Method and apparatus for corrosion protection of ground grid material

Abstract

The embodiment of the application provides a kind of ground net material's anticorrosion treatment method and equipment.The method comprises the following steps: according to the multiple anticorrosion performance evaluation indexes of ground net material, construct anticorrosion performance evaluation function;With the maximization of anticorrosion performance evaluation function as target, combining preset constraint condition, the process parameters of ultrasonic surface roller pressing treatment and laser impact treatment are optimized jointly using global optimization algorithm, to obtain target process parameter set;Preset constraint condition includes process parameter adjustable range constraint;According to target process parameter set, ground net material is carried out including ultrasonic surface roller pressing treatment and laser impact treatment composite reinforcement processing.The method is used to improve the effect of the comprehensive corrosion resistance of ground net material.

Description

Technical Field

[0001] This application relates to the field of power systems, and in particular to a method and equipment for corrosion protection of grounding grid materials. Background Technology

[0002] Grounding grid materials (typically Q235 steel) are buried in the soil environment for a long time. Existing protection methods mostly use coating, galvanizing, ultrasonic surface rolling, laser impact and other surface strengthening methods to improve corrosion resistance.

[0003] However, coating and galvanizing have limited lifespans and high maintenance costs. While ultrasonic surface rolling (USRP) can improve surface texture and smoothness, its stress depth is insufficient. While laser shock peening (LSP) can form a deeper compressive stress layer, it is prone to problems such as increased surface roughness and unsatisfactory near-surface stress distribution, making it difficult to achieve the comprehensive protection performance required for long-term service of the grounding grid.

[0004] Therefore, how to effectively evaluate the strengthening effect of composite surfaces and optimize the process to improve the overall corrosion resistance of grounding grid materials has become an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides a method and equipment for corrosion protection of grounding grid materials, which can improve the overall corrosion resistance of grounding grid materials.

[0006] In a first aspect, embodiments of this application provide a method for corrosion protection of grounding grid materials, including:

[0007] Based on multiple anti-corrosion performance evaluation indicators of grounding grid materials, an anti-corrosion performance evaluation function is constructed.

[0008] With the goal of maximizing the corrosion resistance performance evaluation function, and in conjunction with preset constraints, a global optimization algorithm is used to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment to obtain a target set of process parameters; the preset constraints include adjustable range constraints of process parameters.

[0009] According to the target process parameter set, the grounding grid material is subjected to a composite strengthening treatment including ultrasonic surface rolling and laser shock treatment.

[0010] In one possible implementation, the objective is to maximize the corrosion resistance performance evaluation function. Combined with preset constraints, a global optimization algorithm is used to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment, resulting in a target set of process parameters, including:

[0011] The search space is determined based on the adjustable range of the process parameters. Multiple particles are randomly generated in the search space. The position of each particle is a set of process parameters. The set of process parameters includes the first process parameters of the ultrasonic surface rolling treatment and the second process parameters of the laser shock treatment.

[0012] For each particle, after performing the composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particle, the anti-corrosion performance of the grounding grid material is extracted, and the fitness of the particle is calculated using the anti-corrosion performance evaluation function based on the anti-corrosion performance.

[0013] The positions of all particles are updated based on the fitness of each particle.

[0014] The fitness of each particle is recalculated based on its updated position, and the positions of all particles are updated again based on the new fitness of each particle to enter the next iteration round. This step is repeated until the preset iteration termination condition is met, and the target process parameter set is obtained.

[0015] In one possible implementation, the step of constructing a corrosion resistance evaluation function based on multiple corrosion resistance evaluation indicators of the grounding grid material includes:

[0016] Peak residual compressive stress Surface hardness peak and depth of influence of residual compressive stress As the evaluation index for corrosion resistance performance, the expression for the corrosion resistance performance evaluation function J is constructed as follows:

[0017]

[0018] in, , as well as The weights corresponding to each corrosion resistance performance evaluation index; This is a preset reference value for the peak residual compressive stress index; This is a preset reference value for the peak surface hardness index; This is a preset reference value for the depth of influence of residual compressive stress.

[0019] In one possible implementation, after performing the composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particles, extracting the corrosion resistance of the grounding grid material includes:

[0020] The ultrasonic surface rolling process of the grounding grid material is simulated using the first process parameters corresponding to the particles through a finite element model or proxy model, so as to obtain the first surface grain size of the material after a single ultrasonic surface rolling process, as well as the first residual compressive stress and the first surface hardness of the material at different depths.

[0021] The laser shock treatment of the grounding grid material is simulated using the second process parameters corresponding to the particles through a finite element model or proxy model, so as to obtain the first residual compressive stress influence depth of the material after a single laser shock treatment, as well as the second residual compressive stress and the second surface hardness of the material at different depths.

[0022] Based on the first and second residual compressive stresses at different depths of the material, a composite residual compressive stress model is constructed, and based on the first and second surface hardnesses at different depths of the material, a composite surface hardness model is constructed.

[0023] The peak value of residual compressive stress of the composite-strengthened material is extracted from the composite residual compressive stress model, the peak value of surface hardness of the composite-strengthened material is extracted from the composite surface hardness model, and the depth of influence of the second residual compressive stress of the composite-strengthened material is calculated based on the first surface grain size, the second surface grain size of the grounding grid material when it is not strengthened, and the depth of influence of the first residual compressive stress.

[0024] The composite residual compressive stress model is used to indicate the residual compressive stress of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set; the surface hardness model is used to indicate the surface hardness of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set.

[0025] In one possible implementation, the corrosion resistance evaluation index further includes surface roughness; correspondingly, after performing the composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particles, extracting the corrosion resistance of the grounding grid material further includes:

[0026] After the grounding grid material is subjected to actual composite strengthening treatment according to the process parameter set, the surface roughness of the grounding grid material is obtained by actual measurement method.

[0027] In one possible implementation, the composite residual compressive stress model is:

[0028]

[0029] in, This represents the residual compressive stress at depth z in the material after composite strengthening treatment; This represents the stress coupling correction factor; This represents the yield strength of the material at depth z after composite strengthening treatment; This represents the residual compressive stress at depth z in the material after a single ultrasonic surface roll forming treatment. This represents the residual compressive stress at depth z in the material after a single laser shock treatment.

[0030] In one possible implementation, the composite surface hardness model is:

[0031]

[0032]

[0033]

[0034] in, This indicates the surface hardness of the material at depth z after composite strengthening treatment; Indicates the hardness of the base material of the grounding grid; This represents the hardness coupling correction factor; This indicates the surface hardness of the material at depth z after a single ultrasonic surface roll forming treatment. This indicates the surface hardness of the material at depth z after a single laser shock treatment.

[0035] In one possible implementation, calculating the second residual compressive stress influence depth of the composite-strengthened material based on the first surface grain size, the second surface grain size of the grounding grid material before strengthening treatment, and the first residual compressive stress influence depth includes:

[0036] The Hall-Petch equation is used to calculate the first yield strength corresponding to the first surface grain size and the second yield strength corresponding to the second surface grain size.

[0037] Based on the first yield strength, the second yield strength, and the first residual compressive stress influence depth, the second residual compressive stress influence depth of the material after composite strengthening treatment is calculated using the stress influence depth model.

[0038] The stress influence depth model is as follows:

[0039]

[0040]

[0041] in, This indicates the depth of influence of the second residual compressive stress; This indicates the depth of influence of the first residual compressive stress; This represents the first yield strength; Indicates the second yield strength; This represents the correction coefficient that affects deep coupling.

[0042] Secondly, embodiments of this application provide an anti-corrosion treatment device for grounding grid materials, comprising:

[0043] The module is used to construct corrosion performance evaluation functions based on multiple corrosion performance evaluation indicators of grounding grid materials;

[0044] The decision module is used to optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment by combining preset constraints with the goal of maximizing the anti-corrosion performance evaluation function, and to obtain the target process parameter set by using a global optimization algorithm. The preset constraints include the adjustable range constraints of the process parameters.

[0045] The processing module is used to perform a composite strengthening treatment on the grounding grid material, including ultrasonic surface rolling and laser shock treatment, according to the target process parameter set.

[0046] Thirdly, embodiments of this application provide a computer device, including: a memory and a processor;

[0047] The memory stores computer-executed instructions;

[0048] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0049] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0050] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0051] The anti-corrosion treatment method and equipment for grounding grid materials provided in this application embodiment construct an anti-corrosion performance evaluation function based on multiple anti-corrosion performance evaluation indicators of the grounding grid material. With the goal of maximizing the anti-corrosion performance evaluation function, under preset constraints such as adjustable range of process parameters, a global optimization algorithm is used to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment to obtain a target process parameter set that matches the anti-corrosion requirements of the grounding grid material. Based on this, a composite strengthening treatment including ultrasonic surface rolling treatment and laser shock treatment is implemented to improve the comprehensive corrosion resistance and long-term service protection effect of the grounding grid material. Attached Figure Description

[0052] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0053] Figure 1 A schematic flowchart illustrating a corrosion protection method for a grounding grid material provided in Embodiment 1 of this application;

[0054] Figure 2 This is a schematic diagram showing a comprehensive comparison of performance indicators provided in the embodiments of this application;

[0055] Figure 3 The residual compressive stress distribution curve along the depth direction provided for this application;

[0056] Figure 4 The convergence curve of PSO combined with 8 parameters optimization provided in Embodiment 3 of this application;

[0057] Figure 5 This is a schematic diagram of the anti-corrosion treatment device for grounding grid material provided in Embodiment Six of this application;

[0058] Figure 6 A schematic diagram of the structure of the computer device provided in this application.

