A method and system for designing wall targeting structure of thin-walled ring vibrating polisher

Abstract

The invention discloses a method and system for designing a targeted structure of a thin-walled ring vibrating polisher wall, and relates to the technical field of surface rolling and finishing processing, wherein the method comprises: initializing container parameters of a thin-walled ring vibrating polisher; constructing an EDEM simulation model, performing discrete element simulation on the initialized container parameters, and obtaining simulation results; establishing a targeting capability index based on the energy state density of a granular medium; obtaining optimal container motion parameters based on the dynamic behavior of the energy state density of the granular medium and the targeting capability index; obtaining the sensitivity of the container wall targeting structure using the targeting capability index as a response value, and obtaining design variables based on a sensitivity threshold; fitting an objective function based on the targeting capability index using the design variables as constraints, obtaining optimal design parameters of the container wall targeting structure by solving the design variables, and completing the design of the thin-walled ring vibrating polisher wall targeting structure in combination with the optimal container motion parameters.

Description

Technical Field

[0001] The invention relates to the technical field of surface rolling and finishing processing, and in particular to a method and system for designing a wall targeting structure of a vibration polisher for thin-walled ring parts. Background Art

[0002] The annular casing and flame tube of aircraft engines are key supporting and energy conversion components in the engine. Most of their overall features are thin-walled cylindrical or conical annular structures, and their local features often contain a large number of processing features such as special-shaped holes, welded / milled boss islands, profile edges, grooves, etc. After forming, the surface is rough and the transition edges will have obvious burrs, sharp edges and defects, which become the main initiation sites of fatigue sources of engine fatigue failure, seriously affecting the service performance of parts. At present, such parts are generally polished manually, but different polishing tools need to be replaced for different processing features, which makes them inefficient and poor in stability. Vibration polishing has been widely used in many high-end equipment due to its excellent adaptability. Therefore, for the processing goal of efficient and high-quality polishing of such thin-walled ring parts, a combination of vibration excitation and wall constraint is used to realize the motion control of granular media under periodic vibration in an asymmetric potential field. However, in the process of control, the dynamic behavior of the entire granular medium group is jointly affected by geometric constraints and motion constraints. There are complex characteristics such as multivariable, nonlinear, and strong coupling between the two, which makes it challenging to design the wall structure and adjust the motion parameters. At the same time, the wall structure of the vibration polishing container is a key factor affecting the motion state of the granular medium. In order to achieve the particle flow field enhancement effect around the target workpiece or a certain part of the workpiece, it is urgent to form a wall structure design method that targets the workpiece or a certain processing feature on the workpiece and can give the granular medium targeting ability, thereby improving the processing quality of the workpiece. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a method for designing a targeted structure of a vibration polishing device wall for thin-walled rings. By selecting and designing motion parameters and device wall geometric parameters, the energy state density of the granular medium acting on the target workpiece or workpiece portion during the vibration polishing process is improved, so that the device wall geometric constraints are sufficient to give the granular medium the ability to target the workpiece or workpiece, and produce efficient processing capabilities on the target workpiece or portion, thereby achieving efficient and high-quality polishing.

[0004] To achieve the above object, the present invention provides a method for designing a wall targeting structure of a thin-walled ring vibrating polisher, the steps comprising:

[0005] S1. Initialize the container parameters of the thin-walled ring vibrating polisher, the container parameters including the container motion parameters and the design parameters of the container wall targeting structure; the set of the container motion parameters is ,in, is the motion matrix of the container vibration; i, j, k represent natural numbers; 1i is the complex number symbol; t is time; D is a one-dimensional vector with six degrees of freedom, ; A is the vibration amplitude, When the vibration direction is circular vibration, the swing angle amplitude is A / l 1 , l 1 is the container diameter; is the vibration frequency; the set of design parameters is , where the width ;high ; Distance from base surface to workpiece ; Asymmetric deflection angle β; Angle between the spiral direction and the vibration direction θ; The distance from the top of the structure to the bottom of the target part L=n 4 d;n 1 —n 4 It is a multiple of the nominal diameter d of the granular medium;

[0006] S2. constructing an EDEM simulation model using the Hertz-Mindlin contact model, and performing discrete element simulation on the initialized container parameters to obtain simulation results;

