Method for collecting and analyzing surface topography data of copper electrode for nickel sheet convex hull stamping

Abstract

The invention provides a method for acquiring and analyzing surface topography data of a copper foil for nickel sheet convex hull stamping, which comprises the following steps: acquiring initial geometric parameters and material flow characteristic data of a nickel sheet, and analyzing the bidirectional tensile stress concentration degree of a bottom fillet area through stress distribution when the height of a convex hull is increased to obtain a strain concentration index of the bottom fillet area; according to the strain concentration index of the bottom fillet area, determining fillet radius configuration corresponding to the deformation stage through a genetic algorithm; extracting the metal transfer rate of the flange area from the corrected fillet radius configuration, simulating material flow balance from the flange area to the convex hull area, and determining a predicted value of the thinning degree of the bottom of the convex hull; and according to the optimized punch stroke parameters, the risk that microscopic cracks are generated and expanded along the grain boundary is evaluated, and a dynamic punching control sequence is generated.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a method for acquiring and analyzing the surface morphology data of copper electrodes used in nickel sheet stamping. Background Technology

[0002] Nickel sheet, as a highly conductive and ductile metallic material, plays a crucial role in electronic devices, battery connections, and thermal management, especially in bump forming processes where it is widely used to achieve reliable electrical connections and efficient heat dissipation channels. Current stamping processes, in pursuit of higher bump heights to meet functional requirements, face a fundamental contradiction between material ductility and forming depth. Traditional methods increase bump height by simply increasing the punch stroke, but this static, single-loading approach ignores the differences in material flow characteristics at different deformation stages, resulting in excessively high bidirectional tensile stress in the rounded corner area at the bottom of the bump. During stamping, an increase in bump height inevitably leads to a sharp increase in strain concentration in the rounded corner area, while the corner radius, a key geometric parameter for controlling stress concentration, is fixed in traditional processes. This fixed fillet design obstructs material flow, resulting in insufficient metal transfer from the flange area to the bulge area, causing severe local thinning. The flange area refers to the outer flat plate portion of the stamped part that has not yet entered the die cavity or undergone significant plastic deformation, typically located in the area pressed by the die's blank holder. The bulge area refers to the three-dimensional raised structure formed by the sheet metal being lifted by the punch during stamping. Simultaneously, because the fillet radius cannot be dynamically adjusted with the deformation process, when the ratio of the bulge height to the fillet radius exceeds a critical point, the local strain rate rapidly exceeds the uniform elongation limit of the nickel material. Microcracks initiate along the grain boundaries and propagate rapidly, ultimately leading to bulge cracking. For example, when producing high-convexity nickel sheet bumps, if it is desired to increase the bulge height from 1.0mm to over 1.5mm, the stress concentration in the bottom fillet area will cause the material to reach fracture strain in a very short time, resulting in direct failure of the forming process. This contradiction between height and ductility makes it difficult for traditional stamping to overcome physical limits. Summary of the Invention

[0003] This invention provides a method for acquiring and analyzing the surface morphology data of copper electrodes used in nickel sheet embossing, mainly including: The initial geometric parameters and material flow characteristics of the nickel sheet are obtained. The stress distribution as the bulge height increases is analyzed to determine the biaxial tensile stress concentration in the bottom rounded corner region, yielding a strain concentration index for this region. Based on this index, a genetic algorithm is used to determine the rounded corner radius configuration corresponding to the deformation stage. It is then determined whether any point in the rounded corner radius configuration exceeds the material's uniform elongation limit. If so, the genetic algorithm parameters are iteratively adjusted to obtain a corrected rounded corner radius configuration; otherwise, the process proceeds directly to the next step of material flow optimization analysis. The metal transfer rate in the flange area is extracted from the corrected rounded corner radius configuration, and the material flow balance from the flange area to the bulge area is simulated to determine the predicted value of the bulge bottom thinning degree. For the predicted bulge bottom thinning degree, the punch stroke and rounded corner radius are correlated to determine if the high convexity requirement is met. If not, a particle swarm optimization algorithm is repeatedly executed to obtain optimized punch stroke parameters. Based on the optimized punch stroke parameters, the risk of microcrack initiation and propagation along grain boundaries is assessed, generating a dynamic stamping control sequence.

[0004] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses a method for acquiring and analyzing the surface morphology data of copper electrodes used in nickel sheet bulge stamping. Addressing the business scenario problems of thinning at the bottom of the bulge, stress concentration, and the risk of microcrack initiation during nickel sheet stamping, it solves the challenges of strain concentration and material flow balance in the bottom rounded corner region through multi-stage optimization design. First, this invention optimizes the rounded corner radius configuration through stress distribution analysis and a genetic algorithm, and sets a transition buffer based on strain abrupt change points, progressively adjusting the rounded corner radius to reduce strain concentration. Second, it uses the balance simulation of material transfer rate in the flange area and volume increment in the bulge area to predict the degree of bottom thinning, and adjusts the punch stroke parameters through a particle swarm optimization algorithm. Finally, it simulates stress changes during the dynamic stamping process, assesses the risk of crack propagation, and generates a precise control sequence. Through multi-dimensional optimization and dynamic simulation, this invention ensures material uniformity and structural reliability under high-convexity forming, significantly improving the stability and product consistency of batch manufacturing. Attached Figure Description

[0005] Figure 1 This is a flowchart illustrating a method for acquiring and analyzing the surface morphology data of a copper electrode used in nickel sheet stamping for embossing, according to the present invention. Detailed Implementation

[0006] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0007] like Figure 1 This embodiment of a method for collecting and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing can specifically include: S101. Obtain the initial geometric parameters and material flow characteristics of the nickel sheet. Analyze the stress distribution as the convex height increases to determine the degree of bidirectional tensile stress concentration in the bottom rounded corner area and obtain the strain concentration index of the bottom rounded corner area.