[0059] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0060] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0061] To facilitate understanding of the technical content of this application, the background technology is described in detail below:

[0062] Corrosion protection treatment of grounding grid materials falls under the technical field of power equipment safety protection and metal surface engineering. It primarily targets grounding devices that operate underground for extended periods, such as those in substations, transmission line corridors, power plants, and large industrial parks. These grounding devices are typically composed of Q235 steel flat bars, round bars, or welded components. During service, they are continuously exposed to soil environments with varying moisture, salinity, acidity / alkalinity, and microbial activity. They must meet conductivity and current discharge requirements while maintaining structural strength and connection reliability over the long term.

[0063] In existing technologies, corrosion protection for grounding grid steel components mainly employs methods such as coating with anti-corrosion layers, hot-dip galvanizing, and surface strengthening. Coating and galvanizing reduce the probability of contact between corrosive media and the metal substrate by forming an isolation layer on the steel surface. Ultrasonic surface rolling improves the surface structure, increases surface hardness, and reduces roughness through mechanical extrusion and high-frequency action. Laser shock blasting utilizes transient shock waves for non-contact processing, introducing a deeper residual compressive stress layer within the material, thereby enhancing resistance to crack initiation and propagation without damaging the surface.

[0064] These solutions each have their own mechanisms of action, but all have significant limitations in the long-term underground service scenarios of grounding grids. Coating and galvanizing are affected by soil abrasion, groundwater erosion, and construction damage, and the protective layer is prone to aging, damage, or local failure, resulting in high maintenance costs. While single ultrasonic surface rolling is beneficial for optimizing surface condition, it mainly acts on the shallow surface layer and cannot meet the needs of deep stress protection. Although single laser shock can form a deeper compressive stress layer, it may increase surface roughness and result in insufficient near-surface microstructure optimization, leading to unstable overall protective performance.

[0065] Given the aforementioned two surface strengthening processes, ultrasonic surface rolling and laser shock blasting, research has found that they possess naturally complementary characteristics in terms of microstructure and stress field: ultrasonic surface rolling excels at surface nanostructuring and hardening, while laser shock blasting excels at constructing deep stress fields. The ideal effect of combining the two is a dual anti-corrosion mechanism of "shallow nanostructuring + deep compressive stress".

[0066] However, existing composite reinforcement applications largely rely on empirically set process parameters, lacking a unified evaluation method for corrosion resistance. This makes it difficult to accurately reflect the comprehensive impact of different process parameter combinations on the material's corrosion resistance, and also hinders the synergistic optimization between ultrasonic surface rolling treatment and laser shock treatment. Consequently, it is not conducive to obtaining stable and repeatable corrosion resistance in grounding grid projects. Therefore, how to effectively evaluate the corrosion resistance of grounding grid materials after composite surface reinforcement, and based on this, achieve joint optimization of ultrasonic surface rolling treatment and laser shock treatment parameters, has become an urgent technical problem to be solved.

[0067] To address the aforementioned problems, this application provides a method for corrosion protection of grounding grid materials. This method constructs a corrosion performance evaluation function based on multiple corrosion performance evaluation indicators of the grounding grid material. Using this evaluation function as the objective function, and under preset constraints such as adjustable process parameters, a global optimization algorithm is employed to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment, obtaining a target set of process parameters. Then, based on this target set of process parameters, a composite strengthening treatment, including ultrasonic surface rolling treatment and laser shock treatment, is applied to the grounding grid material. By integrating performance evaluation, parameter optimization, and composite treatment processes, the limitations of single processes or empirical parameter selection can be avoided, thereby improving the overall corrosion resistance and engineering applicability of the grounding grid steel.

[0068] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0069] Figure 1 This is a schematic flowchart illustrating a corrosion protection method for grounding grid materials provided in Embodiment 1 of this application. Figure 1 As shown, the method includes:

[0070] S101: Construct a corrosion resistance performance evaluation function based on multiple corrosion resistance performance evaluation indicators of grounding grid materials.

[0071] In this step, it is necessary to determine multiple anti-corrosion performance evaluation indicators for grounding grid materials, and construct anti-corrosion performance evaluation functions based on each indicator.

[0072] Among them, the grounding grid material refers to the metal material used to construct the grounding device (i.e., grounding grid) of electrical equipment, which is mainly Q235B or Q235C grade hot-rolled flat steel (hereinafter referred to as Q235 steel) conforming to the GB / T 700 standard.

[0073] Evaluation indicators include, for example, surface roughness, peak residual compressive stress, depth of stress influence, peak surface hardness, and soil solution immersion corrosion rate; the evaluation function is used to map multiple interrelated performance indicators into comparable target values, thereby avoiding the inability of a single indicator to fully reflect the comprehensive anti-corrosion effect of the grounding grid material.

[0074] S102: With the goal of maximizing the anti-corrosion performance evaluation function, and combined with preset constraints, a global optimization algorithm is used to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment to obtain the target process parameter set.

[0075] Among them, the preset constraints include the adjustable range constraints of process parameters.

[0076] In this step, the process parameters for ultrasonic surface rolling treatment refer to the various process condition parameters that can be adjusted and controlled as needed during the ultrasonic surface rolling treatment of the material. The process parameters for laser shock treatment refer to the various process condition parameters that can be adjusted and controlled as needed during the laser shock treatment of the material.

[0077] Global optimization algorithms can employ Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), or combinations thereof. Their function is to simultaneously search multiple parameter dimensions within a given search space, avoiding process deviations caused by local optima. Adjustable range constraints on process parameters limit their variation within safe limits imposed by equipment capacity, material load-bearing capacity, and without introducing surface burns, excessive plastic deformation, or microcracks. By combining adjustable range constraints with global optimization, a balance can be achieved between the obtained target process parameter set and the feasibility of processing.

[0078] S103: Based on the target process parameter set, perform composite strengthening treatment on the grounding grid material, including ultrasonic surface rolling treatment and laser shock treatment.

[0079] In this step, the grounding grid material needs to undergo a composite strengthening treatment, including ultrasonic surface rolling and laser shock treatment, according to the parameters in the target process parameter set.

[0080] The sequence of ultrasonic surface rolling treatment and laser shock treatment is not specifically limited in this embodiment. Specifically, it may include the following steps 1 and 2:

[0081] Process 1: First, the grounding grid material is subjected to ultrasonic surface rolling treatment, and then laser impact treatment, i.e., "USRP first, then LSP"; Process 2: First, the grounding grid material is subjected to laser impact treatment, and then ultrasonic surface rolling treatment, i.e., "LSP first, then USRP".

[0082] It should be noted that, for Q235 steel, process 1 is the preferred process in this scheme, and the verification of its beneficial effects will be introduced later.

[0083] As a specific example, the surface of the grounding grid material can be cleaned and pretreated first to remove oxide scale, oil stains and attached impurities, so that the rolling and impact energy can be effectively transferred to the substrate surface. Then, ultrasonic surface rolling treatment is carried out according to the target process parameter set, so that the surface layer undergoes microscopic plastic flow and peak-valley leveling under high-frequency mechanical extrusion, thereby reducing surface roughness, closing shallow defects and increasing surface hardness. Then, laser shock treatment is carried out according to the target process parameter set, using the transient shock wave generated by plasma expansion to introduce a deeper residual compressive stress layer inside the material and inhibit the initiation and propagation of microcracks.

[0084] Since ultrasonic surface rolling mainly improves the shallow layer structure and surface morphology, while laser shock mainly enhances the stress protection capability of deeper layers, the combination of the two can form a gradient reinforcement structure from the surface to the near-surface layer and then to the deeper layers, making it more difficult for corrosive media to enter the matrix through surface defects, while reducing the risk of stress corrosion cracking.

[0085] The anti-corrosion treatment method for grounding grid materials provided in this application improves the overall corrosion resistance of grounding grid materials by integrating anti-corrosion performance evaluation, global parameter optimization, and composite strengthening treatment. This ensures that the process parameters are matched with actual corrosion resistance requirements.

[0086] Furthermore, Embodiment 2 of this application provides a specific method for corrosion protection of grounding grid materials. Based on the above embodiments, the method provided in this application includes the following:

[0087] Step 21: Calculate the peak value of residual compressive stress. Surface hardness peak and depth of influence of residual compressive stress As an evaluation index for corrosion resistance performance, the expression for the corrosion resistance performance evaluation function J is constructed as follows:

[0088]

[0089] in, , as well as The weights corresponding to each corrosion resistance performance evaluation index; This is a preset reference value for the peak residual compressive stress index; This is a preset reference value for the peak surface hardness index; This is a preset reference value for the depth of influence of residual compressive stress.

[0090] In detail, the peak value of residual compressive stress is used to characterize the degree of compressive stress reinforcement in the surface and near-surface layers, the peak value of surface microhardness is used to characterize the surface layer's resistance to plastic deformation, and the depth of influence of residual compressive stress is used to characterize the effective range of the compressive stress layer. Incorporating all three into the corrosion resistance performance evaluation function unifies the shallow surface hardening effect of ultrasonic surface rolling and the deep compressive stress effect of laser shock into the same evaluation framework. This allows the evaluation results to simultaneously reflect surface densification ability, crack initiation inhibition ability, and the ability to impede the diffusion of corrosive media into the substrate.

[0091] The weights corresponding to each indicator are used to reflect the degree of contribution of the indicator to the corrosion resistance performance. In practical applications, each weight can be determined according to the Analytic Hierarchy Process (AHP) of the grounding grid corrosion protection project requirements. This application does not impose restrictions on the setting of each weight value. For example, each weight may be set as follows: , , .

