Modeling method and modeling system for supporting platform

Abstract

The invention provides a modeling method of a supporting platform and a system thereof, and relates to the field of dynamic modeling, the modeling method comprises the following steps: establishing an initial finite element model based on the structure of an actual supporting platform, calculating the initial finite element model to obtain simulation modal data, the simulation modal data comprises a plurality of simulation inherent frequencies and simulation vibration modes corresponding to the inherent frequencies; performing an experiment on the actual supporting platform to obtain actual modal data, wherein the actual modal data comprises a plurality of actual inherent frequencies and actual vibration modes corresponding to the actual inherent frequencies; constructing a model evaluation function based on a difference value between the simulated inherent frequency and the actual inherent frequency and a correlation degree between the simulated vibration mode and the actual vibration mode; and optimizing the parameters of the initial finite element model until the residual error of the structural characteristic quantity calculated based on the model evaluation function reaches the minimum value. According to the modeling method, the accuracy of the finite element model can be improved, so that the accuracy of the intrinsic mode characteristics obtained through simulation is improved.

Description

Technical Field

[0001] The present invention relates to the field of dynamic modeling, and in particular to a modeling method of a support platform and a modeling system thereof. Background Art

[0002] The support platform is a device used to carry mechanical equipment. In order to assist in the structural design of the support platform, it is necessary to establish a model of the support platform to simulate the stress and strain distribution of the model under different loads, so as to optimize the structure of the support platform.

[0003] The digital model of finite element simulation established by related methods has poor accuracy and is difficult to simulate complex nonlinear connection relationships. The accuracy of the inherent modal characteristics obtained by simulation is also low. Summary of the invention

[0004] The present invention provides a modeling method of a support platform and a modeling system thereof, which are used to solve the technical problem of how to improve the accuracy of an established finite element model, thereby improving the accuracy of inherent modal characteristics obtained by simulation.

[0005] An embodiment of the present invention provides a modeling method for a support platform, which includes: establishing an initial finite element model based on the structure of an actual support platform, calculating simulated modal data based on the initial finite element model, the simulated modal data including multiple simulated natural frequencies and simulated vibration modes corresponding to each of the simulated natural frequencies; performing experiments on the actual support platform to obtain actual modal data, the actual modal data including multiple actual natural frequencies and actual vibration modes corresponding to each of the actual natural frequencies; constructing a model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode; and optimizing the parameters of the initial finite element model until the residual error of the structural characteristic quantity calculated based on the model evaluation function reaches a minimum value.

[0006] In some embodiments, constructing a model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode includes: calculating the difference between the simulated natural frequency and the actual natural frequency and standardizing the difference to obtain a standardized frequency difference; calculating a modal confidence criterion based on the simulated vibration mode and the actual vibration mode; and constructing the model evaluation function as a weighted sum of the standardized frequency difference and the modal confidence criterion.

[0007] In some embodiments, the calculation of the difference between the simulated natural frequency and the actual natural frequency includes: calculating the difference between the first five orders of the simulated natural frequencies and the first five orders of the actual natural frequencies, wherein the first five orders of the simulated natural frequencies are the first five simulated natural frequencies in a sequence in which the simulated natural frequencies are arranged from small to large, and the first five orders of the actual natural frequencies are the first five actual frequencies in a sequence in which the actual natural frequencies are arranged from small to large; the calculation based on the simulated vibration shapes and the actual vibration shapes to obtain the modal confidence criterion includes: obtaining the modal confidence criterion for the first five orders of the simulated vibration shapes and the first five orders of the actual vibration shapes, wherein the first five orders of the simulated vibration shapes are the simulated vibration shapes corresponding to the first five orders of the simulated frequencies, and the first five orders of the actual vibration shapes are the actual vibration shapes corresponding to the first five orders of the actual frequencies.

[0008] In some embodiments, the support platform is used to support optical equipment, and the support platform includes: a support platform and leveling support legs, and a plurality of the leveling support legs are spaced apart at the bottom of the support platform to adjust the lifting and lowering of the support platform, wherein the leveling support legs include: a support bearing, a thrust bearing, a screw, an outer sleeve, an inner sleeve, a ball seat and a base, and establishing an initial finite element model based on the structure of the actual support platform includes: simplifying the connection relationship between the support bearing and the thrust bearing and each part into a plurality of spring units; dividing the support platform, the screw, the outer sleeve, the inner sleeve, the ball seat and the base into a plurality of solid units.