[0007] S3. Establishing a targeting capability index based on the energy state density of the particle medium; the targeting capability index includes , where TA is the targeting capability indicator; is the upper quartile of the energy state probability density function f(e) of the particle medium at the target site; The upper quartile of the energy state probability density function f(e) at the non-target site;

[0008] S4. Based on the dynamic behavior of the energy state density of the particle medium and the targeting capability index, the simulation results are decoupled and analyzed to obtain the optimal container motion parameters;

[0009] S5. Taking the targeting capability index as the response value, the response value and sensitivity of the container wall targeting structure are obtained through simulation calculation, and by setting a sensitivity threshold, the low-sensitivity design parameters are filtered out, and the high-sensitivity design parameters are used as design variables;

[0010] S6. Taking the design variables as constraints, fit the objective function based on the targeting capability index, solve the design variables through a nonlinear optimization algorithm, obtain the optimal design parameters of the container wall targeting structure, and combine with the optimal container motion parameters to complete the design of the thin-walled ring vibration polisher wall targeting structure.

[0011] Preferably, the larger the targeting index is, the longer the particle medium in the targeted area acts in a high energy state than in the non-targeted area in the same period of time, and the stronger the targeting ability of the wall structure to the particle medium is. Satisfy the following formula:

[0012] ,

[0013] Where F(e) is the distribution function of energy state; e _0.75 represents the critical value of 75% cumulative probability in the energy state distribution; f(e) is the probability density function of the energy state at point e, which is the energy state at t discrete moments within a period of time in the statistical area. The nonparametric estimate of is as follows:

[0014] ,

[0015] In the formula, is the normal force on the workpiece at t discrete moments within a period of time in the region; is the tangential velocity of the particle at t discrete moments in a period of time in the region; 𝑛 is the number of energy state E intervals; h w Indicates the width of each equal interval.

[0016] Preferably, in step S4, the decoupling analysis determines the motion law of the granular medium according to the stress state of the granular medium on the wall surface, and then analyzes the relationship between the geometric design parameters and the container motion parameters, wherein the motion differential equation of the granular medium constrained by the wall is:

[0017] ,

[0018] ,

[0019] The differential equation of motion of the granular medium constrained by the wall is:

[0020] ,

[0021] ,

[0022] In the formula, m is the weight of a single particle medium, G is the acceleration due to gravity, and f is x 、f y is the friction coefficient of the particle medium along the plane of the targeting structure; a x1 、a y1 、a z1 and a x2 、a y2 、a z2They are the decomposition of the acceleration of the container along the plane normal and tangential at the upper and lower edges of the structure respectively; ± represents the positive and reverse sliding of the granular medium along the tangent plane.

[0023] Preferably, in step S5, the simulation calculation discretizes the design parameters, designs an L25 (5^6) orthogonal simulation experiment, calculates the targeting capability index of each group, and uses it as the response value; is the response value of the simulation experiment of the i-th group and the j-th group, where the range of i and j is 1-5, and the sensitivity is based on the array through It can be calculated that is the arithmetic mean of TA when the k-th design parameter of set X remains unchanged at level i and the other parameters change. The calculation formula is:

[0024] ,

[0025] ,

[0026] ,

[0027] ,

[0028] ,

[0029] ,

[0030] Furthermore, a design parameter X k Sensitivity to TA value , and its calculation formula is:

[0031] ,

[0032] Among them, n=5.

[0033] Preferably, in step S5, the calculation formula of the sensitivity threshold includes:

[0034] ,

[0035] Among them, S TH represents the sensitivity threshold; Represents the design parameter X k Sensitivity to TA value.

[0036] According to S TH Screen design parameters and determine the optimal design parameter set ; Based on the existing simulation data, the mathematical model of the design parameter objective function is obtained through nonlinear fitting .

[0037] Preferably, in step S6, the nonlinear optimization algorithm adopts the Lagrange multiplier method, where is the design parameter inequality constraint, To design parameter equality constraints, the mathematical model includes:

[0038] ,

[0039] ,

[0040] ,

[0041] Among them, i, j, p, q represent natural numbers; min means taking the minimum value.

