System-level optimization method for dynamics parameters of micro-vibration isolator of optical remote sensing satellite

Abstract

The present application relates to optical remote sensing satellite micro-vibration isolator dynamics parameter system level optimization method, belongs to spacecraft vibration control technical field;Establish the finite element model of the whole satellite;Modal analysis is carried out to the isolation system, and the function relation of the natural frequency of the isolation system and the axial stiffness k w , lateral stiffness k v Is fitted;The constraint condition of natural frequency f 横向 And f 纵向 Is set;The function relation of the angular displacement of high-resolution camera and the axial stiffness k w , lateral stiffness k v Of the isolator is fitted;The function relation of the angular displacement of the main components and the axial stiffness k w , lateral stiffness k v Of the isolator is fitted;The objective function F is constructed;With the constraint condition of lateral natural frequency f 横向 And longitudinal natural frequency f 纵向 As constraint, the objective function F is solved by nonlinear optimization using quasi-newton method, and the lateral natural frequency f 横向 , longitudinal natural frequency f 纵向 Of the optimized isolation system;The present application controls micro-vibration from the system level, and gives the specific parameter requirement of isolator design and development.

Description

Technical Field

[0001] This invention belongs to the field of spacecraft vibration control technology, and relates to a system-level optimization method for dynamic parameters of micro-vibration isolators for optical remote sensing satellites. Background Technology

[0002] With the development of aerospace technology, high-precision spacecraft, represented by sub-meter level optical remote sensing satellites, are increasingly used in fields such as Earth observation, laser communication, and deep space exploration, and their precision is also getting higher and higher. Micro-vibration has become one of the key factors affecting the imaging quality and other performance of high-precision spacecraft.

[0003] my country's high-precision spacecraft development is rapid, but it lacks systematic theoretical guidance in micro-vibration suppression. The design and development of vibration isolators mainly rely on an empirical and experimental approach. Based on vibration isolators used in launched satellites, multiple test pieces with similar parameters are produced, and a large number of tests are conducted to select the vibration isolator with better isolation performance. This method mainly has the following problems:

[0004] (1) This method can only be carried out at the single-machine level. After being installed on the whole satellite, its frequency may be coupled with the satellite structure frequency or the frequency of large equipment, resulting in a significant reduction in the vibration isolation effect.

[0005] (2) This method requires the production of a large number of test pieces, which is very costly and time-consuming, and may affect the development progress of the entire satellite.

[0006] (3) Although this method produces a large number of test pieces, it is impossible to determine whether the optimal solution can be obtained due to the lack of systematic theoretical guidance;

[0007] (4) This method has poor scalability and inheritance. The screening process must be completely repeated for different satellites and different vibration disturbance devices. Summary of the Invention

[0008] The technical problem solved by this invention is to overcome the shortcomings of the prior art and propose a system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites. This method controls micro-vibration at the system level and provides specific parameter requirements for the design and development of the isolator. This is of great significance for saving manpower and financial resources, ensuring the progress of satellite development, and improving vibration isolation efficiency.

[0009] The solution of the present invention is:

[0010] System-level optimization methods for dynamic parameters of micro-vibration isolators for optical remote sensing satellites include:

[0011] Establish a finite element model of the entire satellite; the entire satellite includes the satellite body, high-resolution camera, and vibration isolators; define the axial stiffness of the vibration isolator finite element model as... Horizontal stiffness is ;

[0012] Define the high-resolution camera as the object to be isolated; the vibration isolation system consists of the vibration isolator and the object to be isolated; perform modal analysis on the vibration isolation system to obtain its transverse natural frequencies. Longitudinal natural frequency And fit the transverse natural frequency of the vibration isolation system. With axial stiffness lateral stiffness The functional relationship; fitting the longitudinal natural frequency. With axial stiffness lateral stiffness The functional relationship;

[0013] Setting the transverse natural frequency and longitudinal natural frequency Constraints;

