Method and system for generating magnetic configuration of magnetic material and storage medium

Abstract

The invention relates to the technical field of model construction, in particular to a method and system for generating a magnetic configuration of a magnetic material and a storage medium. The method comprises the following steps: collecting physical information of a magnetic material, and extracting shape features of the physical information of the magnetic material; determining stress distribution characteristics of the magnetic material according to the shape characteristics; collecting the elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material; constructing a stress magnetic framework based on the stress distribution characteristics; calculating stress sensitive parameters according to the elastic modulus and the Poisson's ratio; performing magnetic anisotropy induced analysis on the stress sensitive parameters and the stress magnetic architecture to generate a magnetic anisotropy distribution diagram; through a data processing technology and a magnetic field coupling analogue simulation technology, magnetization simulation of the magnetic material under different stress and shape conditions is realized, and a magnetic configuration is generated, so that the precision and reliability of performance design of the magnetic material are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of model construction, and in particular to a method, system and storage medium for generating a magnetic configuration of a magnetic material. Background Art

[0002] The magnetic configuration of a magnetic material refers to the arrangement and distribution of its internal magnetic moments, which plays a decisive role in determining its properties (such as magnetization, coercivity, and magnetic energy product). Mechanical stress exerted on a magnetic material has a significant impact on its magnetic configuration, but existing methods are insufficient when considering the effects of stress. For example, in magnetic films and nanostructures, stress can induce magnetic anisotropy and alter the magnetic domain structure. However, existing methods for generating magnetic configurations often employ simplified models when simulating the effects of stress, failing to accurately describe the complex relationship between stress and magnetic configuration. The shape of a magnetic material (such as a thin film, nanowire, or nanoparticle) significantly influences its magnetic configuration. For example, the shape anisotropy of a nanowire can induce a specific magnetic domain structure. However, existing methods lack effective theoretical and computational models for addressing the interplay between shape and magnetic configuration, making it difficult to accurately predict the magnetic configuration under different shapes. Summary of the Invention

[0003] Based on this, it is necessary to provide a method, system and storage medium for generating the magnetic configuration of a magnetic material to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for generating a magnetic configuration of a magnetic material is provided, the method comprising the following steps:

[0005] Step S1: collecting physical information of the magnetic material and extracting shape characteristics of the physical information of the magnetic material; determining stress distribution characteristics of the magnetic material based on the shape characteristics; collecting elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material;

[0006] Step S2: constructing a stress magnetic structure based on the stress distribution characteristics; calculating stress sensitive parameters according to the elastic modulus and Poisson's ratio; performing magnetic anisotropy induction analysis on the stress sensitive parameters and the stress magnetic structure to generate a magnetic anisotropy distribution map;

[0007] Step S3: constructing a shape magnetic architecture based on the shape characteristics; evaluating the magnetic domain structure effect of the shape magnetic architecture to obtain magnetic domain evaluation data; detecting the magnetic flux change under different shape conditions based on the magnetic domain evaluation data, and constructing a magnetic domain structure model;

[0008] Step S4: performing magnetic field coupling on the magnetic anisotropy distribution map and the magnetic domain structure model to obtain a magnetic field coupling model; in the magnetic field coupling model, performing magnetization curve simulation on the magnetic material under different stress and shape conditions to generate magnetic model simulation data;

[0009] Step S5: numerically verifying the magnetic field coupling model according to the magnetic model simulation data to obtain a model verification result; adjusting the model structure parameters according to the model verification result to generate a magnetic configuration.

[0010] By collecting physical information about magnetic materials and extracting their shape characteristics, the present invention can accurately determine the stress distribution characteristics of magnetic materials, providing a basic basis for subsequent magnetic analysis. At the same time, the elastic modulus and Poisson's ratio corresponding to the shape characteristics are collected. These parameters are key to the subsequent calculation of stress-sensitive parameters, ensuring the accuracy and reliability of subsequent analysis. Constructing a stress magnetic architecture based on the stress distribution characteristics can clarify the path of stress's influence on the magnetic properties of magnetic materials. Calculating stress-sensitive parameters based on the elastic modulus and Poisson's ratio further quantifies the relationship between stress and magnetism. A magnetic anisotropy induction analysis is performed on the stress-sensitive parameters and the stress magnetic architecture to generate a magnetic anisotropy distribution map. This process can intuitively present the magnetic anisotropy behavior of magnetic materials under different stress conditions, providing important magnetic distribution information for the subsequent generation of magnetic configurations, making the generation of magnetic configurations more consistent with the magnetic behavior under actual stress conditions. Constructing a shape magnetic architecture based on shape characteristics can analyze the magnetism of magnetic materials from a shape perspective. Evaluating the magnetic domain structure effect of the shape magnetic architecture to obtain magnetic domain evaluation data can provide a deep understanding of the behavior of the magnetic domain structure under different shape conditions. By detecting the magnetic flux changes under different shape conditions based on the magnetic domain assessment data and constructing a magnetic domain structure model, the relationship between the magnetic domain structure and the magnetic flux is further clarified, as well as the variation of the magnetic domain structure under different shape conditions. This provides detailed information on the magnetic domain structure for the subsequent construction of the magnetic field coupling model, allowing the generation of magnetic configurations to fully consider the influence of the magnetic domain structure and better reflect the actual magnetic behavior of the magnetic material. The magnetic field coupling of the magnetic anisotropy distribution map with the magnetic domain structure model creates a magnetic field coupling model. This process organically combines stress magnetism with magnetic domain structure magnetism, allowing the generation of magnetic configurations to simultaneously consider the influence of both stress and magnetic domain structure, and more comprehensively reflect the magnetic characteristics of the magnetic material. In the magnetic field coupling model, the magnetization curves of the magnetic material under different stress and shape conditions are simulated to generate magnetic model simulation data. This allows for the prediction of the magnetic behavior of the magnetic material under various conditions, providing an important reference for the optimization of the magnetic configuration, so that the generated magnetic configuration can better meet the magnetic requirements of different application scenarios. The magnetic field coupling model is numerically verified based on the magnetic model simulation data to obtain model verification results. This process can quantitatively evaluate the accuracy of the magnetic field coupling model and ensure that the model can truly reflect the magnetic characteristics of the magnetic material. Based on the model verification results, the model structural parameters are adjusted to generate a magnetic configuration. This process can optimize the model based on the verification results, further improving the accuracy and reliability of the magnetic configuration. The resulting magnetic configuration can be better applied to the actual design and application of magnetic materials, meeting the precise requirements of different application scenarios for the magnetic material magnetic configuration.

[0011] Preferably, step S1 includes the following steps:

[0012] Step S11: collecting physical information of the magnetic material, measuring the dimensions of the physical information of the magnetic material, and determining the values ​​of the length, width, and height of the magnetic material;

[0013] Step S12: determining the shape characteristics of the magnetic material according to the values ​​of the length, width, and height of the magnetic material; and dividing the magnetic material into a plurality of stress regions based on the shape characteristics;

[0014] Step S13: In each region, different forces are applied to monitor the deformation of the magnetic material and record the deformation data; the stress value of each region is calculated based on the deformation data to obtain the stress distribution characteristics of the magnetic material;

[0015] Step S14: performing a tensile test on the magnetic material in each region, and recording the elongation under different tensile forces;

[0016] Step S15: Calculate the stress and strain of the magnetic material under different tensile forces to obtain a stress-strain curve; select a linear portion from the stress-strain curve, calculate the slope, and obtain the elastic modulus;

[0017] Step S16: In each region, a compression test is performed on the magnetic material, and the compression amount under different pressures is recorded; and the Poisson's ratio is calculated based on the compression test data.

[0018] The present invention can accurately determine the length, width and height values ​​of the magnetic material by collecting the physical information of the magnetic material and performing dimensional measurement, and then accurately determine its shape characteristics. After dividing the magnetic material into multiple stress regions based on the shape characteristics, different forces are applied to each region and the deformation is monitored. The deformation data is recorded to calculate the stress value of each region, thereby obtaining the stress distribution characteristics of the magnetic material. Furthermore, a tensile test is carried out in each region, the elongation under different tensile forces is recorded, the stress and strain are calculated and the stress-strain curve is obtained, the linear part is selected to calculate the slope to obtain the elastic modulus; at the same time, a compression test is carried out, the compression under different pressures is recorded, and the Poisson's ratio is calculated. This series of steps can systematically obtain key physical parameters such as the stress distribution, elastic modulus and Poisson's ratio of the magnetic material, providing comprehensive and accurate physical basic data for the subsequent generation of magnetic configurations, ensuring that the generation of magnetic configurations can accurately reflect the magnetic performance of the magnetic material under actual stress conditions, thereby improving the performance and reliability of the magnetic material in actual application scenarios.

[0019] Preferably, calculating the stress-sensitive parameter according to the elastic modulus and Poisson's ratio in step S2 includes:

[0020] Mark multiple measurement points on the surface of the magnetic material, each measurement point corresponds to a specific stress state;

[0021] Calculate the theoretical strain value of magnetic materials under different stress states based on elastic modulus and Poisson's ratio;

[0022] Use high-precision strain gauges to measure the actual strain value at each measuring point;

[0023] Compare and analyze the actual strain value with the theoretical strain value, calculate the ratio of stress to strain at each measuring point, and obtain the local stress sensitivity coefficient;

[0024] The weighted average of all local stress sensitivity coefficients is performed to obtain the overall stress sensitivity parameter of the magnetic material.

[0025] The present invention marks multiple measurement points on the surface of the magnetic material and corresponds to a specific stress state, which can realize the refined monitoring of the stress distribution on the surface of the magnetic material. By calculating the theoretical strain value under different stress states based on the elastic modulus and Poisson's ratio, and using a high-precision strain gauge to measure the actual strain value of each measurement point, the actual strain value is further compared and analyzed with the theoretical strain value, and the stress-strain ratio of each measurement point is calculated to obtain the local stress sensitivity coefficient. Finally, all local stress sensitivity coefficients are weighted averaged to obtain the overall stress sensitivity parameter of the magnetic material. This process can accurately quantify the stress-strain relationship of the magnetic material under different stress states, ensure the accuracy and reliability of the overall stress sensitivity parameter, and provide a key stress sensitivity quantification basis for the generation of the magnetic configuration of the magnetic material, so as to more accurately predict and regulate the magnetic performance of the magnetic material in actual application scenarios, and improve the performance stability and application adaptability of the magnetic material under complex stress conditions.

