A design method for multi-element weather-resistant special panels

Abstract

The present application relates to the field of data processing technology, and discloses a multi-element weather-resistant special plate design method. The method comprises: performing trapezoidal cross-section design processing on the geometric structure of the special plate according to the axial force distribution law to obtain the equal-width variable thickness tapping parameters, performing stress matching calculation processing on the equal-width variable thickness tapping parameters through a mechanical analysis algorithm to obtain thickness-force correspondence data, performing weather resistance fusion processing on the multi-element formula system and the thickness-force correspondence data to obtain a material composition distribution scheme, and performing hot rolling forming optimization processing on the special plate manufacturing process according to the material composition distribution scheme to obtain the multi-element weather-resistant special plate design parameters. The present application solves the technical problems in the existing steel plate design that the geometric structure and the axial force distribution are not matched, and the multi-element formula system lacks a design fusion with the force characteristics. At the same time, it solves the technical problems that the manufacturing process of the variable thickness special-shaped plate lacks systematic optimization and cannot achieve precise forming control of equal-width and unequal-thickness structures.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method for designing multi-element weather-resistant special panels. Background Art

[0002] Existing steel plate manufacturing technology mainly adopts a uniform thickness design scheme, and produces standard steel plate products with uniform specifications through a hot rolling process. In application fields such as power towers, wind turbine towers, and street light poles, the traditional practice is to connect multiple pieces of uniform thickness steel plates through a welding process to form the required structural shape. In order to meet weather resistance requirements, surface treatment technologies such as hot-dip galvanizing are usually used for corrosion protection. The geometric design of steel plates in existing technologies is mainly based on the assumption of uniform stress, and the changing laws of axial stress distribution in actual engineering are not fully considered. The material formula design is relatively simple, and the performance of steel is mainly improved by adding a single or a few alloying elements.

[0003] The shortcomings of existing technologies are mainly reflected in the mismatch between geometric design and force distribution, resulting in low material utilization. Steel plates of equal thickness cannot achieve optimal material configuration when subjected to varying loads. Multi-stage welding processes increase manufacturing costs and structural complexity. Surface treatment processes such as hot-dip galvanizing not only increase production costs by 500-1000 yuan per ton, but also pose environmental pollution problems. Traditional material formulas cannot simultaneously meet the dual requirements of high strength and excellent weather resistance. Existing design methods lack systematic optimization means and cannot find the best balance between lightweight, economy and weather resistance.

[0004] Further analysis found that the existing technology lacks a geometric structure design method for the axial force distribution law, cannot establish an accurate correspondence between thickness changes and force distribution, lacks the fusion design technology of multi-element formula system and structural force characteristics, cannot achieve the optimal distribution of material components in space, lacks the manufacturing process optimization technology for variable thickness special-shaped plates, and cannot solve the problem of precise forming control of equal width and unequal thickness structures. The existence of these technical problems limits the development of steel plate products in the direction of lightweight, high performance and low cost. There is an urgent need to develop a systematic multi-element weather-resistant special plate design method to solve the above technical difficulties. Summary of the Invention

[0005] This application provides a multi-element weather-resistant, special-shaped plate design method to address the technical issues in existing steel plate design, such as the mismatch between geometric structure and axial stress distribution, and the lack of a multi-element formulation system integrated with stress characteristics. It also addresses the technical issues of a lack of systematic optimization in the manufacturing process for variable-thickness special-shaped plates, and the inability to achieve precise forming control for structures with uniform widths and unequal thicknesses.

[0006] The present application provides a multi-element weather-resistant heterogeneous plate design method, which includes: performing trapezoidal cross-section design processing on the heterogeneous plate geometric structure according to the axial force distribution law to obtain equal-width variable-thickness tapping parameters; performing stress matching calculation processing on the equal-width variable-thickness tapping parameters through a mechanical analysis algorithm to obtain thickness-force correspondence data; performing weather resistance fusion processing on the multi-element formula system and the thickness-force correspondence data to obtain a material composition distribution scheme; performing hot rolling forming optimization processing on the heterogeneous plate manufacturing process according to the material composition distribution scheme to obtain multi-element weather-resistant heterogeneous plate design parameters.

[0007] In the technical solution provided by the present application, the equal-width variable-thickness tapping parameters are obtained by performing trapezoidal cross-section design on the geometric structure of the heterogeneous plate according to the axial force distribution law, thereby solving the problem of mismatch between traditional equal-thickness steel plates and actual force distribution, achieving accurate correspondence between plate thickness and axial force, so that areas with large thickness bear large loads and areas with small thickness bear small loads, avoiding excessive and insufficient configuration of materials, and achieving a 5%-30% saving in steel weight while ensuring bearing capacity. At the same time, the axial bearing capacity does not decrease but increases by 10%-20%. The stress matching calculation of the equal-width variable-thickness tapping parameters is performed through a mechanical analysis algorithm to obtain thickness-force correspondence relationship data, and a quantitative relationship between plate geometric parameters and mechanical properties is established, providing information for subsequent material formula design. It has a precise mechanical basis and avoids the inaccuracy of relying on empirical estimation in traditional design. The multi-element formula system and thickness-force correspondence data are fused for weather resistance to obtain the material composition distribution scheme, which realizes the optimized spatial distribution of six elements such as niobium, aluminum, vanadium, titanium, silicon and molybdenum, so that the high stress area has a better strengthening element ratio and the low stress area has a better weathering element ratio, which solves the problem that the traditional uniform formula cannot take into account the performance requirements of different regions. According to the material composition distribution scheme, the hot rolling forming process of the special plate manufacturing process is optimized to obtain the multi-element weathering special plate design parameters, which solves the process control problem in the manufacturing process of variable thickness special-shaped plates, realizes the coordinated optimization of temperature, reduction and rolling speed, and ensures the forming accuracy and quality stability of the product.

