range of the green ball performance is selected as the retained amount of bentonite candidate dry basis.

[0010] More preferably, after step S3, the following steps are also included: Obtain the burst temperature range and the pre-calibrated burst temperature screening relationship; Based on the particle size distribution of the iron concentrate, the specific surface area of ​​the air permeability method, the moisture content of the mixture, and the amount of each retained bentonite candidate dry basis, the corresponding predicted bursting temperature is determined using the bursting temperature screening relationship. Based on the predicted bursting temperature and the bursting temperature range, the remaining candidate dry basis amounts of bentonite are screened to obtain candidate dry basis amounts of bentonite that meet the green pellet performance range and the bursting temperature range.

[0011] Further, in step S4, determining the amount of the candidate dry flux specifically includes the following steps: For each retained candidate bentonite dry basis dosage, the mass of silica brought in by the bentonite is determined based on the retained candidate bentonite dry basis dosage and the dry basis composition data of the bentonite. The mass of silicon dioxide and calcium oxide brought in by the iron concentrate are determined based on the dry basis weight of the iron concentrate to be prepared and the dry basis composition data of the iron concentrate. Based on the mass of silica brought in by the bentonite, the mass of silica and calcium oxide brought in by the iron concentrate, and the dry basis composition data of the flux, the candidate dry basis amount of the flux is determined within the range of the flux dry basis amount.

[0012] Furthermore, in step S4, forming the candidate ingredient scheme specifically includes the following steps: The amount of each raw material dry basis is determined based on the dry basis amount of the iron concentrate to be prepared, the amount of bentonite candidate dry basis, and the amount of flux candidate dry basis. The predicted pellet composition is determined based on the dry basis dosage of each of the raw materials and the corresponding dry basis component data. The combination of dry basis amounts of each raw material that conforms to the predicted pellet composition range is determined as the candidate formulation.

[0013] Furthermore, in step S5, determining the ingredient setting value specifically includes the following steps: Obtain the target dry basis amounts of iron concentrate, bentonite, and flux in the target batching scheme; Based on the moisture content of the iron concentrate, bentonite, and flux, the corresponding target dry basis dosage is converted into the corresponding wet basis dosage. The feed setting value of the corresponding feeding device is determined according to the amount of wet base used.

[0014] Furthermore, the following steps are included after step S5: To obtain actual green pellet performance and actual pellet composition; The process of determining the iron concentrate cementing requirement or the bentonite cementing capacity based on the deviation between the actual green pellet performance and the predicted green pellet performance; The process of determining the predicted pellet composition is corrected based on the deviation between the actual pellet composition and the predicted pellet composition.

[0015] The present invention also provides a bentonite dosage optimization system for pellet batching, which applies the bentonite dosage optimization method for pellet batching as described above, including a data acquisition module, a cementation requirement determination module, a cementation capacity determination module, a bentonite candidate dosage determination module, a component linkage calculation module, and a feeding control module. The data acquisition module is used to acquire the dry basis amount of iron concentrate to be mixed, the range of dry basis amount of flux, raw material data, target moisture content of the mixture, range of green pellet performance, and range of pellet composition. The bonding requirement determination module is used to determine the bonding requirement of iron concentrate based on the particle size distribution, the air permeability specific surface area, and the moisture content of the iron concentrate. The cementing capacity determination module is used to determine the cementing capacity of bentonite based on the montmorillonite content, the resin value, and the target moisture content of the mixture. The bentonite candidate dosage determination module is used to determine the theoretical dry basis dosage of bentonite, and to generate and screen candidate dry basis dosages of bentonite. The component linkage calculation module is used to determine the candidate dry basis amount of flux, predict the pellet composition and candidate batching scheme; The feeding control module is used to determine the batching set value according to the target batching scheme and the moisture content of each raw material, and to control the feeding equipment to feed according to the batching set value.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention first determines the cementing requirements of iron concentrate, and then determines the cementing capacity of bentonite. This allows the bentonite dosage to be matched to the pelletizing characteristics of iron concentrate and batch-specific performance variations of bentonite, rather than relying solely on fixed empirical ratios or single particle size indicators. By determining the candidate dry basis dosage of bentonite based on the iron concentrate cementing requirements, bentonite cementing capacity, and the dry basis amount of the iron concentrate to be prepared, and then screening based on predicted green pellet performance, this invention reduces the fluctuations in green pellet strength caused by insufficient bentonite addition and the increase in gangue content caused by excessive addition. Furthermore, by considering the retained candidate dry basis dosages of bentonite… The method calculates the mass of silica and calcium oxide before flux addition, and determines the candidate dry basis amount of flux and the predicted pellet composition accordingly. This allows the silica introduced by changes in bentonite dosage to be included in the flux dosage and pellet composition verification process, reducing repeated corrections when bentonite and flux adjustments are performed separately. By determining the target batching scheme from candidate batching schemes where both predicted green pellet performance and predicted pellet composition meet the corresponding ranges and converting the batching setpoints, the correlation between bentonite addition, green pellet performance, and finished pellet composition can be improved. This invention achieves coordinated ratio optimization of iron concentrate, bentonite, and flux by rapidly analyzing the particle size distribution, permeability specific surface area, moisture, and composition of iron concentrate, the montmorillonite content, resin value, moisture, and composition of bentonite, and the flux. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a method for optimizing the amount of bentonite used in pelleting according to an embodiment of the present invention.