[0026] Preferably, performing magnetic anisotropy induction analysis on the stress sensitive parameters and the stress magnetic architecture in step S2 includes:

[0027] On the surface of the magnetic material, several equally spaced measurement lines are marked along its length and width, and each measurement line corresponds to a specific stress direction;

[0028] On each measuring line, the magnetic field strength is measured in turn, and the changes in the magnetic field strength at different positions are recorded to obtain the magnetic field position strength data;

[0029] Perform magnetic anisotropic parameter detection based on magnetic field position intensity data and stress sensitive parameters to generate magnetic anisotropic parameter values;

[0030] The correlation coefficient between the change of magnetic field intensity and stress direction on each measuring line is calculated based on the magnetic anisotropic parameter value;

[0031] Anisotropic induction analysis is performed on the correlation coefficient on each measurement line to obtain anisotropic correlation coefficient; anisotropic correlation coefficient is weighted to obtain anisotropic weighted coefficient;

[0032] The magnetic anisotropy distribution diagram of the magnetic material in different directions is drawn according to the anisotropy weighting coefficient.

[0033] The present invention marks equally spaced measurement lines on the surface of the magnetic material along the length and width directions and corresponds to a specific stress direction, which can fully cover the surface of the material and accurately associate the stress direction. By measuring the magnetic field intensity on each measuring line in turn and recording the changes in the magnetic field intensity at different positions, the magnetic field position intensity data is obtained, providing a basis for subsequent analysis. Magnetic anisotropic parameter detection is performed based on the magnetic field position intensity data and stress sensitive parameters, and magnetic anisotropic parameter values ​​are generated. The correlation coefficient between the magnetic field intensity change and the stress direction on each measuring line is then calculated, which can quantitatively evaluate the degree of correlation between the magnetic field intensity change and the stress direction. Anisotropic induction analysis is performed on the correlation coefficient to obtain the anisotropic correlation coefficient, and the anisotropic weighted coefficient is weighted and calculated to obtain the anisotropic weighted coefficient. Finally, the magnetic anisotropy distribution map of the magnetic material in different directions is drawn according to the anisotropic weighted coefficient. This series of steps can accurately quantify the magnetic anisotropy characteristics of magnetic materials in different directions, ensure the accuracy and reliability of the magnetic anisotropy distribution map, and provide detailed magnetic anisotropy information for the generation of magnetic configurations of magnetic materials, thereby more accurately predicting and controlling the magnetic performance of magnetic materials in actual application scenarios, and improving their magnetic properties and application adaptability under complex stress conditions.

[0034] Preferably, the step S3 of evaluating the magnetic domain structure effect of the shape magnetic architecture includes:

[0035] Using a magnetic domain imaging device to image the shaped magnetic structure, during the imaging process, external magnetic fields in different directions are applied to the shaped magnetic structure, and the responses under different magnetic field directions are identified to obtain a magnetic domain image;

[0036] Marking magnetic image features on the magnetic domain image, and calculating magnetic domain size parameters and magnetic domain distribution density of the magnetic image features;

[0037] Determine the magnetic domain wall movement speed according to the magnetic domain size parameter, and determine the magnetic domain distribution density according to the magnetic domain distribution density;

[0038] The magnetic domain structure interaction strength is evaluated based on the magnetic domain wall movement speed and magnetic domain distribution density to generate magnetic domain evaluation data.

[0039] The present invention uses a magnetic domain imaging device to image a shaped magnetic structure and applies external magnetic fields of different directions during the imaging process to identify its response. This allows the acquisition of magnetic domain images of magnetic materials under different magnetic field conditions. By labeling the magnetic domain images with magnetic image features and calculating the magnetic domain size parameters and magnetic domain distribution density, the microstructural characteristics of the magnetic domains can be quantitatively described. Furthermore, by determining the domain wall movement velocity based on the magnetic domain size parameters and the magnetic domain distribution density based on the magnetic domain distribution density, the dynamic behavior and spatial distribution of the magnetic domains under different conditions can be clarified. The interaction strength of the magnetic domain structure is assessed based on the domain wall movement velocity and magnetic domain distribution density, generating magnetic domain assessment data that comprehensively reflects the inherent interaction mechanism of the magnetic domain structure. This series of steps can systematically quantify the characteristics and interactions of the magnetic domain structure, providing accurate magnetic domain structure information for the generation of magnetic configurations of magnetic materials, ensuring that the magnetic configuration accurately reflects the influence of the magnetic domain structure on magnetism, thereby improving the magnetic performance optimization and application adaptability of magnetic materials in practical application scenarios.

[0040] Preferably, detecting the change of magnetic flux under different shape conditions according to the magnetic domain evaluation data in step S3 includes:

[0041] Under different shape conditions, multiple magnetic flux detection points are set along the length, width and thickness directions of the magnetic material according to the magnetic domain evaluation data. The distance between adjacent detection points in the length direction is 1 / 10 of the material length, in the width direction is 1 / 10 of the material width, and in the thickness direction is 1 / 10 of the material thickness;

[0042] Perform periodic magnetic flux measurement on each magnetic flux detection point, record the magnetic flux values ​​measured at each detection point in different measurement cycles, and classify and organize them according to the location of the detection point and the measurement time to form a multi-dimensional information magnetic flux matrix;

[0043] The magnetic flux variation per unit period is calculated for the data in the multi-dimensional information magnetic flux matrix to generate the magnetic flux variation characteristics, and a magnetic domain structure model is constructed based on the magnetic flux variation characteristics.

[0044] The present invention sets multiple magnetic flux detection points along the length, width, and thickness directions of the magnetic material according to magnetic domain evaluation data under different shape conditions, and the distance between adjacent detection points in each direction is 1 / 10 of the corresponding size of the material, which can fully cover the three-dimensional space of the magnetic material and ensure the uniformity and representativeness of the magnetic flux detection. Periodic magnetic flux measurement is performed on each magnetic flux detection point, and the measured values ​​are classified and sorted according to the detection point position and measurement time to form a multi-dimensional information magnetic flux matrix, which can systematically record and organize the spatiotemporal variation data of the magnetic flux. By calculating the unit cycle magnetic flux change of the data in the multi-dimensional information magnetic flux matrix, the magnetic flux change characteristics are generated, and a magnetic domain structure model is constructed based on this characteristic. It can accurately reflect the dynamic magnetic flux change law of the magnetic domain structure under different shape conditions, and provide detailed information on the relationship between magnetic flux change and magnetic domain structure for the generation of magnetic configuration of magnetic materials, thereby more accurately predicting the magnetic performance of magnetic materials in actual application scenarios and improving their magnetic design and application adaptability under complex shape conditions.

[0045] Preferably, performing magnetic field coupling on the magnetic anisotropy distribution map and the magnetic domain structure model in step S4 includes:

[0046] Discretize the magnetic field intensity data in the magnetic anisotropy distribution map and divide the space of the magnetic material into multiple uniform grid cells, each grid cell corresponding to a magnetic field intensity value;

[0047] Numbering each magnetic domain unit in the magnetic domain structure model, and determining the grid area corresponding to the magnetic domain unit in the discretized magnetic anisotropy distribution map according to the geometric position and shape of the magnetic domain unit;

[0048] According to the magnetization direction and strength of the magnetic domain unit, combined with its corresponding magnetic field strength value, the angle between the magnetization direction of the magnetic domain unit and the external magnetic field direction is calculated, thereby obtaining the interaction energy of each magnetic domain unit;

[0049] For each magnetic domain unit inside the magnetic material, the magnetic moment interaction energy between it and the adjacent magnetic domain unit is calculated, and the interaction energy between the magnetic domain units is recorded;

[0050] The external magnetic field interaction energy of all magnetic domain units and the magnetic moment interaction energy between adjacent magnetic domain units are magnetically coupled to obtain a magnetic field coupling model.

[0051] The present invention discretizes the magnetic field intensity data in the magnetic anisotropy distribution map, divides the magnetic material space into multiple uniform grid units, and assigns a magnetic field intensity value to each unit, enabling accurate quantification and spatial positioning of the magnetic field distribution. Simultaneously, each magnetic domain unit in the magnetic domain structure model is numbered, and its corresponding grid area in the discretized magnetic anisotropy distribution map is determined based on its geometric position and shape, ensuring an accurate association between the magnetic domain unit and the magnetic field intensity value. By calculating the angle between the magnetization direction of the magnetic domain unit and the direction of the external magnetic field, the external magnetic field interaction energy of each magnetic domain unit is obtained. Combined with the magnetic moment interaction energy between the domain unit and the adjacent domain units, the energy state of the domain unit under the interaction of the external magnetic field and the internal magnetic moment can be comprehensively evaluated. Ultimately, the external magnetic field interaction energy and magnetic moment interaction energy of all domain units are magnetically coupled to obtain a magnetic field coupling model. This model accurately reflects the magnetic interaction mechanism within the magnetic material, providing comprehensive and accurate magnetic field coupling information for the generation of magnetic configurations. This model allows for more accurate prediction of the magnetic performance of magnetic materials in practical application scenarios, improving their performance optimization and application adaptability under complex magnetic field conditions.

[0052] Preferably, in step S4, in the magnetic field coupling model, simulating the magnetization curve of the magnetic material under different stress and shape conditions includes:

[0053] In the magnetic field coupling model, stress conditions are set, including tensile stress, compressive stress, and shear stress, and multiple stress levels are set for each stress condition. Among them, the tensile stress is set at a stress level of 10 MPa from 0 to 100 MPa, the compressive stress is set at a stress level of 10 MPa from 0 to -100 MPa, and the shear stress is set at a stress level of 5 MPa from 0 to 50 MPa.

[0054] In the magnetic field coupling model, shape conditions are set, including cylindrical, rectangular, and irregular shapes. Multiple size parameters are set for each shape condition. The diameter of the cylinder ranges from 1 mm to 10 mm, with a size parameter set every 1 mm. The length, width, and height of the rectangular shape range from 1 mm to 10 mm, with a size parameter set every 1 mm.

[0055] Under the set stress and shape conditions, the magnetization curve of the magnetic material is simulated. By gradually increasing the external magnetic field strength from 0 to 1T, the magnetization intensity is recorded every 0.1T to obtain the magnetization curve under different stress and shape conditions. The magnetization curve uses the magnetic field strength as the horizontal axis and the magnetization intensity as the vertical axis;

[0056] The simulated magnetization curve data is analyzed, and the characteristic parameters of the magnetization curve under each stress and shape condition are calculated, including the residual magnetization intensity, coercive force and maximum magnetic energy product, to obtain the magnetic model simulation data.

