Spacecraft assembly state model construction method and system

Abstract

The application provides a spacecraft assembly state model construction method and system, and relates to the technical field of model construction. The specific steps include: discretizing a three-dimensional assembly geometric model into a global standard voxel grid and identifying constraint source components, constructing a three-dimensional anisotropic power density voxel field model, generating a sensitive target three-dimensional space Boolean mask and performing space superposition mapping to obtain effective voxel nodes, calculating the spatial distribution extreme value and spatial cumulative total value of the radiation received power and judging the local state and the overall state, and encapsulating the power density voxel field and the double state into a model-attached non-entity physical constraint attribute to complete the spacecraft assembly state model construction. The application remedies the defects of existing models that only display static geometry, converts space into a voxel grid carrying physical values, identifies the local state and the overall state through double-dimensional comparison, and constructs an assembly state model with non-entity physical constraint attributes.

Description

Technical Field

[0001] This invention relates to the field of model building technology, specifically to a method and system for building spacecraft assembly state models. Background Technology

[0002] With the development of aerospace technology, spacecraft assembly processes are evolving towards digital assembly and digital twins. Three-dimensional assembly geometric models, as the fundamental data carrier, have been widely used in geometric collision avoidance inspection, assembly path planning, and process simulation. To support precise assembly and state verification, constructing dynamic assembly state models to characterize the process characteristics and spatial topological relationships of each stage has become an important means of identifying design risks in advance in virtual space and guiding on-site physical assembly.

[0003] In the prior art, patent document CN118691748A discloses a method and apparatus for constructing a spacecraft assembly state model. This method associates spacecraft product information with its 3D model, extracts information from a product state table or comparison table, and determines the model transformation rules and the product's effective results. Subsequently, the model state is adjusted based on the effective results; for example, uninstalled component nodes are hidden, and the appearance transformation rules for components that are effective or have different states are changed to convert them to different configuration states. Finally, the model is constructed based on the above rules and states, achieving a 3D visualization of the assembly state.

[0004] However, the three-dimensional assembly geometric models of spacecraft constructed using the aforementioned technologies can only characterize the static geometric forms and discrete assembly attributes of components, limited to visibility control and visual rendering in geometric space. Constraint source components in the actual assembly layout, such as antennas, emit electromagnetic or thermal radiation outwards in three-dimensional space, forming complex non-physical constraint fields. Simultaneously, the spacecraft interior is densely packed with sensitive targets highly sensitive to electromagnetic or thermal environments, such as star sensors and high-precision optical payloads. Once exposed to excessive radiation fields, these sensitive targets are highly susceptible to point breakdown or thermal overload failure. Existing technologies lack the ability to discretize and extrapolate the distribution patterns of physical fields, failing to map the non-physical environment into the assembly model. This prevents the quantitative extraction of the power spatial distribution when the radiation field penetrates the location occupied by sensitive targets, thus hindering the identification of local or overall limit exceedance risks caused by interference from non-physical fields. This results in a technical blind spot in the verification of the assembly state model at the physical constraint level.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for constructing a spacecraft assembly state model, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: The method for constructing a spacecraft assembly state model includes the following specific steps: The three-dimensional assembly geometry model of the spacecraft is obtained, the global assembly space covered by the three-dimensional assembly geometry model is discretized into a global standard voxel mesh, the constraint source components with radiation boundary function are identified, and their radiation energy, radiation emission pointing normal vector of each radiation surface and the three-dimensional coordinates of the constraint source are extracted. By introducing the dual constraints of radiation propagation spatial distance attenuation law and radiation emission azimuth anisotropic angle attenuation, the radiation power density of each voxel node in the global standard voxel grid is solved iteratively to construct a three-dimensional anisotropic power density voxel field model. Based on a unified global coordinate system, sensitive targets are located, the three-dimensional outer contour of the sensitive targets is matched with the boundaries of the global standard voxel mesh, and three-dimensional spatial regions with consistent matching degree are extracted to generate a three-dimensional spatial Boolean mask for the sensitive targets. Extract the effective voxel nodes covered by the sensitive target, traverse the effective voxel nodes, complete the spatial registration and superposition of the three-dimensional spatial Boolean mask and the power density voxel field model in the same coordinate system, and obtain the coupled voxel model of the sensitive target radiation constraint. Based on the coupled voxel model, retrieve the radiation power density and preset equivalent radiation-receiving cross-sectional area of ​​all matched and bound effective voxel nodes, solve the radiation received power of the corresponding node, and solve the spatial distribution extreme value and spatial cumulative total value of the radiation received power of the sensitive target. The local and global states of sensitive targets are determined separately. Based on the original three-dimensional assembly geometry model of the spacecraft, the power density voxel field and the dual states of sensitive targets are encapsulated as non-physical physical constraint attributes attached to the model, thus completing the construction of the spacecraft assembly state model.

[0008] Furthermore, the three-dimensional assembly geometric model of the spacecraft is read and loaded, and the global axial spatial bounding box of the model is solved using a unified global coordinate system and the spatial bounding box extreme value extraction formula, thereby defining the range of voxel discrete boundaries. Based on the preset voxel segmentation resolution and relying on a unified global coordinate system, each uniform cube voxel node generated by segmentation is assigned a unique three-dimensional coordinate. All voxel nodes with assigned values ​​are integrated to form a global standard voxel mesh.

[0009] Furthermore, the built-in product structure tree of the three-dimensional assembly geometry model is traversed to identify and locate the constraint source components that have the function of radiation boundary. The matching equipment attribute database is called to read the radiation energy of the constraint source components and the radiation emission pointing normal vector of each radiation surface. The unified global coordinate system is reused to extract the three-dimensional coordinates corresponding to the assembly position of the constraint source components.