[0019] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0022] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0023] Furthermore, the use of terms such as "first" and "second" in this invention is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature. Additionally, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. When the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed by this invention.

[0024] The technical solution of this application will be further explained below in conjunction with a chain grate machine-rotary kiln pelletizing production line. The sampling period, performance range, pellet composition range, equipment accuracy, and model parameters below are all exemplary parameters and do not indicate that field test results have been obtained; in formal implementation, they should be confirmed based on the production line equipment capacity, raw material inspection report, pelletizing test results, and product quality standards.

[0025] In this embodiment, the raw materials for pelletizing include iron concentrate, bentonite, and flux. The iron concentrate can be a single type of iron concentrate or a mixture of multiple iron concentrates in a predetermined ratio. The flux can be limestone, quicklime, dolomite, or other raw materials used to adjust the basicity of the pellets. The iron concentrate, bentonite, and flux are fed into the mixing equipment via corresponding feeding devices, and the discharge from the mixing equipment enters the pelletizing equipment. The feeding device can be a weighing feeder, a screw feeder, or a batching belt scale. The control terminal of the feeding device is electrically or communicatively connected to the production control system via an industrial network.

[0026] The production control system includes a data acquisition module, a cementation requirement determination module, a cementation capacity determination module, a bentonite candidate dosage determination module, a component linkage calculation module, a feed control module, and a feedback correction module. An automatic sampling device is installed at the iron concentrate sampling location, with its outlet connected to the inlet of the sampling device. The sampling device divides the same total sample into particle size analysis samples, air permeability specific surface area analysis samples, moisture analysis samples, and chemical composition analysis samples. Each sample has the same sample identification and sampling time.

[0027] Please see Figure 1 This embodiment provides a method for optimizing the amount of bentonite used in pellet formulation, including the following steps: S1. Obtain the dry basis amount of the iron concentrate to be mixed, the dry basis amount range of the flux, raw material data, target moisture content of the mixture, green pellet performance range, and pellet composition range; wherein, the raw material data includes the particle size distribution, permeability specific surface area, moisture and dry basis composition data of the iron concentrate, the montmorillonite content, resin value, moisture and dry basis composition data of the bentonite, and the moisture and dry basis composition data of the flux.

[0028] The dry basis quantity of iron concentrate to be prepared is determined by the production control system according to the target dry basis processing volume within this batching cycle, or calculated based on the wet basis feed rate and moisture content of the iron concentrate. In this embodiment, 100 tons / hour is used as an exemplary calculation benchmark for the dry basis quantity of iron concentrate to be prepared.

[0029] The particle size distribution of the iron concentrate was obtained using a particle size analyzer. After processing the sample under predetermined dispersion conditions, the mass percentage and representative particle size of multiple particle size ranges were obtained. For example, the particle size ranges included those less than 45 micrometers, 45 micrometers to 74 micrometers, and those greater than 74 micrometers; alternatively, the complete particle size distribution output by the particle size analyzer could be used. The air permeability specific surface area was obtained using an air permeability specific surface area analyzer. The analytical samples were measured under uniform drying conditions, sample weight, and material layer porosity to ensure the comparability of data from different batches.

[0030] The dry basis composition data of the iron concentrate includes at least the total iron content and the silicon dioxide content, and may include the calcium oxide content if necessary. In this embodiment, the iron concentrate has a -200 mesh content of 88%, a total iron content of 68.5%, a silicon dioxide content of 3.5%, and a moisture content of 8.0%. The dry basis composition data of the bentonite includes at least the silicon dioxide content, and preferably also includes the contents of alumina, calcium oxide, and magnesium oxide. The dry basis composition data of the flux includes at least the calcium oxide content and the silicon dioxide content.

[0031] Data on montmorillonite content, resin value, moisture content, and dry basis composition of bentonite can be obtained from incoming inspection, batch inspection, or valid quality reports in the laboratory information system. Bentonite batch records must include at least the batch identifier, montmorillonite content, resin value, moisture content, silica content, testing time, and expiration date. When switching batches in the bentonite silo, the data acquisition module synchronously updates the corresponding raw material data for that batch.

[0032] In this embodiment, iron concentrate is sampled every 30 minutes, and particle size, moisture, and chemical composition analysis are completed within minutes after sampling. The air permeability specific surface area is measured every cycle; when on-site analysis capabilities are not suitable for cycle-by-cycle measurement, measurements can be taken based on iron concentrate source, silo, or batch, and the current air permeability specific surface area is retrieved within the batch's validity period. A re-measurement is triggered when the iron concentrate source changes, the particle size distribution exceeds the applicable range of the pre-calibrated relationship, or the predicted green pellet performance continuously deviates from the actual green pellet performance.

