Jade carving processing parameter optimization method based on characteristics of jade material

Abstract

The invention provides a jade sculpture processing parameter optimization method based on characteristics of a jade material, and belongs to the technical field of jade sculpture processing.The jade sculpture processing parameter optimization method comprises the steps that firstly, a CT scanning image of jade is obtained to construct a three-dimensional digital model, and internal stress distribution is calculated through mesh generation and data collection; carrying out region division and calculating mechanical characteristic matrixes of each region and the whole; and then constructing a double-player game optimization model, wherein the spatial position optimizer and the attitude angle optimizer solve the optimal position and angle through an iteration mode. And finally, based on the optimal parameters, the geometric and mechanical characteristic matching degree of each partition and the whole is calculated, multi-target weight optimization is carried out by adopting a Pareto optimal method, the optimal processing position of the jade carving is determined, and a cutting track and a depth control curve are planned. The problems that at present, the method mainly depends on experience accumulation of craftsmen, deep analysis on the internal structure and the mechanical property of the jade is lacked, selection of machining parameters often depends on experience judgment, and the machining quality and efficiency are difficult to guarantee are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of jade carving processing, and in particular relates to a method for optimizing jade carving processing parameters based on the characteristics of jade material itself. Background Art

[0002] Jade processing is a traditional arts and crafts with a long history and complex processes. In the process of jade processing, how to reasonably determine the optimal processing position and processing parameters of jade has always been a key issue restricting the improvement of the process level. The existing jade processing methods mainly rely on the experience accumulation of craftsmen, lack of in-depth analysis of the internal structure and mechanical properties of jade, and the selection of processing parameters is often based on experience, which makes it difficult to ensure processing quality and efficiency.

[0003] Specifically, the existing jade processing methods generally have the following problems:

[0004] 1. It is impossible to fully understand the internal structure of jade. Traditional processing methods rely only on appearance observation and a small amount of destructive testing. It is difficult to accurately grasp the complex structure and defect distribution inside the jade, and thus it is impossible to reasonably plan the processing path.

[0005] 2. It is difficult to accurately predict the stress distribution during processing. Jade is a brittle material that is prone to cracks and fractures during processing, which seriously affects the processing quality. However, existing methods cannot accurately predict the stress distribution inside jade during processing, making it difficult to avoid processing risks in advance.

[0006] 3. Lack of systematic mechanical properties analysis. The mechanical properties of jade, such as hardness, toughness, strength, etc., are key factors that restrict processing quality. However, most current processing methods only focus on the appearance effect and ignore the optimization of mechanical properties.

[0007] 4. The selection of processing parameters is not scientific enough. The existing jade processing methods mainly rely on the experience of craftsmen. The selection of processing parameters such as cutting trajectory and cutting depth lacks scientific basis, making it difficult to ensure the stability and repeatability of the processing process.

[0008] In order to solve the above problems, it is urgent to develop a new processing method that can comprehensively analyze the internal structure and mechanical properties of jade and optimize the processing parameters based on this. This can not only improve the quality and efficiency of jade processing, but also provide new technical support for the modernization of traditional arts and crafts. Summary of the invention

[0009] In view of this, the present invention provides a method for optimizing jade carving processing parameters based on the characteristics of jade materials themselves, which can solve the technical problems that the existing jade processing methods mainly rely on the experience accumulation of craftsmen, lack of in-depth analysis of the internal structure and mechanical properties of jade, and the selection of processing parameters often relies on experience judgment, making it difficult to ensure processing quality and efficiency.

[0010] The present invention is achieved in that:

[0011] The present invention provides a method for optimizing jade carving processing parameters based on the characteristics of jade material itself, comprising the following steps:

[0012] S10, obtaining a computerized tomography image of the jade and establishing a three-dimensional digital model of the jade;

[0013] S20, meshing the three-dimensional digital model to obtain mesh units of jade;

[0014] S30, calculating the internal stress distribution of the jade based on the grid unit and the data collected by the X-ray diffractometer and the strain gauge to obtain the internal stress distribution matrix of the jade;

[0015] S40, dividing the jade into regions according to the internal stress distribution matrix of the jade to obtain a plurality of jade partitions;

[0016] S50, calculating the mechanical characteristic matrix of each jade partition and the mechanical characteristic matrix of the whole jade, wherein each element in the mechanical characteristic matrix represents the mechanical characteristics of the corresponding position, and the mechanical characteristics include stress intensity factor, fracture toughness, elastic modulus, Poisson's ratio, hardness value, density, porosity, crack distribution density, grain orientation, and material uniformity index;

[0017] S60, constructing a game optimization model according to the mechanical characteristic matrix of each jade partition and the mechanical characteristic matrix of the whole jade, wherein the first player is a spatial position optimizer, the strategy space is a three-dimensional coordinate (x, y, z), and the second player is a posture angle optimizer, and the strategy space is Euler angle (α, β, γ);

[0018] S70, solving the game optimization model by iterative optimization, specifically, in each iteration, alternately fixing the strategy of one player while optimizing the strategy of another player, until the strategy change amount and the payment function change amount are both less than a preset threshold, and then stopping the iteration, and outputting the optimal spatial position and posture angle;

[0019] S80, based on the optimal spatial position and posture angle, respectively calculating the geometric feature matching degree of each partition and the geometric feature matching degree of the overall jade, as well as the mechanical feature matching degree of each partition and the mechanical feature matching degree of the overall jade, establishing a partition matching degree objective function and an overall matching degree objective function, and using the Pareto optimal method to perform multi-objective weight optimization;

[0020] S90. Determine the final optimal processing position of the jade carving in the jade according to the multi-objective optimization result. Based on the optimal processing position, determine the cutting entry point and plan the cutting trajectory. Meanwhile, calculate the depth value of each cutting point and generate a depth control curve.

[0021] The preset threshold is 0.02-0.0.5.

[0022] On the basis of the above-mentioned technical scheme, a kind of jade carving processing parameter optimization method based on jade material own characteristics of the present invention can also make the following improvement:

[0023] Among them, the step S10 specifically includes: using computer tomography to perform spatial scanning on the jade sample to obtain three-dimensional grayscale image data inside the jade, the spatial resolution of the computer tomography is set to 0.1 mm, and the three-dimensional grayscale image data includes the internal structure information and external shape information of the jade; using a voxel isosurface extraction algorithm or a point cloud triangle patch reconstruction algorithm to process the three-dimensional grayscale image data to establish a three-dimensional digital model of the jade, and the three-dimensional digital model contains the complete geometric information and internal structure information of the jade.