[0092] Optionally, surface roughness can also be adjusted. As an indicator for evaluating corrosion resistance, the corresponding corrosion resistance evaluation function... The expression is:

[0093]

[0094] in, The weights corresponding to the surface roughness index, These are preset reference values ​​for the surface roughness index. Accordingly, in this optional scheme, the weights are set as follows: , , , .

[0095] Specifically, surface roughness is used to characterize the microscopic undulations of the grounding grid material surface after composite anti-corrosion treatment. It should be understood that the smaller the surface roughness of the treated material, the smoother its surface, which is more conducive to reducing the adhesion and retention of corrosive media on the surface, and thus the better the anti-corrosion effect. Therefore, the surface roughness index in the evaluation function adopts... Represented in the form of .

[0096] Additionally, it should be noted that in the aforementioned evaluation function, each reference normalized value can be determined based on the material matrix properties, experience in ultrasonic-laser composite strengthening engineering of similar materials, and the corrosion resistance requirements of the grounding grid, to ensure that the evaluation function has a stable response to process differences. For example, For example, take 0.75 times the typical compressive stress of the same type of material after composite strengthening treatment; For example, take 1.8 times the hardness of the substrate; For example, take the lower limit of depth in ultrasonic-laser composite strengthening treatment of similar materials; For example, the values ​​that can be stably achieved by ultrasonic rolling are taken. Taking Q235 steel as an example, its reference values ​​are set as follows: =4000Mpa, =350HV, =100 m, =0.2 m.

[0097] By using the above weighted normalization expression, the composite strengthening process can be accurately guided to converge towards improving the overall anti-corrosion performance during parameter optimization, thereby improving the long-term anti-corrosion stability of grounding grid materials in complex soil environments.

[0098] Step 22: With the goal of maximizing the anti-corrosion performance evaluation function, and in conjunction with preset constraints, a global optimization algorithm is used to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment to obtain the target process parameter set. The preset constraints include constraints on the adjustable range of the process parameters. In this embodiment, the PSO algorithm is used for optimization, and the specific process includes the following steps 22.1 to 22.4:

[0099] Step 22.1: Determine the search space based on the adjustable range of process parameters, and randomly generate multiple particles within the search space. The position of each particle represents a set of process parameters.

[0100] The process parameter set includes first process parameters for ultrasonic surface rolling treatment and second process parameters for laser shock treatment. Specifically, the first process parameters may include amplitude A and static pressure F. s The first process parameter is the feed rate f, and the number of rolling passes N1. The second process parameter may include the power density I0, the spot diameter D, the spot overlap rate η, and the number of impacts N2.

[0101] The search space is a multi-dimensional set of parameters formed on the basis of the range. Its dimensions correspond one-to-one with the first process parameter and the second process parameter, and it can completely characterize the process combination of composite processing.

[0102] Taking Q235 steel as an example, the adjustable range of each process parameter can be set as follows: 10≤A≤25 m, 300≤F s ≤800N, 0.03≤f≤0.12mm / r, 1≤N1≤6, 2≤I0≤8GW / cm 2 , 1.5≤D≤4.5mm, 30≤η≤70%, 1≤N2≤5.

[0103] Step 22.2: For each particle, after performing composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particle, extract the anti-corrosion performance of the grounding grid material, and calculate the fitness of the particle using the anti-corrosion performance evaluation function based on the anti-corrosion performance.

[0104] In this step, for each particle, the grounding grid material will be subjected to composite anti-corrosion treatment according to its corresponding process parameter set, and its anti-corrosion performance will be tested. The detected performance will be input into the aforementioned evaluation function to obtain the fitness of the particle.

[0105] In this scheme, the objective is to maximize the evaluation function, i.e., the objective function is set as follows: The higher the particle fitness, the better the composite anti-corrosion effect corresponding to the parameter set, and the easier it is to be retained during the iteration process and guide subsequent searches.

[0106] In practical applications, the evaluation function values ​​(i.e., J values) corresponding to each process can be determined in advance through experiments after the material has undergone composite strengthening treatment in processes 1 and 2. The process with the larger J value is then identified as the target process (for Q235 steel, the target process is process 1). In the subsequent optimization process, the strengthening process is applied to the material directly according to the target process and the corresponding set of process parameters for the particles. The method for applying the strengthening process to the material can be either the actual processing method using physical samples or numerical simulation analysis based on a simulation model.

[0107] In one possible implementation, the peak value of residual compressive stress, the peak value of surface hardness, and the depth of influence of residual compressive stress of the material after composite strengthening treatment corresponding to each set of process parameters can be obtained using the following steps a to d:

[0108] Step a: Simulate the ultrasonic surface rolling process of the grounding grid material using the first process parameters corresponding to the particles through the finite element model or proxy model of ultrasonic surface rolling, so as to obtain the first surface grain size of the material after a single ultrasonic surface rolling process, as well as the first residual compressive stress and the first surface hardness of the material at different depths.

[0109] Among them, the finite element model or proxy model refers to the calculation model that can predict the performance parameters of the grounding grid material after the strengthening process can be simulated.

[0110] In detail, the finite element model of ultrasonic surface rolling refers to a numerical simulation model built in finite element analysis software based on elastoplastic mechanics and dynamics theory. This model accurately simulates the action of ultrasonic rolling tools on grounding grid materials and can predict the performance parameters of the treated materials. The surrogate model (also known as the response surface model or meta-model) of ultrasonic surface rolling refers to a simplified mathematical model pre-constructed using mathematical regression or machine learning algorithms based on sample data obtained from finite element simulations or physical experiments. This model can quickly map the nonlinear relationship between the process parameters of ultrasonic surface rolling and the performance parameters of the treated grounding grid materials. In practical applications, the surrogate model can be used to replace the computationally expensive finite element model for parameter optimization, thereby improving the efficiency of the optimization process.

[0111] As a specific example, this step may specifically include the following 1) to 3):

[0112] 1) Construct a first residual compressive stress model for the material after single ultrasonic surface roll forming treatment. This model is used to characterize the residual compressive stress at different depths in the material after single ultrasonic surface roll forming treatment. The first residual compressive stress model is as follows:

[0113]

[0114] In this model, This represents the first residual compressive stress (i.e., the stress distribution of the material in the depth direction) at depth z after a single ultrasonic surface roll forming process. This represents the residual compressive stress on the surface of the material after a single ultrasonic surface roll forming process (i.e., ); This indicates the depth of influence of residual compressive stress on a material after a single ultrasonic surface roll forming treatment. It represents the residual compressive stress attenuation rate coefficient of a material after a single ultrasonic surface roll forming treatment.

[0115] in, , as well as All of these are coefficients to be fitted.

[0116] The specific coefficient fitting method is as follows: Substituting the first process parameters into a finite element model or surrogate model, the first residual compressive stress at different depths of the material after single ultrasonic surface rolling strengthening is simulated, resulting in several sets of discrete data. Using these discrete data, the undetermined coefficients of the first residual compressive stress model are fitted (e.g., using the least squares method), ultimately obtaining the first residual compressive stress model matched to the set of process parameters. Based on this, the first residual compressive stress at different depths of the material after single ultrasonic surface rolling treatment can be obtained.

[0117] 2) Construct a first surface hardness model for the material after single ultrasonic surface rolling treatment. This model is used to characterize the surface hardness of the material at different depths after single ultrasonic surface rolling treatment. The first surface hardness model is as follows:

[0118]

[0119] In this model, This indicates the first surface hardness of the material at depth z after a single ultrasonic surface roll forming treatment. Indicates the hardness of the base material of the grounding grid; and All are material hardness conversion coefficients; The hardening index of the material; The Hall-Petch grain boundary strengthening coefficient of the material; This represents the grain size of the material at depth z after a single ultrasonic surface roll forming treatment. This represents the equivalent plastic strain at depth z of the material after a single ultrasonic surface roll forming process.

[0120] in, The hardness can be obtained by testing the unstrengthened material (i.e., the substrate). For example, the substrate hardness of Q235 steel is 180HV. It can be determined by uniaxial tensile testing of the base material. Taking Q235 steel as an example, ; The value is determined by the material's crystal structure and metallographic properties, and can be calibrated through static tensile testing. Taking Q235 steel as an example... ≈0.74MPa. It should be understood that... , as well as These are all inherent physical property parameters of the material. The values ​​of these performance parameters for the same type of material are not affected by changes in the ultrasonic rolling process parameters. For the optimization of parameters for the same type of material, only one calibration is required.

[0121] and The first process parameters can be input into a finite element model or a proxy model and obtained through simulation calculation; as well as The method for obtaining the hardness is as follows: the first process parameters are imported into a finite element model or a proxy model, and discrete sample data of surface hardness corresponding to different depths are obtained through simulation. Based on this set of discrete data, a fitting algorithm is used to solve for the undetermined coefficients, thereby obtaining a hardness prediction model corresponding to the set of process parameters. Based on this, the first surface hardness of the material at different depths after a single ultrasonic surface rolling treatment can be obtained.

[0122] 3) Based on the simulation obtained in 2), The first surface grain size of the material after single ultrasonic surface rolling treatment was obtained. That is, the first surface grain size. .

[0123] Step b: Using a finite element model or proxy model of laser shock, simulate the laser shock treatment of the grounding grid material with the second process parameters corresponding to the particles, in order to obtain the depth of influence of the first residual compressive stress of the material after a single laser shock treatment, as well as the second residual compressive stress and the second surface hardness of the material at different depths.

