NdFeB waste recycling parameter optimization method and system based on recovery rate prediction

Abstract

The present invention relates to the technical field related to NdFeB recovery, specifically including a method and system for optimizing NdFeB waste recovery parameters for recovery rate prediction, including: determining physical property indicators, configuring a pyrolysis parameter set in combination with pyrolysis temperature gradient simulation, uploading acid leaching concentration parameters, configuring an acid leaching parameter combination, coupled analysis and iteration, and collecting parameters to establish a recovery parameter feedback adjustment mechanism. The method solves the technical problem that fixed pyrolysis parameters are difficult to adapt to different waste characteristics, and the change in waste characteristics after pyrolysis directly affects the acid leaching efficiency, causing a dense inert layer to form on the surface of some waste after pyrolysis, thereby falling into a dissolution bottleneck. The method realizes the analysis of the recovery process under different temperature gradients, accurately configures the recovery process parameter set corresponding to different pyrolysis temperature ranges, fully considers the coupling relationship between acid leaching and pyrolysis, ensures that the dissolution efficiency of rare earth elements, the amount of impurities dissolved and the reaction rate under different acid leaching concentrations reach the best balance, and improves the recovery efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field related to NdFeB recycling, and in particular to a method and system for optimizing NdFeB waste recycling parameters for recovery rate prediction. Background Art

[0002] NdFeB permanent magnet materials, as an important carrier for the application of rare earth elements, have excellent magnetic properties and are widely used in many products such as wind turbines, electric vehicles, and smart home appliances. During the production, processing, and use of NdFeB permanent magnet materials, a large amount of NdFeB waste is inevitably generated. These wastes contain rich rare earth elements. If they cannot be effectively recycled, it will not only cause a huge waste of rare earth resources, but also cause serious pollution to the environment.

[0003] However, due to the differences in the physical properties of NdFeB waste, such as the rare earth element content, oxide layer thickness and magnetic phase distribution parameters, the diffusion of rare earth elements, the decomposition of the oxide layer and the reconstruction of the magnetic phase during pyrolysis are difficult to accurately control, which in turn affects the recycling effect.

[0004] In summary, the existing technology has the technical problem that fixed pyrolysis parameters are difficult to adapt to different waste characteristics, and the changes in waste characteristics after pyrolysis directly affect the acid leaching efficiency, causing a dense inert layer to form on the surface of some waste after pyrolysis, thus falling into a dissolution bottleneck. Summary of the Invention

[0005] This application provides a NdFeB waste recycling parameter optimization system with recovery rate prediction, aiming to solve the technical problem in the existing technology that fixed pyrolysis parameters are difficult to adapt to different waste characteristics, changes in waste characteristics after pyrolysis directly affect the acid leaching efficiency, and cause a dense inert layer to form on the surface of some waste after pyrolysis, thus falling into a dissolution bottleneck.

[0006] In view of the above problems, the technical solution to implement this application is:

[0007] In one aspect, the present application provides a method for optimizing NdFeB waste recycling parameters for recovery rate prediction, wherein the method comprises:

[0008] According to the target NdFeB scrap, the physical property indicators including rare earth element content, oxide layer thickness and magnetic phase distribution parameters are determined; the pyrolysis temperature gradient is introduced, and the rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction processes under different temperature gradients are simulated through finite element analysis in combination with the physical property indicators, and a set of recovery process parameters corresponding to different pyrolysis temperature ranges is configured; the acid leaching concentration parameters are uploaded, and the acid leaching parameter combination that meets the preset recovery rate target value is configured through multivariate analysis of the rare earth element dissolution efficiency, impurity dissolution amount and reaction rate under different acid leaching concentrations in combination with the physical property indicators. The preset recovery rate target value is associated with the scrap recycling task; the recovery process parameter set corresponding to the different pyrolysis temperature ranges and the acid leaching parameter combination are coupled and analyzed, a collaborative optimization matrix is set, and the recovery parameters are iterated according to the scrap recycling task, and the actual recovery rate of rare earth elements, impurity residue, reaction energy consumption and equipment operation status parameters are simultaneously collected to establish a recovery parameter feedback adjustment mechanism.

[0009] On the other hand, the present application provides a NdFeB waste recycling parameter optimization system for recovery rate prediction, wherein the system comprises:

[0010] An indicator determination module is used to determine the physical property indicators including rare earth element content, oxide layer thickness and magnetic phase distribution parameters based on the target NdFeB scrap; a first configuration module is used to introduce a pyrolysis temperature gradient, and combine the physical property indicators to simulate the rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction process under different temperature gradients through finite element analysis, and configure a set of recovery process parameters corresponding to different pyrolysis temperature ranges; a second configuration module is used to upload acid leaching concentration parameters, and combine the physical property indicators to configure an acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of rare earth element dissolution efficiency, impurity dissolution amount and reaction rate under different acid leaching concentrations, and the preset recovery rate target value is associated with the scrap recycling task; a coupling analysis module is used to couple the recovery process parameter set corresponding to the different pyrolysis temperature ranges with the acid leaching parameter combination, set a collaborative optimization matrix, and iterate the recovery parameters according to the scrap recycling task, synchronously collect the actual recovery rate of rare earth elements, impurity residue, reaction energy consumption, and equipment operating status parameters, and establish a recovery parameter feedback adjustment mechanism.

[0011] In summary, the one or more technical solutions provided in this application realize the analysis of the recovery process under different temperature gradients, combine the physical properties of the waste, accurately configure the recovery process parameter sets corresponding to different pyrolysis temperature ranges, fully consider the coupling relationship between acid leaching and pyrolysis, and ensure that the dissolution efficiency of rare earth elements, impurity dissolution amount and reaction rate under different acid leaching concentrations reach the best balance, thereby improving the technical effect of recovery efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flow chart of a method for optimizing NdFeB waste recycling parameters with recovery rate prediction is provided for this application;

[0013] Figure 2 A structural diagram of a NdFeB waste recycling parameter optimization system for recovery rate prediction is provided for this application.