[0009] In some embodiments, simplifying the connection relationship between the support bearing and the thrust bearing and various components into multiple spring units includes: simplifying the support bearing and the thrust bearing into multiple spring units; simplifying the connection position between the screw rod and the inner sleeve into multiple spring units, simplifying the connection position between the ball seat and the base into a spring unit, and simplifying the connection position between the base and the support surface into a spring element.

[0010] In some embodiments, before optimizing the parameters of the initial finite element model, the modeling method further includes: determining the parameters in the initial finite element model whose influence on the local stiffness is greater than an influence threshold as optimization parameters, wherein the influence of the stiffness parameter of the spring unit on the local stiffness is greater than the influence threshold, and the stiffness parameter of the spring unit is determined as the optimization parameter; optimizing the parameters of the initial finite element model until the residual of the structural feature quantity calculated based on the model evaluation function reaches a minimum value includes: optimizing the optimization parameters until the residual of the structural feature quantity calculated based on the model evaluation function reaches a minimum value.

[0011] In some embodiments, determining the parameters in the initial finite element model whose influence on local stiffness is greater than an influence threshold as optimization parameters includes: constructing a system response function of the initial finite element model, and calculating the partial derivative of the system response function with respect to each of the parameters, and determining the parameters whose partial derivatives are greater than the influence threshold as optimization parameters.

[0012] In some embodiments, after optimizing the parameters of the initial finite element model until the residual of the structural feature quantity calculated based on the model evaluation function reaches a minimum value, the modeling method further includes: converting each of the spring units into a rigid unit, and determining the degree of freedom of the converted rigid unit based on the stiffness parameter of each of the spring units, wherein the degree of freedom of the spring unit whose stiffness parameter is greater than a stiffness threshold is determined to be fixed, and the degree of freedom of the spring unit whose stiffness parameter is less than the stiffness threshold is determined to be free.

[0013] An embodiment of the present invention also provides a modeling system for a support platform, including a simulation unit for calculating simulated modal data based on an initial finite element model, wherein the simulated modal data includes multiple simulated natural frequencies and simulated vibration modes corresponding to each of the simulated natural frequencies; a storage unit for storing the simulated modal data, and for storing actual modal data obtained by experiments on the actual support platform, wherein the actual modal data includes multiple actual natural frequencies and actual vibration modes corresponding to each of the actual natural frequencies; a data processing unit for constructing a model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode, and for optimizing the parameters of the initial finite element model until the residual of the structural characteristic quantity calculated based on the model evaluation function reaches a minimum value.

[0014] In some embodiments, the data processing unit is further used to calculate the difference between the simulated natural frequency and the actual natural frequency and to standardize the difference to obtain a standardized frequency difference; is further used to calculate a modal confidence criterion based on the simulated vibration shape and the actual vibration shape; and is further used to construct the weighted sum of the standardized frequency difference and the modal confidence criterion as the model evaluation function.

[0015] An embodiment of the present invention provides a modeling method for a support platform, which includes establishing an initial finite element model based on an actual support platform, calculating simulated natural frequencies and simulated vibration modes corresponding to each simulated natural frequency based on the initial finite element model, conducting experiments on the actual support platform to obtain actual natural frequencies and actual vibration modes corresponding to each actual natural frequency, and at the same time, constructing a model evaluation function through the difference between the simulated natural frequency and the actual natural frequency and the correlation between the simulated vibration mode and the actual vibration mode, and optimizing the parameters of the initial finite element model until the residual of the structural characteristic quantity calculated based on the model evaluation function reaches a minimum value. It can be understood that the parameters of the initial finite element model are optimized according to the difference between the actual modal data of the actual support platform and the simulated modal data of the initial finite element model, so that the optimized finite element model can be closer to the structural parameters and modal parameters of the actual support platform, that is, the finite element model has higher accuracy, and the model evaluation parameters are constructed by the difference between the two dimensions of natural frequency and vibration mode, which can more accurately reflect the difference between the finite element model and the actual support platform, further improve the accuracy of the optimized finite element model, thereby improving the accuracy of the natural modal characteristics obtained by simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a first support platform modeling method provided in an embodiment of the present invention;

[0017] Figure 2 A schematic flow chart of a second support platform modeling method provided in an embodiment of the present invention;

[0018] Figure 3 It is a structural diagram of the support platform;

[0019] Figure 4 It is a schematic diagram of the structure of the leveling support legs in the support platform;

[0020] Figure 5 A schematic flow chart of a third support platform modeling method provided in an embodiment of the present invention;

[0021] Figure 6 A simplified schematic diagram of the structure for leveling the support legs;

[0022] Figure 7 A schematic flow chart of a fourth support platform modeling method provided in an embodiment of the present invention;

[0023] Figure 8 A schematic flow chart of a fifth support platform modeling method provided in an embodiment of the present invention;

[0024] Fig. 9A schematic diagram of the structure of a modeling system of a support platform provided in an embodiment of the present invention.