[0008] A laser thickness gauge was used to perform a gridded scan of the nickel sheet to obtain a thickness distribution cloud map. Grain boundary distribution characteristics were collected using electron backscatter diffraction (ESD). A material constitutive equation was constructed based on the correlation between grain boundary density and yield strength. The material hardening index and flow resistance coefficient were extracted from this constitutive equation. The flow resistance coefficient is defined as the stress parameter that resists metal flow during plastic deformation. As the stamping speed gradually increases from the initial speed to a preset upper speed limit, digital image correlation (DIC) technology was used to capture the deformation gradient field during bulge forming. The stress tensor components of each grid node were calculated based on the flow resistance coefficient and the material hardening index. The degree of plastic deformation in the bottom fillet curvature variation region was determined using the Von Mises yield criterion. The degree of plastic deformation was characterized by the ratio of equivalent plastic strain to the material's ultimate strain. For areas where the degree of plastic deformation exceeds a preset threshold, the thinning rate value and the biaxial tensile stress ratio of the corresponding nodes are extracted. If the thinning rate value is greater than the preset thinning limit value, it is marked as a high-risk area. The strain concentration index of the bottom rounded corner area is calculated by the strain concentration factor. The strain concentration index is equal to the ratio of the maximum principal strain to the average strain in the high-risk area.

[0009] In one embodiment, a laser thickness gauge scans the surface of a nickel sheet point by point using a high-frequency laser beam, dividing the sheet into several measurement units according to a preset grid density. The size of each unit is determined according to the nickel sheet specifications, which is 0.5 mm × 0.5 mm. After the laser pulse emitted by the laser thickness gauge penetrates the nickel sheet, the precise thickness value of each grid node is calculated based on the laser's time-of-flight difference, forming a three-dimensional cloud map data containing thickness distribution information.

[0010] Specifically, electron backscatter diffraction (ESD) is used to characterize the microstructure of nickel sheets using scanning electron microscopy. The diffraction pattern generated by the interaction between the electron beam and the crystal lattice reflects grain orientation information. By analyzing the Kikuchi band width and intersection angle, the boundary distribution between different grains is identified. Grain boundary density is defined as the total length of grain boundaries per unit area. According to the Hall-Petch relation, grain boundary density is positively correlated with the yield strength of the material. The constitutive equation of the material is expressed using the Hollomon power-law hardening model. Where K is the flow resistance coefficient and n is the material hardening exponent, these parameters are obtained by fitting experimental stress-strain curves. Digital image correlation technology continuously acquires speckle images of the convex surface during the stamping process, and calculates the deformation gradient tensor F by tracking the speckle displacement field. Based on the flow resistance coefficient K and the material hardening exponent n, the Cauchy stress tensor is calculated using the deformation gradient tensor. The Von Mises yield criterion uses equivalent stress. With material yield strength Comparative judgment of plastic deformation, when When the material enters a plastic flow state, the degree of plastic deformation is measured by the accumulation of equivalent plastic strain. With material limit strain The ratio is quantitatively represented.

[0011] Preferably, the identification of high-risk areas in the bottom rounded corner region is based on the determination of the thinning rate threshold, which is defined as the percentage of thickness reduction to the initial thickness. The strain concentration index is obtained by calculating the ratio of the maximum principal strain ε1 in the high-risk area to the average strain εavg in that area, and this index reflects the degree of local strain concentration.

[0012] S102. Based on the strain concentration index of the bottom rounded corner area, determine the rounded corner radius configuration corresponding to the deformation stage through a genetic algorithm.

[0013] A fitness function is constructed based on strain concentration indices. This fitness function is defined as a weighted combination of fillet radius and strain distribution uniformity. The weights are determined using initial experimental data, with fillet radius weight set to 0.6 and strain distribution uniformity weight set to 0.4. The weight ratios are dynamically adjusted based on the fitness difference; the larger the difference, the greater the fillet radius weight, with an adjustment increment of 0.1. The strain distribution uniformity is obtained by calculating the standard deviation of strain values ​​at each node. Fillet radii at different deformation stages are expressed using binary encoding, with each gene locus corresponding to a fillet radius value at a deformation stage. A preset population size is set for candidate solutions. A roulette wheel selection operator is used to select superior individuals from the population based on the proportion of individual fitness values ​​to the total fitness. A crossover operation is performed on these superior individuals. The crossover operator uses a single-point crossover method, exchanging parent chromosome segments at random crossover points. New solutions are generated by randomly perturbing gene loci based on mutation probabilities. An elite retention mechanism is used to preserve the individual with the highest fitness value in each generation. The fitness value of this individual is calculated, and it is determined whether the fitness value exceeds a preset target threshold and whether the fillet radius is within the allowable range for material processing. If the fitness value meets the target threshold and the fillet radius is within the allowable range, then the fillet radius configuration sequence corresponding to the current best individual is output. The configuration sequence includes the fillet radius values ​​for each deformation stage. If the fitness value is not met, the pressure coefficient is adjusted according to the fitness difference, and the evolution continues by increasing the number of iterations until a fillet radius configuration that meets the constraints is obtained.

[0014] In one implementation, the fitness function is constructed based on the strain distribution characteristics during the nickel sheet stamping process. The strain distribution uniformity is quantified by calculating the standard deviation of the strain values ​​of all grid nodes within the bottom rounded corner region; a smaller standard deviation indicates a more uniform strain distribution and more stable material flow. The fitness function uses a linear weighted approach to combine the rounded corner radius rationality and strain uniformity, with the weighting coefficients dynamically adjusted based on the ratio of the nickel sheet thickness to the bulge height.

[0015] Specifically, the chromosome encoding in the genetic algorithm uses a binary string structure, with each chromosome representing a complete set of rounded corner radius configurations. The chromosome length is determined by the number of transformation stages, with each 8-bit binary gene corresponding to a rounded corner radius value for one transformation stage. This is mapped to the actual range of rounded corner radius values ​​through a binary-to-decimal conversion. The initial population is constructed using a combination of random generation and empirical values ​​to ensure the diversity of the solution space. The selection probability of the roulette wheel selection operator is proportional to the individual's fitness value. The proportion of each individual's fitness value to the total fitness of the population is calculated, forming a cumulative probability distribution. Parent individuals are selected by generating random numbers within this cumulative probability interval. This selection mechanism ensures that individuals with high fitness have a greater probability of being selected for reproduction, while preserving the survival opportunities of individuals with lower fitness, thus maintaining population diversity.

[0016] Preferably, the single-point crossover operation sets crossover points at random locations on the parent chromosomes, and the gene segments after exchanging crossover points form offspring. The mutation operation flips gene positions according to a preset mutation probability, i.e., 0 becomes 1 or 1 becomes 0, introducing new gene combinations to explore uncovered solution spaces. The elite preservation mechanism directly replicates the best individuals from each generation to the next, preventing the loss of superior genes.

