Method, device and apparatus for conditioning alumina recycle liquor

Abstract

This invention discloses a method, apparatus, and equipment for preparing alumina circulating mother liquor. The method includes: obtaining a first component of decomposition mother liquor, obtaining a second component of evaporation mother liquor, and obtaining a third component of liquid alkali; optimizing the preparation strategy of the alumina circulating mother liquor based on the first, second, and third components and a preset target optimization algorithm to obtain a first addition amount of decomposition mother liquor, a second addition amount of evaporation mother liquor, and a third addition amount of liquid alkali; the optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and a preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and a preset molecular ratio; and preparing the alumina circulating mother liquor based on the first addition amount of decomposition mother liquor, the second addition amount of evaporation mother liquor, and the third addition amount of liquid alkali. This invention solves the technical problem of low preparation accuracy of alumina circulating mother liquor.

Description

Technical Field

[0001] This invention belongs to the field of alumina production technology, and particularly relates to a method, apparatus and equipment for preparing alumina circulating mother liquor. Background Technology

[0002] Alumina circulating mother liquor is a high-concentration alkaline mother liquor specifically prepared according to process parameters for leaching bauxite in alumina production. Online analysis of the composition of alumina circulating mother liquor mainly includes the three-temperature, three-conductivity method for determining solution composition, the refractive index method for determining the caustic alkali concentration, or a combination of conductivity and refractive index methods to measure the caustic alkali concentration and molecular ratio. Due to the complex operating conditions in alumina production (such as strong alkali and easy scaling), the above techniques all exhibit decreasing predictive accuracy over time during on-site industrial trials, making them unsuitable for actual production needs. The composition of alumina circulating mother liquor is still primarily determined by manual sampling and laboratory analysis. While manual analysis offers high accuracy, it suffers from time lag and cannot provide precise guidance for continuous production processes.

[0003] Currently, the preparation of alumina circulating mother liquor relies heavily on manual experience, resulting in significant fluctuations in solution composition and an inability to accurately adjust it according to demand. Furthermore, the actual batching process depends on manual laboratory analysis results, but these data are delayed by approximately two hours. Since batching is a continuous operation, the mother liquor data used for calculations is historical. Consequently, subsequent production indicators fluctuate considerably, severely impacting the stability of the production process. Therefore, the low accuracy of alumina circulating mother liquor preparation is a pressing technical problem that needs to be addressed. Summary of the Invention

[0004] This invention provides a method, apparatus, and equipment for preparing alumina circulating mother liquor, which solves the technical problem of low accuracy in preparing alumina circulating mother liquor.

[0005] In a first aspect, embodiments of the present invention provide a method for preparing alumina circulating mother liquor, comprising: obtaining a first component of decomposition mother liquor, obtaining a second component of evaporation mother liquor, and obtaining a third component of liquid alkali; optimizing the preparation strategy of alumina circulating mother liquor based on the first component, the second component, the third component, and a preset target optimization algorithm to obtain a first addition amount of the decomposition mother liquor, a second addition amount of the evaporation mother liquor, and a third addition amount of the liquid alkali; wherein, the optimization variables of the target optimization algorithm are the addition amount of the decomposition mother liquor, the addition amount of the evaporation mother liquor, and the addition amount of the liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints; the optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and a preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and a preset molecular ratio; and preparing the alumina circulating mother liquor based on the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali.

[0006] In conjunction with the first aspect of the present invention, in some embodiments, the first component of the decomposition mother liquor includes the concentration of caustic alkali, the concentration of alumina, and the concentration of carbon alkali in the decomposition mother liquor; the second component of the evaporation mother liquor includes the concentration of caustic alkali, the concentration of alumina, and the concentration of carbon alkali in the evaporation mother liquor; and the third component of the liquid alkali includes the concentration of caustic alkali in the liquid alkali.

[0007] In conjunction with the first aspect of the present invention, in some embodiments, the decomposition mother liquor is obtained by treating the decomposition stock solution with a target decomposition process; obtaining the first component of the decomposition mother liquor includes: obtaining the first material parameters of the decomposition stock solution and the first process parameters of the target decomposition process; inputting the first material parameters and the first process parameters into a first index prediction model to obtain the first component of the decomposition mother liquor.