[0008] In the specific application field of multi-element weather-resistant heterogeneous plate design, the application of mechanical analysis algorithms has significantly improved the design accuracy and optimization effect. The algorithm realizes the precise conversion from geometric parameters to mechanical responses through a series of data processing steps such as cross-sectional geometric characteristic calculation, point-by-point calculation of axial stress distribution, and differential calculation of thickness change rate for equal-width and variable-thickness tapping parameters. The core contribution of the algorithm is to establish a mathematical mapping relationship between thickness and force, which transforms the design process from qualitative analysis to quantitative calculation, avoiding the subjective judgment and experience dependence in traditional design. The application of interpolation algorithm and numerical integration algorithm realizes the continuous processing of discrete data and the accurate calculation of cumulative effect, providing reliable data for the mechanical analysis of complex geometric shapes. Numerical foundations, optimization algorithms, especially the application of Lagrange multiplier method in process parameter optimization, realize the search for global optimal solutions under multi-objective and multi-constraint conditions through algorithm features such as constraint condition construction, objective function establishment, iterative solution, and convergence judgment. The convergence and stability of the algorithm ensure the reliability and engineering applicability of the optimization results. The synergistic effect of these artificial intelligence algorithms has enabled the complex multi-element weather-resistant heterogeneous plate design problems to be systematically solved. Compared with the traditional trial and error method, the algorithm-driven design method has greatly improved the design efficiency and product performance, and achieved the comprehensive optimization goals of lightweight, high performance and low cost, providing important support for the technological upgrade of key infrastructure such as power towers, wind turbine towers, and street light poles. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 This is a schematic diagram of an embodiment of the multi-element weather-resistant special board design method in the embodiment of this application. DETAILED DESCRIPTION

[0011] An embodiment of the present application provides a method for designing a multi-element weather-resistant heterogeneous panel. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, methods, products or apparatus.

[0012] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In the embodiment of the present application, an embodiment of the multi-element weather-resistant plate design method includes:

[0013] Step S101: perform trapezoidal cross-section design on the geometric structure of the different plates according to the axial force distribution law to obtain the constant width and variable thickness tapping parameters;

[0014] Step S102: performing stress matching calculation on the constant-width variable-thickness tapping parameters using a mechanical analysis algorithm to obtain thickness-stress correspondence data;

[0015] Step S103: performing weather resistance fusion processing on the multi-element formula system and the thickness-stress correspondence relationship data to obtain a material composition distribution scheme;

[0016] Step S104: performing hot rolling optimization processing on the heterogeneous plate manufacturing process according to the material composition distribution scheme to obtain multi-element weather-resistant heterogeneous plate design parameters.

[0017] Specifically, when designing a trapezoidal cross-section of a heterogeneous plate geometry according to the axial force distribution law, it is necessary to collect the actual working condition data of the power tower or wind turbine tower, and obtain the load change curve along the axial distribution by performing force analysis on the heterogeneous plate application conditions. This curve reflects the law of decreasing force from the large end to the small end. Subsequently, the geometric dimensions of the plate are subjected to equal width constraint design according to the axial force distribution curve data to ensure that the plate width remains parallel while the thickness changes in a trapezoidal state. The thickness change gradient is optimized and calculated based on the width parallelization parameter, and the optimal thickness difference is calculated through a numerical iterative algorithm to convert the thickness trapezoidal The distribution data is input into the geometric modeling algorithm for cross-section parameter generation. The algorithm first performs numerical discretization on the thickness trapezoidal distribution data, converts the continuous thickness change into discrete node coordinates, performs geometric constraint calculation on the tapping angle according to the thickness node coordinate set, determines the tapping angle numerical range through the trigonometric function relationship, performs continuous interpolation processing on the cross-section profile based on the tapping angle numerical range, uses the spline interpolation algorithm to generate a smooth cross-section transition curve, and inputs the smooth cross-section curve into the parametric modeling program for geometric reconstruction. Finally, the equal-width variable-thickness tapping parameters containing the length, width, and thickness change rules are obtained. When performing stress matching calculation on the parameters of the equal-width variable-thickness tapping through the mechanical analysis algorithm, the cross-sectional geometric characteristics of the parameters of the equal-width variable-thickness tapping are calculated, the moment of inertia value of each section is calculated through integral operation, the axial stress distribution is calculated point by point based on the moment of inertia data set of each section, the stress value of each section is calculated using the material mechanics formula, the thickness change rate is differentially derived and calculated based on the stress gradient numerical sequence, the mathematical relationship between thickness and stress change rate is established through the numerical differentiation algorithm, the thickness-stress change rate correlation matrix is ​​input into the interpolation algorithm for data smoothing, the numerical fluctuation in the calculation process is eliminated, the continuous stress distribution function is numerically integrated and calculated, the cumulative stress load is calculated through the Simpson integral method, the thickness parameter is reversely mapped and calculated based on the cumulative stress load data, a one-to-one correspondence between thickness and force is established, and thickness-force correspondence relationship data is formed.

[0018] When the multi-element formula system is integrated with the thickness-stress correspondence data for weather resistance, the component weight distribution calculation of the multi-element formula system is performed. According to the content ranges of niobium 0.03-0.15%, aluminum 0.2-0.65%, vanadium 0.02-1.2%, titanium 0.3-0.9%, silicon 0.5-1%, and molybdenum 0.5-1.5%, a niobium, aluminum, vanadium, titanium, silicon, and molybdenum element concentration matrix is ​​established. According to the niobium, aluminum, vanadium, titanium, silicon, and molybdenum element concentration matrix, the weather resistance performance index is quantitatively evaluated. The comprehensive weather resistance performance value is calculated by the weighted summation algorithm. Based on the weather resistance performance data The thickness-stress correspondence data were analyzed and processed based on the value sequence, and the Pearson correlation coefficient algorithm was used to calculate the correlation strength between composition and mechanical properties. The composition-thickness-stress ternary relationship table was input into the optimization algorithm to adjust the formula ratio. The optimal component ratio was found through the genetic algorithm. The spatial distribution of the optimized component ratio data was calculated, and the concentration gradient of each element along the thickness direction was calculated. The uniformity of the material structure was checked according to the element gradient distribution along the thickness direction. The uniformity of the component distribution was verified through variance analysis, and the material component distribution plan was obtained. When hot rolling forming optimization is performed on the manufacturing process of heterogeneous plates according to the material composition distribution scheme, the rolling temperature range calculation is performed on the material composition distribution scheme, the most suitable rolling temperature range is calculated according to the melting point and precipitation temperature of each element, the gradient setting processing is performed on the roll gap change according to the segmented temperature control data, the reduction distribution at different positions is determined by numerical calculation, the rolling speed parameters are synchronously adjusted based on the reduction distribution sequence, and a matching relationship between speed and reduction is established. The speed-reduction matching relationship is input into the process parameter optimization algorithm for numerical solution processing. The algorithm constructs constraint conditions for the speed-reduction matching relationship and sets the process parameters. The upper and lower boundary constraints are set, and the objective function is established with multiple variables according to the process parameter boundary constraint matrix. An optimization function with plate quality as the target is constructed. The Lagrange multiplier method is iteratively solved based on the rolling quality evaluation function. The optimal solution that meets the constraints is found through numerical iteration. The set of candidate solutions of process parameters is input into the convergence judgment algorithm for optimal solution screening. The parameter combination with the highest convergence accuracy is selected, and the forming accuracy verification calculation of the optimal rolling process parameter combination is performed. The thickness deviation control effect is verified by finite element analysis. The process parameters are fine-tuned and corrected according to the thickness deviation control data, and finally the design parameters of multi-element weather-resistant special plates are obtained.