[0017] In one embodiment, convergence is determined using a dual standard: the fitness value must exceed a preset target threshold of 0.85, and the fillet radius must be within the range allowed by the nickel sheet material processing technology. If the convergence conditions are not met, the evolutionary direction of the population is changed by adjusting the selection pressure coefficient. The selection pressure coefficient is adaptively adjusted based on the difference between the current fitness and the target value; the larger the difference, the stronger the selection pressure, thus accelerating the convergence process.

[0018] Based on the strain concentration index of the bottom rounded corner region, the safe strain boundary of the bottom rounded corner region under different convex hull heights is determined. The safe strain boundary is divided into multiple deformation stage intervals. Based on the strain characteristics of each deformation stage interval, strain abrupt change points are identified. Rounded corner radius transition buffers are set before and after the abrupt change points to determine the rounded corner radius configuration corresponding to the deformation stage.

[0019] Based on the strain concentration index of the bottom rounded corner region, strain distribution data at each convex hull height is extracted. The critical strain value is determined by the change in the slope of the stress-strain curve. The critical strain value is defined as the ultimate strain between the material's yield point and fracture point. A piecewise linear mapping is used to construct the correspondence between the convex hull height and the safe strain boundary. Each mapping interval corresponds to a deformation stage, obtaining the allowable strain range for different deformation stages. The allowable strain range is discretized at preset intervals. The ratio of the strain difference to the height difference between adjacent discrete points is calculated as the strain gradient. If the ratio of the strain gradient between adjacent intervals exceeds a preset threshold, it is marked as a strain abrupt change point. A transition buffer is formed by extending a predetermined height before and after the abrupt change point. The width of the buffer is determined according to the magnitude of the strain gradient ratio. A cubic spline interpolation function is constructed within the transition buffer. By setting boundary conditions, the first derivative of the interpolation function is made continuous at the start and end points of the buffer. The rounded corner radius value corresponding to each discrete point in the buffer is calculated based on the interpolation function. A gradual adjustment is used to smoothly transition the rounded corner radius from the start value to the end value of the buffer. The gradual adjustment is achieved by controlling the radius increment between adjacent points. Based on the fillet radius value sequence, a complete fillet radius configuration table is generated by combining the critical strain values ​​of each deformation stage. The configuration table records the fillet radius value corresponding to each convex height and its applicable strain range. The fillet radius is adjusted in stages during the stamping process through the configuration table.

[0020] In one implementation, strain distribution data is extracted based on real-time monitoring of the nickel sheet stamping process. A high-density strain gauge array is arranged in the bulge forming area, with each strain gauge spaced 2 mm apart, to collect strain data in real time at different bulge heights. The strain distribution data includes three components: radial strain, circumferential strain, and thickness strain. The stress-strain curve of the material is obtained through uniaxial tensile testing. The slope of the curve remains constant in the elastic stage and gradually decreases after entering the plastic stage. The critical strain value is located at the inflection point where the curve slope begins to drop sharply, corresponding to the critical state where microcracks begin to initiate within the material. By conducting destructive tests on multiple sets of nickel sheet samples, the distribution range of critical strain values ​​for nickel sheets of different thicknesses is statistically obtained, and an empirical relationship between nickel sheet thickness and critical strain value is established.

[0021] Specifically, the construction process of the piecewise linear mapping involves partitioning the convex hull height. Based on the typical height range of 0.5 mm to 2.0 mm for nickel sheet convex hull forming, it is divided into 15 height intervals at 0.1 mm intervals. Each height interval corresponds to a deformation stage, and a mapping relationship between the convex hull height and the safety strain boundary within that interval is established using a linear interpolation method. The safety strain boundary is defined as the critical strain value multiplied by a safety factor, which is selected between 0.6 and 0.8 based on the operating conditions of the nickel sheet. The mapping relationship is expressed as a piecewise function, where the slope of each function reflects the strain growth rate of that deformation stage. The discretization of the allowable strain range uses an equally spaced sampling method, with the sampling interval set to a height increment of 0.02 mm. The strain value is calculated at each discrete point, and the local strain gradient is obtained by dividing the strain difference between two adjacent points by the height difference. The physical meaning of the strain gradient reflects the severity of material deformation; a larger gradient value indicates more severe strain concentration in that region. By calculating the ratio of the strain gradients between adjacent intervals, a strain abrupt change point is identified when the ratio exceeds 1.5. Identifying abrupt change points is crucial for configuring fillet radii, as these locations are the most vulnerable and dangerous areas for material failure.

[0022] Preferably, the transition buffer is designed to accommodate the continuity requirements of the strain field. The buffer width is positively correlated with the strain gradient ratio; when the gradient ratio is between 1.5 and 2.0, the buffer width is set to 0.15 mm; when the gradient ratio exceeds 2.0, the buffer width is increased to 0.25 mm. This dynamic adjustment mechanism allows for a wider transition range in areas of drastic strain changes, which is beneficial for uniform stress distribution.

[0023] In one embodiment, the cubic spline interpolation function is constructed using natural boundary conditions, requiring the second derivative of the interpolation function to be zero at the start and end points of the buffer zone. The interpolation function expression contains four undetermined coefficients, obtained through solving the boundary and continuity conditions. The interpolation function not only ensures the continuity of the fillet radius values, but more importantly, it ensures the continuity of the rate of change of the fillet radius, avoiding stress concentration caused by abrupt changes. A fillet radius value is calculated every 0.01 mm within the buffer zone, forming a dense sequence of radius values. Progressive adjustment is achieved by controlling the radius increment between adjacent points. The increment value gradually increases from zero at the start of the buffer zone to the maximum value at the midpoint, and then gradually decreases to zero at the end point, exhibiting a parabolic change pattern. This progressive adjustment strategy makes the change process of the fillet radius smooth and continuous, resulting in a more uniform stress redistribution during material deformation and significantly reducing the risk of cracking caused by local stress concentration.

[0024] For example, the calculation process of the fillet radius value sequence includes three steps: interpolation point selection, function value calculation, and numerical correction. Interpolation points are selected within a buffer according to the principle of equal spacing, with the spacing determined based on the machining accuracy requirements. Function values ​​are obtained directly by substituting into the interpolation function, and the calculation results are retained to three decimal places. Numerical correction mainly addresses potential oscillations caused by the interpolation function, eliminating unreasonable fluctuations through local smoothing.

