Plating magnetism optimization method and system for rare earth magnetic material and medium

Abstract

The invention discloses a plating magnetism optimization method and system of a rare earth magnetic material and a medium, and relates to the technical field of metal material surface plating, the method comprises the steps that a historical plating magnetism database of a rare earth magnetic material similar magnetic material is acquired, and the historical plating magnetism database comprises multiple sets of plating data sets; extracting predetermined plating magnetic indexes such as corrosion resistance and saturation magnetization intensity, and traversing in the target plating data set to obtain target magnetic index parameters; performing weighted calculation by combining any predetermined weight of any magnetic index to obtain a target plating magnetic index; a historical optimal plating process parameter is obtained through optimization according to the maximum target plating magnetic index; and the plating magnetic treatment of the rare earth magnetic material is optimized according to the historical optimal plating process parameters. According to the method, the technical problems that the plating mode of the rare earth magnetic material is difficult to comprehensively balance multiple magnetic related properties of the rare earth magnetic material and the magnetic property of the material cannot reach the optimal state are solved, and the technical effects of optimizing the plating effect of the rare earth magnetic material and improving the comprehensive magnetic property of the rare earth magnetic material are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of metal material surface plating, and in particular to a plating magnetic optimization method, system and medium for rare earth magnetic materials. Background Art

[0002] The plating of rare earth magnetic materials is crucial to optimizing their magnetic properties, and directly affects the application effect of the materials in various types of equipment. In the existing technology, the plating of rare earth magnetic materials mostly relies on empirical process parameter settings, and the traditional trial and error method is used to adjust the parameters such as the composition of the plating solution and the plating time to optimize the magnetism. These methods can play a certain role in simple scenarios, but as the requirements for the performance of magnetic materials increase, they are exposed to limitations in complex application scenarios. Traditional methods do not systematically integrate historical data, and it is difficult to comprehensively balance multiple magnetic indicators such as corrosion resistance and saturation magnetization. As a result, the magnetism of the material after plating cannot be optimized, and it is difficult to meet the performance requirements of high-precision equipment for magnetic materials. Summary of the Invention

[0003] The present application provides a method, system and medium for optimizing the plating magnetic properties of rare earth magnetic materials, which are used to solve the technical problem that the plating method of rare earth magnetic materials is difficult to comprehensively balance their multiple magnetic-related properties and cannot make the material's magnetic properties reach the optimal state.

[0004] The first aspect of the present application provides a method for optimizing the plating magnetic properties of rare earth magnetic materials, the method comprising: obtaining a historical plating magnetic database of similar magnetic materials of the rare earth magnetic material, wherein the historical plating magnetic database comprises multiple sets of plating data sets; extracting any magnetic index from predetermined plating magnetic indexes, and traversing the arbitrary magnetic index in a target plating data set to obtain a target magnetic index parameter, wherein the predetermined plating magnetic index comprises at least corrosion resistance, saturation magnetization, coercive force and Curie temperature, and the target plating data set refers to any set of data sets in the multiple sets of plating data sets; performing a weighted calculation on the target magnetic index parameter in combination with any predetermined weight of the arbitrary magnetic index to obtain a target plating magnetic index; performing an optimization analysis with the maximum target plating magnetic index as the goal to obtain the historical optimal plating process parameters; and performing plating magnetic optimization processing on the rare earth magnetic material according to the historical optimal plating process parameters.

[0005] The second aspect of the present application provides a plating magnetic optimization system for rare earth magnetic materials, the system comprising: a historical plating magnetic database acquisition module for acquiring a historical plating magnetic database of similar magnetic materials of the rare earth magnetic material, wherein the historical plating magnetic database includes multiple sets of plating data sets; a target magnetic index parameter acquisition module for extracting any magnetic index from predetermined plating magnetic indexes, and traversing the arbitrary magnetic index in the target plating data set to obtain target magnetic index parameters, wherein the predetermined plating magnetic index includes at least corrosion resistance, saturation magnetization, coercive force and Curie temperature, and the target plating data set refers to any set of data sets in the multiple sets of plating data sets; a target plating magnetic index acquisition module for performing weighted calculation on the target magnetic index parameters in combination with any predetermined weight of the arbitrary magnetic index to obtain a target plating magnetic index; a historical optimal plating process parameter acquisition module for performing optimization analysis with the target plating magnetic index as the maximum as the target to obtain the historical optimal plating process parameters; a plating magnetic optimization execution module for performing plating magnetic optimization processing on the rare earth magnetic material according to the historical optimal plating process parameters.

[0006] The third aspect of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for optimizing the plating magnetic properties of rare earth magnetic materials provided in the present application.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application obtains historical plating magnetic data of similar magnetic materials of rare earth magnetic materials, extracts magnetic indicators and traverses to obtain parameters, and obtains the plating magnetic index through weighted calculation. The historical optimal process parameters are obtained by optimizing with the maximum index as the goal, and then incremental optimization is performed through the process increment strategy to determine the target optimal plating process parameters, and the rare earth magnetic material is plated, so that the plating magnetism of the rare earth magnetic material is effectively optimized, thereby achieving the technical effect of optimizing the plating effect of the rare earth magnetic material and improving its comprehensive magnetic performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 It is a flow chart of the method for optimizing the plating magnetic properties of rare earth magnetic materials provided in an embodiment of the present application.

[0010] Figure 2It is a structural schematic diagram of the plating magnetic optimization system of rare earth magnetic materials provided in an embodiment of the present application.

[0011] Explanation of the reference numerals: historical plating magnetic database acquisition module 1, target magnetic index parameter acquisition module 2, target plating magnetic index acquisition module 3, historical optimal plating process parameter acquisition module 4, plating magnetic optimization execution module 5. DETAILED DESCRIPTION

[0012] The present application provides a method, system and medium for optimizing the plating magnetic properties of rare earth magnetic materials, which are used to solve the technical problem that the plating method of rare earth magnetic materials is difficult to comprehensively balance their multiple magnetic-related properties and cannot make the material's magnetic properties reach the optimal state.

[0013] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0014] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0015] Example 1, as Figure 1 As shown, a method for optimizing the plating magnetic properties of rare earth magnetic materials, wherein the method comprises: Step A100: Acquire a historical plating magnetic database of similar magnetic materials of the rare earth magnetic material, wherein the historical plating magnetic database includes multiple sets of plating data sets.

[0016] In the embodiments of the present application, rare earth magnetic material is a magnetic material containing rare earth metal elements and transition metal elements. The type and proportion of its metal elements are the key to distinguishing similar magnetic materials. Through a specific plating process, its corrosion resistance, saturation magnetization intensity, coercive force, Curie temperature and other magnetic properties can be optimized.