[0033] In this embodiment, the target moisture content of the mixture refers to the moisture content that the mixture should reach before entering the pelletizing equipment, used to determine the activation state and cementing effect of bentonite during the pelletizing process. The target moisture content is set by engineers on the HMI interface based on the characteristics of iron concentrate, the water absorption of bentonite, and production experience. An online moisture detector at the mixture outlet monitors the actual moisture content of the mixture in real time. The deviation between the actual moisture content and the target moisture content is used to adjust the water addition amount in the mixing water addition device or the drying water amount in the concentrate drying stage, so that the mixture moisture content approaches the target moisture content. The green pellet performance range includes the green pellet drop performance range and the green pellet compressive strength range. For example, the green pellet drop performance is not less than 3 drops / 0.5 meters, and the green pellet compressive strength is not less than 10 N / pellet. Green pellet drop performance usually corresponds to the industry-standard "green pellet drop strength" or "drop count". Green pellet compressive strength usually corresponds to "green pellet compressive strength" or "single pellet compressive strength". The pellet composition range includes the range of silica content, basicity, and total iron content. For example, the silica content is 4.5% to 5.2%, the basicity is 0.25 to 0.35, and the total iron content is not less than 64.0%. All of the above ranges should be confirmed according to the actual quality standards of the production line.

[0034] In this step, the dry basis weight of the iron concentrate to be mixed, the moisture content of each raw material, and the dry basis composition data of each raw material are placed in the same batching calculation cycle, thereby avoiding the composition calculation deviation caused by mixing wet basis weight and dry basis weight.

[0035] S2. Determine the geometric specific surface area based on the particle size distribution, determine the iron concentrate bonding requirement based on the pre-calibrated relationship between the air permeability specific surface area and the geometric specific surface area and the moisture content of the iron concentrate, and determine the bentonite bonding capacity based on the montmorillonite content, the colloid value and the target moisture content of the mixture.

[0036] Specifically, the particle size distribution of iron concentrate is divided into multiple particle size intervals. The mass percentage of the j-th particle size interval is... The represented particle size is The density of iron concentrate particles is The particle shape correction factor is Geometric specific surface area Determine by the following formula: Where n represents the number of particle size ranges. The particle density of iron concentrate ranges from 4.5 g / cm³ to 5.2 g / cm³. The particle shape correction factor is not based on an unverified fixed theoretical value, but is calibrated based on the particle size distribution, specific surface area by air permeability method, pelletizing performance, and image analysis results of typical iron concentrate samples.

[0037] Furthermore, the pre-calibration relationship is established using particle size distribution, geometric specific surface area, permeable specific surface area, moisture content, bentonite content, green pellet drop performance, and green pellet compressive strength of multiple iron concentrate samples as calibration samples. The calibration samples should cover at least two iron concentrate sources or batches, and preferentially include samples with similar particle size distributions but differences in permeable specific surface area. The pre-calibration relationship can be established using piecewise linear relationships, table lookup interpolation relationships, or regression relationships with monotonic constraints, and its applicable iron concentrate sources, applicable moisture ranges, sample sizes, and validation errors should be preserved.

[0038] Let the specific surface area of ​​the current iron concentrate by the air permeability method be... The reference ratio of the specific surface area to the geometric specific surface area of ​​iron concentrate using the air permeability method is [value missing]. Then the surface condition correction amount It can be determined by the following formula: The surface condition correction amount describes the degree of deviation of the current iron concentrate from the reference iron concentrate under the same particle size calculation benchmark, and does not represent the absolute true surface area of ​​the particles. When the surface condition correction amount deviates from the benchmark state, it indicates that the particle morphology, surface roughness, open pores, or fine particle adhesion state of the current iron concentrate may be different from those of the reference iron concentrate.

[0039] Iron concentrate bonding requirements Determine by the following formula: in, This refers to the surface correction relationship determined based on the surface condition correction amount. This is a wetting correction relationship determined based on the moisture content of iron concentrate. The moisture content of the iron concentrate is used. When the moisture content of the iron concentrate is in the first moisture range, the wetting correction relationship reflects the cementing requirement corresponding to insufficient liquid bridge formation on the particle surface; when the moisture content of the iron concentrate is in the second moisture range, the baseline wetting correction relationship is used; when the moisture content of the iron concentrate is in the third moisture range, the wetting correction relationship reflects the influence of bentonite water absorption and mixture pore drainage on the cementing requirement. In this embodiment, the first, second, and third moisture ranges are defined by 8.0% and 9.5%, respectively.