[0025] Description of Reference Numerals

[0026] 1. Load-bearing platform; 2. Leveling support leg; 21. Support bearing; 22. Thrust bearing; 23. Screw; 24. Outer sleeve; 25. Inner sleeve; 26. Ball seat; 27. Base. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0028] The various specific technical features in the various embodiments described in the specific implementation methods can be combined in various ways without contradiction. For example, different implementation methods can be formed by combining different specific technical features. In order to avoid unnecessary repetition, the various possible combinations of the specific technical features in the present invention will not be described separately.

[0029] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only structures and / or processing steps closely related to the scheme of the present invention are shown in the drawings, while other details that are not closely related to the present invention are omitted.

[0030] In addition, it should be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the following description, the terms "first\second\..." involved are merely used to distinguish different objects, and do not indicate that the objects have the same or related points. It should be understood that the directions described by the directions nouns such as "above", "below", "inside" and "outside" involved are all directions in normal use.

[0031] In the following specific implementations, the support platform can be used to carry any mechanical equipment, such as a high-precision measuring device or an optical device. The support platform can be used only for support or have other functions. For example, the support platform also has a lifting function to drive the mechanical equipment to lift or level the support platform. For example, the support platform also has a vibration reduction function to reduce the impact of external vibration on the mechanical equipment. The steps of the modeling method of the support platform are exemplarily described below in combination with various embodiments.

[0032] In some embodiments, Figure 1 As shown, Figure 1 A schematic flow chart of a first support platform modeling method provided in an embodiment of the present invention, the modeling method comprising:

[0033] Step S101: establishing an initial finite element model based on the structure of the actual support platform.

[0034] It can be understood that a finite element model corresponding to the structure of the actual support platform is established in the finite element simulation software. The finite element model includes multiple units and nodes are formed between the units. The units are connected through nodes, transmit forces only at the nodes, and are constrained only at the nodes. At the same time, each unit has attribute parameters, which include dynamic parameters such as elastic modulus, stiffness and rotational inertia. It should be noted that the attribute parameters of each unit in the initial finite element model constructed here are the initial parameters determined by the modeler based on the actual dynamic parameters and experience of the actual support platform. The accuracy of the initial finite element model is low, and the accuracy of the inherent modal parameters obtained by simulating the initial finite element model is low, and the parameters of the initial finite element model need to be optimized.

[0035] Step S102: Calculate and obtain simulated modal data based on the initial finite element model.

[0036] It can be understood that, in the finite element simulation software, boundary conditions are imposed on the initial finite element model based on the load conditions of the actual support platform, and the initial finite element model calculates the simulated modal data under the boundary conditions. The simulated modal data includes multi-order modal data, and each order of modal data includes a natural frequency and simulated vibration shape data corresponding to the natural frequency.

[0037] Step S103: Conduct experiments on the actual support platform to obtain actual modal data.

[0038] It can be understood that the structural parameters of the actual support platform are obtained through experiments, and the actual modal data of the actual support platform are calculated through the structural parameters. The actual modal data include multi-order actual modal data, and each order of actual modal data includes a natural frequency and an actual vibration mode corresponding to the natural frequency.

[0039] Step S104: construct a model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode.

[0040] It can be understood that the constructed model evaluation function includes evaluation indicators of two dimensions. One evaluation indicator is the overlap degree between the simulated natural frequency and the actual natural frequency, and the other evaluation indicator is the overlap degree of the corresponding vibration mode in each order modal data. The model evaluation parameter can be used to determine the overlap degree between the modal data of the constructed finite element model and the modal data of the actual support platform. Since the evaluation parameter takes into account both the overlap degree of the natural frequency and the overlap degree of the vibration mode at the same time, the accuracy of the established finite element model can be evaluated more accurately.

[0041] Step S105: Optimize the parameters of the initial finite element model until the residual of the structural characteristic quantity calculated based on the model evaluation function reaches a minimum value.

