Spacecraft digital twin modeling method and system

Abstract

The invention relates to the technical field of digital twinning, and particularly discloses a spacecraft digital twinning modeling method and system.The method comprises the steps that a multi-level modeling method is adopted to decompose a spacecraft into a plurality of subsystems and assemblies, and corresponding digital twinning models are constructed respectively; integrating the digital twin models into a complete aircraft model through a data integration algorithm; simulating the attitude characteristics of the aircraft model according to the real-time attitude data of the aircraft model and the number of orbits at the current moment; the attitude of the aircraft model is monitored and analyzed in real time by using machine learning and deep learning algorithms so as to predict and diagnose potential faults and performance degradation problems.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to a spacecraft digital twin modeling method and system. Background Art

[0002] Existing technologies create virtual copies of physical entities to enable real-time monitoring, prediction, and optimization of their performance and status. Through modeling and simulation technology, digital twin models of space vehicles are built in combination with the design parameters, physical characteristics, and environmental data of the vehicle. These models can integrate real-time data from various sensors and systems to simulate the actual operating status of the vehicle. Through core technologies such as complex product model building, information-physical fusion, data collection and transmission, and big data technology, the simulation of space vehicles in virtual space is realized.

[0003] Although existing technologies provide methods for building product models, existing methods may still face challenges in highly complex and sophisticated products such as spacecraft, especially in simulating the extreme environmental adaptability and long-term operational reliability of aircraft. In the space environment, especially under long-distance communication and high-speed motion conditions, existing technologies may not be able to meet the high requirements of real-time and accuracy. In space vehicle applications, how to achieve efficient and accurate information-physical fusion, especially in dynamic environments, is a technical problem that technicians in this field need to solve urgently. Summary of the invention

[0004] To achieve the purpose of the present invention, the present application provides a spacecraft digital twin modeling method, comprising: Step S1: Decomposing the spacecraft into multiple subsystems and components by using a multi-level modeling method, constructing corresponding digital twin models respectively, and integrating the digital twin models into a complete aircraft model by using a data integration algorithm; Step S2: According to the real-time attitude data of the aircraft model and the number of tracks at the current moment, the attitude characteristics of the aircraft model are simulated; Step S3: Using machine learning and deep learning algorithms, the attitude of the aircraft model is monitored and analyzed in real time to predict and diagnose potential failures and performance degradation problems.

[0005] In some specific embodiments, the step S1 includes: performing modal analysis on the structure of the spacecraft based on the on-orbit working state of the spacecraft, and determining the digital twin model according to the following formula: ; In the formula, λi Indicates i The eigenvalue of order, Indicatesi eigenvectors, K represents the stiffness matrix, and M represents the mass matrix of the system.

[0006] In some specific embodiments, in step S2, the simulation result is divided into three-axis stable attitude simulation and spin simulation according to the attitude stabilization mode of the spacecraft.

[0007] In some of the specific embodiments, when three-axis stable attitude simulation is adopted, the Kepler roots at the current epoch and the sidereal time at the current time are calculated by orbit extrapolation based on the semi-major axis, eccentricity, inclination, ascending node right ascension, perigee argument and mean anomaly of the satellite's Kepler orbit elements at a certain time; and the true anomaly is calculated based on the satellite's mean anomaly and eccentricity, thereby determining the simulation result of the spacecraft.

[0008] In some specific embodiments, when spin simulation is used, the attitude matrix of the spacecraft is determined according to the right ascension, declination, nutation, and rotation speed of the spacecraft in an inertial system, as shown below: ; In the formula, s is the current sidereal time, is right ascension, is the declination, is the nutation angle, ω is the rotation speed.

