Optimization design method and system for oversized transmission drum body structure

Abstract

The invention discloses an oversized transmission drum body structure optimization design method and system, and the method comprises the steps: firstly building a drum body parameterized model in a finite element environment, building design variables of all structural parameters of a drum body, carrying out the grid division, adding constraints, and carrying out the static simulation, thereby obtaining the deformation of the drum body and all stress values of a dangerous section; creating and generating output variables according to the parameters; secondly, obtaining corresponding experimental data matrix data between multiple groups of structural design variables and output variables by utilizing an experimental design module in ANSYS; thirdly, importing experimental matrix data into Matlab, fitting to obtain a function relational expression between a structural design variable and an output variable, then creating a variable, a constraint function and an objective function of an optimization design model, creating an optimization program based on a heritage algorithm, and realizing the volume optimization of the cylinder on the premise of meeting various constraint conditions; therefore, the optimization design of the cylinder structure is completed; according to the scheme, by means of the method, the precision of optimization design of the oversized transmission drum body structure is further improved.

Description

Technical Field

[0001] This invention relates to the field of industrial manufacturing technology, specifically to a system and method for optimizing the design of an ultra-large transmission roller structure. Background Technology

[0002] Belt conveyors have become one of the main pieces of equipment for transporting raw coal in underground coal mines due to their advantages such as large capacity, long conveying distance, high efficiency, and strong adaptability. The drive drum (as shown below) is one of the most important components of a belt conveyor. Figure 1 As shown, on the one hand, its structural form and working performance become key factors in determining whether the overall performance of the machine is stable and good; on the other hand, the failure of the transmission roller will have serious consequences for personal safety and the entire system, causing huge economic losses to the enterprise.

[0003] In recent years, with the continuous increase in coal mine transport volume and distance, and the limitation of working conditions such as the inability to add central drives due to space constraints in underground coal mine roadways, the size of drive drums for belt conveyors has been continuously increasing. Belt conveyor drums are classified according to the load they bear into light-duty (resultant force ≤ 500kN), medium-duty (500kN < resultant force ≤ 1500kN), heavy-duty (1500kN < resultant force ≤ 3100kN), and extra-large (resultant force > 3100kN). According to statistical analysis, the weight of extra-large drums exceeds 10 tons. Therefore, research on lightweighting extra-large drums is becoming increasingly urgent.

[0004] The drive drum mainly consists of three parts: the drum body, the drive drum shaft, and the drum bearing housing (as follows). Figure 1 Statistical analysis of previous ultra-large drum structure parameters revealed that the weight of the drum body component accounts for approximately 50% of the total drum weight. This demonstrates that optimized drum body design is crucial for lightweighting ultra-large drums. Therefore, the invention of an optimized design method for ultra-large drum bodies has significant practical implications.

[0005] The current design of the cylinder structure for ultra-large drums has the following shortcomings: 1. The design of the drum body mainly adopts the analogy method and empirical formulas for strength and stiffness. At present, there are no relevant standards or specifications for the design of the drum body structure, resulting in very low design accuracy. This leads to the need to adopt a large safety margin to ensure reliable strength, especially for ultra-large drums, where the problem of bulky structure becomes prominent.

[0006] 2. When using finite element simulation to analyze the strength and stiffness of the cylinder, the radial and tangential load values ​​of the transmission drum cylinder gradually decrease from the belt entry point S1 to the departure point S2. The uniform pressure and uniform tangential force loading method is obviously not in line with the actual working conditions.

[0007] 3. The following problems exist in the current structural optimization design methods for cylinders: (1) The finite element simulation software was used for optimization design. The maximum static stress obtained from the finite element simulation of the cylinder was used to create a static strength constraint function. However, since the cylinder is a body of revolution, the static strength constraint only reduces the accuracy of the optimization design calculation. Therefore, the fatigue strength of the cylinder needs to be calculated as the constraint function. However, the fatigue strength of the cylinder needs to be obtained through complex calculations. The optimization design module of the finite element simulation software cannot realize the constraint equation of the complex function.

[0008] (2) Use programming software or calculation software (such as Matlab) to create an optimization mathematical model and complete the structural optimization. However, the above software can only obtain the dangerous stress of the cylinder through empirical formulas. Compared with the stress and deformation values ​​obtained by finite element simulation, the accuracy is greatly reduced, which leads to a significant reduction in the accuracy of the cylinder strength constraint function. It can be seen that the calculation accuracy of this optimization method is limited.