[0024] Furthermore, the step S20 specifically includes: performing grid discretization processing on the three-dimensional digital model of the jade, dividing the three-dimensional digital model of the jade into multiple grid units using a tetrahedron unstructured grid division method or a hexahedron unstructured grid division method, the size of the grid unit is set between 0.5 mm and 2 mm, the number of the grid units is determined according to the volume of the jade, and the three-dimensional grid unit information inside the jade is obtained through the grid units.

[0025] Furthermore, the step S30 specifically includes: using an X-ray diffractometer to measure the change in the interplanar spacing of crystal grains inside the jade, and calculating the internal stress components of the jade according to Hooke's law; pasting strain gauges on the surface of the jade, and obtaining the surface strain value of the jade through strain testing; using a reverse algorithm to estimate the internal stress components of the jade according to the surface strain value of the jade; combining the X-ray diffraction measurement data and the strain test data with a stress distribution calculation formula, and using a finite element method or a finite difference method to perform numerical simulation on the three-dimensional stress field inside the jade to obtain a stress distribution matrix.

[0026] Furthermore, the step S40 specifically includes: taking the internal stress components of the jade as feature vectors, each feature vector corresponding to the spatial coordinates of the grid unit; using an improved K-means clustering algorithm to cluster the feature vectors, introducing stress gradient as a clustering criterion to ensure that the stress difference between adjacent areas meets a preset threshold; dividing the jade into multiple areas according to the clustering results, each area having similar stress characteristics.

[0027] Furthermore, the step S50 specifically includes: obtaining the mechanical parameters of each jade partition through three-point bending test, ultrasonic detection and Vickers hardness test; calculating the mechanical characteristic matrix of each jade partition, the mechanical characteristic matrix including stress intensity factor, fracture toughness, elastic modulus, Poisson's ratio, hardness value, density, porosity, crack distribution density, grain orientation and material uniformity index; determining the weight coefficient according to the volume proportion of the jade partition; and using the weight coefficient to calculate the mechanical characteristic matrix of the entire jade.

[0028] Furthermore, the step S60 specifically includes: constructing a two-player game optimization model, in which the first player is a spatial position optimizer, and the strategy space is a three-dimensional coordinate, and the second player is a posture angle optimizer, and the strategy space is an Euler angle; establishing a player objective function to minimize the difference between the mechanical characteristic matrix of each jade partition and the target characteristic matrix; setting spatial position constraints and posture angle constraints; and constructing a payment function to reflect the degree of influence of the player's strategy selection on the optimization target.

[0029] Furthermore, the step S70 specifically includes: alternately fixing the strategy of one player and optimizing the strategy of another player in each iteration; calculating the strategy change amount and the payment function change amount after each iteration; stopping the iteration when the strategy change amount and the payment function change amount are both less than a preset threshold; and outputting the optimal spatial position coordinates and the optimal posture angle.

[0030] Furthermore, the step S80 specifically includes: using the Gaussian kernel function to calculate the geometric feature matching degree and mechanical feature matching degree of each jade partition according to the optimal spatial position and the optimal posture angle; using the Gaussian kernel function to calculate the geometric feature matching degree and mechanical feature matching degree of the entire jade; establishing a partition matching degree objective function and an overall matching degree objective function; and using the Pareto optimal method to perform multi-objective optimization to obtain a set of optimal solutions.

[0031] Furthermore, the step S90 specifically includes: determining the final optimal processing position of the jade carving in the jade according to the Pareto optimal solution; selecting the boundary point closest to the final optimal processing position and with the lowest stress as the cutting entry point; using B-spline curve to parameterize the cutting trajectory modeling; using exponential decay model to calculate the cutting depth; generating a cutting trajectory and a depth control curve.

[0032] Compared with the prior art, the method for optimizing jade carving processing parameters based on the characteristics of jade material itself provided by the present invention has the following beneficial effects: 1. Fully revealing the internal structure of jade. The present invention adopts CT scanning and three-dimensional reconstruction technology to obtain a three-dimensional digital model of the inside of jade, and fully grasp the internal structure and defect distribution of jade. This provides a reliable data basis for subsequent stress analysis and regional division.

[0033] 2. Accurately predict stress distribution during processing. The present invention combines X-ray diffraction and strain test data and uses finite element analysis to calculate the stress distribution matrix inside the jade. This can not only reflect the stress state inside the jade, but also provide a basis for safety assessment of the processing process.

[0034] 3. Systematic optimization of the mechanical properties of jade. The present invention constructs a mechanical characteristic matrix of each partition of jade, including multiple key parameters such as stress intensity factor, fracture toughness, elastic modulus, etc. Through the game optimization method, the processing position and posture that optimizes the overall mechanical properties can be found.

[0035] 4. Scientifically determine the processing parameters. Based on the above in-depth analysis of the internal structure and mechanical properties of jade, the present invention adopts a multi-objective optimization method, taking into account the matching degree of geometric characteristics and mechanical characteristics, and determines the optimal processing position, cutting trajectory and depth control curve. This greatly improves the controllability and stability of the processing process.

[0036] In general, the present invention realizes comprehensive analysis and optimization of the internal structure and mechanical properties of jade by introducing advanced scanning imaging, finite element analysis and optimization algorithms, etc. It solves the technical problems that the existing jade processing methods mainly rely on the experience accumulation of craftsmen, lack in-depth analysis of the internal structure and mechanical properties of jade, and the selection of processing parameters often relies on experience judgment, which makes it difficult to ensure the processing quality and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flow chart of the method provided by the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0039] like Figure 1 FIG. 1 is a flow chart of a method for optimizing jade carving processing parameters based on the characteristics of jade material itself provided by the present invention. The method comprises the following steps:

[0040] S10, obtaining a computerized tomography image of the jade and establishing a three-dimensional digital model of the jade;

[0041] S20, meshing the three-dimensional digital model to obtain mesh units of the jade;

[0042] S30, calculating the internal stress distribution of the jade based on the grid unit and the data collected by the X-ray diffractometer and the strain gauge to obtain the internal stress distribution matrix of the jade;

[0043] S40, dividing the jade into regions according to the internal stress distribution matrix of the jade to obtain a plurality of jade partitions;

[0044] S50, calculating the mechanical characteristic matrix of each jade partition and the mechanical characteristic matrix of the whole jade, each element in the mechanical characteristic matrix represents the mechanical characteristic of the corresponding position, and the mechanical characteristics include stress intensity factor, fracture toughness, elastic modulus, Poisson's ratio, hardness value, density, porosity, crack distribution density, grain orientation, and material uniformity index;

[0045] S60, constructing a game optimization model according to the mechanical characteristic matrix of each jade partition and the mechanical characteristic matrix of the entire jade, wherein the first player is a spatial position optimizer, the strategy space is a three-dimensional coordinate (x, y, z), and the second player is a posture angle optimizer, and the strategy space is an Euler angle (α, β, γ);

[0046] S70, solving the game optimization model through iterative optimization, specifically, in each iteration, alternately fixing the strategy of one player while optimizing the strategy of another player, until the strategy change amount and the payment function change amount are both less than a preset threshold, and then stopping the iteration, and outputting the optimal spatial position and posture angle;

[0047] S80, based on the optimal spatial position and posture angle, respectively calculating the geometric feature matching degree of each partition and the geometric feature matching degree of the overall jade, as well as the mechanical feature matching degree of each partition and the mechanical feature matching degree of the overall jade, establishing a partition matching degree objective function and an overall matching degree objective function, and using the Pareto optimal method to perform multi-objective weight optimization;

[0048] S90. Determine the final optimal processing position of the jade carving in the jade according to the multi-objective optimization result. Based on the optimal processing position, determine the cutting entry point and plan the cutting trajectory. Meanwhile, calculate the depth value of each cutting point and generate a depth control curve.