[0057] In the magnetic field coupling model of the present invention, by setting multiple stress levels of tensile stress, compressive stress and shear stress, as well as multiple size parameters of cylindrical, rectangular and irregular shapes, it is possible to comprehensively cover the complex stress and shape conditions encountered by magnetic materials in practical applications. Under the set stress and shape conditions, the magnetization curve of the magnetic material is simulated, and the magnetization curves under different conditions are obtained by gradually increasing the external magnetic field intensity and recording the magnetization intensity. The magnetization curve data is further analyzed, and characteristic parameters such as residual magnetization intensity, coercive force and maximum magnetic energy product are calculated to obtain magnetic model simulation data. This process can systematically quantify the magnetization characteristics of magnetic materials under different stress and shape conditions, and provide detailed magnetic performance data for the generation of magnetic configurations, so as to more accurately predict the magnetic performance of magnetic materials in actual application scenarios, and improve their performance optimization and application adaptability under complex working conditions.

[0058] This specification also provides a system for generating a magnetic configuration of a magnetic material, which is used to execute the method for generating a magnetic configuration of a magnetic material as described above. The system for generating a magnetic configuration of a magnetic material includes:

[0059] The magnetic material information acquisition module is used to collect physical information of the magnetic material and extract the shape characteristics of the physical information of the magnetic material; determine the stress distribution characteristics of the magnetic material based on the shape characteristics; and collect the elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material;

[0060] The magnetic anisotropy induction analysis module is used to construct a stress magnetic structure based on stress distribution characteristics; calculate stress sensitive parameters based on elastic modulus and Poisson's ratio; and perform magnetic anisotropy induction analysis on the stress sensitive parameters and stress magnetic structure to generate a magnetic anisotropy distribution map.

[0061] A magnetic domain evaluation module is used to construct a shaped magnetic architecture based on shape features; evaluate the magnetic domain structure effect of the shaped magnetic architecture to obtain magnetic domain evaluation data; detect magnetic flux changes under different shape conditions based on the magnetic domain evaluation data, and construct a magnetic domain structure model;

[0062] The magnetization curve simulation module is used to perform magnetic field coupling between the magnetic anisotropy distribution map and the magnetic domain structure model to obtain a magnetic field coupling model. In the magnetic field coupling model, the magnetization curve of the magnetic material under different stress and shape conditions is simulated to generate magnetic model simulation data.

[0063] The magnetic configuration generation module is used to numerically verify the magnetic field coupling model based on the magnetic model simulation data to obtain the model verification results; adjust the model structure parameters according to the model verification results to generate the magnetic configuration.

[0064] The magnetic material magnetic configuration generation system of the present invention accurately collects the physical information of the magnetic material through the magnetic material information acquisition module, extracts the shape characteristics and determines the stress distribution characteristics, and simultaneously collects the corresponding elastic modulus and Poisson's ratio to provide basic data for subsequent analysis. The magnetic anisotropy induction analysis module constructs a stress magnetic architecture based on the stress distribution characteristics, calculates the stress sensitive parameters, and generates a magnetic anisotropy distribution map, realizing the correlation analysis between stress and magnetism. The magnetic domain evaluation module constructs a shape magnetic architecture, evaluates the effect of the magnetic domain structure, constructs a magnetic domain structure model, and further refines the microscopic magnetic characteristics of the magnetic material. The magnetization curve simulation module couples the magnetic anisotropy distribution map with the magnetic domain structure model through the magnetic field, simulates the magnetization curve under different stress and shape conditions, generates magnetic model simulation data, and provides a quantitative basis for the generation of the magnetic configuration. The magnetic configuration generation module numerically verifies the model and adjusts the parameters according to the simulation data, and finally generates the magnetic configuration. The entire system realizes full-process automation and refined processing from physical information collection to magnetic configuration generation. It can efficiently and accurately generate the magnetic configuration of magnetic materials, meet the magnetic design requirements under complex stress and shape conditions, and improve the performance and reliability of magnetic materials in practical applications.

[0065] A computer-readable medium stores a computer program, which implements the above-mentioned method for generating the magnetic configuration of a magnetic material when the computer program is executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic flow chart of steps for a method for generating a magnetic configuration of a magnetic material;

[0067] Figure 2 for Figure 1 Detailed implementation steps of step S1 in FIG.

[0068] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0069] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. It is obvious that the embodiments described are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts are within the scope of protection of the present invention.

[0070] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor and / or microcontroller approaches.

[0071] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0072] To achieve this, please refer to Figures 1 to 2 , a method for generating a magnetic configuration of a magnetic material, the method comprising the following steps:

[0073] Step S1: collecting physical information of the magnetic material and extracting shape characteristics of the physical information of the magnetic material; determining stress distribution characteristics of the magnetic material based on the shape characteristics; collecting elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material;

[0074] Step S2: constructing a stress magnetic structure based on the stress distribution characteristics; calculating stress sensitive parameters according to the elastic modulus and Poisson's ratio; performing magnetic anisotropy induction analysis on the stress sensitive parameters and the stress magnetic structure to generate a magnetic anisotropy distribution map;

[0075] Step S3: constructing a shape magnetic architecture based on the shape characteristics; evaluating the magnetic domain structure effect of the shape magnetic architecture to obtain magnetic domain evaluation data; detecting the magnetic flux change under different shape conditions based on the magnetic domain evaluation data, and constructing a magnetic domain structure model;

[0076] Step S4: performing magnetic field coupling on the magnetic anisotropy distribution map and the magnetic domain structure model to obtain a magnetic field coupling model; in the magnetic field coupling model, performing magnetization curve simulation on the magnetic material under different stress and shape conditions to generate magnetic model simulation data;

[0077] Step S5: numerically verify the magnetic field coupling model according to the magnetic model simulation data to obtain a model verification result; adjust the model structure parameters according to the model verification result to generate a magnetic configuration.

[0078] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a flow chart of a method for generating a magnetic configuration of a magnetic material according to the present invention. In this example, the method for generating a magnetic configuration of a magnetic material includes the following steps:

[0079] Step S1: collecting physical information of the magnetic material and extracting shape characteristics of the physical information of the magnetic material; determining stress distribution characteristics of the magnetic material based on the shape characteristics; collecting elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material;

[0080] In an embodiment of the present invention, a three-dimensional laser scanner is first used to perform non-contact physical information collection on a magnetic material sample. The magnetic material sample is placed on the scanner's work platform, and the scanner's focal length and scanning angle are adjusted to ensure that the scanning range completely covers the sample surface. The scanner's laser emission frequency is set to 1000 Hz, with a scanning accuracy of 0.01 mm. Point cloud data of the sample surface is acquired through the principle of laser reflection, which contains information about the sample's shape characteristics. Subsequently, the acquired point cloud data is imported into computer-aided design (CAD) software, and the software's geometric analysis module is used to process the point cloud data to extract the sample's shape characteristic parameters, including the sample's length L, width W, and height H, as well as the surface curvature radius R. Based on the extracted shape characteristic parameters, a geometric model of the magnetic material is established in conjunction with finite element analysis software, and the corresponding boundary conditions and loads are applied. During the simulation process, the meshing accuracy is set to 0.5 mm, and linear units are used for meshing. By solving the static equations, the stress distribution characteristics within the magnetic material are calculated, specifically expressed as a stress distribution diagram, where the stress values ​​are represented by a color gradient, with red areas representing high stress areas and blue areas representing low stress areas. At the same time, tensile tests were performed on magnetic material samples using material testing equipment to measure their elastic modulus E and Poisson's ratio ν. The samples were clamped in the upper and lower clamps of a universal material testing machine, and the loading rate of the testing machine was set to 1 mm / min. The stress-strain curve of the sample during the tensile process was recorded. The elastic modulus E was calculated from the slope of the curve and its value was 210 GPa. By analyzing the deformation characteristics of the curve, the Poisson's ratio ν was calculated and its value was 0.3. Finally, the collected elastic modulus E and Poisson's ratio ν were correlated with the shape characteristics and stress distribution characteristics of the magnetic material.

[0081] Step S2: constructing a stress magnetic structure based on the stress distribution characteristics; calculating stress sensitive parameters according to the elastic modulus and Poisson's ratio; performing magnetic anisotropy induction analysis on the stress sensitive parameters and the stress magnetic structure to generate a magnetic anisotropy distribution map;

[0082] In an embodiment of the present invention, first, based on the stress distribution characteristics of the magnetic material obtained in step S1, a stress magnetic architecture is constructed using the magnetic field module in the finite element analysis software. The stress distribution map is imported into the software, and the distribution density of the magnetic field unit is set to match the stress gradient according to the stress distribution, that is, the density of the magnetic field unit is increased to 10 units per square millimeter in the high stress area, and is set to 5 units per square millimeter in the low stress area. Subsequently, the stress sensitive parameter is calculated using the material mechanics formula based on the elastic modulus E and Poisson's ratio ν of the magnetic material collected in step S1. The specific calculation formula is: stress sensitive parameter α = (E×ν) / (1-ν 2 ), substituting E = 210 GPa and ν = 0.3, the stress sensitive parameter α = 84 GPa is calculated. Then, the calculated stress sensitive parameter α is used in conjunction with the stress magnetic structure for magnetic anisotropy induction analysis. The magnetic anisotropy analysis module is set up in the finite element analysis software, the stress sensitive parameter α is input, and the magnetic field unit distribution of the stress magnetic structure is combined to calculate the magnetic anisotropy distribution through numerical simulation. During the simulation, the magnetic field iteration accuracy is set to 1×10 -4 T, the number of iterations is capped at 1000 to ensure the accuracy of the calculation results. Finally, a magnetic anisotropy distribution map is generated, in which different colors represent the magnitude and direction of magnetic anisotropy. Red areas represent areas with strong magnetic anisotropy, and blue areas represent areas with weak magnetic anisotropy. The direction of the arrow indicates the direction of magnetic anisotropy.