[0124] In detail, the finite element model of laser shock refers to a numerical simulation model built in finite element analysis software based on the theory of elastoplastic mechanics and dynamics, which can accurately simulate the effect of laser shock on grounding grid materials and predict the performance parameters of the treated materials. The surrogate model of laser shock refers to a simplified mathematical model built in advance based on sample data obtained from finite element simulation or physical experiments, through mathematical regression or machine learning algorithms, which can quickly map the nonlinear relationship between the process parameters of laser shock and the performance parameters of the grounding grid materials after treatment.

[0125] As a specific example, this step may specifically include the following 4) to 6):

[0126] 4) Construct a second residual compressive stress model for the material after a single laser shock treatment. This model is used to characterize the residual compressive stress at different depths in the material after a single ultrasonic surface rolling treatment. The second residual compressive stress model is as follows:

[0127]

[0128] In this model, This represents the second residual compressive stress at depth z in the material after a single laser shock treatment. This represents the residual compressive stress on the surface of a material after a single laser shock treatment (i.e., ); This indicates the depth of influence of residual compressive stress on a material after a single laser shock treatment. This represents the residual compressive stress attenuation rate coefficient of a material after a single laser shock treatment. The shape index represents the residual compressive stress distribution of a material after a single laser shock treatment.

[0129] in, , , as well as These are all coefficients to be fitted. For specific coefficient fitting methods, please refer to the specific example in step a above, which will not be repeated here.

[0130] 5) Considering that the hardness improvement from single laser shock treatment mainly comes from high-density dislocations and impact phase transitions, its hardness increment is relatively small (30~60 HV) and is mainly concentrated near the surface. Therefore, it can be set as... It can be a constant, for example, the surface hardness of the material at different depths after a single laser shock treatment can be taken as 45.

[0131] 6) Fit the above 5) The depth of influence of the first residual compressive stress in the material after a single laser shock treatment was determined.

[0132] Optionally, in practical applications, the aforementioned discrete data can also be obtained through actual processing and testing. Taking residual compressive stress as an example, after the grounding grid material is actually reinforced according to the corresponding process parameters, the residual compressive stress at different depths can be detected and obtained using X-ray diffraction (XRD).

[0133] Step c: Based on the first and second residual compressive stresses at different depths of the material, construct a composite residual compressive stress model, and based on the first and second surface hardnesses at different depths of the material, construct a composite surface hardness model.

[0134] Among them, the composite residual compressive stress model is used to indicate the residual compressive stress of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set; the surface hardness model is used to indicate the surface hardness of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set.

[0135] In this step, it is necessary to obtain the information as described above. as well as A model representing the residual compressive stress at depth z in the material after composite strengthening treatment is constructed. Simultaneously, it is also necessary to rely on the aforementioned data... as well as A model representing the surface hardness of the material at depth z after composite strengthening treatment was constructed.

[0136] It is worth noting that, according to the inventor's research, the effect of composite strengthening is not a simple linear superposition of the two effects, but involves complex multi-physics coupling phenomena. Specifically, this includes: (1) Microstructure coupling, that is, the nanocrystalline layer generated by ultrasonic surface rolling treatment changes the mechanical properties of the material surface (such as the Hall-Petch effect increasing the yield strength of the material from 235MPa to 400-600MPa), which will significantly affect the propagation behavior and plastic deformation response of the shock wave in the material after subsequent laser shock treatment. That is, the high-strength material on the surface allows the shock wave energy to "penetrate" more into the deep layer, increasing the effective stress influence depth of the laser shock treatment. Conversely, if laser shock treatment is performed first, followed by ultrasonic surface rolling treatment, the deep residual compressive stress field established in the material by the laser shock treatment may be "erased" or "redistributed" by the high-stress treatment part of the surface layer of ultrasonic surface rolling treatment. (2) Coupling of residual compressive stress fields: The residual compressive stress fields generated by the two processes overlap in space, but the superposition behavior is nonlinear. That is, in the region where the material has entered plastic deformation, the additional stress will not accumulate linearly, but will be constrained by the yield limit of the material, forming a "stress saturation" effect. This nonlinear superposition cannot be described by the traditional simple addition method.

[0137] In view of this, this application also provides a method for obtaining the residual compressive stress and surface strength of the material at depth z after nonlinear superposition for composite strengthening treatment, that is, the constructed composite residual compressive stress model can be:

[0138]

[0139] in, This represents the residual compressive stress at depth z in the material after composite strengthening treatment; This represents the stress coupling correction factor; This represents the yield strength of the material at depth z after composite strengthening treatment.

[0140] In practical applications, as well as The residual compressive stress can also be calculated using finite element simulation (e.g., using a finite element model or surrogate model corresponding to the superposition process, where the simulated process is a pre-defined target process). The specific process will not be elaborated further. After fitting, the residual compressive stress with depth z as the independent variable can be obtained. Parse the expression.

[0141] in, It mainly depends on the material properties and the composite process steps. For the same type of material, the parameters are constant under the same processing steps and do not change with the process parameters. For parameter optimization of the same type of material, only one calibration is needed. For example, taking Q235 steel as an example, if the process of "USRP first, then LSP" is adopted, (Calibration was performed using 5 sets of parameter combinations, with a coefficient of determination R) 2 (0.981); if the "LSP first, USRP later" process is adopted, The latter indicates that the ultrasonic surface rolling process has a stronger "overwriting" effect on the existing stress field of laser shock.

[0142] in, This is a nonlinear correction term, and its physical meaning is "stress loss caused by plastic flow when a new stress is superimposed on an existing stress field".

[0143] Since both treatments cause local plastic zone overlap, when the near-surface compressive stress is already high, the stress increment introduced by subsequent laser shock will be attenuated due to yield constraint. Therefore, using this nonlinear correction term for coupling correction can more realistically reflect the stress evolution law after composite treatment.

[0144] In addition, the constructed composite surface hardness model can be:

[0145]

[0146]

[0147]

[0148] in, This indicates the surface hardness of the material at depth z after composite strengthening treatment; This represents the hardness coupling correction factor.

[0149] In practical applications, The surface hardness can also be calculated using the finite element method, the specific process of which will not be elaborated here. After fitting, the surface hardness with depth z as the independent variable can be obtained. Parse the expression. It should be understood that... These are parameters representing the friction / contact characteristics of a material, which are intrinsic properties of the material and do not change with process parameters. For the same type of material, parameter optimization only requires one calibration. For example, Q235 steel... 0.15 is acceptable.

[0150] The composite surface microhardness model provided in this application adds the hardening increments of individual treatments and introduces... The coupling correction term describes the nonlinear superposition relationship between the two strengthening mechanisms in the near-surface tissue densification, work hardening, and stress field reconstruction processes. This correction term is used to characterize the synergistic or saturation effects of ultrasonic surface rolling and laser shock within the same depth range. When the two treatments have overlapping contributions to microstructure refinement and dislocation density enhancement, this correction term can suppress the overestimation caused by simple linear addition, thereby... It more closely approximates the hardness distribution after actual composite treatment.

[0151] Step d: Extract the peak residual compressive stress of the composite-strengthened material from the composite residual compressive stress model. Extracting the peak surface hardness of the composite-strengthened material from the composite surface hardness model. The second residual compressive stress influence depth of the material after composite strengthening treatment is calculated based on the first surface grain size, the second surface grain size of the grounding grid material before strengthening treatment, and the first residual compressive stress influence depth.

[0152] Specifically, it can be expressed using the following formula:

[0153]

[0154]

[0155] in, Indicates the upper limit of the material's depth.

[0156] The calculation of the influence depth of the second residual compressive stress, when the selected process is "USRP first, then LSP", may specifically include the following steps d1 to d2:

[0157] Step d1: Using the Hall-Petch equation, calculate the first yield strength corresponding to the first surface grain size and the second yield strength corresponding to the second surface grain size.

[0158] The Hall-Petch equation is as follows: .in, Frictional stress in the single-crystal lattice of a material is an intrinsic physical property parameter that can be determined through tensile testing of grain size. Taking Q235 steel as an example, its... ; d represents the surface grains of the material.

[0159] The first surface grain size obtained above Substituting this into the equation, we get... The first yield strength corresponding to the first surface grain size is obtained. The grain size of the second surface of the grounding grid material before reinforcement treatment. Substituting this into the equation, we get... The second yield strength corresponding to the second surface grain size is obtained. .

[0160] Step d2: Based on the first yield strength, the second yield strength, and the first residual compressive stress influence depth, calculate the second residual compressive stress influence depth of the material after composite strengthening treatment using the stress influence depth model.

[0161] The stress influence depth model is as follows:

[0162]

[0163]

[0164] in, This indicates the depth of influence of the second residual compressive stress in the material after composite strengthening treatment; Indicates the depth of influence of the first residual compressive stress; This represents the correction coefficient that affects deep coupling. The physical meaning of λ is the contribution rate of the increase in unit yield strength to the depth of stress influence, which can also be obtained using finite element simulation. Taking Q235 steel as an example, λ = 0.35 ± 0.04.

[0165] In this step, the previously obtained first residual compressive stress influence depth, first yield strength, and second yield strength are substituted into the previously calibrated... The depth of influence of the second residual compressive stress can be obtained from the formula.

[0166] After the processing of steps a to d above, the peak value of residual compressive stress, the peak value of surface hardness, and the depth of influence of residual compressive stress of the material after composite processing using this set of process parameters are obtained.

[0167] In addition, if the constructed evaluation function includes a surface roughness index, the surface roughness of the composite-strengthened material corresponding to each set of process parameters can be obtained using the following step e:

[0168] Step e: After performing actual composite reinforcement treatment on the grounding grid material according to the process parameter set, the surface roughness of the grounding grid material is measured by actual measurement method.

[0169] Specifically, the actual measurement method refers to directly using surface roughness measuring equipment (such as a stylus surface roughness meter) to conduct laboratory tests on the treated material surface in order to obtain the surface roughness of the material.

