Three-dimensional temperature estimation method based on grid topology and physical partition and related device

Abstract

This application relates to the field of three-dimensional temperature field reconstruction technology, and provides a three-dimensional temperature estimation method and related apparatus based on mesh topology and physical partitioning. The method includes: acquiring a three-dimensional mesh model of a target object; using each triangular facet in the three-dimensional mesh model as a graph node in a graph structure, and constructing a mesh topology graph structure based on the spatial adjacency relationship between each triangular facet to obtain an initial graph structure; performing physical partitioning annotation processing on each graph node in the initial graph structure to obtain a physical partitioning graph structure; performing cross-component edge processing on the adjacent edges in the physical partitioning graph structure to obtain a physical partitioning cross-component edge graph structure; marking the graph nodes in the physical partitioning cross-component edge graph structure with temperature nodes to obtain a marked temperature graph structure; and performing temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partitioning cross-component edge graph structure to obtain the temperature estimation value corresponding to each node to be estimated.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to the field of three-dimensional temperature field reconstruction technology, specifically to a three-dimensional temperature estimation method and related apparatus based on mesh topology and physical partitioning. Background Technology

[0002] With the development of industrial equipment condition monitoring and fault diagnosis technologies, the demand for acquiring the three-dimensional temperature field of target objects is increasing. Currently, infrared thermometry is commonly used to obtain the temperature distribution on the surface of target objects. However, for areas invisible to infrared cameras, temperature estimation methods are needed. Existing temperature estimation methods do not fully consider the influence of the internal structural features and physical properties of the target object on the heat conduction path, resulting in insufficient accuracy of temperature estimation results for invisible areas. Summary of the Invention

[0003] This application provides a three-dimensional temperature estimation method and related apparatus based on mesh topology and physical partitioning, which can achieve accurate temperature estimation for invisible areas of a three-dimensional temperature field.

[0004] A first aspect of this application provides a three-dimensional temperature estimation method based on mesh topology and physical partitioning, the method comprising: Obtain the 3D mesh model of the target object; Each triangular facet in the 3D mesh model is used as a graph node in the graph structure. The mesh topology graph structure is constructed based on the spatial adjacency relationship between each triangular facet to obtain the initial graph structure. Based on the component segmentation information of the target object, each graph node in the initial graph structure is physically partitioned and labeled to obtain a physical partition graph structure. Perform cross-component edge processing on the adjacent edges in the physical partition graph structure to obtain the physical partition cross-component edge graph structure. Based on the infrared visibility detection results of the target object, temperature nodes are marked on the graph nodes in the physical partition cross-component edge graph structure to obtain the marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated. Based on the adjacency relationship in the cross-component edge graph structure of the physical partition, temperature propagation estimation is performed on each node to be estimated in the marked temperature graph structure to obtain the temperature estimation value corresponding to each node to be estimated.

[0005] A second aspect of this application provides a three-dimensional temperature estimation device based on mesh topology and physical partitioning, the device comprising: Acquisition unit, used to acquire the 3D mesh model of the target object; The building unit is used to treat each triangular facet in the 3D mesh model as a graph node in the graph structure, and to construct the mesh topology graph structure based on the spatial adjacency relationship between each triangular facet to obtain the initial graph structure. The first processing unit is used to perform physical partitioning and labeling processing on each graph node in the initial graph structure according to the component segmentation information of the target object, so as to obtain a physical partitioning graph structure. The second processing unit is used to perform cross-component edge processing on the adjacent edges in the physical partition graph structure to obtain the physical partition cross-component edge graph structure. The third processing unit is used to mark the graph nodes in the physical partition cross-component edge graph structure with temperature nodes according to the infrared visibility detection results of the target object, so as to obtain a marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated. The fourth processing unit is used to perform temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, and obtain the temperature estimation value corresponding to each node to be estimated.

[0006] A third aspect of this application provides a terminal including a processor, an input device, an output device, and a memory, wherein the processor, input device, output device, and memory are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to execute the step instructions as described in the first aspect of this application.

[0007] A fourth aspect of this application provides a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of this application.

[0008] A fifth aspect of this application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of this application. The computer program product may be a software installation package.