[0017] Specifically, before obtaining a historical plating magnetic database of similar rare earth magnetic materials, the metal element composition of the target rare earth magnetic material should be clarified. For example, if the target material contains rare earth metal elements Sm and Dy in a ratio of 4:1 and transition metal elements Co and Cu in a ratio of 9:1, and the total rare earth metal element accounts for 25% and the total transition metal element accounts for 75%, then similar magnetic materials need to be screened based on this.

[0018] Subsequently, the team reviewed existing magnetic material plating records, verifying the types and ratios of the metal elements in each of the magnetic materials. If a historical magnetic material contained Sm, Dy, and Co but lacked Cu, or if the Sm:Dy ratio was 3:2, these materials would not meet the same standards and would be excluded. Only magnetic materials containing Sm, Dy, Co, and Cu, with the exact ratio of each element matching the target material, would be considered similar.

[0019] For the selected similar magnetic materials, corresponding plating datasets are collected. Each dataset must include specific plating process parameters, such as the metal salt concentration in the plating solution, the reducing agent concentration, and the plating time, as well as corresponding magnetic index parameters such as corrosion resistance, saturation magnetization, coercivity, and Curie temperature. By collecting multiple plating datasets, a historical plating magnetic database containing multiple sets of different process parameters and corresponding magnetic indexes is ultimately established.

[0020] By screening similar magnetic materials and collecting multiple sets of their plating data sets, a historical plating magnetic database was established, which provided consistent and comparable basic data for the subsequent extraction of magnetic index parameters and optimization analysis, ensuring the effectiveness of subsequent optimization steps.

[0021] Step A200: Extract any magnetic index from the predetermined coating magnetic indexes, and traverse the arbitrary magnetic index in the target coating data set to obtain target magnetic index parameters, wherein the predetermined coating magnetic index includes at least corrosion resistance, saturation magnetization, coercive force and Curie temperature, and the target coating data set refers to any one of the multiple sets of coating data sets.

[0022] Optionally, when optimizing the magnetic properties of rare earth magnetic materials, one can first select any one of the predetermined coating magnetic indices. The predetermined coating magnetic indices include at least corrosion resistance, saturation magnetization, coercivity, and Curie temperature. The corresponding acquisition and quantification methods are shown in Table 1. For example, corrosion resistance can be selected first. In this case, the quantification method for this indicator must be clarified, such as using the corrosion rate (in mm / year) in a specific corrosive environment as a measurement standard.

[0023] Table 1: Table of methods for obtaining and quantifying the magnetic indexes of the predetermined coating

[0024] Next, select any one of the multiple plating datasets as the target plating dataset. Assume that the plating process parameters corresponding to this target plating dataset are: metal salt concentration 30g / L, reducing agent concentration 10g / L, stabilizer concentration 5g / L, rare earth salt concentration 2g / L, and plating time 15 minutes. In this target plating dataset, the magnetic index data corresponding to the above process parameters are recorded. At this point, it is necessary to traverse this target plating dataset and find the specific value corresponding to the corrosion resistance. For example, the corrosion resistance parameter under the process of this plating dataset is 0.02mm / year.

[0025] If saturation magnetization is selected as the arbitrary magnetic index, the same traversal is performed using the target plating dataset as the object. Saturation magnetization is typically measured in Tesla (T). After traversal, the corresponding saturation magnetization parameter for this process parameter can be obtained from the target plating dataset, which is 1.1T. Similarly, if coercivity or Curie temperature is selected, the corresponding target magnetic index parameters, such as 800kA / m and 370°C, can be obtained by traversing the same target plating dataset.

[0026] By determining any magnetic index and traversing the target plating data set, the corresponding target magnetic index parameters are obtained, providing specific and quantifiable basic data for subsequent weighted calculations, ensuring the accuracy of the plating magnetic index calculation.

[0027] Step A300: performing weighted calculation on the target magnetic index parameters in combination with any predetermined weight of the arbitrary magnetic index to obtain a target coating magnetic index.

[0028] In one embodiment of the present application, before performing the weighted calculation, arbitrary predetermined weights for any magnetic index are first determined. These arbitrary predetermined weights can be set by those skilled in the art based on the actual application scenarios of rare earth magnetic materials. For example, in magnetic materials used for precision motors, the saturation magnetization and coercive force have a more significant impact and can be assigned a weight of 0.3 respectively, while corrosion resistance and Curie temperature can be assigned a weight of 0.2 each. If used in high-temperature environment equipment, the weight of Curie temperature can be increased to 0.4, and the weight of the other three can be 0.2 each.

[0029] Next, retrieve the acquired target magnetic index parameters. Each magnetic index has its original measurement data, and the units and ranges of these data vary. For example, corrosion resistance may be corrosion rate (mm / year), saturation magnetization intensity is Tesla (T), etc. In order to perform weighted calculations on different indicators, they need to be converted to a unified scale. The standardization steps are as follows: First, the value ranges in the original measurement data and historical data for each magnetic index must be clearly defined. This includes the minimum value corresponding to the worst performance (normalized to 0) and the maximum value corresponding to the best performance (normalized to 100). For indicators such as saturation magnetization, coercive force, and Curie temperature, where larger values ​​indicate better performance, subtract the minimum value from the actual data, divide by the difference between the maximum and minimum values, and multiply by 100 to obtain the normalized value. For indicators such as corrosion resistance, where smaller values ​​indicate better performance (such as corrosion rate), subtract the actual data from the maximum value, divide by the difference between the maximum and minimum values, and multiply by 100 to obtain the normalized value. This way, specific data in different units and ranges are uniformly converted to normalized values ​​ranging from 0 to 100.

[0030] Assume that the parameters corresponding to a target plating data set are: corrosion resistance normalized value 90, saturation magnetization normalized value 85, coercivity normalized value 90, and Curie temperature normalized value 80, where the full score is 100.

[0031] Calculation is performed according to the set weights. Taking the precision motor scenario as an example, the calculation process is: 90×0.2+85×0.3+90×0.3+80×0.2=18+25.5+27+16=86.5. This result is the target plating magnetic index corresponding to the target plating dataset. If the weights for high temperature environment are used instead, the calculation is 90×0.2+85×0.2+90×0.2+80×0.4=18+17+18+32=85, thus obtaining the corresponding target plating magnetic index.