[0019] Taking a power tower project as an example, the length of the plate was set to 12 meters and the width to 4 meters, with the thickness varying linearly from 60 mm to 20 mm. A force analysis revealed a distribution curve of axial force decreasing from 300 kN at the tower base to 100 kN at the top. This distribution curve was numerically discretized to obtain 24 thickness node coordinates, with each node spaced 0.5 meters apart. Geometric constraint calculations determined a 1.9-degree taper angle. A cubic spline interpolation algorithm was used to generate a smooth cross-sectional curve. Mechanical analysis algorithms calculated the stress at 60 mm to be 200 MPa and at 20 mm to be 150 MPa. A linear thickness-force relationship was established, and the niobium content was set to 0. The formula of 0.08%, 0.4% aluminum, 0.6% vanadium, 0.6% titanium, 0.75% silicon and 1.0% molybdenum was integrated with mechanical data, and the correlation analysis determined that niobium element has the strongest correlation with high stress area. The optimized composition distribution scheme adjusted the niobium content to 0.12% at the thick end and maintained it at 0.05% at the thin end. The rolling temperature was set to a gradient control of 1150℃ to 950℃. The reduction was rolled from the initial 80 mm in 8 passes to the final thickness. The rolling speed was gradually adjusted from 1.2 meters per second to 0.8 meters per second. The final process parameter combination was optimized by the Lagrange multiplier method to achieve thickness deviation control within the range of ±0.5 mm.

[0020] In a specific embodiment, the process of executing step S101 may specifically include the following steps:

[0021] Perform stress analysis on the working conditions of different plates to obtain axial force distribution curve data;

[0022] According to the axial force distribution curve data, the plate geometric dimensions are subjected to equal width constraint design processing to obtain the width parallelization parameters;

[0023] Based on the width parallelization parameter, the thickness gradient is optimized and calculated to obtain the thickness trapezoidal distribution data;

[0024] The thickness trapezoidal distribution data is input into the geometric modeling algorithm to generate cross-section parameters and obtain the constant width and variable thickness tapping parameters.

[0025] Specifically, when performing stress analysis on heterogeneous plate application conditions, it is necessary to obtain the load distribution in specific application scenarios such as power towers, wind turbine towers, and street light poles. By collecting stress data of the structure under various working conditions such as wind load, deadweight, and power equipment load, the law of axial force change from the root to the top of the structure is established. This analysis process simplifies the complex loads in actual engineering into a concentrated force sequence distributed along the axial direction. Each position point corresponds to a specific axial force value. The discrete force value points are connected into continuous axial force distribution curve data through a numerical fitting algorithm. The curve reflects the gradual weakening of the force from the large end to the small end. The slope of the curve represents the rate of change of the axial force, and the integral value of the curve represents the total axial load. The axial force distribution curve data becomes the core basis for subsequent geometric design.

[0026] When performing equal-width constraint design processing on the geometric dimensions of the plate according to the axial force distribution curve data, the peak points and valley points of the axial force distribution curve are first extracted to determine the cross-sectional positions corresponding to the maximum axial force and the minimum axial force. Based on the design concept of equal width and unequal thickness, the plate width is set to a fixed value. The width value is determined according to the load-bearing requirements of the structure and the manufacturing process limitations. The width parallelization parameters include the fixed width value of the plate, the geometric constraints in the width direction, and the boundary conditions for the width to remain parallel. In the process of determining the width parallelization parameters, the load transfer path of the axial force distribution curve needs to be considered to ensure that the change in thickness can match the distribution of the axial force under the premise of unchanged width. The width parallelization parameters become the constraints for the thickness change design.

[0027] When the thickness change gradient is optimized and calculated based on the width parallelization parameter, the tipping refers to the conical change of the plate thickness along the axial direction, and the gradient represents the rate of thickness change. The tipping optimization calculation requires converting the axial force distribution curve into a thickness distribution curve. This conversion process is based on the relationship between stress and section modulus in material mechanics. The starting point of the thickness distribution curve corresponds to the maximum thickness at the maximum axial force position, and the end point corresponds to the minimum thickness at the minimum axial force position. The thickness of each intermediate point is calculated by linear interpolation or nonlinear interpolation algorithm. The goal of the tipping optimization calculation is to minimize the material usage while meeting the bearing capacity. The calculation process adopts a numerical optimization algorithm, with thickness distribution as the design variable, minimum material usage as the objective function, and bearing capacity satisfaction as the constraint condition. The optimal thickness change gradient is obtained through iterative calculation. The thickness trapezoidal distribution data contains the thickness values ​​at each position along the axial direction and the gradient information of the thickness change.

[0028] When the thickness trapezoidal distribution data is input into the geometric modeling algorithm for cross-section parameter generation, the geometric modeling algorithm first performs numerical discretization on the thickness trapezoidal distribution data, converting the continuous thickness change curve into a finite number of discrete thickness nodes. Each node contains the axial position coordinates and the corresponding thickness value. The accuracy of the discretization determines the accuracy of the subsequent geometric reconstruction. The selection of the number of nodes needs to balance the calculation accuracy and calculation efficiency. Then, the geometric constraint calculation of the tapping angle is performed based on the thickness node coordinate set. The tapping angle refers to the angle between the thickness change direction and the axial direction. The angle is calculated by the thickness difference and axial spacing of adjacent thickness nodes. The geometric constraint calculation needs to ensure that the tapping angle is within the appropriate range. Within the reasonable range, avoid stress concentration caused by too large an angle or material waste caused by too small an angle, and perform continuous interpolation processing on the cross-sectional profile based on the numerical range of the tapping degree. The interpolation algorithm connects discrete thickness nodes into a smooth cross-sectional profile curve. The interpolation methods include linear interpolation, spline interpolation, etc. The interpolation results need to meet the requirements of continuity and differentiability. Finally, the smooth cross-sectional curve is input into the parametric modeling program for geometric reconstruction. The parametric modeling program generates a three-dimensional geometric model according to the cross-sectional profile curve. The model contains all geometric information such as the length, width, and thickness changes of the different plates. The equal-width and variable-thickness tapping parameters include key geometric parameters such as the total length of the different plates, fixed width, thickness change law, and tapping angle.