[0009] Therefore, since the optimized design of the drive roller is crucial, how to solve the technical problems existing in the above-mentioned optimized design method of the cylinder structure is a problem that needs to be solved in this field. Summary of the Invention

[0010] In view of the above-mentioned technical problems in existing methods for optimizing the design of drive rollers, the purpose of this invention is to provide a method for optimizing the structure of an ultra-large drive roller, which can effectively solve the problems existing in existing methods for optimizing the design of drive rollers. On this basis, a corresponding system for optimizing the structure of an ultra-large drive roller is also provided.

[0011] To achieve the above objectives, the present invention provides a method for optimizing the structure of an ultra-large transmission drum, the method comprising the following steps: S1: Determine the initial structural parameters of the cylinder based on the configuration requirements of the belt conveyor and the empirical formula for cylinder structure design, and create a parametric model of the cylinder in the finite element environment, and create design variables for each structural parameter of the cylinder. S2: After the cylindrical body parameter model is created in S1, the boundary conditions of the super-large cylindrical body are loaded and static simulation is performed to obtain the output variables of the deformation of the cylindrical body and the stress values ​​of various critical sections. S3: The experimental matrix of the design variables in S1 and the output variables in S2 is obtained through ANSYS simulation and experimental design; S4: Import the experimental matrix data from S3 into Matlab, fit the functional relationship between the structural design variables and the output variables, then create the variables, constraint functions, and objective functions of the optimization design model, create an optimization program based on the legacy algorithm, and achieve the optimal volume of the cylinder under the premise of satisfying various constraints, thereby completing the optimization design of the cylinder structure.

[0012] Furthermore, the initial structural parameters in S1 include: (1) Determine the diameter of the drive drum based on the belt strength used in the belt conveyor, and determine the length of the drive drum based on the belt width of the belt conveyor; (2) Determine the expansion sleeve model based on the transmitted torque, thereby determining the cylinder hub bore diameter; (3) Determine the outer diameter of the cylinder hub based on the empirical formula for the structural strength of the installed expansion sleeve hub; (4) Determine the wheel hub width based on the empirical formula that the wheel hub width is ≥ 1.5-2.0 mm of the expansion sleeve width; (5) Determine the thickness of the tube skin according to the empirical formula of Japanese Munetaka.

[0013] Further, S2 includes: S21: After the cylindrical parametric model is created in S1, it is meshed to facilitate numerical calculation and analysis; S22: After meshing the cylindrical parametric model in S21, apply boundary conditions to it; S23: After adding the boundary conditions of the cylinder in S22, perform static simulation to obtain the initial cylinder volume, deformation displacement cloud map, normal stress at the critical section, and shear stress cloud map. The maximum normal stress, minimum normal stress, maximum shear stress, minimum shear stress, and maximum displacement at the critical section are parameterized and become the output variables for subsequent optimization design.

[0014] Furthermore, the boundary condition loading method in S22 includes: (1) The wrap angle of the cylinder is 200°. The entire arc segment is divided into 25° segments. The cylinder is divided into 8 segments along the circumference. The radial load is applied by uniformly distributing the pressure value at the middle position of each segment to the arc segment. The tangential load is applied by multiplying the pressure value of the arc segment by the friction coefficient. The moving arc segment is added with both normal and tangential loads, while the stationary arc segment is only added with normal loads. (2) Add remote displacement constraint at the hub hole where the expansion sleeve is installed on the cylinder.

[0015] Furthermore, in S3, the structural design variables and output variables are created using Latin hypercube sampling and a custom method of generating multiple sets of samples each time. After simulation calculation of the cylindrical parameterized model, multiple sets of "input variables and their corresponding output parameters" arrays are finally obtained, forming an experimental matrix diagram between design variables and output variables.

[0016] Furthermore, the design variables in S4 are the structural parameters of the cylinder, and the hub radius H40, cylinder radius, cylinder thickness, hub height, and spoke radius are finally determined as structural design variables.

[0017] Furthermore, in S4, the objective function is the volume of the cylinder. The cylinder structure is appropriately simplified and divided into three parts: the cylinder skin, the spokes, and the hub. The final objective function formula is obtained through calculation.

[0018] Furthermore, the constraint functions for cylinder optimization in S4 include strength conditions, stiffness conditions, and boundary conditions for structural parameters.

[0019] Furthermore, in S4, the nonlinear least squares method is used for fitting, and the function form is defined as polynomial form.