[0008] In conjunction with the first aspect of the present invention, in some embodiments, the first index prediction model is pre-constructed through the following steps: constructing a first mechanism model of the decomposition process based on the principle of seed crystal decomposition process; training a first machine learning model with multiple sets of first samples to obtain a first data-driven model of the decomposition process; each set of first samples includes material parameters, process parameters, and component deviation compensation values ​​of the decomposition process; connecting the first mechanism model and the first data-driven model in parallel to obtain the first index prediction model; the output prediction value of the first index prediction model is a weighted sum of the output prediction value of the first mechanism model and the output prediction value of the first data-driven model.

[0009] In conjunction with the first aspect of the present invention, in some embodiments, the mother liquor is obtained by treating the raw evaporator through a target evaporation process; obtaining the second component of the mother liquor includes: obtaining the second material parameters of the raw evaporator and the second process parameters of the target evaporation process; inputting the second material parameters and the second process parameters into a second index prediction model to obtain the second component of the mother liquor.

[0010] In conjunction with the first aspect of the present invention, in some embodiments, the second index prediction model is pre-constructed through the following steps: constructing a second mechanism model of the evaporation process based on the principle of multi-effect evaporation; training the second machine learning model with multiple sets of second samples to obtain a second data-driven model of the evaporation process; each set of second samples includes the material parameters, process parameters, and component deviation compensation values ​​of the evaporation process; connecting the second mechanism model and the second data-driven model in parallel to obtain the second index prediction model; the output prediction value of the second index prediction model is a weighted sum of the output prediction value of the second mechanism model and the output prediction value of the second data-driven model.

[0011] In conjunction with the first aspect of the present invention, in some embodiments, optimizing the alumina circulating mother liquor formulation strategy based on the first component, the second component, the third component, and a preset target optimization algorithm to obtain the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali includes: initializing the hyperparameters and initial solution group of the target optimization algorithm; the initial solution group includes multiple sets of candidate solutions, each set of candidate solutions including the addition amount of the decomposition mother liquor, the addition amount of the evaporation mother liquor, and the addition amount of the liquid alkali; based on the first component, the second component, and the preset target optimization algorithm, the optimization strategy for the alumina circulating mother liquor formulation strategy to obtain the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali; The third component and the amount added to each of the multiple candidate solutions are used to determine the caustic alkali concentration and molecular ratio of the alumina circulating mother liquor corresponding to each of the multiple candidate solutions; based on the caustic alkali concentration and molecular ratio of the alumina circulating mother liquor corresponding to each of the multiple candidate solutions, the fitness value of each of the multiple candidate solutions is determined; based on the fitness value of each of the multiple candidate solutions, the solution group of the target optimization algorithm is iteratively optimized until a preset iteration termination condition is met, so as to obtain the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali.

[0012] In conjunction with the first aspect of the present invention, in some embodiments, the equipment capability constraints include the allowable range of the amount of the decomposition mother liquor added, the allowable range of the amount of the evaporation mother liquor added, and the allowable range of the amount of the liquid alkali added.

[0013] Secondly, embodiments of the present invention provide a preparation device for alumina circulating mother liquor, comprising: a component acquisition unit for acquiring a first component of decomposition mother liquor, a second component of evaporation mother liquor, and a third component of liquid alkali; an optimization unit for optimizing the preparation strategy of alumina circulating mother liquor based on the first component, the second component, the third component, and a preset target optimization algorithm to obtain a first addition amount of the decomposition mother liquor, a second addition amount of the evaporation mother liquor, and a third addition amount of the liquid alkali; wherein, the optimization variables of the target optimization algorithm are the addition amount of the decomposition mother liquor, the addition amount of the evaporation mother liquor, and the addition amount of the liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints; the optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and a preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and a preset molecular ratio; and a preparation unit for preparing the alumina circulating mother liquor based on the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali.