[0042] The present invention also provides a system for designing targeted structures of thin-walled ring vibration polisher walls, the system being used to implement the above method, comprising: an initialization module, a simulation module, a construction module, a decoupling module, a filtering module and a solving module;

[0043] The initialization module is used to initialize the container parameters of the thin-walled ring vibrating polisher, and the container parameters include the container motion parameters and the design parameters of the container wall targeting structure; the set of the container motion parameters is ,in, is the motion matrix of the container vibration; i is the element number of amplitude A, j is the element number of frequency f, k is the element number of vector D; 1i is the complex number symbol; t is time; D is a one-dimensional vector with six degrees of freedom, ; A is the vibration amplitude, When the vibration direction is circular vibration, the swing angle amplitude is A / l 1 , l 1 is the container diameter; is the vibration frequency; the set of design parameters is , where the width ;high ; Distance from base surface to workpiece ; Asymmetric deflection angle β; Angle between the spiral direction and the vibration direction θ; The distance from the top of the structure to the bottom of the target part L=n 4 d;n 1 —n 4 It is a multiple of the nominal diameter d of the granular medium;

[0044] The simulation module is used to construct an EDEM simulation model using a Hertz-Mindlin contact model, and to perform discrete element simulation on the initialized container parameters to obtain simulation results;

[0045] The building block is used to establish a targeting capability index based on the energy state density of the particle medium; the targeting capability index includes , where TA is the targeting capability indicator; is the upper quartile of the energy state probability density function f(e) of the particle medium at the target site; The upper quartile of the energy state probability density function f(e) at the non-target site;

[0046] The decoupling module is used to perform decoupling analysis on the simulation results based on the dynamic behavior of the energy state density of the particle medium and the targeting capability index to obtain the optimal container motion parameters;

[0047] The filtering module is used to obtain the response value and sensitivity of the container wall targeting structure by simulation calculation using the targeting capability index as the response value, and to filter the low-sensitivity design parameters by setting the sensitivity threshold, and to use the high-sensitivity design parameters as the design variables;

[0048] The solution module is used to fit the objective function based on the targeting capability index with the design variables as constraints, solve the design variables through a nonlinear optimization algorithm, obtain the optimal design parameters of the container wall targeting structure, and complete the design of the thin-walled ring vibration polisher wall targeting structure in combination with the optimal container motion parameters.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] Based on the dynamic behavior of granular media in the rolling finishing process, the present invention establishes an evaluation index for the targeting ability of granular media to the target processing position. Through the adjustment of vibration excitation and the design of geometric constraints of the wall, the granular media is given the ability of targeting, and the motion regulation under periodic vibration in an asymmetric potential field is realized, thereby further improving the processing ability and processing efficiency of the target position. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0052] Figure 1 is a flowchart of a method according to an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of design parameters of a vibration polishing container wall structure according to an embodiment of the present invention;

[0054] Figure 3A schematic diagram of setting contact parameters of a workpiece, a container and a granular medium according to an embodiment of the present invention;

[0055] Figure 4 A scatter plot of the normal force and tangential velocity of the granular medium in the target area of ​​an embodiment of the present invention;

[0056] Figure 5 A scatter plot of the normal force and tangential velocity of the particle medium in the non-targeted area of ​​an embodiment of the present invention;

[0057] Figure 6 The probability density curve of the energy states in the target area and the non-target area of ​​the embodiment of the present invention;

[0058] Figure 7 The figure is a comparison of the reduction rate of machining wear depth between the target area and the non-target area of ​​the embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0061] Figure 1 The target area of ​​this example is a boss on the outer wall of the aluminum alloy thin-walled ring. Figure 2 As shown. The outer wall diameter of the thin-walled ring is 200mm, the wall thickness is 5mm, and the height is 100mm. The particle medium adopts a 3mm oblique triangular silicon carbide grinding block. Figure 1 A method for designing a wall targeting structure for a thin-walled ring vibrating polisher is shown, comprising the following steps:

[0062] S1. Initialize the container parameters of the thin-walled ring vibrating polisher.

[0063] In this embodiment, the container parameters include container motion parameters and design parameters of the container wall targeting structure. Specifically, the set of container motion parameters is:

[0064] ,

[0065] in, is the motion matrix of the container vibration; i, j, k represent natural numbers; 1i is the complex number symbol; t is time; D is a one-dimensional vector with six degrees of freedom, ; A is the vibration amplitude, When the vibration direction is circular vibration, the swing angle amplitude is A / l 1 , l 1 is the container diameter; is the vibration frequency. In this embodiment, the initial vibration direction is , take the initial value , take the initial value Therefore, the motion matrix of the initial container vibration is .