[0029] In a specific embodiment, the step of inputting the thickness trapezoidal distribution data into the geometric modeling algorithm for cross-section parameter generation processing may specifically include the following steps:

[0030] Perform numerical discretization on the thickness trapezoidal distribution data to obtain the thickness node coordinate set;

[0031] The geometric constraint calculation of the tapping angle is performed according to the thickness node coordinate set to obtain the tapping degree range;

[0032] Based on the numerical range of the taper degree, the cross-section profile is continuously interpolated to obtain a smooth cross-section curve;

[0033] The smooth cross-section curve is input into the parametric modeling program for geometric reconstruction to obtain the constant width and variable thickness tapping parameters.

[0034] Specifically, when performing numerical discretization on the thickness trapezoidal distribution data, the continuous thickness change curve is converted into a finite number of discrete data points. The discretization process adopts an equally spaced sampling method, and the sampling interval is determined according to the total length of the heterogeneous plate and the accuracy requirements. Each sampling point contains the axial position coordinates and the corresponding thickness value. The discretization accuracy directly affects the accuracy of subsequent calculations. Too few sampling points will lead to the loss of geometric information, and too many sampling points will increase the calculation complexity. The thickness node coordinate set contains the spatial coordinate information of all sampling points. The coordinates of each node are composed of three components: axial position, lateral position, and thickness value. The node coordinate set is arranged in order from small to large according to the axial position to form an ordered data sequence. When the tapping angle is geometrically constrained and calculated based on the thickness node coordinate set, the tapping angle refers to the angle between the thickness change direction of the heterogeneous plate and the axial direction. The angle is calculated by the ratio of the thickness difference of adjacent nodes to the axial spacing. The calculation process uses the inverse tangent function to convert the thickness gradient into an angle value. The geometric constraint calculation needs to check whether the tapping angle of each node position is within a reasonable range. Excessive tapping angles will lead to stress concentration and manufacturing difficulties, and excessively small tapping angles will lead to low material utilization. The tapping degree range is obtained by counting the tapping angles of all node positions. The range includes statistical parameters such as the minimum tapping angle, the maximum tapping angle, and the average tapping angle. The determination of the tapping degree range needs to consider the uniformity requirements of mechanical transmission and the feasibility of the manufacturing process.

[0035] When performing continuity interpolation on the cross-sectional profile based on the numerical range of the taper degree, the interpolation algorithm connects the discrete thickness nodes into a continuous and smooth curve. The selection of the interpolation method needs to consider the continuity and differentiability requirements of the curve. The linear interpolation method is simple but will produce corner points, and the spline interpolation method is complex but can ensure the smoothness of the curve. The interpolation process first constructs the interpolation basis function, then calculates the interpolation coefficient through the node coordinates, and finally generates a continuous cross-sectional profile function. The mathematical expression of the smooth cross-sectional curve contains the correspondence between the axial position variable and the thickness function. The first-order derivative of the curve represents the thickness change rate, and the second-order derivative represents the thickness change acceleration. The interpolation result needs to meet the boundary conditions and continuity constraints.

[0036] When a smooth cross-section curve is input into a parametric modeling program for geometric reconstruction, the parametric modeling program generates a three-dimensional geometric model based on the cross-section profile curve. The geometric reconstruction process includes steps such as curve stretching, surface generation, and solid construction. The stretching operation sweeps the two-dimensional cross-section profile along the axial direction to generate a three-dimensional surface. The surface generation process needs to process the connection and stitching of the surface. The solid construction converts the closed surface into a solid geometric model. The equal-width and variable-thickness tapping parameters contain complete information such as the geometric size, shape characteristics, and manufacturing constraints of the heterogeneous plate. The parameters include key geometric features such as the total length of the heterogeneous plate, fixed width, thickness change function, tapping angle distribution, and surface smoothness.

[0037] Take the design of a special plate of a power steel tower as an example. The power steel tower bears wind loads and the weight of power equipment. The length of the special plate is 15 meters, corresponding to a standard section of the tower body. The thickness trapezoidal distribution data obtained according to the previous mechanical analysis shows that the thickness decreases linearly from 70 mm at the root to 25 mm at the top. When the thickness distribution data is numerically discretized, 0.5-meter equal-interval sampling is used to obtain 31 thickness nodes. Each node contains axial coordinates, thickness values, lateral boundary coordinates and other information. The axial coordinate of the first node is 0 meters and the thickness is 70 mm. The axial coordinate of the 31st node is 15 meters and the thickness is 25 mm. The thickness of each intermediate node is calculated by linear interpolation. The thickness node coordinate set is sorted according to the axial position to form an ordered array. The tapping angle of each position is calculated based on the thickness node coordinate set. The thickness difference between adjacent nodes is 1.5 mm, the axial spacing is 0.5 meters, and the tapping angle is 0.17 degrees calculated by the inverse tangent function. The tapping angle of all node positions is 0.17 degrees and remains consistent. The minimum, maximum and average values ​​of the tapping degree range are all 0.17 degrees. This angle value meets the geometric constraint requirements of trapezoidal section design. The cubic spline interpolation algorithm is used to continuously interpolate the section profile based on the numerical range of the taper angle. The interpolation algorithm first calculates the first-order derivative and second-order derivative of each node position, and then constructs a cubic polynomial interpolation function. The thickness value of the smooth section curve generated by the interpolation result at each node position is completely consistent with the original data. The continuity of the first-order derivative of the curve indicates that the thickness changes smoothly without abrupt changes, and the continuity of the second-order derivative indicates that the curvature changes smoothly without inflection points. After the smooth section curve is input into the parametric modeling program, the modeling program first reads the mathematical expression and boundary conditions of the curve, and then sweeps the section profile along the width direction through a stretching operation to generate a three-dimensional geometric surface of the heterogeneous plate. The stretching width is set to a standard of not less than 2 meters. The surface generation process processes the surface connection and edge closure of the thickness change area. The final generated equal-width variable-thickness tapping parameters include complete geometric information such as length 15 meters, width 3 meters, continuous thickness change from 70 mm to 25 mm, tapping angle 0.17 degrees, and surface smoothness that meets manufacturing requirements.