[0032] By combining the predetermined weights of each magnetic index to perform weighted calculation on the target magnetic index parameters, the target coating magnetic index is obtained, which realizes the comprehensive quantification of multiple magnetic properties and provides a unified and comparable evaluation standard for subsequent optimization analysis with the goal of maximizing the index.

[0033] Step A400: performing optimization analysis with the maximum target plating magnetic index as the goal, and obtaining the historical optimal plating process parameters.

[0034] Specifically, the target plating data set is arranged in descending order according to the target plating magnetic index to obtain a data set sequence, and the plating process parameters of the first data set are taken as the historical optimal plating process parameters. The specific steps are described in detail in A410-A420.

[0035] Step A500: performing a plating magnetic optimization process on the rare earth magnetic material according to the historical optimal plating process parameters.

[0036] Specifically, the rare earth magnetic material is first pretreated by ultrasonic cleaning to remove impurities such as oil and oxide layers on the surface, ensuring a clean surface and providing a good base for subsequent plating. Assume that the historically optimal plating process parameters are: a metal salt NiCl2 concentration of 45g / L, a reducing agent H2BO3 concentration of 20g / L, a stabilizer sodium citrate concentration of 8g / L, a rare earth salt LaCl3 concentration of 5g / L, and a plating time of 20 minutes.

[0037] Subsequently, a plating solution is prepared according to the aforementioned process parameters, and each component is added to deionized water in proportion and stirred until completely dissolved. The pH value of the plating solution is adjusted to a predetermined range, such as 5.5-6.0. The pretreated rare earth magnetic material is placed in a plating tank, ensuring that the rare earth magnetic material is completely immersed in the plating solution. The plating equipment is started, the plating solution temperature is controlled at 50°C, a stable current is applied, and the plating operation is performed for 20 minutes according to the aforementioned historical optimal plating time.

[0038] After plating, the rare earth magnetic material was removed from the plating tank, rinsed with deionized water to remove any residual plating solution, and then dried in a drying oven at 80°C for 30 minutes to form a uniform and complete coating. The treated rare earth magnetic material was then tested for magnetic properties, including corrosion resistance, corrosion rate, saturation magnetization, coercivity, and Curie temperature. All indicators were superior to those obtained without the process parameters.

[0039] By performing pretreatment, plating solution configuration, plating operation and post-processing according to the historically optimal plating process parameters, the plating quality of rare earth magnetic materials was effectively improved and their comprehensive magnetic properties were optimized.

[0040] Furthermore, step A100 in the method provided in the embodiment of the present application includes: A110: The similar magnetic material refers to a magnetic material having the same type and proportion of metal elements as those in the rare earth magnetic material, and the metal elements include rare earth metal elements and transition metal elements.

[0041] Specifically, when optimizing the magnetic properties of rare earth magnetic materials, it is first necessary to determine the metal element composition of the target rare earth magnetic material. Assume that the target rare earth magnetic material contains rare earth metal elements La and Nd in a ratio of 3:7 and transition metal elements Fe and Co in a ratio of 8:2, and the total rare earth metal element accounts for 30% and the total transition metal element accounts for 70%.

[0042] Subsequently, while collecting historical magnetic data on coatings, it was necessary to screen the various types of magnetic materials available. Each magnetic material was individually examined for its metallic elements to confirm whether it contained La, Nd, Fe, and Co. The ratios of these elements were then checked to determine whether the La to Nd ratio was 3:7, the Fe to Co ratio was 8:2, and the total ratio of rare earth metals to transition metals was 3:7.

[0043] For example, if a historical magnetic material contains the four elements mentioned above but has a La:Nd ratio of 2:8, it will be excluded due to the inconsistent element ratio, even if other conditions are met. Similarly, if a magnetic material lacks the transition metal element Co and contains only Fe, it will be screened out. Only magnetic materials that fully meet the requirements of the target material in terms of metal element types and ratios will be included in the historical plating magnetic database for similar magnetic materials.

[0044] Through the above screening steps, it is ensured that the data in the historical database are highly consistent and comparable with the target rare earth magnetic materials, providing a reliable data basis for the subsequent optimization of plating process parameters based on historical data, thereby ensuring the accuracy of the plating magnetic optimization results.

[0045] Furthermore, step A400 in the method provided in the embodiment of the present application includes: A410: Arrange the target plating data set in descending order based on the target plating magnetic index to obtain a data set sequence.

[0046] A420: Obtain the first data set in the data set sequence, and use the plating process parameters in the first data set as the historical optimal plating process parameters.

[0047] Optionally, multiple target plating data sets are first determined, each of which contains a corresponding target plating magnetic index and specific plating process parameters. For example, assuming there are 6 target plating data sets, their corresponding target plating magnetic indices are 82, 90, 86, 93, 88, and 85, respectively, and each data set records specific process parameters such as the metal salt ratio in the plating solution, the reducing agent concentration, and the plating time.

[0048] Next, the six target plating datasets were sorted in descending order based on the target plating magnetic index. The positions of the data sets were adjusted from largest to smallest indices. The resulting dataset sequences corresponded to the indices of 93, 90, 88, 86, 85, and 82, respectively. The position of each target plating dataset in the dataset sequence was determined by the size of its target plating magnetic index, with the target plating dataset with the larger index positioned closer to the front.

[0049] Next, the first target plating dataset in the dataset sequence is extracted, i.e., the target plating dataset ranked first in the dataset sequence with an index of 93. The plating process parameters recorded in this target plating dataset are reviewed, such as the rare earth salt concentration in the plating solution, the stabilizer concentration, and the plating duration, and these plating process parameters are determined as the historically optimal plating process parameters.

[0050] By arranging the target plating data sets in descending order according to the magnetic index and selecting the process parameters of the first data set, the historical optimal plating process parameters were quickly determined, providing a direct and effective reference for the optimization of the plating magnetic properties of rare earth magnetic materials.

[0051] Furthermore, step A500 in the method provided in the embodiment of the present application includes: A510: Extract any process indicator from the predetermined plating process indicators.

[0052] A520: Match any process parameter corresponding to any process indicator in the historical optimal plating process parameters.

[0053] A530: Retrieve the process increment strategy to perform incremental processing on the arbitrary process parameters to obtain an arbitrary parameter domain.

[0054] A540: An incremental optimization space is established based on the arbitrary parameter domain, and the plating magnetic prediction index is used as an optimization evaluation index to perform incremental optimization on the historical optimal plating process parameters to obtain the target optimal plating process parameters.

[0055] A550: Performing plating magnetic optimization treatment on the rare earth magnetic material according to the target optimal plating process parameters.