[0066] The targeting structure of the container wall is obtained by rotating and stretching the asymmetric sawtooth section around the base surface of the container wall. The set of design parameters is: , where the width ;high ; Distance from base surface to workpiece ; Asymmetric deflection angle β; Angle between the spiral direction and the vibration direction θ; The distance from the top of the structure to the bottom of the target part L=n 4 d;n 1 —n 4 is a multiple of the nominal diameter d of the particle medium. Therefore, the design parameters of the targeting structure are initialized , d=3mm.

[0067] S2. The EDEM simulation model is constructed using the Hertz-Mindlin contact model, and the initialized container parameters are simulated using discrete element method to obtain the simulation results.

[0068] S201. Set the workpiece motion parameters to be consistent with the container motion parameters, and set the contact parameters of the workpiece, container and granular medium as follows: Figure 3 The intrinsic parameters are shown in Table 1 below.

[0069] Table 1

[0070] .

[0071] S202. The simulation time is 10 seconds, of which the first second is used to generate the granular medium with a filling amount of 75%, 1 to 10 seconds are the vibration polishing process, and the simulation data is saved with a time step of 0.001.

[0072] S3. Establish a targeting capability index based on the energy state density of the particle medium.

[0073] S301. Establish a data block in the target area and extract the normal force F of the granular medium on the workpiece at each moment after 4s of simulation n With tangential velocity F t , Figure 4 and Figure 5 The normal force F at each moment in the target area and the non-target area is n With tangential velocity F t Distribution map of .

[0074] S302. Calculate the energy state e at different times according to the following formula i , and draw a probability density curve with a width of 0.5 and a grouping of 100, such as Figure 6 shown.

[0075] ,

[0076] In the formula, is the normal force on the workpiece at t discrete moments within a period of time in the region; is the tangential velocity of the particle at t discrete moments within a period of time in the region.

[0077] The energy states of the target region and the non-target region at t discrete moments in a period of time are calculated according to the following formula The probability density function of the energy state is calculated as follows: Figure 6 shown.

[0078] ,

[0079] In the formula, is the normal force on the workpiece at t discrete moments within a period of time in the region; is the tangential velocity of the particle at t discrete moments in a period of time in the region; 𝑛 is the number of energy state E intervals; h w Indicates the width of each equal interval.

[0080] According to the formula, we can get Figure 6 The target area probability density function shown is:

[0081] ,

[0082] The probability density function of the non-targeted area is:

[0083] , where e is the natural logarithm and x represents the energy state variable.

[0084] Then the targeting capability index, namely the targeting index, is:

[0085] ,

[0086] Among them, TA is the targeting ability indicator; is the upper quartile of the energy state probability density function f(e) of the particle medium at the target site; is the upper quartile of the energy state probability density function f(e) of the non-target site

[0087] It represents the energy state corresponding to the probability that the energy state in the two regions accounts for more than 75%. The larger the TA, the longer the time that the particle medium in the targeted area acts in a high energy state compared to the non-targeted area in the same period of time, and the stronger the targeting ability of the wall structure to the particle medium. Satisfy the following formula:

[0088] ,

[0089] Where F(e) is the distribution function of energy state; e _0.75 represents the critical value of 75% cumulative probability in the energy state distribution; f(e) is the probability density function of the energy state at point e, which is the energy state at t discrete moments within a period of time in the statistical area. Nonparametric estimation of .

[0090] In summary, the targeting capability index of this embodiment is:

[0091] .

[0092] S4. Based on the dynamic behavior of the energy state density of the granular medium and the targeting capability index, the simulation results are decoupled and analyzed to obtain the optimal container motion parameters.