[0014] Description of reference numerals: indicator determination module M100, first configuration module M200, second configuration module M300, coupling analysis module M400. DETAILED DESCRIPTION

[0015] Example 1: The present application will be described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides a method for optimizing NdFeB waste recycling parameters for recovery rate prediction, wherein the method comprises:

[0016] S1: Based on the target NdFeB scrap, determine the physical property indicators including rare earth element content, oxide layer thickness and magnetic phase distribution parameters.

[0017] Specifically, the key physical property indicators of the target NdFeB scrap are identified. The rare earth element content determines the potential for recovering rare earths in the scrap. The thickness of the oxide layer affects the diffusion difficulty of rare earth elements during pyrolysis. The magnetic phase distribution parameters are related to the existence form and distribution range of the magnetic phase in the scrap. These factors together determine the reaction characteristics of the scrap in the subsequent pyrolysis and acid leaching processes.

[0018] In a feasible embodiment, the detection of rare earth element content can be achieved through spectral analysis and other technologies, the thickness of the oxide layer can be measured by scanning electron microscopy combined with energy spectrum analysis, and the magnetic phase distribution parameters can be characterized by means of X-ray diffraction and other means. For example, in the detection of a specific batch of NdFeB waste, if the rare earth element content is 30%, the average oxide layer thickness is 5 microns, and the magnetic phase distribution is relatively uniform, then when configuring the subsequent pyrolysis and acid leaching process parameters, it is necessary to use these specific values to accurately determine the treatment conditions suitable for this batch of waste to ensure the efficiency of the recycling process.

[0019] S2: Introduce a pyrolysis temperature gradient, and simulate the rare earth element diffusion, oxide layer decomposition, and magnetic phase reconstruction processes under different temperature gradients through finite element analysis in combination with the physical property indicators, and configure a set of recovery process parameters corresponding to different pyrolysis temperature ranges.

[0020] Specifically, the introduction of pyrolysis temperature gradient refers to setting a series of different temperature intervals during the pyrolysis process to simulate the diffusion of rare earth elements, decomposition of oxide layers and reconstruction of magnetic phases. It uses the finite element analysis method to establish a mathematical model based on predetermined physical property indicators (rare earth element content, oxide layer thickness and magnetic phase distribution parameters), and simulates the physical and chemical changes inside the waste at different temperatures through a computer; configures a set of recycling process parameters corresponding to different pyrolysis temperature intervals, that is, based on the simulation results, sets the corresponding pyrolysis time, heating rate, holding time, atmosphere flow rate and other process parameter combinations for each temperature interval to adapt to the pyrolysis requirements of waste with different physical properties.

[0021] In one feasible implementation, finite element analysis simulations revealed that in the first temperature range (100°C-300°C), the rare earth element diffusion rate is slow, the oxide layer has not yet begun to decompose, and the magnetic phase remains stable. In the second temperature range (300°C-500°C), the oxide layer begins to decompose, the rare earth element diffusion rate accelerates, but the magnetic phase has not yet undergone significant reconstruction. In the third temperature range (500°C-800°C), the rare earth elements diffuse fully, the oxide layer completely decomposes, and the magnetic phase reconstructs. Based on the simulation results, a set of recycling process parameters is configured for each temperature range. By precisely controlling the temperature gradient and corresponding process parameters, sufficient rare earth element diffusion, complete oxide layer decomposition, and appropriate magnetic phase reconstruction are achieved.

[0022] Preferably, the pyrolysis method using a temperature gradient and a corresponding parameter set effectively solves the problem of poor pyrolysis effect due to differences in the physical properties of the waste, provides a good material basis for the subsequent acid leaching process, and ensures the improvement of the overall recovery efficiency.

[0023] S3: Upload the acid leaching concentration parameters, and configure an acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of the rare earth element dissolution efficiency, impurity dissolution amount, and reaction rate at different acid leaching concentrations in combination with the physical property indicators. The preset recovery rate target value is associated with the waste recovery task.

[0024] Specifically, uploading acid leaching concentration parameters refers to inputting a series of acid parameters of different concentrations, which will be used for subsequent multivariate analysis; multivariate analysis refers to comprehensively considering multiple factors such as rare earth element dissolution efficiency, impurity dissolution amount, reaction rate, etc., and analyzing the changing trends and mutual relationships of these factors at different acid leaching concentrations by establishing a mathematical model and using statistical methods, so as to determine the optimal acid leaching conditions.

[0025] In one feasible implementation, a series of hydrochloric acid leaching parameters of different concentrations (such as 1 mol / L, 2 mol / L, 3 mol / L, 4 mol / L, and 5 mol / L) are uploaded. Through multivariate analysis, the balance between rare earth element dissolution efficiency, impurity dissolution amount, and reaction rate under different acid leaching concentrations is fully considered, and the physical property indicators of the waste are accurately matched. This effectively improves the pertinence and effectiveness of the acid leaching process, ensures that the overall recovery process achieves the predetermined recovery rate target, and improves the economy and environmental protection of rare earth element recovery.

[0026] S4: Conduct coupling analysis on the recovery process parameter sets and acid leaching parameter combinations corresponding to the different pyrolysis temperature ranges, set up a collaborative optimization matrix, and iterate the recovery parameters according to the waste recovery task. Simultaneously collect the actual recovery rate of rare earth elements, residual impurities, reaction energy consumption, and equipment operating status parameters, and establish a recovery parameter feedback adjustment mechanism.

