Neodymium-iron-boron waste recovery parameter optimization method and system for recovery rate prediction

Abstract

The invention relates to the related technical field of neodymium-iron-boron recovery, in particular to a neodymium-iron-boron waste recovery parameter optimization method and system capable of predicting the recovery rate, and the method comprises the steps: determining a physical characteristic index, simulating and configuring a pyrolysis parameter set in combination with a pyrolysis temperature gradient, uploading an acid leaching concentration parameter, configuring an acid leaching parameter combination, and carrying out coupling analysis and iteration. And collecting parameters to establish a recovery parameter feedback adjustment mechanism. The technical problems that fixed pyrolysis parameters are difficult to adapt to different waste characteristics, the characteristic change of the pyrolyzed waste directly affects the acid leaching efficiency, a compact inert layer is generated on the surface of part of the pyrolyzed waste, and the dissolution bottleneck is caused are solved, the recovery process under different temperature gradients is analyzed, and the recovery efficiency is improved. The method has the advantages that recycling process parameter sets corresponding to different pyrolysis temperature intervals are accurately configured, the coupling relation between acid leaching and pyrolysis is fully considered, it is guaranteed that the dissolution efficiency, the impurity dissolution amount and the reaction rate of rare earth elements under different acid leaching concentrations reach the optimal balance, and the recycling efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field related to neodymium iron boron recovery, and particularly to an optimization method and system for neodymium iron boron waste recovery parameters for recovery rate prediction. Background Art

[0002] As an important carrier for the application of rare earth elements, neodymium iron boron permanent magnet materials 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 neodymium iron boron permanent magnet materials, a large amount of neodymium iron boron waste will inevitably be generated. These wastes contain rich rare earth elements. If they cannot be effectively recycled, it will not only cause great waste of rare earth resources, but also cause serious pollution to the environment.

[0003] However, due to the differences in the physical properties of neodymium iron boron waste, such as the content of rare earth elements, the thickness of the oxide layer, and the magnetic phase distribution parameters, etc., it is difficult to precisely control the diffusion of rare earth elements, the decomposition of the oxide layer, and the reconstruction process of the magnetic phase during the pyrolysis process, thereby affecting the recovery effect.

[0004] In summary, in the prior art, there are technical problems that fixed pyrolysis parameters are difficult to adapt to the characteristics of different wastes, and the changes in the characteristics of the wastes after pyrolysis directly affect the acid leaching efficiency, resulting in the formation of a dense inert layer on the surface of some wastes after pyrolysis, thus falling into a dissolution bottleneck. Summary of the Invention

[0005] The present application provides an optimization system for neodymium iron boron waste recovery parameters for recovery rate prediction, aiming to solve the technical problems in the prior art that fixed pyrolysis parameters are difficult to adapt to the characteristics of different wastes, and the changes in the characteristics of the wastes after pyrolysis directly affect the acid leaching efficiency, resulting in the formation of a dense inert layer on the surface of some wastes after pyrolysis, thus falling into a dissolution bottleneck.

[0006] In view of the above problems, the technical solution of the present application is as follows: On the one hand, the present application provides an optimization method for neodymium iron boron waste recovery parameters for recovery rate prediction, wherein the method includes: According to the target NdFeB waste, determine the physical property indexes including rare earth element content, oxide layer thickness and magnetic phase distribution parameters; introduce a pyrolysis temperature gradient, and combine the physical property indexes to simulate the processes of rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction under different temperature gradients through finite element analysis, and configure a set of recovery process parameters corresponding to different pyrolysis temperature ranges; upload the acid leaching concentration parameters, and combine the physical property indexes to configure an acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of the dissolution efficiency of rare earth elements, impurity dissolution amount and reaction rate under different acid leaching concentrations, where the preset recovery rate target value is associated with the waste recycling task; perform a coupling analysis on the set of recovery process parameters corresponding to different pyrolysis temperature ranges and the acid leaching parameter combination, set a collaborative optimization matrix, and perform recovery parameter iteration according to the waste recycling task, and simultaneously collect the actual recovery rate of rare earth elements, impurity residue amount, reaction energy consumption, and equipment operation status parameters, and establish a feedback adjustment mechanism for recovery parameters.

[0007] On the other hand, the present application provides a system for optimizing the recovery parameters of NdFeB waste for predicting the recovery rate, wherein the system includes: An index determination module for determining physical property indexes including rare earth element content, oxide layer thickness and magnetic phase distribution parameters according to the target NdFeB waste; a first configuration module for introducing a pyrolysis temperature gradient, and combining the physical property indexes to simulate the processes of rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction under different temperature gradients through finite element analysis, and configuring a set of recovery process parameters corresponding to different pyrolysis temperature ranges; a second configuration module for uploading the acid leaching concentration parameters, and combining the physical property indexes to configure an acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of the dissolution efficiency of rare earth elements, impurity dissolution amount and reaction rate under different acid leaching concentrations, where the preset recovery rate target value is associated with the waste recycling task; a coupling analysis module for performing a coupling analysis on the set of recovery process parameters corresponding to different pyrolysis temperature ranges and the acid leaching parameter combination, setting a collaborative optimization matrix, and performing recovery parameter iteration according to the waste recycling task, and simultaneously collecting the actual recovery rate of rare earth elements, impurity residue amount, reaction energy consumption, and equipment operation status parameters, and establishing a feedback adjustment mechanism for recovery parameters.