[0038] In a specific embodiment, the process of executing step S102 may specifically include the following steps:

[0039] The cross-sectional geometric characteristics of the constant width and variable thickness tapping parameters are calculated and processed to obtain the moment of inertia data set of each section;

[0040] The axial stress distribution is calculated point by point based on the moment of inertia data set of each section to obtain a stress gradient numerical sequence;

[0041] The thickness change rate is differentially calculated based on the stress gradient numerical sequence to obtain the thickness-stress change rate correlation matrix;

[0042] The thickness-stress change rate correlation matrix is ​​input into the interpolation algorithm for data smoothing to obtain a continuous stress distribution function;

[0043] Perform numerical integration calculation on the continuous stress distribution function to obtain cumulative stress load data;

[0044] The thickness parameters are reverse mapped and calculated according to the accumulated stress load data to obtain the thickness-force correspondence data.

[0045] Specifically, when calculating the cross-sectional geometric characteristics of the equal-width variable-thickness tapping parameters, it is necessary to calculate the cross-sectional inertia moment at each position along the axial direction of the different plate. The moment of inertia is a geometric characteristic parameter that reflects the bending resistance of the cross section. The calculation formula for the moment of inertia of a rectangular cross section is:

[0046]

[0047] in: Axial position The moment of inertia of the section at ; b is the width of the different plate, which remains constant; h(x) is the thickness at the axial position x; x is the position coordinate along the axial direction of the different plate.

[0048] Since the thickness of the heterogeneous plate changes continuously along the axial direction while the width remains unchanged, the moment of inertia of each section changes in a cubic relationship with the thickness. The calculation process traverses all discretized node positions and calculates the corresponding section moment of inertia based on the thickness value and fixed width at each position. The moment of inertia data sets of each section are arranged in order according to the axial position to form an ordered array. When the axial stress distribution is calculated point by point based on the moment of inertia data sets of each section, the calculation formula for the axial stress is:

[0049]

[0050] in: is the axial stress at the axial position x (MPa); is the axial force at the axial position x (N).

[0051] Since the axial force borne by the heterogeneous plate varies along the axial distribution, the stress value at each cross-sectional position is determined by the ratio of the axial force to the moment of inertia at that position. The point-by-point calculation process traverses all cross-sectional positions, and the corresponding axial force value is divided by the moment of inertia value. The stress gradient value sequence reflects the variation law of stress along the axial direction, and the stress gradient value is obtained by dividing the stress difference between adjacent sections by the axial spacing.

[0052] When the thickness change rate is differentially calculated based on the stress gradient numerical sequence, the thickness change rate represents the speed at which the thickness changes with the axial position. The ratio of the thickness difference to the position difference between adjacent nodes is calculated through the numerical differentiation algorithm. The differential differentiation calculation converts the discrete thickness data into a continuous change rate function. The thickness-stress change rate association matrix establishes the corresponding relationship between the thickness change rate and the stress gradient. The rows of the matrix correspond to different axial positions, and the columns correspond to the thickness change rate and stress gradient values.

[0053] When the thickness-stress change rate correlation matrix is ​​input into the interpolation algorithm for data smoothing, the interpolation algorithm eliminates the numerical fluctuations caused by discrete calculations and generates a continuous and smooth stress distribution function through spline interpolation or polynomial interpolation methods. The mathematical expression of the continuous stress distribution function describes the continuous change law of stress with axial position. The derivative of the function represents the stress change rate, and the second-order derivative represents the acceleration of stress change.

[0054] When numerically integrating a continuous stress distribution function, the integral operation calculates the cumulative value of the stress function over the entire axial range. The numerical integration employs either the trapezoidal integration method or the Simpson integration method, dividing the integral interval into several smaller intervals. The integral value within each smaller interval is calculated by multiplying the function value by the interval length. The accumulated stress load data represents the cumulative load distribution at each location on the plate. When reverse mapping the thickness parameters based on the accumulated stress load data, the reverse mapping establishes an inverse functional relationship from the accumulated load to the thickness parameter. Numerical solutions are used to determine the corresponding thickness value under given load conditions. The thickness-force correspondence data establishes a one-to-one correspondence between thickness and force, serving as the fundamental input for subsequent material formulation design.

[0055] In a specific embodiment, the process of executing step S103 may specifically include the following steps:

[0056] The weight distribution calculation of the multi-element formula system is performed to obtain the niobium, aluminum, vanadium, titanium, silicon and molybdenum element concentration matrix;

[0057] The weather resistance performance index is quantitatively evaluated based on the niobium, aluminum, vanadium, titanium, silicon and molybdenum element concentration matrix to obtain a weather resistance performance numerical sequence;

[0058] Based on the weather resistance performance numerical sequence, the thickness-stress correspondence data was analyzed and processed to obtain the composition-thickness-stress ternary relationship table;

[0059] Input the composition-thickness-force ternary relationship table into the optimization algorithm to adjust the formula ratio and obtain the optimized composition ratio data;

[0060] Perform spatial distribution calculation on the optimized component ratio data to obtain the element gradient distribution along the thickness direction;

[0061] The uniformity of the material structure is verified according to the element gradient distribution along the thickness direction to obtain the material composition distribution plan.

[0062] Specifically, when performing component weight distribution calculations on a multi-element formula system, a weight distribution mechanism for each element is established based on the content ranges of niobium 0.03-0.15%, aluminum 0.2-0.65%, vanadium 0.02-1.2%, titanium 0.3-0.9%, silicon 0.5-1%, and molybdenum 0.5-1.5%. The weight distribution calculation takes into account the contribution of each element to weather resistance, and converts the content of each element into a standardized weight coefficient through a weighted average algorithm. The weight coefficient calculation process converts the percentage value of the element content into a weight value between 0 and 1. The niobium, aluminum, vanadium, titanium, silicon, and molybdenum element concentration matrix is ​​a six-row and multi-column data matrix, where the rows represent six elements and the columns represent different formula schemes. Each element in the matrix represents the concentration value of a certain element in a specific formula. The concentration matrix generation process traverses all element content combinations and calculates the concentration distribution of each combination.

[0063] When quantitatively evaluating weather resistance performance indicators based on the niobium, aluminum, vanadium, titanium, silicon and molybdenum element concentration matrix, weather resistance performance indicators include multiple dimensions such as corrosion resistance, oxidation resistance, and UV resistance. The quantitative evaluation process converts qualitative weather resistance performance into quantitative numerical indicators. The evaluation algorithm uses a linear weighted summation method. The comprehensive evaluation function of weather resistance performance is:

[0064]

[0065] in: Score the overall weather resistance performance; , , , , , are the performance weight coefficients of niobium, aluminum, vanadium, titanium, silicon, and molybdenum elements respectively; , , , , , The percentages (%) of the elements niobium, aluminum, vanadium, titanium, silicon, and molybdenum are shown in the table below. The contribution of each element to weather resistance is calculated by multiplying its concentration by the corresponding performance coefficient. The performance coefficient reflects the influence of different elements on weather resistance. The weather resistance numerical sequence is arranged in the order of the formulations. Each value in the sequence represents the comprehensive weather resistance score of the corresponding formulation. A larger value indicates better weather resistance.