[0020] To achieve the above objectives, the present invention provides a structural optimization design system for an ultra-large transmission roller, characterized in that it includes: The model creation module is used to create a parametric model of the belt conveyor cylinder in a finite element environment based on the initial structural parameters of the cylinder, and to finally determine and create design variables. The boundary condition loading and static simulation module interacts with the model creation module. It is used to mesh the super-large cylindrical model created by the model creation module, add boundary conditions, and complete static simulation. It also reads out the maximum and minimum shear stress, maximum and minimum normal stress values ​​at the critical section and the maximum deformation of the cylindrical body to form output variables. The cylindrical body experimental design module interacts with the model creation module and the boundary condition loading and static simulation module. It is used to obtain the experimental matrix of design variables and output variables through ANSYS simulation and experimental design. This experimental matrix will be used to fit the constraint function for the subsequent optimization design of the cylindrical body in Matlab. The cylinder optimization design module interacts with the cylinder experimental design module. It is used to import the experimental matrix data in the cylinder experimental design module into Matlab, fit the functional relationship between the structural design variables and the output variables, and then create the variables, constraint functions, and objective functions of the optimization design model. Based on the inheritance algorithm, an optimization program is created to achieve the optimal volume of the cylinder under the premise of satisfying various constraints, thereby completing the cylinder structure optimization design.

[0021] The present invention provides a method and system for optimizing the design of ultra-large transmission drum cylinder structure. First, the experimental matrix of design variables and output variables is obtained through ANSYS simulation and experimental design. Based on this data set, the functional relationship between the two is obtained by fitting in Matlab, thereby creating a strength constraint function. This function replaces the Matlab optimization constraint function based on the stress empirical formula, which greatly improves the design accuracy.

[0022] Secondly, by utilizing the powerful mathematical computation capabilities of Matlab, subsequent function fitting, genetic algorithm optimization model creation and solution are completed, improving the efficiency and accuracy of optimization design, and realizing the optimal design of the cylinder structure, which will greatly reduce the structural weight, especially for ultra-large rollers.

[0023] Meanwhile, the finite element simulation adopts a more accurate loading method based on actual working conditions, which improves the simulation accuracy.

[0024] In addition, it avoids using only analogy, empirical formulas, and large safety margins to check the strength and stiffness of the cylinder. Furthermore, it calculates the fatigue strength of the cylinder based on stress data obtained from finite element simulation analysis, replacing the previous method of only checking static strength. This approach is more in line with actual working conditions and improves design accuracy. Attached Figure Description

[0025] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0026] Figure 1 Here is a structural diagram of an existing ultra-large drive roller; Figure 2 This is a schematic diagram of the optimization design method for the structure of this ultra-large transmission drum. Figure 3 This is a schematic diagram of the design variables for the transmission drum structure in this ultra-large transmission drum structure optimization design method. Figure 4 This is a schematic diagram of the finite element parametric model of the cylinder in the optimization design method of this ultra-large transmission drum cylinder structure; Figure 5 This is a schematic diagram of the radial load distribution of the drive drum in the optimized design method of the ultra-large drive drum structure. Figure 6 This is a schematic diagram of the boundary condition loading of the cylinder in the optimization design method of this ultra-large transmission drum cylinder structure; Figure 7 This is a schematic diagram of the cylinder volume in the optimized design method of this ultra-large transmission drum cylinder structure; Figure 8 The displacement cloud diagram of the cylinder in this optimization design method for the ultra-large transmission drum cylinder structure; Figure 9 This is a cloud diagram of the shear stress at the critical point of the cylinder in the optimized design method of this ultra-large transmission drum cylinder structure; Figure 10 This is a cloud diagram of the normal stress at the critical point of the cylinder in the optimized design method of this ultra-large transmission drum cylinder structure; Figure 11 This is a schematic diagram of the experimental design parameter settings in the structural optimization design method of this ultra-large transmission drum. Figure 12This is a schematic diagram of the experimental matrix between design variables and output variables in the optimization design method for the ultra-large transmission drum structure. Figure 13 A flowchart illustrating the parameter setting procedure for the genetic algorithm in the optimized design method for the ultra-large transmission drum body structure. Figure 14 This is a schematic diagram of the parameter values ​​obtained by MATLAB optimization in the structural optimization design method of this ultra-large transmission drum. Figure 15 This is a schematic diagram of the optimized drum body volume in this ultra-large transmission drum body structure optimization design method. Figure 16 This is a cloud diagram of the optimized cylinder deformation displacement in the optimized design method of this ultra-large transmission drum cylinder structure. Figure 17 This is a cloud diagram of the shear stress at the critical section of the cylinder after optimization in the structural optimization design method of this ultra-large transmission drum. Figure 18 This is the optimized normal stress cloud diagram of the dangerous section of the cylinder in the optimized design method of this ultra-large transmission drum cylinder structure. Detailed Implementation

[0027] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below with reference to specific illustrations.