[0008] In summary, one or more technical solutions provided in the present application achieve the technical effect of analyzing the recovery process under different temperature gradients, combining the physical property indexes of the waste, accurately configuring a set of recovery process parameters corresponding to different pyrolysis temperature ranges, fully considering the coupling relationship between acid leaching and pyrolysis, ensuring the best balance of the dissolution efficiency of rare earth elements, impurity dissolution amount and reaction rate under different acid leaching concentrations, and improving the recovery efficiency. Description of the Drawings

[0009] Figure 1This application provides a flow schematic diagram of a method for optimizing the recovery parameters of Nd-Fe-B waste for recovery rate prediction; Figure 2 This application provides a structural schematic diagram of a system for optimizing the recovery parameters of Nd-Fe-B waste for recovery rate prediction.

[0010] Explanation of reference numerals: Index determination module M100, first configuration module M200, second configuration module M300, coupling analysis module M400. Detailed implementation manners

[0011] Example 1. The present application will be specifically described below with reference to the accompanying drawings. As Figure 1 shown, the present application provides a method for optimizing the recovery parameters of Nd-Fe-B waste for recovery rate prediction. Among them, the method includes: S1: According to the target Nd-Fe-B waste, determine the physical property indexes including rare earth element content, oxide layer thickness, and magnetic phase distribution parameters.

[0012] Specifically, identify the key physical property indexes of the target Nd-Fe-B waste. Further, the rare earth element content determines the potential of recoverable rare earths in the waste, the oxide layer thickness affects the diffusion difficulty of rare earth elements during pyrolysis, and the magnetic phase distribution parameters are related to the existence form and distribution range of magnetic phases in the waste. These factors together determine the reaction characteristics of the waste during subsequent pyrolysis and acid leaching processes.

[0013] In a feasible implementation manner, the detection of rare earth element content can be achieved through techniques such as spectral analysis, the oxide layer thickness can be measured by means of scanning electron microscopy combined with energy spectrum analysis, and the magnetic phase distribution parameters can be characterized by means of X-ray diffraction, etc. For example, in the detection of a specific batch of Nd-Fe-B 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 process parameters for subsequent pyrolysis and acid leaching, specific values need to be based on these to accurately determine the processing conditions suitable for this batch of waste to ensure the efficiency of the recovery process.

[0014] S2: Introduce a pyrolysis temperature gradient, and combine the physical property indexes to simulate the processes of rare earth element diffusion, oxide layer decomposition, and magnetic phase reconstruction at different temperature gradients through finite element analysis, and configure the set of recovery process parameters corresponding to different pyrolysis temperature intervals.

[0015] Specifically, introducing a pyrolysis temperature gradient means setting a series of different temperature ranges during the pyrolysis process to simulate the processes of rare earth element diffusion, oxide layer decomposition, and magnetic phase reconstruction. Using the finite element analysis method, a mathematical model is established based on pre-determined physical property indicators (rare earth element content, oxide layer thickness, and magnetic phase distribution parameters), and the physical and chemical changes inside the waste at different temperatures are simulated by computer; a set of recovery process parameters corresponding to different pyrolysis temperature ranges is configured, that is, according to the simulation results, process parameter combinations such as pyrolysis time, heating rate, heat preservation duration, and gas flow rate are set for each temperature range to meet the pyrolysis requirements of waste with different physical properties.

[0016] In a feasible implementation, it is simulated by finite element analysis that in the first temperature range (100°C - 300°C), the diffusion rate of rare earth elements is slow, the decomposition of the oxide layer has not started, and the magnetic phase remains stable; in the second temperature range (300°C - 500°C), the oxide layer begins to decompose, the diffusion rate of rare earth elements accelerates, but the magnetic phase has not undergone obvious reconstruction; in the third temperature range (500°C - 800°C), the rare earth elements are fully diffused, the oxide layer is completely decomposed, and the magnetic phase is reconstructed. According to the simulation results, a set of recovery process parameters is configured for each temperature range respectively, and by precisely controlling the temperature gradient and the corresponding process parameters, the rare earth elements are fully diffused, the oxide layer is completely decomposed, and the magnetic phase is reasonably reconstructed.

[0017] Preferably, the pyrolysis method using the temperature gradient and the corresponding parameter set effectively solves the problem of poor pyrolysis effect caused by the 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.

[0018] 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 dissolution efficiency of rare earth elements, the dissolution amount of impurities, and the reaction rate at different acid leaching concentrations in combination with the physical property indicators, where the preset recovery rate target value is associated with the waste recovery task.

