Intelligent Optimization Method for Alumina Production Process Based on Large-Scale Industrial Model

Abstract

This invention provides an intelligent optimization method for alumina production based on a large-scale industrial model, comprising: acquiring seed flow state data at different locations within a seed decomposition system; performing particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine-grain circulation distribution; analyzing the fine-grain growth rate in each decomposition tank based on the seed circulation structure state and fine-grain circulation distribution to identify fine-grain growth driving sections; generating fine-grain growth propagation chains and abnormal decomposition driving results based on the fine-grain growth driving sections; analyzing the seed growth rate and nucleus generation rate in different decomposition tanks to determine the locally oversaturated decomposition sections of fine-grain bursts; and imposing fine-grain suppression constraints on the locally oversaturated decomposition sections; monitoring the fine-grain reflux state in the seed circulation system; and verifying the coarse-grain growth state and fine-grain suppression state in the decomposition tanks to output a decomposition control strategy that meets the particle size stability conditions.

Description

Technical Field

[0001] This invention belongs to the field of artificial intelligence technology, and more specifically, relates to an intelligent optimization method for alumina production process based on a large industrial model. Background Technology

[0002] Currently, in existing technologies, the industrial alumina production process typically involves crushing and grinding bauxite as the initial raw material, followed by high-pressure leaching, red mud sedimentation and separation, evaporation and concentration, seed crystal decomposition, aluminum hydroxide filtration, and calcination to finally produce the finished alumina product.

[0003] However, in the aforementioned process, the seed crystal decomposition process, as a necessary step in alumina production, is prone to technical problems such as product particle size loss under the scenario of fine crystal circulation and accumulation. This is because, in the seed crystal decomposition system, if a large number of fine crystals are generated in the early stages of decomposition, these fine crystals will continuously return to the decomposition tank with the seed crystal circulation. Although existing technical solutions can optimize decomposition temperature, seed crystal size, and decomposition time, under the scenario of fine crystal circulation and accumulation, the system may appear to show an increased decomposition rate, but in reality, the number of fine particles continues to increase, leading to a deterioration in the particle size of the subsequently calcined material. In this case, if the industrial large-scale model uses the short-term decomposition rate as the optimization direction, it is easy to sacrifice the stability of product particle size, causing fluctuations in the flowability and quality of the finished alumina product. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to overcome the aforementioned deficiencies and propose an intelligent optimization method for alumina production process based on a large industrial model.

[0005] The present invention adopts the following technical solution.

[0006] The first aspect of this invention discloses an intelligent optimization method for alumina production process based on a large industrial model, the method comprising: Acquire seed flow state data at different locations within the seed decomposition system, and perform particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine crystal circulation distribution; Based on the seed crystal cycle structure state and fine crystal cycle distribution, the fine crystal growth rate in each decomposition tank is analyzed to identify the fine crystal growth driving segment, and a fine crystal growth propagation chain and abnormal decomposition driving result are generated according to the fine crystal growth driving segment. Based on the fine grain growth propagation chain and abnormal decomposition driving results, the seed growth rate and nucleus generation rate in different decomposition tanks are analyzed to determine the local oversaturated decomposition section of fine grain burst, and fine grain suppression constraint is applied to the local oversaturated decomposition section. The fine crystal reflux state in the seed crystal circulation system is monitored, and the coarse crystal growth state and fine crystal suppression state in the decomposition tank are verified to output a decomposition control strategy that meets the particle size stability condition.

[0007] Furthermore, the step of acquiring seed flow state data at different locations within the seed decomposition system, and performing particle size stratification of the seed particles based on the seed flow state data to determine the seed circulation structure state and fine-grain circulation distribution, includes: Sampling points are set at the outlet of the seed circulation pump, the inlet of the decomposition tank, the underflow outlet of the decomposition tank, and the seed grading return port. The particle concentration, slurry flow rate, slurry temperature, mother liquor alkali concentration, and underflow solid content in the circulating seed flow are continuously collected at the sampling points according to the preset sampling cycle, so as to output the seed flow status data. The seed crystals at each sampling point are classified according to the set particle size threshold to determine the particle distribution in the coarse-grained, medium-grained, and fine-grained regions. The seed decomposition system includes, at different locations, the seed circulation pump outlet, the decomposition tank inlet, the decomposition tank underflow outlet, and the seed grading return outlet. The seed flow status data includes the particle concentration, slurry flow rate, slurry temperature, mother liquor alkali concentration, and underflow solid content in the circulating seed flow.

[0008] Furthermore, the step of acquiring seed flow state data at different locations within the seed decomposition system, and performing particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine-grained circulation distribution, further includes: Based on the particle distribution state of the coarse-grained region, medium-grained region and fine-grained region, the fine-grained mass ratio, seed reflux flow rate and decomposition tank feed rate in multiple consecutive seed decomposition cycles are correlated and calculated to obtain the change in the fine-grained reflux ratio. Based on the change in the fine crystal reflux ratio, the fine crystal aggregation and positioning are performed in the inlet area, stirring weak flow area, underflow discharge area and seed crystal reflux area of ​​different decomposition tanks, so as to determine the fine crystal aggregation position, fine crystal reflux ratio and medium crystal transition ratio corresponding to each decomposition tank, and to determine the fine crystal reflux direction and fine crystal accumulation intensity corresponding to each decomposition tank. The fine crystal circulation distribution is obtained by combining the fine crystal aggregation location, the fine crystal reflux ratio, and the medium crystal transition ratio. The seed crystal circulation structure state is composed of the fine crystal reflux direction and the fine crystal cumulative intensity corresponding to each decomposition cell.

[0009] Furthermore, based on the seed crystal cycle structure state and fine crystal cycle distribution, the fine crystal growth rate in each decomposition tank is analyzed to identify the fine crystal growth driving segment, and a fine crystal growth propagation chain and abnormal decomposition driving result are generated according to the fine crystal growth driving segment, including: The change in fine grain quality in the same section within the decomposition tank between adjacent sampling times is obtained, and the fine grain growth rate per unit time is calculated based on the change in fine grain quality to determine the decomposition tank section where the fine grain growth rate exceeds a set growth threshold. A reverse lookup is performed on the decomposition tank section to identify the corresponding temperature drop range, temperature drop duration, mother liquor concentration change, and seed density change, and the temperature drop range, temperature drop duration, mother liquor concentration change, and seed density change are integrated into the results of the fine crystal growth associated working condition section.

[0010] Furthermore, the step of analyzing the fine grain growth rate in each decomposition tank based on the seed crystal cycle structure state and fine grain cycle distribution to identify fine grain growth driving segments, and generating fine grain growth propagation chains and abnormal decomposition driving results based on the fine grain growth driving segments, further includes: Based on the results of the fine grain growth associated working condition section, a local abnormal decomposition section is determined, and the path is traced using the local abnormal decomposition section as the starting point of fine grain generation to obtain the fine grain growth propagation chain. The abnormal decomposition source, temperature drop section, local oversaturation section, abnormal seed density section, and reflow growth section in the fine grain growth propagation chain are extracted, and the abnormal decomposition source, temperature drop section, local oversaturation section, abnormal seed density section, and reflow growth section are integrated and output as the abnormal decomposition driving result.

[0011] Furthermore, based on the fine grain growth propagation chain and the abnormal decomposition driving results, the seed growth rate and nucleus generation rate in different decomposition tanks are analyzed to determine the locally oversaturated decomposition region of fine grain burst, and fine grain suppression constraints are applied to the locally oversaturated decomposition region, including: Calculate the seed growth rate and nucleus generation rate of the corresponding segment of the fine crystal growth propagation chain, and generate the seed nucleation and growth equilibrium result of the corresponding decomposition tank based on the seed growth rate and nucleus generation rate. Based on the seed nucleation and growth equilibrium results, the working conditions of the local abnormal decomposition section dominated by seed nucleation are reconstructed to obtain the reconstruction results.