[0083] Step S3: constructing a shape magnetic architecture based on the shape characteristics; evaluating the magnetic domain structure effect of the shape magnetic architecture to obtain magnetic domain evaluation data; detecting the magnetic flux change under different shape conditions based on the magnetic domain evaluation data, and constructing a magnetic domain structure model;

[0084] In this embodiment of the present invention, in step S3, a shaped magnetic structure is first constructed using computer-aided design (CAD) software based on the shape features of the magnetic material extracted in step S1. Based on the shape feature parameters of the magnetic material, such as length L, width W, height H, and surface curvature radius R, a three-dimensional model is precisely drawn that matches the magnetic material's geometric shape. This model is then divided into multiple tiny volume units, each measuring 0.1 mm × 0.1 mm × 0.1 mm, to ensure accurate description of the shape features. Subsequently, a magnetic domain structure analysis instrument is used to evaluate the magnetic domain structure effects of the shaped magnetic structure. The constructed shaped magnetic structure model is imported into the magnetic domain structure analysis software, with the magnetic field intensity scan range set to 0 to 1 T with a step size of 0.01 T, and the temperature set to room temperature (25°C). The software simulates the evolution of magnetic domains under different applied magnetic fields, recording the magnetization direction and domain wall position of each volume unit to obtain magnetic domain evaluation data, including domain size, domain wall density, and domain orientation distribution. Based on the magnetic domain evaluation data, a gauss meter and a Hall effect sensor are used to detect changes in magnetic flux under different shape conditions. A magnetic material sample was placed in the measurement area of ​​a Gaussmeter, with a measurement accuracy of 1 mT. Hall-effect sensors were placed at various locations around the sample to measure the magnetic flux distribution in different directions. By varying the sample's shape characteristics (such as length L, width W, and height H), the magnetic flux variation under different shape conditions was measured and the data recorded. Finally, based on the magnetic flux variation data, a magnetic domain structure model was constructed using magnetic domain structure analysis software. The magnetic flux variation data was imported into the software and combined with the magnetic domain assessment data. Numerical fitting and inversion algorithms were used to determine the magnetic domain structure parameters, including the shape, size, orientation, and distribution of the domain walls. Through iterative optimization, the constructed magnetic domain structure model accurately reflects the magnetic domain distribution characteristics of the magnetic material under different shape conditions, thus completing the construction of the magnetic domain structure model.

[0085] Step S4: performing magnetic field coupling on the magnetic anisotropy distribution map and the magnetic domain structure model to obtain a magnetic field coupling model; in the magnetic field coupling model, performing magnetization curve simulation on the magnetic material under different stress and shape conditions to generate magnetic model simulation data;

[0086] In an embodiment of the present invention, the magnetic anisotropy distribution map generated in step S2 is magnetically coupled with the magnetic domain structure model constructed in step S3. The specific operation is: the magnetic anisotropy parameters (including the magnetic anisotropy constant Ku and the magnetic anisotropy direction vector) of each unit in the magnetic anisotropy distribution map are imported into the corresponding position of the magnetic domain structure model. In the finite element analysis software, the grid accuracy of the coupling calculation is set to 0.05mm to ensure the accurate coupling of the magnetic field. The magnetic field distribution of the coupled model is calculated by the magnetic field solver of the software to generate a magnetic field coupling model. During the calculation process, the magnetic field iteration accuracy is set to 1×10 -6 T, the upper limit of the number of iterations is 2000 times to ensure the convergence and accuracy of the calculation results. In the magnetic field coupling model, the magnetization curve of the magnetic material under different stress and shape conditions is simulated. The specific operation is: first set the stress condition, by applying uniform axial stress and radial stress in the finite element model, the stress range is from 0 to 100MPa, and the step length is 10MPa. For the shape condition, by adjusting the geometric parameters of the model, set the length L from 10mm to 50mm, with a step length of 5mm; the width W from 5mm to 20mm, with a step length of 3mm; the height H from 2mm to 10mm, with a step length of 2mm. During the simulation process, the external magnetic field intensity range is set to 0 to 1T, with a step length of 0.01T, and the temperature is maintained at room temperature 25°C. Through the magnetization curve simulation module of the finite element analysis software, the relationship between the magnetization intensity of the magnetic material and the external magnetic field under different stress and shape conditions is calculated to obtain the magnetization curve. Record the magnetization curve data under each condition, including parameters such as magnetization intensity M, coercive force Hc, and remanent magnetization Mr, to generate magnetic model simulation data. During the data recording process, set the data sampling frequency to 100 Hz.

[0087] Step S5: numerically verifying the magnetic field coupling model according to the magnetic model simulation data to obtain a model verification result; adjusting the model structure parameters according to the model verification result to generate a magnetic configuration.

[0088] In an embodiment of the present invention, the magnetic field coupling model is verified by using numerical verification technology, and the magnetic model simulation data generated in step S4 is imported into the numerical verification software, and the accuracy of the verification parameters is set to 0.001T, which is used to evaluate the accuracy of the magnetization curve. By comparing the parameters such as the magnetization intensity M, coercive force Hc and residual magnetization Mr in the simulation data with the experimental data or known standard data, the error percentage is calculated. If the error percentage exceeds the set threshold of 5%, it is determined that the model needs to be adjusted. Adjust the model structure parameters according to the model verification results. If the error mainly comes from the magnetic domain structure model, adjust the magnetic domain size and magnetic domain wall density parameters, set the magnetic domain size adjustment range to from 10nm to 50nm, with a step size of 5nm; set the magnetic domain wall density adjustment range to from 10 5 / m2 to 10 6 / m 2 , with a step size of 10 4 / m 2 If the error mainly comes from the magnetic anisotropy distribution diagram, adjust the value of the magnetic anisotropy constant Ku, and the adjustment range is from 1×10 5 J / m 3 to 5×10 5 J / m 3 , with a step size of 1×10 4 J / m 3 , and at the same time adjust the angle of the magnetic anisotropy direction vector from 0° to 360° with a step size of 10°. After completing the parameter adjustment, rerun the magnetization curve simulation and perform numerical verification again until the error percentage drops below 5%. Finally, generate the magnetic configuration based on the verified model structure parameters. The adjusted magnetic field coupling model is exported as a magnetic configuration file, which contains information such as the shape characteristics of the magnetic material, magnetic domain structure distribution, magnetic anisotropy parameters, and magnetization curve, which will be used for subsequent magnetic material design and application development.

[0089] As an example of the present invention, refer to Figure 2 As shown, in this example, step S1 includes:

[0090] Step S11: collecting physical information of the magnetic material, measuring the dimensions of the physical information of the magnetic material, and determining the values ​​of the length, width, and height of the magnetic material;

[0091] Step S12: determining the shape characteristics of the magnetic material according to the values ​​of the length, width, and height of the magnetic material; and dividing the magnetic material into a plurality of stress regions based on the shape characteristics;

[0092] Step S13: In each region, different forces are applied to monitor the deformation of the magnetic material and record the deformation data; the stress value of each region is calculated based on the deformation data to obtain the stress distribution characteristics of the magnetic material;

[0093] Step S14: performing a tensile test on the magnetic material in each region, and recording the elongation under different tensile forces;

[0094] Step S15: Calculate the stress and strain of the magnetic material under different tensile forces to obtain a stress-strain curve; select a linear portion from the stress-strain curve, calculate the slope, and obtain the elastic modulus;

[0095] Step S16: In each region, a compression test is performed on the magnetic material, and the compression amount under different pressures is recorded; and the Poisson's ratio is calculated based on the compression test data.

[0096] In an embodiment of the present invention, when implementing step S11, a high-precision three-dimensional coordinate measuring instrument is used to collect physical information of the magnetic material sample. The sample is placed on the workbench of the measuring instrument, and the length L, width W and height H of the magnetic material are measured by combining an optical probe and a contact probe. The measurement accuracy is set to 0.001mm, and the measurement range covers the entire sample surface. After the measurement is completed, the length L of the magnetic material is recorded as 50.000mm, the width W is 20.000mm, and the height H is 5.000mm. Entering step S12, the shape characteristics of the magnetic material are determined using image processing software based on the measured values ​​of the length L, width W and height H. The values ​​of the length L, width W and height H are input into the software, and the magnetic material is determined to be a rectangular parallelepiped through a preset shape determination algorithm. Based on the rectangular parallelepiped shape characteristics, the magnetic material is divided into multiple stress regions, specifically into four regions, namely region 1, region 2, region 3 and region 4. Region 1 is located in the upper left corner of the sample, region 2 is located in the upper right corner, region 3 is located in the lower left corner, and region 4 is located in the lower right corner. In step S13, a universal material testing machine is used to apply different forces to the magnetic material for each stress region. A tensile force of 100N is applied to region 1, a tensile force of 150N is applied to region 2, a tensile force of 200N is applied to region 3, and a tensile force of 250N is applied to region 4. At the same time, a strain gauge sensor is used to monitor the deformation of the magnetic material. The strain gauge has a measurement accuracy of 0.01% and a sampling frequency of 10Hz. The deformation data of each region under different tensile forces is recorded, including elongation and lateral deformation. Based on the deformation data, the stress value of each region is calculated using Hooke's law to obtain the stress distribution characteristics of the magnetic material. The stress value of region 1 is 20MPa, the stress value of region 2 is 30MPa, the stress value of region 3 is 40MPa, and the stress value of region 4 is 50MPa. Proceed to step S14 to perform a tensile test on the magnetic material in each stress region. Using an electronic universal material testing machine, set the tensile rate to 2mm / min, apply different tensile forces to area 1, area 2, area 3 and area 4 respectively, and record the elongation under different tensile forces. The tensile force starts from 0 and gradually increases to 500N, and the elongation is recorded every time it increases by 50N. In step S15, the stress and strain of the magnetic material under different tensile forces are calculated based on the tensile force and elongation data recorded in step S14. The stress calculation formula is stress σ = F / A, where F is the tensile force and A is the cross-sectional area of ​​the magnetic material; the strain calculation formula is strain ε = ΔL / L0, where ΔL is the elongation and L0 is the initial length of the magnetic material. The calculated stress and strain data are plotted as a stress-strain curve. The linear part is selected from the stress-strain curve, and the slope is calculated by linear fitting to obtain the elastic modulus E. The calculated result is elastic modulus E = 210GPa. Finally, in step S16, a compression test is performed on the magnetic material in each stress area.Using an electronic universal testing machine, set the compression rate to 1 mm / min, different pressures were applied to Areas 1, 2, 3, and 4, and the compression at each pressure was recorded. The pressure was increased from 0 to 300 N, with the compression recorded every 30 N increase. Based on the compression test data, the Poisson's ratio (ν) was calculated using the formula ν = -εt / εl, where εt is the transverse strain and εl is the longitudinal strain. The calculated Poisson's ratio (ν) was 0.3.