[0093] S401. According to the force state of the granular medium on the surface of the targeting structure of the vessel wall, the motion law of the granular medium is determined, and then the relationship between the geometric design parameters and the container motion parameters is analyzed, wherein the motion differential equation of the granular medium constrained by the vessel wall is:

[0094] ,

[0095] ,

[0096] The differential equation of motion of the granular medium constrained by the wall is:

[0097] ,

[0098] ,

[0099] In the formula, m is the weight of a single particle medium, G is the acceleration due to gravity, and f is x 、f y is the friction coefficient of the particle medium along the plane of the targeting structure; a x1 、a y1 、a z1 and a x2 、a y2 、a z2They are the decomposition of the acceleration of the container along the plane normal and tangential at the upper and lower edges of the structure respectively; ± represents the positive and reverse sliding of the granular medium along the tangent plane.

[0100] S402. To ensure that more granular media move to the target position, it is determined according to the differential equation of motion that under a suitable asymmetric deflection angle β, the acceleration provided by the container vibration should be greater than the gravitational acceleration after geometric decomposition, and the greater the acceleration, the more violent the sliding.

[0101] S5. Taking the targeting capability index as the response value, the response value and sensitivity of the targeting structure of the container wall are obtained through simulation calculation, and by setting the sensitivity threshold, the design parameters with low sensitivity are filtered out, and the design parameters with high sensitivity are used as design variables.

[0102] S501. By discretizing the design parameters, an L25 (5^6) orthogonal simulation experiment is designed, wherein the factor levels of the orthogonal experiment target structure design parameters are shown in Table 2:

[0103] Table 2

[0104] .

[0105] S502. Simulate and calculate the targeting ability evaluation index TA of each group and use it as the response value. And calculate the sensitivity array through the TA value ,in is the arithmetic mean of TA when the k-th design parameter of set X remains unchanged at level i and the other parameters change. The calculation formula is:

[0106] ,

[0107] ,

[0108] ,

[0109] ,

[0110] ,

[0111] ,

[0112] Furthermore, a design parameter X k Sensitivity to TA value , and its calculation formula is:

[0113] ,

[0114] Among them, n=5.

[0115] According to the formula in S502, the calculation results are shown in Table 3:

[0116] Table 3

[0117] .

[0118] S503. Calculate the density threshold according to the above table:

[0119] ,

[0120] Among them, S TH represents the sensitivity threshold; Represents the design parameter X k Sensitivity to TA value.

[0121] According to the calculation in Table 3, the sensitivity threshold of this example is 0.0512, so the entire design parameter has a great influence on the targeting index. The optimal design parameter set is ; Based on the existing simulation data, the mathematical model of the design parameter objective function is obtained through nonlinear fitting .

[0122] S504. Based on the existing simulation data, the mathematical model of the design parameter objective function is obtained by nonlinear fitting:

[0123] ,

[0124] Among them, w represents width, h represents height, D w It represents the distance from the base surface to the workpiece; β represents the asymmetric deflection angle; θ represents the angle between the spiral direction and the vibration direction; L represents the distance from the structure vertex to the bottom of the target part.

[0125] S6. Taking the design variables as constraints, fit the objective function based on the targeting capability index, solve the design variables through the nonlinear optimization algorithm, obtain the optimal design parameters of the container wall targeting structure, and combine with the optimal container motion parameters to complete the design of the thin-walled ring vibration polisher wall targeting structure.

[0126] S601. According to the objective function obtained by fitting and the constraints of the high sensitivity parameters, the following mathematical model is established:

[0127] ,

[0128] ,

[0129] ,

[0130] Among them, w represents width, h represents height, D wrepresents the distance from the base surface to the workpiece; β represents the asymmetric deflection angle; θ represents the angle between the spiral direction and the vibration direction; L represents the distance from the structure vertex to the bottom of the target part; i, j, p, q represent natural numbers; is the design parameter inequality constraint; is the design parameter equality constraint; min means taking the minimum value.

[0131] S602. Use the nonlinear optimization algorithm integrated in Matlab and the Lagrange multiplier method to solve the mathematical model.

[0132] S603: Modeling the solution results and performing simulation verification again. The TA value is 4.1, which is greater than the TA value of the existing simulation results and meets the design requirements.

[0133] The designed targeting structure parameters are arrayed along the height direction and actual processing tests are carried out. The processing results are as follows: Figure 7 As shown in the figure, within the same processing time, the outer surface roughness reduction rate of the thin-walled ring with targeted structure is 10%-25% higher than that of the non-targeted structure; the inner surface roughness reduction rate of the thin-walled ring with targeted structure is 10%-25% higher than that of the non-targeted structure.