[0019] Specifically, uploading the acid leaching concentration parameters means inputting a series of acid solution parameters with different concentrations, which will be used for subsequent multivariate analysis; multivariate analysis means comprehensively considering multiple factors such as the dissolution efficiency of rare earth elements, the dissolution amount of impurities, and the reaction rate, and analyzing the change trends and mutual relationships of these factors at different acid leaching concentrations by establishing a mathematical model and using statistical methods to determine the optimal acid leaching conditions.

[0020] In a feasible implementation, a series of hydrochloric acid leaching parameters at different concentrations (such as 1 mol / L, 2 mol / L, 3 mol / L, 4 mol / L, 5 mol / L) are uploaded; through multivariate analysis, the balance relationship among the dissolution efficiency of rare earth elements, the amount of impurity dissolution, and the reaction rate under different leaching concentrations is fully considered, the physical property indexes of the waste materials are accurately matched, the pertinence and effectiveness of the acid leaching process are effectively improved, the overall recovery process is ensured to reach the predetermined recovery rate target, and the economy and environmental protection of rare earth element recovery are enhanced.

[0021] S4: Perform coupling analysis on the set of recovery process parameters corresponding to the different pyrolysis temperature ranges and the acid leaching parameter combinations, set a collaborative optimization matrix, and perform iterative recovery parameter according to the waste material recovery task, synchronously collect the actual recovery rate of rare earth elements, the amount of impurity residue, the reaction energy consumption, and the equipment operation status parameters, and establish a feedback adjustment mechanism for recovery parameters.

[0022] 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 combinations 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; iterative recovery parameters refer to the process of repeatedly adjusting and optimizing the pyrolysis and acid leaching parameters according to the results of each recovery process; the feedback adjustment mechanism for recovery parameters is used to collect and analyze the data in the recovery process in real time, and then dynamically adjust the recovery parameters according to these data to ensure the high efficiency and stability of the recovery process.

[0023] In a feasible implementation, there is a set of recovery process parameters corresponding to a group of pyrolysis temperature ranges (such as 300 °C, 400 °C, 500 °C), and a set of acid leaching parameter combinations corresponding to a group of acid leaching concentrations (such as 1 mol / L, 2 mol / L, 3 mol / L); through coupling analysis, it is found that when the pyrolysis temperature is 400 °C, the oxide layer of the waste material decomposes more fully. 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. According to 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.

[0024] During the execution of the waste material recovery task, the first iterative recovery parameter is carried out, data is synchronously collected, and adjustments are made in the next iteration through the feedback adjustment mechanism of the recovery parameters. Through this coupling analysis and parameter iteration method, combined with real-time data feedback adjustment, the optimal recovery parameter combination is determined, the efficient completion of the waste material recovery task is achieved, the recovery rate of rare earth elements is ensured to be stable above the target value, the impurity residue and reaction energy consumption are reduced at the same time, and the reliability of equipment operation is improved.

[0025] Furthermore, synchronously collect the actual recovery rate of rare earth elements, the residual amount of impurities, the reaction energy consumption, and the equipment operation state parameters, and establish a feedback adjustment mechanism for recovery parameters. The method of this application includes: According to the preset recovery rate target value, combine the actual recovery rate of rare earth elements, the residual amount of impurities, the reaction energy consumption, and the equipment operation state parameters to optimize the recovery rate prediction feedback; at the same time, combine the recovery reaction conditions to establish a feedback adjustment mechanism for recovery parameters.

[0026] Specifically, the recovery rate prediction feedback refers to dynamically predicting and adjusting the recovery process based on the actually collected recovery rate of rare earth elements, the residual amount of impurities, the reaction energy consumption, and the equipment operation state parameters. Further, a prediction model is established. The prediction model takes parameters such as the actual recovery rate, the residual amount of impurities, and the reaction energy consumption as inputs, and the optimized recovery parameters as outputs; 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.

[0027] In a feasible implementation manner, through continuous feedback and optimization iteration of the feedback adjustment mechanism, the equipment operation state tends to be stable; based on the dynamic adjustment mechanism of real-time data, it can effectively cope with the changes in the physical properties of the waste and the fluctuations in equipment operation, ensure that the recovery process always operates around the preset target, and improve the overall recovery efficiency and product quality.

[0028] Furthermore, combining the recovery reaction conditions, the method of this application includes: 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 at different positions during the pyrolysis process; based on the dielectric constant of the waste, combine the three-dimensional temperature field distribution cloud map to perform pyrolysis zoning and set a gradient temperature control interval, where the gradient temperature control interval includes an oxidation layer decomposition temperature control zone and a magnetic phase reconstruction temperature control zone.

[0029] 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 of each position 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 of different positions 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 property requirements of the waste, and each interval corresponds to a different temperature setting; the oxidation 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 oxidation layer decomposition and magnetic phase reconstruction respectively.

[0030] In a feasible implementation, an infrared temperature measurement array is deployed inside the pyrolysis reactor, and a temperature measurement point is set at a certain interval (such as 10 cm), forming 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 a data processing system.