[0042] It can be understood that by adjusting the parameters in the initial finite element model in the search area, new model modal data is obtained through the simulation software after each adjustment, and the structural feature quantity residual is calculated based on the model evaluation function until the structural feature quantity residual converges to the minimum value that can be obtained. The structural feature residual represents the difference between the finite element model and the actual support platform. When the structural feature residual reaches the minimum value, it can be considered that the parameter optimization in the initial finite element model is completed, and the optimized finite element model can more accurately reflect the structural characteristics and modal characteristics of the actual support platform, that is, the accuracy of the established finite element model is improved, thereby improving the accuracy of the inherent modal characteristics obtained by simulation. Among them, the parameter adjustment of the finite element model can be an exhaustive search in the search area, and the parameter adjustment can also be achieved by the gradient descent method. The parameter adjustment can also be achieved by other intelligent algorithms, such as simulated annealing algorithm or particle swarm algorithm.

[0043] Optionally, adjusting the parameters in the initial finite element model may be adjusting all parameters in the initial finite element model; optionally, adjusting the parameters in the initial finite element model may be adjusting some key parameters in the initial finite element model.

[0044] An embodiment of the present invention provides a modeling method for a support platform, which includes establishing an initial finite element model based on an actual support platform, calculating simulated natural frequencies and simulated vibration modes corresponding to each simulated natural frequency based on the initial finite element model, conducting experiments on the actual support platform to obtain actual natural frequencies and actual vibration modes corresponding to each actual natural frequency, and at the same time, constructing a model evaluation function through the difference between the simulated natural frequency and the actual natural frequency and the correlation between the simulated vibration mode and the actual vibration mode, and optimizing the parameters of the initial finite element model until the residual of the structural characteristic quantity calculated based on the model evaluation function reaches a minimum value. It can be understood that the parameters of the initial finite element model are optimized according to the difference between the actual modal data of the actual support platform and the simulated modal data of the initial finite element model, so that the optimized finite element model can be closer to the structural parameters and modal parameters of the actual support platform, that is, the finite element model has higher accuracy, and the model evaluation parameters are constructed by the difference between the two dimensions of natural frequency and vibration mode, which can more accurately reflect the difference between the finite element model and the actual support platform, further improve the accuracy of the optimized finite element model, thereby improving the accuracy of the natural modal characteristics obtained by simulation.

[0045] In some embodiments, Figure 2 As shown, Figure 2 A schematic diagram of a flow chart of a second support platform modeling method provided in an embodiment of the present invention, based on Figure 1 , Figure 1 Step S104 in the embodiment includes:

[0046] Step S201: Calculate the difference between the simulated natural frequency and the actual natural frequency and standardize the difference to obtain a standardized frequency difference.

[0047] It can be understood that the frequency difference of each order of natural frequency is obtained by subtracting the corresponding simulated natural frequency from the actual natural frequency of each order, and the frequency difference of each order of natural frequency is divided by the corresponding actual natural frequency to obtain the standardized frequency difference of each order, thereby reducing the influence of the absolute size of the natural frequency on the residual of the structural characteristic quantity.

[0048] Optionally, in order to reduce the influence of the magnitude relationship between the simulated natural frequency and the actual natural frequency, the absolute value obtained by subtracting the corresponding simulated natural frequency of each order from the actual natural frequency of each order may be determined as the frequency difference of the natural frequency of each order.

[0049] Optionally, among the modal parameters of each order, the low-frequency natural frequency has the greatest impact on the simulation results, and the difference between the first five simulated natural frequencies and the first five actual natural frequencies can be calculated, where the first five simulated natural frequencies are the first five simulated natural frequencies in the sequence obtained by arranging the simulated natural frequencies from small to large, and the first five actual natural frequencies are the first five actual natural frequencies in the sequence obtained by arranging the actual natural frequencies from small to large.

[0050] Step S202: Calculate and obtain a modal confidence criterion based on the simulated vibration mode shape and the actual vibration mode shape.

[0051] It can be understood that each order of simulated vibration mode and the corresponding actual vibration mode are brought into the modal confidence criterion calculation formula to obtain each order of modal confidence criterion. The modal confidence criterion is used to indicate the correlation between each order of simulated vibration mode and the actual vibration mode. The modal confidence criterion is between 0 and 1. The larger the modal confidence criterion, the higher the correlation between the two vibration modes and the smaller the difference between the two vibration modes. The modal confidence criterion calculation formula is:

[0052]

[0053] In the formula, C maci represents the modal confidence criterion between the ith simulated vibration mode and the ith actual vibration mode, Φ 1i represents the i-th order simulated vibration mode, Φ 2i represents the actual vibration mode of the i-th order.