[0009] To achieve the same invention purpose, the present application also provides a spacecraft digital twin modeling system, including: Aircraft model building module: used to decompose the spacecraft into multiple subsystems and components using a multi-level modeling method, build corresponding digital twin models respectively, and integrate the digital twin models into a complete aircraft model through a data integration algorithm; Simulation module: used to simulate the attitude characteristics of the aircraft model according to the real-time attitude data of the aircraft model and the number of tracks at the current moment; Monitoring and analysis module: used to use machine learning and deep learning algorithms to monitor and analyze the attitude of the aircraft model in real time to predict and diagnose potential failures and performance degradation problems.

[0010] In some specific embodiments, the aircraft model construction module is used to: perform modal analysis on the structure of the spacecraft on the on-orbit working state of the spacecraft, and determine the digital twin model according to the following formula: ; In the formula, λi Indicates i The eigenvalue of order, Indicatesi eigenvectors, K represents the stiffness matrix, and M represents the mass matrix of the system.

[0011] In some specific embodiments, the simulation module is used to: divide the simulation result into three-axis stable attitude simulation and spin simulation according to the attitude stabilization mode of the spacecraft.

[0012] In some of the specific embodiments, when three-axis stable attitude simulation is adopted, the Kepler roots at the current epoch and the sidereal time at the current time are calculated by orbit extrapolation based on the semi-major axis, eccentricity, inclination, ascending node right ascension, perigee argument and mean anomaly of the satellite's Kepler orbit elements at a certain time; and the true anomaly is calculated based on the satellite's mean anomaly and eccentricity, thereby determining the simulation result of the spacecraft.

[0013] In some specific embodiments, when spin simulation is used, the attitude matrix of the spacecraft is determined according to the right ascension, declination, nutation, and rotation speed of the spacecraft in an inertial system, as shown below: ; In the formula, s is the current sidereal time, is right ascension, is the declination, is the nutation angle, ω is the rotation speed.

[0014] Beneficial effects of the above technical solution: The present invention can improve the accuracy of the digital twin model by proposing a high-precision multi-level modeling method and introducing finer-grained simulation of physical and environmental parameters at the subsystem and component levels. This enables the model to more accurately reflect the actual state and performance of the spacecraft, thereby providing more reliable decision support for design, testing and operation. Combined with attitude simulation technology and methods for dynamically adjusting model parameters, the digital twin model can better adapt to the complex and changeable space environment. By developing an efficient data synchronization mechanism and using machine learning algorithms for data preprocessing, real-time processing and synchronization of high-dimensional data are achieved. This ensures that the digital twin model can reflect the latest attitude of the spacecraft in a timely and accurate manner. Using machine learning and deep learning algorithms, the accuracy and efficiency of fault prediction and diagnosis are improved. The detailed and accurate digital twin model provided by the present invention provides a powerful tool for the design and improvement of aircraft, which helps to promote technological innovation and performance optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A schematic diagram of a flow chart of a spacecraft digital twin modeling method provided by an embodiment of the present invention; Figure 2 A schematic structural diagram of a spacecraft digital twin modeling system provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0018] Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar symbols throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0019] Embodiment 1

[0020] An embodiment of the present invention provides a method for modeling a digital twin of a spacecraft, referring to Figure 1 As shown, including: Step S1: Use a multi-level modeling method to decompose the spacecraft into multiple subsystems and components, build corresponding digital twin models for each subsystem, and integrate the digital twin models into a complete aircraft model through a data integration algorithm.

[0021] In a specific embodiment of the present invention, a structural model is first established. For each component in the block diagram, a motion differential equation is established using Newton's second law: ; Where m1, m2, and m3 represent the masses of different mass blocks, k1, k2, and k3 represent different stiffness coefficients, x1, x2, and x3 represent the displacements of different mass points, and F1, F2, and F3 represent the forces on different mass points.

[0022] Converting the coupled second-order linear system represented by the above equation into a matrix form, we can see that the mass of each component is decoupled, while the stiffness is coupled.

[0023] ; ; Where M is the mass matrix of the system, K is the stiffness matrix, F is the load matrix, x is the displacement vector, is the acceleration vector.