[0014] Transient response analysis was performed on the whole satellite finite element model to obtain the angular displacement of the high-resolution camera that affects imaging quality. The relationship between the angular displacement of the high-resolution camera and the axial stiffness of the vibration isolator was then obtained through fitting. lateral stiffness The functional relationship between the components was determined; the main components affecting the imaging quality of the high-resolution camera were extracted through transient response analysis; and the angular displacement of the main components and the axial stiffness of the vibration isolator were fitted. lateral stiffness The functional relationship;

[0015] The angular displacement of the main components and the axial stiffness of the vibration isolator are compared. lateral stiffness Substituting the functional relationship into the linear optical system model, we obtain the image shift caused by vibration and the axial stiffness of the vibration isolator. lateral stiffness The functional relationship between the imaging image shift and the axial stiffness of the vibration isolator; and based on the relationship between the imaging image shift and the axial stiffness of the vibration isolator. lateral stiffness The functional relationship is used to construct the objective function. ;

[0016] With transverse natural frequency and longitudinal natural frequency The constraints are defined as follows: The quasi-Newton method is used to evaluate the objective function. By performing nonlinear optimization, the transverse natural frequency of the optimized vibration isolation system is obtained. Longitudinal natural frequency This means achieving minimal image shift and optimal image quality.

[0017] In the above-mentioned system-level optimization method for the dynamic parameters of the micro-vibration isolator of the optical remote sensing satellite, the whole satellite finite element model adopts free boundary; among them, the finite element model of the isolator adopts BUSH element modeling; and the high-resolution camera and the satellite body adopt plate and shell element modeling.

[0018] In the aforementioned system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites, a nonlinear least squares method is used to fit the transverse natural frequency of the isolation system. With axial stiffness Horizontal stiffness is The functional relationship is obtained; the longitudinal natural frequency is fitted using the nonlinear least squares method. With axial stiffness Horizontal stiffness is The functional relationship.

[0019] In the aforementioned system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites, the nonlinear least squares method is implemented using Matlab.

[0020] In the aforementioned system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites, the transverse natural frequency... and longitudinal natural frequency The configuration requirement is: avoid the entire satellite's base frequency. Launch vehicle natural frequency And the natural frequency of the object being isolated, and to avoid the frequency. The multiple is used as the benchmark.

[0021] In the aforementioned system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites, the transverse natural frequency... The constraints are:

[0022]

[0023] In the formula, The inherent frequency of the launch vehicle carrying the entire satellite;

[0024] This is the base frequency of the entire satellite.

[0025] In the aforementioned system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites, the longitudinal natural frequency... The constraints are:

[0026]

[0027] In the formula, The base frequency of the entire satellite;

[0028] This is the inherent frequency of the high-resolution camera.

[0029] In the aforementioned system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites, a nonlinear least squares method is used to fit the angular displacement of the high-resolution camera and the axial stiffness of the isolator. lateral stiffness The functional relationship; the nonlinear least squares method is implemented using Matlab.

[0030] In the aforementioned system-level optimization method for the dynamic parameters of the micro-vibration isolator for optical remote sensing satellites, the main components affecting imaging quality inside the high-resolution camera are the secondary mirror and the primary mirror. The nonlinear least squares method is used to fit the angular displacement of the secondary mirror and the axial stiffness of the isolator, respectively. lateral stiffness The functional relationship between the primary mirror angular displacement and the axial stiffness of the vibration isolator. lateral stiffness The functional relationship.

[0031] In the aforementioned system-level optimization method for the dynamic parameters of micro-vibration isolators for optical remote sensing satellites, the objective function is... for:

[0032]

[0033] In the formula, For integration, shift to the image;

[0034] For linear array image shifting;

[0035] This represents the maximum value of the integral towards the image, i.e., the number of pixels that the integral towards the image cannot exceed.

[0036] The advantages of this invention compared to the prior art are:

[0037] (1) The present invention provides a method for optimizing the dynamic parameters of a vibration isolator at the system level. This method can take into account the frequency isolation between the vibration isolation system and the entire satellite, the carrier, and the sensitive load, and avoid frequency coupling amplification.