[0027] Specifically, coupling analysis refers to the joint analysis of the set of recovery process parameters corresponding to the pyrolysis temperature range and the acid leaching parameter combination to study the interaction and influence between the two; the collaborative optimization matrix is used to comprehensively consider various parameters in the pyrolysis and acid leaching processes, and find the optimal parameter combination through matrix operations; recycling parameter iteration refers to the process of repeatedly adjusting and optimizing the pyrolysis and acid leaching parameters based on the results of each recycling process; the recycling parameter feedback adjustment mechanism is used to collect and analyze data in the recycling process in real time, and then dynamically adjust the recycling parameters based on these data to ensure the efficiency and stability of the recycling process.

[0028] In a feasible embodiment, there is a set of recovery process parameters corresponding to a pyrolysis temperature range (such as 300°C, 400°C, and 500°C), and a set of acid leaching parameter combinations corresponding to acid leaching concentrations (such as 1 mol / L, 2 mol / L, and 3 mol / L). Through coupling analysis, it was found that when the pyrolysis temperature is 400°C, the oxide layer of the waste material is more fully decomposed. At this time, under the condition of an acid leaching concentration of 2 mol / L, the dissolution efficiency of rare earth elements is the highest. Based on this result, a pyrolysis temperature of 400°C and an acid leaching concentration of 2 mol / L are set as the initial optimization combination in the collaborative optimization matrix.

[0029] During the execution of the waste recycling task, the first recycling parameter iteration is carried out, and data is collected synchronously. Adjustments are made in the next iteration through the recycling parameter feedback adjustment mechanism. Through this coupled analysis and parameter iteration method, combined with real-time data feedback adjustment, the optimal recycling parameter combination is determined, and the efficient completion of the waste recycling task is achieved, ensuring that the rare earth element recovery rate is stable above the target value, while reducing impurity residues and reaction energy consumption, and improving the reliability of equipment operation.

[0030] Furthermore, the actual recovery rate of rare earth elements, residual impurities, reaction energy consumption, and equipment operating status parameters are collected simultaneously to establish a recovery parameter feedback adjustment mechanism. The present application method includes:

[0031] According to the preset recovery rate target value, the recovery rate prediction feedback optimization is carried out in combination with the actual recovery rate of the rare earth elements, the residual impurities, the reaction energy consumption, and the equipment operating status parameters; at the same time, a recovery parameter feedback adjustment mechanism is established in combination with the recovery reaction conditions.

[0032] Specifically, recovery rate prediction feedback refers to the dynamic prediction and adjustment of the recovery process based on the actual collected rare earth element recovery rate, impurity residue, reaction energy consumption and equipment operating status parameters, and further establishing a prediction model. The prediction model uses the actual recovery rate, impurity residue, reaction energy consumption and other parameters as input, and the optimized recovery parameters as output; the recovery parameter feedback adjustment mechanism automatically adjusts the process parameters of pyrolysis and acid leaching according to the output of the prediction model to ensure the efficiency and stability of the recovery process.

[0033] In a feasible implementation method, through continuous feedback and optimization iteration of the feedback regulation mechanism, the equipment operation status tends to be stable; the dynamic adjustment mechanism based on real-time data can effectively respond to changes in the physical properties of waste and fluctuations in equipment operation, ensuring that the recycling process always runs around the preset goals, thereby improving overall recycling efficiency and product quality.

[0034] Furthermore, in combination with the recovery reaction conditions, the method of the present application includes:

[0035] An infrared temperature measurement array is deployed to generate a three-dimensional temperature field distribution cloud map, which is used to restore the energy absorption and transfer characteristics of different positions during the pyrolysis process. Based on the dielectric constant of the waste material, the pyrolysis is partitioned in combination with the three-dimensional temperature field distribution cloud map, and a gradient temperature control interval is set, wherein the gradient temperature control interval includes an oxide layer decomposition temperature control zone and a magnetic phase reconstruction temperature control zone.

[0036] Specifically, the infrared temperature measurement array is a sensor array composed of multiple infrared temperature measurement points, which is used to monitor the temperature changes at various locations of the waste during the pyrolysis process in real time; the three-dimensional temperature field distribution cloud map is an image generated by processing and visualizing the data collected by the temperature measurement array, showing the temperature distribution at different locations of the waste during the pyrolysis process; the dielectric constant of the waste is a physical quantity that measures the degree of polarization of the waste in the electromagnetic field, and is closely related to the composition and structure of the waste; the gradient temperature control interval refers to dividing the entire pyrolysis area into multiple temperature control intervals according to the different physical properties of the waste, and each interval corresponds to a different temperature setting; the oxide layer decomposition temperature control zone and the magnetic phase reconstruction temperature control zone are special temperature control areas set for the two key processes of waste oxide layer decomposition and magnetic phase reconstruction respectively.

[0037] In one feasible implementation, an infrared temperature measurement array is deployed inside the pyrolysis reactor, with a temperature measurement point set at a certain interval (e.g., 10 cm) to form a three-dimensional temperature measurement network. During the pyrolysis process, the infrared temperature measurement array collects temperature data in real time, updates it once per second, and generates a three-dimensional temperature field distribution cloud map through the data processing system.

[0038] Using the three-dimensional temperature field distribution cloud map, it is determined that the temperature in the center of the waste is lower and the temperature near the reactor wall is higher, resulting in uneven decomposition of the oxide layer; by measuring the dielectric constant of the waste and combining it with the three-dimensional temperature field distribution cloud map, the pyrolysis area is divided into multiple zones; in the gradient temperature control range, the pyrolysis efficiency is significantly improved, the recovery rate of rare earth elements is increased, and better quality materials are provided for the subsequent acid leaching process, ensuring the efficient implementation of the overall recovery process while reducing energy consumption.