[0028] To address the aforementioned technical problems with existing methods for optimizing the design of drive rollers, this invention provides a method for optimizing the structure of an ultra-large drive roller, which effectively solves the problems existing in current methods. (See attached document.) Figure 2 The method for optimizing the structure of the ultra-large transmission drum provided by this invention includes the following steps: S1: Determining the initial structural parameters of the ultra-large drum body and creating a parametric model, constructing structural variables.

[0029] First, the initial structural parameters of the cylinder are determined based on the configuration requirements of the belt conveyor and empirical formulas for cylinder structure design. Specifically, the structural parameters are determined using the following empirical formulas for cylinder structure design: (1) Determine the diameter D of the drive drum based on the belt strength of the belt conveyor (D=2240mm for the selected drum calculation case), and determine the length L of the drive drum based on the belt width of the belt conveyor (L=2560mm for the selected drum calculation case).

[0030] (2) Determine the expansion sleeve model based on the transmitted torque, and thus determine the cylinder hub bore diameter D1 (in the selected cylinder calculation case, D1=910mm). (3) Determine the outer diameter D2 of the cylinder hub according to the empirical formula for the structural strength of the installed expansion sleeve hub.

[0031] (4) Determine LG based on the empirical formula LG ≥ 1.5-2.0 expansion sleeve width.

[0032] (5) Determine the thickness of the tube skin V64 according to the empirical formula of Japanese Munetaka.

[0033] After determining the initial structural parameters of the cylinder based on the above principles, a parametric model of the cylinder was created in the finite element environment. According to the design criteria mentioned above, the hub radius H40, cylinder radius H81, cylinder thickness V64, hub height V62, and spoke radius H72 were determined as structural design variables. The final determined design variables and the created parametric model are as follows: Figure 3 , Figure 4 As shown (to reduce the simulation time for optimization design, symmetric constraints are used to create only a semi-cylinder structure).

[0034] S2: Boundary condition loading and static simulation of the ultra-large cylinder to obtain the deformation of the cylinder and various stress values ​​of the critical section.

[0035] S21: After the cylindrical parametric model is created in S1, it is meshed to facilitate numerical calculation and analysis.

[0036] As an example, the cylinder can be preferably divided into three parts: two side hubs and a middle cylinder. The middle cylinder is generated into regular hexahedral elements using rotational sweeping, while the two side hubs, which have complex structures, are automatically meshed into tetrahedral elements. This can ensure the solution accuracy while maximizing the solution accuracy.

[0037] S22: After meshing the cylindrical parametric model in S21, apply boundary conditions to it.

[0038] The boundary conditions here include, but are not limited to, the loads and constraints on the cylinder. The way the boundary conditions are applied determines the accuracy of the simulation results.

[0039] The radial load on the roller surface is distributed circumferentially as follows: Figure 5 As shown, the tangential load gradually decreases from the entry point S1 to the departure point S2, and the trend of tangential load variation is the same. Therefore, see... Figure 6 The present invention preferably employs a load loading method that more accurately simulates actual working conditions: The cylinder has a wrap angle of 200°. The entire arc is divided into segments of 25° each. The cylinder is divided into 8 segments along the circumference. The radial load is applied by uniformly distributing the pressure value at the middle position of each segment to that arc. The tangential load is applied by multiplying the pressure value of that arc by the friction coefficient. Normal and tangential loads are added to the moving arc segment, while only the normal load is added to the stationary arc segment.

[0040] The pressure exerted by the conveyor belt on any point of the sliding arc of the cylinder is: Within the stationary arc, the pressure exerted by the conveyor belt on the surface of the roller is: The frictional force per unit area between the conveyor belt and the cylinder is: In the formula, This refers to the pressure area of ​​the roller; For bandwidth; The diameter of the drum; The tension of the conveyor belt at point B; The tension of the conveyor belt at point A; The coefficient of friction between the conveyor belt and the cylinder surface; This is the normal reaction force acting on the stationary arc.

[0041] (2) Add remote displacement constraint at the hub hole where the expansion sleeve is installed on the cylinder.

[0042] This solution employs the aforementioned more accurate loading method based on actual working conditions during finite element simulation, thereby improving simulation accuracy.

[0043] S23: After adding the boundary conditions for the cylinder in S22, perform a static simulation to obtain the following results: Figure 7-10 The initial volume diagram, deformation displacement cloud diagram, and normal stress and shear stress cloud diagram at the critical section of the cylinder.

[0044] S24: Based on the stress diagram in S, the maximum normal stress P23, minimum normal stress P22, maximum shear stress P21, minimum shear stress P20, and maximum displacement at the critical section are parameterized and become the output variables for subsequent optimization design, which are used to create the fatigue constraint function in subsequent optimization design.