[0038] (2) This invention considers the optimization of the dynamic parameters of the vibration isolator at the system level, taking into account the satellite structural subsystem, optical subsystem and control subsystem;

[0039] (3) This invention can provide specific parameter requirements for the design and development of vibration isolators. Compared with the previous experience and test methods, it is of great significance for saving manpower and financial resources, ensuring the progress of satellite development and improving vibration isolation efficiency. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating the system-level optimization of dynamic parameters for the optical remote sensing satellite micro-vibration isolator of this invention. Detailed Implementation

[0041] The present invention will be further described below with reference to the embodiments.

[0042] This invention provides a system-level optimization method for the dynamic parameters of a micro-vibration isolator for optical remote sensing satellites. It can consider the frequency isolation between the vibration isolation system and the entire satellite, launch vehicle, and sensitive loads, avoiding frequency coupling amplification. It considers the optimization of the isolator's dynamic parameters at the system level, taking into account the satellite's structural subsystem, optical subsystem, and control subsystem. It can also provide specific parameter requirements for the design and development of the isolator. Compared with the previous experience-based and experimental methods, this method is of great significance for saving manpower and financial resources, ensuring the satellite development schedule, and improving vibration isolation efficiency.

[0043] System-level optimization methods for dynamic parameters of micro-vibration isolators for optical remote sensing satellites, such as... Figure 1 As shown, the specific steps include the following:

[0044] A finite element model of the entire satellite is established; the entire satellite includes the satellite body, the high-resolution camera, and the vibration isolator; the finite element model of the entire satellite adopts free boundary conditions; among them, the vibration isolator finite element model uses BUSH elements; the high-resolution camera and the satellite body are modeled using plate and shell elements. The axial stiffness of the vibration isolator finite element model is defined as... Horizontal stiffness is .

[0045] Define the high-resolution camera as the object to be isolated; the vibration isolation system consists of the vibration isolator and the object to be isolated; perform modal analysis on the vibration isolation system to obtain its transverse natural frequencies. Longitudinal natural frequency And fit the transverse natural frequency of the vibration isolation system. With axial stiffness lateral stiffness The functional relationship; fitting the longitudinal natural frequency. With axial stiffness lateral stiffness The functional relationship.

[0046] This invention uses the nonlinear least squares method to fit the transverse natural frequency of the vibration isolation system. With axial stiffness Horizontal stiffness is The functional relationship is obtained; the longitudinal natural frequency is fitted using the nonlinear least squares method. With axial stiffness Horizontal stiffness is The functional relationship is shown. The nonlinear least squares method is implemented using Matlab.

[0047] The transverse natural frequency is set based on the frequencies of the vibration isolation system, the entire satellite, and large onboard equipment (equipment exceeding 10% of the total satellite mass). and longitudinal natural frequency Constraints. Transverse natural frequency. and longitudinal natural frequency The configuration requirement is: avoid the entire satellite's base frequency. Launch vehicle natural frequency And the natural frequency of the object being isolated, and to avoid the frequency. The multiple is used as the benchmark.

[0048] Specifically, transverse natural frequency The constraints are:

[0049]

[0050] In the formula, The inherent frequency of the launch vehicle carrying the entire satellite;

[0051] This is the base frequency of the entire satellite.

[0052] Longitudinal natural frequency The constraints are:

[0053]

[0054] In the formula, The base frequency of the entire satellite;

[0055] This is the inherent frequency of the high-resolution camera.