[0170] Step 22.3: Update the positions of all particles globally based on the fitness of each particle.

[0171] In this step, based on the fitness of each particle, the historical best position and the global best position of the population are determined, and the update rate of each particle is determined accordingly; the position of each particle is updated according to the update rate corresponding to each particle.

[0172] Step 22.4: Recalculate the fitness of each particle based on its updated position, and update the position of all particles again based on their new fitness to enter the next iteration round. Repeat this step until the preset iteration termination condition is met to obtain the target process parameter set.

[0173] In this step, the position of each particle will be iteratively updated until the preset termination condition is met, and the target parameter set can be obtained.

[0174] Specifically, during the iteration process, the update rate of each particle can be determined using the following formula:

[0175]

[0176]

[0177] in, This represents the update rate of the i-th particle in the (t+1)-th iteration;

[0178] This represents the update rate of the i-th particle in the t-th iteration; Represents individual learning factors. Represents the global learning factor. and A random number uniformly distributed within the interval [0,1]. The i-th particle's historical best position is represented by gbest; gbest represents the group's global best position. x represents the position of the i-th particle in the t-th iteration; i (t+1) represents the position of the i-th particle in the (t+1)-th iteration; w represents the inertial weight.

[0179] The inertia weight can adopt the current decreasing strategy, i.e. ,in, This represents the maximum number of iterations. That is, the inertia weight is 0.9 in the first iteration, and gradually decreases during multiple iterations until it reaches a value of 0.4 in the final iteration. This method is beneficial for both early-stage global search and later-stage fine-grained local search. and All values ​​can be 2.

[0180] As a specific example, considering the empirically recommended value of 5 to 10 times the dimension for 8-dimensional problems, the number of randomly generated particles N can be set. p =50; Additionally, the maximum number of iterations can be set. = 150 iterations, the iteration termination condition is that the change in the maximum fitness value of the population is less than 10 over 20 consecutive iterations. -4 Additionally, speed limits are set during the iteration process to prevent excessively large particle movement steps; that is, a maximum speed is set for each parameter dimension of a single particle. , where v max This represents the upper limit of the parameter dimension during a single iteration of the particle; x upper This represents the lower limit value of the particle in this parameter dimension during a single iteration. Additionally, after each position update, rounding is performed on the dimensions corresponding to the process parameters N1 and N2. Specifically, based on process requirements, rounding rules (round to the nearest integer, round up, or round down) are selected to convert the floating-point value output by the algorithm into an integer.

[0181] Optionally, in practical applications, since PSO is a heuristic algorithm, a single run may get stuck in a local optimum. Multiple independent runs (e.g., 10 runs) can be performed, each generating different random particles. From the results of these multiple independent runs, the set of target process parameters that maximizes the corresponding corrosion resistance performance evaluation function value is selected as the optimal solution.

[0182] Furthermore, to further ensure the reliability of the obtained optimal solution, the coefficient of variation among the values ​​of the corrosion resistance performance evaluation function corresponding to each independent run can be calculated. If the coefficient of variation is less than a preset threshold (e.g., 3%), the result is considered reliable; otherwise, multiple independent runs will be performed until the coefficient of variation meets the requirement. The coefficient of variation can be calculated as the arithmetic mean of the corrosion resistance performance evaluation function values ​​obtained from multiple independent runs.

[0183] Optionally, in practical applications, additional constraints can be set, such as total machining time constraints (i.e., economic constraints) and surface roughness constraints, for example, requirements... Correspondingly, if the total processing time or surface roughness corresponding to the target process parameter set does not meet the corresponding constraints, parameter optimization is performed again until the determined target process parameter set meets the additional constraints.

[0184] Step 3: Based on the target process parameter set, perform a composite strengthening treatment on the grounding grid material, including ultrasonic surface rolling and laser shock treatment. The process sequence of the composite strengthening treatment is the target process.

[0185] Specifically, in this step, the grounding grid material needs to undergo a composite strengthening treatment, including ultrasonic surface rolling and laser shock treatment, according to the target process, thereby completing the anti-corrosion treatment of the grounding grid material.

[0186] As a specific example, surface acoustic wave (SAW) rolling includes:

[0187] 1a: Selection of processing equipment and tool heads

[0188] The ultrasonic surface rolling equipment is mounted on a CNC lathe or horizontal milling machine; the rated center frequency of the ultrasonic device is 28kHz, the maximum amplitude is 30μm, and the rated maximum static pressure is 1000N. The rolling tool head is made of WC-Co tungsten cobalt cemented carbide, and different ball radii are matched according to the workpiece type: when machining flat steel, a tool head with a ball radius of 3mm is selected; when machining round steel, a tool head with a ball radius of 2mm is selected.

[0189] 1b: USRP process parameter settings

[0190] The process parameters are set according to the optimal solution obtained through optimization; at the same time, the motion parameters are matched according to the equipment mode: the workpiece speed is set in turning mode, and the table feed speed is set in milling mode. When using multi-pass rolling, all process parameters are kept constant throughout the process, and adjacent rolling passes use alternating feeds in the forward and reverse directions to reduce the anisotropy generated by the process and ensure the uniformity of surface structure and properties.

[0191] 1c: Processing path and on-site environment requirements

[0192] The processing path is distinguished according to the shape of the workpiece:

[0193] Flat steel is subjected to full surface treatment by rolling on all four sides sequentially; round steel is subjected to continuous circumferential rolling by rotating the workpiece. After each single side / single pass of rolling is completed, the condition of the workpiece is inspected and confirmed before proceeding to the next process.

[0194] Processing environment control requirements: The ambient temperature is maintained between 15 and 35°C, and the relative humidity of the air is less than 80%; the processing uses cutting oil atomized micro-lubrication to reduce tool head wear and suppress the accumulation of rolling friction heat.

[0195] 1d: Online monitoring of the processing

[0196] The equipment is equipped with an online monitoring module that monitors three key operating indicators in real time: the amplitude fluctuation range of the ultrasonic tool head is controlled within ±5%, the static pressure fluctuation range of the rolling process is controlled within ±3%, and the tool head operating temperature is below 150℃. When the amplitude or static pressure deviation exceeds the limit threshold, the equipment automatically stops and issues an alarm signal to ensure the stability of the processing and product quality.

[0197] Laser shock treatment includes:

[0198] 2a: Surface pretreatment

[0199] Functional layers were sequentially prepared on the surface of the USRP-strengthened workpiece: a 100μm thick aluminum foil was used as the laser absorption layer, and a 2mm thick flowing water film was formed on the outside of the aluminum foil as the constraint layer.

[0200] 2b: Laser System and Basic Parameter Settings

[0201] An Nd:YAG pulsed laser was used, with the following technical parameters: laser wavelength 1064nm, pulse width 15ns (FWHM), adjustable repetition frequency range of 1–10Hz, and square output spot. Based on the optimal solution obtained from the optimization algorithm, the process parameters were set, with the spot overlap rate precisely controlled by adjusting the laser scanning step distance.

[0202] 2c: Requirements for multi-pass impact operations

[0203] When using a multi-pass impact process, the condition of the absorption layer is checked after each round of laser scanning: any areas where the aluminum foil has burned through or detached are promptly repaired or the entire piece is replaced, and a continuous water film layer is re-laid before proceeding to the next round of scanning. The spot positions of adjacent passes are offset by D / 4 along the scanning direction to avoid stress concentration caused by repeated loading of the fixed overlap area and to optimize the surface stress field distribution.

[0204] 2d: Online monitoring of LSP process

[0205] The entire processing is monitored by an online system: laser pulse energy is monitored in real time using photodiodes to control energy fluctuations to within a specified range. The position of the light spot is detected using a charge-coupled device (CCD) vision module, and the positional deviation is controlled within... Within; at the same time, it is confirmed in real time that the water film maintains continuous and complete coverage to ensure stable constraint effect.

[0206] The anti-corrosion treatment method for grounding grid materials provided in this application update the particle positions based on fitness. The movement direction of global particles is determined by the current combination of superior and inferior processes, allowing the search process to continuously approach a region with higher anti-corrosion performance while retaining excellent parameter characteristics. By repeatedly calculating fitness and updating positions, the shallow densification effect formed by ultrasonic surface rolling treatment and the deep residual compressive stress effect formed by laser shock treatment are synergistically matched, thereby inhibiting the penetration of corrosive media, delaying crack initiation, and improving surface stability. Ultimately, a target process parameter set suitable for grounding grid materials is obtained, thereby improving the long-term service reliability of composite anti-corrosion treatment. In addition, this embodiment also provides specific evaluation functions, a nonlinear superposition composite residual compressive stress model, a composite surface hardness model, and an influence depth model, which can accurately model and calculate the distribution law of the mechanical properties of the material along the depth after composite strengthening treatment. This supports the optimization design of process parameters, achieving the effect of improving the reliability and efficiency of the determined target process parameter set with lower physical test costs.

[0207] Furthermore, taking Q235 steel as an example, its corresponding target process is process 1 (i.e., "USRP first, then LSP"), and the specific verification process is as follows:

[0208] In this experiment, hot-rolled flat steel (-60×6mm or -50×5mm) or round steel (Φ12mm or Φ16mm) of grade Q235B or Q235C conforming to GB / T 700 standard were selected, and samples were taken from the same batch to ensure consistency. Chemical composition requirements: C 0.14~0.22%, Si≤0.35%, Mn 0.30~0.65%, P≤0.045%, S≤0.045%. At least 20 pieces were sampled from each batch for subsequent group tests.