[0045] Specifically, after the finite element method is completed, select the stress-critical section of the cylinder (the circumferential weld of the cylinder), and insert the normal stress and shear stress in the solution menu to obtain the results. Figure 17 , Figure 18 The stress cloud diagram of the circumferential weld shown can be used to read the maximum normal stress P23, minimum normal stress P22, maximum shear stress P21, and minimum shear stress P20. The maximum displacement can be obtained by inserting the total deformation of the cylinder in the solve menu.

[0046] Under the Solve menu, select a result object you have added (such as stress or total deformation T). In the detailed information panel that appears, find the result quantity that needs to be parameterized, check the checkbox next to the result name, and the letter P will appear in the box, indicating that the result has been successfully set as an output parameter.

[0047] S3: Cylindrical Experimental Design This step specifically involves obtaining the experimental matrix of design variables and output variables through ANSYS simulation and experimental design. This experimental matrix will be used to design the fitting constraint function for the subsequent optimization of the cylinder in Matlab.

[0048] Specifically, the design variables here are the structural variables obtained in the experimental design in S1, namely the hub radius H40, cylinder radius H81, cylinder thickness V64, hub height V62, and spoke radius H72. The output variables are the maximum normal stress P23, minimum normal stress P22, maximum shear stress P21, minimum shear stress P20, and maximum equivalent stress P24 at the critical section obtained in S2.

[0049] This step of the project uses the structural design variables of the cylinder—hub radius H40, cylinder radius H81, cylinder thickness V64, hub height V62, and spoke radius H72—as input parameters, and the maximum normal stress P23, minimum normal stress P22, maximum shear stress P21, minimum shear stress P20, and maximum equivalent stress P24 at the critical section as output parameters. Then, the experimental design is created using Latin hypercube sampling and a custom method of generating multiple samples each time (as follows). Figure 11 As shown), after simulation calculations on the parameterized model of the cylinder, multiple sets of "input variables and their corresponding output parameters" arrays are finally obtained, forming an experimental matrix diagram between design variables and output variables (as shown below). Figure 12 (As shown).

[0050] This scheme preferentially adopts Latin hypercube sampling because it is an efficient sampling method that strives to explore the entire design space efficiently under limited computational costs. This method ensures that sample points are uniformly distributed across each dimension (each input parameter), avoiding oversampling of certain parameter values ​​due to the absence of clustering. Compared to pure random sampling, Latin hypercube sampling can cover the design space more stably and uniformly with fewer sample points; it can also effectively capture the complex, nonlinear response relationship between input and output.

[0051] Furthermore, it should be noted that this solution does not limit the number of sample groups generated each time. For example, it can be 20 groups, 30 groups, 40 groups, etc., and the specific number can be determined according to the actual situation.

[0052] This scheme obtains the experimental matrix of design variables and output variables through ANSYS simulation and experimental design. Based on this data set, the functional relationship between the two is obtained by fitting in Matlab, thereby creating a strength constraint function. This function replaces the Matlab optimization constraint function based on the stress empirical formula, which greatly improves the design accuracy.

[0053] S4: Cylinder Optimization Design Based on Genetic Algorithm By creating a parametric model of the cylinder in the finite element software, completing static simulation, and obtaining the experimental matrix between variables and stress, the optimization design of the cylinder will be further completed.

[0054] This optimization design employs a genetic algorithm, which is both intelligent and computationally efficient, and the optimization model and optimization calculations are completed using Matlab software.

[0055] S41: Creating an Optimized Mathematical Model This step specifically imports the experimental matrix data output from S3 into Matlab, fits the functional relationship between the structural design variables and the output variables, then creates the variables, constraint functions, and objective functions of the optimization design model, creates an optimization program based on the legacy algorithm, and achieves the optimal volume of the cylinder under the premise of satisfying various constraints, thereby completing the optimization design of the cylinder structure.

[0056] (1) Design variables The optimal design of the drum body should aim to minimize the drum's mass (i.e., minimize its volume) while meeting the requirements for the strength and rigidity of the drive drum. Therefore, the design variables for the optimal design are the structural parameters of the drum body, and H40, H81, V64, V62, and H72 are ultimately determined as the structural design variables.

[0057] (2) Objective function The objective function is the volume V of the cylinder. The structure of the cylinder is appropriately simplified and divided into three parts: the cylinder skin, the spokes, and the hub. The objective function formula (1) is obtained after calculation.

[0058] (1) (3) Constraint functions The constraint functions for cylinder optimization include strength conditions, stiffness conditions, and boundary conditions for structural parameters.