[0014] Thirdly, embodiments of the present invention provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in any of the first aspects.

[0015] The one or more technical solutions provided in the embodiments of the present invention achieve at least the following technical effects or advantages: This invention involves obtaining a first component of the decomposition mother liquor, a second component of the evaporation mother liquor, and a third component of the liquid alkali. Based on the first, second, and third components and a preset target optimization algorithm, the formulation strategy of the alumina circulating mother liquor is optimized to obtain a first addition amount of the decomposition mother liquor, a second addition amount of the evaporation mother liquor, and a third addition amount of the liquid alkali. The optimization variables of the target optimization algorithm are the addition amounts of the decomposition mother liquor, the evaporation mother liquor, and the liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints. The optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and the preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and the preset molecular ratio. The alumina circulating mother liquor is then formulated based on the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali. By adjusting the amounts of decomposition mother liquor, evaporation mother liquor, and liquid alkali added using a target optimization algorithm, the deviations of the caustic alkali concentration in the alumina circulating mother liquor from the preset caustic alkali concentration, and the deviations of the molecular ratio in the alumina circulating mother liquor from the preset molecular ratio, are minimized. This allows for the preparation of the alumina circulating mother liquor according to demand, avoiding large fluctuations in solution composition caused by manual experience-based preparation. Therefore, the accuracy of alumina circulating mother liquor preparation is improved. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of the method for preparing the alumina circulating mother liquor in an embodiment of the present invention; Figure 2 This is a functional block diagram of the alumina circulating mother liquor preparation device in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0018] 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.

[0019] In this invention, the terms "first," "second," etc., are used 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. Furthermore, 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. If 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.

[0020] This invention provides a method for preparing alumina circulating mother liquor, as described in the following embodiments. Figure 1 As shown, the method includes the following steps S101 to S103: S101: Obtain the first component of the decomposition mother liquor, obtain the second component of the evaporation mother liquor, and obtain the third component of the liquid alkali.

[0021] In some embodiments, the first component of the decomposition mother liquor includes the concentration of caustic alkali, alumina, and carbon alkali in the decomposition mother liquor; the second component of the evaporation mother liquor includes the concentration of caustic alkali, alumina, and carbon alkali in the evaporation mother liquor; and the third component of the liquid alkali includes the concentration of caustic alkali in the liquid alkali.

[0022] In some embodiments, the decomposition mother liquor is obtained by treating the decomposition stock solution with a target decomposition process; obtaining the first component of the decomposition mother liquor includes: obtaining the first material parameters of the decomposition stock solution and the first process parameters of the target decomposition process; inputting the first material parameters and the first process parameters into a first index prediction model to obtain the first component of the decomposition mother liquor.

[0023] It should be noted that the first material parameter includes the seed crystal coefficient and composition. The composition can be the concentration of caustic alkali, alumina, and total alkali; or the concentration of caustic alkali, molecular ratio, and total alkali; or the concentration of caustic alkali, molecular ratio, and carbon-alkali concentration; or the concentration of alumina, molecular ratio, and total alkali concentration; or the concentration of alumina, molecular ratio, and carbon-alkali concentration. The first process parameter includes the stirring speed, initial decomposition temperature, temperatures at different stages of the decomposition process, and decomposition time.

[0024] In some implementations, the first index prediction model is pre-constructed through the following steps: constructing a first mechanism model of the decomposition process based on the principle of seed crystal decomposition; training the first machine learning model with multiple sets of first samples to obtain a first data-driven model of the decomposition process; each set of first samples includes material parameters, process parameters, and composition deviation compensation values ​​of the decomposition process; connecting the first mechanism model and the first data-driven model in parallel to obtain the first index prediction model; the output prediction value of the first index prediction model is a weighted sum of the output prediction value of the first mechanism model and the output prediction value of the first data-driven model.

[0025] It should be noted that the first mechanistic model is a mathematical relationship between material parameters, process parameters, and the composition of the mother liquor in the decomposition process. The first machine learning model can be a dynamic adaptive LSTM neural network model. Multiple sets of first samples can be stable historical production data from the past 3 to 6 months.