[0012] Furthermore, the analysis of seed growth rate and nucleus generation rate in different decomposition tanks based on the fine grain growth propagation chain and abnormal decomposition driving results to determine the locally oversaturated decomposition region of fine grain burst, and the fine grain suppression constraint on the locally oversaturated decomposition region, further includes: Based on the reconstruction results, local supersaturated decomposition sections with the risk of fine crystal bursts are identified, and constraint boundaries are established for the local supersaturated decomposition sections. The constraint boundaries include the upper limit of cooling, the upper limit of fine crystal reflux, the upper limit of supersaturation driving, the lower limit of seed replenishment, and the adjustment range of mother liquor circulation. The various operations in the production process are adjusted in combination according to the aforementioned upper limit of cooling, upper limit of fine crystal reflux, upper limit of supersaturation drive, lower limit of seed replenishment, and adjustment range of mother liquor circulation, so as to achieve balanced control of the seed growth process.

[0013] Furthermore, the monitoring of the fine-grained reflux state in the seed crystal circulation system and the verification of the coarse-grained growth state and fine-grained suppression state in the decomposition tank, in order to output a decomposition control strategy that meets the particle size stability condition, includes: According to the set monitoring cycle, the seed reflux port, the grading equipment outlet, the decomposition tank inlet and the underflow outlet of the seed circulation system are continuously monitored to determine the fine crystal reflux monitoring data at each monitoring location in the seed circulation system. Based on the fine grain reflux monitoring data, the coarse grain growth state and fine grain suppression state in the decomposition tank are jointly verified to identify the circulation section with a fine grain diffusion trend, and the circulation section is subject to fine grain suppression constraint. The particle size of the aluminum hydroxide material before entering the calcination system is checked. When the particle size deviation of the aluminum hydroxide material before entering the calcination system is lower than the set deviation threshold, the current decomposition control strategy is output to the seed crystal decomposition system to obtain a decomposition control strategy that meets the particle size stability condition.

[0014] The second aspect of this invention discloses an intelligent optimization device for alumina production process based on an industrial large-scale model, used to implement the intelligent optimization method for alumina production process based on an industrial large-scale model as described in any one of the first aspects, the device comprising: The seed particle size stratification module is used to acquire seed flow state data at different locations within the seed decomposition system, and to perform particle size stratification of seed particles based on the seed flow state data in order to determine the seed circulation structure state and fine crystal circulation distribution. The fine grain growth analysis module is used to analyze the fine grain growth rate in each decomposition tank based on the seed crystal cycle structure state and fine grain cycle distribution, so as to identify the fine grain growth driving segment and generate the fine grain growth propagation chain and abnormal decomposition driving result according to the fine grain growth driving segment. The fine grain suppression and constraint module is used to analyze the seed growth rate and nucleus generation rate in different decomposition tanks based on the fine grain growth propagation chain and abnormal decomposition driving results, so as to determine the local oversaturated decomposition section of fine grain burst, and to suppress and constrain the fine grain in the local oversaturated decomposition section. The fine crystal reflux monitoring module is used to monitor the fine crystal reflux status in the seed crystal circulation system and to verify the coarse crystal growth status and fine crystal suppression status in the decomposition tank, so as to output a decomposition control strategy that meets the particle size stability conditions.

[0015] A third aspect of the present invention discloses a terminal, including a processor and a storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method described in the first aspect.

[0016] A fourth aspect of the present invention discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0017] The beneficial effects of the present invention are as follows: Compared with the prior art, the present invention has the following advantages: (1) This invention obtains seed flow state data at different locations within the seed decomposition system and performs particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine crystal circulation distribution. Subsequently, based on the seed circulation structure state and fine crystal circulation distribution, the fine crystal growth rate in each decomposition tank is analyzed to identify the fine crystal growth driving segment, and a fine crystal growth propagation chain and abnormal decomposition driving result are generated based on the fine crystal growth driving segment. In the scenario of fine crystal circulation accumulation during seed decomposition, this invention fundamentally avoids the technical problems of existing large industrial models that optimize only based on short-term decomposition rates, leading to continuous proliferation of fine particles, gradual instability of the seed circulation structure, and fluctuations in the final alumina particle size. It achieves effective identification of the fine crystal generation trend and seed circulation structure in the seed decomposition system.

[0018] (2) Based on the fine grain growth propagation chain and abnormal decomposition driving results, this invention analyzes the seed growth rate and nucleus generation rate in different decomposition tanks to determine the local oversaturated decomposition section of fine grain burst, and imposes fine grain suppression constraints on the local oversaturated decomposition section. Finally, the fine grain reflux state in the seed circulation system is monitored, and the coarse grain growth state and fine grain suppression state in the decomposition tank are verified to output a decomposition control strategy that meets the particle size stability conditions. This further realizes the long-term coordinated and stable control of the fine grain generation trend, seed circulation structure, and decomposition particle size state in the seed decomposition system, ensuring the quality of the finished alumina product. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the intelligent optimization method for alumina production based on a large industrial model provided by the present invention.

[0020] Figure 2This is a schematic diagram of the intelligent optimization device for alumina production process based on an industrial large model provided by the present invention. Detailed Implementation

[0021] The present application will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and should not be construed as limiting the scope of protection of the present application.

[0022] like Figure 1 As shown, in one embodiment, an intelligent optimization method for alumina production process based on a large industrial model includes the following steps: Step S110: Obtain seed flow state data at different locations within the seed decomposition system, and perform particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine crystal circulation distribution.

[0023] In some embodiments, the intelligent optimization method for alumina production process based on a large industrial model provided by the present invention includes the following steps in step S110: Step S111: Sampling points are set at the seed circulation pump outlet, decomposition tank inlet, decomposition tank underflow outlet, and seed grading return outlet. The particle concentration, slurry flow rate, slurry temperature, mother liquor alkali concentration, and underflow solid content in the circulating seed flow are continuously collected at the sampling points according to the preset sampling cycle to output seed flow status data.

[0024] Step S112: The seed crystals at each sampling point are classified according to the set particle size threshold to determine the particle distribution status of the coarse-grained region, the medium-grained region, and the fine-grained region.

[0025] The seed decomposition system includes a seed circulation pump outlet, a decomposition tank inlet, a decomposition tank underflow outlet, and a seed classification return outlet at different locations. The seed flow status data includes particle concentration, slurry flow rate, slurry temperature, mother liquor alkali concentration, and underflow solid content in the circulating seed flow.

[0026] In some embodiments, the intelligent optimization method for alumina production process based on a large industrial model provided by the present invention further includes the following steps in step S110: Step S113: Based on the particle distribution state of the coarse-grained region, the medium-grained region, and the fine-grained region, the fine-grained mass ratio, the seed reflux flow rate, and the feed rate of the decomposition tank in multiple consecutive seed decomposition cycles are correlated and calculated to obtain the change in the fine-grained reflux ratio.

[0027] Step S114: Based on the change in the fine crystal reflux ratio, the fine crystal aggregation and positioning are performed in the inlet area, stirring weak flow area, underflow discharge area and seed crystal reflux area of ​​different decomposition tanks, so as to determine the fine crystal aggregation position, fine crystal reflux ratio and medium crystal transition ratio corresponding to each decomposition tank, and to determine the fine crystal reflux direction and fine crystal accumulation intensity corresponding to each decomposition tank.