[0009] Implementing the embodiments of this application has the following beneficial effects: By acquiring a 3D mesh model of the target object and using each triangular facet in the 3D mesh model as a graph node in the graph structure, a mesh topology graph structure is constructed based on the spatial adjacency relationship between each triangular facet, resulting in an initial graph structure. Further, based on the component segmentation information of the target object, physical partitioning and labeling processing is performed on each graph node in the initial graph structure to obtain a physical partitioning graph structure. Adjacent edges in the physical partitioning graph structure are then processed across components to obtain a physical partitioning cross-component edge graph structure. Based on the infrared visibility detection results of the target object, temperature nodes are marked on the graph nodes in the physical partitioning cross-component edge graph structure, resulting in a marked temperature graph structure including known temperature nodes and nodes to be estimated. Furthermore, based on the adjacency relationship in the physical partitioning cross-component edge graph structure, temperature propagation estimation is performed on each node to be estimated in the marked temperature graph structure to obtain the temperature estimation value corresponding to each node to be estimated. This improves the accuracy of temperature estimation for invisible areas of the 3D temperature field. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This application provides a schematic diagram of the structure of a three-dimensional temperature estimation system based on mesh topology and physical partitioning. Figure 2 This application provides a flowchart illustrating a three-dimensional temperature estimation method based on mesh topology and physical partitioning. Figure 3 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application; Figure 4 This application provides a schematic diagram of the structure of a three-dimensional temperature estimation device based on mesh topology and physical partitioning. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0014] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0015] To better understand the technical solution of this application, we first analyze existing three-dimensional temperature field estimation methods. Existing three-dimensional temperature field estimation methods mainly employ spatial distance interpolation, such as inverse distance weighting and Kriging interpolation, which estimate temperature solely based on the spatial distance between nodes. However, three-dimensional objects exhibit self-occlusion regions in infrared monitoring, i.e., surface areas that cannot be directly observed by the infrared camera, resulting in missing temperature data for these areas. Traditional interpolation methods only consider spatial distance, neglecting the thermal isolation characteristics between different components (such as heat conduction interruptions caused by air gaps) and the differences in thermal conduction between different materials (such as the difference in thermal conductivity between copper and insulating materials). This leads to estimation results that easily produce temperature values ​​at component boundaries that do not conform to physical laws.

[0016] To address the aforementioned issues, this application provides a three-dimensional temperature estimation method based on mesh topology and physical partitioning. By constructing a mesh topology graph structure and physically partitioning and labeling the graph nodes and processing cross-component edges, temperature propagation estimation is performed only between nodes with actual heat conduction paths, thereby improving the accuracy and physical consistency of temperature estimation in invisible areas.

[0017] Please see Figure 1 , Figure 1 This application provides a schematic diagram of the structure of a three-dimensional temperature estimation system based on mesh topology and physical partitioning, as an embodiment of the present application. Figure 1As shown, a 3D temperature estimation system based on mesh topology and physical partitioning may include: a model acquisition module for acquiring a 3D mesh model of the target object; a graph structure construction module for using each triangular facet in the 3D mesh model as a graph node in the graph structure, and constructing a mesh topology graph structure based on the spatial adjacency relationship between each triangular facet to obtain an initial graph structure; a physical partitioning annotation module for performing physical partitioning annotation processing on each graph node in the initial graph structure based on the component segmentation information of the target object to obtain a physical partitioning graph structure; a cross-component edge processing module for performing cross-component edge processing on the adjacent edges in the physical partitioning graph structure to obtain a physical partitioning cross-component edge graph structure; a temperature node marking module for marking the graph nodes in the physical partitioning cross-component edge graph structure with temperature nodes based on the infrared visibility detection results of the target object to obtain a marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated; and a temperature propagation estimation module for performing temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partitioning cross-component edge graph structure to obtain a temperature estimation value corresponding to each node to be estimated.

[0018] Please see Figure 2 , Figure 2 This application provides a flowchart illustrating a three-dimensional temperature estimation method based on mesh topology and physical partitioning, as illustrated in this embodiment. Figure 2 As shown, the three-dimensional temperature estimation method based on mesh topology and physical partitioning includes: S10: Obtain the 3D mesh model of the target object.