[0031] Using the three-dimensional temperature field distribution cloud map, if it is determined that the temperature in the central area of the waste is relatively low and the temperature near the reactor wall is relatively high, resulting in uneven decomposition of the oxide layer; by measuring the dielectric constant of the waste and combining the three-dimensional temperature field distribution cloud map, the pyrolysis area is divided into multiple zones; in the gradient temperature control interval, the pyrolysis efficiency is significantly improved, the recovery rate of rare earth elements is increased, providing higher-quality materials for the subsequent acid leaching process, ensuring the efficient progress of the overall recovery process, and at the same time reducing energy consumption.

[0032] Furthermore, based on the dielectric constant of the waste and combined with the three-dimensional temperature field distribution cloud map for pyrolysis zoning and setting a gradient temperature control interval, the method of the present application further includes: In the waste pretreatment stage, a microwave resonance cavity array is introduced. Based on the dielectric constant of the waste, a three-dimensional electromagnetic field hot spot distribution map is generated; a Helmholtz coil group is used to apply an alternating magnetic field. After generating the eddy current heating effect, the infrared temperature measurement array is started; at the same time, based on the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map, the local hot spot area is located, and the temperature setting of the gradient temperature control interval is dynamically fine-tuned.

[0033] Specifically, the microwave resonance cavity array is a device for pretreating waste using microwave energy. Through the coordinated action of multiple resonance cavities, the microwave energy can be evenly distributed in the waste; the three-dimensional electromagnetic field hot spot distribution map is an image generated by an electromagnetic field simulation software based on the dielectric constant of the waste and the working parameters of the microwave resonance cavity array, used to display the distribution of the electromagnetic field intensity inside the waste, where the hot spot area represents the area where the 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, an eddy current heating effect is induced inside the waste to further heat the waste; dynamic fine-tuning refers to making small adjustments to the temperature setting of the gradient temperature control interval according to real-time monitored data (such as the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map) to achieve more accurate temperature control.

[0034] In a feasible implementation, during the waste pretreatment stage, a microwave resonator array is introduced. Based on the dielectric constant of the waste, a three-dimensional electromagnetic field hot spot distribution map is generated. Further, under the action of the microwave resonator array, it is found that there are multiple electromagnetic field hot spot regions inside the waste. Among them, the electromagnetic field intensity in the electromagnetic field hot spot regions is higher than that in the surrounding regions by a certain proportion (30%). At this time, an alternating magnetic field is applied using a Helmholtz coil set to generate an eddy current heating effect inside the waste, causing the temperature in the electromagnetic field hot spot regions to rise. Subsequently, an infrared temperature measurement array is activated to collect temperature data at a fixed frequency and generate a three-dimensional temperature field distribution cloud map.

[0035] By comparing the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map, it is found that the temperature in the hot spot regions has a positive correlation with the electromagnetic field intensity, that is, the higher the electromagnetic field intensity in a region, the greater the increase in temperature. Based on these data, the gradient temperature control interval is dynamically fine-tuned, and the temperature setting in the low-temperature blind area is increased. After the fine-tuning, the temperature distribution inside the waste is more uniform, the oxidation layer decomposition rate and the magnetic phase reconstruction rate are increased, providing a more uniform and higher-quality material for the subsequent pyrolysis and acid leaching processes, effectively improving the recovery efficiency of rare earth elements, and at the same time reducing the energy waste and equipment loss caused by uneven temperature.

[0036] Furthermore, the method of this application further includes: Performing spatial registration on the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map to identify local overheating regions and low-temperature blind areas under the electromagnetic-thermal field coupling effect; establishing a temperature gradient compensation matrix based on the local overheating regions and low-temperature blind areas under the electromagnetic-thermal field coupling effect; introducing an energy consumption constraint condition, and configuring a collaborative optimization mapping instruction set for the gradient temperature control interval and the acid leaching concentration parameter based on the temperature gradient compensation matrix.

[0037] Specifically, spatial registration means accurately aligning the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map in the same coordinate system to accurately compare and analyze the corresponding relationship between the two; the local overheating region refers to the part where the temperature is significantly higher than the surrounding regions under the electromagnetic-thermal field coupling effect and may affect the waste treatment effect; the low-temperature blind area refers to the region where the temperature fails to reach the expected value during the pyrolysis process due to the uneven distribution of the electromagnetic field and the thermal field; the temperature gradient compensation matrix is used to describe the temperature deviation in different regions and provide corresponding compensation solutions; the energy consumption constraint condition refers to the energy consumption limit that must be satisfied during the optimization process to ensure the economy and feasibility of the entire recovery process; the collaborative optimization mapping instruction set is a predefined instruction used to guide the collaborative optimization adjustment between the gradient temperature control interval and the acid leaching concentration parameter to achieve the best recovery effect.

[0038] In a feasible implementation, through the action of a microwave resonator array and a Helmholtz coil group, a three-dimensional electromagnetic field hot spot distribution map and a three-dimensional temperature field distribution cloud map are generated; after spatial registration, local overheating regions and low-temperature blind spots are found inside the waste material, and a temperature gradient compensation matrix is established. The temperature gradient compensation matrix sets compensation values for the local overheating regions and low-temperature blind spots. At the same time, an energy consumption constraint condition is introduced to limit the energy consumption during the pyrolysis-acid leaching process; based on the temperature gradient compensation matrix, a collaborative optimization mapping instruction set for configuring the gradient temperature control interval 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, the amount of impurity dissolution, and the reaction rate reach the best balance at different acid leaching concentrations.