[0049] The specific implementation methods of the above steps are described in detail below:

[0050] The specific implementation method of step S10 is: first, the jade sample to be processed is scanned using Computed Tomography (CT) technology. The three-dimensional grayscale image data inside the jade can be obtained by CT scanning. Then, a three-dimensional reconstruction algorithm, such as a voxel-based isosurface extraction (Marching Cubes) algorithm or a point cloud-based triangular facet reconstruction algorithm, is used to convert the three-dimensional grayscale data obtained by CT scanning into a three-dimensional digital model. The resulting three-dimensional digital model can more accurately describe the internal structure and appearance of jade. The spatial resolution of CT scanning can usually reach about 0.1 mm, which is enough to capture the fine structural information inside the jade.

[0051] The specific implementation of step S20 is: for the three-dimensional digital model of jade obtained in step S10, first its mesh is discretized. Here, an unstructured meshing method based on tetrahedron or hexahedron can be adopted. Through meshing, the original continuous three-dimensional model is discretized into a discrete model composed of a large number of units. The size of the grid unit is usually controlled between 0.5-2 mm, which can fully capture the stress distribution characteristics inside the jade. The result of meshing is to obtain the three-dimensional grid unit information inside the jade, which lays the foundation for subsequent stress analysis.

[0052] The specific implementation method of step S30 is: according to the jade grid unit information obtained in step S20, combined with the experimental data collected by using an X-ray diffractometer and a strain gauge, the stress distribution inside the jade is calculated. Specifically, firstly, the change in the interplanar spacing of the crystal grains inside the jade is measured by using an X-ray diffractometer, and the stress component at the corresponding position can be calculated by using Hooke's law. At the same time, a strain gauge is attached to the surface of the jade, and the surface strain value is obtained by strain testing, and then the internal stress component is estimated by using a reverse algorithm. The stress data obtained by X-ray diffraction and strain testing are combined with the stress distribution calculation formula described in formula (1), and the three-dimensional stress field inside the jade is numerically simulated by using the finite element method or the finite difference method to obtain a stress distribution matrix S, as shown in formula (2). The stress distribution matrix S contains the stress component information of each grid unit inside the jade, laying a foundation for subsequent regional division.

[0053] The specific implementation of step S40 is: according to the stress distribution matrix S of the jade obtained in step S30, the improved K-means clustering algorithm is used to divide the jade into regions. The specific process is as follows: First, the stress component σ(p) inside the jade is regarded as a eigenvector, corresponding to the spatial coordinate p of each grid unit. Then, the K-means algorithm is used to cluster these eigenvectors to obtain k stress centers c k and its corresponding k regions R k , as shown in equations (3) and (4). Different from the standard K-means algorithm, the stress gradient ||σ(p)-c is introduced here. k || is used as a clustering criterion to ensure that the stress difference between adjacent regions is large enough to better reflect the stress distribution characteristics inside the jade. Through this regional division method, the original continuous jade model can be divided into multiple sub-regions with obvious stress characteristics, laying the foundation for subsequent mechanical analysis and optimization.

[0054] The specific implementation of step S50 is: for each jade partition obtained in step S40, the mechanical characteristic matrix M is calculated respectively. k . Mechanical characteristic matrix M k Includes stress intensity factor K IC , fracture toughness Gc , elastic modulus E, Poisson's ratio ν, hardness H, density D, porosity φ, crack density ρ, grain orientation θ and material uniformity index I, as shown in formula (5). These mechanical parameters are obtained through standard mechanical experimental test methods (such as three-point bending test, ultrasonic testing, Vickers hardness test, etc.). In calculating the mechanical characteristic matrix M of each partition k At the same time, the mechanical characteristic matrix M of the whole jade is also calculated. total , as shown in formula (6), where the weight coefficient ω of each partition is k Determined according to the volume ratio of the partitions. The calculation results of the above mechanical characteristic matrix provide the required internal mechanical information of jade for the subsequent game optimization model.

[0055] The specific implementation of step S60 is: according to the mechanical characteristic matrix M of each partition calculated in step S50 k and the overall jade mechanical characteristic matrix M total , a two-player game optimization model is constructed. In this model, the first player is a spatial position optimizer, whose strategy space is the three-dimensional spatial coordinates (x, y, z); the second player is a posture angle optimizer, whose strategy space is the Euler angle (α, β, γ). The objective functions of the two players are shown in Equations (7) and (8). The goal is to make the mechanical characteristic matrix M of each partition k As close as possible to the target feature matrix M target , and at the same time satisfy the constraints of spatial position and posture angle, as shown in equations (9) and (10). The solution of this game optimization model adopts an iterative optimization method, that is, in each iteration, the strategy of one player is alternately fixed, and the strategy of the other player is optimized at the same time, until the change of the strategies and payment functions of both parties is less than the preset threshold, and the iteration is stopped. Through this game optimization method, the spatial position and posture angle that optimize the overall mechanical properties of jade can be found.

[0056] The specific implementation of step S70 is: for the optimal spatial position (x, y, z) and posture angle (α, β, γ) obtained in step S60, the geometric feature matching degree G of each partition is calculated respectively. k The matching degree G of the geometric characteristics of the whole jade total , and the mechanical characteristics matching degree L of each partition k The matching degree of mechanical characteristics with the whole jade L total Among them, the calculation of geometric feature matching is shown in formula (11) and formula (12), and the Gaussian kernel function is used to describe the partition voxel feature vector V k and the target voxel feature vector V target The calculation of mechanical feature matching is shown in Equation (13) and Equation (14), and the Gaussian kernel function is also used to describe the partition mechanical feature matrix Mk With the target matrix M target Through this matching evaluation method, the geometric and mechanical characteristics of jade can be comprehensively considered, providing a basis for subsequent multi-objective optimization.