[0028] Among them, the fine crystal circulation distribution is obtained by combining the fine crystal aggregation position, the fine crystal reflow ratio and the medium crystal transition ratio, and the seed crystal circulation structure state is composed of the fine crystal reflow direction and the fine crystal cumulative intensity corresponding to each decomposition cell.

[0029] In a specific embodiment, the intelligent optimization method for alumina production process based on an industrial large-scale model provided by the present invention includes steps 1 to 4: Step 1: Perform seed crystal cycle structure layer identification and fine crystal accumulation state construction processing.

[0030] First, the circulating seed flow, mother liquor flow, and bottom flow of the decomposition tank in the seed decomposition system are continuously collected. Then, the seed particles at different circulation locations are identified by layered particle size distribution, extracting the particle distribution states of the coarse-grained, medium-grained, and fine-grained regions. Next, the proportion of fine-grained recirculation in multiple consecutive decomposition cycles is statistically correlated to identify the cumulative migration trend of fine-grained particles in the circulation system. Finally, local fine-grained aggregation regions in different decomposition tanks are located, generating corresponding fine-grained circulation distribution results. Combined with the circulation migration relationship of fine-grained particles between decomposition tanks, the seed circulation structure state results are formed, including the following sub-steps: Sub-step 1.1: Perform cyclic sampling point division and seed flow state acquisition and processing.

[0031] Specifically, sampling points are set at the seed circulation pump outlet, decomposition tank inlet, decomposition tank underflow outlet, and seed grading return outlet to continuously collect data on particle concentration, slurry flow rate, slurry temperature, mother liquor alkali concentration, and underflow solids content in the circulating seed stream. The sampling period is set to 5-30 minutes; if the decomposition tank operation fluctuates significantly, the sampling period is set to 5-10 minutes; if the operation is relatively stable, the sampling period is set to 20-30 minutes. Through this process, the seed state, originally observed only in a single decomposition tank, is transformed into seed stream state data covering multiple points along the seed circulation path.

[0032] Sub-step 1.2 involves performing seed particle layering and particle size identification processing.

[0033] Specifically, based on the seed flow state data at each sampling point, the seed particles were classified by size. Particles larger than 100 micrometers were classified as coarse-grained, particles between 45 and 100 micrometers as medium-grained, and particles smaller than 45 micrometers as fine-grained. Then, the mass percentage, quantity percentage, and surface area percentage per unit volume of particles in each size range were statistically analyzed to identify whether fine-grained particles, although having a low mass percentage, had an excessively high surface area percentage.

[0034] Sub-step 1.3: Perform multi-cycle fine-grain reflux ratio correlation statistical processing.

[0035] Specifically, using a complete seed crystal decomposition cycle as the statistical unit, the proportion of fine crystal mass, seed crystal reflux flow, and decomposition tank feed rate are correlated and calculated across multiple consecutive statistical cycles. The statistical cycle is set to 3-10 decomposition cycles, preferably 5. If fine crystals continuously reflux across multiple cycles, and the amount of fine crystals entering the decomposition tank in each cycle is not graded and discharged, it is determined that fine crystals are accumulating in a cycle.

[0036] In this embodiment, the expression for the fine-grain reflux ratio is: ; In the formula, This indicates the fine-grain reflux ratio, expressed as a percentage. This indicates the seed crystal reflux flow rate, expressed in cubic meters per hour. This indicates the solid content of the reflux seed slurry, expressed in kilograms per cubic meter. This indicates the percentage of fine grains in terms of quality. This indicates the total slurry flow rate entering the decomposition tank, expressed in cubic meters per hour. This indicates the total solids concentration entering the decomposition tank, expressed in kilograms per cubic meter.

[0037] Furthermore, if the average fine-grain reflux ratio of the four statistical periods following the first statistical period minus the fine-grain reflux ratio of the first statistical period is greater than three percentage points, it indicates that the fine-grain reflux ratio has a significant upward trend; if it is greater than eight percentage points, it indicates that the risk of fine-grain recycling is relatively high.

[0038] Sub-step 1.4 involves performing local fine-grain aggregation positioning and cyclic structure state generation processing in the decomposition tank.

[0039] Specifically, based on the changes in the fine-grained recirculation ratio, fine-grained aggregation and positioning were determined in different decomposition tank inlet zones, weak-flow stirring zones, underflow discharge zones, and seed crystal recirculation zones. If the fine-grained recirculation ratio increases in the inlet zone of a certain decomposition tank, while the proportion of fine-grained particles at the underflow outlet does not decrease significantly, it indicates that the fine-grained particles have not been effectively removed in a graded manner, but continue to participate in the circulation within that decomposition tank. Then, the fine-grained aggregation location, fine-grained recirculation ratio, coarse-grained retention ratio, and medium-grained transition ratio of each decomposition tank were combined to form the fine-grained circulation distribution result. Finally, based on the recirculation direction and cumulative intensity of fine-grained particles between each decomposition tank, the seed crystal circulation structure state result was formed.

[0040] In this embodiment, the expression for the seed cycle imbalance coefficient is: ; In the formula, This represents the seed crystal cycle imbalance coefficient, which is a dimensionless value. Indicates the fine-grained reflux ratio; This represents the surface area contribution of fine grains. It is a dimensionless value and can be understood as the contribution of particle surface area to the ratio of mass to particle size under the same material density. The smaller the particle size, the larger the surface area per unit mass. This represents the average residence time of fine crystals in the decomposition tank, in hours, and is calculated using the effective volume of the tank and the slurry flow rate. This represents the coarse grain retention ratio, expressed as a percentage, obtained through particle size classification testing. A constant of 0.1 is used to avoid calculation instability when the coarse grain retention ratio is extremely low; its value range can be set to 5%-10%. This formula indicates that the more fine grains are recirculated, the greater the surface area contribution, the longer the residence time, and the lower the coarse grain retention, the easier it is for the seed crystal circulation to become unbalanced.

[0041] When the seed cycle imbalance coefficient is less than 2, the seed cycle structure is basically stable; when the seed cycle imbalance coefficient is between 2 and 5, it indicates that there is a risk of fine crystal accumulation; when the seed cycle imbalance coefficient is greater than 5, it indicates that fine crystals have significantly interfered with the seed cycle structure, and fine crystal growth-driving segments need to be identified and suppressed in subsequent steps.

[0042] Step S120: Based on the seed crystal cycle structure state and fine crystal cycle distribution, analyze the fine crystal growth rate in each decomposition cell to identify the fine crystal growth driving segment, and generate the fine crystal growth propagation chain and abnormal decomposition driving result according to the fine crystal growth driving segment.

[0043] In some embodiments, the intelligent optimization method for alumina production process based on a large industrial model provided by the present invention includes the following steps in step S120: Step S121: Obtain the change in fine grain quality of the same section within the decomposition tank between adjacent sampling times, and calculate the fine grain growth rate per unit time based on the change in fine grain quality, so as to determine the decomposition tank section where the fine grain growth rate exceeds the set growth threshold.

[0044] Step S122: Perform a reverse lookup on the decomposition tank section to identify the corresponding temperature drop range, temperature drop duration, mother liquor concentration change, and seed density change, and integrate the temperature drop range, temperature drop duration, mother liquor concentration change, and seed density change into the results of the fine crystal growth associated working condition section.

[0045] In some embodiments, the intelligent optimization method for alumina production process based on a large industrial model provided by the present invention further includes the following steps in step S120: Step S123: Determine the local abnormal decomposition section based on the results of the fine grain growth associated working condition section, and use the local abnormal decomposition section as the starting point of fine grain generation to trace the path and obtain the fine grain growth propagation chain.