[0039] Furthermore, the method of the present application includes: Obtain the matching degree between the oxidation layer decomposition rate and the magnetic phase reconstruction rate in the local hot spot region, and make a judgment in combination with a preset rate deviation, and set a 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.

[0040] Specifically, obtaining the matching degree between the oxidation layer decomposition rate and the magnetic phase reconstruction rate in the local hot spot region means determining the coordination between these two rates by monitoring and analyzing the oxidation layer decomposition rate and the magnetic phase reconstruction rate in the local hot spot region; making a judgment in combination with a preset rate deviation is to compare the actually measured rate with the pre-set standard rate to determine whether adjustment is needed. Setting the matching compensation rule is to formulate corresponding rules according to the judgment result to adjust relevant parameters to achieve the matching of the oxidation 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 correspondingly affect the heating intensity, magnetic field distribution, and pyrolysis reaction time of the waste material.

[0041] In a feasible implementation, in the local hot spot area, the measured decomposition rate of the oxide layer is 0.05 μm / min, the magnetic phase reconstruction rate is 0.04 μm / min, and the preset allowable range of rate deviation is ±0.01 μm / min. The calculated matching degree M between the two is: M = |0.05 - 0.04| = 0.01 μm / min. Since 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, the current phase angle of the Helmholtz coil, and the pyrolysis residence time are adjusted. Among them, the adjustment of the microwave power density is used to reduce the microwave power density to slow down the decomposition rate of the oxide layer; the adjustment of the current phase angle of the Helmholtz coil aims to optimize the current phase angle to improve the magnetic field distribution and promote the magnetic phase reconstruction; the adjustment of the pyrolysis residence time aims to extend the pyrolysis time to balance the rates of the two. After adjustment, the decomposition rate of the oxide layer and the magnetic phase reconstruction rate are measured again, and the matching degree M is calculated again. Through precise rate matching and parameter adjustment, the coordinated progress of the oxide layer decomposition and the magnetic phase reconstruction during the pyrolysis process is ensured, and the overall recovery efficiency and product quality are improved.

[0042] Furthermore, the preset recovery rate target value is associated with the waste material recovery task, and the method of the present application further includes: In the acid leaching treatment stage, with the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable, combined with the acid leaching reaction time, an acid leaching optimization space is set. In the acid leaching optimization space, 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, and the acid leaching optimization parameter sequence is mapped one-to-one with the acid leaching parameter combination.

[0043] Specifically, the acid leaching optimization space refers to the multi-dimensional combination range jointly composed of parameters such as the stirring rate (continuous variable), the solid-liquid ratio (discrete variable), and the acid leaching reaction time during the acid leaching treatment process. Within this acid leaching optimization space, different parameter combinations correspond to different acid leaching effects. The rare earth leaching rate is a measure of the efficiency of rare earth elements being leached from the waste material into the solution, usually expressed as a percentage. The acid consumption ratio reflects the amount of acid solution consumed per unit mass or volume of the waste material 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 solution. The global search is to comprehensively scan and analyze within the acid leaching optimization space to find the parameter combination that makes the objective function (the comprehensive index of the rare earth leaching rate and the acid consumption ratio) reach the optimal value.

[0044] In a feasible implementation, during the acid leaching treatment stage, with the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable, combined with the acid leaching reaction time, an acid leaching optimization space is set. For example, when treating a certain batch of neodymium-iron-boron waste, 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, 1:15, etc., and the acid leaching reaction time can be set between 30 and 180 minutes. In the acid leaching optimization space, a global search is carried out with 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 is found that when the stirring rate is 600 r / min, the leaching rate of rare earth elements reaches 85% and the acid consumption ratio is 0.8 L / kg; when the solid-liquid ratio is 1:10, the leaching rate is 80% and the acid consumption ratio is 0.7 L / kg; when the acid leaching reaction time is 120 minutes, the leaching rate is 82% and the acid consumption ratio is 0.75 L / kg. The finally determined acid leaching optimization parameter sequence is: stirring rate 600 r / min, solid-liquid ratio 1:10, acid leaching reaction time 120 minutes, and these parameters form a one-to-one associated mapping with the acid leaching parameter combination. This optimization process significantly improves the recovery rate of rare earth elements, reduces the consumption of acid solution at the same time, and improves the economy and environmental protection of the acid leaching process.

[0045] Furthermore, when carrying out a global search with 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, the method of the present application further includes: Based on the acid leaching optimization space, variable boundaries and constraint conditions are defined; according to the acid solution supplement amount, proportional volume transportation of the recycled acid leaching solution and the supplementary acid leaching solution is carried out to obtain the acid leaching concentration parameter of the mixed acid leaching solution; through the objective function, under the variable boundaries and constraint conditions, combined with the acid leaching concentration parameter of the mixed acid leaching solution, the acid solution supplement amount is iteratively updated.