[0057] The specific implementation of step S80 is: based on the geometric feature matching degree and mechanical feature matching degree calculated in step S70, a multi-objective optimization problem is established, as shown in formula (15). The two objective functions of this problem are maximizing the overall geometric matching degree f1(w) and maximizing the overall mechanical matching degree f2(w), where w k is the weight coefficient of each partition. By solving this Pareto optimal problem, a set of different Pareto optimal solutions can be obtained, that is, the best compromise between the two objectives of geometry and mechanics. This provides a basis for determining the optimal processing position in the next step.

[0058] The specific implementation of step S90 is: according to the Pareto optimal solution obtained in step S80, determine the final optimal processing position P of the jade carving in the jade opt , as shown in formula (16). This position takes into account both the geometric feature matching degree G(p) and the mechanical feature matching degree L(p). After determining the optimal processing position, the next step is to plan the cutting trajectory. First, according to formula (17), select the optimal position P opt The nearest boundary point with the least stress is used as the cutting entry point E i Then, the cutting trajectory is parameterized and modeled using the B-spline curve, as shown in formula (18), to ensure the smoothness and continuity of the cutting process. At the same time, the exponential decay model is used to model the cutting depth, as shown in formula (19), to ensure the stability of the processing process. In summary, through the above steps S10 to S90, the jade carving processing parameters can be systematically optimized to improve the processing quality and efficiency.

[0059] The following is a description of the formula involved in the calculation process in the specific implementation method:

[0060] 1. Calculation of internal stress distribution of jade

[0061] The calculation formula of the internal stress distribution of the jade is specifically expressed as follows:

[0062]

[0063] In the formula, σ ij is the stress tensor (MPa, 0-500); u i is the displacement component (mm); x j is the spatial coordinate (mm); E is the Young's modulus (GPa, 50-100); λ is the Lame constant (GPa, 20-40); δ ijis the Kronecker function; η is the damping coefficient (0.01~0.1); t is the time variable (s).

[0064] 2. Jade internal stress distribution matrix

[0065] The jade internal stress distribution matrix is ​​specifically expressed as follows:

[0066]

[0067] In the formula, σ ij (i,j=1,2,3) represents stress component (MPa); ε S is the stress measurement error matrix (MPa, ±5%).

[0068] 3. Jade regional division

[0069] The mathematical model of the jade regional division is specifically expressed as follows:

[0070]

[0071]

[0072] In the formula, R k is the kth partition; p is the coordinate of the spatial point; σ(p) is the stress value at point p (MPa); c k is the stress center value of the kth region (MPa); μ k is the clustering error (±2%); |R k | is region R k The number of points included.

[0073] 4. Calculation of mechanical characteristic matrix of jade partition

[0074] The mechanical characteristic matrix calculation formula of the jade partition is specifically expressed as follows:

[0075]

[0076] In the formula, M k is the mechanical characteristic matrix of the kth partition; K IC is the stress intensity factor (MPa·m 1 / 2 );G c is the fracture toughness (J / m 2 ); E is elastic modulus (GPa); ν is Poisson's ratio; H is hardness value (GPa); D is density (g / cm 3 ); φ is the porosity (%); ρ is the crack distribution density (cracks / cm 2 ), θ is the grain orientation (°), I is the material uniformity index, ξ k is the measurement error matrix.

[0077] 5. Calculation of overall jade mechanical characteristic matrix

[0078] The mechanical characteristic matrix calculation formula of the overall jade is specifically expressed as follows:

[0079]

[0080] In the formula, M total is the mechanical characteristic matrix of the whole jade; ω k is the weight coefficient of the kth partition, n is the total number of partitions; Δ is the comprehensive error term.

[0081] 6. Game optimization model

[0082] The objective function of the game optimization model is specifically expressed as follows:

[0083] Player 1 (Spatial Position Optimizer):

[0084]

[0085] Player 2 (Stance Angle Optimizer):

[0086]

[0087] Constraints:

[0088]

[0089] Where, F1, F2 are the objective functions; (x, y, z) are the spatial position coordinates (mm); (α, β, γ) are the Euler angles (rad); M target is the target feature matrix; R(α,β,γ) is the rotation matrix; λ1,λ2 are penalty factors.

[0090] 7. Calculation of geometric feature matching

[0091] The geometric feature matching degree calculation formula is specifically expressed as follows:

[0092] Partition geometry matching:

[0093]

[0094] Overall geometric matching:

[0095]

[0096] In the formula, G k is the geometric matching degree of the kth partition; V k is the partition voxel feature vector; V target is the target voxel feature vector; σ gis the standard deviation of matching; ∈ g is the geometric error term; η k is the partition weight.

[0097] 8. Calculation of mechanical characteristics matching

[0098] The mechanical characteristics matching degree calculation formula is specifically expressed as follows:

[0099] Partition mechanics matching:

[0100]

[0101] Overall mechanical matching:

[0102]

[0103] Where, L k is the mechanical matching degree of the kth partition; ||·|| F is the Frobenius norm; σ m is the standard deviation of matching; ∈ m is the mechanical error term; τ k is the partition weight.

[0104] 9. Multi-objective optimization

[0105] The multi-objective optimization model is specifically expressed as follows:

[0106] Pareto optimality problem:

[0107]

[0108] Constraints:

[0109]

[0110] Where f1(w), f2(w) are the objective functions; w k is the weight coefficient.

[0111] 10. Determination of optimal processing position

[0112] The optimal processing position determination formula is specifically expressed as follows:

[0113] P opt = argmax p∈Ω {w1G(p)+w2L(p)};

[0114] Where, P opt is the optimal processing position; Ω is the feasible domain; G(p), L(p) are the geometric and mechanical matching degrees at position p respectively; w1, w2 are weight coefficients.

[0115] 11. Cutting trajectory planning

[0116] The cutting trajectory planning formula is specifically expressed as follows:

[0117] Entry point selection:

[0118]

[0119] Trajectory planning:

[0120]

[0121] In the formula, E i For the entry point; is the boundary point set; κ is the stress weight coefficient; stress(e) is the stress value at point e; T(t) is the parameterized trajectory curve; is the n-order B-spline basis function; α i is the control point; δ(t) is the trajectory error term.

[0122] 12. Depth control curve generation

[0123] The depth control curve generation formula is specifically expressed as follows:

[0124]

[0125] Where D(s) is the cutting depth function; s is the curve parameter; D0 is the initial depth; β is the attenuation coefficient; γ i is the coefficient; φ i (s) is the basis function; ∈(s) is the depth error term.

[0126] Parameter acquisition method:

[0127] 1) Stress measurement: The change in interplanar spacing is measured by X-ray diffractometer, and the stress is calculated in combination with Hooke's law;

[0128] 2) Mechanical characteristics measurement: using standard experimental methods, including three-point bending test, ultrasonic testing, Vickers hardness test, etc.;

[0129] 3) Geometric feature extraction: 3D scanning and image processing technology are used to obtain voxel features;

[0130] 4) Parameter calibration: Determine various coefficients through least squares method and cross validation.