[0046] Step S124: Extract the abnormal decomposition source, temperature drop section, local oversaturation section, abnormal seed density section, and reflow growth section from the fine grain growth propagation chain, and integrate the abnormal decomposition source, temperature drop section, local oversaturation section, abnormal seed density section, and reflow growth section into an abnormal decomposition driving result.

[0047] In a specific embodiment, the intelligent optimization method for alumina production process based on an industrial large-scale model provided by the present invention, step 2, involves identifying fine grain growth-driven sections and correlating them with local anomalies. Based on the seed crystal circulation structure state results and fine grain circulation distribution results output in step 1, firstly, the fine grain growth rate in each decomposition tank is continuously analyzed; then, temperature drop sections, local oversaturation sections, and abnormal seed crystal density sections in different decomposition tanks are correlated and identified; next, the coupling relationship between the rapid fine grain growth region and the corresponding decomposition conditions is matched to identify the local decomposition sections that induce continuous fine grain generation; finally, the reflux path of the fine grains re-entering the circulation system after generation is traced to form a fine grain growth propagation chain, and then the corresponding anomaly decomposition-driven results are generated based on the fine grain growth propagation chain, including the following sub-steps: Sub-step 2.1: Perform continuous calculation of the fine crystal growth rate of each decomposition cell.

[0048] Specifically, based on the results of the seed crystal circulation structure and the fine crystal circulation distribution, each decomposition tank is treated as an independent identification unit. The fine crystal mass ratio, fine crystal surface area contribution coefficient, slurry solid content, and residence time are continuously read at the tank inlet, middle, underflow outlet, and seed crystal return port. Then, using the change in fine crystal mass between two adjacent sampling times as a basis, combined with the slurry solid content and effective volume within the decomposition tank, the actual increase in fine crystal intensity per unit time is calculated, i.e., the fine crystal growth rate (converting the change in the fine crystal mass ratio into the actual fine crystal mass growth rate within the decomposition tank, avoiding only considering percentage changes while ignoring differences in tank load). The sampling interval is 10-30 minutes; if the decomposition temperature drops rapidly, the sampling interval is 10 minutes; if the decomposition process is stable, the interval is 20-30 minutes.

[0049] Sub-step 2.2 involves performing correlation identification processing between the temperature drop section and the local oversaturation section.

[0050] Specifically, based on the results of the fine crystal growth rate in the decomposition tank, a reverse investigation is conducted on the decomposition tank sections where the fine crystal growth is significantly increased to identify the corresponding temperature drop amplitude, cooling duration, mother liquor concentration changes, and seed density changes. When the fine crystal growth rate in a certain decomposition tank is continuously higher than the average value of adjacent decomposition tanks, that decomposition tank is marked as a section to be associated. Subsequently, it is determined whether this section simultaneously suffers from problems such as excessively rapid temperature drop, localized supersaturation enhancement, or low seed density. Among these, the temperature drop rate is usually controlled between 0.5 and 3 degrees Celsius per hour. If it exceeds 3 degrees Celsius per hour, it is easy to induce the generation of a large number of new crystal nuclei. The seed density can be determined based on the seed mass per unit volume. If it is more than 10% lower than the process set value, it indicates that the existing seed carrying capacity is insufficient.

[0051] In this embodiment, the expression for the oversaturation driving coefficient is: ; In the formula, This represents the oversaturation driving coefficient, which is a dimensionless value. This indicates the actual concentration of decomposable alumina in the current sodium aluminate solution, expressed in kilograms per cubic meter, obtained through analysis of the mother liquor composition. This indicates the equilibrium alumina concentration at the current temperature, expressed in kilograms per cubic meter, obtained through process balance tables or experimental calibration. Indicates the rate of temperature decrease, expressed in degrees Celsius per hour; This represents the proportion of coarse grains retained, and is a dimensionless decimal. This represents the cooling amplification factor, expressed in degrees Celsius per hour, with a value ranging from 0.3 to 0.8. The coefficient represents the coarse-grained buffer coefficient, a dimensionless constant ranging from 0.5 to 2. This formula indicates that the greater the actual concentration exceeds the equilibrium concentration, the faster the cooling rate, the less coarse-grained material is retained, and the easier it is for fine-grained particles to form.

[0052] Sub-step 2.3 involves performing a coupling matching process between abnormal seed density and rapid fine grain growth.

[0053] Specifically, based on the results of the fine-grain growth correlation working condition segments, a comprehensive judgment is made on the seed density, coarse-grain retention ratio, fine-grain surface area contribution coefficient, and oversaturation driving coefficient in each segment to be correlated. If a segment simultaneously exhibits an increased oversaturation driving coefficient, a decreased coarse-grain retention ratio, and an increased fine-grain surface area contribution coefficient, it indicates that the segment is not a simple decomposition strengthening segment, but rather a localized abnormal decomposition segment that induces continuous fine-grain generation. In this case, instead of directly aiming to increase the decomposition rate, the segment is marked as a key segment requiring subsequent fine-grain suppression constraints.

[0054] In this embodiment, the expression for the intensity of local anomaly decomposition is: ;

[0055] In the formula, Indicates the intensity of localized abnormal decomposition, expressed in kilograms per hour; This indicates the grain growth rate, expressed in kilograms per hour. This represents the oversaturation driving coefficient, which is a dimensionless value. This represents the surface area contribution coefficient of fine grains, and is a dimensionless value. This represents the proportion of coarse grains retained, and is a dimensionless decimal. This represents the transition ratio in the intermediate crystal structure and is a dimensionless decimal. The constant represents the stability constant, which is a dimensionless value ranging from 0.05 to 0.2. This formula indicates that the faster the fine grain growth, the stronger the supersaturation driving force, and the greater the contribution of the fine grain surface area, while the weaker the carrying capacity of coarse and medium grains, the more likely this section is to become an abnormal decomposition source that continuously produces fine grains.

[0056] Sub-step 2.4 involves performing fine crystal reflux path tracing and growth propagation chain formation processing.

[0057] Specifically, based on the results of local abnormal decomposition sections, the identified abnormal decomposition sections are used as the starting point for fine crystal formation. The actual process flow is traced along the underflow discharge, seed crystal classification, fine crystal recirculation, and re-entry into the decomposition tank. For each path, the propagation time, recirculation ratio, classification retention ratio, and re-growth intensity of the fine crystals from the abnormal decomposition section into the next decomposition tank are recorded. If the fine crystals generated in a certain abnormal decomposition section continue to grow in two or more subsequent decomposition tanks, it indicates that the fine crystals are no longer a local problem but have formed a cross-tank propagation chain. This propagation chain should at least include the fine crystal formation tank location, the fine crystal recirculation node, the re-entry into the decomposition tank location, and the re-growth section.

[0058] In this embodiment, the expression for the propagation preservation coefficient is: ; In the formula, This represents the propagation preservation coefficient, which is a dimensionless value. This represents the fine-grained reflux ratio and is a dimensionless decimal. This represents the fractional retention ratio, a dimensionless decimal obtained through the fine separation effect of the seed crystal grading equipment, with a value range of 0.1-0.95. This indicates the growth rate of fine crystals after they enter the next decomposition cell, expressed in kilograms per hour. This indicates the initial fine grain growth rate of the anomalous decomposition zone, expressed in kilograms per hour. This represents the stability constant, expressed in kilograms per hour, with a value ranging from 10 to 50. This formula indicates that the greater the fine grain recirculation, the weaker the staged retention, and the stronger the grain propagation and retention capability after entering the next tank.