[0056] Specifically, first, when extracting any process indicator from the predetermined plating process indicators, first obtain a set of plating solution components containing metal salts, reducing agents, etc., form a plating solution preparation process indicator set based on their types and proportions, and then use the plating time and the indicator set as the predetermined plating process indicators. The specific steps are described in detail in A511-A513.

[0057] Before parameter matching, the specific contents of the historically optimal plating process parameters must be clarified. For example, the historically optimal plating process parameters include: the metal salts in the plating solution are nickel sulfate and cobalt chloride, with a ratio of 5:2; the reducing agent is sodium hypophosphite, accounting for 100%; the stabilizer is potassium sodium tartrate, accounting for 100%; the rare earth salt is praseodymium nitrate, accounting for 100%, and the plating time is 22 minutes. These parameters together constitute the complete historically optimal process parameters.

[0058] Then, any one of the predetermined plating process indicators is selected. For example, if the selected arbitrary process indicator is the type and ratio of the metal salt, the corresponding content needs to be found in the historical optimal plating process parameters. From the above example, the specific types of metal salts are extracted as nickel sulfate and cobalt chloride, and the ratio of the two is 5:2, which is used as the arbitrary process parameter corresponding to the arbitrary process indicator.

[0059] If the selected arbitrary process indicator is plating time, the specific value of plating time, 22 minutes, is directly located in the historical optimal plating process parameters and determined as the corresponding arbitrary process parameter. Similarly, if the type of reducing agent is selected as an arbitrary process indicator, the reducing agent type can be matched to sodium hypophosphite.

[0060] Next, when invoking the process increment strategy to perform incremental processing on any process parameter, if the arbitrary process parameter is a type of plating solution component, it is necessary to extract a type-specific incremental plan and retrieve the corresponding predetermined set of similar components as the arbitrary parameter domain of the parameter. The specific steps are detailed in A531-A532. If the arbitrary process parameter is a plating solution component ratio or plating time, it is necessary to extract a numerical incremental plan and obtain its neighborhood as the arbitrary parameter domain of the parameter. The specific steps are detailed in A533-A534.

[0061] Then, an incremental optimization space is established based on an arbitrary parameter domain, and correlation analysis is performed with process parameters as independent variables and magnetic index parameters as dependent variables. A process factor set and coefficient set are established, and the plating magnetic index of the incremental parameters is predicted and optimized to obtain the target optimal plating process parameters. The specific steps are described in detail in A541-A546.

[0062] When optimizing the magnetic properties of rare earth magnetic materials based on the target optimal plating process parameters, the rare earth magnetic materials must first be pretreated. Use an alkaline cleaning solution, such as a 5% sodium hydroxide solution, to clean the surface of the magnetic material to remove impurities such as oil, dust, etc. attached to the surface. The cleaning time is controlled within 10 minutes. Then rinse with deionized water until neutral. Then use 10% dilute hydrochloric acid for activation treatment for 3 minutes to remove the surface oxide layer and improve the bonding strength between the coating and the substrate. After the treatment is completed, rinse again with deionized water and dry.

[0063] After pretreatment, the rare earth magnetic material enters the plating stage, and the plating solution must be configured strictly according to the target optimal process parameters. For example, if the target optimal plating process parameters include a nickel sulfate to cobalt chloride ratio of 3.3:1, a reducing agent concentration of 16g / L, and a pH of 5.8, then the corresponding masses of nickel sulfate, cobalt chloride, and reducing agent are accurately weighed and dissolved in deionized water, stirring evenly. The pH of the plating solution is then adjusted to 5.8 with dilute sulfuric acid or sodium hydroxide solution, and the solution is allowed to stand for 30 minutes to stabilize.

[0064] At the same time, set the plating equipment parameters based on the optimal plating time (e.g., 22 minutes) and temperature (e.g., 50°C). Heat the plating tank to 50°C and maintain a constant temperature within ±1°C. Suspend the pretreated rare earth magnetic material on a plating rack and immerse it in the plating solution, ensuring that the surface of the rare earth magnetic material is in complete contact with the plating solution. For electrolytic plating, connect the power supply, adjust the current density to the optimal value, start the timer, and maintain all parameters stable for 22 minutes.

[0065] During the plating process, an online monitoring system tracks the bath temperature, pH value, and current density in real time. If any parameter deviation occurs, such as a temperature rise to 52°C, the online monitoring system automatically activates adjustment mechanisms, such as turning on the cooling device, to ensure that the parameters remain within the optimal range. After plating is completed, the rare earth magnetic material is immediately removed from the plating bath, rinsed three times with deionized water to remove residual plating solution on the surface, and then dried in an 80°C oven for 30 minutes to obtain a preliminarily optimized plated rare earth magnetic material.

[0066] Finally, the magnetic indexes of the optimized rare earth magnetic materials were tested, the saturation magnetization intensity and coercive force were measured using a magnetic property tester, the corrosion resistance was evaluated through a salt spray test, and the index data before and after optimization were compared to verify the effectiveness and effect of the optimization effect.

[0067] By strictly implementing steps such as pretreatment, plating solution configuration, parameter control, post-processing and performance testing, the target optimal plating process parameters are converted into actual operations, ultimately achieving a significant improvement in the magnetic properties of rare earth magnetic materials after plating.

[0068] Furthermore, step A510 in the method provided in the embodiment of the present application includes: A511: Obtain a plating solution component set, wherein the plating solution component set includes at least a metal salt, a reducing agent, a stabilizer and a rare earth salt.

[0069] A512: Based on the type and proportion of the metal salt, the type and proportion of the reducing agent, the type and proportion of the stabilizer, and the type and proportion of the rare earth salt, a set of plating solution preparation process indicators is formed.

[0070] A513: The plating time and the plating solution preparation process indicator set are used as the predetermined plating process indicators.

[0071] In an embodiment of the present application, the predetermined plating process indicators are the plating time and a set of plating solution preparation process indicators formed based on the type and proportion of metal salts, the type and proportion of reducing agents, the type and proportion of stabilizers, and the type and proportion of rare earth salts.

[0072] Specifically, when extracting the predetermined plating process indicators, it is first necessary to obtain the plating solution component set. This step requires collecting various components required in the plating process, which at least include metal salts, reducing agents, stabilizers and rare earth salts. Specifically, metal salts are compounds that provide plating metal ions. They serve as the source of plating metal in plating and provide basic substances for the formation of metal plating on the surface of rare earth magnetic materials. Reducing agents can reduce metal ions in the plating solution to metal elements, promote the deposition of metal ions on the surface of the material, and ensure the formation of the plating layer. Stabilizers can inhibit unnecessary chemical reactions in the plating solution, prevent the spontaneous precipitation of metal ions, maintain the stability and uniformity of the plating solution, and ensure the quality of the plating layer. Rare earth salts contain rare earth elements and can participate in the formation of the plating layer, which helps to improve the magnetic properties, corrosion resistance and other properties of the plating layer, and enhance the overall plating effect of rare earth magnetic materials.