[0131] Formula construction principle description:

[0132] 1) Stress distribution calculation takes into account elastic deformation, Poisson effect and dynamic response;

[0133] 2) The improved K-means algorithm is used for regional division, and stress gradient constraints are introduced;

[0134] 3) The characteristic matrix is ​​constructed by comprehensively considering multiple physical quantities and adopting a weighted combination method;

[0135] 4) The game optimization model finds the optimal solution through Nash equilibrium;

[0136] 5) The matching degree is calculated using the Gaussian kernel function, taking into account feature similarity;

[0137] 6) Multi-objective optimization uses the Pareto frontier method to balance multiple objectives;

[0138] 7) B-spline curve is used in trajectory planning to ensure smoothness and continuity;

[0139] 8) Depth control uses an exponential decay model to ensure processing stability.

[0140] Improvements over existing technologies:

[0141] 1) Introduce stress distribution analysis to improve processing safety;

[0142] 2) Use game theory methods to optimize position and posture and improve the stability of the solution;

[0143] 3) Consider multi-objective optimization and balance geometric and mechanical characteristics;

[0144] 4) Introduce error terms and constraints to improve model robustness;

[0145] 5) Use parameterized curves to describe trajectory and depth to improve control accuracy.

[0146] The key features of the whole approach are as follows:

[0147] The introduction of technologies such as CT scanning, finite element analysis and micromechanical testing can fully obtain the geometric and mechanical characteristics of the jade.

[0148] By using the game theory optimization method, the optimal processing position and posture of jade can be adaptively determined to improve the processing accuracy.

[0149] Multi-objective optimization that considers both geometric and mechanical objectives can take into account both appearance and performance requirements and achieve comprehensive optimization of jade carving processing.

[0150] Using parametric modeling methods to describe cutting trajectory and depth control can improve processing stability and repeatability.

[0151] The overall method has good universality and can be applied to the optimization of jade processing with various complex structures.

[0152] Specifically, the principle of the present invention is to make full use of the geometric and mechanical characteristics of the jade material itself to achieve scientific optimization of processing parameters. Specifically, the method mainly includes the following key steps:

[0153] 1. Construction of 3D digital model. First, CT scanning is used to obtain the 3D grayscale data inside the jade.

[0154] And use 3D reconstruction algorithm to convert it into a 3D digital model This digital model can accurately reflect the internal structure and appearance characteristics of jade, laying the foundation for subsequent analysis.

[0155] 2. Stress distribution analysis. Based on the 3D mesh model obtained in step 1 Combining X-ray diffraction and strain test data, the finite element method is used to calculate the three-dimensional stress distribution matrix S inside the jade. This stress analysis method based on the physical model can accurately predict the stress state inside the jade during processing and provide a basis for regional division and processing safety assessment.

[0156] 3. Regional division and mechanical feature extraction. Based on the stress distribution matrix S obtained in step 2, the improved K-means algorithm is used to divide the jade into regions, and multiple sub-regions with significant stress characteristics are obtained. Then, the mechanical characteristic matrix M is calculated for each sub-region. k , including key parameters such as stress intensity factor, fracture toughness, elastic modulus, etc. These mechanical characteristic information provides the required input data for subsequent optimization.

[0157] 4. Game optimization and multi-objective decision-making. Based on the mechanical characteristics information extracted in step 3, a two-player game optimization model is constructed. In this model, the first player is the spatial position optimizer and the second player is the posture angle optimizer. Through iterative optimization, the spatial position x that optimizes the overall mechanical characteristics of the jade can be found. * and attitude angle θ * Then, a multi-objective optimization method is used to comprehensively consider the matching degree of geometric features and mechanical features to determine the final optimal processing position p opt .

[0158] 5. Processing trajectory planning. Finally, according to the optimal processing position p obtained in step 4 opt , select the appropriate cutting entry point e i , and the B-spline curve is used to parametrically model the cutting trajectory T(t) to ensure the smoothness and continuity of the cutting process. At the same time, the exponential decay model is used to model the cutting depth D(s) to ensure the stability of the processing process.

[0159] In summary, the jade processing optimization method of the present invention is mainly based on the following three key technical innovations:

[0160] 1. CT scanning and finite element analysis technology were introduced to fully explore the internal geometric and mechanical information of the jade, providing reliable data support for the optimization of processing parameters.

[0161] 2. The game optimization and multi-objective decision-making methods are adopted to achieve a good balance between geometric features and mechanical features, ensuring the simultaneous improvement of processing quality and efficiency.

[0162] 3. Parametric curve modeling technology is used to accurately plan the cutting trajectory and depth control, improving the controllability and stability of the processing process.

[0163] A specific embodiment 1 of the present invention is provided below. The specific implementation of each step in this embodiment 1 is described in detail as follows: The specific implementation of step S10 is as follows:

[0164] First, the jade samples to be processed are scanned using computed tomography (CT) technology. CT scanning can obtain three-dimensional grayscale image data inside the jade, which can more accurately describe the internal structure and appearance of the jade. The spatial resolution of CT scanning can usually reach about 0.1 mm, which is enough to capture the subtle structural information inside the jade.

[0165] The three-dimensional grayscale data obtained by CT scanning is then converted into a three-dimensional digital model using a three-dimensional reconstruction algorithm. Methods such as the marching cubes algorithm based on voxels or the triangular patch reconstruction algorithm based on point clouds can be used here. Specifically, the original three-dimensional grayscale data is spatially discretized and topologically connected to obtain a three-dimensional digital model composed of a large number of triangular patches. The three-dimensional digital model It can describe the internal structure and appearance characteristics of the jade to be processed more accurately.

[0166] In summary, step S10 obtains a three-dimensional digital model of the internal structure of the jade through CT scanning and three-dimensional reconstruction technology. This lays the foundation for subsequent meshing and stress analysis.

[0167] The specific implementation of step S20 is as follows:

[0168] The three-dimensional digital model of jade obtained in step S10 First, it needs to be meshed and discretized. Here, an unstructured meshing method based on tetrahedron or hexahedron is used to divide the original continuous three-dimensional model into Discretize into a discrete model composed of a large number of unit grids

[0169] Specifically, the grid division process is as follows: Let the grid unit in the three-dimensional space be Ω e , it can be expressed as:

[0170]

[0171] Among them, N e is the total number of grid cells. Each grid cell Ω e Internally, define a finite number of nodes x i ,i=1,2,…,N p , where N p is the total number of nodes. By determining the position and node coordinates of each grid unit, the discretized grid model of jade can be constructed.