[0059] Stiffness constraints: Displacement contour plots obtained from the initial static simulation of the cylinder (see...) Figure 8 As can be seen, the deformation of the cylinder is only 0.355mm. According to the stiffness condition, the deformation of the cylinder is less than the hub center distance / 500=4.2mm. The deformation is much smaller than the allowable value. Therefore, in order to reduce the amount of calculation, the stiffness condition is not used as an optimization constraint. After finding the optimal structural parameters, it is sufficient to verify whether the stiffness condition is met through simulation analysis.

[0060] Fatigue strength constraints: Since the cylinder is a rotating body during operation, its fatigue strength must be guaranteed in addition to its static strength. For fatigue strength calculation of the cylinder, the normal and tangential stress cycle characteristics of the critical section can be used, and the fatigue strength can be checked using biaxial composite stress. The specific calculation method is as follows: First, based on the static simulation results, the maximum normal stress corresponding to the critical point of the cylinder's strength is obtained. and minimum normal stress Maximum tangential stress and minimum tangential stress The fatigue strength safety factor of the cylinder should satisfy formula (2): (2) In equation (2), the allowable fatigue stress , Basic values ​​of allowable tensile and compressive fatigue stresses for welded components Stress cycle characteristic value Substituting the above parameters into equation (2), we obtain the constraint function (3) regarding the fatigue strength of the cylinder: (3) Boundary condition constraints (4) and (5): (4) (5) This approach avoids relying solely on analogy, empirical formulas, and large safety margins for strength and stiffness verification of the cylinder. Furthermore, it calculates the fatigue strength of the cylinder based on stress data obtained from finite element simulation analysis, replacing the previous method of only verifying static strength. This approach better reflects actual working conditions and improves design accuracy.

[0061] S42: Matlab Optimization Simulation (1) Fit the functional relationship between the above four stress output variables and input variables. In the above formula , , , By fitting data with Matlab, the data matrix values ​​between the design variables and stress variables obtained through the ANSYS experimental design can be read into Matlab, and the functional relationship between each stress value and the design variable can be obtained through data fitting.

[0062] There are many methods for fitting functions. For cases with too many parameters, multiple linear regression is generally used for fitting, but this method is not very accurate. This project uses the least squares method to minimize nonlinearity for fitting, and the function form is defined as polynomial. The fitted function expression is shown in equation (6) below: (6) (2) Setting of genetic algorithm parameters Set the genetic algorithm parameters as follows: population size 1000, number of iterations 1000, crossover probability 0.8, mutation probability 0.1. The Matlab program settings are as follows: Figure 13 As shown.

[0063] (3) Create and run the Matlab optimization program. After developing and running the Matlab optimization program, provide the optimal solution that satisfies the constraints, as well as the optimized volumetric objective function value and fatigue constraint function value (as follows). Figure 14 As shown in the figure, the cylinder optimization is completed.

[0064] Using the co-simulation optimization method of this super-large cylinder, the initial structural parameters of the cylinder in Table 1 below (the determination of these initial parameters is detailed in S1) are optimized. After optimization simulation by MATLAB, the optimized structural parameters of the cylinder are shown in Table 1 below.

[0065] Table 1 Comparison of parameters before and after cylinder optimization

[0066] The optimized structural design variables were re-imported into the ANSYS cylindrical parametric model, and the simulation analysis was run again. The resulting drum volume is shown in Figure 15 below, and the displacement contour plot at the critical section of the optimized cylinder is shown below. Figure 16 As shown, the stress cloud diagram is as follows: Figure 17-18 As shown. Based on the stress values ​​of the critical section obtained from the above simulation, the fatigue strength safety factor is calculated to be 0.994 by substituting them into Formula 3.

[0067] The final parameters of the cylinder before optimization, the parameters after MATLAB optimization, and the parameters obtained from the ANSYS simulation of the new structure are shown in Table 1. A comparative analysis of the three sets of parameters in Table 1 shows that: the cylinder volume obtained by MATLAB optimization has an error of 1.9% compared to the value obtained by ANSYS simulation; the fatigue strength value obtained by MATLAB optimization has an error of 5.3% compared to the value obtained by ANSYS simulation; the cylinder volume after optimization is reduced by 17.2% compared to before optimization, and both the fatigue strength and cylinder deformation meet the design requirements. It is evident that, on the one hand, for the same cylinder structural parameters, the errors between the output variable values ​​obtained using the MATLAB fitting function and the values ​​obtained by ANSYS simulation are all within 10%, indicating high accuracy; on the other hand, this joint simulation optimization method effectively completed the optimization task of the ultra-large cylinder, achieving a 17.2% weight reduction.