[0010] Furthermore, the radiated power density of each voxel node within the global standard voxel mesh is solved iteratively to construct a three-dimensional anisotropic power density voxel field model. The specific logic is as follows: Based on a unified global coordinate system, the three-dimensional coordinates of the target voxel node and the three-dimensional coordinates of the constraint source are extracted respectively. The spatial relative position vector between the two is calculated, and the magnitude of the spatial relative position vector is calculated to obtain the spatial relative straight-line distance. Perform a dot product operation between the spatial relative position vector and the radiation emission pointing normal vector of the constrained source component, and determine the radiation orientation based on the dot product result: If the calculation result is less than or equal to 0, the target voxel node is determined to be located in the constraint source back blind zone, and the angle attenuation weight is set to 0. If the calculation result is greater than 0, the calculation result will be used as the angle attenuation weight; The radiation power density of the target voxel node is calculated by multiplying the radiation energy of the constrained source component with the angle attenuation weight, and then dividing the result of the multiplication by the cube of the relative straight distance in space and the constant of pi. Radial topological traversal iterative calculation is carried out with the three-dimensional coordinates of the constraint source as the center. When the traversal addressing obtains voxel nodes with radiation power density less than or equal to the preset attenuation cutoff threshold, and the nodes form a closed spatial boundary, the iterative calculation of radiation power density of the current constraint source component is stopped. The radiation power density of all remaining voxel nodes outside the closed space is directly assigned to 0, and a three-dimensional anisotropic power density voxel field model is generated.

[0011] Furthermore, a 3D spatial region with consistent matching degree is extracted to generate a 3D spatial Boolean mask specific to the sensitive target. The specific logic is as follows: Traverse the built-in product structure tree of the 3D assembly geometry model, identify and locate sensitive targets at preset installation positions in the global coordinate system, extract the original 3D geometric boundary data of the sensitive targets, combine the global standard voxel mesh, and determine the spatial positional relationship between each voxel node inside the global standard voxel mesh and the original 3D geometric boundary of the sensitive targets according to the 3D spatial interferometry algorithm. If the voxel node is located inside or on the original 3D geometric boundary of the sensitive targets, it is assigned the label 1; if the voxel node is located outside the original 3D geometric boundary of the sensitive targets, it is assigned the label 0. Based on the traversal results of all voxel node binary labels, encapsulate and generate a 3D spatial Boolean mask for the sensitive targets.

[0012] Furthermore, the effective voxel nodes covered by the sensitive target are extracted, and the effective voxel nodes are traversed to complete the registration and superposition of the 3D spatial Boolean mask and the power density voxel field model in the same coordinate system. The specific logic is as follows: Based on the node label attributes of the three-dimensional spatial Boolean mask, the global standard voxel mesh is traversed to filter and extract voxel nodes with a label value of 1; Using the global unified coordinate system as the reference coordinate system, the grid origin and axial scale of the three-dimensional spatial Boolean mask and the voxel node resolution of the three-dimensional anisotropic power density voxel field model are aligned to complete the rigid registration of the dual models in the pre-space space. For each of the collected effective voxel nodes of sensitive targets, Boolean mask space labels and three-dimensional coordinates of voxel field grid nodes are matched to achieve one-to-one mapping and binding of mask nodes and radiation power density nodes. Using the Boolean mask label threshold as a spatial superposition constraint, the mask constraint attributes of the effective voxel nodes of the sensitive target and the corresponding node radiation power density are coupled and superimposed at the pixel level. Invalid voxel meshes with a mask label of 0 are removed, and the coupled spatial superposition of the two models is completed to obtain the coupled voxel model of the sensitive target radiation constraint. The calculation logic for solving the spatial extreme values ​​of the radiated received power of sensitive targets and the spatial cumulative total is as follows: Based on the coupled voxel model, all matched and bound effective voxel nodes are retrieved, and the radiation power density corresponding to each effective voxel node is retrieved. The radiation power density of a single effective voxel node is multiplied by the preset equivalent radiation-receiving cross-sectional area to obtain the radiation received power of the corresponding effective voxel node. The radiated received power of all effective voxel nodes is traversed and compared, and the maximum power value is selected. This maximum value is defined as the spatial extreme value of the radiated received power of the sensitive target. A global summation operation is performed on the radiated received power of all effective voxel nodes, and the summation result is defined as the spatial cumulative total value of the radiated received power of the sensitive target.

[0013] Furthermore, based on the spatial extreme values ​​of the radiated received power of the sensitive target and the spatial cumulative total value, the local and global states of the sensitive target are determined respectively, as follows: If the spatial distribution extreme value is less than the preset distribution extreme value threshold, the sensitive target is judged to be locally radiation safe. If the spatial distribution extreme value is greater than or equal to the preset distribution extreme value threshold, the sensitive target is judged to be a local radiation violation. If the total spatial accumulation is less than the preset total accumulation threshold, the sensitive target is determined to be safe for overall radiation. If the total spatial cumulative value is greater than or equal to the preset total cumulative value threshold, the sensitive target is judged to have exceeded the overall radiation limit.

[0014] Furthermore, based on the original three-dimensional assembly geometry model of the spacecraft, the power density voxel field and the dual state of sensitive targets are encapsulated as non-physical physical constraint attributes attached to the model, thus completing the construction of the spacecraft assembly model. The specific logic is as follows: The three-dimensional anisotropic power density voxel field and the local and global states of the sensitive target are unified as an auxiliary attribute dataset of the final assembly model. The power density voxel field is defined as a topological property of the physical environment of the assembly model, and the local and global states of sensitive targets are defined together as radiation safety warning properties. Traverse the built-in product structure tree of the 3D assembly geometry model to locate the root node of the overall assembly and the assembly sub-nodes corresponding to the radiation-sensitive targets. Based on a unified coordinate system, node topology matching is completed, the association relationship between model assembly nodes is established, the physical environment topology attributes are attached and bound to the root node of the final assembly, and the radiation safety warning attributes are attached and bound to the assembly sub-nodes corresponding to sensitive targets; finally, a spacecraft assembly state model integrating a three-dimensional geometric solid model and two types of non-physical physical constraint attributes is output. The non-physical physical constraint attributes include physical environment topology attributes and radiation safety warning attributes.