[0056] Transient response analysis was performed on the whole satellite finite element model to obtain the angular displacement of the high-resolution camera that affects imaging quality. The relationship between the angular displacement of the high-resolution camera and the axial stiffness of the vibration isolator was then obtained through fitting. lateral stiffness The functional relationship between the high-resolution camera angular displacement and the vibration isolator axial stiffness is fitted using the nonlinear least squares method. lateral stiffness The functional relationship was determined; the nonlinear least squares method was implemented using Matlab. Transient response analysis was used to extract the main components inside the high-resolution camera that affect image quality; and the angular displacement of the main components was fitted to the axial stiffness of the vibration isolator. lateral stiffness The functional relationship between the secondary mirror and the primary mirror is used. The main components affecting image quality inside a high-resolution camera are the secondary mirror and the primary mirror. The nonlinear least squares method is used to fit the angular displacement of the secondary mirror and the axial stiffness of the vibration isolator. lateral stiffness The functional relationship between the primary mirror angular displacement and the axial stiffness of the vibration isolator. lateral stiffness The functional relationship should generally include a constant term, a linear term, a quadratic term, and a cross term.

[0057] The angular displacement of the main components and the axial stiffness of the vibration isolator are compared. lateral stiffness Substituting the functional relationship into the linear optical system model, we obtain the image shift caused by vibration and the axial stiffness of the vibration isolator. lateral stiffness The functional relationship between the imaging image shift and the axial stiffness of the vibration isolator; and based on the relationship between the imaging image shift and the axial stiffness of the vibration isolator. lateral stiffness The functional relationship is used to construct the objective function. Objective function for:

[0058]

[0059] In the formula, For integration, shift to the image;

[0060] For linear array image shifting;

[0061] This represents the maximum value of the integral towards the image, i.e., the number of pixels that the integral towards the image cannot exceed.

[0062] For example, a satellite requires that the linear array image shift not exceed 1 pixel and the integral image shift not exceed 0.35 pixels. For this satellite, the objective function is defined as " ".

[0063] With transverse natural frequency and longitudinal natural frequency The constraints are defined as follows: The quasi-Newton method is used to evaluate the objective function. By performing nonlinear optimization, the transverse natural frequency of the optimized vibration isolation system is obtained. Longitudinal natural frequency This means achieving minimal image shift and optimal image quality.

[0064] This invention first establishes finite element models of the entire satellite and the vibration isolators based on the satellite structure; then, it performs modal analysis on the vibration isolation system, fitting the natural frequencies of the vibration isolation system and the lateral stiffness of the vibration isolators. and axial stiffness The functional relationship between the vibration isolation system and the entire satellite and its large onboard equipment was determined; and the constraints were obtained based on the frequency coupling analysis results. Then, transient response analysis of the entire satellite was performed, and the angular displacements of the secondary and primary mirrors and the lateral stiffness of the vibration isolator were fitted. and axial stiffness The functional relationship between the image shift and the vibration isolator parameters is obtained by substituting the relationship into the optical system model and constructing the objective function. Finally, nonlinear optimization is performed based on the objective function and constraints to obtain the optimized vibration isolator parameters.

[0065] This invention is a system-level method for optimizing the dynamic parameters of vibration isolators. This method can consider the frequency isolation between the vibration isolation system and the entire satellite, launch vehicle, and sensitive loads, avoiding frequency coupling amplification. It can provide specific parameter requirements for the design and development of vibration isolators. Compared with the previous experience-based and experimental methods, this method is of great significance for saving manpower and financial resources, ensuring the progress of satellite development, and improving vibration isolation efficiency.

[0066] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.