[0066] When performing correlation analysis on the thickness-force correspondence data based on the weather resistance numerical sequence, the correlation analysis algorithm calculates the correlation strength between weather resistance and thickness-force relationship. The analysis process uses the Pearson correlation coefficient algorithm. The calculation formula of the Pearson correlation coefficient is:

[0067]

[0068] in: is the Pearson correlation coefficient; , are the two variable values ​​of the i-th sample; , is the mean of the two variables; n is the total number of samples.

[0069] Calculate the degree of linear correlation between the two sets of data. The numerical range of the correlation coefficient is from -1 to 1. Positive values ​​indicate positive correlation, negative values ​​indicate negative correlation, and the absolute value indicates the strength of correlation. The calculation process of the correlation analysis calculates the correlation between the weather resistance value sequence and the thickness data and the stress data respectively to obtain the correlation between weather resistance and thickness, and the correlation between weather resistance and stress. The composition-thickness-stress ternary relationship table establishes a multivariate relationship between the three variables. The rows of the table correspond to different cross-sectional positions, and the columns correspond to component concentration, thickness value, and stress value. Each data unit in the table records the ternary relationship data of a specific position.

[0070] When the composition-thickness-force ternary relationship table is input into the optimization algorithm for formula ratio adjustment, the optimization algorithm uses a genetic algorithm to find the optimal formula combination. The initial population of the genetic algorithm consists of multiple formula schemes. Each individual represents a formula. The individual's genetic code corresponds to the content ratio of each element. The fitness function evaluates the comprehensive performance of the individual, including multiple objectives such as weather resistance, mechanical properties, and cost. The selection operation selects excellent individuals for reproduction based on the fitness value. The crossover operation recombines the gene fragments of two parent individuals to produce offspring. The mutation operation randomly changes the individual's gene value to increase population diversity. After multiple generations of evolution, the optimal formula combination is obtained. The optimized component ratio data contains the optimal content ratio of each element and the corresponding performance prediction value.

[0071] When performing spatial distribution calculation on the optimized component ratio data, the spatial distribution calculation determines the concentration distribution law of each element in the thickness direction of the plate. The calculation process takes into account the impact of thickness change on element distribution. Areas with larger thickness require higher element content to bear greater stress, and areas with smaller thickness require relatively lower element content to bear smaller stress. The distribution calculation uses a linear interpolation algorithm to establish a mapping relationship between element concentration and thickness based on the relationship between thickness and stress. The element gradient distribution along the thickness direction describes the law of change of each element concentration with thickness. The gradient distribution calculation is obtained by the ratio of the concentration difference to the thickness difference at adjacent thickness positions.

[0072] When the uniformity of the material structure is verified based on the element gradient distribution along the thickness direction, the uniformity verification algorithm checks the continuity and stability of the element distribution. The verification process calculates the variance and standard deviation of the element concentration. The variance value reflects the degree of discreteness of the element distribution, and the standard deviation value represents the fluctuation amplitude of the element concentration. The verification standard requires that the gradient of the element concentration change is within a reasonable range to avoid uneven structure caused by sudden concentration changes. The verification algorithm also checks the continuity of the element concentration at adjacent positions to ensure a smooth transition of concentration changes. The material composition distribution scheme integrates the final distribution patterns of all elements. The scheme includes the specific content values ​​and distribution curves of each element at different thickness positions.

[0073] In a specific embodiment, the process of executing step S104 may specifically include the following steps:

[0074] Calculate the rolling temperature range of the material composition distribution scheme to obtain segmented temperature control data;

[0075] The roll gap change is processed with gradient setting according to the segmented temperature control data to obtain the reduction amount distribution sequence;

[0076] Based on the reduction distribution sequence, the rolling speed parameters are synchronously adjusted to obtain the speed-reduction matching relationship;

[0077] The speed-reduction matching relationship is input into the process parameter optimization algorithm for numerical solution to obtain the optimal rolling process parameter combination;

[0078] Perform forming accuracy verification calculation on the optimal rolling process parameter combination to obtain thickness deviation control data;

[0079] The process parameters are fine-tuned and corrected according to the thickness deviation control data to obtain the design parameters of multi-element weather-resistant special boards.

[0080] Specifically, when calculating the rolling temperature range of the material composition distribution scheme, the optimal solution temperature and precipitation temperature range of each element are calculated according to the characteristics of the added trace elements such as niobium, aluminum, vanadium, titanium, silicon, molybdenum, etc. The calculation of the rolling temperature range needs to consider the phase change behavior and diffusion ability of each element at different temperatures. The calculation process adopts a weighted average algorithm to weight the optimal rolling temperature of each element according to its content ratio to obtain the comprehensive optimal rolling temperature. At the same time, according to the spatial distribution difference of the element content, the temperature requirements corresponding to different thickness positions are calculated. The thicker area requires a relatively higher rolling temperature due to the higher element content, and the thinner area requires a relatively lower rolling temperature due to the lower element content. The segmented temperature control data divides the rolling process of the heterogeneous plate into multiple temperature intervals. Each interval corresponds to a specific thickness range and temperature value. The temperature control data is arranged in a time series according to the rolling progress to form a control curve of temperature change over time.

[0081] When the roll gap change is gradient-set according to the segmented temperature control data, the roll gap determines the final thickness of the plate. The gradient setting refers to the continuous change of the roll gap along the rolling direction. The setting process calculates the roll gap value for each rolling position based on the target thickness distribution and temperature control data. The calculation algorithm uses geometric relationship derivation to convert the relationship between the target thickness and the rolling temperature into the set value of the roll gap. When the temperature is high, the material has better plasticity and requires a larger reduction. When the temperature is low, the material has poor plasticity and requires a smaller reduction. The reduction distribution sequence records the reduction value at each time point during the entire rolling process. The sequence data is arranged according to the rolling progress. The distribution of reduction needs to meet the continuity requirements of material deformation. The difference in reduction at adjacent time points cannot be too large to avoid material cracking.