[0054] Optionally, among the modal parameters of each order, the low-frequency natural frequency has the greatest impact on the simulation results, and the difference between the first five simulated natural frequencies and the first five actual natural frequencies can be calculated, where the first five simulated natural frequencies are the first five simulated natural frequencies in the sequence obtained by arranging the simulated natural frequencies from small to large, and the first five actual natural frequencies are the first five actual natural frequencies in the sequence obtained by arranging the actual natural frequencies from small to large.

[0055] Optionally, among the modal parameters of each order, the low-frequency natural frequency has the greatest impact on the simulation results, and the modal confidence criteria of the first five simulated vibration modes and the first five actual vibration modes can be calculated, where the first five simulated vibration modes are the simulated vibration modes corresponding to the first five simulated natural frequencies, and the first five actual vibration modes are the actual vibration modes corresponding to the first five actual natural frequencies.

[0056] Step S203: constructing a model evaluation function by adding a weighted sum of the normalized frequency difference and the modal confidence criterion.

[0057] That is, the model evaluation function is to perform weighted sum calculation on each order of standardized frequency difference and the corresponding modal confidence criterion, and then accumulate each weighted sum. Optionally, in order to further avoid the influence of the modal criterion on the model evaluation function, it is also necessary to divide each order of modal confidence criterion by the corresponding actual modal confidence criterion. Specifically, the model evaluation function is:

[0058]

[0059] Where J(p) is the residual of the feature quantity, w is the weight, and f ai is the ith order simulated natural frequency, f bi is the actual natural frequency of the i-th order, C maci It represents the modal confidence criterion between the i-th order simulated vibration mode and the i-th order actual vibration mode. In the process of modal confidence criterion calculation, two vibration mode matrices need to be multiplied. In order to keep the calculation unit consistent, it is necessary to subtract 1 from the modal confidence criterion under the square root and then perform a quadratic operation on the calculated difference.

[0060] In some embodiments, the support platform is used to carry optical equipment, such as Figure 3 As shown, the support platform includes: a carrying platform 1 and a leveling support leg 2. The carrying platform 1 is used to carry the optical device. A plurality of leveling support legs 2 are located below the carrying platform 1. The carrying platform 1 can be driven to move up and down by the synchronous lifting and lowering movement of each leveling support leg 2. Moreover, the angle between the carrying platform 1 and the horizontal plane can be adjusted by the asynchronous lifting and lowering movement of each leveling support leg 2 to achieve the leveling of the carrying platform 1. The structure of the leveling support leg 2 is further described below. Figure 4As shown, the leveling support leg 2 includes: a support bearing 21, a thrust bearing 22, a screw rod 23, an outer sleeve 24, an inner sleeve 25, a ball seat 26 and a base 27. The outer sleeve 24 is sleeved on the outside of the inner sleeve 25 and is slidably connected to the inner sleeve. The screw rod 23 is rotationally connected to the inner sleeve 25 and is connected to the outer sleeve 24. The rotation of the screw rod 23 relative to the inner sleeve 25 can drive the screw rod 23 and the outer sleeve 24 to slide in the vertical direction. The outer sleeve 24 is connected to the support platform 1 to drive the support platform 1 to move up and down. The support bearing 21 is located between the screw rod 23 and the outer sleeve 24. The support bearing 21 can move up and down with the outer sleeve 24 and the screw rod 23 and allow The screw rod 23 is allowed to rotate relative to the outer sleeve 24, and the longitudinal load carried by the outer sleeve 24 is transmitted to the screw rod 23 through the support bearing 21; the thrust bearing 22 is located between the screw rod 23 and the outer sleeve 24, and the outer ring of the thrust bearing 22 is connected to the outer sleeve 24, and the inner ring of the thrust bearing 22 is connected to the screw rod 23, which allows the screw rod 23 and the outer sleeve 24 to rotate relative to each other while transmitting the vertical force of the screw rod 23 to the outer sleeve 24; the inner sleeve 25 is connected to the base 27 through the ball seat 26, so that the inner sleeve 25 can swing or rotate relative to the base 27 around the center of the ball seat 26, and the base 27 is fixedly connected to the support surface to provide reliable support for the leveling support leg 2. The modeling process of the preliminary finite element model based on the above structure and connection method is explained below, as shown in FIG. Figure 5 As shown, Figure 5 A schematic diagram of a flow chart of a modeling method of a third support platform provided in an embodiment of the present invention, based on Figure 1 , Figure 1 Step S101 in the embodiment includes:

[0061] Step S301, simplifying the connection relationship between the support bearing, the thrust bearing and various components into a plurality of spring units.