[0073] When selecting metal salts, reducing agents, stabilizers, and rare earth salts, the plating objectives and material magnetic requirements must be considered, with priority given to ingredients similar to those used in the historically optimal process. Metal salts should be selected to provide the metal ions required for the coating and have good compatibility with rare earth magnetic materials. Reducing agents must be able to efficiently reduce metal ions to elemental metal to ensure uniform deposition of the coating. Stabilizers should be selected to inhibit impurity reactions in the plating solution and maintain its stability. Rare earth salts should preferably be rare earth element compounds that help improve magnetic properties such as corrosion resistance and saturation magnetization. These salts can be selected based on the predetermined set of similar ingredients in the process increment strategy.

[0074] For example, the metal salt may be nickel sulfate or copper sulfate, the reducing agent may be sodium hypophosphite, the stabilizer may be sodium citrate, and the rare earth salt may be lanthanum chloride. These components together constitute the basic composition of the plating solution.

[0075] Next, a set of process specifications for plating bath preparation is generated based on the types and ratios of the aforementioned components. For example, assume the ratio of nickel sulfate to copper sulfate in the metal salt is 4:1; sodium hypophosphite is used as the reducing agent, at a 100% ratio; sodium citrate is used as the stabilizer, at a 100% ratio; and lanthanum chloride is used as the rare earth salt, at a 100% ratio. These information and specific ratios together form the set of process specifications for plating bath preparation, which is used to standardize the plating bath preparation process.

[0076] Finally, the plating duration is incorporated into the set of process indicators for the plating solution preparation process as a predetermined plating process indicator. For example, the plating duration is set to a range of 15-25 minutes. Combined with the previously formed set of process indicators for the plating solution preparation process, this fully defines the key process indicators that need to be paid attention to during the plating process.

[0077] By obtaining the composition of the plating solution, forming a set of plating solution preparation process indicators and incorporating the plating time, the specific content of the predetermined plating process indicators is clarified, providing a clear and operational basis for subsequent matching of process parameters and incremental processing.

[0078] Furthermore, step A530 in the method provided in the embodiment of the present application includes: A531: If the arbitrary process parameter is the type of plating solution component, then extract the type-based incremental plan in the process incremental strategy.

[0079] A532: Retrieve a predetermined set of similar components corresponding to the type of plating solution components according to the type-based incremental plan, and use the predetermined set of similar components as the arbitrary parameter domain of the arbitrary process parameter.

[0080] Specifically, when dealing with the process parameter of plating solution composition type, first determine the type of plating solution composition that the current arbitrary process parameter refers to. For example, if the metal salt type in the historical optimal plating process parameters is nickel sulfate, then the arbitrary process parameter at this time will be the metal salt type nickel sulfate.

[0081] Subsequently, the process increment strategy is retrieved, which contains a specific type of incremental plan specifically for the type of parameter. This type of incremental plan is a pre-defined adjustment plan for different types of plating solution components by technicians in this field. It clearly defines the range of similar replacements for each type of component. For example, for metal salt types, the plan will list other types of metal salts with similar functions to the current metal salt. For example, if nickel sulfate is currently used, the plan may include similar metal salts such as copper sulfate and nickel chloride. For reducing agents, if sodium hypophosphite is currently used, the plan will include similar reducing agents such as sodium borohydride and hydrazine hydrate. For stabilizers and rare earth salts, the plan will also list similar components that match their properties. For example, if sodium citrate is currently used as a stabilizer, the plan may include similar stabilizers such as potassium sodium tartrate. If lanthanum chloride is currently used as a rare earth salt, the plan may include similar rare earth salts such as praseodymium nitrate. Through this preset, the type-based incremental plan can provide a clear range of alternative components for each type of plating solution component.

[0082] Then, based on the type-based incremental plan, the system further retrieves a predefined set of similar components corresponding to the current plating solution. For example, for nickel sulfate, a metal salt, its corresponding predefined set of similar components might include copper sulfate, nickel chloride, and nickel nitrate, all of which are metal salts suitable for similar plating systems. For sodium hypophosphite, a reducing agent, the corresponding predefined set of similar reducing agents might include sodium borohydride, hydrazine hydrate, and other similar reducing agents.

[0083] Finally, the retrieved set of predetermined similar components is determined as the arbitrary parameter domain of the arbitrary process parameter. For example, the arbitrary parameter domain of the metal salt type is {copper sulfate, nickel chloride, nickel nitrate}, and the arbitrary parameter domain of the reducing agent type is {sodium borohydride, hydrazine hydrate}.

[0084] By clarifying the parameters of the plating solution composition type, calling up the type-specific incremental plan and obtaining the corresponding predetermined set of similar components, an arbitrary parameter domain of the parameter is formed, providing a clear scope and basis for the subsequent establishment of an incremental optimization space based on this and for more accurate process optimization.

[0085] Furthermore, step A530 in the method provided in the embodiment of the present application includes: A533: If the arbitrary process parameter is the proportion of plating solution components or the plating time, the numerical incremental plan in the process incremental strategy is extracted.

[0086] A534: Obtain the neighborhood of the plating solution composition ratio or the plating time according to the numerical incremental plan, and use the neighborhood of the plating solution composition ratio or the plating time as the arbitrary parameter domain of the arbitrary process parameter.

[0087] In one embodiment, when processing arbitrary process parameters such as the ratio of plating solution components or plating duration, the specific type and value of the current arbitrary process parameter must first be determined. For example, if the arbitrary process parameter is a 3:1 ratio of nickel sulfate to cobalt chloride metal salt in the plating solution, or a plating duration of 20 minutes, then the corresponding processing flow must be initiated for such numerical parameters.