[0209] The substrate underwent the following pretreatment: the sample was progressively ground using coarse sandpaper (80#), medium sandpaper (400#), and fine sandpaper (800#) (or sandblasted using 60#–80# alumina abrasive at 0.3–0.5 MPa pressure) to control the surface roughness of the sample to 0.8–1.6 μm. Subsequently, the sample was placed sequentially in acetone and anhydrous ethanol solutions and cleaned for 15 minutes each using a 40 kHz ultrasonic cleaner. Finally, the sample surface was dried using compressed air to obtain the pretreated substrate.

[0210] The first strengthened specimen is obtained by USRP (Ultrasound-Reinforced Polymerization) on the pretreated substrate; the second strengthened specimen is obtained by LSP (Laminated Strength Plasma Processing) on ​​the pretreated substrate; the third strengthened specimen is obtained by performing a composite strengthening treatment on the pretreated substrate following the "USRP first, then LSP" procedure; and the fourth strengthened specimen is obtained by performing a composite strengthening treatment on the pretreated substrate following the "LSP first, then USRP" procedure. The process parameters used for processing each strengthened specimen are the same; specific intermediate level parameters for each process can be selected. For example, the process parameters for ultrasonic surface rolling treatment are: The process parameters for laser shock treatment are as follows: .

[0211] Multiple performance tests were conducted on the pretreated substrate, the first strengthened specimen, the second strengthened specimen, the third strengthened specimen, and the fourth strengthened specimen. The tests included peak residual compressive stress, peak surface hardness, surface roughness, and simulated soil solution immersion corrosion rate, supplemented by electrochemical performance characterization. Additionally, the depth of influence of residual compressive stress on each strengthened specimen was also tested. During the experiment, each indicator for each group of specimens was tested five times, and the average of the multiple test results was used as the final valid data.

[0212] The testing methods for each indicator are as follows:

[0213] Residual compressive stress detection: using XRD combined with The residual compressive stress on the material surface was measured using a CrKα target with Fe(211) crystal plane and nine ψ angles. The sample was peeled layer by layer using electropolishing, with a perchloric acid:anhydrous ethanol ratio of 1:9 and a working voltage of 30V. The residual compressive stress depth distribution curve was plotted based on the layer-by-layer test results. And extract the peak value of residual compressive stress from the curve.

[0214] Microhardness testing: A Vickers hardness tester was used, with a test load of HV0.2. The test depth range was from the sample surface to 500 μm inside, with a test point placed every 25 μm along the depth direction. Hardness depth distribution curves were plotted based on the test data. And extract the surface hardness peak from the curve.

[0215] Surface roughness inspection: The inspection was carried out using a stylus profilometer with an evaluation length of 4 mm and a cutoff wavelength of 0.8 mm.

[0216] Accelerated corrosion test:

[0217] a: Immersion weight loss test: A simulated soil solution was prepared with the following components and concentrations: sodium chloride 2 g / L, sodium sulfate 0.5 g / L, sodium bicarbonate 0.3 g / L. The pH of the solution was adjusted to 6.5, and the ambient temperature was maintained at 25℃. The sample was immersed in this solution for 14 consecutive days, and the sample was weighed every 7 days to calculate the corrosion rate. b: Electrochemical testing: Potentiodynamic polarization curve testing was conducted with a scan rate set to 0.5 mV / s; electrochemical impedance spectroscopy (EIS) was performed simultaneously with a frequency range of 10 mV / s. 5 Hz~10 -2 Hz, AC disturbance voltage 10mV.

[0218] Depth of influence of residual compressive stress: The surface grain size was obtained through electron backscatter diffraction (EBSD) analysis. Based on the surface grain size, the depth of influence of residual compressive stress was calculated using the Hall-Petch equation.

[0219] Taking Q235B flat steel with dimensions of 60×6mm as an example, the test values ​​of each sample are as follows:

[0220] Substrate: Peak residual compressive stress -15 MPa (near zero), peak surface hardness 182 HV, surface friction 1.2 μm, 14-day corrosion rate 8.5. .

[0221] The first strengthened specimen had a residual compressive stress peak of 310 MPa, a surface hardness peak of 320 HV, a surface friction force of 0.15 μm, a residual compressive stress influence depth of 185 μm, and a 14-day corrosion rate of 2.38. (Compared to the substrate, it decreased by 72%, that is, the corrosion reduction rate was 72%).

[0222] The second strengthened specimen exhibited a peak residual compressive stress of 380 MPa, a peak surface hardness of 268 HV, a surface friction of 1.8 μm, a residual compressive stress influence depth of 78 μm, and a 14-day corrosion rate of 2.04. (76% lower than the base material).

[0223] The third reinforced specimen exhibited a peak residual compressive stress of 450 MPa, a peak surface hardness of 352 HV, a surface friction of 0.18 μm, a residual compressive stress influence depth of 260 μm, and a 14-day corrosion rate of 0.82. (90.4% lower than the base material).

[0224] The fourth reinforced specimen exhibited a peak residual compressive stress of 405 MPa, a peak surface hardness of 318 HV, a surface friction of 0.14 μm, a residual compressive stress influence depth of 148 μm, and a 14-day corrosion rate of 1.28. (80.9% lower than the substrate).

[0225] The value J3 of the corrosion resistance evaluation function corresponding to the third reinforced specimen is calculated as follows:

[0226]

[0227] The value J4 of the corrosion resistance evaluation function corresponding to the fourth reinforced specimen is calculated as follows:

[0228]

[0229] In practical applications, the weights corresponding to each indicator can be perturbed within the range of 0.25 to 0.45 (for example, the value of J can be calculated in multiple rounds, and weight values ​​can be randomly selected within the range of 0.25 to 0.45 in different rounds of calculation), and the reversal of the J values ​​corresponding to the two processes can be analyzed. In this experiment, after multiple rounds of calculation, the process of "USRP first, then LSP" was consistently superior to "LSP first, then USRP".

[0230] Meanwhile, compared to the third strengthened specimen obtained by composite strengthening treatment according to the "USRP first, then LSP" process, the fourth strengthened specimen obtained by composite strengthening treatment according to the "LSP first, then USRP" process showed a greater reduction in corrosion rate compared to the substrate.

[0231] Furthermore, the third-strengthened specimen exhibits a deeper stress influence depth compared to the fourth-strengthened specimen. Analysis revealed the influence mechanism of the nanocrystalline layer on the shock wave propagation of laser-induced shock treatment: after the shock wave from laser-induced shock treatment enters the material, stress wave splitting occurs at the elasto-plastic interface—the elastic precursor wave propagates at the longitudinal wave velocity, while the plastic wave propagates at a lower velocity. The higher the yield strength of the material, the more significant the elasto-plastic splitting, resulting in more shock wave energy propagating deeper as elastic waves, reducing plastic energy dissipation at the surface. Therefore, the nanocrystalline layer obtained after ultrasonic surface rolling treatment acts as a "high-strength force transmission medium," enabling the shock wave energy from laser-induced shock treatment to be more effectively transferred to deeper layers. This mechanism also effectively demonstrates the superior effect of the "USRP first, then LSP" process.

[0232] Based on the above analysis, it can be concluded that the "USRP first, then LSP" process provides a better overall corrosion protection effect than the "LSP first, then USRP" process. Therefore, process 1 is determined as the target process for Q235 steel.

[0233] Furthermore, Figure 2This is a comprehensive comparison diagram of performance indicators provided in the embodiments of this application, from... Figure 2 As can be seen more intuitively, compared with the first and second strengthened specimens that are subjected to single strengthening treatment, the third strengthened specimen, which can be obtained by using the "USRP first and then LSP" process, has better performance in terms of residual compressive stress peak value, surface hardness peak value, residual compressive stress influence depth, surface roughness and corrosion reduction rate.

[0234] at the same time, Figure 3 The residual compressive stress distribution curve along the depth direction provided for this application. For example... Figure 3 As shown, the blue line represents the residual compressive stress distribution of the material after a single USRP treatment, exhibiting a high level in the shallow layer and a rapid attenuation in the deep layer; the yellow line represents the residual compressive stress distribution of the material after a single LSP treatment, exhibiting a medium level on the surface and a deep penetration; the red line represents the composite stress distribution predicted by the composite residual compressive stress model provided in this application. It can be seen that the composite distribution is significantly higher than that of any single process in the range of 0–100 μm, and the depth of influence exceeds the sum of the two.

[0235] Based on Figure 2 and Figure 3 The relevant analysis shows that the composite strengthening process has a better overall corrosion protection effect than the single strengthening process.

[0236] Furthermore, the verification process for the effectiveness of the aforementioned stress influence depth model is as follows:

[0237] First, nanoindentation tests (Berkovich indenter, maximum load 10 mN) were performed on the nanocrystalline layer of Q235 steel after single USRP treatment. The nanohardness was measured to be H = 4.8 GPa. Based on the Tabor relationship, the corresponding yield strength of the material was calculated to be H / 3 = 1600 MPa. In reality, due to size effect correction, a value of H / 3 was used. The grain size of the substrate obtained by EBSD scanning was 22 μm, which was then calculated using the Hall-Petch equation. XRD layer-by-layer stress measurements were performed on the material after single LSP treatment to obtain... .Will , , Substitute the stress influence depth model provided in this application ( In the prediction, The value is 139.84 μm, which means that the enhancement ratio of LSP to USRP predicted by the stress influence depth model of this application is 139.84 / 78 = 1.79.

[0238] For the material that has undergone USRP treatment followed by LSP treatment, XRD layer-by-layer stress measurement was also performed. The measured depth of residual compressive stress influence was 155 μm, which means that the measured reinforcement ratio of LSP to USRP was 155 / 78 = 1.99.