[0024] The modal analysis of the structure is carried out for the on-orbit working state of the spacecraft. In order to obtain the dynamic characteristics of the structure, it is also necessary to carry out a steady-state response analysis. Assuming that the structure is subjected to forced motion under simple harmonic excitation, the force is in the form of: ; ; In the formula, m is the mass matrix, j is the rotation or oscillation, w is the angular frequency of the excitation, x i is the displacement response of the structure, e jwt ≠0, j 2 =-1, the coefficients in the above equations are not all zero, that is, there are non-zero solutions, so the value of the coefficient determinant is zero, that is, the following formula is obtained: ; In the formula, λi represents the i-th order eigenvalue, Indicates i feature vectors.

[0025] The above formula can be used to build a high-precision digital twin model of the space vehicle.

[0026] Step S2: simulating the attitude characteristics of the aircraft model according to the real-time attitude data of the aircraft model and the number of orbits at the current moment.

[0027] In a specific embodiment of the present invention, in step S2, the simulation result is divided into three-axis stable attitude simulation and spin simulation according to the attitude stabilization mode of the spacecraft.

[0028] Specifically, the application mission of a spacecraft requires that the attitude of the spacecraft maintain high-precision orientation in space, or that the attitude of the spacecraft be maneuvered in space according to predetermined requirements. The attitude motion of a spacecraft is the rotational motion of the spacecraft around its own center of mass, and is also the angular motion of the spacecraft. Using real-time attitude data and the orbital roots at the current moment, the attitude characteristics of a spacecraft in space can be simulated.

[0029] In a specific embodiment of the present invention, when three-axis stable attitude simulation is adopted, the Kepler roots at the current epoch and the sidereal time at the current moment are calculated by orbit extrapolation based on the semi-major axis, eccentricity, inclination, ascending node right ascension, perigee argument and mean anomaly of the satellite's Kepler orbit elements at a certain moment; and the true anomaly is calculated based on the satellite's mean anomaly and eccentricity, thereby determining the simulation result of the spacecraft.

[0030] In a specific embodiment of the present invention, when spin simulation is used, the attitude matrix of the spacecraft is determined according to the right ascension, declination, nutation, and rotation speed of the spacecraft in an inertial system, as shown below: ; In the formula, s is the current sidereal time, is right ascension, is the declination, is the nutation angle, ω is the rotation speed.

[0031] Specifically, for a three-axis stabilized spacecraft, its attitude simulation algorithm is: according to the Kepler orbit elements a, e, i, Ω, ω, M (representing the semi-major axis, eccentricity, inclination, right ascension of the ascending node, argument of perigee, and mean anomaly, respectively, where all angles are in radians) of the satellite at a certain moment, the Kepler elements at the current epoch are calculated by orbit extrapolation, the sidereal time s at that moment is calculated, and the true anomaly f is calculated according to the mean anomaly M and eccentricity e. Without considering the influence of the interference torque, the attitude (default attitude, in the body coordinate system, the forward direction is specified as the X axis, and the Z axis points to the center of the earth) model matrix is ​​calculated as follows, namely: ; If the three Euler angles φ, θ, ψ provided by the measurement and control data are used, then: ; The transformation matrix of the current attitude of the satellite model is: ; If the three rotation speeds (ω x ,ω y ,ω z ), time t and initial value of Euler angle ( ), then calculate the Euler angles (φ, θ, ψ) at the current moment.

[0032] ; in: ; ; ; set up , then the Euler angle at the current moment is: .

[0033] For a spinning spacecraft, the attitude simulation algorithm is: in view of the characteristics of a spinning spacecraft, the measurement and control data often provide the right ascension, declination, nutation and rotation speed data of the spacecraft in the inertial system.