[0026] It should be noted that the inputs to the first mechanistic model are the material parameters of the decomposition feedstock and the process parameters of the decomposition process, while the output of the first mechanistic model is the composition of the mother liquor. The inputs to the first data-driven model are the same as those to the first mechanistic model, and the output of the first data-driven model is the deviation compensation value for the composition of the mother liquor. The outputs of the first data-driven model correspond to the outputs of the first mechanistic model. For example, if the output of the first mechanistic model includes the caustic alkali concentration of the mother liquor, then the output of the first data-driven model includes the deviation compensation value for the caustic alkali concentration of the mother liquor. The inputs to the first index prediction model are the inputs to both the first mechanistic model and the first data-driven model.

[0027] In some embodiments, the mother liquor is obtained by treating the raw evaporator with a target evaporation process; obtaining the second component of the mother liquor includes: obtaining the second material parameters of the raw evaporator and the second process parameters of the target evaporation process; inputting the second material parameters and the second process parameters into a second index prediction model to obtain the second component of the mother liquor.

[0028] In some implementations, the second material parameters include the composition, temperature, and flow rate of the evaporating feedstock. The second process parameters include the fresh steam temperature and flow rate, the pressure of each effect evaporator, and the flash evaporator pressure.

[0029] In some implementations, the second index prediction model is pre-built through the following steps: constructing a second mechanism model of the evaporation process based on the principle of multi-effect evaporation; training the second machine learning model with multiple sets of second samples to obtain a second data-driven model of the evaporation process; each set of second samples includes the material parameters, process parameters, and component deviation compensation values ​​of the evaporation process; connecting the second mechanism model and the second data-driven model in parallel to obtain the second index prediction model; the output prediction value of the second index prediction model is a weighted sum of the output prediction value of the second mechanism model and the output prediction value of the second data-driven model.

[0030] It should be noted that the second mechanistic model is a mathematical relationship between material parameters, process parameters, and the composition of the mother liquor in the evaporation process. The second machine learning model can be a dynamic adaptive RNN neural network model. Multiple sets of second samples can be stable historical production data from the past 3 to 6 months.

[0031] It should be noted that the inputs to the second mechanism model are the material parameters of the evaporation feedstock and the process parameters of the evaporation process, while the output of the second mechanism model is the composition of the evaporation mother liquor. The inputs to the second data-driven model are the same as those to the second mechanism model, and the output of the second data-driven model is the deviation compensation value for the composition of the evaporation mother liquor. The outputs of the second data-driven model correspond to the outputs of the second mechanism model. For example, if the output of the second mechanism model includes the caustic alkali concentration of the evaporation mother liquor, then the output of the second data-driven model includes the deviation compensation value for the caustic alkali concentration of the evaporation mother liquor. The inputs to the second index prediction model are the inputs to both the second mechanism model and the second data-driven model.

[0032] It's important to note that the data-driven model is used to compensate for discrepancies between the mechanistic model and actual production data. The mechanistic model provides theoretical predictions of component outputs, ensuring the physical plausibility of the predictions. Simply put, the mechanistic model predicts based on theoretical derivation, while the data-driven model predicts based on data learning. The coupled index prediction model leverages the mechanistic model to ensure the physical plausibility of the predictions while using the data-driven model to compensate for the insufficient prediction accuracy caused by simplifications in assumptions and fluctuations in material properties due to actual operating conditions. Therefore, the index prediction model achieves accurate prediction of mother liquor composition, thereby improving the accuracy of alumina circulating mother liquor formulation.

[0033] S102: Optimize the formulation strategy of alumina circulating mother liquor based on the first component, the second component, the third component, and the preset target optimization algorithm to obtain the first addition amount of decomposition mother liquor, the second addition amount of evaporation mother liquor, and the third addition amount of liquid alkali; wherein, the optimization variables of the target optimization algorithm are the addition amount of decomposition mother liquor, the addition amount of evaporation mother liquor, and the addition amount of liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints; the optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and the preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and the preset molecular ratio.