[0068] Therefore, this invention: (1) uses finite element simulation instead of analogy method and stress empirical formula for cylinder strength and stiffness design, uses biaxial composite stress method to check cylinder fatigue strength instead of static strength check based on the stress values ​​of each critical section obtained by finite element, and uses a piecewise loading method that gradually decreases from entry point S1 to departure point S2 to replace uniform load loading method during finite element simulation, all of which improve design accuracy; (2) uses ANSYS and Matlab joint simulation method, which utilizes the convenience and accuracy of ANSYS software in structural strength and stiffness calculation, and also leverages the powerful functions of Matlab software in using intelligent optimization algorithm (genetic algorithm is used in this invention) and handling complex constraint models, further improving the accuracy and efficiency of the optimization design of the ultra-large transmission drum cylinder structure; (3) solves the problem of the bulky structure of the ultra-large transmission drum.

[0069] The optimization design method for the ultra-large drive roller structure presented in this example can be used to construct a corresponding software program, forming a corresponding optimization design system for the ultra-large drive roller structure. When running, this software program will execute the aforementioned optimization design method for the ultra-large drive roller structure and store it in a corresponding storage medium for the processor to retrieve and execute.

[0070] The resulting ultra-large transmission drum cylinder structure optimization design system mainly includes the following modules in terms of functionality: model creation module, boundary condition loading and static simulation module, cylinder experimental design module, and cylinder optimization design module.

[0071] The model creation module in this system is used to create a parametric model of the belt conveyor cylinder in a finite element environment based on the initial structural parameters of the cylinder, and finally determine and create the design variables.

[0072] The model creation module is configured to perform the steps of determining the initial structural parameters of the super-large drum body and creating the parameterized model to achieve the corresponding functions.

[0073] The boundary condition loading and static simulation module in this system interacts with the model creation module. It is used to mesh the ultra-large cylindrical model created by the model creation module, add boundary conditions, and complete static simulation. It also reads out the maximum and minimum shear stress, maximum and minimum normal stress values ​​at the critical section, and the maximum deformation of the cylindrical body to form output variables.

[0074] The boundary condition loading and static simulation module is configured to perform the steps of the above-mentioned ultra-large cylinder boundary condition loading and static simulation to achieve the corresponding functions.

[0075] The cylinder experimental design module in this system interacts with the model creation module and the boundary condition loading and static simulation module. It is used to obtain the experimental matrix of design variables and output variables through ANSYS simulation and experimental design. This experimental matrix will be used to fit the constraint function for the subsequent optimization design of the cylinder in Matlab.

[0076] The cylinder experiment design module is configured to execute the steps of the above-mentioned cylinder experiment design to achieve the corresponding functions.

[0077] The cylinder optimization design module and the cylinder experimental design module in this system interact with each other. The latter is used to import the experimental matrix data in the cylinder experimental design module into Matlab, fit the functional relationship between the structural design variables and the output variables, and then create the variables, constraint functions and objective functions of the optimization design model. Based on the legacy algorithm, an optimization program is created to achieve the optimal volume of the cylinder under the premise of satisfying various constraints, thereby completing the cylinder structure optimization design.

[0078] The cylinder optimization design module is configured to perform the above-mentioned cylinder optimization design steps to achieve the corresponding functions.

[0079] The method, specific system unit, or part thereof of the present invention described above is a pure software architecture. It can be deployed via program code on physical media, such as hard disks, optical discs, or any electronic device (such as smartphones or computer-readable storage media). When a machine loads and executes the program code (e.g., a smartphone loads and executes it), the machine becomes a device for implementing the present invention. The method and device of the present invention can also be transmitted in program code form via transmission media, such as cables, optical fibers, or any other transmission method. When the program code is received, loaded, and executed by a machine (e.g., a smartphone), the machine becomes a device for implementing the present invention.

[0080] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing the design of an ultra-large transmission drum structure, characterized in that... The optimized design method for the ultra-large transmission drum structure includes the following steps: S1: Determine the initial structural parameters of the cylinder based on the configuration requirements of the belt conveyor and the empirical formula for cylinder structure design, and create a parametric model of the cylinder in the finite element environment, and create design variables for each structural parameter of the cylinder. S2: After the cylindrical body parameter model is created in S1, the boundary conditions of the super-large cylindrical body are loaded and static simulation is performed to obtain the output variables of the deformation of the cylindrical body and the stress values ​​of various critical sections. S3: The experimental matrix of the design variables in S1 and the output variables in S2 is obtained through ANSYS simulation and experimental design; S4: Import the experimental matrix data from S3 into Matlab, fit the functional relationship between the structural design variables and the output variables, then create the variables, constraint functions, and objective functions of the optimization design model, create an optimization program based on the legacy algorithm, and achieve the optimal volume of the cylinder under the premise of satisfying various constraints, thereby completing the optimization design of the cylinder structure.