[0040] Furthermore, the calibration samples for the cementing capacity of bentonite include data on montmorillonite content, colloidal value, moisture content, dry basis composition, mixture moisture content, bentonite dry basis dosage, and corresponding green pellet performance from different batches of bentonite. During calibration, the basic cementing capacity is determined by the montmorillonite content, the colloidal state is corrected by the deviation of the colloidal value from the reference value of the same montmorillonite content, and the activation state of bentonite is corrected by the mixture moisture content.

[0041] Bentonite cementing capacity It can be determined by the following formula: in, To provide a reference for the cementing capacity of bentonite under target moisture conditions in a reference mixture, This refers to the montmorillonite content. For the price of gum, The moisture content of the mixture. To correct the relationship for montmorillonite content, The correction relationship between the resin value and the reference value of montmorillonite content. The activation correction relationship corresponds to the target moisture content of the mixture. In this example, the montmorillonite content is 60% to 85%, and the resin value is 40 ml / 15 g to 80 ml / 15 g.

[0042] In this embodiment, iron concentrates with similar particle size distribution but different permeability specific surface areas can meet different iron concentrate cementing requirements through the above-described method; the mineral composition, colloidal properties and moisture adaptability of different bentonite batches can be incorporated into the process of determining the cementing capacity of bentonite.

[0043] S3. Determine the theoretical dry basis amount of bentonite based on the bonding requirements of the iron concentrate, the bonding capacity of the bentonite, and the dry basis amount of the iron concentrate to be prepared. Generate multiple candidate dry basis amounts of bentonite, determine the predicted pelletizing performance of each candidate dry basis amount of bentonite, and retain the candidate dry basis amounts of bentonite that meet the range of pelletizing performance.

[0044] In this embodiment, the theoretical dry basis dosage of bentonite Determine by the following formula: in, This is the dry basis weight of the iron concentrate to be prepared. This is the conversion factor determined based on historical pelleting tests. The conversion factor is calibrated by pelleting tests under the same or similar iron concentrate sources, bentonite batches, and target moisture conditions of the mixture. Its physical meaning is to convert the relative relationship between the iron concentrate binding requirement and the bentonite binding capacity into an executable bentonite dry basis dosage.

[0045] When generating multiple candidate bentonite dry basis dosages based on the theoretical dry basis dosage, the candidate interval is determined according to the feeding accuracy and allowable adjustment range of the bentonite feeding equipment. For example, when the theoretical addition ratio is 1.80% of the dry basis amount of iron concentrate to be prepared, candidate bentonite dry basis dosages corresponding to 1.70%, 1.75%, 1.80%, 1.85%, and 1.90% can be generated at intervals of 0.05 percentage points. The above values ​​are only used to illustrate the candidate generation method; the actual candidate interval is determined by the resolution and calibration results of the feeding equipment.

[0046] Furthermore, the pre-defined green pellet performance relationship uses iron concentrate cementing requirements, bentonite cementing capacity, candidate bentonite dry basis dosage, and mixture moisture content as inputs, and predicted green pellet drop performance and predicted green pellet compressive strength as outputs. For each candidate bentonite dry basis dosage, the predicted green pellet drop performance and predicted green pellet compressive strength are determined; when both meet the green pellet performance range, the candidate bentonite dry basis dosage is retained. For example, if the predicted green pellet drop performance is 4 drops / 0.5 meters and the predicted green pellet compressive strength is 12 N / ball, and the corresponding range requirements are not less than 3 drops / 0.5 meters and 10 N / ball, respectively, the candidate dosage is retained.

[0047] Further, after step S3, the bursting temperature range and a pre-calibrated bursting temperature screening relationship are obtained. The bursting temperature screening relationship is established through offline pelleting and drying bursting tests. Its inputs include iron concentrate particle size distribution, permeable surface area, mixture moisture content, green pellet size range, and the amount of bentonite candidate dry basis material. The output is the predicted bursting temperature or whether it meets the bursting temperature range. During online batching, the bursting temperature screening relationship is queried based on the current raw material data and the retained amount of bentonite candidate dry basis material to obtain the predicted bursting temperature.

[0048] For example, the burst temperature range requires a predicted burst temperature of no less than 450 degrees Celsius. Bentonite candidates with dry basis weights whose predicted burst temperatures do not meet the burst temperature range are eliminated; only candidates with dry basis weights that meet both the green pellet performance range and the burst temperature range are retained.

[0049] This embodiment, after screening green pellets based on their drop performance and compressive strength, further screens candidate quantities based on predicted bursting temperatures. This allows for the identification of green pellets that, while possessing the mechanical strength required for transport and compaction, may crack during the drying stage of the chain grate due to obstructed internal moisture migration. By retaining candidate dry-basis quantities of bentonite with predicted bursting temperatures within the bursting temperature range, the determined target batching scheme simultaneously adapts to green pellet transport, distribution, and subsequent drying conditions. By querying a pre-calibrated bursting temperature screening relationship to obtain the predicted bursting temperature, there is no need to repeat offline pelleting and drying bursting tests in each batching cycle. This allows for timely completion of the screening of candidate dry-basis quantities of bentonite even after changes in raw material conditions, and updates to the bursting temperature screening relationship using subsequent actual bursting temperature test results.