[0046] Specifically, the variable boundaries and constraint conditions refer to the value ranges and limiting conditions set for parameters such as the stirring rate, solid-liquid ratio, and acid leaching reaction time within the acid leaching optimization space, and these limitations are usually based on equipment capabilities and process requirements; proportional volume transportation means mixing the recycled acid leaching solution and the supplementary acid leaching solution according to 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 acid leaching parameter combinations, and the comprehensive index of the rare earth leaching rate and acid consumption ratio is used as the objective function; iterative update means gradually adjusting the acid solution supplement amount according to the calculation results of each time to approach the optimal acid leaching parameter combination.

[0047] In a feasible implementation manner, in the acid leaching treatment stage, based on the acid leaching optimization space, variable boundaries and constraint conditions are defined, including the stirring rate range (0 to 800 r / min), optional values of the solid-liquid ratio (1:5, 1:10, 1:15), the acid leaching reaction time range (30 to 150 minutes). At the same time, the constraint conditions also include the acid solution temperature (maintained at 25°C ± 2°C), and the pressure in the acid leaching tank needs to be kept at atmospheric pressure.

[0048] According to the acid solution supplement amount, proportional capacity transportation is carried out for the recycled acid leaching solution and the supplementary acid leaching solution. For example, the initial acid solution supplement amount is set to 90 L, the recycled acid leaching solution amount is 50 L, and the supplementary acid leaching solution amount is 200 L. They are mixed in a ratio of 1:2 (the recycled acid leaching solution amount is 30 L and the supplementary acid leaching solution amount is 60 L) to obtain the acid leaching concentration parameter of the mixed acid leaching solution. Through the objective function, that is, the comprehensive index of the rare earth leaching rate and the acid consumption ratio, under the variable boundaries and constraint conditions, combined with the acid leaching concentration parameter of the mixed acid leaching solution, the acid solution supplement amount is iteratively updated, and the acid solution supplement amount is continuously iteratively adjusted until the optimal acid leaching effect is achieved. This ensures the efficient recovery of rare earth elements while significantly reducing the usage amount of the acid solution, improving the environmental friendliness of the acid leaching process, and providing strong support for the efficient operation of the overall recovery process.

[0049] In summary, the beneficial effects of the embodiments of the present application are: By determining the physical property indexes including rare earth element content, oxide layer thickness and magnetic phase distribution parameters according to the target NdFeB waste; introducing a pyrolysis temperature gradient, and through finite element analysis in combination with the physical property indexes to simulate the processes of rare earth element diffusion, oxide layer decomposition and magnetic phase reconstruction under different temperature gradients, configuring a set of recovery process parameters corresponding to different pyrolysis temperature intervals; uploading the acid leaching concentration parameters, and 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 indexes, configuring an acid leaching parameter combination that meets the preset recovery rate target value, and the preset recovery rate target value is associated with the waste recycling task; performing a coupling analysis on the set of recovery process parameters corresponding to different pyrolysis temperature intervals and the acid leaching parameter combination, setting a collaborative optimization matrix, and performing recovery parameter iteration according to the waste recycling task, synchronously collecting the actual recovery rate of rare earth elements, impurity residue amount, reaction energy consumption, equipment operation status parameters, and establishing a recovery parameter feedback adjustment mechanism. By providing an NdFeB waste recycling parameter optimization method and system for predicting the recovery rate, the present application realizes the analysis of the recycling process under different temperature gradients, combines the physical property indexes of the waste, accurately configures a set of recovery process parameters corresponding to different pyrolysis temperature intervals, fully considers the coupling relationship between acid leaching and pyrolysis, and ensures that the dissolution efficiency of rare earth elements, impurity dissolution amount and reaction rate reach the best balance at different acid leaching concentrations, achieving the technical effect of improving the recovery efficiency.

[0050] Embodiment 2. Based on the same inventive concept as the neodymium-iron-boron waste recycling parameter optimization method for recovery rate prediction in the foregoing embodiment, as Figure 2 shown, the embodiment of the present application provides a system for optimizing the recycling parameters of neodymium-iron-boron waste for recovery rate prediction. Among them, the system includes: An index determination module M100, configured to determine physical property indexes including rare earth element content, oxide layer thickness, and magnetic phase distribution parameters according to the target neodymium-iron-boron waste.

[0051] A first configuration module M200, configured to introduce a pyrolysis temperature gradient, and configure a set of recovery process parameters corresponding to different pyrolysis temperature ranges by simulating the diffusion of rare earth elements, decomposition of the oxide layer, and magnetic phase reconstruction processes at different temperature gradients through finite element analysis in combination with the physical property indexes.

[0052] A second configuration module M300, configured to upload acid leaching concentration parameters, and configure an acid leaching parameter combination that meets a preset recovery rate target value by performing multivariate analysis of the dissolution efficiency of rare earth elements, impurity dissolution amount, and reaction rate at different acid leaching concentrations in combination with the physical property indexes. The preset recovery rate target value is associated with the waste recycling task.