[0134] In addition, in step S6, the targeting capability requirement is the global optimal solution of the targeting capability index. If the targeting capability requirement is not met, return to S5 and repeat S5-S6 until the requirement of the particle medium targeting capability is met. The targeting area can be a certain feature on the workpiece or the entire surface to be processed of the workpiece, wherein the targeting structure can be arranged in an array for the entire surface to be processed.

[0135] Embodiment 2

[0136] This embodiment also provides a system for designing a wall targeted structure of a thin-walled ring vibrating polisher, including: an initialization module, a simulation module, a construction module, a decoupling module, a filtering module, and a solving module;

[0137] The initialization module is used to initialize the container parameters of the thin-walled ring vibrating polisher. The container parameters include the container motion parameters and the design parameters of the container wall targeting structure. The set of container motion parameters is ,in, is the motion matrix of the container vibration; i, j, k represent natural numbers; 1i is the complex number symbol; t is time; D is a one-dimensional vector with six degrees of freedom, ; A is the vibration amplitude, When the vibration direction is circular vibration, the swing angle amplitude is A / l 1 , l 1 is the container diameter; is the vibration frequency; the set of design parameters is , where the width ;high ; Distance from base surface to workpiece ; Asymmetric deflection angle β; Angle between the spiral direction and the vibration direction θ; The distance from the top of the structure to the bottom of the target part L=n 4 d;n 1 —n 4 It is a multiple of the nominal diameter d of the granular medium;

[0138] The simulation module is used to construct an EDEM simulation model using the Hertz-Mindlin contact model and perform discrete element simulation on the initialized container parameters to obtain simulation results;

[0139] The building blocks are used to establish targeting capability indicators based on the energy state density of the particle medium; targeting capability indicators include , where TA is the targeting capability indicator; is the upper quartile of the energy state probability density function f(e) of the particle medium at the target site; The upper quartile of the energy state probability density function f(e) at the non-target site;

[0140] The decoupling module is used to decouple the simulation results based on the dynamic behavior of the energy state density of the particle medium and the targeting capability index to obtain the optimal container motion parameters;

[0141] The filtering module is used to obtain the response value and sensitivity of the container wall targeting structure by simulation calculation with the targeting capability index as the response value, and to filter the low-sensitivity design parameters by setting the sensitivity threshold, and to use the high-sensitivity design parameters as the design variables;

[0142] The solution module is used to fit the objective function based on the targeting capability index with the design variables as constraints, solve the design variables through the nonlinear optimization algorithm, obtain the optimal design parameters of the container wall targeting structure, and complete the design of the thin-walled ring vibration polisher wall targeting structure in combination with the optimal container motion parameters.

[0143] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for designing a wall targeting structure of a thin-walled ring vibrating polisher, characterized in that the steps include: S1. Initialize the container parameters of the thin-walled ring vibrating polisher, wherein the container parameters include the container motion parameters and the design parameters of the container wall targeting structure; S2. constructing an EDEM simulation model using the Hertz-Mindlin contact model, and performing discrete element simulation on the initialized container parameters to obtain simulation results; S3. Establishing a targeting capability index based on the energy state density of the particle medium; the targeting capability index includes , where TA is the targeting capability indicator; is the upper quartile of the energy state probability density function f(e) of the particle medium at the target site; The upper quartile of the energy state probability density function f(e) at the non-target site; S4. Based on the dynamic behavior of the energy state density of the particle medium and the targeting capability index, the simulation results are decoupled and analyzed to obtain the optimal container motion parameters; S5. Taking the targeting capability index as the response value, the response value and sensitivity of the container wall targeting structure are obtained through simulation calculation, and by setting a sensitivity threshold, the low-sensitivity design parameters are filtered out, and the high-sensitivity design parameters are used as design variables; S6. Taking the design variables as constraints, fit the objective function based on the targeting capability index, solve the design variables through a nonlinear optimization algorithm, obtain the optimal design parameters of the container wall targeting structure, and combine with the optimal container motion parameters to complete the design of the thin-walled ring vibration polisher wall targeting structure.