[0039] Furthermore, based on the dielectric constant of the waste material and in combination with the three-dimensional temperature field distribution cloud map, pyrolysis partitioning is performed and a gradient temperature control range is set. The method of the present application also includes:

[0040] During the waste pretreatment stage, a microwave resonant cavity array is introduced to generate a three-dimensional electromagnetic field hotspot distribution map based on the dielectric constant of the waste. An alternating magnetic field is applied using a Helmholtz coil assembly, and after generating an eddy current thermal effect, the infrared temperature measurement array is activated. At the same time, based on the three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map, the local hotspot area is located, and the gradient temperature control range is dynamically fine-tuned.

[0041] Specifically, a microwave resonant cavity array is a device that uses microwave energy to pre-treat waste. Through the synergistic effect of multiple resonant cavities, the microwave energy can be evenly distributed in the waste. The three-dimensional electromagnetic field hotspot distribution map is an image generated by electromagnetic field simulation software based on the dielectric constant of the waste and the working parameters of the microwave resonant cavity array. It is used to show the distribution of electromagnetic field intensity inside the waste. Among them, the hotspot area represents the area where electromagnetic field energy is concentrated and the temperature rises. The Helmholtz coil group is a coil structure that can generate a uniform alternating magnetic field. By applying an alternating magnetic field, eddy current thermal effects are induced inside the waste, further heating the waste. Dynamic fine-tuning refers to making slight adjustments to the temperature settings of the gradient temperature control range based on real-time monitoring data (such as the three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map) to achieve more precise temperature control.

[0042] In a feasible embodiment, during the waste pretreatment stage, a microwave resonant cavity array is introduced, and a three-dimensional electromagnetic field hotspot distribution map is generated based on the dielectric constant of the waste. Furthermore, under the action of the microwave resonant cavity array, multiple electromagnetic field hotspot areas are found inside the waste, among which the electromagnetic field intensity in the electromagnetic field hotspot area is higher than that in the surrounding area by a certain proportion (30%). At this time, an alternating magnetic field is applied using a Helmholtz coil group to generate an eddy current thermal effect inside the waste, causing the temperature of the electromagnetic field hotspot area to rise; then the infrared temperature measurement array is started, temperature data is collected at a fixed frequency, and a three-dimensional temperature field distribution cloud map is generated.

[0043] By comparing the three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map, it was found that the temperature in the hotspot area is positively correlated with the electromagnetic field intensity, that is, the higher the electromagnetic field intensity, the greater the temperature rise; based on these data, the gradient temperature control range is dynamically fine-tuned, and the temperature setting of the low-temperature blind area is increased. After fine-tuning, the temperature distribution inside the waste is more uniform, which increases the decomposition rate of the oxide layer and the reconstruction rate of the magnetic phase, providing more uniform and higher-quality materials for subsequent pyrolysis and acid leaching processes, effectively improving the recovery efficiency of rare earth elements, and at the same time reducing energy waste and equipment loss caused by uneven temperature.

[0044] Furthermore, the present application method also includes:

[0045] The three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map are spatially aligned to identify local overheating areas and low-temperature blind areas under the electromagnetic-thermal field coupling effect; a temperature gradient compensation matrix is established based on the local overheating areas and low-temperature blind areas under the electromagnetic-thermal field coupling effect; energy consumption constraints are introduced, and based on the temperature gradient compensation matrix, a collaborative optimization mapping instruction set of the gradient temperature control range and the acid leaching concentration parameter is configured.

[0046] Specifically, spatial registration refers to the precise alignment of the three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map in the same coordinate system, so as to accurately compare and analyze the correspondence between the two; the local overheating area refers to the area where the temperature is significantly higher than the surrounding area under the coupling of electromagnetic and thermal fields and may affect the waste treatment effect; the low-temperature blind area refers to the area where the temperature fails to reach the expected value due to the uneven distribution of electromagnetic and thermal fields during the pyrolysis process; the temperature gradient compensation matrix is used to describe the temperature deviation in different areas and provide corresponding compensation solutions; the energy consumption constraint refers to the energy consumption limit that must be met during the optimization process to ensure the economy and feasibility of the entire recycling process; the collaborative optimization mapping instruction set is a pre-defined instruction used to guide the collaborative optimization adjustment between the gradient temperature control range and the acid leaching concentration parameters to achieve the best recovery effect.

[0047] In a feasible implementation, a three-dimensional electromagnetic field hotspot distribution map and a three-dimensional temperature field distribution cloud map are generated through the action of a microwave resonant cavity array and a Helmholtz coil group; after spatial alignment, local overheating areas and low-temperature blind areas are found inside the waste, and a temperature gradient compensation matrix is established. The temperature gradient compensation matrix sets compensation values for the local overheating areas and low-temperature blind areas. At the same time, energy consumption constraints are introduced to limit the energy consumption of the pyrolysis-acid leaching process; based on the temperature gradient compensation matrix, a collaborative optimization mapping instruction set of gradient temperature control intervals and acid leaching concentration parameters is configured; through this collaborative optimization method, the coupling relationship between acid leaching and pyrolysis is fully considered to ensure that the dissolution efficiency of rare earth elements, impurity dissolution amount and reaction rate are optimally balanced under different acid leaching concentrations.

[0048] Furthermore, the present application method includes:

[0049] The matching degree between the decomposition rate of the oxide layer and the reconstruction rate of the magnetic phase in the local hot spot area is obtained, and a judgment is made in combination with the preset rate deviation to set the matching compensation rule; wherein, the technical parameter indicators associated with the matching compensation rule include microwave power density, Helmholtz coil current phase angle, and pyrolysis residence time.