[0097] Preferably, calculating the stress-sensitive parameter according to the elastic modulus and Poisson's ratio in step S2 includes:

[0098] Mark multiple measurement points on the surface of the magnetic material, each measurement point corresponds to a specific stress state;

[0099] Calculate the theoretical strain value of magnetic materials under different stress states based on elastic modulus and Poisson's ratio;

[0100] Use high-precision strain gauges to measure the actual strain value at each measuring point;

[0101] Compare and analyze the actual strain value with the theoretical strain value, calculate the ratio of stress to strain at each measuring point, and obtain the local stress sensitivity coefficient;

[0102] The weighted average of all local stress sensitivity coefficients is performed to obtain the overall stress sensitivity parameter of the magnetic material.

[0103] In an embodiment of the present invention, first, a laser marking machine is used to mark multiple measurement points on the surface of the magnetic material, and each measurement point corresponds to a specific stress state. The measurement points are distributed in a grid pattern with a spacing of 5mm×5mm, covering the entire surface of the magnetic material. The position coordinates of each measurement point are recorded using a coordinate measurement system to ensure the accuracy of subsequent measurements. According to the elastic modulus E=210GPa obtained in step S15 and the Poisson's ratio ν=0.3 obtained in step S16, the theoretical strain value of the magnetic material under different stress states is calculated. For each measurement point, the theoretical strain value is calculated using Hooke's law formula according to its corresponding stress state. Assuming that the stress at measurement point 1 is σ1=30MPa, its theoretical strain value ε_theory1=σ1 / E=(30×10 6 ) / (210×10 9 )=1.43×10 -4 Use a high-precision strain gauge to measure the actual strain value at each measuring point. Paste the strain gauge of the strain gauge on each measuring point to ensure that the strain gauge fits tightly against the surface of the magnetic material. The measurement accuracy of the strain gauge is 0.1με and the sampling frequency is 1Hz. After the measurement is completed, record the actual strain value of each measuring point. For example, the actual strain value of measuring point 1 is ε_actual1=1.45×10-4 The actual strain value is compared with the theoretical strain value. For each measurement point, the difference between the actual strain value and the theoretical strain value is calculated. Taking measurement point 1 as an example, Δε1=ε_actual1-ε_theory1=1.45×10 -4 -1.43×10 -4 =2×10 -6 Next, calculate the ratio of stress to strain at each measurement point, i.e., the local stress sensitivity coefficient. The calculation formula for the local stress sensitivity coefficient is: k_local=σ / Δε. For measurement point 1, k_local1=σ1 / Δε1=(30×10 6 ) / (2×10 -6 )=1.5×10 10 . The weighted average of the local stress sensitivity coefficients of all measurement points is performed to obtain the overall stress sensitivity parameter of the magnetic material. Assume that there are 100 measurement points in total, and the local stress sensitivity coefficients of each measurement point are k_local1, k_local2, ..., k_local100. According to the stress magnitude of each measurement point, a corresponding weight is assigned. The greater the stress, the greater the weight. The weight calculation formula is: w_i = σ_i / Σσ, where w_i is the weight of the i-th measurement point, σ_i is the stress of the i-th measurement point, and Σσ is the sum of the stresses of all measurement points. The overall stress sensitivity parameter calculation formula is: k_total = Σ(k_locali × w_i). The overall stress sensitivity parameter k_total of the magnetic material is obtained by calculation.

[0104] Preferably, performing magnetic anisotropy induction analysis on the stress sensitive parameters and the stress magnetic architecture in step S2 includes:

[0105] On the surface of the magnetic material, several equally spaced measurement lines are marked along its length and width, and each measurement line corresponds to a specific stress direction;

[0106] On each measuring line, the magnetic field strength is measured in turn, and the changes in the magnetic field strength at different positions are recorded to obtain the magnetic field position strength data;

[0107] Perform magnetic anisotropic parameter detection based on magnetic field position intensity data and stress sensitive parameters to generate magnetic anisotropic parameter values;

[0108] The correlation coefficient between the change of magnetic field intensity and stress direction on each measuring line is calculated based on the magnetic anisotropic parameter value;

[0109] Anisotropic induction analysis is performed on the correlation coefficient on each measurement line to obtain anisotropic correlation coefficient; anisotropic correlation coefficient is weighted to obtain anisotropic weighted coefficient;

[0110] The magnetic anisotropy distribution diagram of the magnetic material in different directions is drawn according to the anisotropy weighting coefficient.

[0111] In an embodiment of the present invention, a laser scriber is used to mark several equally spaced measurement lines along the length and width of the magnetic material surface. The measurement line spacing is set to 1 mm, with 10 measurement lines marked along the length and 5 measurement lines marked along the width. Each measurement line corresponds to a specific stress direction. A high-precision magnetic field intensity meter with a measurement accuracy of 0.1 mT and a range of 0 to 1 T is used to measure the magnetic field intensity along each measurement line. The changes in magnetic field intensity at different locations are recorded to obtain magnetic field position intensity data, with a data recording frequency of 10 Hz. Based on the magnetic field position intensity data and the stress sensitivity parameter obtained in step S1, magnetic anisotropy parameter detection is performed using a magnetic anisotropy detection system. The magnetic field position intensity data is input into the detection system and, combined with the stress sensitivity parameter α = 84 GPa (calculated in step S2), the magnetic anisotropy parameter value for each measurement line is generated using the system's built-in magnetic anisotropy calculation algorithm. The magnetic anisotropy parameter value includes the magnetic anisotropy constant Ku and the magnetic anisotropy direction vector θ. Based on the magnetic anisotropic parameter values, the correlation coefficient between the magnetic field intensity variation and the stress direction was calculated for each measurement line. Using correlation analysis software, a linear fit was performed between the magnetic field intensity variation data and the stress direction data to calculate the correlation coefficient R. The correlation coefficient R ranges from -1 to 1, with R = 1 indicating a perfect positive correlation and R = -1 indicating a perfect negative correlation. For the first measurement line along the length, the calculated correlation coefficient R1 = 0.95, indicating a high correlation between the magnetic field intensity variation and the stress direction. Anisotropy-induced analysis was performed on the correlation coefficients for each measurement line. Using anisotropy analysis software, the correlation coefficients R for all measurement lines were comprehensively analyzed to obtain the anisotropic correlation coefficient R_aniso. The anisotropic correlation coefficient R_aniso was calculated by weighted averaging, with weights assigned based on the importance of the measurement line location and stress direction. The weight for the measurement lines along the length was 0.6, and the weight for the measurement lines along the width was 0.4. The calculated anisotropic correlation coefficient R_aniso = 0.92. The anisotropy correlation coefficient R_aniso is weighted to obtain the anisotropy weighting coefficient K_aniso. The weighting calculation formula is K_aniso = R_aniso × α, where α is the stress sensitivity parameter. The calculated anisotropy weighting coefficient K_aniso = 0.92 × 84 GPa = 77.28 GPa. Based on the anisotropy weighting coefficient K_aniso, a magnetic anisotropy distribution diagram of the magnetic material in different directions is plotted using mapping software. In the distribution diagram, the intensity of the magnetic anisotropy is represented by color, with darker colors indicating stronger magnetic anisotropy. The magnetic anisotropy intensity in the longitudinal direction is higher, resulting in darker colors; the magnetic anisotropy intensity in the width direction is lower, resulting in lighter colors. This distribution diagram can intuitively demonstrate the magnetic anisotropy characteristics of the magnetic material in different directions.

[0112] Preferably, the step S3 of evaluating the magnetic domain structure effect of the shape magnetic architecture includes:

[0113] Using a magnetic domain imaging device to image the shaped magnetic structure, during the imaging process, external magnetic fields in different directions are applied to the shaped magnetic structure, and the responses under different magnetic field directions are identified to obtain a magnetic domain image;

[0114] Marking magnetic image features on the magnetic domain image, and calculating magnetic domain size parameters and magnetic domain distribution density of the magnetic image features;

[0115] Determine the magnetic domain wall movement speed according to the magnetic domain size parameter, and determine the magnetic domain distribution density according to the magnetic domain distribution density;

[0116] The magnetic domain structure interaction strength is evaluated based on the magnetic domain wall movement speed and magnetic domain distribution density to generate magnetic domain evaluation data.

[0117] In an embodiment of the present invention, a shaped magnetic structure is first imaged using a magnetic domain imaging device. This device utilizes magneto-optical Kerr effect (MOKE) imaging technology, enabling high-resolution imaging of the magnetic domain structure of magnetic materials. During imaging, the shaped magnetic structure is placed on the imaging device's sample stage, ensuring that the sample surface is parallel to the imaging plane. The imaging device's magnetic field generator is capable of applying an external magnetic field in different directions, with a magnetic field strength ranging from 0 to 1 T and a uniform distribution of magnetic field directions from 0° to 360° in 15° increments. Under each magnetic field direction, the imaging device captures a magnetic domain image with an exposure time of 10 ms, an image resolution of 1024 × 1024 pixels, and a pixel size of 0.1 μm × 0.1 μm. Magnetic image features are marked on the captured magnetic domain images. Image processing software is used to analyze the magnetic domain images to identify the boundaries of magnetic domains and the locations of magnetic domain walls. The software processes the magnetic domain images using edge detection algorithms, such as the Canny edge detection algorithm, to mark the outlines of the magnetic domains. Simultaneously, magnetic domain size parameters and domain distribution density, characteristic of the magnetic image, are calculated. The magnetic domain size parameter is obtained by measuring the area of ​​the magnetic domain, and the unit is square micrometer (μm 2 The magnetic domain distribution density is obtained by counting the number of magnetic domains per unit area, and the unit is / μm 2 For example, under a certain magnetic field direction, the average size of the magnetic domain measured is 10μm. 2 , the magnetic domain distribution density is 0.05 / μm 2 The domain wall movement speed is determined based on the domain size parameters. The domain wall movement speed is related to the rate of change of the domain size. By collecting domain images at different time points, the rate of change of the domain size is calculated. Assume that within the time interval Δt = 1s, the domain size changes from 10μm to 2 Change to 12μm 2The domain wall movement velocity v can be calculated by the following formula: v = (ΔA / Δt) / L, where ΔA is the change in the magnetic domain area and L is the length of the domain wall. If the domain wall length is 5μm, then the domain wall movement velocity v = (2μm 2 / 1s) / 5μm=0.4μm / s. The uniformity of the magnetic domain distribution density is determined based on the magnetic domain distribution density. The uniformity of the magnetic domain distribution is evaluated by calculating the standard deviation of the magnetic domain distribution density. The smaller the standard deviation, the more uniform the magnetic domain distribution. For example, the standard deviation of the magnetic domain distribution density under a certain magnetic field direction is 0.01 / μm 2 , indicating that the magnetic domain distribution is relatively uniform. The magnetic domain structure interaction strength is evaluated based on the magnetic domain wall movement speed and magnetic domain distribution density. Using the magnetic domain interaction analysis software, the magnetic domain wall movement speed and magnetic domain distribution density data are input. The software calculates the magnetic domain structure interaction strength by simulating the interaction force between the magnetic domain walls. The interaction strength evaluation results are expressed as a dimensionless interaction coefficient ranging from 0 to 1. The closer the interaction coefficient is to 1, the stronger the interaction between the magnetic domain structures. For example, the calculated interaction coefficient is 0.8, indicating that there is a strong interaction between the magnetic domain structures. Finally, the magnetic domain wall movement speed, magnetic domain distribution density and magnetic domain structure interaction strength evaluation results are integrated into magnetic domain evaluation data for subsequent magnetic material property analysis.