[0015] To achieve the above objectives, the present invention also provides the following technical solution: A spacecraft assembly state model construction system, the system being used to execute any of the aforementioned spacecraft assembly state model construction methods, including: Voxel extraction module: acquires the three-dimensional assembly geometry model of the spacecraft, discretizes the global assembly space covered by the three-dimensional assembly geometry model into a global standard voxel mesh, identifies the constraint source components with radiation boundary effects, and extracts their radiation energy, radiation emission pointing normal vector of each radiation surface, and three-dimensional coordinates of the constraint source. Power density calculation module: Introducing the dual constraints of radiation propagation spatial distance attenuation law and radiation emission azimuth anisotropic angle attenuation, the radiation power density of each voxel node in the global standard voxel grid is solved iteratively to construct a three-dimensional anisotropic power density voxel field model. Mask extraction module: Based on a unified global coordinate system, locate sensitive targets, match the three-dimensional outer contour of the sensitive targets with the boundaries of the global standard voxel mesh, extract three-dimensional spatial regions with consistent matching degree, and generate three-dimensional spatial Boolean masks of sensitive targets; Power calculation module: Extract the effective voxel nodes covered by the sensitive target, traverse the effective voxel nodes, complete the spatial registration and superposition of the three-dimensional spatial Boolean mask and the power density voxel field model in the same coordinate system, and obtain the coupled voxel model of the sensitive target radiation constraint. Based on the coupled voxel model, retrieve the radiation power density and preset equivalent radiation-receiving cross-sectional area of ​​all matched and bound effective voxel nodes, solve the radiation received power of the corresponding node, and solve the spatial distribution extreme value and spatial cumulative total value of the radiation received power of the sensitive target. Model building module: It determines the local and global states of sensitive targets respectively. Based on the original three-dimensional assembly geometry model of the spacecraft, it encapsulates the power density voxel field and the dual states of sensitive targets as non-physical physical constraint attributes attached to the model, and completes the construction of the spacecraft assembly state model.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention, based on the dual constraints of radiation propagation spatial distance attenuation law and radiation emission azimuth anisotropic angular attenuation, iteratively solves the radiation power density of each voxel node within the global standard voxel grid, constructing a three-dimensional anisotropic power density voxel field model. This processing logic overcomes the limitations of existing technologies that can only characterize the static geometric form and discrete assembly attribute labels of spacecraft components. By deduce the attenuation and distribution state of the radiation energy of the constraint source component in the assembly space, the static geometric space is transformed into a grid carrier carrying real physical values, filling the gap in existing technologies that cannot map non-physical environments to state models. This allows the previously invisible physical fields to be quantified and visualized, providing an objective data basis for evaluating physical constraint interference in actual space. This invention also generates a 3D spatial Boolean mask of the sensitive target and performs spatial registration and superposition in the same coordinate system to extract the effective voxel nodes covered by the sensitive target. Then, it solves for the spatial distribution extrema and spatial cumulative total of the radiated received power, and uses these to determine the local and global states respectively. Finally, it encapsulates these into non-physical physical constraint attributes attached to the model to complete the construction of the spacecraft assembly state model. This processing logic utilizes the mask attribute to achieve physical trimming of spatial data, removes redundant calculations in irrelevant background areas to reduce computational power consumption, and mathematically decouples the two types of failure mechanisms—single-point penetration and overall thermal overload—solving the problem that existing technologies cannot extract the power distribution when the radiation field penetrates the actual location occupied by the sensitive target. This enables the quantitative identification of physical field interference risks and the reconstruction of 3D model data. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a schematic diagram of the overall system structure of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0019] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0020] Example: Please see Figure 1 The present invention provides a technical solution: The method for constructing a spacecraft assembly state model includes the following specific steps: Step 1: Obtain the three-dimensional assembly geometry model of the spacecraft, discretize the global assembly space covered by the three-dimensional assembly geometry model into a global standard voxel mesh, identify the constraint source components with radiation boundary effects, and extract their radiation energy, radiation emission pointing normal vector of each radiation surface, and three-dimensional coordinates of the constraint source. In this embodiment, the three-dimensional assembly geometric model of the spacecraft is read and loaded. Using a unified global coordinate system, the global axial spatial bounding box of the model is solved based on the spatial bounding box extremum extraction formula to define the range of voxel discrete boundaries. Combining the preset voxel segmentation resolution and relying on a unified global coordinate system, each uniform cube voxel node generated by segmentation is assigned a unique three-dimensional coordinate. All voxel nodes that have been assigned values ​​are integrated to form a global standard voxel mesh. The unified global coordinate system sets the geometric center point of the docking and separation surface between the spacecraft and the launch vehicle as the spatial origin of the global coordinate system. The axis perpendicular to the docking and separation surface and pointing towards the interior of the spacecraft cabin is defined as the Z-axis direction of the global coordinate system. Within the docking and separation surface, the intersection lines of two mutually perpendicular symmetric planes of the spacecraft cabin structure are defined as the X-axis direction and Y-axis direction of the global coordinate system, respectively. The preset voxel segmentation resolution is determined by relevant personnel as the standard physical boundary length of a single voxel mesh node by extracting the overall physical scale of the global axial bounding box of the three-dimensional assembly geometry model of the spacecraft and combining it with the preset spatial simulation accuracy requirements required for non-physical field deduction. Traverse the built-in product structure tree of the 3D assembly geometry model, identify and locate the constraint source components that have the function of radiation boundary, call the supporting equipment attribute database, read the radiation energy of the constraint source components and the radiation emission pointing normal vector of each radiation surface, reuse the unified global coordinate system, and extract the 3D coordinates corresponding to the assembly position of the constraint source components.

[0021] Building upon the above, it should be noted that the global standard voxel grid reflects the spatial discretization and reconstruction of the complex and continuous physical field inside the spacecraft. Traditional three-dimensional assembly geometric models of spacecraft can only characterize the boundaries of entities and cannot bear the physical field properties of the gaps between entities. Discretizing the global assembly space into a global standard voxel grid can transform the originally continuous and attribute-less geometric space into a grid data container that can bear physical values, indicating that each voxel node with independent three-dimensional coordinates can serve as a spatial reference for subsequent recording of radiated power density; The three extracted parameters of the constrained source component combine the initial boundary conditions of the non-physical field radiating outward in space: the three-dimensional coordinates of the constrained source reflect the spatial origin of the radiation field in the global coordinate system, establishing the positional reference for subsequent distance attenuation calculations. The radiation energy reflects the absolute initial magnitude of the radiation emitted outward by the constrained source component; the larger the value, the wider the range of physical space that the radiation field generated by the constrained source can penetrate and the deeper its influence. The radiation emission pointing normal vector reflects the anisotropic distribution law of the radiation energy in three-dimensional space, illustrating the angular attenuation characteristics of the radiation field in different spatial orientations in the forward main lobe region and the backward blind zone.