[0062] That is, the main structure is divided into a finite element model represented by multiple solid units; the bearing connection structure and the connection relationship between components are simplified into spring units, which can characterize the force between the connection stiffness transmission components.

[0063] Combine the following Figure 4 and Figure 6The specific method of simplifying the connection position of the components into spring units is explained. The support bearing and the thrust bearing are simplified into multiple spring units. Specifically, the spring unit in area A simulates the connection relationship of the support bearing 21, and the axial translation and axial rotation degrees of freedom are released. The spring unit in area B simulates the connection relationship of the upper end of the thrust bearing 22, and the axial translation and axial rotation degrees of freedom are released. The spring unit in area C simulates the connection relationship of the lower end of the thrust bearing 22, and the axial rotation degree of freedom is released; the connection position of the screw rod and the sleeve is simplified into multiple spring units, that is, the connection between the screw rod 23 and the internal thread of the inner sleeve 25 is simulated by area D, and the axial rotation degree of freedom is released; the connection position of the ball seat and the base is simplified into a spring unit, that is, the connection between the inner sleeve 25 and the ball seat 26 is simulated by the spring unit in area E, and the rotational freedom around three orthogonal axes is released; the connection position of the base and the support surface is simplified into a spring unit, that is, the spring unit in area F simulates the connection between the base 27 and the support surface.

[0064] Step S302: Divide the support platform, the screw rod, the outer sleeve, the inner sleeve, the ball seat and the base into a plurality of entity units.

[0065] The supporting platform, screw rod, outer sleeve, inner sleeve, ball seat and base are divided into solid units. At the same time, after the division of each solid unit and elastic unit is completed, the parameters of each unit are initialized based on the material and connection form of each part of the actual supporting platform. For example, the torsional stiffness of the elastic unit of the supporting bearing is initialized to 1×10 11 N / mm (Newton per millimeter).

[0066] In some embodiments, Figure 7 As shown, Figure 7 A schematic diagram of a flow chart of a fourth support platform modeling method provided in an embodiment of the present invention, based on Figure 5 ,exist Figure 5 Before step S105 in the step, the modeling method further includes:

[0067] Step S401: Determine the parameters in the initial finite element model whose influence on the local stiffness is greater than the influence threshold as optimization parameters.

[0068] It can be understood that by determining the parameters that have a greater impact on the local stiffness as the optimization parameters, it is possible to optimize the key parameters in the subsequent parameter optimization process, thereby reducing the workload in the parameter optimization process; it should be noted that the optimization parameters can be determined in different ways. For example, the optimization parameters can be determined by simulation tests, that is, each parameter is fine-tuned one by one, and the change in the local stiffness of the system before and after the fine-tuning is observed, and the parameters that cause a significant change in the local stiffness of the system are determined as the optimization parameters; for example, the optimization parameters can be determined by theoretical analysis, that is, the response function of the system is constructed by theoretical analysis, and the partial derivative of the system response function relative to each parameter is calculated, and the parameters whose partial derivatives are greater than the influence threshold are determined as the optimization parameters. Among them, after analysis, the influence of the stiffness parameter of the spring unit on the local stiffness is greater than the influence threshold, so the stiffness of the spring unit is determined as the optimization parameter.

[0069] Correspondingly, Figure 5 Step S105 in the embodiment includes:

[0070] Step S402: Optimize the optimization parameters until the residual of the structural feature quantity calculated based on the model evaluation function reaches a minimum value.

[0071] That is, the stiffness parameters of the elastic unit are optimized until the difference between the simulated modal data and the actual modal data reaches a minimum.

[0072] In some embodiments, Figure 8 As shown, Figure 8 A schematic diagram of a fifth support platform modeling method provided in an embodiment of the present invention, based on Figure 5 ,exist Figure 5 After step S105 in the method, the modeling method further includes:

[0073] Step S501: convert each spring unit into a rigid unit, and determine the degree of freedom of the converted rigid unit based on the stiffness parameters of each spring unit.