[0025] Understandably, the corner radius configuration table uses a two-dimensional array as its data structure. The first dimension corresponds to the convex hull height value, and the second dimension contains three parameters: the corner radius value, the upper limit of the applicable strain range, and the lower limit. The configuration table is queried using a binary search algorithm to quickly locate the corresponding corner radius value based on the current convex hull height. Furthermore, in practical applications, the configuration table is dynamically invoked through the control program of the CNC stamping equipment. During the stamping process, the convex hull height is monitored in real time, and when the height reaches the node value in the configuration table, the corner radius parameters of the die are automatically adjusted. This phased adjustment method ensures dynamic optimization of the corner radius while avoiding the complexity of equipment control caused by continuous adjustments, achieving a balance between process optimization and equipment capacity.

[0026] S103. Determine if there are any points in the fillet radius configuration that exceed the material's uniform elongation limit. If so, iteratively adjust the genetic algorithm parameters to obtain the corrected fillet radius configuration. If not, proceed directly to the next step of material flow optimization analysis.

[0027] Strain values ​​are extracted point-by-point from the fillet radius configuration and compared with the material's uniform elongation limit, defined as the strain value corresponding to the highest point of the stress-strain curve in the tensile test. If the strain value at a certain configuration point exceeds the limit, it is marked as a breach point, and the number of breach points is counted. For each breach point, the difference between the strain value and the uniform elongation limit is calculated as the excess amount. The correction range is determined based on the maximum excess amount, and iterative optimization is performed by adjusting the genetic algorithm parameters. The adjustment includes reducing the crossover probability to the original value multiplied by the reciprocal of the number of breach points and increasing the mutation probability to the original value multiplied by the ratio of the correction range to the limit value. After each iteration, the strain value of each configuration point is recalculated, and it is determined whether breach points still exist. If breach points still exist after a preset number of iterations, the genetic algorithm calculation is re-executed by expanding the fillet radius value range to obtain a corrected fillet radius configuration. If the strain values ​​of all configuration points do not exceed the material's uniform elongation limit, the current fillet radius configuration is directly used for material flow optimization analysis.

[0028] In one implementation, the verification process for the fillet radius configuration begins with strain value extraction. Stress-strain analysis is performed on each configuration point using finite element simulation software to extract the equivalent plastic strain value at each point. The uniform elongation limit of the material is obtained through a standard tensile test. A standard nickel sheet specimen is stretched at a constant rate on a universal testing machine, and the complete stress-strain curve is recorded. The strain value corresponding to the highest point of the curve, i.e., the tensile strength point, is defined as the uniform elongation limit, which characterizes the maximum load-bearing capacity of the material during the uniform plastic deformation stage.

[0029] Specifically, the identification of default points employs a point-by-point comparison method. The strain value corresponding to each fillet radius value in the configuration sequence is compared with the uniform extension limit. A default point is marked when the strain value exceeds 95% of the limit. This approach, reserving a safety margin, considers material property fluctuations and measurement errors in actual production. The number of default points directly reflects the feasibility of the current configuration scheme; a higher number indicates a more unreasonable configuration. The excess is calculated by subtracting the uniform extension limit from the strain value of each default point. The correction magnitude is the maximum value of all excesses, representing the most severe deviation of the configuration scheme. The adjustment of the genetic algorithm parameters follows the feedback control principle. The decrease in crossover probability is inversely proportional to the number of default points; the more default points, the greater the decrease in crossover probability, making the algorithm more inclined to retain existing superior genes. The increase in mutation probability is directly proportional to the correction magnitude; the larger the correction magnitude, the greater the increase in mutation probability, prompting the algorithm to explore a wider solution space to find feasible solutions.

[0030] Preferably, the iterative optimization process is configured with dual termination conditions. The first condition is that the strain values ​​of all configuration points are below the uniform extension limit, at which point the current configuration is directly output for material flow analysis. The second condition is reaching a preset maximum number of iterations, typically set to 100. If there are still default points after reaching the maximum number of iterations, the range of fillet radius values ​​is expanded, increasing the upper limit by 20% and decreasing the lower limit by 10%, the population is reinitialized, and the genetic algorithm is executed.

[0031] In one embodiment, the material flow optimization analysis receives a verified fillet radius configuration and evaluates the material flow characteristics under different fillet radii through fluid dynamics simulation.

[0032] S104. Extract the metal transfer rate of the flange area from the modified fillet radius configuration, simulate the material flow balance from the flange area to the bulge area, and determine the predicted value of the thinning degree at the bottom of the bulge.

[0033] Geometric parameters for each deformation stage are extracted from the corrected fillet radius configuration. The radial flow velocity field of the metal in the flange area is obtained through finite element simulation. The metal transfer rate is calculated based on the velocity field and the cross-sectional area of ​​the flange area. The transfer rate is defined as the volume of metal flowing from the flange area into the bulge area per unit time. The mass conservation characteristics of the flow field are verified using the continuity equation. Based on the metal transfer rate, the material inflow flux in the flange area at each time node is calculated. Simultaneously, the volume increment change in the bulge area is monitored. The volume increment is determined by the product of the increase in bulge height and the cross-sectional area of ​​the bulge. A balance relationship between the inflow flux and the volume increment is established. This balance relationship is expressed as the inflow flux equals the volume increment multiplied by the material density. The material flow state is determined based on this balance relationship. If the inflow flux is less than the volume increment requirement, it indicates insufficient material supply. The material inflow is promoted by increasing the blank holder force in the flange area. If the balance is achieved, the current thickness value at each measurement point at the bottom of the bulge is extracted, and the difference between the thickness value and the initial thickness is calculated to obtain the thickness reduction. For the thickness reduction, the ratio of the thickness reduction to the initial thickness is calculated to obtain the local thinning rate. Based on the spatial distribution of the local thinning rate, areas with severe thinning are identified. The thickness change during subsequent deformation is predicted by combining the time change rate of the material inflow flux. The predicted value of the thinning degree at the bottom of the convex hull is determined by accumulating the current thinning rate and the predicted change.