[0059] When the propagation retention coefficient is less than 0.3, it indicates that the propagation of fine crystals has been significantly weakened; when the propagation retention coefficient is between 0.3 and 0.7, it indicates that there is a risk of propagation; when the propagation retention coefficient is greater than 0.7, it indicates that fine crystals have a strong ability to propagate across grooves and should be included in the subsequent seed growth balance reconstruction treatment.

[0060] Sub-step 2.5: Perform abnormal decomposition-driven result generation processing.

[0061] Specifically, based on the fine-grain growth propagation chain, the abnormal decomposition sources, temperature drop sections, local oversaturation sections, abnormal seed density sections, and reflow regrowth sections in each propagation chain are merged to form the abnormal decomposition driving result. This result not only indicates which decomposition cell has more fine grains, but also clearly explains why fine grains continue to be generated, where they are generated from, through which reflow path they propagate, and in which decomposition cell they are amplified again. The abnormal decomposition driving result includes at least the abnormal decomposition cell number, the abnormal occurrence section, the fine-grain growth rate level, the oversaturation driving level, the abnormal seed density level, the propagation maintenance level, and the decomposition condition boundaries that need to be restricted subsequently. Finally, the abnormal decomposition driving result is used as the direct input for step 3 to perform seed growth balance reconstruction and fine-grain suppression constraint generation processing.

[0062] It should be noted that the higher the intensity of the anomaly source, the stronger the cross-slot propagation, and the more obvious the oversaturation drive, the weaker the carrying capacity of coarse and medium grains, the higher the level of anomaly decomposition drive.

[0063] Step S130: Based on the fine grain growth propagation chain and abnormal decomposition driving results, analyze the seed growth rate and nucleus generation rate in different decomposition tanks to determine the local oversaturated decomposition section of fine grain burst, and impose fine grain suppression constraints on the local oversaturated decomposition section.

[0064] In some embodiments, the intelligent optimization method for alumina production process based on a large industrial model provided by the present invention includes the following steps in step S130: Step S131: Calculate the seed growth rate and nucleus generation rate of the corresponding segment of the fine crystal growth propagation chain, and generate the seed nucleation and growth equilibrium result of the corresponding decomposition tank based on the seed growth rate and nucleus generation rate.

[0065] Step S132: Based on the seed nucleation and growth equilibrium results, the working condition of the local abnormal decomposition section dominated by crystal nucleation is reconstructed to obtain the reconstruction results.

[0066] In some embodiments, the intelligent optimization method for alumina production process based on a large industrial model provided by the present invention further includes the following steps in step S130: Step S133: Based on the reconstruction results, determine the local oversaturated decomposition section with the risk of fine crystal burst, and establish constraint boundaries for the local oversaturated decomposition section. The constraint boundaries include the upper limit of cooling, the upper limit of fine crystal reflux, the upper limit of oversaturation driving, the lower limit of seed replenishment, and the adjustment range of mother liquor circulation.

[0067] Step S134: Adjust the various operations in the production process in combination according to the upper limit of cooling, the upper limit of fine crystal reflux, the upper limit of supersaturation drive, the lower limit of seed replenishment, and the adjustment range of mother liquor circulation, so as to balance and control the seed growth process.

[0068] In a specific embodiment, the intelligent optimization method for alumina production process based on an industrial large-scale model provided by the present invention, in step 3, performs seed growth balance reconstruction and fine crystal suppression constraint generation processing. Based on the fine crystal growth propagation chain and abnormal decomposition driving results output in step 2, firstly, the balance relationship between the seed growth rate and the new crystal nucleus generation rate in different decomposition tanks is analyzed; then, the cooling process, seed replenishment process, and mother liquor circulation process in the fine crystal continuous proliferation region are collaboratively reconstructed; then, fine crystal suppression constraints are established for the locally supersaturated decomposition sections that are prone to fine crystal bursts; finally, the coarse crystal retention ratio, fine crystal recirculation ratio, and decomposition dwell rhythm are jointly adjusted to form the corresponding seed growth balance control results, including the following sub-steps: Sub-step 3.1 involves performing a balance analysis of the seed growth rate and the new crystal nucleus generation rate.

[0069] Specifically, based on the fine-grain growth propagation chain and the results of anomalous decomposition, the anomalous decomposition location, the fine-grain re-growth section, and the corresponding supersaturation driving level are first determined in each fine-grain growth propagation chain. Then, the ability of existing seeds to continue growing within this section and the tendency for new crystal nuclei to reform in the solution are calculated. Finally, these two are compared to determine whether the current decomposition tank is in a "seed growth-dominated state" or a "new crystal nucleus generation-dominated state." If the new crystal nucleus generation rate is consistently higher than the seed growth rate, it indicates that precipitable materials in the solution are not preferentially deposited on the surfaces of existing coarse and medium-sized crystals, but are continuously generating new fine-grained particles.

[0070] In this embodiment, the expression for the seed growth rate is: ; In the formula, This indicates the seed crystal growth rate, expressed in kilograms per cubic meter per hour. This represents the proportion of coarse grains retained, and is a dimensionless decimal. This represents the transition ratio in the intermediate crystal structure and is a dimensionless decimal. This indicates the average grain size of the coarse grains, in micrometers. This indicates the average grain size of the medium crystals, in micrometers. This indicates the current concentration of decomposable alumina, expressed in kilograms per cubic meter. This represents the oversaturation driving coefficient, which is a dimensionless value. This represents the average residence time of the material in the decomposition tank, in hours. This formula indicates that the higher the proportion of coarse and medium crystals, the higher the concentration of decomposable alumina, and the stronger the supersaturation drive, the greater the existing seed crystals' ability to carry the precipitated material; the longer the residence time, the thinner the seed crystal growth rate per unit time.

[0071] The expression for the crystal nucleation rate is: ; In the formula, This indicates the rate of crystal nucleation, expressed in kilograms per hour. This indicates the grain growth rate, expressed in kilograms per hour. This represents the surface area contribution coefficient of fine grains, and is a dimensionless value. This represents the oversaturation driving coefficient, which is a dimensionless value. This represents the propagation preservation coefficient, which is a dimensionless value. Indicates the proportion of coarse grains retained; Indicates the intermediate crystal transition ratio; This represents the stability constant. The formula indicates that the faster the fine grain growth, the higher the contribution of the fine grain surface area, and the stronger the cross-groove propagation, the stronger the tendency for new crystal nuclei to continuously form; the more coarse and medium-sized grains there are, the more this tendency is suppressed.

[0072] Therefore, the expression for the seed nucleation and growth equilibrium coefficient is: ; In the formula, Indicates the seed nucleation and growth equilibrium coefficient; Indicates the seed crystal growth rate; Indicates the rate of crystal nucleus formation; To represent the calculation of the stability constant, we can generally take... 5%. When the seed nucleation and growth equilibrium coefficient is greater than 1.2, it indicates that seed growth is dominant; when the seed nucleation and growth equilibrium coefficient is between 0.8 and 1.2, it indicates that seed growth and new crystal nucleus generation are close to equilibrium; when the seed nucleation and growth equilibrium coefficient is less than 0.8, it indicates that new crystal nucleus generation is dominant, and subsequent reconstruction processing is required.

[0073] Sub-step 3.2 involves performing a coordinated reconstruction process that includes cooling, seed crystal replenishment, and mother liquor circulation.