[0034] In some implementations, the formulation strategy of the alumina circulating mother liquor is optimized based on the first component, the second component, the third component, and a preset target optimization algorithm to obtain the first addition amount of decomposition mother liquor, the second addition amount of evaporation mother liquor, and the third addition amount of liquid alkali. This includes: initializing the hyperparameters and initial solution group of the target optimization algorithm; the initial solution group includes multiple candidate solutions, each candidate solution including the addition amount of decomposition mother liquor, the addition amount of evaporation mother liquor, and the addition amount of liquid alkali; based on the first component, the second component, the third component, and the multiple candidate solutions... The amount of caustic alkali added to each candidate solution is determined, and the concentration and molecular ratio of caustic alkali in the alumina circulating mother liquor corresponding to each candidate solution are determined. Based on the concentration and molecular ratio of caustic alkali in the alumina circulating mother liquor corresponding to each candidate solution, the fitness value of each candidate solution is determined. Based on the fitness value of each candidate solution, the solution group of the target optimization algorithm is iteratively optimized until the preset iteration termination condition is met, so as to obtain the first amount of decomposition mother liquor added, the second amount of evaporation mother liquor added, and the third amount of liquid alkali added.

[0035] In some implementations, equipment capacity constraints include allowable ranges for the addition of decomposition mother liquor, evaporation mother liquor, and liquid alkali. These ranges do not include negative numbers.

[0036] It should be noted that the liquid alkali ratio can be constrained to 0 to 0.15. Specifically, assuming the amount of evaporation mother liquor added is Q1, the amount of decomposition mother liquor added is Q2, and the amount of liquid alkali added is Q3, then 0 ≤ Q3 / (Q1 + Q2 + Q3) ≤ 0.15.

[0037] S103: Based on the first addition amount of decomposition mother liquor, the second addition amount of evaporation mother liquor, and the third addition amount of liquid alkali, prepare the alumina circulating mother liquor.

[0038] It should be noted that after determining the first addition amount of decomposition mother liquor, the second addition amount of evaporation mother liquor, and the third addition amount of liquid alkali, the corresponding amounts of decomposition mother liquor, evaporation mother liquor, and liquid alkali can be injected into the alumina circulating mother liquor mixing tank by means of solenoid valve control.

[0039] It should be noted that the liquid caustic soda can be purchased directly from outside or obtained by "cooking solid caustic soda flakes" on-site in the evaporation area, and the concentration of the liquid caustic soda is known (such as 42% NaOH liquid caustic soda).

[0040] It should be noted that the model in this embodiment of the invention breaks through the limitations of purely data-driven models, and simultaneously solves the difficulties in obtaining complex mechanism models and heat transfer parameters in the decomposition process, ensuring the interpretability and extrapolation of the model. This embodiment of the invention can achieve online continuous detection of the components of both the decomposition mother liquor and the evaporation mother liquor, with prediction accuracy exceeding 98.5%. Based on the composition and characteristics of bauxite, customized formulation of the circulating mother liquor composition can be achieved, with the average accuracy of parameters such as the concentration and molecular ratio of caustic alkali in the circulating mother liquor reaching over 98.5% throughout the entire production cycle, meeting production requirements. The intelligent formulation method for circulating mother liquor in the alumina process proposed in this embodiment of the invention can overcome the limitations of strong alkali systems in alumina production, such as corrosion and scaling of measuring instruments, reduce the time lag in manual analysis, has strong industrial adaptability, can significantly improve the operating efficiency of equipment in the batching and leaching process, reduce system fluctuations, and is suitable for widespread application in alumina enterprises.