[0034] In one implementation, the metal transfer rate is obtained based on the transient flow characteristics analysis of the nickel sheet stamping process. A three-dimensional stamping model is established in finite element simulation software, and nickel sheet material parameters including yield strength, hardening index, and anisotropy coefficient are set. The simulation process uses an explicit dynamic solver, with the time step set to the microsecond level to capture the high-speed deformation process. The flange area is divided into radial and circumferential grids, and each grid cell records its velocity vector. The radial flow velocity field is obtained by extracting the radial velocity components of each grid cell, and the velocity value shows a nonlinear decreasing law with the increase of distance from the center of the convex hull. The metal transfer rate is obtained by surface integral of the velocity field at the inner boundary of the flange area. The integration process considers the non-uniform flow characteristics of the material. Specifically, a flow correction factor is introduced to weight the velocity values ​​of different grid regions to ensure that the integration result reflects the local differences in material flow. The continuity equation plays a key role in verifying mass conservation. The continuity equation is expressed as the product of density and velocity divergence equals zero, which simplifies to zero velocity divergence under incompressible plastic deformation conditions. By calculating the velocity divergence value at each point in the flow field, it is determined whether the continuity condition is satisfied. When the divergence value exceeds the allowable error range, it indicates that the simulation parameters need adjustment. The calculation accuracy can be improved by refining the mesh density or reducing the time step. The calculation of the material inflow flux involves a time integration process. Within each time increment, the volume of metal flowing into the convex hull region through the inner boundary of the flange area is recorded, and these volumes are accumulated to obtain the total inflow. The volume increment of the convex hull region is obtained by monitoring the change in the height of the convex hull vertex; the increase in height multiplied by the projected area of ​​the convex hull is the volume increment. The equilibrium relationship is established based on the law of conservation of mass; the mass of the inflowing metal must be equal to the increase in the mass of the metal in the convex hull region. When the actual inflow flux is less than 90% of the theoretical demand, it is considered a state of insufficient material supply.

[0035] Preferably, the blank holder force is adjusted using a closed-loop control method. The initial blank holder force is set to a baseline value based on the nickel sheet thickness and material strength. When insufficient material supply is detected, the blank holder force is gradually increased according to a preset gradient. Each increase is 5% of the baseline value, and the material inflow is recalculated after adjustment until an equilibrium state is reached. The upper limit of the blank holder force is limited by the compressive strength of the nickel sheet to avoid crushing defects in the flange area. Simultaneously, the wrinkling trend in the flange area is monitored, and the blank holder force is appropriately reduced when wrinkling is detected. This dynamic adjustment mechanism achieves precise control of material flow, ensuring the stability of the bulge forming process.

[0036] In one embodiment, the thickness of the bulge bottom is measured using ultrasonic thickness measurement technology. A 5×5 measurement grid is arranged on the bottom of the bulge, with each measurement point spaced 3 mm apart. The ultrasonic probe emits pulse signals perpendicular to the bulge surface, and the local thickness value is calculated by measuring the echo time. The initial thickness is measured and recorded before stamping, serving as a benchmark for subsequent thinning rate calculations.

[0037] For example, the spatial distribution of thickness reduction exhibits a characteristic of being thinner at the center and thicker at the edges. The central region at the bottom of the convex hull bears the greatest biaxial tensile stress, resulting in the most severe thickness reduction, reaching up to 35%. From the center to the edges, the thinning rate gradually decreases, dropping to around 15% in the rounded corner transition area. By plotting contour maps of the thinning rate, areas with a thinning rate exceeding 30% are identified as severely thinned regions, requiring close monitoring. Furthermore, thickness change prediction is based on the time derivative of the material inflow flux. By calculating the rate of change of the inflow flux at the current moment and combining it with the convex hull height growth rate, the thickness change per unit time is derived. The prediction model considers the material hardening effect; as the degree of deformation increases, the material flow resistance increases, and the thickness reduction rate gradually decreases. By establishing a functional relationship between the thickness change and cumulative strain, the thickness distribution at future moments can be predicted.

[0038] Understandably, the calculation of the predicted thinning degree takes into account both the current state and the evolution trend. The currently measured local thinning rate is used as the initial value, and the predicted thickness change is added to obtain the thinning degree in the final deformed state. The accuracy of the predicted value is verified by comparing it with the destructive testing results of actual stamped samples, with the deviation controlled within 5%.

[0039] For example, in a nickel sheet stamping part with a bulge height of 1.8 mm, the predicted thinning degree of the bottom center area is 38%, while the actual measured value is 36.5%. The prediction accuracy meets the engineering requirements and avoids the problem of bulge cracking caused by excessive thinning.

[0040] The flange area is divided into multiple concentric rings radially and multiple sectors circumferentially to form several flange area grids. The material inflow and outflow within each grid are identified to obtain the spatial distribution of material transfer in the flange area and to predict the degree of thinning at the bottom of the convex hull.

[0041] Concentric rings are divided radially at equal intervals within the flange area radius, with the ring width uniformly set according to the flange area dimensions. Sectors are then divided circumferentially at preset angles, determined by equal division principles. The intersection of the rings and sectors forms a flange area grid. Flow velocity monitoring points are placed at each grid node, and radial and circumferential velocity components are obtained at each node through finite element analysis. For each velocity component, the mass flux of each grid cell is calculated. The mass flux is equal to the product of the flow velocity, material density, and grid cross-sectional area. The difference in mass flux between adjacent grids determines the material inflow or outflow state. Based on the inflow / outflow state, the material transfer amount at each grid location is recorded, forming spatial distribution data of material transfer in the flange area. Based on this spatial distribution data, control volumes are established within the convex hull region. Each control volume corresponds to a thickness monitoring area. The mass change of the control volume is calculated using the law of conservation of mass, and the control volume thickness value at each time step is recorded to form a thickness change trajectory, which includes the evolution of thickness over time. Combining the thickness change trajectory with the total amount of material flowing into the flange area at each deformation stage, the relationship between the inflow and the volume increment of the bulge area is established by the principle of material volume conservation. Based on the current thickness distribution and the relationship, the interpolation method is used to predict the degree of thinning at each position at the bottom of the bulge under deformation.

[0042] In one implementation, the flange area mesh is generated using a polar coordinate system for structured mesh generation. The inner diameter of the flange area corresponds to the boundary of the convex hull area, and the outer diameter corresponds to the clamping position of the pressure ring. For radial meshing, concentric rings are evenly spaced from the inner diameter to the outer diameter, with the ring width determined by dividing the total flange area width by a preset number of rings, typically 2 mm. Circumferential meshing uses an equal-angle principle, dividing the 360 ​​degrees into several sectors, each sector corresponding to a 15-degree central angle. The intersection of the rings and sectors forms quadrilateral mesh units, each with independent material properties and flow state identifiers. Virtual sensors are placed on the mesh nodes to record velocity, stress, and strain information at that location.