[0050] S4. For each retained candidate bentonite dry basis amount, based on the dry basis amount of the iron concentrate to be prepared, the retained candidate bentonite dry basis amount, and the dry basis composition data of the iron concentrate and bentonite, determine the silica mass and calcium oxide mass before flux addition; based on the silica mass, the calcium oxide mass, the dry basis composition data of the flux, the range of flux dry basis amount, and the range of pellet composition, determine the candidate dry basis amount of flux, and determine the predicted pellet composition based on the dry basis amount of each raw material and the corresponding dry basis composition data, forming a candidate batching scheme.

[0051] Specifically, this step involves calculating the mass of silica and calcium oxide introduced by the iron concentrate and bentonite before flux addition for each retained candidate bentonite dosage on a dry basis. The mass of silica introduced by the bentonite is calculated separately. Determine by the following formula: in, The amount of bentonite to be retained on a dry basis. This refers to the silica content in the dry basis composition data of bentonite.

[0052] The mass of silica brought in by the iron concentrate, the mass of calcium oxide brought in by the iron concentrate, and the mass of calcium oxide brought in by the bentonite are obtained by multiplying the dry basis amount of the iron concentrate to be prepared or the retained candidate dry basis amount of bentonite by the corresponding dry basis composition data. The mass of silica brought in by the iron concentrate and the mass of calcium oxide brought in by the bentonite are added together to obtain the mass of silica before flux addition; the mass of calcium oxide brought in by the iron concentrate and the mass of calcium oxide brought in by the bentonite are added together to obtain the mass of calcium oxide before flux addition.

[0053] Further, candidate flux dry basis amounts are determined based on the mass of silica and calcium oxide before flux addition, flux dry basis composition data, flux dry basis dosage range, and pellet composition range. In one embodiment, the theoretical flux dry basis dosage is calculated back based on the basicity range within the pellet composition range, and then the intersection of the theoretical flux dry basis dosage and the flux dry basis dosage range is taken to generate candidate flux dry basis dosages. In another embodiment, multiple candidate flux dry basis dosages are generated within the flux dry basis dosage range based on the accuracy of the flux feeding equipment, and the predicted pellet composition is calculated for each candidate.

[0054] The dry basis amounts of flux candidates, iron concentrate to be prepared, and retained bentonite candidate dry basis amounts correspond to the same candidate combination. Different bentonite candidate dry basis amounts introduce different amounts of silica, thus corresponding to different flux candidate dry basis amounts.

[0055] Predicting alkalinity Determine by the following formula: Predicting silica content Determine by the following formula: Predicting total iron grade Determine by the following formula: in, The sum of the masses of calcium oxide introduced by iron concentrate, bentonite, and flux. The sum of the masses of silica introduced by iron concentrate, bentonite, and flux. This is the sum of the total iron mass brought in by each raw material. This is the sum of the dry basis masses of the iron concentrate, bentonite, and flux to be prepared. All masses use a uniform dry basis mass boundary.

[0056] In one implementation, a component transfer parameter is used to map the dry basis composition of the mixture to the composition of the finished pellets. The component transfer parameter is calibrated based on historical production data and finished pellet test results; for example, the single correction range does not exceed 5% of the parameter value before correction. When the predicted pellet composition falls within the pellet composition range, the corresponding dry basis amount of iron concentrate to be mixed, the candidate dry basis amount of bentonite, and the candidate dry basis amount of flux are combined to form a candidate batching scheme.

[0057] This embodiment determines the mass of silica and calcium oxide introduced by iron concentrate and bentonite before flux addition for each retained candidate bentonite dry basis dosage, and determines the corresponding candidate flux dry basis dosage within the flux dry basis dosage range accordingly. This allows the silica introduced by changes in the bentonite candidate dry basis dosage to be directly transferred to the flux dosage calculation process, avoiding deviations in predicted basicity, predicted silica content, and predicted total iron grade from the pellet composition range caused by relying solely on fixed bentonite addition ratios or fixed flux dosages for composition control. By placing the dry basis mass and dry basis composition data of the flux under a unified dry basis mass boundary for calculating and predicting the pellet composition, the impact of raw material moisture differences on the composition calculation can be reduced. By matching the candidate dry basis dosage of each bentonite with the candidate dry basis dosage of the flux to form a candidate batching scheme, it is possible to screen raw material combinations that meet the pellet composition range while satisfying the green pellet performance range, reducing the repeated corrections to the batching caused by adjusting the dosage of bentonite and then separately adjusting the flux. By using the test results of the finished pellets to correct the composition transfer parameters, the predicted pellet composition can be gradually adapted to changes in raw material batches and production status.