[0041] This invention involves obtaining a first component of the decomposition mother liquor, a second component of the evaporation mother liquor, and a third component of the liquid alkali. Based on the first, second, and third components and a preset target optimization algorithm, the formulation strategy of the alumina circulating mother liquor is optimized to obtain a first addition amount of the decomposition mother liquor, a second addition amount of the evaporation mother liquor, and a third addition amount of the liquid alkali. The optimization variables of the target optimization algorithm are the addition amounts of the decomposition mother liquor, the evaporation mother liquor, and the liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints. The optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and the preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and the preset molecular ratio. The alumina circulating mother liquor is then formulated based on the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali. By adjusting the amounts of decomposition mother liquor, evaporation mother liquor, and liquid alkali added using a target optimization algorithm, the deviations of the caustic alkali concentration in the alumina circulating mother liquor from the preset caustic alkali concentration, and the deviations of the molecular ratio in the alumina circulating mother liquor from the preset molecular ratio, are minimized. This allows for the preparation of the alumina circulating mother liquor according to demand, avoiding large fluctuations in solution composition caused by manual experience-based preparation. Therefore, the accuracy of alumina circulating mother liquor preparation is improved.

[0042] Based on the same inventive concept, and referring to Figure 2 As shown, this embodiment of the invention provides a mixing device 10 for alumina circulating mother liquor, comprising: a component acquisition unit 110, used to acquire a first component of decomposition mother liquor, a second component of evaporation mother liquor, and a third component of liquid alkali; an optimization unit 120, used to optimize the mixing strategy of alumina circulating mother liquor based on the first component, the second component, the third component, and a preset target optimization algorithm, to obtain a first addition amount of decomposition mother liquor, a second addition amount of evaporation mother liquor, and a third addition amount of liquid alkali; wherein, the optimization variables of the target optimization algorithm are the addition amount of decomposition mother liquor, the addition amount of evaporation mother liquor, and the addition amount of liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints; the optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and the preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and the preset molecular ratio; and a mixing unit 130, used to mix the alumina circulating mother liquor based on the first addition amount of decomposition mother liquor, the second addition amount of evaporation mother liquor, and the third addition amount of liquid alkali. The first component of the decomposition mother liquor includes the concentrations of caustic alkali, alumina, and carbon alkali in the decomposition mother liquor; the second component of the evaporation mother liquor includes the concentrations of caustic alkali, alumina, and carbon alkali in the evaporation mother liquor; and the third component of the liquid alkali includes the concentration of caustic alkali in the liquid alkali.

[0043] It is understood that the decomposition mother liquor is obtained by treating the decomposition raw liquid through the target decomposition process; the component acquisition unit 110 includes: a first acquisition subunit, used to acquire the first component of the decomposition mother liquor; the first acquisition subunit is specifically used to: acquire the first material parameters of the decomposition raw liquid and the first process parameters of the target decomposition process; input the first material parameters and the first process parameters into the first index prediction model to obtain the first component of the decomposition mother liquor.

[0044] It is understandable that the alumina circulating mother liquor preparation device 10 also includes: a first model building unit, used to construct a first index prediction model; the first model building unit is specifically used to: construct a first mechanism model of the decomposition process based on the principle of seed crystal decomposition process; train the first machine learning model through multiple sets of first samples to obtain a first data-driven model of the decomposition process; each set of first samples includes the material parameters, process parameters, and component deviation compensation values ​​of the decomposition process; connect the first mechanism model and the first data-driven model in parallel to obtain a first index prediction model; the output prediction value of the first index prediction model is a weighted sum of the output prediction value of the first mechanism model and the output prediction value of the first data-driven model.

[0045] It is understood that the mother liquor is obtained by processing the raw liquid through the target evaporation process; the component acquisition unit 110 further includes: a second acquisition subunit for acquiring the second component of the mother liquor; the second acquisition subunit is specifically used for: acquiring the second material parameters of the raw liquid and the second process parameters of the target evaporation process; and inputting the second material parameters and the second process parameters into the second index prediction model to obtain the second component of the mother liquor.

[0046] It is understandable that the alumina circulating mother liquor preparation device 10 also includes: a second model building unit, used to construct a second index prediction model; the second model building unit is specifically used to: construct a second mechanism model of the evaporation process based on the principle of multi-effect evaporation; train the second machine learning model through multiple sets of second samples to obtain a second data-driven model of the evaporation process; each set of second samples includes the material parameters, process parameters, and component deviation compensation values ​​of the evaporation process; connect the second mechanism model and the second data-driven model in parallel to obtain a second index prediction model; the output prediction value of the second index prediction model is a weighted sum of the output prediction value of the second mechanism model and the output prediction value of the second data-driven model.