[0050] Specifically, obtaining the matching degree between the oxide layer decomposition rate and the magnetic phase reconstruction rate in the local hotspot area means determining the coordination between the two rates by monitoring and analyzing the oxide layer decomposition rate and the magnetic phase reconstruction rate in the local hotspot area; judging in combination with the preset rate deviation is to compare the actual measured rate with the pre-set standard rate to determine whether adjustment is needed. Setting the matching compensation rule is to formulate corresponding rules to adjust the relevant parameters based on the judgment results to achieve matching between the oxide layer decomposition rate and the magnetic phase reconstruction rate. The corresponding technical parameter indicators include microwave power density, Helmholtz coil current phase angle and pyrolysis residence time, which correspond to the heating intensity, magnetic field distribution and pyrolysis reaction time that affect the waste.

[0051] In a feasible embodiment, in the local hot spot area, the measured oxide layer decomposition rate is 0.05 μm / min, and the magnetic phase reconstruction rate is 0.04 μm / min. The preset rate deviation allowable range is ±0.01 μm / min, and the matching degree M between the two is calculated as: M=|0.05-0.04|=0.01 μm / min; because the matching degree M reaches the upper limit of the preset deviation, it is determined that compensation adjustment is required; according to the matching compensation rule, the microwave power density, Helmholtz coil current phase angle and pyrolysis residence time are adjusted, wherein the microwave power density adjustment is used to reduce the microwave power density to slow down the oxide layer decomposition rate; the Helmholtz coil current phase angle adjustment is intended to optimize the current phase angle to improve the magnetic field distribution and promote magnetic phase reconstruction; the pyrolysis residence time adjustment is intended to extend the pyrolysis time to balance the two rates; after adjustment, the oxide layer decomposition rate and magnetic phase reconstruction rate are measured again, and the matching degree M is calculated again. Through precise rate matching and parameter adjustment, the coordinated decomposition of the oxide layer and the reconstruction of the magnetic phase during the pyrolysis process are ensured, thereby improving the overall recovery efficiency and product quality.

[0052] Furthermore, the preset recovery rate target value is associated with the waste recycling task, and the method of the present application further includes:

[0053] During the acid leaching treatment stage, an acid leaching optimization space is set with the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable in combination with the acid leaching reaction time. In the acid leaching optimization space, a global search is performed with the rare earth leaching rate and the acid consumption ratio as objective functions to determine an acid leaching optimization parameter sequence synchronized with the acid leaching reaction time. The acid leaching optimization parameter sequence is mapped one-to-one with the acid leaching parameter combination.

[0054] Specifically, the acid leaching optimization space refers to the multi-dimensional combination range composed of parameters such as stirring rate (continuous variable), solid-liquid ratio (discrete variable) and acid leaching reaction time during the acid leaching process; within this acid leaching optimization space, different parameter combinations correspond to different acid leaching effects; rare earth leaching rate is a measure of the efficiency of leaching rare earth elements from waste into solution, usually expressed as a percentage; acid consumption ratio reflects the amount of acid consumed per unit mass or volume of waste during the acid leaching process, and is often used to evaluate the economy of the acid leaching process and the utilization efficiency of the acid; global search is to find the parameter combination that makes the objective function (a comprehensive indicator of rare earth leaching rate and acid consumption ratio) reach the optimal value through comprehensive scanning and analysis within the acid leaching optimization space.

[0055] In one feasible embodiment, during the acid leaching process, an acid leaching optimization space is set, using the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable, combined with the acid leaching reaction time. For example, when processing a batch of NdFeB scrap, the stirring rate can be continuously adjusted within the range of 0 to 1000 r / min, the solid-liquid ratio can be selected as discrete values such as 1:5, 1:10, and 1:15, and the acid leaching reaction time can be set between 30 and 180 minutes. Within the acid leaching optimization space, a global search is performed using the rare earth leaching rate and acid consumption ratio as the objective function to determine the acid leaching optimization parameter sequence synchronized with the acid leaching reaction time. Through experiments and simulations, it was found that when the stirring rate was 600 r / min, the rare earth element leaching rate reached 85%, and the acid consumption ratio was 0.8 L / kg; when the solid-liquid ratio was 1:10, the leaching rate was 80%, and the acid consumption ratio was 0.7 L / kg; when the acid leaching reaction time was 120 minutes, the leaching rate was 82%, and the acid consumption ratio was 0.75 L / kg. The final optimized acid leaching parameter sequence was determined as follows: a stirring rate of 600 rpm, a solid-liquid ratio of 1:10, and an acid leaching reaction time of 120 minutes. These parameters formed a one-to-one correlation mapping with the acid leaching parameters. This optimization process significantly improved the recovery rate of rare earth elements while reducing acid consumption, improving the economic and environmental performance of the acid leaching process.

[0056] Furthermore, a global search is performed with the rare earth leaching rate and the acid consumption ratio as the objective function to determine the acid leaching optimization parameter sequence synchronized with the acid leaching reaction time. The method of the present application also includes:

[0057] Based on the acid leaching optimization space, variable boundaries and constraints are defined; according to the acid solution replenishment amount, the recovered acid leaching liquid and the replenished acid leaching liquid are transported in proportional capacity to obtain an acid leaching concentration parameter of the mixed acid leaching liquid; and the acid solution replenishment amount is iteratively updated based on the objective function, the variable boundaries and constraints, and the acid leaching concentration parameter of the mixed acid leaching liquid.