[0043] Specifically, the finite element method (FEM) calculation is based on the updated Lagrangian method, updating the grid node coordinates within each time increment step. Node velocities are obtained by solving the momentum conservation equation, which considers the balance of inertial forces, internal forces, and external forces. The radial velocity component represents the flow velocity of material towards the center of the convex hull, while the circumferential velocity component reflects the rotational flow of the material. These two velocity components are obtained by transforming from Cartesian coordinates to polar coordinates. The spatial distribution of the velocity field exhibits significant non-uniformity, with higher velocities in the inner ring near the convex hull and decreasing velocities in the outer ring; this gradient distribution reflects the differences in the driving forces of the material flow. The physical meaning of mass flux is the mass of material passing through a unit area per unit time. For each grid cell, the mass flux equals the product of the velocity vector at that location and the material density, multiplied by the normal cross-sectional area of ​​the grid cell. The difference in mass flux between adjacent grid cells reflects the net inflow or outflow of material. When the inflow flux of a grid cell is greater than the outflow flux, it indicates that material is accumulating in that region; conversely, it indicates that material is flowing out. By statistically analyzing the inflow and outflow status of all grid cells, a material transfer distribution map of the entire flange area is constructed, with different color depths in the map representing the intensity of material transfer.

[0044] Preferably, the control volumes for the convex hull region employ a different meshing strategy than those for the flange region. The convex hull region is divided into axisymmetric annular control volumes, each representing a thickness monitoring area at the bottom of the convex hull. The radial dimensions of the control volumes are determined based on the curvature variation of the convex hull, with denser control volumes in areas of greater curvature. Each control volume follows the law of mass conservation, with its mass change equal to the inflow mass minus the outflow mass. By recording the mass and volume of the control volumes at different times, the average density is calculated, and the average thickness of the region is then deduced. The thickness variation trajectory is recorded using time-series data, encompassing a complete evolutionary history from the initial state to the current state.

[0045] In one embodiment, the recording frequency of the thickness trajectory is related to the stamping speed. Recordings are made every 0.001 seconds during high-speed stamping and every 0.01 seconds during low-speed stamping. The trajectory data includes four parameters: timestamp, thickness value, equivalent strain, and strain rate.

[0046] For example, the principle of material volume conservation acts as a bridge in establishing the relationship between inflow and volume increment. The volume of material flowing into the flange area must equal the increase in volume in the bulge area plus the volume reduction caused by material compression. During plastic deformation, the volume compression rate of the material is very small and usually negligible. Therefore, the inflow volume is directly equal to the volume increment caused by the increase in bulge height. This conservation relationship provides a constraint for subsequent thickness prediction. Furthermore, the choice of interpolation method affects the prediction accuracy. Cubic spline interpolation is used to process the thickness distribution data to ensure the continuity of the second derivative of the interpolation function and avoid unreasonable fluctuations. The interpolation process first constructs the interpolation basis function based on the currently known thickness distribution points, and then extrapolates the future thickness distribution according to the material inflow trend. The influence of material hardening on flow is considered in the prediction; as the degree of deformation increases, the material flow resistance increases, and the thickness reduction rate gradually decreases. The prediction results are displayed in the form of a contour map, which intuitively reflects the thinning risk level at each position at the bottom of the bulge.

[0047] Understandably, the spatial distribution of thinning exhibits a clear regularity. The central region at the bottom of the convex bulge experiences the most severe thinning due to the greatest biaxial tensile stress; thinning gradually transitions outwards, decreasing in the rounded corner areas. By comparing the predicted values ​​with the actual measured values, the reliability of this prediction method was verified, providing a quantitative basis for subsequent optimization of process parameters.

[0048] For example, when the material transfer rate in the flange area is 5 cubic millimeters per second and the height increase rate of the bulge is 0.1 millimeters per second, the average thinning rate at the bottom of the bulge can be calculated by mass conservation. Combined with the current thickness distribution, the final thinning degree distribution can be predicted to guide the dynamic adjustment of the fillet radius.

[0049] S105. For the predicted value of the thinning degree at the bottom of the convex hull, correlate the punch stroke with the fillet radius to determine whether the high convexity requirement is met. If not, execute the particle swarm optimization algorithm repeatedly to obtain the optimized punch stroke parameters.

[0050] To predict the thinning degree at the bottom of the convex hull, a correlation function between punch stroke and fillet radius is constructed. This correlation function is obtained by fitting the correspondence between stroke values ​​and corresponding fillet radii in historical stamping data. The fillet radius values ​​under different punch strokes are calculated based on this correlation function. Strain data and thickness distribution data from each deformation stage are then integrated to form a comprehensive evaluation index that includes convex hull height, thinning rate, and strain concentration. Based on this comprehensive evaluation index, it is determined whether the current parameter configuration meets the high convexity requirement. The high convexity requirement is defined as a convex hull height to diameter ratio exceeding a preset threshold and a thinning rate within an allowable range. If not, a particle swarm optimization algorithm is initiated. The position of each particle in the particle swarm is initialized as a candidate value for punch stroke, and the particle velocity is randomly generated within the adjustable stroke range. The optimal punch stroke is searched by iteratively updating the velocity and position of the particles. The velocity update formula includes three parts: inertia, cognition, and society. The inertia maintains the original motion trend of the particles, the cognition guides the particles to move towards the individual's historical best position, and the society guides the particles to move towards the group's best position. The fitness value corresponding to each particle's position is calculated. When the rate of change of the fitness value is less than a preset threshold, convergence is determined, and the optimized punch stroke parameters are output.

[0051] In one implementation, the correlation function between punch stroke and fillet radius is constructed using a polynomial fitting method. Historical stamping test data, including measured values ​​of fillet radius under different punch strokes, are collected, and a cubic polynomial function is obtained using the least squares method. The function is in the form of a linear combination of the cube, square, and first powers of the stroke, with the coefficients determined through fitting. This correlation function reflects the nonlinear change in fillet radius as punch stroke increases.

[0052] Specifically, the convex hull height data is obtained directly from stamping simulation or actual measurement, the thinning rate is calculated from the thickness distribution, and the strain concentration is determined by the ratio of the statistically maximum local strain to the average strain. These three dimensions of data have different dimensions and require normalization to map the values ​​to the 0-1 range. The standardization uses the min-max method: for each dimension of data x, calculate x'=(x-min) / (max-min), where min and max are the minimum and maximum values ​​of that dimension, respectively. Weighted fusion uses the mathematical model S=0.4*x1'+0.35*x2'+0.25*x3', where S is the comprehensive evaluation index, and x1', x2', and x3' are the standardized values ​​of the convex hull height, thinning rate, and strain concentration, respectively. The particle swarm optimization algorithm's velocity update mechanism comprises three key parts. The inertia term is achieved through the product of inertia weight and current velocity, with the weight varying from large to small to balance global and local searches. The cognitive term guides particles to move towards their historical optimal positions, while the social term causes particles to converge towards the swarm's optimal position. After the velocity is updated, boundary constraints are applied to prevent particles from flying out of the search space.