[0047] Understandably, the optimization unit 120 is specifically used for: initializing the hyperparameters and initial solution group of the target optimization algorithm; the initial solution group includes multiple candidate solutions, each candidate solution including the amount of decomposition mother liquor added, the amount of evaporation mother liquor added, and the amount of liquid alkali added; based on the first component, the second component, the third component, and the amount of each candidate solution in the multiple candidate solutions, determining the caustic alkali concentration and molecular ratio of the alumina circulating mother liquor corresponding to each candidate solution in the multiple candidate solutions; based on the caustic alkali concentration and molecular ratio of the alumina circulating mother liquor corresponding to each candidate solution in the multiple candidate solutions, determining the fitness value of each candidate solution in the multiple candidate solutions; based on the fitness value of each candidate solution in the multiple candidate solutions, iteratively optimizing the solution group of the target optimization algorithm until the preset iteration termination condition is met, so as to obtain the first amount of decomposition mother liquor added, the second amount of evaporation mother liquor added, and the third amount of liquid alkali added.

[0048] Among them, the equipment capacity constraints include the allowable range of the amount of decomposition mother liquor added, the allowable range of the amount of evaporation mother liquor added, and the allowable range of the amount of liquid alkali added.

[0049] It should be understood that further implementation details of the alumina circulating mother liquor preparation device 10 in the embodiments of the present invention are as described in the aforementioned alumina circulating mother liquor preparation method, and will not be repeated here for the sake of brevity.

[0050] Based on the same inventive concept, embodiments of the present invention also provide an electronic device, such as... Figure 3As shown, it includes a memory 304, a processor 302, and a computer program stored in the memory 304 and executable on the processor 302. The processor 302 executes the program to implement the steps described in any embodiment of the method for preparing alumina circulating mother liquor.

[0051] Among them, Figure 3 In this document, a bus architecture (represented by bus 300) is used. Bus 300 may include any number of interconnected buses and bridges, linking various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same element, i.e., a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 can be used to store data used by processor 302 during operation.

[0052] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this invention and the appended claims. For example, due to the nature of software, the functions described above can be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units can be integrated into a single processing unit, or each unit can exist physically separately, or two or more units can be integrated into a single unit.

[0053] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0054] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0055] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0056] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for preparing alumina circulating mother liquor, characterized in that, include: Obtain the first component of the decomposition mother liquor, the second component of the evaporation mother liquor, and the third component of the liquid alkali; Based on the first component, the second component, the third component, and a preset target optimization algorithm, the formulation strategy of the alumina circulating mother liquor is optimized to obtain the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali. The optimization variables of the target optimization algorithm are the addition amounts of the decomposition mother liquor, the evaporation mother liquor, and the liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints. The optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and the preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and the preset molecular ratio. The alumina circulating mother liquor is prepared based on the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali.

2. The method for preparing alumina circulating mother liquor according to claim 1, characterized in that, The first component of the decomposition mother liquor includes the concentration of caustic alkali, the concentration of alumina, and the concentration of carbon alkali in the decomposition mother liquor; The second component of the evaporation mother liquor includes the concentration of caustic alkali, the concentration of alumina, and the concentration of carbon alkali in the evaporation mother liquor; The third component of the liquid alkali includes the caustic alkali concentration of the liquid alkali.

3. The method for preparing alumina circulating mother liquor according to claim 1, characterized in that, The decomposition mother liquor is obtained by treating the decomposition stock liquor using the target decomposition process; The first component of the decomposition mother liquor obtained includes: Obtain the first material parameters of the decomposition stock solution and the first process parameters of the target decomposition process; The first material parameters and the first process parameters are input into the first index prediction model to obtain the first component of the decomposition mother liquor.