[0082] When the rolling speed parameters are synchronously adjusted based on the reduction distribution sequence, there is a matching relationship between the rolling speed and the reduction. Too fast speed will lead to insufficient material deformation, and too slow speed will lead to low production efficiency. The synchronous adjustment process determines the corresponding rolling speed according to the size of the reduction. The adjustment algorithm adopts an inverse proportional function relationship. When the reduction is large, the rolling speed is relatively slow, and when the reduction is small, the rolling speed is relatively fast. Speed ​​adjustment also needs to consider the strain rate sensitivity of the material. Different element contents correspond to different optimal strain rates. The speed-reduction matching relationship establishes a functional relationship between the two parameters. This relationship is extracted from the experimental data through a data fitting algorithm. The mathematical expression of the matching relationship describes the quantitative correspondence between speed and reduction.

[0083] When the speed-reduction matching relationship is input into the process parameter optimization algorithm for numerical solution, the goal of the optimization algorithm is to find the optimal process parameter combination while meeting the product quality requirements. The numerical solution adopts the Lagrange multiplier method, which converts the constrained optimization problem into an unconstrained optimization problem. The solution process first constructs the objective function and constraints. The objective function takes product quality and production efficiency as the optimization goals. The constraints include equipment capacity limitations, material performance requirements, process stability requirements, etc. The Lagrange multiplier method integrates the constraints into the objective function by introducing Lagrange multipliers to form a Lagrangian function. The solution process calculates the partial derivative of the Lagrangian function and sets it to zero to obtain the necessary conditions for the optimal solution. The optimal process parameter combination is obtained by solving the equation group through a numerical iterative algorithm. The combination includes key parameters such as the optimal rolling temperature, the optimal reduction distribution, and the optimal rolling speed.

[0084] When performing forming accuracy verification calculations on the optimal rolling process parameter combination, the verification calculation uses the finite element analysis method to simulate the material deformation behavior during the rolling process. The calculation process inputs the optimal process parameters as boundary conditions into the finite element model. The model calculates the stress and strain distribution and the final geometric shape of each position of the heterogeneous plate. The forming accuracy is evaluated by calculating the deviation between the actual thickness and the target thickness. The deviation calculation uses a statistical analysis method to calculate statistical parameters such as the mean, standard deviation, and maximum deviation of the thickness deviation. The thickness deviation control data records the thickness deviation value and the statistical distribution of the deviation at each position. The control data also includes the spatial distribution law of the deviation and the trend of the deviation changing with the process parameters.

[0085] When fine-tuning and correcting the process parameters according to the thickness deviation control data, the fine-tuning correction adopts a feedback control algorithm to adjust the corresponding process parameters according to the size and direction of the thickness deviation. The correction algorithm adopts a proportional-integral-differential controller. The proportional term is corrected according to the current deviation size, the integral term is corrected according to the historical deviation accumulation, and the differential term is corrected according to the deviation change trend. The amplitude of the parameter correction is determined according to the sensitivity analysis of the deviation. The sensitivity analysis calculates the degree of influence of the process parameter change on the thickness deviation. The corrected process parameters need to be re-verified and recalculated to confirm the correction effect. The design parameters of the multi-element weather-resistant plate integrate the finalized process parameters, material composition distribution, geometric dimensions and other complete design information.

[0086] In a specific embodiment, the process of inputting the velocity-reduction matching relationship into the process parameter optimization algorithm for numerical solution processing may specifically include the following steps:

[0087] The constraint conditions of the speed-reduction matching relationship are constructed to obtain the process parameter boundary constraint matrix;

[0088] The objective function is processed with multiple variables according to the boundary restriction matrix of process parameters to obtain the rolling quality evaluation function;

[0089] Based on the rolling quality evaluation function, the Lagrange multiplier method is iteratively solved to obtain a set of candidate process parameter solutions.

[0090] The candidate solution set of process parameters is input into the convergence judgment algorithm to screen the optimal solution and obtain the optimal rolling process parameter combination.

[0091] Specifically, when constructing constraints for the speed-reduction matching relationship, the constraints include multiple dimensions such as equipment physical limitations, material performance limitations, and process stability limitations. The construction process first analyzes the hardware constraints such as the maximum pressure bearing capacity of the rolling equipment, the maximum rolling speed range, and the temperature control accuracy. Then, based on the material properties of multi-element weathering steel, the deformation resistance range, strain rate sensitivity, temperature sensitivity and other material constraints are determined. Finally, the geometric characteristics of different widths and thicknesses of different plates are combined to determine the process constraints such as thickness variation continuity, surface quality requirements, and dimensional accuracy requirements. The constraint construction uses inequality mathematical expressions to convert various constraints into numerical boundaries. The process parameter boundary constraint matrix is ​​a data matrix with multiple rows and two columns. The number of rows corresponds to the number of constraints, and the two columns correspond to the lower and upper boundary values ​​of each constraint. Each element in the matrix records the numerical range of a specific constraint. The boundary constraint matrix is ​​sorted according to the importance of the constraints, and the key constraints are placed at the front of the matrix.

[0092] When the objective function is established with multiple variables according to the process parameter boundary restriction matrix, the objective function is a mathematical expression for evaluating the comprehensive performance of the rolling process. The multivariable establishment process integrates multiple objectives such as rolling quality, production efficiency, and energy consumption cost into a single optimization objective. The establishment process adopts a weighted summation method and assigns weight coefficients according to the importance of each objective. The rolling quality objective is quantified by indicators such as thickness accuracy, surface quality, and mechanical properties. The production efficiency objective is quantified by indicators such as rolling speed, equipment utilization, and output. The energy consumption cost objective is quantified by indicators such as power consumption, equipment wear, and labor cost. The rolling quality evaluation function linearly combines multiple quantitative indicators according to weight coefficients. The independent variables of the function include process parameters such as rolling temperature, reduction, and rolling speed. The function value represents the comprehensive quality score under a given combination of process parameters. The mathematical form of the evaluation function is a multivariate nonlinear function, and the partial derivative of the function represents the degree of influence of each process parameter on the quality score.

[0093] When the Lagrange multiplier method is iteratively solved based on the rolling quality evaluation function, the Lagrange multiplier method converts the constrained optimization problem into an unconstrained optimization problem. The solution process constructs a Lagrangian function, which links the objective function and the constraints through Lagrange multipliers. The iterative solution adopts the gradient descent algorithm. The partial derivatives of the Lagrangian function with respect to all variables are calculated in each iteration. The direction and step size of the parameter adjustment are determined according to the sign and size of the partial derivatives. The process parameters and Lagrange multipliers are updated simultaneously during the iteration process. The update of the process parameters follows the negative direction of the objective function gradient. The update of the Lagrange multiplier is determined according to the degree of violation of the constraints. The convergence criteria of the iterative solution include multiple indicators such as the change amplitude of the objective function value, the change amplitude of the parameters, and the degree of satisfaction of the constraints. The iteration process ends when all convergence criteria are simultaneously met. The set of process parameter candidate solutions contains all parameter combinations that meet the convergence criteria during the iteration process. Each candidate solution in the set corresponds to a set of specific process parameter values ​​and the corresponding objective function value.