[0172] The size of the grid unit is usually controlled between 0.5-2 mm, which can fully capture the stress distribution characteristics inside the jade. The result of grid division is to obtain the three-dimensional grid unit information inside the jade. Lay the foundation for subsequent stress analysis.

[0173] The specific implementation of step S30 is as follows:

[0174] The jade mesh model obtained in step S20 The stress distribution inside the jade is calculated by combining the experimental data collected by X-ray diffractometer and strain gauge.

[0175] Specifically, the change in the interplanar spacing Δd of the crystal grains inside the jade is first measured using an X-ray diffractometer, and the stress component σ at the corresponding position can be calculated using the following relationship:

[0176]

[0177] Among them, E is Young's modulus, v is Poisson's ratio, and d0 is the initial interplanar spacing. At the same time, strain gauges are attached to the surface of jade, and the surface strain value ε is obtained through strain testing, and then the internal stress component σ is estimated using the inverse problem solving method.

[0178] The stress data obtained by X-ray diffraction and strain testing are combined with the following stress distribution calculation formula, and the finite element method or finite difference method is used to numerically simulate the three-dimensional stress field inside the jade to obtain the stress distribution matrix S:

[0179]

[0180] Among them, σ ij is the stress tensor component (unit: MPa), εS is the stress measurement error matrix (unit: MPa).

[0181] The stress distribution matrix S contains the stress component information of each grid unit inside the jade, laying the foundation for subsequent regional division.

[0182] The specific implementation of step S40 is as follows:

[0183] According to the jade internal stress distribution matrix S obtained in step S30, the improved K-means clustering algorithm is used to divide the jade into regions. The specific process is as follows:

[0184] First, the stress component σ(x) inside the jade is regarded as a eigenvector, where x is the spatial coordinate of the grid unit. Then, the K-means algorithm is used to cluster these eigenvectors to obtain K stress centers c k and its corresponding K regions As shown below:

[0185]

[0186] in, For Region The number of grid cells included, μ k is the clustering error.

[0187] Different from the standard K-means algorithm, the stress gradient ||σ(x)-c is introduced here. k || is used as a clustering criterion to ensure that the stress difference between adjacent regions is large enough to better reflect the stress distribution characteristics inside the jade.

[0188] Through this area division method, the original continuous jade model can be Divided into multiple sub-regions with distinct stress characteristics Lay the foundation for subsequent mechanical analysis and optimization.

[0189] The specific implementation of step S50 is as follows:

[0190] For each jade partition obtained in step S40 Calculate the mechanical characteristic matrix M k . Mechanical characteristic matrix M k Contains the following 10 key mechanical parameters: Stress intensity factor K IC (Unit: MPa·m 1 / 2 ) ; fracture toughness G c (Unit: J / m 2 ); elastic modulus E (unit: GPa); Poisson's ratio v; hardness H (unit: GPa); density ρ (unit: g / cm3 ); porosity φ (unit: %); crack density ρ c (Unit:pcs / cm 2 ); grain orientation θ (unit: degree); material uniformity index I;

[0191] The specific calculation formula is as follows:

[0192]

[0193] Among them, k is the measurement error matrix. These mechanical parameters are obtained through standard experimental methods (such as three-point bending test, ultrasonic testing, Vickers hardness test, etc.).

[0194] In calculating the mechanical characteristic matrix M of each partition k At the same time, the mechanical characteristic matrix M of the whole jade is also calculated. total , as shown below:

[0195]

[0196] Among them, ω k is the weight coefficient of the kth partition (satisfying ), Δ is the comprehensive error term.

[0197] The calculation results of the above mechanical characteristic matrix provide the required internal mechanical information of jade for the subsequent game optimization model.

[0198] The specific implementation of step S60 is as follows:

[0199] The mechanical characteristic matrix M of each partition calculated in step S50 k and the overall jade mechanical characteristic matrix M total , a two-player game optimization model is constructed. In this model, the first player is a spatial position optimizer, whose strategy space is the three-dimensional spatial coordinate x = (x, y, z); the second player is a posture angle optimizer, whose strategy space is the Euler angle θ = (α, β, γ).

[0200] The objective functions of the two players are:

[0201]

[0202] Among them, M target is the target mechanical characteristic matrix, R(θ) is the rotation matrix, C1(x) and C2(θ) are the constraints of spatial position and attitude angle, and λ1 and λ2 are penalty factors.

[0203] The solution of the game optimization model adopts an iterative optimization method, that is, in each iteration, the strategy of one player is fixed alternately, while the strategy of the other player is optimized, until the change of the strategies and payment functions of both parties is less than the preset threshold, the iteration is stopped. Through this game optimization method, the spatial position x that makes the overall mechanical properties of the jade optimal can be found. * and attitude angle θ * .

[0204] The specific implementation of step S70 is as follows:

[0205] The optimal spatial position x obtained in step S60 * and attitude angle θ * , calculate the geometric feature matching degree G of each partition respectively k The matching degree G of the geometric characteristics of the whole jade total , and the mechanical characteristics matching degree L of each partition k The matching degree of mechanical characteristics with the whole jade L total .

[0206] The geometric feature matching degree is calculated as follows:

[0207]

[0208]

[0209] Among them, V k For partition The voxel feature vector, V target is the target voxel feature vector, σ g is the standard deviation of matching,∈ g is the geometric error term, η k is the partition weight.

[0210] The calculation of mechanical characteristics matching is as follows:

[0211]

[0212]

[0213] Among them,||·|| F is the Frobenius norm, σ m is the standard deviation of matching,∈ m is the mechanical error term, τ k is the partition weight.

[0214] Through this matching evaluation method, the geometric and mechanical characteristics of jade can be comprehensively considered, providing a basis for subsequent multi-objective optimization.

[0215] The specific implementation of step S80 is as follows:

[0216] Based on the geometric feature matching degree and mechanical feature matching degree calculated in step S70, a multi-objective optimization problem is established as follows:

[0217]

[0218] Where w=(w1,w2,…,w K ) is the weight coefficient of each partition (satisfying ).

[0219] The two objective functions of this problem are to maximize the overall geometric matching degree f1(w) and to maximize the overall mechanical matching degree f2(w). By solving this Pareto optimal problem, a set of different Pareto optimal solutions can be obtained, that is, the best compromise between the two objectives of geometry and mechanics. This provides a basis for determining the optimal processing position in the next step.

[0220] The specific implementation of step S90 is as follows:

[0221] According to the Pareto optimal solution obtained in step S80, the final optimal processing position p of the jade carving in the jade is determined. opt , as shown below:

[0222] p opt = argmax p∈Ω {w1G(p)+w2L(p)};

[0223] Among them, Ω is the feasible domain, G(p) and L(p) are the geometric and mechanical matching degrees at position p, respectively, and w1 and w2 are the corresponding weight coefficients. opt At the same time, the optimal matching of geometric characteristics and mechanical characteristics is taken into account.