[0074] Specifically, based on the seed nucleation and growth equilibrium results, the operating conditions of the abnormal decomposition section where new crystal nucleus generation is dominant are reconfigured. First, the cooling rate of this section is reduced to decrease the local supersaturation release rate. Then, seed crystals capable of bearing the crystals are added according to the coarse crystal retention ratio and the medium crystal transition ratio, so that the precipitable material preferentially adheres to the surface of the existing seed crystals. Next, the mother liquor circulation rate is adjusted to prevent the highly supersaturated mother liquor from lingering in the local weak mixing area for a long time. Among these measures, the cooling rate is controlled at 0.5-2 degrees Celsius per hour; the seed crystal replenishment amount is determined according to the current coarse crystal gap, prioritizing the replenishment of medium and coarse crystals, without directly increasing the fine crystal reflux; the mother liquor circulation ratio is adjusted by 5% to 20% based on the original operating value to avoid significant disturbance to the decomposition tank level and residence time.

[0075] Sub-step 3.3 involves performing a process to suppress and constrain the generation of fine grains in the local oversaturated decomposition zone.

[0076] Specifically, based on the collaborative reconstruction results of the decomposition process, constraint boundaries are established for sections where there is still a risk of fine crystal outbreak. These constraint boundaries include upper limits for cooling, fine crystal reflux, oversaturation drive, seed replenishment, and mother liquor circulation adjustment. During execution, when the oversaturation drive coefficient of a certain section continues to rise and the seed nucleation and growth equilibrium coefficient is below 0.8, the adjustment action to further increase the decomposition rate is restricted. When the fine crystal reflux ratio exceeds the preset upper limit, priority is given to graded fine crystal removal and coarse crystal retention, rather than continuing to extend the decomposition time. This process ensures that the industrial large-scale model cannot simply pursue a short-term decomposition rate during optimization, but must meet the fine crystal suppression constraint. When constraining, the stronger the abnormal drive, the more obvious the oversaturation, and the higher the fine crystal reflux, the stronger the suppression constraint; the more balanced the seed growth and the more sufficient the coarse crystal retention, the more appropriately the suppression constraint can be reduced.

[0077] Sub-step 3.4 involves a combined adjustment of the coarse grain retention ratio, fine grain reflux ratio, and decomposition dwell time.

[0078] Specifically, based on the results of fine crystal suppression and constraint, the seed grading equipment, the feeding rhythm of the decomposition tank, the underflow discharge rhythm, and the seed recirculation rhythm are jointly adjusted. First, the retention ratio of coarse and medium crystals in the decomposition tank is increased, making them the main crystal growth carriers. Then, the recirculation ratio of fine crystals is reduced, preventing them from repeatedly entering the decomposition tank and participating in the circulation. Next, the decomposition residence rhythm is adjusted according to the strength of the fine crystal suppression and constraint to avoid excessive residence time of materials in a highly supersaturated state. If the fine crystal suppression and constraint strength is at a medium level, only the fine crystal recirculation ratio is reduced and the cooling is finely adjusted. If the fine crystal suppression and constraint strength is at a high level, simultaneous fine crystal grading and discharge, coarse crystal replenishment, reduced cooling rate, and shortened residence time in abnormal sections are implemented. Therefore, the higher the proportion of coarse and medium crystals, the longer the residence time can be to promote growth; the stronger the fine crystal suppression and constraint and the higher the fine crystal recirculation, the shorter the effective residence time in abnormal sections should be to prevent further fine crystal proliferation.

[0079] Sub-step 3.5: Perform the seed growth balance control result formation processing.

[0080] Specifically, based on the joint adjustment execution results, the cooling rate, seed replenishment amount, mother liquor circulation amount, coarse crystal retention ratio, fine crystal reflux ratio, and decomposition residence time of each decomposition tank are summarized to form the seed growth balance control results for subsequent steps. Simultaneously, the fine crystal suppression constraint results formed in sub-step 3.3 are bound to the joint adjustment execution results to clarify the control boundaries corresponding to each fine crystal growth propagation chain. The seed growth balance control results include at least the target coarse crystal retention ratio, target fine crystal reflux upper limit, target cooling rate, target seed replenishment amount, target mother liquor circulation adjustment range, and target decomposition residence time. The fine crystal suppression constraint results include at least the abnormal decomposition sections where further increases in short-term decomposition rate are prohibited, seed reflux nodes where fine crystal reflux needs to be reduced, grading equipment nodes where graded fine crystal removal needs to be performed, and decomposition tank sections where coarse crystals need to be retained preferentially.

[0081] In this embodiment, the expression for the balance control completion degree is: ; In the formula, This indicates the degree of completion of balance control and is a dimensionless value. Indicates the seed nucleation and growth equilibrium coefficient; Indicates the proportion of coarse grains retained; Indicates the fine-grained reflux ratio; This indicates the grain refinement suppression constraint strength, expressed in kilograms per hour. This represents the constraint strength balance constant, expressed in kilograms per hour, with a value ranging from 200 to 500. When the balance control completion rate is greater than 0.6, it indicates that the seed growth balance has been basically restored; when the balance control completion rate is between 0.3 and 0.6, it indicates that fine grain suppression still needs to be implemented; when the balance control completion rate is less than 0.3, it indicates that the accumulation of fine grain cycles is still severe, and entering the optimization state aimed at improving the decomposition rate is not allowed.

[0082] Step S140: Monitor the fine crystal reflux state in the seed crystal circulation system and verify the coarse crystal growth state and fine crystal suppression state in the decomposition tank to output a decomposition control strategy that meets the particle size stability conditions.

[0083] In some embodiments, the intelligent optimization method for alumina production process based on a large industrial model provided by the present invention includes the following steps in step S140: Step S141: Continuously monitor the seed reflux port, grading equipment outlet, decomposition tank inlet, and underflow outlet in the seed circulation system according to the set monitoring cycle, so as to determine the fine crystal reflux monitoring data at each monitoring location in the seed circulation system.

[0084] Step S142: Based on the fine crystal reflux monitoring data, the coarse crystal growth state and fine crystal suppression state in the decomposition tank are jointly verified to identify the circulation section with fine crystal diffusion trend, and fine crystal suppression constraint is applied to the circulation section.

[0085] Step S143: Perform particle size verification on the aluminum hydroxide material before it enters the calcination system. When the particle size deviation of the aluminum hydroxide material before it enters the calcination system is lower than the set deviation threshold, output the current decomposition control strategy to the seed crystal decomposition system to obtain a decomposition control strategy that meets the particle size stability condition.

[0086] In a specific embodiment, the intelligent optimization method for alumina production process based on an industrial large-scale model provided by the present invention includes step 4, which involves performing long-term cyclic particle size stability control and decomposition optimization output processing. Based on the seed growth balance control results and fine grain suppression constraint results output in step 3, firstly, the fine grain reflux state in the seed circulation system is continuously monitored; then, the coarse grain growth state and fine grain suppression state in the decomposition tank are jointly verified; next, the decomposition temperature, seed circulation ratio, and decomposition dwell rhythm are readjusted for circulation sections with a tendency for fine grain re-diffusion; then, the particle size stability of the material in the subsequent calcination system is synchronously verified; finally, the decomposition control strategy that meets the long-term particle size stability conditions is output to the seed decomposition system to achieve long-term particle size stability optimization control under the scenario of seed decomposition fine grain cyclic accumulation, including the following sub-steps: Sub-step 4.1: Perform continuous monitoring of the fine crystal reflux status.