[0058] S5. Obtain the target batching scheme from the candidate batching schemes whose predicted green pellet performance meets the green pellet performance range and whose predicted pellet composition meets the pellet composition range. Determine the batching set value according to the target batching scheme and the moisture content of each raw material, and control the feeding equipment to feed according to the batching set value.

[0059] Specifically, when multiple candidate batching schemes exist, the target batching scheme is determined according to preset selection rules. These preset selection rules may include prioritizing candidate batching schemes with lower bentonite dry basis content, predicted pellet composition falling within the middle range of pellet composition, and flux dry basis content falling within the range of flux dry basis content. These rules should be determined based on quality objectives, raw material costs, and equipment stability before the production control system is put into operation.

[0060] Furthermore, the target dry basis quantities of iron concentrate, bentonite, and flux in the target batching scheme are first obtained. Then, the target wet basis quantities are calculated based on the moisture content of each raw material. Finally, the batching settings for the corresponding feeding equipment are determined. For example, if the target dry basis quantity of bentonite is 1.80 tons / hour and the bentonite moisture content is 10.0%, the corresponding wet basis quantity is calculated based on the dry basis quantity and moisture content. The iron concentrate and flux are calculated in the same way. Each target wet basis quantity is converted into the corresponding mass flow rate settings for the iron concentrate feeding equipment, bentonite feeding equipment, and flux feeding equipment, and then distributed through the industrial network.

[0061] The feeding equipment can provide feedback on the actual mass flow rate at a feedback cycle of 1 to 5 seconds. If the actual mass flow rate does not fall within the allowable deviation range of the batching setpoint within a continuous preset time period, the production control system maintains the previous valid batching setpoint and outputs a manual verification prompt. The allowable deviation range and the continuous preset time period are determined based on the actual response characteristics of the feeding equipment.

[0062] Further, after step S5, the actual green pellet properties and actual pellet composition are obtained. The actual green pellet properties include actual green pellet drop performance and actual green pellet compressive strength; the actual pellet composition includes actual silica content, actual basicity, and actual total iron content. The deviation between the actual green pellet properties and the predicted green pellet properties is used to correct the process for determining the iron concentrate cementing requirements or the bentonite cementing capacity; the deviation between the actual pellet composition and the predicted pellet composition is used to correct the process for determining the predicted pellet composition.

[0063] When multiple iron concentrate batches exhibit unidirectional green pellet performance deviations while bentonite batches remain unchanged, priority should be given to correcting the pre-calibrated relationship between the permeability specific surface area and geometric specific surface area, or the process for determining the iron concentrate's cementing requirements. When the iron concentrate state is basically consistent but green pellet performance deviations occur after switching bentonite batches, priority should be given to correcting the process for determining the bentonite's cementing capacity. The deviation between the actual pellet composition and the predicted pellet composition is used to correct component transfer parameters, the validity of raw material dry basis composition data, or related parameters for dry basis conversion, and is not directly used to correct the bentonite's cementing capacity.

[0064] This embodiment uses the deviation between actual and predicted green pellet performance as the correction basis for determining the iron concentrate cementing requirements or bentonite cementing capacity, and the deviation between actual and predicted pellet composition as the correction basis for determining the predicted pellet composition. This allows the deviations in green pellet mechanical strength and pellet chemical composition to act on parameter sets with corresponding physical meanings. Furthermore, it corrects the pre-calibration relationship between permeable surface area and geometric surface area, or the iron concentrate cementing requirements determination process, based on the unidirectional green pellet performance deviations from multiple iron concentrate batches while keeping the bentonite batches constant. Furthermore, when the iron concentrate is in a basically consistent state but bentonite batches change and green pellet performance deviations occur, the process of determining the bentonite's binding capacity can be corrected. This allows for the identification of possible sources of green pellet performance deviations based on changes in raw material batches. By using actual pellet composition deviations to correct component transfer parameters, the validity of raw material dry basis composition data, or dry basis conversion parameters, rather than using them to correct bentonite binding capacity, the possibility of deviations caused by raw material composition detection, dry basis conversion, or calcination component transfer being incorrectly transmitted to the bentonite dosage calculation process can be reduced. This improves the adaptability of subsequent batching settings to green pellet performance and pellet composition.

[0065] This embodiment also provides a bentonite dosage optimization system for pellet batching, including a data acquisition module, a cementation requirement determination module, a cementation capacity determination module, a bentonite candidate dosage determination module, a component linkage calculation module, and a feeding control module.

[0066] Specifically, the data acquisition module is connected to the iron concentrate sampling device, the sample distribution device, the particle size analysis equipment, the air permeability specific surface area analysis equipment, the moisture analysis equipment, the component analysis equipment, the bentonite batch database, the flux batch database, and the production control system. It is used to acquire the dry basis amount of the iron concentrate to be mixed, the dry basis amount range of the flux, the raw material data, the target moisture content of the mixture, the green pellet performance range, and the pellet composition range.