[0118] Preferably, detecting the change of magnetic flux under different shape conditions according to the magnetic domain evaluation data in step S3 includes:

[0119] Under different shape conditions, multiple magnetic flux detection points are set along the length, width and thickness directions of the magnetic material according to the magnetic domain evaluation data. The distance between adjacent detection points in the length direction is 1 / 10 of the material length, in the width direction is 1 / 10 of the material width, and in the thickness direction is 1 / 10 of the material thickness;

[0120] Perform periodic magnetic flux measurement on each magnetic flux detection point, record the magnetic flux values ​​measured at each detection point in different measurement cycles, and classify and organize them according to the location of the detection point and the measurement time to form a multi-dimensional information magnetic flux matrix;

[0121] The magnetic flux variation per unit period is calculated for the data in the multi-dimensional information magnetic flux matrix to generate the magnetic flux variation characteristics, and a magnetic domain structure model is constructed based on the magnetic flux variation characteristics.

[0122] In an embodiment of the present invention, multiple magnetic flux detection points are set along the length, width, and thickness directions of the magnetic material based on magnetic domain evaluation data under different shape conditions. For a magnetic material with a length of L, the spacing between adjacent detection points in the length direction is set to L / 10; for a magnetic material with a width of W, the spacing between adjacent detection points in the width direction is set to W / 10; and for a magnetic material with a thickness of H, the spacing between adjacent detection points in the thickness direction is set to H / 10. For example, when the length L of the magnetic material is 50 mm, the width W is 20 mm, and the thickness H is 5 mm, the spacing between adjacent detection points in the length direction is 5 mm, in the width direction is 2 mm, and in the thickness direction is 0.5 mm. A high-precision magnetic flux sensor is used to periodically measure the magnetic flux at each magnetic flux detection point. The sensor has a measurement accuracy of 1 μWb and a sampling frequency of 10 Hz. The measurement cycle is set to 1 second, and each detection point measures the magnetic flux value 10 times during each measurement cycle. The magnetic flux values ​​measured at each test point during different measurement cycles are recorded and categorized by the test point's location (coordinates in the length, width, and thickness directions) and measurement time. For example, the magnetic flux value for the first test point in the length direction during the first measurement cycle is Φ1,1, the magnetic flux value for the second measurement cycle is Φ1,2, and so on. This organized data forms a multidimensional information flux matrix, whose dimensions include the test point's location coordinates (in the length, width, and thickness directions) and the measurement time. The magnetic flux change per unit cycle is calculated for the data in the multidimensional information flux matrix. For each test point, the change in magnetic flux value, ΔΦ, between adjacent measurement cycles is calculated. For example, for the first test point in the length direction, the magnetic flux change per unit cycle, ΔΦ1, = Φ1,2 - Φ1,1. The calculated magnetic flux change per unit cycle for all test points is summarized to generate a magnetic flux variation signature. This magnetic flux variation signature reflects the dynamic changes in magnetic flux in a magnetic material at different locations and times. A magnetic domain structure model is constructed based on the magnetic flux variation characteristics. Using magnetic domain structure analysis software, the magnetic flux variation characteristic data is input into the software. Using a fitting algorithm, the software inverts the distribution of the magnetic domain structure based on the magnetic flux variation characteristics. When constructing the model, the size, shape, orientation, and location of the magnetic domain walls are taken into account. For example, if the magnetic flux variation characteristics at a certain detection point exhibit periodic alternating positive and negative fluctuations, the software identifies this area as the location of a magnetic domain wall and estimates the size of the magnetic domain based on the amplitude of the fluctuation. Ultimately, the resulting magnetic domain structure model can reflect the magnetic domain distribution characteristics of magnetic materials under different shape conditions, providing a basis for further analysis and application of magnetic materials.

[0123] Preferably, performing magnetic field coupling on the magnetic anisotropy distribution map and the magnetic domain structure model in step S4 includes:

[0124] Discretize the magnetic field intensity data in the magnetic anisotropy distribution map and divide the space of the magnetic material into multiple uniform grid cells, each grid cell corresponding to a magnetic field intensity value;

[0125] Numbering each magnetic domain unit in the magnetic domain structure model, and determining the grid area corresponding to the magnetic domain unit in the discretized magnetic anisotropy distribution map according to the geometric position and shape of the magnetic domain unit;

[0126] According to the magnetization direction and strength of the magnetic domain unit, combined with its corresponding magnetic field strength value, the angle between the magnetization direction of the magnetic domain unit and the external magnetic field direction is calculated, thereby obtaining the interaction energy of each magnetic domain unit;

[0127] For each magnetic domain unit inside the magnetic material, the magnetic moment interaction energy between it and the adjacent magnetic domain unit is calculated, and the interaction energy between the magnetic domain units is recorded;

[0128] The external magnetic field interaction energy of all magnetic domain units and the magnetic moment interaction energy between adjacent magnetic domain units are magnetically coupled to obtain a magnetic field coupling model.

[0129] In an embodiment of the present invention, the magnetic field intensity data in the magnetic anisotropy distribution map is discretized. Finite element analysis software is used to divide the space of the magnetic material into multiple uniform grid units, and the size of each grid unit is 1mm×1mm×1mm. The magnetic field intensity value corresponding to each grid unit is obtained from the magnetic anisotropy distribution map by an interpolation algorithm, and the interpolation accuracy is set to 0.01T. Then, each magnetic domain unit in the magnetic domain structure model is numbered, and the grid area corresponding to it in the discretized magnetic anisotropy distribution map is determined according to the geometric position and shape of the magnetic domain unit. The specific operation is: match the center coordinates of the magnetic domain unit with the coordinates of the grid unit, and the grid unit covered by the magnetic domain unit is its corresponding grid area. Calculate the angle between the magnetization direction of the magnetic domain unit and the direction of the external magnetic field. The magnetization direction of the magnetic domain unit is represented by the magnetization vector in the magnetic domain structure model, and the direction of the external magnetic field is represented by the discretized magnetic field intensity vector. When calculating the angle, use the vector angle formula: Angle θ = arccos((Mx×Hx+My×Hy+Mz×Hz) / (|M|×|H|)), where Mx, My, and Mz are the components of the magnetization vector of the magnetic domain unit, Hx, Hy, and Hz are the components of the external magnetic field vector, |M| is the modulus of the magnetization vector, and |H| is the modulus of the magnetic field vector. According to the magnetization direction and intensity of the magnetic domain unit, combined with its corresponding magnetic field intensity value, the interaction energy of each magnetic domain unit is calculated. The interaction energy calculation formula is: E_int = -Ku×cos 2(θ), where Ku is the magnetic anisotropy constant, which is 84GPa, and θ is the angle between the magnetization direction of the magnetic domain unit and the direction of the external magnetic field. For each magnetic domain unit inside the magnetic material, the magnetic moment interaction energy between it and the adjacent magnetic domain unit is calculated. The formula for calculating the magnetic moment interaction energy is: E_dip=μ0×(mx_i×mx_j+my_i×my_j+mz_i×mz_j) / r 3 , where μ0 is the vacuum magnetic permeability, mx_i, my_i, and mz_i are the magnetic moment components of magnetic domain unit i, mx_j, my_j, and mz_j are the magnetic moment components of adjacent magnetic domain unit j, and r is the distance between adjacent magnetic domain units. The external magnetic field interaction energy of all magnetic domain units and the magnetic moment interaction energy between adjacent magnetic domain units are magnetically coupled. The interaction energy data is input into the software using the magnetic field coupling module of the finite element analysis software. The software uses numerical calculation methods to comprehensively analyze the external magnetic field interaction energy and the magnetic moment interaction energy to generate a magnetic field coupling model. During the coupling process, the magnetic field iteration accuracy is set to 1×10 -6 T, the upper limit of the number of iterations is 2000 to ensure the accuracy and convergence of the coupling results.

[0130] Preferably, in step S4, in the magnetic field coupling model, simulating the magnetization curve of the magnetic material under different stress and shape conditions includes:

[0131] In the magnetic field coupling model, stress conditions are set, including tensile stress, compressive stress, and shear stress, and multiple stress levels are set for each stress condition. Among them, the tensile stress is set at a stress level of 10 MPa from 0 to 100 MPa, the compressive stress is set at a stress level of 10 MPa from 0 to -100 MPa, and the shear stress is set at a stress level of 5 MPa from 0 to 50 MPa.

[0132] In the magnetic field coupling model, shape conditions are set, including cylindrical, rectangular, and irregular shapes. Multiple size parameters are set for each shape condition. The diameter of the cylinder ranges from 1 mm to 10 mm, with a size parameter set every 1 mm. The length, width, and height of the rectangular shape range from 1 mm to 10 mm, with a size parameter set every 1 mm.

[0133] Under the set stress and shape conditions, the magnetization curve of the magnetic material is simulated. By gradually increasing the external magnetic field strength from 0 to 1T, the magnetization intensity is recorded every 0.1T to obtain the magnetization curve under different stress and shape conditions. The magnetization curve uses the magnetic field strength as the horizontal axis and the magnetization intensity as the vertical axis;

[0134] The simulated magnetization curve data is analyzed, and the characteristic parameters of the magnetization curve under each stress and shape condition are calculated, including the residual magnetization intensity, coercive force and maximum magnetic energy product, to obtain the magnetic model simulation data.