[0074] Among them, the degrees of freedom of the spring unit whose stiffness parameter is greater than the stiffness threshold are determined to be fixed, and the degrees of freedom of the spring unit whose stiffness parameter is less than the stiffness threshold are determined to be free. Specifically, the spring unit has stiffness in six degrees of freedom directions, that is, the degrees of freedom of translation along three mutually orthogonal directions and the degrees of freedom of rotation around the axes of the three mutually orthogonal directions. The stiffness parameters of the spring unit in the six degrees of freedom directions are determined respectively. If the stiffness parameter in the direction is greater than the stiffness threshold, the degree of freedom in the direction is determined to be fixed, and if the stiffness parameter in the direction is less than the stiffness threshold, the degree of freedom in the direction is determined to be free. By simplifying the spring unit into a rigid unit based on the stiffness of the spring unit, the optimized finite element model is simplified, and the amount of calculation required for simulation can be further reduced when simulation is performed based on the finite element model.

[0075] Optionally, after the optimization of the support platform model is completed, if the optimized model needs to be modified, and the modification is only to change the structural size or the number of partial structures, there is no need to simplify the bearings and connection positions into spring units again and optimize based on the spring units again and simplify the spring units into rigid units after optimization. The connection positions of the structure with changed size can be directly defined as rigid units, and the connection positions of the newly added structures can be directly defined as rigid units, and the degrees of freedom of the rigid units of the new connection positions are kept consistent with the degrees of freedom of the rigid units of the connection positions of the corresponding positions after simplification in step S501, so that the modeling method of the support platform can be more easily extended to support platforms with different structures.

[0076] An embodiment of the present invention further provides a modeling system of a support platform, which may be a computing device, such as a personal computer, or a computing server. The structure of the modeling system is exemplified below in conjunction with the embodiment.

[0077] In some embodiments, Fig. 9 As shown, the modeling system includes: a simulation unit 100, a storage unit 200 and a data processing unit. The simulation unit 100 is used to calculate and obtain simulated modal data based on the initial finite element model. The simulated modal data includes multiple simulated natural frequencies and simulated vibration modes corresponding to each simulated natural frequency. After obtaining the simulated modal data, the simulation unit 100 transmits the simulated modal data to the storage unit 200 to store the simulated modal data in the storage unit 200; the storage unit 200 is also used to store the actual modal data obtained by performing experiments on the actual support platform using the simulated modal data, and the actual modal data includes multiple actual natural frequencies and actual vibration modes corresponding to each actual natural frequency.

[0078] The data processing unit 300 is used to construct a model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode, and the function can calculate the residual of the structural characteristic quantity; the data processing unit 300 is also used to optimize the parameters of the initial finite element model until the residual of the structural characteristic quantity calculated based on the model evaluation function reaches the minimum value, that is, the data processing unit 300 can adjust and optimize the parameters in the initial finite element model until the difference between the simulated modal data output by the optimized finite element model and the actual modal data is minimized.

[0079] In some embodiments, the data processing unit 300 is also used to calculate the difference between the simulated natural frequency and the actual natural frequency and standardize the difference to obtain a standardized frequency difference; it is also used to calculate a modal confidence criterion based on the simulated vibration shape and the actual vibration shape; it is also used to construct the weighted sum of the standardized frequency difference and the modal confidence criterion as a model evaluation function.

[0080] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A modeling method for a support platform, characterized in that: The modeling method comprises: An initial finite element model is established based on the structure of the actual support platform, and simulated modal data is calculated based on the initial finite element model, wherein the simulated modal data includes a plurality of simulated natural frequencies and simulated vibration shapes corresponding to each of the simulated natural frequencies; Conducting experiments on the actual support platform to obtain actual modal data, wherein the actual modal data includes a plurality of actual natural frequencies and actual vibration modes corresponding to the actual natural frequencies; Constructing a model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode; The parameters of the initial finite element model are optimized until the residual error of the structural characteristic quantity calculated based on the model evaluation function reaches a minimum value.

2. The modeling method according to claim 1, characterized in that: The constructing of the model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode comprises: Calculating a difference between the simulated natural frequency and the actual natural frequency and standardizing the difference to obtain a standardized frequency difference; Calculating a modal confidence criterion based on the simulated vibration mode shape and the actual vibration mode shape; A weighted sum of the normalized frequency difference and the modal confidence criterion is constructed as the model evaluation function.