[0022] Step 2: Introduce the dual constraints of radiation propagation spatial distance attenuation law and radiation emission azimuth anisotropic angle attenuation, traverse and iteratively solve the radiation power density of each voxel node in the global standard voxel grid, and construct a three-dimensional anisotropic power density voxel field model. In this embodiment, the radiant power density of each voxel node within the global standard voxel grid is solved iteratively to construct a three-dimensional anisotropic power density voxel field model. The specific logic is as follows: Based on a unified global coordinate system, the three-dimensional coordinates of the target voxel node and the three-dimensional coordinates of the constraint source are extracted respectively. The spatial relative position vector between the two is calculated, and the magnitude of the spatial relative position vector is calculated to obtain the spatial relative straight-line distance. Perform a dot product operation between the spatial relative position vector and the radiation emission pointing normal vector of the constrained source component, and determine the radiation orientation based on the dot product result: If the calculation result is less than or equal to 0, the target voxel node is determined to be located in the constraint source back blind zone, and the angle attenuation weight is set to 0. If the calculation result is greater than 0, the calculation result will be used as the angle attenuation weight; The radiation power density of the target voxel node is calculated by multiplying the radiation energy of the constrained source component with the angle attenuation weight, and then dividing the result of the multiplication by the cube of the relative straight distance in space and the constant of pi. The formula used to calculate the radiated power density is as follows: in, In three-dimensional coordinates The radiative power density of the target voxel node at that location. Represents the three-dimensional coordinates of the target voxel node. This represents the radiated energy of the constrained source component. Represents the constraint source 3D coordinates of the target voxel node. This indicates the direction of the radiation emission towards the normal vector. Let represent the constant value of pi, taken as 3.14. Represents a spatial relative position vector. Indicates spatial distance relative to a straight line. Indicates the included angle of radiation emission. This represents the function that takes the maximum value; the result of the function represents the angle attenuation weight. Radial topological traversal iterative calculation is carried out with the three-dimensional coordinates of the constraint source as the center. When the traversal addressing obtains voxel nodes with radiation power density less than or equal to the preset attenuation cutoff threshold, and the nodes form a closed spatial boundary, the iterative calculation of radiation power density of the current constraint source component is stopped. The radiation power density of all remaining voxel nodes outside the closed space is directly assigned to 0, and a three-dimensional anisotropic power density voxel field model is generated. The preset attenuation cutoff threshold is determined by taking into account the background noise of the basic physical environment of the actual spacecraft assembly space and the floating-point operation precision limit of the three-dimensional scalar field simulation algorithm, and a very small constant is used as the engineering approximate zero value. The preset attenuation cutoff threshold is set to be equal to or slightly higher than this engineering approximate zero value.

[0023] Based on the above, it should be noted that calculating the radiated power density of each voxel node within the global standard voxel mesh is to transform the invisible energy distribution radiated outward from the constrained source component into a computable three-dimensional numerical matrix. Since traditional geometric models cannot characterize the energy transfer process between assembly gaps, solving for this parameter can visualize the abstract spatial physical interference risk, allowing for the early detection of physical exceedance defects during the virtual assembly stage. This lays a solid data foundation for subsequent assessments of the local breakdown and overall thermal overload risks of sensitive targets. In the specific computational logic, the radiated power density calculated by the formula reflects the actual physical radiation intensity experienced by the grid node at a specific spatial location. Its numerical value can accurately indicate the degree of safety threat posed by the three-dimensional spatial environment to surrounding electronic components. Establishing this index achieves the technical effect of quantifying non-physical field strength and empowering three-dimensional spatial data structures. The solution for the radiation power density is closely related to the radiation energy of the constrained source component, the three-dimensional coordinates of the target voxel node, the three-dimensional coordinates of the constrained source, and the radiation emission pointing normal vector. This deep correlation stems from the fact that the diffusion of the physical field in space is objectively governed by both the initial energy scale of the source and the geometric and topological characteristics of the spatial propagation path. Among them, the radiation energy of the constrained source component, as the driving force for the generation of the radiation field, determines the initial absolute order of magnitude of the field strength, and therefore shows a significant positive correlation with the radiation power density of the target voxel node. The larger the value, the wider the high-energy danger area that the radiation field can cover. Meanwhile, the magnitude of the spatial relative position vector constructed by the three-dimensional coordinates of the target voxel node and the three-dimensional coordinates of the constraint source reflects the physical length of the radiation propagation attenuation path. This spatial relative straight-line distance has an inverse cubic attenuation relationship with the radiation power density, indicating that the farther away from the source of the constraint, the weaker the radiation energy received by the corresponding voxel node. Furthermore, the angle attenuation weight, formed by the dot product of the spatial relative position vector and the radiation emission pointing normal vector, reflects the anisotropic distribution characteristics of the propagation of the non-physical physical field of the constrained source. This angle attenuation weight is positively correlated with the radiation power density. The larger the value, the closer the target voxel node is to the high-energy region of the radiation main lobe core. Conversely, if the dot product result is less than or equal to zero, it means that the corresponding node is in the back blind zone, and the radiation power density is truncated to zero. The design formula employing the aforementioned combination of cubic attenuation of relative straight-line distance and angular constraint of normal vector is fundamentally based on the fact that real spacecraft antennas or high-power heat-generating devices exhibit extremely strong directional focusing and shielding characteristics in their energy dissipation. Conventional geometric diffusion formulas significantly overestimate the field strength in the back blind zone and underestimate the peak energy level of the forward main lobe. Calculations derived using the formula designed in this application accurately match the propagation laws and attenuation mechanisms of real radiated energy in a complex three-dimensional assembly space, thus providing theoretical guidance and numerical calculation basis for constructing a high-precision assembly state model.

[0024] Step 3: Locate the sensitive target based on a unified global coordinate system, match the three-dimensional outer contour of the sensitive target with the boundary of the global standard voxel mesh, extract the three-dimensional spatial region with consistent matching degree, and generate the three-dimensional spatial Boolean mask of the sensitive target; In this embodiment, a three-dimensional spatial region with consistent matching degree is extracted to generate a three-dimensional Boolean mask for the sensitive target. The specific logic is as follows: Traverse the built-in product structure tree of the 3D assembly geometry model, identify and locate sensitive targets at preset installation positions in the global coordinate system, extract the original 3D geometric boundary data of the sensitive targets, combine the global standard voxel mesh, and determine the spatial positional relationship between each voxel node inside the global standard voxel mesh and the original 3D geometric boundary of the sensitive targets according to the 3D spatial interferometry algorithm. If the voxel node is located inside or on the original 3D geometric boundary of the sensitive targets, it is assigned the label 1; if the voxel node is located outside the original 3D geometric boundary of the sensitive targets, it is assigned the label 0. Based on the traversal results of all voxel node binary labels, encapsulate and generate a 3D spatial Boolean mask for the sensitive targets.