[0135] In an embodiment of the present invention, in the magnetic field coupling model, the stress conditions are first set. Use the stress loading module of the finite element analysis software to set the tensile stress, compressive stress and shear stress respectively. The tensile stress is from 0 to 100MPa, and a stress level is set every 10MPa, that is, 0MPa, 10MPa, 20MPa...100MPa; the compressive stress is from 0 to -100MPa, and a stress level is set every 10MPa, that is, 0MPa, -10MPa, -20MPa...-100MPa; the shear stress is from 0 to 50MPa, and a stress level is set every 5MPa, that is, 0MPa, 5MPa, 10MPa...50MPa. Next, the shape conditions are set. In the finite element analysis software, cylindrical, rectangular and irregular shaped geometric models are created respectively. For cylindrical shapes, the diameters range from 1mm to 10mm, with dimensional parameters set at 1mm intervals, i.e., diameters of 1mm, 2mm, and 10mm, respectively. For rectangular parallelepiped shapes, the length, width, and height range from 1mm to 10mm, with dimensional parameters set at 1mm intervals, i.e., length, width, and height of 1mm × 1mm × 1mm, 2mm × 2mm × 2mm, and 10mm × 10mm × 10mm, respectively. For irregular shapes, geometric parameters are input according to actual requirements. A magnetization curve simulation of the magnetic material is performed under the specified stress and shape conditions. Using the magnetization curve simulation module of finite element analysis software, the external magnetic field intensity is gradually increased from 0 to 1T, with the magnetization intensity recorded every 0.1T. Specifically, for each stress and shape condition, the external magnetic field intensity is started at 0T and gradually increased in steps of 0.1T until it reaches 1T. The magnetization intensity value of the magnetic material is recorded at each magnetic field intensity. Finally, the magnetization curves for different stress and shape conditions are obtained, with the magnetic field intensity as the abscissa and the magnetization intensity as the ordinate. Analyze the simulated magnetization curve data. Using data analysis software, calculate the characteristic parameters of the magnetization curve for each stress and shape condition, including remanent magnetization, coercive force, and maximum magnetic energy product. Remanent magnetization is the magnetization value when the external magnetic field strength is 0 T; coercive force is the external magnetic field strength value corresponding to the magnetization strength dropping from saturation to 0; and maximum magnetic energy product is the maximum value of the area enclosed by the magnetization curve and the magnetic field strength axis. The calculated characteristic parameters are organized into magnetic model simulation data for subsequent analysis and application.

[0136] It is particularly important that the numerical verification of the magnetic field coupling model based on the magnetic model simulation data in step S5 includes:

[0137] Comparing the magnetization curve data in the magnetic model simulation data with the magnetization curve standard data preset in the magnetic field coupling model, and calculating the difference between the simulated magnetization intensity and the standard magnetization intensity for each magnetic field intensity point during the comparison;

[0138] Perform statistical analysis on the difference of each magnetic field intensity point and calculate the mean, maximum and standard deviation of the difference;

[0139] The accuracy of the magnetic field coupling model is determined based on the statistical analysis results. If the average value of the difference is less than the error threshold, the magnetic field coupling model is determined to be accurate at this magnetic field intensity point; if the average value of the difference is greater than or equal to the error threshold, the magnetic field coupling model is determined to have a deviation at this magnetic field intensity point.

[0140] The verification results of all magnetic field intensity points are summarized to obtain the model verification results.

[0141] In an embodiment of the present invention, first, the magnetization curve data in the magnetic model simulation data is compared with the magnetization curve standard data preset in the magnetic field coupling model. Using data analysis software, the simulated magnetization intensity and the standard magnetization intensity of each magnetic field strength point are compared one by one. The specific operation is: for each magnetic field strength point, the difference ΔM between the simulated magnetization intensity and the standard magnetization intensity is calculated, and the formula is ΔM=M_sim-M_std, where M_sim is the simulated magnetization intensity and M_std is the standard magnetization intensity. Then, a statistical analysis is performed on the difference ΔM of each magnetic field strength point. The average value μ, the maximum value ΔM_max and the standard deviation σ of the difference are calculated. The calculation formula for the average value μ is μ=(ΔM1+ΔM2+...+ΔMn) / n, where n is the total number of magnetic field strength points; the maximum value ΔM_max is the maximum value of all differences; the calculation formula for the standard deviation σ is σ=sqrt((ΔM1 2 +ΔM2 2 +...+ΔMn 2 ) / n-μ 2 ). The accuracy of the magnetic field coupling model is judged based on the statistical analysis results. The error threshold is set to 0.05T (assuming the error threshold is 0.05T). If the average value μ of the difference is less than the error threshold of 0.05T, the magnetic field coupling model is judged to be accurate at this magnetic field intensity point; if the average value μ of the difference is greater than or equal to the error threshold of 0.05T, it is judged that the magnetic field coupling model has a deviation at this magnetic field intensity point. Finally, the verification results of all magnetic field intensity points are summarized. The accuracy judgment results of each magnetic field intensity point are sorted out to form a summary table of the model verification results. The summary table records the average value μ, maximum value ΔM_max, standard deviation σ and accuracy judgment results of each magnetic field intensity point. The summary table can intuitively view the accuracy of the magnetic field coupling model in the entire magnetic field intensity range.

[0142] Of particular importance is that adjusting the model structure parameters according to the model validation results in step S5 includes:

[0143] Extract the difference data of each magnetic field intensity point from the model verification results, sort the difference data in ascending order of magnetic field intensity, and form a difference data sequence;

[0144] The difference data sequence is segmented to divide the magnetic field intensity range into several sub-intervals, each of which contains a certain number of magnetic field intensity points;

[0145] In each subinterval, calculate the mean and standard deviation of the difference data;

[0146] According to the mean and standard deviation of the difference in each subinterval, the adjustment direction and amplitude of the model structure parameters in the subinterval are determined;

[0147] Adjusting the structural parameters of each magnetic domain unit in the magnetic field coupling model one by one, including the size, shape, magnetization direction and magnetization intensity of the magnetic domain unit;

[0148] The adjusted model structure parameters are substituted into the magnetic field coupling model, the magnetization curve simulation is re-performed, and the magnetic configuration is generated.

[0149] In an embodiment of the present invention, the difference data of each magnetic field intensity point is extracted from the model verification result, and the difference data is sorted from small to large according to the magnetic field intensity to form a difference data sequence. The difference data sequence contains the difference ΔM corresponding to each magnetic field intensity point, the magnetic field intensity range is from 0T to 1T, and the difference data is arranged in ascending order of magnetic field intensity. The difference data sequence is segmented and the magnetic field intensity range is divided into several subintervals. The magnetic field intensity range 0T to 1T is divided into 10 subintervals, each subinterval containing 10 magnetic field intensity points. For example, the first subinterval is 0T to 0.1T, the second subinterval is 0.1T to 0.2T, and so on, until the last subinterval is 0.9T to 1T. In each subinterval, the mean and standard deviation of the difference data are calculated. Data analysis software is used to perform statistical analysis on the difference data in each subinterval. For example, within the first subinterval, the mean μ1 and standard deviation σ1 of the difference data are calculated; within the second subinterval, the mean μ2 and standard deviation σ2 of the difference data are calculated, and so on, until the mean and standard deviation of all subintervals are calculated. Based on the mean and standard deviation of the difference values ​​within each subinterval, the direction and magnitude of adjustment of the model structural parameters within that subinterval are determined. If the mean μ of the difference values ​​within a subinterval is greater than the error threshold of 0.05T and the standard deviation σ is large, it indicates that the model has large deviations and high data dispersion within that subinterval, requiring significant adjustments to the model structural parameters. Adjustments can include increasing the size of the magnetic domain units, changing their shape, or adjusting their magnetization direction and intensity. The magnitude of the adjustment is determined by the mean and standard deviation of the difference values. For example, if μ = 0.1T and σ = 0.03T, the size of the magnetic domain units is adjusted by 10%, the magnetization direction by 10°, and the magnetization intensity by 15%. The structural parameters of each magnetic domain unit in the magnetic field coupling model are adjusted individually. Finite element analysis software is used to adjust the size, shape, magnetization direction, and magnetization intensity of each magnetic domain unit according to the determined adjustment direction and amplitude. For example, for the magnetic domain unit in the first subinterval, its size is increased by 10%, its shape is adjusted from circular to elliptical, its magnetization direction is rotated 10° clockwise, and its magnetization intensity is increased by 15%. The adjusted model structure parameters are substituted into the magnetic field coupling model, and the magnetization curve simulation is re-performed. Using the magnetization curve simulation module of the finite element analysis software, the external magnetic field intensity is gradually increased from 0T to 1T according to the adjusted model structure parameters, and the magnetization intensity is recorded every 0.1T to generate a new magnetization curve. Based on the new magnetization curve, the magnetic configuration is generated to complete the optimization adjustment of the magnetic field coupling model.

[0150] This specification also provides a system for generating a magnetic configuration of a magnetic material, which is used to execute the method for generating a magnetic configuration of a magnetic material as described above. The system for generating a magnetic configuration of a magnetic material includes:

[0151] The magnetic material information acquisition module is used to collect physical information of the magnetic material and extract the shape characteristics of the physical information of the magnetic material; determine the stress distribution characteristics of the magnetic material based on the shape characteristics; and collect the elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material;

[0152] The magnetic anisotropy induction analysis module is used to construct a stress magnetic structure based on stress distribution characteristics; calculate stress sensitive parameters based on elastic modulus and Poisson's ratio; and perform magnetic anisotropy induction analysis on the stress sensitive parameters and stress magnetic structure to generate a magnetic anisotropy distribution map.

[0153] A magnetic domain evaluation module is used to construct a shaped magnetic architecture based on shape features; evaluate the magnetic domain structure effect of the shaped magnetic architecture to obtain magnetic domain evaluation data; detect magnetic flux changes under different shape conditions based on the magnetic domain evaluation data, and construct a magnetic domain structure model;

[0154] The magnetization curve simulation module is used to perform magnetic field coupling between the magnetic anisotropy distribution map and the magnetic domain structure model to obtain a magnetic field coupling model. In the magnetic field coupling model, the magnetization curve of the magnetic material under different stress and shape conditions is simulated to generate magnetic model simulation data.

[0155] The magnetic configuration generation module is used to numerically verify the magnetic field coupling model based on the magnetic model simulation data to obtain the model verification results; adjust the model structure parameters according to the model verification results to generate the magnetic configuration.