2. The method for designing a wall targeting structure of a thin-walled ring vibrating polisher according to claim 1, characterized in that: The set of container motion parameters is ,in, is the motion matrix of the container vibration; i, j, k represent natural numbers; 1i is the complex number symbol; t is time; D is a one-dimensional vector with six degrees of freedom, ; A is the vibration amplitude, , when the vibration direction is circular vibration, the swing angle amplitude is A / l1, l1 is the container diameter; is the vibration frequency; the set of design parameters is , where the width ;high ; Distance from base surface to workpiece ; Asymmetric deflection angle β; Angle θ between the spiral direction and the vibration direction; The distance from the structure vertex to the bottom of the target part L=n4d; n1-n4 are multiples of the nominal diameter d of the granular medium.

3. The method for designing a wall targeting structure of a thin-walled ring vibrating polisher according to claim 1, characterized in that: The larger the targeting index is, the longer the particle medium in the targeted area acts in a high energy state than in the non-targeted area in the same period of time, and the stronger the targeting ability of the vessel wall structure to the particle medium is. Satisfy the following formula: ， Where F(e) represents the distribution function of energy state; e _0.75 represents the critical value of 75% cumulative probability in the energy state distribution; f(e) is the probability density function of the energy state at point e, which is the energy state at t discrete moments within a period of time in the statistical area. The non-parametric estimate of is as follows: ， In the formula, is the normal force on the workpiece at t discrete moments within a period of time in the region; is the tangential velocity of the particle at t discrete moments in a period of time in the region; 𝑛 is the number of energy state E intervals; h w Indicates the width of each equal interval.

4. The method for designing a wall targeting structure for a thin-walled ring vibrating polisher according to claim 2, characterized in that: In step S4, the decoupling analysis determines the motion law of the granular medium according to the stress state of the granular medium on the wall surface, and then analyzes the relationship between the geometric design parameters and the container motion parameters, wherein the motion differential equation of the granular medium constrained by the wall is: ， ， The differential equation of motion of the granular medium constrained by the wall is: ， ， In the formula, m is the weight of a single particle medium, G is the acceleration due to gravity, and f is x 、f y is the friction coefficient of the particle medium along the plane of the targeting structure; a x1 、a y1 、a z1 and a x2 、a y2 、a z2 They are the decomposition of the acceleration of the container along the plane normal and tangential at the upper and lower edges of the structure respectively; ± represents the positive and reverse sliding of the granular medium along the tangent plane.

5. The method for designing a wall targeting structure for a thin-walled ring vibrating polisher according to claim 1, characterized in that: In step S5, the simulation calculation discretizes the design parameters, designs an orthogonal simulation experiment, calculates the targeting capability index of each group, and uses it as the response value; is the response value of the simulation experiment of the i-th group and the j-th group, where the range of i and j is 1-5, and the sensitivity is based on the array through It can be calculated that is the arithmetic mean of TA when the k-th design parameter of set X remains unchanged at level i and the other parameters change. The calculation formula is: ， ， ， ， ， ， Furthermore, a design parameter X k Sensitivity to TA value , and its calculation formula is: ， Among them, n=5.

6. The method for designing a wall targeting structure for a thin-walled ring vibrating polisher according to claim 1, characterized in that: In step S5, the calculation formula of the sensitivity threshold includes: ， Among them, S TH represents the sensitivity threshold; Represents the design parameter X k Sensitivity to TA value; According to S TH Screen design parameters and determine the optimal design parameter set ; Based on the existing simulation data, the mathematical model of the design parameter objective function is obtained through nonlinear fitting .

7. The method for designing a wall targeting structure for a thin-walled ring vibrating polisher according to claim 1, characterized in that: In step S6, the nonlinear optimization algorithm adopts the Lagrange multiplier method, where is the design parameter inequality constraint, To design parameter equality constraints, the mathematical model includes: ， ， ， Among them, i, j, p, q represent natural numbers; min means taking the minimum value.

8. A system for designing targeted structures of thin-walled ring vibrating polisher walls, the system being used to implement the method described in any one of claims 1 to 7, characterized in that: include: Initialization module, simulation module, construction module, decoupling module, filtering module and solution module; The initialization module is used to implement step S1; The simulation module is used to implement step S2; The building block is used to implement step S3; The decoupling module is used to implement step S4; The filtering module is used to implement step S5; The solution module is used to implement step S6.

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