[0067] The cementing requirement determination module communicates with the data acquisition module to determine the geometric specific surface area based on particle size distribution, and to determine the cementing requirement of iron concentrate based on the air permeability specific surface area, geometric specific surface area, and iron concentrate moisture content. The cementing capacity determination module also communicates with the data acquisition module to determine the bentonite cementing capacity based on montmorillonite content, cementitious value, and the target moisture content of the mixture.

[0068] The bentonite candidate dosage determination module is communicatively connected to the cementing requirement determination module and the cementing capacity determination module, respectively. It is used to determine the theoretical dry basis dosage of bentonite, generate candidate dry basis dosages of bentonite, and screen and retain the candidate dry basis dosages of bentonite based on predicted green pellet performance. The composition linkage calculation module is communicatively connected to the bentonite candidate dosage determination module and the data acquisition module. It is used to determine the silica and calcium oxide mass before flux addition based on the retained candidate dry basis dosages of bentonite, determine the candidate dry basis dosage of flux and predict the pellet composition, and form a candidate batching scheme. The feeding control module is communicatively connected to the composition linkage calculation module and electrically connected to the control terminals of the iron concentrate feeding equipment, bentonite feeding equipment, and flux feeding equipment. It is used to determine the batching setpoints based on the target batching scheme and the moisture content of each raw material, and control the corresponding feeding equipment to feed according to the batching setpoints.

[0069] By means of the above method, the requirements for iron concentrate cementing, the cementing capacity of bentonite, the screening of green pellet performance and the calculation of pellet composition are connected in the same batching calculation. The silica corresponding to the candidate dry basis amount of bentonite is brought into the mass transfer to the process of determining the candidate dry basis amount of flux, so that the feeding equipment obtains the batching set value corresponding to the current raw material state.

[0070] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for optimizing the amount of bentonite used in pelleting, characterized in that, Includes the following steps: S1. Obtain the dry basis amount of the iron concentrate to be mixed, the dry basis amount range of the flux, raw material data, target moisture content of the mixture, green pellet performance range, and pellet composition range; wherein, the raw material data includes the particle size distribution, permeability specific surface area, moisture and dry basis composition data of the iron concentrate, the montmorillonite content, resin value, moisture and dry basis composition data of the bentonite, and the moisture and dry basis composition data of the flux. S2. Determine the geometric specific surface area based on the particle size distribution; determine the iron concentrate bonding requirement based on the pre-calibrated relationship between the air permeability specific surface area and the geometric specific surface area and the moisture content of the iron concentrate; and determine the bentonite bonding capacity based on the montmorillonite content, the colloid value, and the target moisture content of the mixture. S3. Determine the theoretical dry basis amount of bentonite based on the iron concentrate cementing requirements, the bentonite cementing capacity, and the dry basis amount of the iron concentrate to be prepared. Generate multiple candidate dry basis amounts of bentonite. Determine the predicted pelletizing performance of each candidate dry basis amount of bentonite and retain the candidate dry basis amounts of bentonite that meet the pelletizing performance range. S4. For each retained candidate bentonite dry basis dosage, based on the dry basis dosage of the iron concentrate to be prepared, the retained candidate bentonite dry basis dosage, and the dry basis composition data of the iron concentrate and bentonite, determine the silica and calcium oxide mass before flux addition; based on the silica mass, the calcium oxide mass, the dry basis composition data of the flux, the flux dry basis dosage range, and the pellet composition range, determine the candidate flux dry basis dosage, and based on the dry basis dosage of each raw material and the corresponding dry basis composition data, determine the predicted pellet composition to form a candidate batching scheme; S5. Obtain the target batching scheme from the candidate batching schemes whose predicted green pellet performance meets the green pellet performance range and whose predicted pellet composition meets the pellet composition range. Determine the batching set value according to the target batching scheme and the moisture content of each raw material, and control the feeding equipment to feed according to the batching set value.

2. The method for optimizing the bentonite dosage in pellet feed according to claim 1, characterized in that, Step S2, determining the bonding requirements of the iron concentrate, specifically includes the following steps: Based on the particle size distribution, obtain the mass percentage and representative particle size corresponding to multiple particle size intervals; The surface area contribution of each particle size range is determined based on the mass percentage and representative particle size of each particle size range, and the geometric specific surface area is determined based on the surface area contribution of each particle size range. The surface condition correction amount is determined based on the pre-calibrated relationship between the air permeability specific surface area and the geometric specific surface area; The bonding requirements of the iron concentrate are determined based on the surface condition correction amount and the moisture content of the iron concentrate.

3. The method for optimizing the bentonite dosage in pellet feed according to claim 1, characterized in that, In step S2, determining the cementing capacity of the bentonite specifically includes the following steps: The foundation bonding capacity of bentonite is determined based on the montmorillonite content. Based on the colloidal value, the cementing capacity of the bentonite foundation is corrected by the colloidal state to obtain the corrected cementing capacity. The bentonite activation correction amount is determined based on the target moisture content of the mixture; The bentonite cementing capacity is determined based on the modified cementing capacity and the bentonite activation correction amount.