[0058] Specifically, variable boundaries and constraints refer to the ranges and limits set for parameters such as stirring rate, solid-to-liquid ratio, and leaching reaction time within the acid leaching optimization space. These limits are typically based on equipment capabilities and process requirements. Proportional volumetric delivery refers to the mixing of recovered and replenished acid leaching solutions in a set ratio to control the total volume and concentration of the mixed acid leaching solution. The objective function is used to quantitatively evaluate the acid leaching effect under different combinations of acid leaching parameters, using a comprehensive indicator of rare earth leaching rate and acid consumption ratio as the objective function. Iterative updating refers to the gradual adjustment of the acid replenishment amount based on each calculation result to approach the optimal combination of acid leaching parameters.

[0059] In a feasible embodiment, during the acid leaching treatment stage, based on the acid leaching optimization space, variable boundaries and constraints are defined, including the stirring rate range (0 to 800 r / min), the optional solid-liquid ratio values (1:5, 1:10, 1:15), and the acid leaching reaction time range (30 to 150 minutes). The constraints also include the acid solution temperature (maintained at 25°C ± 2°C) and the pressure in the acid leaching tank must be maintained at normal pressure.

[0060] According to the acid replenishment volume, the recovered acid leaching liquid and the replenished acid leaching liquid are transported in proportional capacity. For example, the initial acid replenishment volume is set to 90L, the recovered acid leaching liquid volume is 50L, and the replenished acid leaching liquid volume is 200L. They are mixed in a ratio of 1:2 (the recovered acid leaching liquid volume is 30L and the replenished acid leaching liquid volume is 60L) to obtain the acid leaching concentration parameter of the mixed acid leaching liquid; through the objective function, that is, the comprehensive indicator of rare earth leaching rate and acid consumption ratio, under the variable boundary and constraint conditions, combined with the acid leaching concentration parameter of the mixed acid leaching liquid, the acid replenishment volume is iteratively updated, and the acid replenishment volume is continued to be iteratively adjusted until the optimal acid leaching effect is achieved, ensuring the efficient recovery of rare earth elements while significantly reducing the use of acid, improving the environmental friendliness of the acid leaching process, and providing strong support for the efficient operation of the overall recovery process.

[0061] In summary, the beneficial effects of the embodiments of the present application are:

[0062] Because the physical property indicators including rare earth element content, oxide layer thickness and magnetic phase distribution parameters are determined according to the target NdFeB scrap; the pyrolysis temperature gradient is introduced, and the rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction processes under different temperature gradients are simulated through finite element analysis in combination with the physical property indicators, and the recovery process parameter sets corresponding to different pyrolysis temperature ranges are configured; the acid leaching concentration parameters are uploaded, and the rare earth element dissolution efficiency, impurity dissolution amount and reaction rate are analyzed multivariately in combination with the physical property indicators at different acid leaching concentrations to configure the acid leaching parameter combination that meets the preset recovery rate target value, and the preset recovery rate target value is associated with the scrap recycling task; the recovery process parameter sets corresponding to different pyrolysis temperature ranges and the acid leaching parameter combinations are coupled and analyzed, a collaborative optimization matrix is set, and the recovery parameters are iterated according to the scrap recycling task, and the actual recovery rate of rare earth elements, impurity residue, reaction energy consumption and equipment operating status parameters are simultaneously collected to establish a recovery parameter feedback adjustment mechanism. This application provides a NdFeB waste recycling parameter optimization method and system for recovery rate prediction, realizes the analysis of the recovery process under different temperature gradients, combines the physical property indicators of the waste, accurately configures the recovery process parameter set corresponding to different pyrolysis temperature ranges, fully considers the coupling relationship between acid leaching and pyrolysis, ensures that the dissolution efficiency of rare earth elements, impurity dissolution amount and reaction rate under different acid leaching concentrations reach the best balance, and improves the technical effect of recovery efficiency.

[0063] Example 2, based on the same inventive concept as the method for optimizing the recycling parameters of NdFeB waste for recovery rate prediction in the previous example, Figure 2 As shown, the embodiment of the present application provides a NdFeB waste recycling parameter optimization system for recovery rate prediction, wherein the system includes:

[0064] The index determination module M100 is used to determine the physical property indexes including rare earth element content, oxide layer thickness and magnetic phase distribution parameters according to the target NdFeB scrap.

[0065] The first configuration module M200 is used to introduce a pyrolysis temperature gradient, simulate the rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction processes under different temperature gradients through finite element analysis in combination with the physical property indicators, and configure a set of recovery process parameters corresponding to different pyrolysis temperature ranges.

[0066] The second configuration module M300 is used to upload the acid leaching concentration parameters, and configure the acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of the rare earth element dissolution efficiency, impurity dissolution amount, and reaction rate at different acid leaching concentrations in combination with the physical property indicators. The preset recovery rate target value is associated with the waste recovery task.

[0067] The coupling analysis module M400 is used to perform coupling analysis on the recovery process parameter sets and acid leaching parameter combinations corresponding to the different pyrolysis temperature ranges, set a collaborative optimization matrix, and iterate the recovery parameters according to the waste recovery task, while simultaneously collecting the actual recovery rate of rare earth elements, residual impurities, reaction energy consumption, and equipment operating status parameters, and establishing a recovery parameter feedback adjustment mechanism.

[0068] Furthermore, the coupling analysis module M400 is used to perform the following method:

[0069] According to the preset recovery rate target value, the recovery rate prediction feedback optimization is carried out in combination with the actual recovery rate of the rare earth elements, the residual impurities, the reaction energy consumption, and the equipment operating status parameters; at the same time, a recovery parameter feedback adjustment mechanism is established in combination with the recovery reaction conditions.