[0239] Analysis showed that the measured enhancement ratio of 1.99 was slightly higher than the predicted value of 1.79 (a deviation of 11%), possibly because the high dislocation density of the nanocrystalline layer contributed additionally to the stress wave energy transfer. However, the overall deviation was small, so the stress influence depth model provided in this application still has high reliability.

[0240] The validity verification process for the composite residual compressive stress model obtained by the aforementioned nonlinear superposition is as follows:

[0241] First, a finite element model with sequential USRP+LSP loading is established in the finite element analysis software. The USRP load (contact mechanics model) is applied first, followed by the LSP shock wave load. The stress distribution along the depth direction is then extracted. It is used to characterize the residual compressive stress at different depths of the material after the reinforcement treatment.

[0242] Then, actual tests were conducted on the samples to obtain the stress distribution in the depth direction of the material after a single USRP treatment, and the stress distribution after a single LSP treatment. Substituting into the aforementioned composite residual compressive stress model, the calculation yields... .

[0243] After comparison, the results at each depth point (0μm, 25μm, 50μm, 75μm, 100μm, 150μm, 200μm, 250μm, 300μm) showed... and The mean absolute percentage error (MAPE) is 6.8%. The maximum deviation occurs at z=50μm. =-465MPa, =438MPa, deviation 5.8%), thus it can be seen that the verification residual compressive stress model provided in this application can truly reflect the residual compressive stress distribution of the composite-strengthened material.

[0244] Furthermore, the verification of the effectiveness of the surface strengthening treatment is the same as the verification process of the aforementioned residual compressive stress model, and will not be repeated here.

[0245] Furthermore, Embodiment 3 of this application provides a specific method for corrosion protection of grounding grid materials. In this embodiment, the PSO is configured as follows: , Second-rate, , 10 independent runs.

[0246] The optimal solution obtained is: , The optimal solution corresponds to a J value of 3.85. The J value range for one run is 3.79~3.85, with a CV of 0.7%, indicating reliable results. (Details follow...) Figure 4 As shown in the figure, the convergence curve of PSO combined with 8-parameter optimization in this embodiment is illustrated. The horizontal axis represents the number of iterations (0-150), and the vertical axis represents the J value (i.e., the highest fitness value of the population) corresponding to that round. The J value rapidly increases from approximately 2.0 initially to 3.5 after 50 iterations, and then slowly converges to 3.85 after 100 iterations.

[0247] Based on this optimal solution, the material underwent actual composite strengthening treatment in process 1. The measured residual compressive stress peak value was 425 MPa, the surface hardness peak value was 352 HV, the residual compressive stress influence depth was 245 μm, the surface friction force was 0.18 μm, and the 14-day corrosion rate was 0.82. It meets the requirements for a moderately corrosive environment (pH=6.5). The target corrosion rate after 14 days is ≤0.1%. Requirements.

[0248] In addition, this embodiment also conducted a comparative experiment by first independently optimizing the parameters corresponding to the USRP and then independently optimizing the parameters corresponding to the LSP. The process parameters obtained under this comparative experiment are as follows: ;

[0249] The J value corresponding to this set of process parameters is 3.32. It can be seen that the J value obtained through joint optimization is 16% higher than the J value obtained through independent optimization of each process. This is because step-by-step optimization ignores the influence of USRP parameters on the LSP effect (such as Hall-Petch enhancement and the interaction of nonlinear superposition). This also demonstrates the advantage of joint optimization in this application.

[0250] Embodiment 4 of this application provides a specific method for corrosion protection of grounding grid materials. In this embodiment, the PSO is configured as follows: , Second-rate, , 10 independent runs.

[0251] The optimal solution obtained is: ,

[0252] The optimal solution corresponds to a J value of 3.85. The J value range for one run is 3.79~3.85, with a CV of 0.7%, indicating that the result is reliable.

[0253] Furthermore, Embodiment 4 of this application provides a specific method for corrosion protection of grounding grid materials. In this embodiment, the grounding grid material is a round steel material with a size of Φ16mm. During the PSO optimization process, the curvature constraint of the round steel needs to be considered (e.g., adjusting the adjustable range of process parameters), and the optimal solution obtained is: , Its corresponding J value is 3.58.

[0254] First, the round steel material undergoes pretreatment: a rotary turning process is employed. The round steel rotates uniformly around its own axis, while the rolling tool head feeds linearly along the workpiece's axis, achieving continuous and uniform surface strengthening of the cylindrical shape. The process speed is set to 200 rpm, and the corresponding surface linear velocity of the round steel is calculated as follows: To address the issues of reduced contact area and uneven stress distribution caused by the curvature of the round steel, the rolling static pressure is appropriately increased to compensate for these problems and ensure a uniform and consistent surface strengthening effect on the cylinder.

[0255] Based on this optimal solution, the material underwent actual composite strengthening treatment in process 1. The measured residual compressive stress peak value was 408 MPa, the surface hardness peak value was 340 HV, the residual compressive stress influence depth was 215 μm, the surface friction force was 0.20 μm, and the 14-day corrosion rate was 0.95. When applying the LSP process, the LSP step employs circumferential segmented scanning, for example, each segment covering a 60° arc range. The variation in laser incident angle within a single segment is controlled within ±30°, effectively reducing spot distortion. Simultaneously, spot curvature correction (used to adjust process parameters) can be introduced to ensure the uniformity of the cylindrical surface strengthening. Specifically, spot curvature correction... .

[0256] Furthermore, Embodiment 5 of this application provides a specific method for corrosion protection of grounding grid materials. In this embodiment, the grounding grid material is hot-dip galvanized Q235 steel (zinc layer thickness 60-85 μm). During PSO optimization, zinc layer integrity constraints can be considered (e.g., adjusting the adjustable range of process parameters, such as reducing the upper limit of A to 10 μm, F...). s The upper limit is reduced by 350N).

[0257] The optimal solution obtained is: , The optimal solution corresponds to a J value of 2.95. Due to the limited adjustable range of parameters, its J value is lower than that of Q235 bare steel.

[0258] Based on this optimal solution, the material underwent actual composite strengthening treatment using process 1. The measured peak residual compressive stress was 285 MPa, the depth of influence of the residual compressive stress was 125 μm, and the corrosion rate after 14 days was 0.28. The corrosion rate was reduced by 96.7% compared to the substrate due to the dual protection of the zinc layer and the stress field. Additionally, during the composite strengthening process, the absorbent layer needed to be changed to black paint to prevent the aluminum foil-zinc layer reaction.

[0259] Figure 5 This is a schematic diagram of the structure of an anti-corrosion treatment device for grounding grid material provided in Embodiment Six of this application, as shown below. Figure 5 As shown, the anti-corrosion treatment device 20 for grounding grid material provided in this embodiment includes:

[0260] Module 201 is used to construct a corrosion resistance evaluation function based on multiple corrosion resistance evaluation indicators of grounding grid materials.

[0261] Decision module 202 is used to optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment by combining preset constraints with the goal of maximizing the anti-corrosion performance evaluation function, and to obtain the target process parameter set by using a global optimization algorithm. The preset constraints include the adjustable range constraints of the process parameters.

[0262] The processing module 203 is used to perform a composite strengthening treatment on the grounding grid material, including ultrasonic surface rolling and laser shock treatment, according to the target process parameter set.

[0263] In one possible implementation, the decision module 203 is specifically used for:

[0264] The search space is determined based on the adjustable range of process parameters. Multiple particles are randomly generated within the search space. The position of each particle is a set of process parameters, which includes the first process parameters for ultrasonic surface rolling treatment and the second process parameters for laser shock treatment.

[0265] For each particle, after performing composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particle, the anti-corrosion performance of the grounding grid material is extracted. Based on the anti-corrosion performance, the fitness of the particle is calculated using the anti-corrosion performance evaluation function.

[0266] The positions of all particles are updated based on the fitness of each particle.

[0267] The fitness of each particle is recalculated based on its updated position, and the positions of all particles are updated again based on the new fitness of each particle to enter the next iteration round. This step is repeated until the preset iteration termination condition is met to obtain the target process parameter set.

[0268] In one possible implementation, the construction module 202 is specifically used for:

[0269] Peak residual compressive stress Surface hardness peak H maxAnd using the residual compressive stress influence depth z0 as an evaluation index for corrosion resistance performance, the expression for the corrosion resistance performance evaluation function J is constructed as follows:

[0270]

[0271] Among them, w1, w2, and w3 are the weights corresponding to each corrosion resistance performance evaluation index; This is a preset reference value for the peak residual compressive stress index; H ref z0 is a preset reference value for the peak surface hardness index; z0 is a preset reference value for the depth of influence of residual compressive stress index.

[0272] In one possible implementation, the decision module is specifically used for:

[0273] The ultrasonic surface rolling process of the grounding grid material is simulated by using the first process parameters corresponding to the particles through the finite element model or proxy model. This is to obtain the first surface grain size of the material after a single ultrasonic surface rolling process, as well as the first residual compressive stress and the first surface hardness of the material at different depths.

[0274] The laser shock treatment of grounding grid material is simulated by using the finite element model or proxy model of laser shock with the second process parameters corresponding to the particles, so as to obtain the influence depth of the first residual compressive stress of the material after a single laser shock treatment, as well as the second residual compressive stress and the second surface hardness of the material at different depths.

[0275] Based on the first and second residual compressive stresses at different depths of the material, a composite residual compressive stress model is constructed, and based on the first and second surface hardnesses at different depths of the material, a composite surface hardness model is constructed.