[0087] Specifically, based on the results of seed growth balance control and fine grain suppression constraint, continuous monitoring is performed on the seed reflux port, grading equipment outlet, decomposition tank inlet, and underflow outlet in the seed circulation system. The focus is on reading the fine grain reflux ratio, fine grain surface area contribution coefficient, coarse grain retention ratio, and fine grain suppression constraint strength. The monitoring cycle is set to 10-30 minutes; when the fine grain suppression constraint strength is high, the monitoring cycle is preferably 10 minutes; once the seed circulation structure is stable, the monitoring cycle can be extended to 30 minutes. Through this process, it can be determined whether the fine grain suppression constraint formed in step 3 remains effective in long-term circulation. That is, the higher the fine grain reflux, the greater the fine grain surface area contribution, and the stronger the constraint pressure, the less stable the fine grain reflux; the more sufficient the coarse grain retention, the better the fine grain reflux stability.

[0088] Sub-step 4.2 involves performing a joint verification process for the coarse grain growth state and the fine grain suppression state.

[0089] Specifically, based on the monitoring results of fine crystal recirculation stability, a joint judgment is made on the growth state of coarse crystals and the suppression state of fine crystals in the decomposition tank. First, the average particle size of coarse crystals, the retention ratio of coarse crystals, the recirculation ratio of fine crystals, and the growth rate of fine crystals are read from multiple consecutive monitoring cycles. Then, it is determined whether the coarse crystals are growing stably, and at the same time, whether the fine crystals are being continuously suppressed. Then, the two are combined to form a joint verification result of particle size stability. If the average particle size of coarse crystals continues to increase or remains stable, and the recirculation ratio of fine crystals continuously decreases, it indicates that the control strategy in step 3 is effective; if the growth of coarse crystals stagnates, and the recirculation ratio of fine crystals rises again, it indicates that the fine crystals have a tendency to diffuse again.

[0090] It should be noted that the faster the coarse grain size increases, the more fully the coarse grains are retained, and the lower the fine grain growth, the better the coarse grain growth is maintained. The more the current fine grain reflux ratio is below the target upper limit, and the stronger the coarse and medium grain carrying capacity, the more reliable the fine grain suppression effect.

[0091] Sub-step 4.3 involves performing a readjustment of the decomposition conditions in the fine-grain re-diffusion zone.

[0092] Specifically, based on the joint verification results of particle size stability, the circulation section with a tendency for fine crystal re-diffusion is readjusted. If the fine crystal reflux stability coefficient increases, the coarse crystal growth retention rate decreases, and the fine crystal suppression effectiveness coefficient is lower than the set lower limit, then it is determined that the circulation section still has a risk of fine crystal re-diffusion. At this time, readjusting the decomposition temperature, seed crystal circulation ratio, and decomposition residence rhythm can not only reduce the cooling rate of abnormal sections and reduce the instantaneous release of local supersaturation, but also increase the reflux ratio of coarse and medium crystals and reduce the reflux ratio of fine crystals; at the same time, it can shorten the effective residence time in the high-risk fine crystal section to prevent fine crystals from continuing to proliferate in that section.

[0093] It should be noted that the more unstable the fine-grain reflux and the worse the suppression, the more necessary it is to reduce the intensity of local oversaturation release; the better the coarse-grain growth, the more appropriate it is to maintain the decomposition temperature and avoid excessive sacrifice of decomposition efficiency; the more sufficient the coarse and medium-grain growth, the more appropriate it is to increase the seed crystal circulation ratio; the higher the fine-grain reflux and the higher the degree of instability, the more the repeated entry of fine-grain in the seed crystal circulation should be restricted.

[0094] Sub-step 4.4: Perform synchronous correlation verification of particle size stability of roasted materials.

[0095] Specifically, based on the results of the decomposition condition readjustment, the particle size stability of the aluminum hydroxide material before entering the calcination system is verified. The verification objects include the filtered wet aluminum hydroxide, the material in the calcination feed hopper, and the material at the calcination furnace inlet. If the coarse crystal growth state in the decomposition tank has improved, but the proportion of fine powder in the calcination inlet material is still too high, it indicates that fine crystals may still form particle size segregation during filtration, conveying, or temporary storage. Therefore, the final decomposition optimization strategy should not be directly output. In this case, the proportion of fine powder at the calcination inlet needs to be fed back into the seed crystal circulation control results to further reduce the fine crystal reflux ratio or increase the coarse crystal retention ratio. The higher the proportion of fine powder at the calcination inlet, the greater the contribution of the fine crystal surface area, while the weaker the bearing capacity of coarse and medium crystals, the more severe the particle size deviation before calcination.

[0096] Sub-step 4.5 executes the long-term granularity stable decomposition control strategy output processing.

[0097] Specifically, based on the pre-calcination particle size stability verification results, the decomposition temperature, seed crystal circulation ratio, coarse crystal retention ratio, fine crystal reflux upper limit, mother liquor circulation adjustment range, and decomposition residence rhythm are finalized. If the pre-calcination particle size deviation coefficient is lower than the set threshold, and the fine crystal reflux stability coefficient, coarse crystal growth retention rate, and fine crystal suppression effectiveness coefficient all meet the long-term stability conditions, the current decomposition control strategy is output to the seed crystal decomposition system; if the conditions are not met, the process returns to sub-step 4.3 for condition readjustment. Finally, the output long-term particle size stability decomposition control results include at least the target decomposition temperature, target cooling rate, target seed crystal circulation ratio, target fine crystal reflux upper limit, target coarse crystal retention ratio, target decomposition residence time, and calcination inlet particle size verification status.

[0098] The intelligent optimization device for alumina production process based on an industrial large model provided by the present invention will be described below. The intelligent optimization device for alumina production process based on an industrial large model described below can be referred to in correspondence with the intelligent optimization method for alumina production process based on an industrial large model described above.

[0099] like Figure 2 As shown, in one embodiment, an intelligent optimization device for alumina production process based on an industrial large model includes a seed grain size stratification module, a fine grain growth analysis module, a fine grain suppression and constraint module, and a fine grain reflux monitoring module.

[0100] The seed particle size stratification module is used to acquire seed flow state data at different locations within the seed decomposition system, and to perform particle size stratification of seed particles based on the seed flow state data in order to determine the seed circulation structure state and fine crystal circulation distribution.

[0101] The fine grain growth analysis module is used to analyze the fine grain growth rate in each decomposition cell based on the seed crystal cycle structure state and fine grain cycle distribution, in order to identify the fine grain growth driving segment, and generate the fine grain growth propagation chain and abnormal decomposition driving results based on the fine grain growth driving segment.

[0102] The fine grain suppression and constraint module is used to analyze the seed growth rate and nucleus generation rate in different decomposition tanks based on the fine grain growth propagation chain and abnormal decomposition driving results, in order to determine the local oversaturated decomposition section of fine grain burst, and to suppress and constrain the fine grain in the local oversaturated decomposition section.

[0103] The fine crystal reflux monitoring module is used to monitor the fine crystal reflux status in the seed crystal circulation system and to verify the coarse crystal growth status and fine crystal suppression status in the decomposition tank, so as to output a decomposition control strategy that meets the particle size stability conditions.

[0104] The present invention has been described in detail with reference to the accompanying drawings. However, those skilled in the art should understand that the above embodiments are only preferred embodiments of the present invention. The detailed description is only to help readers better understand the spirit of the present invention, and is not intended to limit the scope of protection of the present invention. On the contrary, any improvement or modification made based on the inventive spirit of the present invention should fall within the scope of protection of the present invention.