4. The method for optimizing the bentonite dosage in pellet feed according to claim 1, characterized in that, Step S3, retaining the amount of bentonite candidate dry basis that meets the performance range of the green pellets, specifically includes the following steps: Obtain the bentonite feeding accuracy, and generate multiple candidate bentonite dry basis amounts based on the theoretical dry basis amount of bentonite and the bentonite feeding accuracy. The predicted green pellet drop performance and predicted green pellet compressive strength are determined based on the dry basis amount of each candidate bentonite, the iron concentrate bonding requirement and the bentonite bonding capacity. The amount of bentonite candidate dry basis that meets both the predicted green ball drop performance and the predicted green ball compressive strength within the range of the green ball performance is selected as the retained amount of bentonite candidate dry basis.

5. The method for optimizing the bentonite dosage in pellet feed according to claim 4, characterized in that, Step S3 is followed by the following steps: Obtain the burst temperature range and the pre-calibrated burst temperature screening relationship; Based on the particle size distribution of the iron concentrate, the specific surface area of ​​the air permeability method, the moisture content of the mixture, and the amount of each retained bentonite candidate dry basis, the corresponding predicted bursting temperature is determined using the bursting temperature screening relationship. Based on the predicted bursting temperature and the bursting temperature range, the remaining candidate dry basis amounts of bentonite are screened to obtain candidate dry basis amounts of bentonite that meet the green pellet performance range and the bursting temperature range.

6. The method for optimizing the bentonite dosage in pellet feed according to claim 1, characterized in that, Step S4, determining the amount of the candidate dry flux specifically includes the following steps: For each retained candidate bentonite dry basis dosage, the mass of silica brought in by the bentonite is determined based on the retained candidate bentonite dry basis dosage and the dry basis composition data of the bentonite. The mass of silicon dioxide and calcium oxide brought in by the iron concentrate are determined based on the dry basis weight of the iron concentrate to be prepared and the dry basis composition data of the iron concentrate. Based on the mass of silica brought in by the bentonite, the mass of silica and calcium oxide brought in by the iron concentrate, and the dry basis composition data of the flux, the candidate dry basis amount of the flux is determined within the range of the flux dry basis amount.

7. The method for optimizing the bentonite dosage in pellet feed according to claim 1, characterized in that, Step S4, forming the candidate ingredient scheme specifically includes the following steps: The amount of each raw material dry basis is determined based on the dry basis amount of the iron concentrate to be prepared, the amount of bentonite candidate dry basis, and the amount of flux candidate dry basis. The predicted pellet composition is determined based on the dry basis dosage of each of the raw materials and the corresponding dry basis component data. The combination of dry basis amounts of each raw material that conforms to the predicted pellet composition range is determined as the candidate formulation.

8. The method for optimizing the bentonite dosage in pellet feed according to claim 1, characterized in that, Step S5, determining the ingredient setting value specifically includes the following steps: Obtain the target dry basis amounts of iron concentrate, bentonite, and flux in the target batching scheme; Based on the moisture content of the iron concentrate, bentonite, and flux, the corresponding target dry basis dosage is converted into the corresponding wet basis dosage. The feed setting value of the corresponding feeding device is determined according to the amount of wet base used.

9. The method for optimizing the bentonite dosage in pellet feed according to claim 1, characterized in that, Step S5 is followed by the following steps: To obtain actual green pellet performance and actual pellet composition; The process of determining the iron concentrate cementing requirement or the bentonite cementing capacity based on the deviation between the actual green pellet performance and the predicted green pellet performance; The process of determining the predicted pellet composition is corrected based on the deviation between the actual pellet composition and the predicted pellet composition.

10. A system for optimizing the bentonite dosage in pellet feed, employing the method for optimizing the bentonite dosage in pellet feed as described in any one of claims 1-9, characterized in that, It includes a data acquisition module, a cementation requirement determination module, a cementation capacity determination module, a bentonite candidate dosage determination module, a component linkage calculation module, and a feeding control module; The data acquisition module is used to acquire the dry basis amount of iron concentrate to be mixed, the range of dry basis amount of flux, raw material data, target moisture content of the mixture, range of green pellet performance, and range of pellet composition. The bonding requirement determination module is used to determine the bonding requirement of iron concentrate based on the particle size distribution, the air permeability specific surface area, and the moisture content of the iron concentrate. The cementing capacity determination module is used to determine the cementing capacity of bentonite based on the montmorillonite content, the resin value, and the target moisture content of the mixture. The bentonite candidate dosage determination module is used to determine the theoretical dry basis dosage of bentonite, and to generate and screen candidate dry basis dosages of bentonite. The component linkage calculation module is used to determine the candidate dry basis amount of flux, predict the pellet composition and candidate batching scheme; The feeding control module is used to determine the batching set value according to the target batching scheme and the moisture content of each raw material, and to control the feeding equipment to feed according to the batching set value.

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