[0224] Determine the optimal processing position p opt After that, the cutting trajectory needs to be planned. First, select the optimal position p according to the following formula. opt The nearest boundary point with the least stress is e i As a cutting entry point:

[0225]

[0226] in, is the boundary point set, σ(e) is the stress value at point e, and κ is the stress weight coefficient.

[0227] Then, the cutting trajectory T(t) is parameterized using the B-spline curve as shown below:

[0228]

[0229] in, is the nth-order B-spline basis function, α i is the control point, and δ(t) is the trajectory error term. This ensures the smoothness and continuity of the cutting process.

[0230] At the same time, the exponential decay model is used to model the cutting depth D(s), as shown below:

[0231]

[0232] Among them, s is the curve parameter, D0 is the initial depth, β is the attenuation coefficient, γ i is the coefficient, φ i (s) is the basis function, ∈(s) is the depth error term. This can ensure the stability of the machining process.

[0233] In order to further better understand and implement the present invention, Example 2 of a specific application scenario of the present invention is provided below: a carving team needs to carve a jade stone to obtain a jade carving.

[0234] First, the carving team used a high-precision computed tomography (CT) device to conduct a comprehensive scan of the jade. The three-dimensional grayscale data obtained from the scan showed that there were many structural defects such as fine cracks and uneven distribution of grain boundaries inside the jade. Through the three-dimensional reconstruction algorithm, the original grayscale data was converted into a three-dimensional digital model composed of tetrahedral grid units. As shown in Table 1. The average side length of the grid unit is controlled at about 1.5 mm, which can accurately capture the detailed structure inside the jade.

[0235] Table 1 Jade 3D mesh model information

[0236] Number of grid cells Number of nodes Minimum side length Maximum side length Average side length 112,456 21,386 0.8mm 2.1mm 1.5mm

[0237] Based on the above three-dimensional mesh model The carving team used the finite element analysis method, combined with X-ray diffraction and strain test data, to calculate the three-dimensional stress distribution matrix S inside the jade. Among them, the X-ray diffraction test results show that the relative change Δd / d0 of the grain spacing inside the jade is within the range of ±0.05; the strain gauge test gives the strain value ε on the surface of the jade within the range of ±0.002. Substituting these experimental data into the stress calculation formula, the stress distribution matrix S shown in Table 2 can be obtained. It can be seen that there is a local stress concentration area inside the jade, and the maximum principal stress value is as high as 350MPa, which poses a potential threat to the subsequent processing safety.

[0238] Table 2. Jade internal stress distribution matrix S;

[0239]

[0240] According to the regional division method in step S40, the carving team used the improved K-means algorithm to partition the stress characteristics inside the jade. Specifically, the stress component σ(x) of the grid unit was first regarded as a feature vector, and then clustered using the K-means algorithm to obtain 9 sub-regions with significant stress characteristics. As shown in Table 3. The stress center value c of each sub-area k and the number of grid cells included It can be seen from the table that the stress difference between adjacent sub-regions is large, which is beneficial to the subsequent mechanical properties analysis.

[0241] Table 3 Results of zoning of internal stress characteristics of jade

[0242]

[0243] Next, the carving team focused on each sub-area The mechanical characteristic parameters were tested respectively, and the mechanical characteristic matrix M was formed. k The test results are shown in Table 4, including the stress intensity factor K IC , fracture toughness G c , elastic modulus E, Poisson's ratio v, hardness H, density ρ, porosity φ, crack density ρ c , grain orientation θ and material It can be seen that there are great differences in the mechanical properties of different sub-regions, which is consistent with the stress distribution characteristics mentioned above. At the same time, the carving team also calculated the mechanical characteristic matrix M of the overall jade. total , as a reference for subsequent optimization.

[0244] Table 4 Mechanical characteristic matrix M of jade sub-region k ;

[0245]

[0246] Based on the geometric and mechanical feature information obtained above, the carving team constructed a two-player game optimization model to determine the optimal processing position and posture of the jade. The first player is the spatial position optimizer, whose strategy space is the three-dimensional coordinates (x, y, z); the second player is the posture angle optimizer, whose strategy space is the Euler angle (α, β, γ). The objective functions of the two players are:

[0247] Player 1 (Spatial Position Optimizer):

[0248]

[0249] Player 2 (Stance Angle Optimizer):

[0250]

[0251] Among them, M target is the target mechanical characteristic matrix, R(α, β, γ) is the rotation matrix, C1 and C2 are the corresponding constraints, and λ1 and λ2 are the penalty factors. Through iterative optimization, the carving team finally determined the spatial position x that optimizes the overall mechanical properties of the jade. * =(123.4mm,85.7mm,42.1mm) and attitude angle θ * =(1.28rad,0.82rad,1.35rad).

[0252] With the optimal spatial position and posture angle, the carving team then calculated the geometric feature matching degree G of each sub-area. k And the mechanical characteristics matching degree L k , and the geometric feature matching degree G of the whole jade total And the mechanical characteristics matching degree L total ,The specific results are shown in Table 5. It can be seen that and The two sub-areas are closest to the target features in terms of both geometric and mechanical characteristics, and therefore are the best processing areas. Overall, the geometric matching degree G total Reached 0.92, mechanical matching degree L total It also reached 0.89, indicating that the selected processing position and posture can better meet the appearance and performance requirements of jade carving.

[0253] Table 5 Jade processing position matching evaluation results

[0254]

[0255] Finally, the carving team planned the cutting trajectory and depth control curve for jade processing based on the above optimization results. First, select the optimal processing position p opt =(123.4mm,85.7mm,42.1mm) The nearest boundary point with the least stress e i = (124.2mm, 86.1mm, 41.8mm) as the cutting entrance. Then, the cutting trajectory T(t) is parameterized using the B-spline curve as shown below:

[0256]

[0257] in, is the 5th degree B-spline basis function, α iis the control point, and δ(t) is the trajectory error term. This ensures the smoothness and continuity of the cutting process.

[0258] At the same time, for the cutting depth D(s), the engraving team adopted the following exponential decay model:

[0259]

[0260] Among them, s is the curve parameter, γ i is the coefficient, φ i (s) is the basis function, and ∈(s) is the depth error term. This can ensure the stability of the machining process and avoid further damage caused by excessive cutting.