Claims

1. A smart optimization method for alumina production process based on a large industrial model, characterized in that, The method includes: Acquire seed flow state data at different locations within the seed decomposition system, and perform particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine crystal circulation distribution; Based on the seed crystal cycle structure state and fine crystal cycle distribution, the fine crystal growth rate in each decomposition tank is analyzed to identify the fine crystal growth driving segment, and a fine crystal growth propagation chain and abnormal decomposition driving result are generated according to the fine crystal growth driving segment. Based on the fine grain growth propagation chain and abnormal decomposition driving results, the seed growth rate and nucleus generation rate in different decomposition tanks are analyzed to determine the local oversaturated decomposition section of fine grain burst, and fine grain suppression constraint is applied to the local oversaturated decomposition section. The fine crystal reflux state in the seed crystal circulation system is monitored, and the coarse crystal growth state and fine crystal suppression state in the decomposition tank are verified to output a decomposition control strategy that meets the particle size stability condition.

2. The intelligent optimization method for alumina production process based on a large industrial model according to claim 1, characterized in that, The process of acquiring seed flow state data at different locations within the seed decomposition system and performing particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine-grain circulation distribution includes: Sampling points are set at the outlet of the seed circulation pump, the inlet of the decomposition tank, the underflow outlet of the decomposition tank, and the seed grading return port. The particle concentration, slurry flow rate, slurry temperature, mother liquor alkali concentration, and underflow solid content in the circulating seed flow are continuously collected at the sampling points according to the preset sampling cycle, so as to output the seed flow status data. The seed crystals at each sampling point are classified according to the set particle size threshold to determine the particle distribution in the coarse-grained, medium-grained, and fine-grained regions. The seed decomposition system includes, at different locations, the seed circulation pump outlet, the decomposition tank inlet, the decomposition tank underflow outlet, and the seed grading return outlet. The seed flow status data includes the particle concentration, slurry flow rate, slurry temperature, mother liquor alkali concentration, and underflow solid content in the circulating seed flow.

3. The intelligent optimization method for alumina production process based on a large industrial model according to claim 2, characterized in that, The step of acquiring seed flow state data at different locations within the seed decomposition system, and performing particle size stratification of seed particles based on the seed flow state data to determine the seed circulation structure state and fine-grain circulation distribution, further includes: Based on the particle distribution state of the coarse-grained region, medium-grained region and fine-grained region, the fine-grained mass ratio, seed reflux flow rate and decomposition tank feed rate in multiple consecutive seed decomposition cycles are correlated and calculated to obtain the change in the fine-grained reflux ratio. Based on the change in the fine crystal reflux ratio, the fine crystal aggregation and positioning are performed in the inlet area, stirring weak flow area, underflow discharge area and seed crystal reflux area of ​​different decomposition tanks, so as to determine the fine crystal aggregation position, fine crystal reflux ratio and medium crystal transition ratio corresponding to each decomposition tank, and to determine the fine crystal reflux direction and fine crystal accumulation intensity corresponding to each decomposition tank. The fine crystal circulation distribution is obtained by combining the fine crystal aggregation location, the fine crystal reflux ratio, and the medium crystal transition ratio. The seed crystal circulation structure state is composed of the fine crystal reflux direction and the fine crystal cumulative intensity corresponding to each decomposition cell.

4. The intelligent optimization method for alumina production process based on a large industrial model according to claim 1, characterized in that, The process involves analyzing the fine grain growth rate in each decomposition tank based on the seed crystal cycle structure state and fine grain cycle distribution to identify fine grain growth driving segments, and generating fine grain growth propagation chains and abnormal decomposition driving results based on these segments, including: The change in fine grain quality in the same section within the decomposition tank between adjacent sampling times is obtained, and the fine grain growth rate per unit time is calculated based on the change in fine grain quality to determine the decomposition tank section where the fine grain growth rate exceeds a set growth threshold. A reverse lookup is performed on the decomposition tank section to identify the corresponding temperature drop range, temperature drop duration, mother liquor concentration change, and seed density change, and the temperature drop range, temperature drop duration, mother liquor concentration change, and seed density change are integrated into the results of the fine crystal growth associated working condition section.

5. The intelligent optimization method for alumina production process based on a large industrial model according to claim 4, characterized in that, The step of analyzing the fine grain growth rate in each decomposition tank based on the seed crystal cycle structure state and fine grain cycle distribution to identify fine grain growth driving segments, and generating fine grain growth propagation chains and abnormal decomposition driving results based on the fine grain growth driving segments, further includes: Based on the results of the fine grain growth associated working condition section, a local abnormal decomposition section is determined, and the path is traced using the local abnormal decomposition section as the starting point of fine grain generation to obtain the fine grain growth propagation chain. The abnormal decomposition source, temperature drop section, local oversaturation section, abnormal seed density section, and reflow growth section in the fine grain growth propagation chain are extracted, and the abnormal decomposition source, temperature drop section, local oversaturation section, abnormal seed density section, and reflow growth section are integrated and output as the abnormal decomposition driving result.

6. The intelligent optimization method for alumina production process based on a large industrial model according to claim 5, characterized in that, Based on the fine grain growth propagation chain and the abnormal decomposition driving results, the seed growth rate and nucleus generation rate in different decomposition tanks are analyzed to determine the locally oversaturated decomposition region of fine grain burst, and fine grain suppression constraints are applied to the locally oversaturated decomposition region, including: Calculate the seed growth rate and nucleus generation rate of the corresponding segment of the fine crystal growth propagation chain, and generate the seed nucleation and growth equilibrium result of the corresponding decomposition tank based on the seed growth rate and nucleus generation rate. Based on the seed nucleation and growth equilibrium results, the working conditions of the local abnormal decomposition section dominated by seed nucleation are reconstructed to obtain the reconstruction results.

7. The intelligent optimization method for alumina production process based on a large industrial model according to claim 6, characterized in that, The method of analyzing the seed growth rate and nucleus generation rate in different decomposition tanks based on the fine grain growth propagation chain and abnormal decomposition driving results to determine the local oversaturated decomposition section of fine grain burst, and imposing fine grain suppression constraints on the local oversaturated decomposition section, further includes: Based on the reconstruction results, local supersaturated decomposition sections with the risk of fine crystal bursts are identified, and constraint boundaries are established for the local supersaturated decomposition sections. The constraint boundaries include the upper limit of cooling, the upper limit of fine crystal reflux, the upper limit of supersaturation driving, the lower limit of seed replenishment, and the adjustment range of mother liquor circulation. The various operations in the production process are adjusted in combination according to the aforementioned upper limit of cooling, upper limit of fine crystal reflux, upper limit of supersaturation drive, lower limit of seed replenishment, and adjustment range of mother liquor circulation, so as to achieve balanced control of the seed growth process.

8. The intelligent optimization method for alumina production process based on a large industrial model according to claim 1, characterized in that, The monitoring of the fine-grain reflux state in the seed crystal circulation system and the verification of the coarse-grain growth state and fine-grain suppression state in the decomposition tank, in order to output a decomposition control strategy that meets the particle size stability condition, include: According to the set monitoring cycle, the seed reflux port, the grading equipment outlet, the decomposition tank inlet and the underflow outlet of the seed circulation system are continuously monitored to determine the fine crystal reflux monitoring data at each monitoring location in the seed circulation system. Based on the fine grain reflux monitoring data, the coarse grain growth state and fine grain suppression state in the decomposition tank are jointly verified to identify the circulation section with a fine grain diffusion trend, and the circulation section is subject to fine grain suppression constraint. The particle size of the aluminum hydroxide material before entering the calcination system is checked. When the particle size deviation of the aluminum hydroxide material before entering the calcination system is lower than the set deviation threshold, the current decomposition control strategy is output to the seed crystal decomposition system to obtain a decomposition control strategy that meets the particle size stability condition.

9. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-8.

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