[0156] The present invention is therefore intended to be illustrative and non-restrictive in all respects, with the scope of the invention being defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the application documents are intended to be embraced therein.

[0157] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. A method for generating a magnetic configuration of a magnetic material, characterized in that: The following steps are involved: Step S1: collecting physical information of magnetic materials and extracting shape features of the physical information of magnetic materials; Determine the stress distribution characteristics of the magnetic material according to the shape characteristics; collect the elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material; Step S2: constructing a stress magnetic structure based on stress distribution characteristics; calculating stress sensitive parameters according to elastic modulus and Poisson's ratio; Conduct magnetic anisotropy induction analysis on stress-sensitive parameters and stress-magnetic architecture to generate a magnetic anisotropy distribution map; Step S3: constructing a shape magnetic architecture based on the shape characteristics; evaluating the magnetic domain structure effect of the shape magnetic architecture to obtain magnetic domain evaluation data; detecting the magnetic flux change under different shape conditions based on the magnetic domain evaluation data, and constructing a magnetic domain structure model; Step S4: performing magnetic field coupling on the magnetic anisotropy distribution map and the magnetic domain structure model to obtain a magnetic field coupling model; in the magnetic field coupling model, performing magnetization curve simulation on the magnetic material under different stress and shape conditions to generate magnetic model simulation data; Step S5: numerically verifying the magnetic field coupling model according to the magnetic model simulation data to obtain a model verification result; adjusting the model structure parameters according to the model verification result to generate a magnetic configuration.

2. The method for generating a magnetic configuration of a magnetic material according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: collecting physical information of the magnetic material, measuring the dimensions of the physical information of the magnetic material, and determining the values ​​of the length, width, and height of the magnetic material; Step S12: determining the shape characteristics of the magnetic material according to the values ​​of the length, width, and height of the magnetic material; and dividing the magnetic material into a plurality of stress regions based on the shape characteristics; Step S13: In each region, different forces are applied to monitor the deformation of the magnetic material and record the deformation data; the stress value of each region is calculated based on the deformation data to obtain the stress distribution characteristics of the magnetic material; Step S14: performing a tensile test on the magnetic material in each region, and recording the elongation under different tensile forces; Step S15: Calculate the stress and strain of the magnetic material under different tensile forces to obtain a stress-strain curve; select a linear portion from the stress-strain curve, calculate the slope, and obtain the elastic modulus; Step S16: In each region, a compression test is performed on the magnetic material, and the compression amount under different pressures is recorded; and the Poisson's ratio is calculated based on the compression test data.

3. The method for generating a magnetic configuration of a magnetic material according to claim 1, characterized in that: Calculating the stress-sensitive parameter according to the elastic modulus and Poisson's ratio in step S2 includes: Mark multiple measurement points on the surface of the magnetic material, each measurement point corresponds to a specific stress state; Calculate the theoretical strain value of magnetic materials under different stress states based on elastic modulus and Poisson's ratio; Use high-precision strain gauges to measure the actual strain value at each measuring point; Compare and analyze the actual strain value with the theoretical strain value, calculate the ratio of stress to strain at each measuring point, and obtain the local stress sensitivity coefficient; The weighted average of all local stress sensitivity coefficients is performed to obtain the overall stress sensitivity parameter of the magnetic material.

4. The method for generating a magnetic configuration of a magnetic material according to claim 1, wherein: In step S2, the magnetic anisotropy induction analysis of the stress sensitive parameters and the stress magnetic structure includes: On the surface of the magnetic material, several equally spaced measurement lines are marked along its length and width, and each measurement line corresponds to a specific stress direction; On each measuring line, the magnetic field strength is measured in turn, and the changes in the magnetic field strength at different positions are recorded to obtain the magnetic field position strength data; Perform magnetic anisotropic parameter detection based on magnetic field position intensity data and stress sensitive parameters to generate magnetic anisotropic parameter values; The correlation coefficient between the change of magnetic field intensity and stress direction on each measuring line is calculated based on the magnetic anisotropic parameter value; Anisotropic induction analysis is performed on the correlation coefficient on each measurement line to obtain anisotropic correlation coefficient; anisotropic correlation coefficient is weighted to obtain anisotropic weighted coefficient; The magnetic anisotropy distribution diagram of the magnetic material in different directions is drawn according to the anisotropy weighting coefficient.

5. The method for generating a magnetic configuration of a magnetic material according to claim 1, characterized in that: The step S3 of evaluating the magnetic domain structure effect of the shape magnetic architecture includes: Using a magnetic domain imaging device to image the shaped magnetic structure, during the imaging process, external magnetic fields in different directions are applied to the shaped magnetic structure, and the responses under different magnetic field directions are identified to obtain a magnetic domain image; Marking magnetic image features on the magnetic domain image, and calculating magnetic domain size parameters and magnetic domain distribution density of the magnetic image features; Determine the magnetic domain wall movement speed according to the magnetic domain size parameter, and determine the magnetic domain distribution density according to the magnetic domain distribution density; The magnetic domain structure interaction strength is evaluated based on the magnetic domain wall movement speed and magnetic domain distribution density to generate magnetic domain evaluation data.

6. The method for generating a magnetic configuration of a magnetic material according to claim 1, characterized in that: In step S3, detecting the change of magnetic flux under different shape conditions according to the magnetic domain evaluation data includes: Under different shape conditions, multiple magnetic flux detection points are set along the length, width and thickness directions of the magnetic material according to the magnetic domain evaluation data. The distance between adjacent detection points in the length direction is 1 / 10 of the material length, in the width direction is 1 / 10 of the material width, and in the thickness direction is 1 / 10 of the material thickness; Perform periodic magnetic flux measurement on each magnetic flux detection point, record the magnetic flux values ​​measured at each detection point in different measurement cycles, and classify and organize them according to the location of the detection point and the measurement time to form a multi-dimensional information magnetic flux matrix; The magnetic flux variation per unit period is calculated for the data in the multi-dimensional information magnetic flux matrix to generate the magnetic flux variation characteristics, and a magnetic domain structure model is constructed based on the magnetic flux variation characteristics.

7. The method for generating a magnetic configuration of a magnetic material according to claim 1, characterized in that: The step S4 of performing magnetic field coupling between the magnetic anisotropy distribution map and the magnetic domain structure model includes: Discretize the magnetic field intensity data in the magnetic anisotropy distribution map and divide the space of the magnetic material into multiple uniform grid cells, each grid cell corresponding to a magnetic field intensity value; Numbering each magnetic domain unit in the magnetic domain structure model, and determining the grid area corresponding to the magnetic domain unit in the discretized magnetic anisotropy distribution map according to the geometric position and shape of the magnetic domain unit; According to the magnetization direction and strength of the magnetic domain unit, combined with its corresponding magnetic field strength value, the angle between the magnetization direction of the magnetic domain unit and the external magnetic field direction is calculated, thereby obtaining the interaction energy of each magnetic domain unit; For each magnetic domain unit inside the magnetic material, the magnetic moment interaction energy between it and the adjacent magnetic domain unit is calculated, and the interaction energy between the magnetic domain units is recorded; The external magnetic field interaction energy of all magnetic domain units and the magnetic moment interaction energy between adjacent magnetic domain units are magnetically coupled to obtain a magnetic field coupling model.

8. The method for generating a magnetic configuration of a magnetic material according to claim 1, characterized in that: In step S4, in the magnetic field coupling model, simulation of magnetization curves of the magnetic material under different stress and shape conditions includes: In the magnetic field coupling model, stress conditions are set, including tensile stress, compressive stress, and shear stress, and multiple stress levels are set for each stress condition. Among them, the tensile stress is set at a stress level of 10 MPa from 0 to 100 MPa, the compressive stress is set at a stress level of 10 MPa from 0 to -100 MPa, and the shear stress is set at a stress level of 5 MPa from 0 to 50 MPa. In the magnetic field coupling model, shape conditions are set, including cylindrical, rectangular, and irregular shapes. Multiple size parameters are set for each shape condition. The diameter of the cylinder ranges from 1 mm to 10 mm, with a size parameter set every 1 mm. The length, width, and height of the rectangular shape range from 1 mm to 10 mm, with a size parameter set every 1 mm. Under the set stress and shape conditions, the magnetization curve of the magnetic material is simulated. By gradually increasing the external magnetic field strength from 0 to 1T, the magnetization intensity is recorded every 0.1T to obtain the magnetization curve under different stress and shape conditions. The magnetization curve uses the magnetic field strength as the horizontal axis and the magnetization intensity as the vertical axis; The simulated magnetization curve data is analyzed, and the characteristic parameters of the magnetization curve under each stress and shape condition are calculated, including the residual magnetization intensity, coercive force and maximum magnetic energy product, to obtain the magnetic model simulation data.

9. A system for generating a magnetic configuration of a magnetic material, characterized in that: For executing the method for generating a magnetic structure of a magnetic material according to claim 1, the system for generating a magnetic structure of a magnetic material comprises: The magnetic material information acquisition module is used to collect physical information of the magnetic material and extract the shape characteristics of the physical information of the magnetic material; determine the stress distribution characteristics of the magnetic material based on the shape characteristics; and collect the elastic modulus and Poisson's ratio corresponding to the shape characteristics of the magnetic material; The magnetic anisotropy induction analysis module is used to construct a stress magnetic structure based on stress distribution characteristics; calculate stress sensitive parameters based on elastic modulus and Poisson's ratio; and perform magnetic anisotropy induction analysis on the stress sensitive parameters and stress magnetic structure to generate a magnetic anisotropy distribution map. A magnetic domain evaluation module is used to construct a shaped magnetic architecture based on shape features; evaluate the magnetic domain structure effect of the shaped magnetic architecture to obtain magnetic domain evaluation data; detect magnetic flux changes under different shape conditions based on the magnetic domain evaluation data, and construct a magnetic domain structure model; The magnetization curve simulation module is used to perform magnetic field coupling between the magnetic anisotropy distribution map and the magnetic domain structure model to obtain a magnetic field coupling model. In the magnetic field coupling model, the magnetization curve of the magnetic material under different stress and shape conditions is simulated to generate magnetic model simulation data. The magnetic configuration generation module is used to numerically verify the magnetic field coupling model based on the magnetic model simulation data to obtain the model verification results; adjust the model structure parameters according to the model verification results to generate the magnetic configuration.

10. A computer-readable medium storing a computer program, characterized in that: When the computer program is executed, the method for generating the magnetic structure of a magnetic material according to any one of claims 1 to 8 is implemented.

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