[0053] A coupling analysis module M400, configured to perform coupling analysis on the set of recovery process parameters corresponding to different pyrolysis temperature ranges and the acid leaching parameter combination, set a collaborative optimization matrix, and perform iterative recycling parameter according to the waste recycling task, and synchronously collect the actual recovery rate of rare earth elements, impurity residue amount, reaction energy consumption, and equipment operation state parameters to establish a feedback adjustment mechanism for recycling parameters.

[0054] Further, the coupling analysis module M400 is configured to execute the following method: According to the preset recovery rate target value, perform recovery rate prediction feedback optimization in combination with the actual recovery rate of rare earth elements, impurity residue amount, reaction energy consumption, and equipment operation state parameters; at the same time, establish a feedback adjustment mechanism for recycling parameters in combination with the recovery reaction conditions.

[0055] Further, the coupling analysis module M400 is further configured to execute the following method: 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 at different positions during the pyrolysis process; based on the waste dielectric constant, perform pyrolysis zoning in combination with the three-dimensional temperature field distribution cloud map, and set a gradient temperature control interval, where the gradient temperature control interval includes an oxide layer decomposition temperature control zone and a magnetic phase reconstruction temperature control zone.

[0056] Further, the coupling analysis module M400 is further configured to execute the following method: In the waste material pretreatment stage, a microwave resonance cavity array is introduced. Based on the dielectric constant of the waste material, a three-dimensional electromagnetic field hot spot distribution map is generated. An alternating magnetic field is applied using a Helmholtz coil group. After the eddy current thermal effect is generated, the infrared temperature measurement array is activated. At the same time, based on the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map, the local hot spot area is located, and the gradient temperature control interval is dynamically fine-tuned.

[0057] Furthermore, the coupling analysis module M400 is also used to execute the following method: Perform spatial registration on the three-dimensional electromagnetic field hot spot 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 areas and low-temperature blind areas under the electromagnetic-thermal field coupling effect, establish a temperature gradient compensation matrix. Introduce energy consumption constraint conditions, and based on the temperature gradient compensation matrix, configure a collaborative optimization mapping instruction set for the gradient temperature control interval and the acid leaching concentration parameter.

[0058] Furthermore, the coupling analysis module M400 is also used to execute the following method: Obtain the matching degree between the oxide layer decomposition rate and the magnetic phase reconstruction rate in the local hot spot area, and make a judgment in combination with a preset rate deviation, and set a matching compensation rule. Among them, the technical parameter indicators associated with the matching compensation rule include microwave power density, Helmholtz coil current phase angle, and pyrolysis residence time.

[0059] Furthermore, the second configuration module M300 is also used to execute the following method: In the acid leaching treatment stage, with the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable, combined with the acid leaching reaction time, set an acid leaching optimization space. In the acid leaching optimization space, perform a global search 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, and the acid leaching optimization parameter sequence is associated with the acid leaching parameter combination in a one-to-one mapping manner.

[0060] Furthermore, the second configuration module M300 is also used to execute the following method: Based on the acid leaching optimization space, define variable boundaries and constraint conditions. According to the acid solution supplement amount, perform proportional capacity transportation on the recycled acid leaching solution and the supplementary acid leaching solution to obtain the acid leaching concentration parameter of the mixed acid leaching solution. Through the objective function, under the variable boundaries and constraint conditions, combined with the acid leaching concentration parameter of the mixed acid leaching solution, iteratively update the acid solution supplement amount.

[0061] In summary, any step can be stored as a computer instruction or program in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor, and no redundant restrictions are imposed here.

[0062] Furthermore, the above technical solution only reflects the preferred technical solution of the technical solution of the embodiments of the present application. Some changes that those skilled in the art may make to some parts thereof all reflect the principles of the new type of the embodiments of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. An optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction, characterized in that, The method includes: Determining physical property indexes including rare earth element content, oxide layer thickness, and magnetic phase distribution parameters according to the target NdFeB waste; Introducing a pyrolysis temperature gradient, and simulating the processes of rare earth element diffusion, oxide layer decomposition, and magnetic phase reconstruction at different temperature gradients through finite element analysis in combination with the physical property indexes, and configuring a set of recovery process parameters corresponding to different pyrolysis temperature intervals; Uploading acid leaching concentration parameters, and configuring an acid leaching parameter combination that meets the preset recovery rate target value through multivariate analysis of the dissolution efficiency of rare earth elements, impurity dissolution amount, and reaction rate at different acid leaching concentrations, where the preset recovery rate target value is associated with the waste recycling task; Performing coupling analysis on the set of recovery process parameters corresponding to different pyrolysis temperature intervals and the acid leaching parameter combination, setting a collaborative optimization matrix, and performing iteration of recovery parameters according to the waste recycling task, and simultaneously collecting actual recovery rates of rare earth elements, impurity residue amounts, reaction energy consumption, and equipment operation state parameters, and establishing a feedback adjustment mechanism for recovery parameters.