2. The method for optimizing the structure of an ultra-large transmission drum as described in claim 1, characterized in that, The initial structural parameters in S1 include: (1) Determine the diameter of the drive drum based on the belt strength used in the belt conveyor, and determine the length of the drive drum based on the belt width of the belt conveyor; (2) Determine the expansion sleeve model based on the transmitted torque, thereby determining the cylinder hub bore diameter; (3) Determine the outer diameter of the cylinder hub based on the empirical formula for the structural strength of the installed expansion sleeve hub; (4) Determine the wheel hub width based on the empirical formula that the wheel hub width is ≥ 1.5-2.0 mm of the expansion sleeve width; (5) Determine the thickness of the tube skin according to the empirical formula of Japanese Munetaka.

3. The method for optimizing the design of an ultra-large transmission roller structure according to claim 1, characterized in that, S2 includes: S21: After the cylindrical parametric model is created in S1, it is meshed to facilitate numerical calculation and analysis; S22: After meshing the cylindrical parametric model in S21, apply boundary conditions to it; S23: After adding the boundary conditions of the cylinder in S22, perform static simulation to obtain the initial cylinder volume, deformation displacement cloud map, normal stress at the critical section, and shear stress cloud map. The maximum normal stress, minimum normal stress, maximum shear stress, minimum shear stress, and maximum displacement at the critical section are parameterized and become the output variables for subsequent optimization design.

4. The method for optimizing the structure of an ultra-large transmission roller as described in claim 1, characterized in that, The boundary condition loading methods in S22 include: (1) The wrap angle of the cylinder is 200°. The entire arc segment is divided into 25° segments. The cylinder is divided into 8 segments along the circumference. The radial load is applied by uniformly distributing the pressure value at the middle position of each segment to the arc segment. The tangential load is applied by multiplying the pressure value of the arc segment by the friction coefficient. The moving arc segment is added with both normal and tangential loads, while the stationary arc segment is only added with normal loads. (2) Add remote displacement constraint at the hub hole where the expansion sleeve is installed on the cylinder.

5. The method for optimizing the design of an ultra-large transmission drum structure according to claim 1, characterized in that, In S3, the structural design variables and output variables are created using Latin hypercube sampling and a custom method of generating multiple sets of samples each time. After simulation calculation of the cylindrical parameterized model, multiple arrays of "input variables and their corresponding output parameters" are finally obtained, forming an experimental matrix diagram between design variables and output variables.

6. The method for optimizing the design of an ultra-large transmission drum structure according to claim 1, characterized in that, In S4, the design variables are the structural parameters of the cylinder. Finally, the hub radius H40, cylinder radius, cylinder thickness, hub height, and spoke radius are determined as structural design variables.

7. The method for optimizing the structure of an ultra-large transmission drum as described in claim 1, characterized in that, In S4, the objective function is the volume of the cylinder. The cylinder structure is appropriately simplified and divided into three parts: the outer shell, the spokes, and the hub. The final objective function formula is obtained through calculation.

8. The method for optimizing the design of an ultra-large transmission drum structure according to claim 1, characterized in that, The constraint functions for the cylinder optimization in S4 include strength conditions, stiffness conditions, and boundary conditions for structural parameters.

9. The method for optimizing the design of an ultra-large transmission drum structure according to claim 1, characterized in that, In S4, the nonlinear least squares method is used for fitting, and the function form is defined as polynomial.

10. A system for optimizing the structure of an ultra-large transmission drum, characterized in that, include: The model creation module is used to create a parametric model of the belt conveyor cylinder in a finite element environment based on the initial structural parameters of the cylinder, and to finally determine and create design variables. The boundary condition loading and static simulation module interacts with the model creation module. It is used to mesh the super-large cylindrical model created by the model creation module, add boundary conditions, and complete static simulation. It also reads out the maximum and minimum shear stress, maximum and minimum normal stress values ​​at the critical section and the maximum deformation of the cylindrical body to form output variables. The cylindrical body experimental design module interacts with the model creation module and the boundary condition loading and static simulation module. It is used to obtain the experimental matrix of design variables and output variables through ANSYS simulation and experimental design. This experimental matrix will be used to fit the constraint function for the subsequent optimization design of the cylindrical body in Matlab. The cylinder optimization design module interacts with the cylinder experimental design module. It is used to import the experimental matrix data in the cylinder experimental design module into Matlab, fit the functional relationship between the structural design variables and the output variables, and then create the variables, constraint functions, and objective functions of the optimization design model. Based on the inheritance algorithm, an optimization program is created to achieve the optimal volume of the cylinder under the premise of satisfying various constraints, thereby completing the cylinder structure optimization design.

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