3. The modeling method according to claim 2, characterized in that: The calculating the difference between the simulated natural frequency and the actual natural frequency comprises: Calculate the difference between the first five orders of the simulated natural frequencies and the first five orders of the actual natural frequencies, wherein the first five orders of the simulated natural frequencies are the first five simulated natural frequencies in a sequence in which the simulated natural frequencies are arranged from small to large, and the first five orders of the actual natural frequencies are the first five actual frequencies in a sequence in which the actual natural frequencies are arranged from small to large; The modal confidence criterion calculated based on the simulated vibration mode and the actual vibration mode comprises: The modal confidence criterion is obtained for the first five orders of the simulated vibration modes and the first five orders of the actual vibration modes, wherein the first five orders of the simulated vibration modes are the simulated vibration modes corresponding to the first five orders of the simulated frequencies, and the first five orders of the actual vibration modes are the actual vibration modes corresponding to the first five orders of the actual frequencies.

4. The modeling method according to any one of claims 1 to 3, characterized in that: The support platform is used to carry optical equipment, and the support platform includes: a load-bearing platform and a leveling support leg, and a plurality of the leveling support legs are arranged at intervals at the bottom of the load-bearing platform to adjust the lifting of the load-bearing platform, wherein the leveling support leg includes: a support bearing, a thrust bearing, a screw rod, an outer sleeve, an inner sleeve, a ball seat and a base, and the initial finite element model established based on the structure of the actual support platform includes: Simplifying the connection relationship between the support bearing and the thrust bearing and various components into a plurality of spring units; The supporting platform, the screw rod, the outer sleeve, the inner sleeve, the ball seat and the base are divided into a plurality of solid units.

5. The modeling method according to claim 4, characterized in that: The method of simplifying the connection relationship between the support bearing and the thrust bearing and various components into a plurality of spring units comprises: Simplifying the support bearing and the thrust bearing into a plurality of spring units; The connection position between the screw rod and the inner sleeve is simplified into a plurality of spring units, the connection position between the ball seat and the base is simplified into a spring unit, and the connection position between the base and the supporting surface is simplified into a spring element.

6. The modeling method according to claim 4, characterized in that: Before optimizing the parameters of the initial finite element model, the modeling method further includes: Determine the parameters in the initial finite element model whose influence on the local stiffness is greater than the influence threshold as optimization parameters, wherein the influence of the stiffness parameter of the spring unit on the local stiffness is greater than the influence threshold, and the stiffness parameter of the spring unit is determined as the optimization parameter; Optimizing the parameters of the initial finite element model until the residual of the structural feature quantity calculated based on the model evaluation function reaches a minimum value includes: The optimization parameters are optimized until the residual error of the structural feature quantity calculated based on the model evaluation function reaches a minimum value.

7. The modeling method according to claim 6, characterized in that: The step of determining the parameters in the initial finite element model whose influence on the local stiffness is greater than the influence threshold as the optimization parameters comprises: A system response function of the initial finite element model is constructed, and a partial derivative of the system response function with respect to each of the parameters is calculated, and a parameter whose partial derivative is greater than the influence threshold is determined as an optimization parameter.

8. The modeling method according to claim 5, characterized in that: After optimizing the parameters of the initial finite element model until the residual of the structural feature quantity calculated based on the model evaluation function reaches a minimum value, the modeling method further includes: Each of the spring units is converted into a rigid unit, and the degree of freedom of the converted rigid unit is determined based on the stiffness parameter of each of the spring units, wherein the degree of freedom of the spring unit whose stiffness parameter is greater than a stiffness threshold is determined to be fixed, and the degree of freedom of the spring unit whose stiffness parameter is less than the stiffness threshold is determined to be free.

9. A modeling system for a support platform, characterized in that: The modeling system comprises: A simulation unit, used for calculating simulated modal data based on an initial finite element model, wherein the simulated modal data includes a plurality of simulated natural frequencies and simulated vibration shapes corresponding to each of the simulated natural frequencies; A storage unit, used to store the simulated modal data, and to store actual modal data obtained by performing experiments on the actual support platform, wherein the actual modal data includes a plurality of actual natural frequencies and actual vibration modes corresponding to the actual natural frequencies; A data processing unit is used to construct a model evaluation function based on the difference between the simulated natural frequency and the actual natural frequency, and the correlation between the simulated vibration mode and the actual vibration mode, and to optimize the parameters of the initial finite element model until the residual of the structural characteristic quantity calculated based on the model evaluation function reaches a minimum value.

10. The modeling system of the support platform according to claim 9, characterized in that: The data processing unit is further used to calculate the difference between the simulated natural frequency and the actual natural frequency and to standardize the difference to obtain a standardized frequency difference; to calculate a modal confidence criterion based on the simulated vibration shape and the actual vibration shape; and to construct a weighted sum of the standardized frequency difference and the modal confidence criterion as the model evaluation function.

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