[0070] Furthermore, the coupling analysis module M400 is further configured to execute the following method:

[0071] An infrared temperature measurement array is deployed to generate a three-dimensional temperature field distribution cloud map, which is used to restore the energy absorption and transfer characteristics of different positions during the pyrolysis process. Based on the dielectric constant of the waste material, the pyrolysis is partitioned in combination with the three-dimensional temperature field distribution cloud map, and a gradient temperature control interval is set, wherein the gradient temperature control interval includes an oxide layer decomposition temperature control zone and a magnetic phase reconstruction temperature control zone.

[0072] Furthermore, the coupling analysis module M400 is further configured to execute the following method:

[0073] During the waste pretreatment stage, a microwave resonant cavity array is introduced to generate a three-dimensional electromagnetic field hotspot distribution map based on the dielectric constant of the waste. An alternating magnetic field is applied using a Helmholtz coil assembly, and after generating an eddy current thermal effect, the infrared temperature measurement array is activated. At the same time, based on the three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map, the local hotspot area is located, and the gradient temperature control range is dynamically fine-tuned.

[0074] Furthermore, the coupling analysis module M400 is further configured to execute the following method:

[0075] The three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map are spatially aligned to identify local overheating areas and low-temperature blind areas under the electromagnetic-thermal field coupling effect; a temperature gradient compensation matrix is established based on the local overheating areas and low-temperature blind areas under the electromagnetic-thermal field coupling effect; energy consumption constraints are introduced, and based on the temperature gradient compensation matrix, a collaborative optimization mapping instruction set of the gradient temperature control range and the acid leaching concentration parameter is configured.

[0076] Furthermore, the coupling analysis module M400 is further configured to execute the following method:

[0077] The matching degree between the decomposition rate of the oxide layer and the reconstruction rate of the magnetic phase in the local hot spot area is obtained, and a judgment is made in combination with the preset rate deviation to set the matching compensation rule; wherein, the technical parameter indicators associated with the matching compensation rule include microwave power density, Helmholtz coil current phase angle, and pyrolysis residence time.

[0078] Furthermore, the second configuration module M300 is further configured to execute the following method:

[0079] During the acid leaching treatment stage, an acid leaching optimization space is set with the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable in combination with the acid leaching reaction time. In the acid leaching optimization space, a global search is performed with the rare earth leaching rate and the acid consumption ratio as objective functions to determine an acid leaching optimization parameter sequence synchronized with the acid leaching reaction time. The acid leaching optimization parameter sequence is mapped one-to-one with the acid leaching parameter combination.

[0080] Furthermore, the second configuration module M300 is further configured to execute the following method:

[0081] Based on the acid leaching optimization space, variable boundaries and constraints are defined; according to the acid solution replenishment amount, the recovered acid leaching liquid and the replenished acid leaching liquid are transported in proportional capacity to obtain an acid leaching concentration parameter of the mixed acid leaching liquid; and the acid solution replenishment amount is iteratively updated based on the objective function, the variable boundaries and constraints, and the acid leaching concentration parameter of the mixed acid leaching liquid.

[0082] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory and can be called and recognized by an unlimited computer processor, without any unnecessary restrictions.

[0083] Furthermore, the above technical solution only reflects the preferred technical solution of the technical solution of the embodiment of the present application. Some changes that may be made to certain parts thereof by technical personnel in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technical personnel in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A method for optimizing NdFeB waste recycling parameters based on recovery rate prediction, characterized in that: The method comprises: Determine the physical property indicators including rare earth element content, oxide layer thickness and magnetic phase distribution parameters based on the target NdFeB scrap; Introducing a pyrolysis temperature gradient, combining the physical property indicators with finite element analysis to simulate the rare earth element diffusion, oxide layer decomposition, and magnetic phase reconstruction processes under different temperature gradients, and configuring a set of recovery process parameters corresponding to different pyrolysis temperature ranges based on the simulation results; Upload the acid leaching concentration parameters, and configure an acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of rare earth element dissolution efficiency, impurity dissolution amount, and reaction rate at different acid leaching concentrations in combination with the physical property indicators. The preset recovery rate target value is associated with the waste recovery task; A coupling analysis is performed on the recovery process parameter sets and acid leaching parameter combinations corresponding to the different pyrolysis temperature ranges, a collaborative optimization matrix is set, and the recovery parameters are iterated according to the waste recovery task. The actual recovery rate of rare earth elements, impurity residue, reaction energy consumption, and equipment operating status parameters are simultaneously collected, and a recovery parameter feedback adjustment mechanism is established. The coupling analysis refers to the joint analysis of the recovery process parameter sets and acid leaching parameter combinations corresponding to the pyrolysis temperature range to study the interaction and influence between the two; the collaborative optimization matrix is used to comprehensively consider various parameters in the pyrolysis and acid leaching processes based on the coupling analysis results, and find the optimal parameter combination through matrix operations; recovery parameter iteration refers to the process of repeatedly adjusting and optimizing the recovery process parameters and acid leaching parameters corresponding to the pyrolysis temperature range according to the results of each recovery process; the recovery parameter feedback adjustment mechanism is used to collect and analyze data from the recovery process in real time, and then dynamically adjust the recovery parameters based on these data.

2. The NdFeB waste recycling parameter optimization method for recovery rate prediction according to claim 1, characterized in that: Simultaneously collect the actual recovery rate of rare earth elements, residual impurities, reaction energy consumption, and equipment operating status parameters, and establish a recovery parameter feedback adjustment mechanism, including: Based on the preset recovery rate target value, the recovery rate prediction feedback optimization is performed in combination with the actual recovery rate of the rare earth element, the residual impurity amount, the reaction energy consumption, and the equipment operating status parameters; At the same time, a feedback adjustment mechanism for recycling parameters is established in combination with the recycling reaction conditions.