[0088] Subsequently, the preset numerical incremental plan in the process incremental strategy is called up. The preset numerical incremental plan is an adjustment plan for numerical parameters such as the proportion of plating solution components and plating time, which is pre-set in the process incremental strategy. Its core is to clarify the specific adjustment rules of various numerical parameters: for the proportion of plating solution components, such as the ratio of nickel sulfate and cobalt chloride in metal salts, the proportion of reducing agents in the plating solution, etc., the numerical incremental plan will set a specific floating ratio range, such as 5%-15% up and down, and the specific value is determined by technical personnel in this field based on historical optimization experience or experimental data; for plating time, the numerical incremental plan will set a fixed floating range, such as 2-5 minutes up and down, to ensure that the adjusted time is still within a reasonable process range. This type of numerical incremental plan is obtained based on the historical process data of rare earth magnetic material plating, a large number of experimental verification results, and process optimization experience in the industry. It is pre-integrated and stored in the process incremental strategy system. When it is necessary to perform incremental processing on numerical process parameters, it can be directly extracted and called from the strategy.

[0089] Then, based on the numerical incremental plan, the parameter's neighborhood is calculated and obtained. For example, for a 3:1 ratio of nickel sulfate to cobalt chloride in the metal salt, with a 10% floating calculation, its neighborhood could include ratio combinations such as 2.7:1, 3:0.9, 3.3:1, and 3:1.1. For a 20-minute plating duration, with a 3-minute floating calculation, its neighborhood would be between 17 and 23 minutes.

[0090] Finally, the calculated neighborhood is determined as the arbitrary parameter domain of the arbitrary process parameter. For example, the arbitrary parameter domain of the metal salt ratio is {2.7:1, 3:0.9, 3.3:1, 3:1.1}, and the arbitrary parameter domain of the plating time is [17 minutes, 23 minutes].

[0091] By clarifying the type of numerical parameters, calling the corresponding incremental plan and calculating the neighborhood, an arbitrary parameter domain is formed, providing a specific and controllable range for the subsequent establishment of an incremental optimization space and the realization of more refined process parameter optimization.

[0092] Furthermore, step A540 in the method provided in the embodiment of the present application includes: A541: Use the target plating process parameters in the target plating data set as independent variables.

[0093] A542: Taking the target magnetic index parameter as a dependent variable.

[0094] A543: Perform correlation analysis on the independent variable and the dependent variable to obtain correlation analysis results.

[0095] A544: An arbitrary process factor set of the arbitrary magnetic index is established based on the correlation analysis result, and the arbitrary process factor set corresponds to an arbitrary factor coefficient set.

[0096] A545: Obtain the first incremental plating process parameter in the incremental optimization space, and predict the plating magnetism of the first incremental plating process parameter in combination with the arbitrary process factor set and the arbitrary factor coefficient set to obtain a first prediction index.

[0097] A546: Perform incremental optimization analysis with the goal of maximizing the first prediction index to obtain the target optimal plating process parameters.

[0098] Optionally, when constructing an incremental optimization space based on an arbitrary parameter domain, the arbitrary parameter domains obtained above need to be integrated. These parameter domains may include a predetermined set of similar components of the plating solution components (such as similar substitutes for metal salts), a neighborhood of the plating solution component ratio (such as a range within which a certain ratio fluctuates up and down), and a neighborhood of the plating time (such as an interval within which a certain time fluctuates up and down). All possible parameters within these parameter domains are combined to form a set containing multiple incremental process parameters, namely the incremental optimization space, which provides a range for subsequent optimization.

[0099] In the incremental optimization space, the relationship between the variables to be analyzed is first clarified: the various plating process parameters in the target plating data set, such as the type and proportion of metal salts, the concentration of reducing agent, and plating time, are used as independent variables, and the corresponding target magnetic index parameters, such as corrosion resistance, saturation magnetization, coercive force, and Curie temperature, are used as dependent variables to establish a basis for correlation analysis between the two.

[0100] Then, a correlation analysis is performed on the independent variables and the dependent variables, and appropriate statistical methods are selected according to the parameter types: for numerical process parameters such as metal salt ratio and plating time and numerical magnetic indicators such as saturation magnetization intensity and coercive force, the Pearson correlation coefficient method is used. By calculating the ratio of the covariance of the two data to the product of the standard deviation, a coefficient reflecting the degree of linear correlation is obtained, ranging from -1 to 1. The closer the absolute value of the coefficient is to 1, the stronger the linear correlation between the process parameter and the magnetic indicator; for categorical process parameters such as reducing agent type and stabilizer type and indicators such as corrosion resistance, point biserial correlation or chi-square test can be used to convert the categorical parameters into virtual variables (such as a certain reducing agent type is recorded as 1, and the others are recorded as 0) and then calculate the correlation coefficient, or by testing the deviation between the actual observed value and the theoretical expected value, it can be judged whether the category change is significantly associated with the indicator change. During the process, it is necessary to first sort out the paired data of each set of process parameters and corresponding magnetic indicators to ensure that the data is complete and matching, and then substitute them into the selected statistical formula for calculation. Finally, based on the obtained coefficient value or significance level, the strength of the influence of each process parameter on the magnetic index is determined to form the correlation analysis results.

[0101] Based on the correlation analysis results, a corresponding arbitrary process factor set is established for each arbitrary magnetic index: the process parameters with a strong correlation with the arbitrary magnetic index are selected as the main factors, and a corresponding coefficient is assigned to each factor according to the strength of the correlation. The stronger the correlation, the larger the coefficient. In this way, the influence weight of each process parameter on the magnetic index is quantified to form an arbitrary process factor set and a corresponding arbitrary factor coefficient set.

[0102] Subsequently, the first incremental plating process parameter is selected from the incremental optimization space, and the arbitrary process factor set and arbitrary factor coefficient set established above are combined to predict the plating magnetism under the incremental parameter through the preset calculation model to obtain a first prediction index that comprehensively reflects various magnetic indicators. This index is used to measure the optimization effect of the incremental parameter.

[0103] Among them, the preset calculation model is a weighted comprehensive prediction model based on the correlation between process factors and magnetic indicators. Its construction process is as follows: first, based on the correlation analysis results of the independent variable and the dependent variable, the process parameters that have a significant impact on each magnetic indicator are screened as an arbitrary process factor set, and each factor is assigned a corresponding weight according to the strength of the correlation, that is, an arbitrary factor coefficient set, and the size of the coefficient is positively correlated with the strength of the correlation; then, a predetermined weight is set for each magnetic indicator to reflect the importance of different indicators. The input of the model includes the first incremental plating process parameters in the incremental optimization space, the corresponding arbitrary process factor set and the arbitrary factor coefficient set. The output is the first prediction index obtained by calculation: first, for each magnetic indicator, the corresponding process factor and coefficient are weighted to obtain a single indicator prediction value; then, combined with the predetermined weights of each magnetic indicator, the single indicator prediction value is comprehensively weighted and summed, and finally the first prediction index reflecting the overall plating magnetic optimization effect is obtained.