[0094] When the set of candidate solutions for process parameters is input into the convergence judgment algorithm for optimal solution screening, the convergence judgment algorithm evaluates the stability and reliability of the candidate solutions. The screening process first calculates the objective function value of each candidate solution, and then sorts them according to the size of the function value. The sorting result puts the candidate solution with the best objective function value in the front position. Then, the sorted candidate solutions are tested for stability. The stability test is achieved through the perturbation analysis method. A small parameter perturbation is applied near the candidate solution, and the change in the objective function value after the perturbation is calculated. The candidate solution with a smaller function value change has better stability. The convergence judgment also includes the test of the degree of constraint satisfaction. The candidate solution that strictly meets all constraints is given priority. The optimal solution screening adopts a multi-criteria decision-making method, which comprehensively considers multiple evaluation indicators such as objective function value, stability, and constraint satisfaction. The optimal rolling process parameter combination is the final result of the screening process. The combination contains the specific values ​​of key process parameters such as rolling temperature, reduction, and rolling speed.

[0095] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A multi-element weather-resistant special board design method, characterized in that: The method comprises: According to the axial force distribution law, the geometric structure of the different plates is designed into a trapezoidal cross section to obtain the constant width and variable thickness tapping parameters. The stress matching calculation of the constant width and variable thickness tapping parameters is performed through the mechanical analysis algorithm to obtain the thickness-stress correspondence data; The multi-element formula system is fused with the thickness-stress correspondence data for weather resistance to obtain a material composition distribution scheme, including: performing component weight distribution calculation processing on the multi-element formula system to obtain a niobium, aluminum, vanadium, titanium, silicon, and molybdenum element concentration matrix; performing quantitative evaluation processing on the weather resistance performance index based on the niobium, aluminum, vanadium, titanium, silicon, and molybdenum element concentration matrix to obtain a weather resistance performance numerical sequence; performing correlation analysis processing on the thickness-stress correspondence data based on the weather resistance performance numerical sequence to obtain a composition-thickness-stress ternary relationship table; inputting the composition-thickness-stress ternary relationship table into an optimization algorithm to adjust the formula ratio to obtain optimized composition ratio data; performing spatial distribution calculation processing on the optimized composition ratio data to obtain an element gradient distribution along the thickness direction; performing uniformity verification processing on the material structure based on the element gradient distribution along the thickness direction to obtain a material composition distribution scheme; The hot rolling forming optimization processing of the heterogeneous plate manufacturing process is carried out according to the material composition distribution scheme to obtain the design parameters of the multi-element weather-resistant heterogeneous plate, including: calculating the rolling temperature range of the material composition distribution scheme to obtain the segmented temperature control data; performing gradient setting processing on the roll gap change according to the segmented temperature control data to obtain the reduction distribution sequence; synchronously adjusting the rolling speed parameters based on the reduction distribution sequence to obtain the speed-reduction matching relationship; inputting the speed-reduction matching relationship into the process parameter optimization algorithm for numerical solution processing to obtain the optimal rolling process parameter combination; performing forming accuracy verification calculation processing on the optimal rolling process parameter combination to obtain the thickness deviation control data; fine-tuning and correcting the process parameters according to the thickness deviation control data to obtain the design parameters of the multi-element weather-resistant heterogeneous plate.

2. The multi-element weather-resistant plate design method according to claim 1, characterized in that: The trapezoidal cross-section design of the different plate geometric structure is performed according to the axial force distribution law to obtain the constant width and variable thickness tapping parameters, including: Perform stress analysis on the working conditions of different plates to obtain axial force distribution curve data; According to the axial force distribution curve data, the plate geometric dimensions are subjected to equal width constraint design processing to obtain the width parallelization parameters; Based on the width parallelization parameter, the thickness gradient is optimized and calculated to obtain the thickness trapezoidal distribution data; The thickness trapezoidal distribution data is input into the geometric modeling algorithm to generate cross-section parameters and obtain the constant width and variable thickness tapping parameters.

3. The multi-element weather-resistant plate design method according to claim 2, characterized in that: The step of inputting the thickness trapezoidal distribution data into a geometric modeling algorithm to generate cross-sectional parameters and obtain the constant width variable thickness tapping parameters includes: Perform numerical discretization on the thickness trapezoidal distribution data to obtain the thickness node coordinate set; The geometric constraint calculation of the tapping angle is performed according to the thickness node coordinate set to obtain the tapping degree range; Based on the numerical range of the taper degree, the cross-section profile is continuously interpolated to obtain a smooth cross-section curve; The smooth cross-section curve is input into the parametric modeling program for geometric reconstruction to obtain the constant width and variable thickness tapping parameters.

4. The multi-element weather-resistant plate design method according to claim 1, characterized in that: The stress matching calculation processing of the constant width variable thickness tapping parameters is performed by the mechanical analysis algorithm to obtain thickness-stress correspondence data, including: The cross-sectional geometric characteristics of the constant width and variable thickness tapping parameters are calculated and processed to obtain the moment of inertia data set of each section; The axial stress distribution is calculated point by point based on the moment of inertia data set of each section to obtain a stress gradient numerical sequence; The thickness change rate is differentially calculated based on the stress gradient numerical sequence to obtain the thickness-stress change rate correlation matrix; The thickness-stress change rate correlation matrix is ​​input into the interpolation algorithm for data smoothing to obtain a continuous stress distribution function; Perform numerical integration calculation on the continuous stress distribution function to obtain cumulative stress load data; The thickness parameters are reverse mapped and calculated according to the accumulated stress load data to obtain the thickness-force correspondence data.

5. The multi-element weather-resistant plate design method according to claim 1, characterized in that: The speed-reduction matching relationship is input into the process parameter optimization algorithm for numerical solution processing to obtain the optimal rolling process parameter combination, including: The constraint conditions of the speed-reduction matching relationship are constructed to obtain the process parameter boundary constraint matrix; The objective function is processed with multiple variables according to the boundary restriction matrix of process parameters to obtain the rolling quality evaluation function; Based on the rolling quality evaluation function, the Lagrange multiplier method is iteratively solved to obtain a set of candidate process parameter solutions. The candidate solution set of process parameters is input into the convergence judgment algorithm to screen the optimal solution and obtain the optimal rolling process parameter combination.

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