[0034] Assume the current sidereal time is s , right ascension is , the declination is , the nutation angle is , the speed is ω , then the attitude matrix of the spinning spacecraft is: ; If we consider the state of a spinning spacecraft during derotation, that is, the antenna part points to the earth and does not rotate with the rotation of the body, assuming that the antenna points in the same direction as the X-axis of the body, and the current position of the spacecraft is: longitude β, then the attitude matrix T of the antenna part during derotation is 消 , calculated as follows: ; First, calculate the attitude matrix of the antenna that does not rotate with the rotation of the body. Based on this, calculate the angle between the projection of the line vector connecting the earth and the body on the XY plane and the X-axis of the body. .

[0035] Assume that the current position of the spacecraft is E (x, y, z), and the position vector of the earth in the body coordinate system is P (P x、 P y、 P z )for: ; The angle is: ; Antenna derotation matrix T 消 for: ; According to the above algorithm, the attitude data of the spacecraft can be better obtained, and the calculated attitude data can be combined with the scene to display it.

[0036] Step S3: Using machine learning and deep learning algorithms, the attitude of the aircraft model is monitored and analyzed in real time to predict and diagnose potential failures and performance degradation problems.

[0037] The present invention aims to provide a more efficient and accurate spacecraft digital twin modeling method and system to support the full life cycle management of spacecraft design, testing, operation and maintenance, and propose a more advanced model building method to more accurately simulate the behavior and state of spacecraft in various environments. It also improves the accuracy and real-time performance of the spacecraft digital twin model, as well as its adaptability in complex space environments. By proposing an attitude simulation method and data integration technology, the present invention can more accurately simulate and predict the attitude and performance of spacecraft, and achieve more effective fault diagnosis and preventive maintenance.

[0038] Embodiment 2 An embodiment of the present invention provides a spacecraft digital twin modeling system, referring to Figure 2 As shown, including: Aircraft model construction module 10: used to decompose the spacecraft into multiple subsystems and components using a multi-level modeling method, respectively construct corresponding digital twin models, and integrate the digital twin models into a complete aircraft model through a data integration algorithm; Simulation module 20: for simulating the attitude characteristics of the aircraft model according to the real-time attitude data of the aircraft model and the number of tracks at the current moment; Monitoring and analysis module 30: used to use machine learning and deep learning algorithms to monitor and analyze the attitude of the aircraft model in real time to predict and diagnose potential failures and performance degradation problems.

[0039] In a specific embodiment of the present invention, the aircraft model construction module 10 is used to: perform modal analysis on the structure of the spacecraft for the on-orbit working state of the spacecraft, and determine the digital twin model according to the following formula: ; In the formula, λi represents the i-th order eigenvalue, Indicates i feature vectors.

[0040] In a specific embodiment of the present invention, the simulation module 20 is used to divide the simulation result into three-axis stable attitude simulation and spin simulation according to the attitude stabilization mode of the spacecraft.

[0041] In a specific embodiment of the present invention, when three-axis stable attitude simulation is adopted, the Kepler roots at the current epoch and the sidereal time at the current moment are calculated by orbit extrapolation based on the semi-major axis, eccentricity, inclination, ascending node right ascension, perigee argument and mean anomaly of the satellite's Kepler orbit elements at a certain moment; and the true anomaly is calculated based on the satellite's mean anomaly and eccentricity, thereby determining the simulation result of the spacecraft.

[0042] In a specific embodiment of the present invention, when spin simulation is used, the attitude matrix of the spacecraft is determined according to the right ascension, declination, nutation, and rotation speed of the spacecraft in an inertial system, as shown below: ; In the formula, s is the current sidereal time, is right ascension, is the declination, is the nutation angle, ω is the rotation speed.