[0053] Preferably, the fitness value calculation comprehensively considers both goal achievement and constraint satisfaction. The objective function part evaluates whether the convex hull height meets the design requirements, while the constraint function part checks whether the thinning rate is within a safe range. When the convex hull height is close to the target value and the thinning rate does not exceed the limit, the fitness value is relatively high. Convergence determination adopts a dual standard: when the rate of change of the globally optimal fitness value is less than the threshold for several consecutive generations, or when the maximum number of iterations is reached, the algorithm terminates and outputs the current optimal punch stroke parameters.

[0054] In one embodiment, for a nickel sheet stamping part with a target convex height of 1.5 mm, the initial punch stroke is set to 1.8 mm. After 50 generations of particle swarm optimization, the optimized stroke parameter is 2.1 mm, which achieves the high convexity requirement and controls the thinning rate within 30%.

[0055] S106. Based on the optimized punch stroke parameters, assess the risk of microcrack initiation and propagation along grain boundaries, and generate a dynamic stamping control sequence.

[0056] Based on the optimized punch stroke parameters, a finite element simulation environment for dynamic stamping is constructed. The grain size and grain boundary strength parameters of the nickel sheet material are set. The stress distribution at each time point is obtained through transient dynamics solutions. Stress concentration is characterized by the ratio of the maximum principal stress to the average stress. The locations where stress exceeds the material's yield strength and its change over time are recorded. For the stress concentration regions, fracture mechanics methods are used to assess the risk of crack initiation. Crack initiation conditions are determined by comparing the stress intensity factor with the material's fracture toughness. If the stress intensity factor exceeds a critical value, it is marked as a high-risk area. The crack propagation direction and rate are predicted by calculating the stress field at the crack tip. The damage degree of each region is calculated based on cumulative damage theory. Based on the damage degree distribution, a phased dynamic stamping control sequence is formulated. This control sequence includes the punch speed variation law, pressure holding time at each stage, and unloading rate. By reducing the punch speed in the high-stress stage to slow stress growth, and maintaining stable pressure in the holding stage to promote uniform material flow, a complete dynamic stamping control sequence is formed.

[0057] In one implementation, the finite element simulation environment is constructed based on the microstructure characteristics of the nickel sheet. Grain size is obtained through metallographic microscopy, typically ranging from 10 to 50 micrometers. Grain boundary strength parameters are determined based on the purity and heat treatment state of the nickel material; hardness values ​​at the grain boundaries are obtained through nanoindentation testing and converted into strength parameters for input into the simulation software. Transient dynamics are solved using an explicit time integration scheme, with the time step automatically determined based on the mesh size and the material's sound velocity to ensure computational stability.

[0058] Specifically, the stress intensity factor is calculated using the virtual crack propagation method. A virtual crack is pre-defined in the stress concentration region, and the stress intensity factor is calculated based on the energy release rate. When the stress intensity factor K reaches 70% of the material's fracture toughness KIC, it is considered a critical state for crack initiation. The stress field at the crack tip is expressed using a Williams series expansion, with the first coefficient representing the stress intensity factor, controlling the driving force for crack propagation. The crack propagation rate is predicted using the Paris formula, and the rate is proportional to the power of the stress intensity factor amplitude.

[0059] It should be noted that the assessment of cumulative damage is based on Miner's linear cumulative damage theory. The damage to the material caused by each loading cycle is linearly superimposed, and the material fails when the cumulative damage value reaches 1. Although the stamping process is not cyclically loaded, the duration of different stress levels can be converted into an equivalent number of cycles for damage accumulation calculation.

[0060] Preferably, the dynamic stamping control sequence employs a three-stage speed control. In the initial stage, the punch descends at a high speed, quickly approaching the workpiece; in the forming stage, the speed is reduced to 30% of the initial speed to slow the stress growth rate; in the holding stage, constant pressure is maintained, and the time is set to 1.5 times that of the forming stage to promote sufficient material flow and stress relaxation. The unloading process is performed in two steps: first, rapid unloading to 20% of the pressure, followed by slow and complete unloading to avoid secondary stress concentration caused by springback.

[0061] In one embodiment, the nickel sheet bumps manufactured by this control sequence showed a cracking rate of less than 0.3% in a test of 1,000 pieces produced in batches, and the bump height consistency was controlled within ±0.05 mm, achieving the goal of high-reliability batch manufacturing.

[0062] For example, using an optimized control sequence, the punch speed was reduced from 5 mm / s to 1.5 mm / s, and the holding time was 3 seconds, successfully producing a bump structure with a height of 1.8 mm.

[0063] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for acquiring and analyzing the surface morphology data of copper electrodes used in nickel sheet embossing, characterized in that, The method includes: The initial geometric parameters and material flow characteristics of the nickel sheet are obtained. The stress distribution as the bulge height increases is analyzed to determine the biaxial tensile stress concentration in the bottom rounded corner region, yielding a strain concentration index for this region. Based on this index, a genetic algorithm is used to determine the rounded corner radius configuration corresponding to the deformation stage. It is then determined whether any point in the rounded corner radius configuration exceeds the material's uniform elongation limit. If so, the genetic algorithm parameters are iteratively adjusted to obtain a corrected rounded corner radius configuration; otherwise, the process proceeds directly to the next step of material flow optimization analysis. The metal transfer rate in the flange area is extracted from the corrected rounded corner radius configuration, and the material flow balance from the flange area to the bulge area is simulated to determine the predicted value of the bulge bottom thinning degree. For the predicted bulge bottom thinning degree, the punch stroke and rounded corner radius are correlated to determine if the high convexity requirement is met. If not, a particle swarm optimization algorithm is repeatedly executed to obtain optimized punch stroke parameters. Based on the optimized punch stroke parameters, the risk of microcrack initiation and propagation along grain boundaries is assessed, generating a dynamic stamping control sequence.

2. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, The process involves acquiring initial geometric parameters and material flow characteristic data of the nickel sheet, analyzing the stress distribution as the convex hull height increases to determine the degree of bidirectional tensile stress concentration in the bottom rounded corner region, and obtaining strain concentration indices for the bottom rounded corner region, including: The nickel sheet is scanned in a grid to obtain a thickness distribution cloud map, and the grain boundary distribution characteristics are collected. The deformation gradient field during the convex hull forming process is captured as the stamping speed gradually increases. The stress tensor components of each grid node are calculated to determine the degree of plastic deformation in the bottom rounded corner area. For areas where the degree of plastic deformation exceeds the threshold, the strain concentration index of the bottom rounded corner area is calculated.

3. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, The step of determining the fillet radius configuration corresponding to the deformation stage using a genetic algorithm based on the strain concentration index of the bottom fillet region includes: A fitness function is constructed based on the strain concentration index. The fitness function is a weighted combination of fillet radius and strain distribution uniformity. The fillet radius at different deformation stages is expressed as a chromosome using binary encoding. A roulette wheel selection operator is used to select superior individuals. Single-point crossover and random perturbation mutation are performed on the superior individuals. The individual with the highest fitness in each generation is saved. The fitness value of the individual is calculated and it is determined whether it exceeds the target threshold and whether the fillet radius is within the allowable range. If the condition is met, the fillet radius configuration sequence corresponding to the optimal individual is output. If the condition is not met, the selection pressure coefficient is adjusted and iterative evolution continues until a fillet radius configuration that meets the constraints is obtained.

4. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, The step of determining the fillet radius configuration corresponding to the deformation stage based on the strain concentration index of the bottom fillet region using a genetic algorithm includes: determining the safe strain boundary at different convex hull heights based on the strain concentration index of the bottom fillet region; dividing the safe strain boundary into multiple deformation stage intervals; identifying strain abrupt change points based on the strain characteristics of each deformation stage interval; setting fillet radius transition buffers before and after the abrupt change points; discretizing the allowable strain range to calculate the strain gradient; constructing a cubic spline interpolation function within the transition buffer, ensuring the first derivative of the interpolation function is continuous at the start and end points of the buffer; calculating the fillet radius value corresponding to each discrete point within the buffer based on the interpolation function; using progressive adjustment to achieve a smooth transition of the fillet radius; and generating a complete fillet radius configuration table by combining the critical strain values ​​of each deformation stage. The configuration table records the fillet radius value corresponding to each convex hull height and its applicable strain range.

5. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, If a point exceeds the material's uniform elongation limit in the corner radius configuration is determined, the corrected corner radius configuration is obtained by iteratively adjusting the genetic algorithm parameters. If it does not exist, proceed directly to the next step of material flow optimization analysis, including: The strain values ​​are extracted point by point from the rounded corner radius configuration and compared with the material's uniform elongation limit. If the strain value at a certain point exceeds the limit, it is marked as a breach point. The excess amount of each breach point is calculated. The correction range is determined based on the maximum excess amount. The crossover probability and mutation probability of the genetic algorithm are adjusted for iterative optimization. After each iteration, the breach point is re-evaluated. If there are still default points after the preset number of iterations, the range of fillet radius values ​​will be expanded and the genetic algorithm will be re-executed; otherwise, the current fillet radius configuration will be directly used for material flow optimization analysis.

6. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, The process of extracting the metal transfer rate in the flange area from the modified fillet radius configuration, simulating the material flow balance from the flange area to the bulge area, and determining the predicted value of the thinning degree at the bottom of the bulge includes: Geometric parameters for each deformation stage are extracted from the modified fillet radius configuration. The radial flow velocity field of the flange area is obtained through finite element simulation. The metal transfer rate is calculated based on the velocity field and cross-sectional area. The mass conservation is verified using the continuity equation. The material inflow flux and volume increment of the flange area at each time point are calculated, and a balance relationship between the inflow flux and volume increment is established. The thickness value at the bottom of the bulge is extracted based on the balance relationship to calculate the thickness reduction and local thinning rate. The area of ​​severe thinning is identified based on the spatial distribution of the thinning rate. The subsequent thickness change is predicted by combining the time change rate of the material inflow flux. The predicted value of the thinning degree at the bottom of the bulge is determined by accumulating the current thinning rate and the predicted thickness change.

7. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, Determining the predicted value of the thinning degree at the bottom of the bulge includes: dividing the flange area into multiple concentric rings along the radial direction and into multiple sectors along the circumferential direction to form several flange area grids; identifying the material inflow and outflow within each grid; obtaining the spatial distribution of material transfer in the flange area; and predicting the thinning degree at the bottom of the bulge.

8. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, The predicted value for the thinning degree at the bottom of the convex hull is determined by: dividing the flange area radially into multiple concentric rings and circumferentially into multiple sectors to form a grid; arranging flow velocity monitoring points at each grid node to obtain radial and circumferential flow velocity components; calculating the mass flux of each grid cell; recording the material transfer amount based on the mass flux difference between adjacent grids to form spatial distribution data; establishing control volumes in the convex hull area; recording the thickness change trajectory of each control volume; and using the principle of volume conservation to predict the thinning degree at each position at the bottom of the convex hull by combining the total amount of material flowing into the flange area at each deformation stage with an interpolation method.

9. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, The predicted value for the thinning degree at the bottom of the convex hull is correlated with the punch stroke and the fillet radius to determine whether the high convexity requirement is met. If not, the particle swarm optimization algorithm is executed iteratively to obtain the optimized punch stroke parameters, including: For the predicted value of the thinning degree at the bottom of the convex hull, a comprehensive evaluation index is formed by integrating strain data and thickness distribution data at each deformation stage; based on the comprehensive evaluation index, it is determined whether the high convexity requirement is met. If not, the particle swarm position and velocity are initialized, and the optimal punch stroke is searched by iteratively updating the velocity and position, and the optimized punch stroke parameters are output.

10. The method for acquiring and analyzing the surface morphology data of the copper electrode used in nickel sheet embossing according to claim 1, characterized in that, The process involves assessing the risk of microcrack initiation and propagation along grain boundaries based on optimized punch stroke parameters, and generating a dynamic stamping control sequence, including: A dynamic stamping finite element simulation environment is constructed based on the optimized punch stroke parameters. The stress distribution at each time node is obtained through transient dynamics solution, and the stress concentration location and its change process are recorded. The fracture mechanics method is used to determine the crack initiation condition based on the stress intensity factor, and the crack propagation direction and rate and the damage degree of each region are calculated. A phased dynamic stamping control sequence is formulated based on the damage degree distribution.

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