[0104] Finally, with the goal of maximizing the first prediction index, the above prediction analysis is performed one by one on all incremental plating process parameters in the incremental optimization space, the prediction index corresponding to each parameter is compared, and the incremental plating process parameter with the largest prediction index is screened out and determined as the target optimal plating process parameter.

[0105] By establishing an incremental optimization space, analyzing variable correlations, quantifying the impact of process factors, predicting evaluation indexes and ultimately optimizing, we achieved fine-tuning of the historically optimal process parameters, thereby obtaining the target optimal process parameters that can further improve the magnetic properties of rare earth magnetic material plating.

[0106] In summary, the method for optimizing the plating magnetic properties of rare earth magnetic materials provided in the embodiments of the present application has the following technical effects: The present application obtains a historical plating magnetic database of similar magnetic materials of rare earth magnetic materials, extracts predetermined plating magnetic indicators, which include at least corrosion resistance, saturation magnetization intensity, coercive force and Curie temperature, and then traverses to obtain target magnetic index parameters, combines them with predetermined weights for weighted calculation to obtain target plating magnetic index, obtains historical optimal plating process parameters through optimization analysis, and then obtains target optimal plating process parameters through incremental optimization and processes them, thereby optimizing the plating magnetic properties of rare earth magnetic materials, making the plating magnetic optimization effect of rare earth magnetic materials more accurate and reliable, and achieving the technical effect of optimizing the plating effect of rare earth magnetic materials and improving their comprehensive magnetic properties.

[0107] Example 2, as Figure 2 As shown, based on the same inventive concept as the aforementioned embodiment 1, the embodiment of the present application provides a plating magnetic optimization system for rare earth magnetic materials, the system comprising: The historical plating magnetic database acquisition module 1 is used to acquire a historical plating magnetic database of similar magnetic materials of rare earth magnetic materials, wherein the historical plating magnetic database includes multiple sets of plating data sets.

[0108] A target magnetic index parameter acquisition module 2 is used to extract any magnetic index from the predetermined coating magnetic indexes, and traverse the arbitrary magnetic index in the target coating data set to obtain target magnetic index parameters, wherein the predetermined coating magnetic index includes at least corrosion resistance, saturation magnetization, coercive force and Curie temperature, and the target coating data set refers to any one of the multiple sets of coating data sets.

[0109] The target plating magnetic index acquisition module 3 is used to perform weighted calculation on the target magnetic index parameter in combination with any predetermined weight of the arbitrary magnetic index to obtain the target plating magnetic index.

[0110] The historical optimal plating process parameter acquisition module 4 is used to perform optimization analysis with the maximum target plating magnetic index as the goal, and obtain the historical optimal plating process parameters.

[0111] The plating magnetic optimization execution module 5 is used to perform plating magnetic optimization processing on the rare earth magnetic material according to the historical optimal plating process parameters.

[0112] Furthermore, the historical plating magnetic database acquisition module 1 is used to perform the following steps: The same type of magnetic material refers to a magnetic material having the same type and ratio of metal elements as those in the rare earth magnetic material, and the metal elements include rare earth metal elements and transition metal elements.

[0113] Furthermore, the historical optimal plating process parameter acquisition module 4 is used to perform the following steps: The target plating data set is arranged in descending order based on the target plating magnetic index to obtain a data set sequence; the first data set in the data set sequence is obtained, and the plating process parameters in the first data set are used as the historical optimal plating process parameters.

[0114] Furthermore, the plating magnetic optimization execution module 5 is used to perform the following steps: Extract any process indicator from the predetermined plating process indicators; match any process parameter corresponding to the arbitrary process indicator in the historical optimal plating process parameters; call the process increment strategy to perform incremental processing on the arbitrary process parameter to obtain an arbitrary parameter domain; establish an incremental optimization space based on the arbitrary parameter domain, and use the plating magnetic prediction index as the optimization evaluation index to perform incremental optimization on the historical optimal plating process parameters to obtain the target optimal plating process parameters; perform plating magnetic optimization processing on the rare earth magnetic material according to the target optimal plating process parameters.

[0115] Furthermore, the plating magnetic optimization execution module 5 is used to perform the following steps: Obtain a plating solution component set, wherein the plating solution component set includes at least a metal salt, a reducing agent, a stabilizer and a rare earth salt; form a plating solution preparation process indicator set based on the type and ratio of the metal salt, the type and ratio of the reducing agent, the type and ratio of the stabilizer and the type and ratio of the rare earth salt; and use the plating time and the plating solution preparation process indicator set as the predetermined plating process indicator.

[0116] Furthermore, the plating magnetic optimization execution module 5 is used to perform the following steps: If the arbitrary process parameter is the type of plating solution component, the type-based incremental plan in the process incremental strategy is extracted; according to the type-based incremental plan, a predetermined set of similar components corresponding to the type of plating solution component is retrieved, and the predetermined set of similar components is used as the arbitrary parameter domain of the arbitrary process parameter.

[0117] Furthermore, the plating magnetic optimization execution module 5 is used to perform the following steps: If the arbitrary process parameter is the ratio of plating liquid components or the plating time, the numerical incremental plan in the process incremental strategy is extracted; the neighborhood of the plating liquid component ratio or the plating time is obtained according to the numerical incremental plan, and the neighborhood of the plating liquid component ratio or the plating time is used as the arbitrary parameter domain of the arbitrary process parameter.

[0118] Furthermore, the plating magnetic optimization execution module 5 is used to perform the following steps: The target plating process parameters in the target plating data set are used as independent variables; the target magnetic index parameters are used as dependent variables; correlation analysis is performed on the independent variables and the dependent variables to obtain correlation analysis results; based on the correlation analysis results, an arbitrary process factor set of the arbitrary magnetic index is established, and the arbitrary process factor set corresponds to an arbitrary factor coefficient set; the first incremental plating process parameter in the incremental optimization space is obtained, and the plating magnetism of the first incremental plating process parameter is predicted in combination with the arbitrary process factor set and the arbitrary factor coefficient set to obtain a first prediction index; incremental optimization analysis is performed with the first prediction index as the maximum as the goal to obtain the target optimal plating process parameter.

[0119] In embodiment three, the present application also provides a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the plating magnetic optimization method of rare earth magnetic materials in the embodiment of the present application, thereby realizing the above-mentioned plating magnetic optimization method of rare earth magnetic materials.

[0120] It should be understood that the embodiments disclosed in this application and the above description can enable those skilled in the art to use this application to implement this application. At the same time, this application is not limited to the embodiments mentioned above. It should be understood that those skilled in the art can still modify the technical solutions described in the above embodiments or replace some of the technical features therein with equivalents; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of this application.