[0261] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for optimizing jade carving processing parameters based on the characteristics of jade material itself, characterized in that: The following steps are involved: S10, obtaining a computerized tomography image of the jade and establishing a three-dimensional digital model of the jade; S20, meshing the three-dimensional digital model to obtain mesh units of jade; S30, calculating the internal stress distribution of the jade based on the grid unit and the data collected by the X-ray diffractometer and the strain gauge to obtain the internal stress distribution matrix of the jade; S40, dividing the jade into regions according to the internal stress distribution matrix of the jade to obtain a plurality of jade partitions; S50, calculating the mechanical characteristic matrix of each jade partition and the mechanical characteristic matrix of the whole jade, wherein each element in the mechanical characteristic matrix represents the mechanical characteristics of the corresponding position, and the mechanical characteristics include stress intensity factor, fracture toughness, elastic modulus, Poisson's ratio, hardness value, density, porosity, crack distribution density, grain orientation, and material uniformity index; S60, constructing a game optimization model according to the mechanical characteristic matrix of each jade partition and the mechanical characteristic matrix of the whole jade, wherein the first player is a spatial position optimizer, the strategy space is a three-dimensional coordinate (x, y, z), and the second player is a posture angle optimizer, and the strategy space is Euler angle (α, β, γ); S70, solving the game optimization model by iterative optimization, specifically, in each iteration, alternately fixing the strategy of one player while optimizing the strategy of another player, until the strategy change amount and the payment function change amount are both less than a preset threshold, and then stopping the iteration, and outputting the optimal spatial position and posture angle; S80, based on the optimal spatial position and posture angle, respectively calculating the geometric feature matching degree of each partition and the geometric feature matching degree of the overall jade, as well as the mechanical feature matching degree of each partition and the mechanical feature matching degree of the overall jade, establishing a partition matching degree objective function and an overall matching degree objective function, and using the Pareto optimal method to perform multi-objective weight optimization; S90. Determine the final optimal processing position of the jade carving in the jade according to the multi-objective optimization result. Based on the optimal processing position, determine the cutting entry point and plan the cutting trajectory. Meanwhile, calculate the depth value of each cutting point and generate a depth control curve.

2. A method for optimizing jade carving processing parameters based on jade material characteristics according to claim 1, characterized in that: The step S10 specifically includes: using computer tomography to perform spatial scanning on the jade sample to obtain three-dimensional grayscale image data inside the jade, the spatial resolution of the computer tomography is set to 0.1 mm, and the three-dimensional grayscale image data includes internal structure information and external shape information of the jade; using a voxel isosurface extraction algorithm or a point cloud triangle patch reconstruction algorithm to process the three-dimensional grayscale image data to establish a three-dimensional digital model of the jade, and the three-dimensional digital model contains complete geometric information and internal structure information of the jade.

3. a kind of jade carving processing parameter optimization method based on jade material own characteristics according to claim 2, it is characterized in that, The step S20 specifically includes: performing grid discretization processing on the three-dimensional digital model of the jade, dividing the three-dimensional digital model of the jade into multiple grid units using a tetrahedron unstructured grid division method or a hexahedron unstructured grid division method, wherein the size of the grid unit is set between 0.5 mm and 2 mm, the number of the grid units is determined according to the volume of the jade, and the three-dimensional grid unit information inside the jade is obtained through the grid units.

4. A method for optimizing jade carving processing parameters based on jade material characteristics according to claim 3, characterized in that: The step S30 specifically includes: using an X-ray diffractometer to measure the change in the interplanar spacing of crystal grains inside the jade, and calculating the internal stress components of the jade according to Hooke's law; pasting strain gauges on the surface of the jade, and obtaining the surface strain value of the jade through strain testing; using a reverse algorithm to estimate the internal stress components of the jade according to the surface strain value of the jade; combining the X-ray diffraction measurement data and the strain test data with a stress distribution calculation formula, and using a finite element method or a finite difference method to perform numerical simulation on the three-dimensional stress field inside the jade to obtain a stress distribution matrix.

5. A method for optimizing jade carving processing parameters based on jade material characteristics according to claim 4, characterized in that: The step S40 specifically includes: taking the internal stress components of the jade as feature vectors, each feature vector corresponding to the spatial coordinates of the grid unit; clustering the feature vectors using an improved K-means clustering algorithm, introducing stress gradient as a clustering criterion to ensure that the stress difference between adjacent areas meets a preset threshold; and dividing the jade into multiple areas according to the clustering results, each area having similar stress characteristics.

6. A method for optimizing jade carving processing parameters based on jade material characteristics according to claim 5, characterized in that: The step S50 specifically includes: obtaining the mechanical parameters of each jade partition through a three-point bending test, ultrasonic testing and Vickers hardness test; calculating the mechanical characteristic matrix of each jade partition, the mechanical characteristic matrix including stress intensity factor, fracture toughness, elastic modulus, Poisson's ratio, hardness value, density, porosity, crack distribution density, grain orientation and material uniformity index; determining a weight coefficient according to the volume proportion of the jade partition; and using the weight coefficient to calculate the mechanical characteristic matrix of the entire jade.

7. A method for optimizing jade carving processing parameters based on jade material characteristics according to claim 6, characterized in that: The step S60 specifically includes: constructing a two-player game optimization model, in which the first player is a spatial position optimizer, and the strategy space is a three-dimensional coordinate, and the second player is a posture angle optimizer, and the strategy space is an Euler angle; establishing a player objective function to minimize the difference between the mechanical characteristic matrix of each jade partition and the target characteristic matrix; setting spatial position constraints and posture angle constraints; and constructing a payment function to reflect the degree of influence of the player's strategy selection on the optimization target.

8. A method for optimizing jade carving processing parameters based on the characteristics of jade material itself according to claim 7, characterized in that, The step S70 specifically includes: alternately fixing the strategy of one player and optimizing the strategy of another player in each iteration; calculating the strategy change amount and the payment function change amount after each iteration; stopping the iteration when the strategy change amount and the payment function change amount are both less than a preset threshold; and outputting the optimal spatial position coordinates and the optimal posture angle.

9. A method for optimizing jade carving processing parameters based on jade material characteristics according to claim 8, characterized in that: The step S80 specifically includes: using the Gaussian kernel function to calculate the geometric feature matching degree and mechanical feature matching degree of each jade partition according to the optimal spatial position and the optimal posture angle; using the Gaussian kernel function to calculate the geometric feature matching degree and mechanical feature matching degree of the entire jade; establishing a partition matching degree objective function and an overall matching degree objective function; and using the Pareto optimal method to perform multi-objective optimization to obtain a set of optimal solutions.

10. A method for optimizing jade carving processing parameters based on the characteristics of jade material itself according to claim 9, characterized in that: The step S90 specifically includes: determining the final optimal processing position of the jade carving in the jade according to the Pareto optimal solution; selecting the boundary point closest to the final optimal processing position and with the lowest stress as the cutting entry point; using the B-spline curve to parameterize the cutting trajectory modeling; using the exponential decay model to calculate the cutting depth; generating the cutting trajectory and the depth control curve.

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