[0043] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0044] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referenced to each other. The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing terminal device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes. Although the preferred embodiments of the embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the attached claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention. Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or terminal device including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0045] The method and device provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

[0046] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", "one specific embodiment" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0047] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A spacecraft digital twin modeling method, characterized in that: include: Step S1: Decomposing the spacecraft into multiple subsystems and components by using a multi-level modeling method, constructing corresponding digital twin models respectively, and integrating the digital twin models into a complete aircraft model by using a data integration algorithm; Step S2: According to the real-time attitude data of the aircraft model and the number of tracks at the current moment, the attitude characteristics of the aircraft model are simulated; Step S3: Using machine learning and deep learning algorithms, the attitude of the aircraft model is monitored and analyzed in real time to predict and diagnose potential failures and performance degradation problems.

2. The spacecraft digital twin modeling method according to claim 1, characterized in that: The step S1 includes: performing modal analysis on the structure of the spacecraft based on the on-orbit working state of the spacecraft, and determining the digital twin model according to the following formula: ； In the formula, λi Indicates i The eigenvalue of order, Indicates i eigenvectors, K represents the stiffness matrix, and M represents the mass matrix of the system.

3. The spacecraft digital twin modeling method according to claim 1, characterized in that: In the step S2, the simulation result is divided into three-axis stable attitude simulation and spin simulation according to the attitude stabilization mode of the spacecraft.

4. The spacecraft digital twin modeling method according to claim 3, characterized in that: When three-axis stable attitude simulation is adopted, the Kepler roots at the current epoch and the sidereal time at the current moment are calculated by orbit extrapolation based on the semi-major axis, eccentricity, inclination, ascending node right ascension, perigee argument and mean anomaly of the satellite's Kepler orbital elements at a certain moment; and the true anomaly is calculated based on the satellite's mean anomaly and eccentricity, thereby determining the simulation result of the spacecraft.

5. The spacecraft digital twin modeling method according to claim 3, characterized in that: When spin simulation is used, the attitude matrix of the spacecraft is determined according to the right ascension, declination, nutation, and rotation speed of the spacecraft in the inertial system, as shown below: ； In the formula, s is the current sidereal time, is right ascension, is the declination, is the nutation angle, ω is the rotation speed.

6. A spacecraft digital twin modeling system, characterized in that: include: Aircraft model building module: used to decompose the spacecraft into multiple subsystems and components using a multi-level modeling method, build corresponding digital twin models respectively, and integrate the digital twin models into a complete aircraft model through a data integration algorithm; Simulation module: used to simulate the attitude characteristics of the aircraft model according to the real-time attitude data of the aircraft model and the number of tracks at the current moment; Monitoring and analysis module: used to use machine learning and deep learning algorithms to monitor and analyze the attitude of the aircraft model in real time to predict and diagnose potential failures and performance degradation problems.

7. The spacecraft digital twin modeling system according to claim 6, characterized in that: The aircraft model building module is used to: perform modal analysis on the structure of the spacecraft for the on-orbit working state of the spacecraft, and determine the digital twin model according to the following formula: ； In the formula, λi Indicates i The eigenvalue of order, Indicates i eigenvectors, K represents the stiffness matrix, and M represents the mass matrix of the system.

8. The spacecraft digital twin modeling system according to claim 6, characterized in that: The simulation module is used for: the simulation result is divided into three-axis stable attitude simulation and spin simulation according to the attitude stabilization mode of the spacecraft.

9. The spacecraft digital twin modeling system according to claim 8, characterized in that: When three-axis stable attitude simulation is adopted, the Kepler roots at the current epoch and the sidereal time at the current moment are calculated by orbit extrapolation based on the semi-major axis, eccentricity, inclination, ascending node right ascension, perigee argument and mean anomaly of the satellite's Kepler orbital elements at a certain moment; and the true anomaly is calculated based on the satellite's mean anomaly and eccentricity, thereby determining the simulation result of the spacecraft.

10. The spacecraft digital twin modeling system according to claim 8, characterized in that: When spin simulation is used, the attitude matrix of the spacecraft is determined according to the right ascension, declination, nutation, and rotation speed of the spacecraft in the inertial system, as shown below: ； In the formula, s is the current sidereal time, is right ascension, is the declination, is the nutation angle, ω is the rotation speed.

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