4. The method for preparing alumina circulating mother liquor according to claim 3, characterized in that, The first indicator prediction model is pre-built through the following steps: A first mechanism model of the decomposition process is constructed based on the principle of seed crystal decomposition process; The first machine learning model is trained by multiple sets of first samples to obtain the first data-driven model of the decomposition process; each set of first samples includes the material parameters, process parameters, and component deviation compensation values ​​of the decomposition process. The first mechanism model and the first data-driven model are connected in parallel to obtain the first indicator prediction model; the output prediction value of the first indicator prediction model is a weighted sum of the output prediction value of the first mechanism model and the output prediction value of the first data-driven model.

5. The method for preparing alumina circulating mother liquor according to claim 1, characterized in that, The mother liquor is obtained by treating the raw evaporator using a target evaporation process; obtaining the second component of the mother liquor includes: Obtain the second material parameters of the evaporation stock solution and the second process parameters of the target evaporation process; The second material parameters and the second process parameters are input into the second index prediction model to obtain the second component of the evaporation mother liquor.

6. The method for preparing alumina circulating mother liquor according to claim 5, characterized in that, The second indicator prediction model is pre-built through the following steps: A second mechanism model of the evaporation process is constructed based on the principle of multi-effect evaporation. The second machine learning model is trained by multiple sets of second samples to obtain the second data-driven model of the evaporation process; each set of second samples includes the material parameters, process parameters, and component deviation compensation values ​​of the evaporation process. The second mechanism model and the second data-driven model are connected in parallel to obtain the second index prediction model; the output prediction value of the second index prediction model is the weighted sum of the output prediction value of the second mechanism model and the output prediction value of the second data-driven model.

7. The method for preparing alumina circulating mother liquor according to claim 1, characterized in that, The optimization of the alumina circulating mother liquor formulation strategy based on the first component, the second component, the third component, and a preset target optimization algorithm to obtain the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali includes: The hyperparameters and initial solution group of the target optimization algorithm are initialized; the initial solution group includes multiple sets of candidate solutions, each set of candidate solutions including the amount of the decomposition mother liquor added, the amount of the evaporation mother liquor added, and the amount of the liquid alkali added; Based on the addition amount of the first component, the second component, the third component, and each candidate solution in the plurality of candidate solutions, the caustic alkali concentration and molecular ratio of the alumina circulating mother liquor corresponding to each candidate solution in the plurality of candidate solutions are determined. Based on the caustic alkali concentration and molecular ratio of the alumina circulating mother liquor corresponding to each of the multiple candidate solutions, the fitness value of each of the multiple candidate solutions is determined. Based on the fitness value of each candidate solution in the multiple candidate solutions, the solution group of the target optimization algorithm is iteratively optimized until the preset iteration termination condition is met, so as to obtain the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali.

8. The method for preparing alumina circulating mother liquor according to any one of claims 1-7, characterized in that, The equipment capacity constraints include the allowable range of the amount of the decomposition mother liquor added, the allowable range of the amount of the evaporation mother liquor added, and the allowable range of the amount of the liquid alkali added.

9. A device for preparing alumina circulating mother liquor, characterized in that, include: The component acquisition unit is used to acquire the first component of the decomposition mother liquor, the second component of the evaporation mother liquor, and the third component of the liquid alkali. An optimization unit is used to optimize the formulation strategy of the alumina circulating mother liquor based on the first component, the second component, the third component, and a preset target optimization algorithm, so as to obtain the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali; wherein, the optimization variables of the target optimization algorithm are the addition amount of the decomposition mother liquor, the addition amount of the evaporation mother liquor, and the addition amount of the liquid alkali, and the boundary constraints include liquid alkali ratio constraints and equipment capacity constraints; the optimization objectives of the target optimization algorithm include minimizing the deviation between the caustic alkali concentration of the alumina circulating mother liquor and the preset caustic alkali concentration, and minimizing the deviation between the molecular ratio of the alumina circulating mother liquor and the preset molecular ratio; The mixing unit is used to mix the alumina circulating mother liquor based on the first addition amount of the decomposition mother liquor, the second addition amount of the evaporation mother liquor, and the third addition amount of the liquid alkali.

10. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-8.

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