[0276] The peak value of residual compressive stress of the composite-strengthened material is extracted from the composite residual compressive stress model, the peak value of surface hardness of the composite-strengthened material is extracted from the composite surface hardness model, and the depth of influence of the second residual compressive stress of the composite-strengthened material is calculated based on the first surface grain size, the second surface grain size of the grounding grid material before strengthening treatment, and the depth of influence of the first residual compressive stress.

[0277] Among them, the composite residual compressive stress model is used to indicate the residual compressive stress of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set; the surface hardness model is used to indicate the surface hardness of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set.

[0278] In one possible implementation, the decision module 202 is specifically used for:

[0279] After performing actual composite reinforcement treatment on the grounding grid material according to the process parameter set, the surface roughness of the grounding grid material is obtained by actual measurement method.

[0280] In one possible implementation, the composite residual compressive stress model is as follows:

[0281]

[0282] in, This represents the residual compressive stress at different depths z of the material after composite strengthening treatment; This represents the stress coupling correction factor; This represents the yield strength of the material at different depths z after composite strengthening treatment; This represents the residual compressive stress at different depths z of the material after a single ultrasonic surface roll forming treatment. This represents the residual compressive stress at different depths z of the material after a single laser shock treatment.

[0283] In one possible implementation, the composite surface hardness model is as follows:

[0284]

[0285]

[0286]

[0287] in, The surface hardness of the material at different depths z after composite strengthening treatment is represented; H0 represents the base material hardness of the grounding grid material; μ represents the hardness coupling correction coefficient. This indicates the surface hardness of the material at different depths z after a single ultrasonic surface roll forming treatment. This indicates the surface hardness of the material at different depths z after a single laser shock treatment.

[0288] In one possible implementation, the decision module 202 is specifically used for:

[0289] The Hall-Petch equation is used to calculate the first yield strength corresponding to the first surface grain size and the second yield strength corresponding to the second surface grain size.

[0290] Based on the first yield strength, the second yield strength, and the first residual compressive stress influence depth, the second residual compressive stress influence depth of the material after composite strengthening treatment is calculated using the stress influence depth model.

[0291] The stress influence depth model is as follows:

[0292]

[0293]

[0294] in, z1 represents the depth of influence of the second residual compressive stress; z2 represents the depth of influence of the first residual compressive stress. Indicates the first yield strength; Indicates the second yield strength; This represents the correction coefficient that affects deep coupling.

[0295] The anti-corrosion treatment device 20 for grounding grid material provided in this embodiment can perform the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0296] Figure 6 A schematic diagram of the structure of the computer device provided in this application. Figure 6 As shown, the computer device 30 provided in this embodiment includes at least one processor 301 and a memory 302. Optionally, the device 30 further includes a communication component 303. The processor 301, memory 302, and communication component 303 are connected via a bus 304.

[0297] In a specific implementation, at least one processor 301 executes computer execution instructions stored in memory 302, causing at least one processor 301 to perform the above-described method.

[0298] The specific implementation process of processor 301 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0299] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0300] The memory may include read-only memory and random access memory. The memory may be volatile or non-volatile, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. Many forms of RAM are available by way of example, but not limitation. Examples include Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Sync Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0301] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0302] This application also provides a computer program product, including a computer program that, when executed, implements the above-described method.

[0303] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed, implement the above-described method.

[0304] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as SRAM, EEPROM, EPROM, PROM, ROM, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0305] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside within an ASIC. Alternatively, the processor and the readable storage medium can exist as discrete components in a device.

[0306] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0307] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0308] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0309] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0310] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0311] The above embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention.

[0312] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for corrosion protection of grounding grid material, characterized in that, The method includes: Based on multiple anti-corrosion performance evaluation indicators of grounding grid materials, an anti-corrosion performance evaluation function is constructed. With the goal of maximizing the corrosion resistance performance evaluation function, and in conjunction with preset constraints, a global optimization algorithm is used to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment to obtain a target set of process parameters; the preset constraints include adjustable range constraints of process parameters. According to the target process parameter set, the grounding grid material is subjected to a composite strengthening treatment including ultrasonic surface rolling and laser shock treatment.

2. The method according to claim 1, characterized in that, The objective is to maximize the corrosion resistance performance evaluation function. Combined with preset constraints, a global optimization algorithm is used to jointly optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment, resulting in a target process parameter set, including: The search space is determined based on the adjustable range of the process parameters. Multiple particles are randomly generated in the search space. The position of each particle is a set of process parameters. The set of process parameters includes the first process parameters of the ultrasonic surface rolling treatment and the second process parameters of the laser shock treatment. For each particle, after performing the composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particle, the anti-corrosion performance of the grounding grid material is extracted, and the fitness of the particle is calculated using the anti-corrosion performance evaluation function based on the anti-corrosion performance. The positions of all particles are updated based on the fitness of each particle. The fitness of each particle is recalculated based on its updated position, and the positions of all particles are updated again based on the new fitness of each particle to enter the next iteration round. This step is repeated until the preset iteration termination condition is met, and the target process parameter set is obtained.

3. The method according to claim 2, characterized in that, The corrosion resistance performance evaluation function is constructed based on multiple corrosion resistance performance evaluation indicators of the grounding grid material, including: Peak residual compressive stress Surface hardness peak and depth of influence of residual compressive stress As the evaluation index for corrosion resistance, the corrosion resistance evaluation function is constructed. The expression is: in, , as well as The weights corresponding to each corrosion resistance performance evaluation index; This is a preset reference value for the peak residual compressive stress index; This is a preset reference value for the peak surface hardness index; This is a preset reference value for the depth of influence of residual compressive stress.

4. The method according to claim 3, characterized in that, After performing the composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particles, the corrosion resistance of the grounding grid material is extracted, including: The ultrasonic surface rolling process of the grounding grid material is simulated using the first process parameters corresponding to the particles through a finite element model or proxy model, so as to obtain the first surface grain size of the material after a single ultrasonic surface rolling process, as well as the first residual compressive stress and the first surface hardness of the material at different depths. The laser shock treatment of the grounding grid material is simulated using the second process parameters corresponding to the particles through a finite element model or proxy model, so as to obtain the first residual compressive stress influence depth of the material after a single laser shock treatment, as well as the second residual compressive stress and the second surface hardness of the material at different depths. Based on the first and second residual compressive stresses at different depths of the material, a composite residual compressive stress model is constructed, and based on the first and second surface hardnesses at different depths of the material, a composite surface hardness model is constructed. The peak value of residual compressive stress of the composite-strengthened material is extracted from the composite residual compressive stress model, the peak value of surface hardness of the composite-strengthened material is extracted from the composite surface hardness model, and the depth of influence of the second residual compressive stress of the composite-strengthened material is calculated based on the first surface grain size, the second surface grain size of the grounding grid material when it is not strengthened, and the depth of influence of the first residual compressive stress. The composite residual compressive stress model is used to indicate the residual compressive stress of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set; the surface hardness model is used to indicate the surface hardness of the grounding grid material at different depths after composite strengthening treatment according to the process parameter set.

5. The method according to claim 3, characterized in that, The corrosion resistance evaluation index also includes surface roughness; correspondingly, after performing the composite strengthening treatment on the grounding grid material according to the process parameter set corresponding to the particles, the extraction of the corrosion resistance of the grounding grid material also includes: After the grounding grid material is subjected to actual composite strengthening treatment according to the process parameter set, the surface roughness of the grounding grid material is obtained by actual measurement method.

6. The method according to claim 4, characterized in that, The composite residual compressive stress model is as follows: in, This represents the residual compressive stress at depth z in the material after composite strengthening treatment; This represents the stress coupling correction factor; This represents the yield strength of the material at depth z after composite strengthening treatment; This represents the residual compressive stress at depth z in the material after a single ultrasonic surface roll forming treatment. This represents the residual compressive stress at depth z in the material after a single laser shock treatment.

7. The method according to claim 4, characterized in that, The hardness model of the composite surface layer is as follows: in, This indicates the surface hardness of the material at depth z after composite strengthening treatment; Indicates the hardness of the base material of the grounding grid; This represents the hardness coupling correction factor; This indicates the surface hardness of the material at depth z after a single ultrasonic surface roll forming treatment. This indicates the surface hardness of the material at depth z after a single laser shock treatment.

8. The method according to claim 4, characterized in that, The step of calculating the second residual compressive stress influence depth of the composite-strengthened material based on the first surface grain size, the second surface grain size of the grounding grid material before strengthening treatment, and the first residual compressive stress influence depth includes: The Hall-Petch equation is used to calculate the first yield strength corresponding to the first surface grain size and the second yield strength corresponding to the second surface grain size. Based on the first yield strength, the second yield strength, and the first residual compressive stress influence depth, the second residual compressive stress influence depth of the material after composite strengthening treatment is calculated using the stress influence depth model. The stress influence depth model is as follows: in, This indicates the depth of influence of the second residual compressive stress; This indicates the depth of influence of the first residual compressive stress; This represents the first yield strength; Indicates the second yield strength; This represents the correction coefficient that affects deep coupling.

9. A corrosion protection device for grounding grid material, characterized in that, The device includes: The module is used to construct corrosion performance evaluation functions based on multiple corrosion performance evaluation indicators of grounding grid materials; The decision module is used to optimize the process parameters of ultrasonic surface rolling treatment and laser shock treatment by combining preset constraints with the goal of maximizing the anti-corrosion performance evaluation function, and to obtain the target process parameter set by using a global optimization algorithm. The preset constraints include the adjustable range constraints of the process parameters. The processing module is used to perform a composite strengthening treatment on the grounding grid material, including ultrasonic surface rolling and laser shock treatment, according to the target process parameter set.

10. A computer device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-8.

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