3. The NdFeB waste recycling parameter optimization method for recovery rate prediction as claimed in claim 2, characterized in that: Combined recovery reaction conditions include: Deploy an infrared temperature measurement array to generate a three-dimensional temperature field distribution cloud map, which is used to restore the energy absorption and transfer characteristics of different positions during the pyrolysis process; Based on the dielectric constant of the waste material and in combination with the three-dimensional temperature field distribution cloud map, pyrolysis zoning is performed to set a gradient temperature control range, wherein the gradient temperature control range includes an oxide layer decomposition temperature control zone and a magnetic phase reconstruction temperature control zone.

4. The NdFeB waste recycling parameter optimization method for recovery rate prediction as claimed in claim 3, characterized in that: Based on the dielectric constant of the waste material and in combination with the three-dimensional temperature field distribution cloud map, pyrolysis partitioning is performed and a gradient temperature control range is set, including: During the waste pretreatment stage, a microwave resonant cavity array is introduced to generate a three-dimensional electromagnetic field hotspot distribution map based on the waste dielectric constant; Applying an alternating magnetic field using a Helmholtz coil assembly to generate an eddy current thermal effect and then starting the infrared temperature measurement array; At the same time, based on the three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map, the local hotspot area is located, and the gradient temperature control range is dynamically fine-tuned.

5. The NdFeB waste recycling parameter optimization method for recovery rate prediction as claimed in claim 4, characterized in that: The method further comprises: Performing spatial registration on the three-dimensional electromagnetic field hotspot distribution map and the three-dimensional temperature field distribution cloud map to identify local overheating areas and low-temperature blind areas under the electromagnetic-thermal field coupling effect; Based on the local overheating area and low-temperature blind area under the electromagnetic-thermal field coupling effect, a temperature gradient compensation matrix is established; Energy consumption constraints are introduced, and based on the temperature gradient compensation matrix, a collaborative optimization mapping instruction set of the gradient temperature control interval and the acid leaching concentration parameter is configured.

6. The NdFeB waste recycling parameter optimization method for recovery rate prediction according to claim 5, characterized in that: The method comprises: Obtain the matching degree between the oxide layer decomposition rate and the magnetic phase reconstruction rate in the local hotspot area, make a judgment based on the preset rate deviation, and set the matching compensation rule; The technical parameter indicators associated with the matching compensation rule include microwave power density, Helmholtz coil current phase angle, and pyrolysis residence time.

7. The NdFeB waste recycling parameter optimization method for recovery rate prediction according to claim 1, characterized in that: The preset recycling rate target value is associated with the waste recycling task, including: In the acid leaching stage, the acid leaching optimization space is set by taking the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable in combination with the acid leaching reaction time; In the acid leaching optimization space, a global search is performed with rare earth leaching rate and acid consumption ratio as objective functions to determine an acid leaching optimization parameter sequence synchronized with the acid leaching reaction time. The acid leaching optimization parameter sequence is mapped one-to-one with the acid leaching parameter combination.

8. The NdFeB waste recycling parameter optimization method for recovery rate prediction according to claim 7, characterized in that: A global search is performed with the rare earth leaching rate and the acid consumption ratio as the objective function to determine an acid leaching optimization parameter sequence synchronized with the acid leaching reaction time, including: Based on the acid leaching optimization space, defining variable boundaries and constraints; According to the amount of acid solution replenished, the recovered acid leaching solution and the replenished acid leaching solution are transported in proportional capacity to obtain the acid leaching concentration parameters of the mixed acid leaching solution; The acid solution replenishment amount is iteratively updated through the objective function, under the variable boundaries and constraints, and in combination with the acid leaching concentration parameter of the mixed acid leaching solution.

9. The NdFeB waste recycling parameter optimization system based on recovery rate prediction is characterized by: A method for optimizing NdFeB waste recycling parameters for implementing the recovery rate prediction according to any one of claims 1 to 8, the system comprising: An index determination module is used to determine physical property indicators including rare earth element content, oxide layer thickness and magnetic phase distribution parameters based on target NdFeB scrap; The first configuration module is used to introduce a pyrolysis temperature gradient, simulate the rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction process under different temperature gradients through finite element analysis in combination with the physical property indicators, and configure the recovery process parameter sets corresponding to different pyrolysis temperature ranges based on the simulation results; The second configuration module is used to upload the acid leaching concentration parameters, and configure an acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of rare earth element dissolution efficiency, impurity dissolution amount, and reaction rate at different acid leaching concentrations in combination with the physical property indicators. The preset recovery rate target value is associated with the waste recovery task; The coupling analysis module is used to perform coupling analysis on the recovery process parameter set and the acid leaching parameter combination corresponding to the different pyrolysis temperature ranges, set up a collaborative optimization matrix, and iterate the recovery parameters according to the waste recycling task, synchronously collect the actual recovery rate of rare earth elements, impurity residue, reaction energy consumption, and equipment operating status parameters, and establish a recovery parameter feedback adjustment mechanism. The coupling analysis refers to the joint analysis of the recovery process parameter set and the acid leaching parameter combination corresponding to the pyrolysis temperature range to study the interaction and influence between the two; the collaborative optimization matrix is used to comprehensively consider the various parameters in the pyrolysis and acid leaching processes based on the coupling analysis results, and find the optimal parameter combination through matrix operations; the recovery parameter iteration refers to the process of repeatedly adjusting and optimizing the recovery process parameters and acid leaching parameters corresponding to the pyrolysis temperature range according to the results of each recovery process; the recovery parameter feedback adjustment mechanism is used to collect and analyze data in the recovery process in real time, and then dynamically adjust the recovery parameters based on these data.

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