Claims

1. A method for optimizing the plating magnetic properties of rare earth magnetic materials, characterized in that: include: Acquire a historical plating magnetic database of similar magnetic materials of the rare earth magnetic material, wherein the historical plating magnetic database includes multiple sets of plating data sets; Extracting any magnetic index from the predetermined magnetic indexes of the coating, and traversing the arbitrary magnetic index in the target coating data set to obtain a target magnetic index parameter, wherein the predetermined magnetic index of the coating at least includes corrosion resistance, saturation magnetization, coercive force, and Curie temperature, and the target coating data set refers to any one of the multiple sets of coating data sets; performing weighted calculation on the target magnetic index parameter in combination with any predetermined weight of the arbitrary magnetic index to obtain a target plating magnetic index; Performing optimization analysis with the maximum target plating magnetic index as the goal to obtain historical optimal plating process parameters; The rare earth magnetic material is subjected to a plating magnetic optimization treatment according to the historical optimal plating process parameters.

2. The method for optimizing the plating magnetic properties of rare earth magnetic materials according to claim 1, wherein: The same type of magnetic material refers to a magnetic material having the same type and ratio of metal elements as those in the rare earth magnetic material, and the metal elements include rare earth metal elements and transition metal elements.

3. The method for optimizing the plating magnetic properties of rare earth magnetic materials according to claim 1, wherein: An optimization analysis is performed with the maximum target plating magnetic index as the goal to obtain the historical optimal plating process parameters, including: Arranging the target plating data set in descending order based on the target plating magnetic index to obtain a data set sequence; A first data set in the data set sequence is obtained, and the plating process parameters in the first data set are used as the historical optimal plating process parameters.

4. The method for optimizing the plating magnetic properties of rare earth magnetic materials according to claim 1, wherein: After performing a plating magnetic optimization process on the rare earth magnetic material according to the historical optimal plating process parameters, the method further includes: Extracting any process index from predetermined plating process indexes; Matching any process parameter corresponding to the arbitrary process indicator in the historical optimal plating process parameters; Retrieving a process increment strategy to perform incremental processing on the arbitrary process parameters to obtain an arbitrary parameter domain; An incremental optimization space is established based on the arbitrary parameter domain, and the plating magnetic prediction index is used as an optimization evaluation index to perform incremental optimization on the historical optimal plating process parameters to obtain the target optimal plating process parameters; The rare earth magnetic material is subjected to a plating magnetic optimization treatment according to the target optimal plating process parameters.

5. The method for optimizing the plating magnetic properties of rare earth magnetic materials according to claim 4, wherein: Extract any process index from the predetermined plating process index, including: Obtaining a plating solution component set, wherein the plating solution component set at least includes a metal salt, a reducing agent, a stabilizer, and a rare earth salt; forming a set of process indicators for preparing a plating solution based on the type and ratio of the metal salt, the type and ratio of the reducing agent, the type and ratio of the stabilizer, and the type and ratio of the rare earth salt; The plating time and the plating solution preparation process index set are used as the predetermined plating process index.

6. The method for optimizing the plating magnetic properties of rare earth magnetic materials according to claim 5, characterized in that: The process increment strategy is called to perform incremental processing on the arbitrary process parameters to obtain an arbitrary parameter domain, including: If the arbitrary process parameter is the type of plating solution component, extracting the type-based incremental plan in the process incremental strategy; According to the type-based incremental plan, a predetermined set of similar components corresponding to the types of plating solution components is retrieved, and the predetermined set of similar components is used as the arbitrary parameter domain of the arbitrary process parameter.

7. The method for optimizing the plating magnetic properties of rare earth magnetic materials according to claim 5, characterized in that: The process increment strategy is called to perform incremental processing on the arbitrary process parameters to obtain an arbitrary parameter domain, including: If the arbitrary process parameter is a plating solution component ratio or a plating time, extracting a numerical incremental plan in the process incremental strategy; The neighborhood of the plating solution component ratio or the plating time is obtained according to the numerical incremental plan, and the neighborhood of the plating solution component ratio or the plating time is used as the arbitrary parameter domain of the arbitrary process parameter.

8. The method for optimizing the plating magnetic properties of rare earth magnetic materials according to claim 4, characterized in that: An incremental optimization space is established based on the arbitrary parameter domain, and the plating magnetic prediction index is used as the optimization evaluation index to perform incremental optimization on the historical optimal plating process parameters to obtain the target optimal plating process parameters, including: Using the target plating process parameters in the target plating data set as independent variables; Taking the target magnetic index parameter as a dependent variable; Performing a correlation analysis on the independent variable and the dependent variable to obtain a correlation analysis result; An arbitrary process factor set of the arbitrary magnetic index is formed based on the correlation analysis result, and the arbitrary process factor set corresponds to an arbitrary factor coefficient set; Obtaining a first incremental plating process parameter in the incremental optimization space, and predicting plating magnetism of the first incremental plating process parameter by combining the arbitrary process factor set and the arbitrary factor coefficient set to obtain a first prediction index; An incremental optimization analysis is performed with the goal of maximizing the first prediction index to obtain the target optimal plating process parameters.

9. A plating magnetic optimization system for rare earth magnetic materials, characterized in that: The system for implementing the method for optimizing the plating magnetic properties of rare earth magnetic materials according to any one of claims 1 to 8 comprises: A historical plating magnetic database acquisition module is used to acquire a historical plating magnetic database of similar magnetic materials of the rare earth magnetic material, wherein the historical plating magnetic database includes multiple sets of plating data sets; a target magnetic index parameter acquisition module, configured to extract any magnetic index from predetermined coating magnetic indexes, and traverse the arbitrary magnetic index in a target coating data set to obtain target magnetic index parameters, wherein the predetermined coating magnetic index includes at least corrosion resistance, saturation magnetization, coercive force, and Curie temperature, and the target coating data set refers to any one of the multiple coating data sets; a target plating magnetic index acquisition module, configured to perform weighted calculation on the target magnetic index parameter in combination with any predetermined weight of the arbitrary magnetic index to obtain the target plating magnetic index; A historical optimal plating process parameter acquisition module is used to perform optimization analysis with the maximum target plating magnetic index as the goal, and obtain the historical optimal plating process parameters; The plating magnetic optimization execution module is used to perform plating magnetic optimization processing on the rare earth magnetic material according to the historical optimal plating process parameters.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for optimizing the plating magnetic properties of a rare earth magnetic material according to any one of claims 1 to 8 is implemented.

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