[0025] Building upon the above, it should be noted that matching the 3D outer contour of the sensitive target with the global standard voxel mesh boundary and generating a 3D spatial Boolean mask for the sensitive target is to accurately locate the microscopic data region occupied by the sensitive target within the global axial space. Since the anisotropic power density field constructed in the previous steps covers the entire assembly space of the spacecraft, while the sensitive target, as the key protection object, is only located in a specific local position, it is necessary to establish a clear mapping relationship between the continuous geometric boundary of the entity and the discrete voxel nodes through spatial interference comparison of the contour and the mesh boundary.

[0026] Subsequent calculations of radiated power and state security assessments must be strictly confined to the actual spatial occupancy of the sensitive target. Without this Boolean mask extraction, it is impossible to extract the physical boundary specific to the sensitive target from the massive global voxel grid, leading to the failure of subsequent spatial superposition of field strength and risk assessment due to the loss of spatial targeting. By generating this specific spatial Boolean mask, not only can the binary attributes of the label be used to directly eliminate redundant calculations in irrelevant background areas in subsequent calculations, significantly improving data processing efficiency, but it can also accurately maintain the spatial resolution of the original boundary of the sensitive target. This provides a data slicing basis for subsequent extraction of effective voxel nodes and solving for the spatial distribution extrema and spatial cumulative total of radiated received power.

[0027] Step 4: Extract the effective voxel nodes covered by the sensitive target, traverse the effective voxel nodes, complete the spatial registration and superposition of the three-dimensional spatial Boolean mask and the power density voxel field model in the same coordinate system, and obtain the coupled voxel model of the sensitive target radiation constraint. Based on the coupled voxel model, retrieve the radiation power density and preset equivalent radiation-receiving cross-sectional area of ​​all matched and bound effective voxel nodes, solve the radiation received power of the corresponding node, and solve the spatial distribution extreme value and spatial cumulative total value of the radiation received power of the sensitive target. In this embodiment, the effective voxel nodes covered by the sensitive target are extracted, and the effective voxel nodes are traversed to complete the registration and superposition of the three-dimensional spatial Boolean mask and the power density voxel field model in the same coordinate system. The specific logic is as follows: Based on the node label attributes of the three-dimensional spatial Boolean mask, the global standard voxel mesh is traversed to filter and extract voxel nodes with a label value of 1; Using the global unified coordinate system as the reference coordinate system, the grid origin and axial scale of the three-dimensional spatial Boolean mask and the voxel node resolution of the three-dimensional anisotropic power density voxel field model are aligned to complete the rigid registration of the dual models in the pre-space space. For each of the collected effective voxel nodes of sensitive targets, Boolean mask space labels and three-dimensional coordinates of voxel field grid nodes are matched to achieve one-to-one mapping and binding of mask nodes and radiation power density nodes. Using the Boolean mask label threshold as a spatial superposition constraint, the mask constraint attributes of the effective voxel nodes of the sensitive target and the corresponding node radiation power density are coupled and superimposed at the pixel level. Invalid voxel meshes with a mask label of 0 are removed, and the coupled spatial superposition of the two models is completed to obtain the coupled voxel model of the sensitive target radiation constraint. The calculation logic for solving the spatial extreme values ​​of the radiated received power of sensitive targets and the spatial cumulative total is as follows: Based on the coupled voxel model, all matched and bound effective voxel nodes are retrieved, and the radiation power density corresponding to each effective voxel node is retrieved. The radiation power density of a single effective voxel node is multiplied by the preset equivalent radiation-receiving cross-sectional area to obtain the radiation received power of the corresponding effective voxel node. The preset equivalent radiation-receiving cross-sectional area is calculated by spatially projecting the three-dimensional outer contour of the sensitive target based on the relative spatial orientation of the radiation source emission direction and various parts of the sensitive target surface, and the effective projected area in the radiation incident direction is obtained. This effective projected area is used as the equivalent radiation-receiving cross-sectional area. The radiated received power of all effective voxel nodes is traversed and compared, and the maximum power value is selected. This maximum value is defined as the spatial extreme value of the radiated received power of the sensitive target. A global summation operation is performed on the radiated received power of all effective voxel nodes, and the summation result is defined as the spatial cumulative total value of the radiated received power of the sensitive target.

[0028] Building upon the above, it's important to note that extracting the effective voxel nodes covered by the sensitive target and calculating the radiated received power of the corresponding nodes aims to transform the abstract radiation environment background in three-dimensional space into a real energy load acting on the surface of a specific device. The previously constructed three-dimensional anisotropic power density voxel field only characterizes the basic radiation field strength across the entire space. However, through mask registration and superposition in the same coordinate system, the effective geometric cross-section covered when the radiation field penetrates the sensitive target can be accurately identified. The introduction of a preset equivalent radiated cross-sectional area for this transformation is necessary because, at the microscopic level, the effective area ratio when the radiation flux is intercepted by the solid surface must be objectively considered. This transformation process directly maps the pure spatial environment data to the compressive characteristics of the sensitive target itself, providing a numerical basis for subsequent quantitative evaluation of the device's physical boundary resistance. In the specific mathematical solution logic, the radiative received power of a single node reflects the direct radiative energy impact borne by a single grid element. Its magnitude directly reflects the potential for thermal ablation or physical breakdown at that local micro-location. The calculation result of this index is jointly governed by the effective voxel node radiative power density and the preset equivalent radiated cross-sectional area. This deep correlation stems from the cumulative effect of energy flux passing through a specific surface in physics. Among them, the effective voxel node radiative power density, as a benchmark of environmental intensity, shows a significant positive correlation with the radiative received power of the corresponding node; the higher the spatial environmental field strength, the greater the accumulated energy load at that cross-sectional point.

[0029] Meanwhile, the pre-defined equivalent radiated cross-sectional area serves as the physical window for energy absorption, and is positively correlated with the received radiation power. The larger the radiated area, the more absolute radiation energy is intercepted by the corresponding voxel node. The reason for adopting this basic product-type operation logic is that, at the microscopic voxel scale, treating the lateral cross-section of the discrete mesh as an ideal two-dimensional irradiated panel allows for the direct reconstruction of the physical impact process of high-frequency radiation energy with extremely low computational overhead. This significantly improves the computational processing efficiency of massive discrete mesh data while ensuring the accuracy of energy dimensionality reduction and transformation.