2. The optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction according to claim 1, characterized in that, Simultaneously collecting actual recovery rates of rare earth elements, impurity residue amounts, reaction energy consumption, and equipment operation state parameters, and establishing a feedback adjustment mechanism for recovery parameters, the method includes: Performing prediction feedback optimization of the recovery rate according to the preset recovery rate target value in combination with the actual recovery rate of rare earth elements, impurity residue amount, reaction energy consumption, and equipment operation state parameters; Meanwhile, establishing a feedback adjustment mechanism for recovery parameters in combination with the recovery reaction conditions.

3. The optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction according to claim 2, characterized in that, In combination with the recovery reaction conditions, the method includes: Deploying 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 at different positions during pyrolysis; Based on the dielectric constant of the waste, performing pyrolysis zoning in combination with the three-dimensional temperature field distribution cloud map, and setting a gradient temperature control interval, where the gradient temperature control interval includes an oxide layer decomposition temperature control zone and a magnetic phase reconstruction temperature control zone.

4. The optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction according to claim 3, characterized in that, Based on the dielectric constant of the waste, performing pyrolysis zoning in combination with the three-dimensional temperature field distribution cloud map, the method further includes: In the waste pretreatment stage, introducing a microwave resonance cavity array, and generating a three-dimensional electromagnetic field hot spot distribution map based on the dielectric constant of the waste; Applying an alternating magnetic field using a Helmholtz coil group, and starting the infrared temperature measurement array after generating an eddy current heating effect; Meanwhile, based on the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map, locating local hot spot areas, and dynamically fine-tuning the gradient temperature control interval.

5. The optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction according to claim 4, characterized in that, The method further includes: Performing spatial registration on the three-dimensional electromagnetic field hot spot distribution map and the three-dimensional temperature field distribution cloud map, and identifying local overheating areas and low-temperature blind spots under the electromagnetic-thermal field coupling effect; Based on the local overheating areas and low-temperature blind spots under the electromagnetic-thermal field coupling effect, establishing a temperature gradient compensation matrix; Introducing an energy consumption constraint condition, and configuring a collaborative optimization mapping instruction set for the gradient temperature control interval and acid leaching concentration parameters based on the temperature gradient compensation matrix.

6. The optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction according to claim 5, characterized in that, The method includes: Obtain the matching degree between the oxide layer decomposition rate and the magnetic phase reconstruction rate of the local hot spot area, and make a judgment in combination with the preset rate deviation, and set the matching compensation rule; Among them, 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 optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction according to claim 1, characterized in that, The preset recovery rate target value is associated with the waste material recovery task, and the method further includes: In the acid leaching treatment stage, taking the stirring rate as a continuous variable and the solid-liquid ratio as a discrete variable, and combining the acid leaching reaction time, set the acid leaching optimization space; In the acid leaching optimization space, perform a global search with 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, and the acid leaching optimization parameter sequence is associated and mapped one-to-one with the acid leaching parameter combination.

8. The optimization method for the recovery parameters of Nd-Fe-B waste materials for recovery rate prediction according to claim 7, characterized in that, Perform a global search with 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, and the method further includes: Based on the acid leaching optimization space, define variable boundaries and constraint conditions; According to the acid solution supplement amount, perform proportional capacity transportation on the recycled acid leaching solution and the supplementary acid leaching solution to obtain the acid leaching concentration parameter of the mixed acid leaching solution; Through the objective function, under the variable boundaries and constraint conditions, in combination with the acid leaching concentration parameter of the mixed acid leaching solution, iteratively update the acid solution supplement amount.

9. The neodymium-iron-boron waste recycling parameter optimization system for recovery rate prediction, characterized in that, For implementing the neodymium-iron-boron waste material recovery parameter optimization method for predicting the recovery rate according to any one of claims 1-8, the system includes: An index determination module, configured to determine physical property indicators including rare earth element content, oxide layer thickness, and magnetic phase distribution parameters according to the target neodymium-iron-boron waste material; A first configuration module, configured to introduce a pyrolysis temperature gradient, and through finite element analysis in combination with the physical property indicators, simulate the processes of rare earth element diffusion, oxide layer decomposition, and magnetic phase reconstruction under different temperature gradients, and configure a set of recovery process parameters corresponding to different pyrolysis temperature intervals; A second configuration module, configured to upload the acid leaching concentration parameter, and through multivariate analysis of the dissolution efficiency of rare earth elements, impurity dissolution amount, and reaction rate at different acid leaching concentrations in combination with the physical property indicators, configure an acid leaching parameter combination that meets the preset recovery rate target value, and the preset recovery rate target value is associated with the waste material recovery task; A coupling analysis module, configured to perform coupling analysis on the set of recovery process parameters corresponding to different pyrolysis temperature intervals and the acid leaching parameter combination, set a collaborative optimization matrix, and perform recovery parameter iteration according to the waste material recovery task, and synchronously collect the actual recovery rate of rare earth elements, impurity residue amount, reaction energy consumption, and equipment operation state parameters, and establish a recovery parameter feedback adjustment mechanism.

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