Claims

1. A system-level optimization method for dynamic parameters of micro-vibration isolators for optical remote sensing satellites, characterized by: include: Establish a finite element model of the entire satellite; the entire satellite includes the satellite body, high-resolution camera, and vibration isolators; Define the axial stiffness of the finite element model of the vibration isolator as k. w The lateral stiffness is k v ; Define the high-resolution camera as the object to be isolated; the vibration isolation system consists of the vibration isolator and the object to be isolated; perform modal analysis on the vibration isolation system to obtain the transverse natural frequency f of the vibration isolation system. 横向 Longitudinal natural frequency f 纵向 And fit the transverse natural frequency f of the vibration isolation system. 横向 With axial stiffness k w lateral stiffness k v The functional relationship; fitting the longitudinal natural frequency f 纵向 With axial stiffness k w lateral stiffness k v The functional relationship; Set the transverse natural frequency f 横向 and longitudinal natural frequency f 纵向 Constraints; Transient response analysis was performed on the whole satellite finite element model to obtain the angular displacement of the high-resolution camera that affects imaging quality. The relationship between the angular displacement of the high-resolution camera and the axial stiffness k of the vibration isolator was then obtained through fitting. w lateral stiffness k v The functional relationship between the components was determined; the main components affecting the imaging quality of the high-resolution camera were extracted through transient response analysis; and the angular displacement of the main components and the axial stiffness k of the vibration isolator were fitted. w lateral stiffness k v The functional relationship; The angular displacement of the main components is compared with the axial stiffness k of the vibration isolator. w lateral stiffness k v Substituting the functional relationship into the linear optical system model, we obtain the image shift caused by vibration and the axial stiffness k of the vibration isolator. w lateral stiffness k v The functional relationship between the imaging image shift and the axial stiffness k of the vibration isolator; and based on the relationship between the imaging image shift and the axial stiffness k of the vibration isolator. w lateral stiffness k v Based on the functional relationships, construct the objective function F; With transverse natural frequency f 横向 and longitudinal natural frequency f 纵向 Given the constraints, the objective function F is solved nonlinearly using the quasi-Newton method to obtain the lateral natural frequency f of the optimized vibration isolation system. 横向 Longitudinal natural frequency f 纵向 This means achieving minimal image shift and optimal image quality.

2. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 1, characterized in that: The whole satellite finite element model adopts free boundary; the vibration isolator finite element model adopts BUSH element modeling; the high-resolution camera and satellite body adopt plate and shell element modeling.

3. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 1, characterized in that: The transverse natural frequency f of the vibration isolation system is fitted using the nonlinear least squares method. 横向 With axial stiffness k w The lateral stiffness is k v The functional relationship is obtained; the longitudinal natural frequency f is fitted using the nonlinear least squares method. 纵向 With axial stiffness k w The lateral stiffness is k v The functional relationship.

4. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 3, characterized in that: The nonlinear least squares method is implemented using Matlab.

5. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 1, characterized in that: Transverse natural frequency f 横向 and longitudinal natural frequency f 纵向 The configuration requirement is: avoid the entire satellite's base frequency f. 整星基频 The natural frequency f of the launch vehicle 运载火箭固有频率 And the natural frequency of the object being isolated, and to avoid the frequency. The multiple is used as the benchmark.

6. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 5, characterized in that: Transverse natural frequency f 横向 The constraints are: In the formula, f 运载火箭固有频率 The inherent frequency of the launch vehicle carrying the entire satellite; f 整星基频 This is the base frequency of the entire satellite.

7. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 6, characterized in that: Longitudinal natural frequency f 纵向 The constraints are: In the formula, f 整星基频 The base frequency of the entire satellite; f 高分相机固有频率 This is the inherent frequency of the high-resolution camera.

8. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 1, characterized in that: The angular displacement of the high-resolution camera and the axial stiffness k of the vibration isolator were fitted using the nonlinear least squares method. w lateral stiffness k v The functional relationship; the nonlinear least squares method is implemented using Matlab.

9. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 1, characterized in that: The main components affecting image quality inside a high-resolution camera are the secondary mirror and the primary mirror; the nonlinear least squares method is used to fit the angular displacement of the secondary mirror and the axial stiffness k of the vibration isolator. w lateral stiffness k v The functional relationship between the primary mirror angular displacement and the axial stiffness k of the vibration isolator. w lateral stiffness k v The functional relationship.

10. The system-level optimization method for dynamic parameters of optical remote sensing satellite micro-vibration isolators according to claim 1, characterized in that: The objective function F is: F=-[(d max ×d-d imX ) 2 +(d-d imY ) 2 ] In the formula, d imX For integration, the image is shifted; d imY For linear array image shift; d max This represents the maximum value of the integral towards the image, i.e., the number of pixels that the integral towards the image cannot exceed.

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