[0030] Building upon this microscopic single-point calculation, further deduction and solution of the spatial distribution extrema and spatial cumulative total of the radiated received power of the sensitive target are aimed at elevating the scattered voxel node data to the level of overall physical evaluation of the sensitive target device. The spatial distribution extrema pinpoints the maximum energy-receiving points among all effective voxel nodes, and extracting this extremum parameter is primarily used to prevent the risk of local transient over-limits caused by single-point high-energy accumulation. The spatial cumulative total sums all radiated received power on the sensitive target surface, truly reflecting the overall thermal dissipation pressure faced by the entire device under this radiation environment. Simultaneously extracting these two cross-dimensional macroscopic indicators, extrema and total, decouples two distinct failure mechanisms—local transient damage and overall temperature rise overload—at the underlying data logic level, thereby truly constructing a dual-check boundary for complex physical interferences during the virtual assembly stage.

[0031] Step 5: Determine the local and global states of the sensitive target respectively. Based on the original three-dimensional assembly geometry model of the spacecraft, encapsulate the power density voxel field and the dual states of the sensitive target as non-physical constraint attributes attached to the model to complete the construction of the spacecraft assembly state model. In this embodiment, the local and global states of the sensitive target are determined based on the spatial extreme values ​​of the radiated received power of the sensitive target and the spatial cumulative total value, as follows: If the spatial distribution extreme value is less than the preset distribution extreme value threshold, the sensitive target is judged to be locally radiation safe. If the spatial distribution extreme value is greater than or equal to the preset distribution extreme value threshold, the sensitive target is judged to be a local radiation violation. If the total spatial accumulation is less than the preset total accumulation threshold, the sensitive target is determined to be safe for overall radiation. If the total spatial accumulation value is greater than or equal to the preset total accumulation value threshold, the sensitive target is judged to have exceeded the overall radiation limit. The preset distribution extreme value threshold and the preset cumulative total value threshold are obtained by extracting the basic physical environment tolerance parameters inherent in the development specifications of the sensitive target's supporting equipment, including the local maximum allowable irradiance and the overall maximum allowable absorbed power of the sensitive target. The local maximum allowable irradiance is multiplied by the preset equivalent irradiated cross-sectional area to obtain the upper limit of the radiation receiving power that the sensitive target can withstand under a single voxel node, and then reduced by 5% as a reserved safety space. This is set as the preset distribution extreme value threshold. The overall maximum allowable absorbed power is reduced by 5% as a reserved safety space and set as the preset cumulative total value threshold. Based on the original three-dimensional assembly geometry model of the spacecraft, the power density voxel field and the dual state of sensitive targets are encapsulated as non-physical physical constraint attributes attached to the model, thus completing the construction of the spacecraft assembly model. The specific logic is as follows: The three-dimensional anisotropic power density voxel field and the local and global states of the sensitive target are unified as an auxiliary attribute dataset of the final assembly model. The power density voxel field is defined as a topological property of the physical environment of the assembly model, and the local and global states of sensitive targets are defined together as radiation safety warning properties. Traverse the built-in product structure tree of the 3D assembly geometry model to locate the root node of the overall assembly and the assembly sub-nodes corresponding to the radiation-sensitive targets. Based on a unified coordinate system, node topology matching is completed, the association relationship between model assembly nodes is established, the physical environment topology attributes are attached and bound to the root node of the final assembly, and the radiation safety warning attributes are attached and bound to the assembly sub-nodes corresponding to sensitive targets; finally, a spacecraft assembly state model integrating a three-dimensional geometric solid model and two types of non-physical physical constraint attributes is output. The non-physical physical constraint attributes include physical environment topology attributes and radiation safety warning attributes.

[0032] Based on the above, it should be noted that separately judging the local and global states of sensitive targets, and encapsulating the three-dimensional anisotropic power density voxel field and the dual states of sensitive targets as non-physical constraint attributes attached to the model, is to ultimately transform the discrete physical values ​​calculated in the early stage into safety control conclusions that can intuitively guide the final assembly process decisions. Judging the local and global states of sensitive targets can effectively deal with physical failure mechanisms with completely different properties. In real spacecraft layouts, spatial distribution extreme values ​​exceeding the preset distribution extreme value threshold will cause local transient over-limits, leading to optical thin film ablation or transient breakdown of local circuits in sensitive targets. On the other hand, spatial cumulative total values ​​exceeding the preset cumulative total value threshold will cause overall radiation over-limits, putting devices under severe thermal overload failure pressure. Judging based on a single dimension is prone to missing potential design defects. Parallel verification of dual dimensions achieves a comprehensive consideration of macroscopic energy consumption pressure and microscopic single-point damage potential. Building upon this foundation, the dataset containing the three-dimensional anisotropic power density voxel field and the local and global states of sensitive targets is unified as an auxiliary attribute dataset of the assembly model and encapsulated. This breaks through the limitations of traditional models that can only express static geometric forms and discrete assembly attribute labels, making the invisible non-physical physical constraint field a physical attribute that can be directly managed, attached, and queried in digital assembly. Defining the three-dimensional anisotropic power density voxel field as a topological attribute of the physical environment of the assembly model and attaching it to the root node of the assembly allows for the reconstruction of the panoramic topological distribution of the physical field inside the spacecraft from a global macroscopic perspective. Meanwhile, defining the local and global states of sensitive targets together as radiation safety warning attributes and attaching them to the corresponding assembly sub-nodes of sensitive targets enables precise risk marking of specific key objects in a localized area. This node topology matching and mounting, which is completed by traversing the built-in product structure tree of the original 3D assembly geometric model, enables the deep integration of the underlying topological relationship between the non-physical environment data and the built-in product structure tree of the original assembly. The final output spacecraft assembly state model is endowed with rich physical deduction dimensions on top of the geometric entity, realizing the quantitative identification and comprehensive verification of the interference risk of non-physical physical fields in the virtual assembly stage.

[0033] Please see Figure 2 The present invention also provides a spacecraft assembly state model construction system, the system being used to execute the spacecraft assembly state model construction method described in any of the above claims, including: Voxel extraction module: acquires the three-dimensional assembly geometry model of the spacecraft, discretizes the global assembly space covered by the three-dimensional assembly geometry model into a global standard voxel mesh, identifies the constraint source components with radiation boundary effects, and extracts their radiation energy, radiation emission pointing normal vector of each radiation surface, and three-dimensional coordinates of the constraint source. Power density calculation module: Introducing the dual constraints of radiation propagation spatial distance attenuation law and radiation emission azimuth anisotropic angle attenuation, the radiation power density of each voxel node in the global standard voxel grid is solved iteratively to construct a three-dimensional anisotropic power density voxel field model. Mask extraction module: Based on a unified global coordinate system, locate sensitive targets, match the three-dimensional outer contour of the sensitive targets with the boundaries of the global standard voxel mesh, extract three-dimensional spatial regions with consistent matching degree, and generate three-dimensional spatial Boolean masks of sensitive targets; Power calculation module: Extract the effective voxel nodes covered by the sensitive target, traverse the effective voxel nodes, complete the spatial registration and superposition of the three-dimensional spatial Boolean mask and the power density voxel field model in the same coordinate system, and obtain the coupled voxel model of the sensitive target radiation constraint. Based on the coupled voxel model, retrieve the radiation power density and preset equivalent radiation-receiving cross-sectional area of ​​all matched and bound effective voxel nodes, solve the radiation received power of the corresponding node, and solve the spatial distribution extreme value and spatial cumulative total value of the radiation received power of the sensitive target. Model building module: It determines the local and global states of sensitive targets respectively. Based on the original three-dimensional assembly geometry model of the spacecraft, it encapsulates the power density voxel field and the dual states of sensitive targets as non-physical physical constraint attributes attached to the model, and completes the construction of the spacecraft assembly state model.

[0034] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0035] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0036] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0037] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for constructing a spacecraft assembly state model, characterized in that, The specific steps include: Step 1: Obtain the three-dimensional assembly geometry model of the spacecraft, discretize the global assembly space covered by the three-dimensional assembly geometry model into a global standard voxel mesh, identify the constraint source components with radiation boundary effects, and extract their radiation energy, radiation emission pointing normal vector of each radiation surface, and three-dimensional coordinates of the constraint source. Step 2: Introduce the dual constraints of radiation propagation spatial distance attenuation law and radiation emission azimuth anisotropic angle attenuation, traverse and iteratively solve the radiation power density of each voxel node in the global standard voxel grid, and construct a three-dimensional anisotropic power density voxel field model. Step 3: Locate the sensitive target based on a unified global coordinate system, match the three-dimensional outer contour of the sensitive target with the boundary of the global standard voxel mesh, extract the three-dimensional spatial region with consistent matching degree, and generate the three-dimensional spatial Boolean mask of the sensitive target; Step 4: Extract the effective voxel nodes covered by the sensitive target, traverse the effective voxel nodes, complete the registration and superposition of the three-dimensional spatial Boolean mask and the power density voxel field model in the same coordinate system, and obtain the coupled voxel model of the sensitive target radiation constraint. Based on the coupled voxel model, retrieve the radiation power density and preset equivalent radiation-receiving cross-sectional area of ​​all matched and bound effective voxel nodes, solve the radiation received power of the corresponding node, and solve the spatial distribution extreme value and spatial cumulative total value of the radiation received power of the sensitive target. Step 5: Determine the local and global states of the sensitive target respectively. Based on the original three-dimensional assembly geometry model of the spacecraft, encapsulate the power density voxel field and the dual states of the sensitive target as non-physical constraint attributes attached to the model, and complete the construction of the spacecraft assembly state model.

2. The method for constructing a spacecraft assembly state model according to claim 1, characterized in that: The three-dimensional assembly geometry model of the spacecraft is read and loaded. Using a unified global coordinate system, the global axial spatial bounding box of the model is solved based on the spatial bounding box extremum extraction formula to define the range of voxel discrete boundaries. Based on the preset voxel segmentation resolution and relying on a unified global coordinate system, each uniform cube voxel node generated by segmentation is assigned a unique three-dimensional coordinate. All voxel nodes with assigned values ​​are integrated to form a global standard voxel mesh.

3. The method for constructing a spacecraft assembly state model according to claim 1, characterized in that: Traverse the built-in product structure tree of the 3D assembly geometry model, identify and locate the constraint source components that have the function of radiation boundary, call the supporting equipment attribute database, read the radiation energy of the constraint source components and the radiation emission pointing normal vector of each radiation surface, reuse the unified global coordinate system, and extract the 3D coordinates corresponding to the assembly position of the constraint source components.

4. The method for constructing a spacecraft assembly state model according to claim 3, characterized in that: The radiative power density of each voxel node within the global standard voxel mesh is solved iteratively to construct a three-dimensional anisotropic power density voxel field model. The specific logic is as follows: Based on a unified global coordinate system, the three-dimensional coordinates of the target voxel node and the three-dimensional coordinates of the constraint source are extracted respectively. The spatial relative position vector between the two is calculated, and the magnitude of the spatial relative position vector is calculated to obtain the spatial relative straight-line distance. Perform a dot product operation between the spatial relative position vector and the radiation emission pointing normal vector of the constrained source component, and determine the radiation orientation based on the dot product result: If the calculation result is less than or equal to 0, the target voxel node is determined to be located in the constraint source back blind zone, and the angle attenuation weight is set to 0. If the calculation result is greater than 0, the calculation result will be used as the angle attenuation weight; The radiation power density of the target voxel node is calculated by multiplying the radiation energy of the constrained source component with the angle attenuation weight, and then dividing the result of the multiplication by the cube of the relative straight distance in space and the constant of pi. Radial topological traversal iterative calculation is carried out with the three-dimensional coordinates of the constraint source as the center. When the traversal addressing obtains voxel nodes with radiation power density less than or equal to the preset attenuation cutoff threshold, and the nodes form a closed spatial boundary, the iterative calculation of radiation power density of the current constraint source component is stopped. The radiation power density of all remaining voxel nodes outside the closed space is directly assigned to 0, and a three-dimensional anisotropic power density voxel field model is generated.

5. The method for constructing a spacecraft assembly state model according to claim 1, characterized in that: Extract 3D spatial regions with consistent matching degrees and generate a specific 3D Boolean mask for the sensitive target. The specific logic is as follows: Traverse the built-in product structure tree of the 3D assembly geometry model, identify and locate sensitive targets at preset installation positions in the global coordinate system, extract the original 3D geometric boundary data of the sensitive targets, combine the global standard voxel mesh, and determine the spatial positional relationship between each voxel node inside the global standard voxel mesh and the original 3D geometric boundary of the sensitive targets according to the 3D spatial interferometry algorithm. If the voxel node is located inside or on the original 3D geometric boundary of the sensitive targets, it is assigned the label 1; if the voxel node is located outside the original 3D geometric boundary of the sensitive targets, it is assigned the label 0. Based on the traversal results of all voxel node binary labels, encapsulate and generate a 3D spatial Boolean mask for the sensitive targets.

6. The method for constructing a spacecraft assembly state model according to claim 5, characterized in that: Extract the effective voxel nodes covered by the sensitive target, traverse the effective voxel nodes, and complete the registration and superposition of the 3D spatial Boolean mask and the power density voxel field model in the same coordinate system. The specific logic is as follows: Based on the node label attributes of the three-dimensional spatial Boolean mask, the global standard voxel mesh is traversed to filter and extract voxel nodes with a label value of 1; Using the global unified coordinate system as the reference coordinate system, the grid origin and axial scale of the three-dimensional spatial Boolean mask and the voxel node resolution of the three-dimensional anisotropic power density voxel field model are aligned to complete the rigid registration of the dual models in the pre-space space. For each of the collected effective voxel nodes of sensitive targets, Boolean mask space labels and three-dimensional coordinates of voxel field grid nodes are matched to achieve one-to-one mapping and binding of mask nodes and radiation power density nodes. Using the Boolean mask label threshold as a spatial superposition constraint, the mask constraint attributes of the effective voxel nodes of the sensitive target and the corresponding node radiation power density are coupled and superimposed at the pixel level. Invalid voxel meshes with a mask label of 0 are removed, and the coupled spatial superposition of the two models is completed to obtain the coupled voxel model of the sensitive target radiation constraint. The calculation logic for solving the spatial extreme values ​​of the radiated received power of sensitive targets and the spatial cumulative total is as follows: Based on the coupled voxel model, all matched and bound effective voxel nodes are retrieved, and the radiation power density corresponding to each effective voxel node is retrieved. The radiation power density of a single effective voxel node is multiplied by the preset equivalent radiation-receiving cross-sectional area to obtain the radiation received power of the corresponding effective voxel node. The radiated received power of all effective voxel nodes is traversed and compared, and the maximum power value is selected. This maximum value is defined as the spatial extreme value of the radiated received power of the sensitive target. A global summation operation is performed on the radiated received power of all effective voxel nodes, and the summation result is defined as the spatial cumulative total value of the radiated received power of the sensitive target.

7. The method for constructing a spacecraft assembly state model according to claim 1, characterized in that: Based on the spatial extreme values ​​of the radiated received power of the sensitive target and the spatial cumulative total value, the local and global states of the sensitive target are determined respectively, as follows: If the spatial distribution extreme value is less than the preset distribution extreme value threshold, the sensitive target is judged to be locally radiation safe. If the spatial distribution extreme value is greater than or equal to the preset distribution extreme value threshold, the sensitive target is judged to be a local radiation violation. If the total spatial accumulation is less than the preset total accumulation threshold, the sensitive target is determined to be safe for overall radiation. If the total spatial cumulative value is greater than or equal to the preset total cumulative value threshold, the sensitive target is judged to have exceeded the overall radiation limit.

8. The method for constructing a spacecraft assembly state model according to claim 7, characterized in that: Based on the original three-dimensional assembly geometry model of the spacecraft, the power density voxel field and the dual state of sensitive targets are encapsulated as non-physical physical constraint attributes attached to the model, thus completing the construction of the spacecraft assembly model. The specific logic is as follows: The three-dimensional anisotropic power density voxel field and the local and global states of the sensitive target are unified as an auxiliary attribute dataset of the final assembly model. The power density voxel field is defined as a topological property of the physical environment of the assembly model, and the local and global states of sensitive targets are defined together as radiation safety warning properties. Traverse the built-in product structure tree of the 3D assembly geometry model to locate the root node of the overall assembly and the assembly sub-nodes corresponding to the radiation-sensitive targets. Based on a unified coordinate system, node topology matching is completed, the association relationship between model assembly nodes is established, the physical environment topology attributes are attached and bound to the root node of the final assembly, and the radiation safety warning attributes are attached and bound to the assembly sub-nodes corresponding to sensitive targets; finally, a spacecraft assembly state model integrating a three-dimensional geometric solid model and two types of non-physical physical constraint attributes is output. The non-physical physical constraint attributes include physical environment topology attributes and radiation safety warning attributes.

9. A spacecraft assembly state model construction system, characterized in that: The system is used to execute the spacecraft assembly state model construction method according to any one of claims 1-8, including: Voxel extraction module: acquires the three-dimensional assembly geometry model of the spacecraft, discretizes the global assembly space covered by the three-dimensional assembly geometry model into a global standard voxel mesh, identifies the constraint source components with radiation boundary effects, and extracts their radiation energy, radiation emission pointing normal vector of each radiation surface, and three-dimensional coordinates of the constraint source. Power density calculation module: Introducing the dual constraints of radiation propagation spatial distance attenuation law and radiation emission azimuth anisotropic angle attenuation, the radiation power density of each voxel node in the global standard voxel grid is solved iteratively to construct a three-dimensional anisotropic power density voxel field model. Mask extraction module: Based on a unified global coordinate system, locate sensitive targets, match the three-dimensional outer contour of the sensitive targets with the boundaries of the global standard voxel mesh, extract three-dimensional spatial regions with consistent matching degree, and generate three-dimensional spatial Boolean masks of sensitive targets; Power calculation module: Extract the effective voxel nodes covered by the sensitive target, traverse the effective voxel nodes, complete the spatial registration and superposition of the three-dimensional spatial Boolean mask and the power density voxel field model in the same coordinate system, and obtain the coupled voxel model of the sensitive target radiation constraint. Based on the coupled voxel model, retrieve the radiation power density and preset equivalent radiation-receiving cross-sectional area of ​​all matched and bound effective voxel nodes, solve the radiation received power of the corresponding node, and solve the spatial distribution extreme value and spatial cumulative total value of the radiation received power of the sensitive target. Model building module: It determines the local and global states of sensitive targets respectively. Based on the original three-dimensional assembly geometry model of the spacecraft, it encapsulates the power density voxel field and the dual states of sensitive targets as non-physical physical constraint attributes attached to the model, and completes the construction of the spacecraft assembly state model.

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