[0019] In this context, the 3D mesh model is a 3D representation of the object's surface composed of triangular facets, commonly in the Standard Tessellation Language (STL) file format. Each triangular facet is defined by three vertex coordinates and a normal vector, which indicates the outward direction of the facet.

[0020] The target object is a three-dimensional object requiring temperature monitoring, such as a power transformer, an electronic device housing, or an industrial pipeline. The three-dimensional mesh model can be exported from computer-aided design (CAD) files or obtained by scanning the surface of the target object using a three-dimensional scanning device; this application does not impose any restrictions on this.

[0021] S20. Each triangular facet in the three-dimensional mesh model is used as a graph node in the graph structure. A mesh topology graph structure is constructed based on the spatial adjacency relationship between each triangular facet to obtain the initial graph structure.

[0022] In this application, a graph structure is a data structure composed of nodes and edges. Each triangular facet in the 3D mesh model is mapped to a graph node in the graph structure, with a one-to-one correspondence between the graph node and the triangular facet. Adjacent edges are edges that connect two graph nodes and can be used to represent the spatial adjacency relationship between two triangular facets.

[0023] Spatial adjacency refers to two triangular faces sharing an edge in a 3D mesh model, meaning they have two common vertices. Based on this spatial adjacency, adjacency edges are established between the corresponding graph nodes to obtain the mesh topology.

[0024] The initial graph structure can refer to the original graph structure, which may only contain topological connection information based on spatial adjacency. In other words, the initial graph structure is the original graph structure without subsequent processing, such as subsequent physical partitioning or cross-component edge processing.

[0025] S30. Based on the component segmentation information of the target object, perform physical partitioning labeling on each graph node in the initial graph structure, and add component type label and material type label to each graph node to obtain a physical partitioning graph structure.

[0026] Component segmentation information describes which components make up the target object and which component each triangular facet belongs to. For example, the component segmentation information of a power transformer may include components such as the core, high-voltage winding, low-voltage winding, oil tank, and radiator.

[0027] It should be noted that the above-mentioned component segmentation information can be obtained in at least one of the following ways: determined according to the assembly hierarchy in the computer-aided design file of the target object; or, by receiving the user's manual annotation information of the components to which each triangular facet belongs in the three-dimensional mesh model; or, by automatically segmenting the three-dimensional mesh model through a component segmentation algorithm. This application does not limit the method of obtaining component segmentation information.

[0028] Physical partitioning labeling is the process of labeling each node in the initial graph structure with component type and material type labels. The component type label identifies the component to which the triangular facet corresponding to the graph node belongs. For example, if the component to which the triangular facet belongs is "iron core," the component type label could be "iron core." The material type label identifies the material type to which the triangular facet corresponding to the graph node belongs. For example, if the material type to which the triangular facet belongs is "insulating paper," the material type label could be "insulating paper."

[0029] After the physical partitioning is labeled, each node in the initial graph structure can carry a component type label and a material type label, thus obtaining the above-mentioned physical partitioning graph structure.

[0030] S40. Perform cross-component edge processing on the adjacent edges in the physical partition graph structure to obtain a physical partition cross-component edge graph structure. The physical partition cross-component edge graph structure refers to the graph structure after cross-component edge processing, where the adjacent edges only connect nodes of the same component or cross-component nodes that have physical contact, and are used to reflect the actual heat conduction path.

[0031] In this context, a cross-component edge refers to an adjacent edge connecting graph nodes with different component type labels, indicating that the edge spans two different components. Cross-component edge processing involves retaining or deleting adjacent edges based on their component type labels, ensuring that the processed graph structure only shows node connections where a heat conduction path actually exists.

[0032] Specifically, for adjacent edges within the same component (with the same component type label on both ends of the diagram), the edge can be retained due to smooth heat conduction within the same component. For adjacent edges across components (with different component type labels on both ends of the diagram), it is necessary to further determine whether there is physical contact between the two components. If physical contact exists, the adjacent edge is retained and labeled with a contact type label. If there is no physical contact (e.g., an air gap exists between the two components), the adjacent edge is deleted. Physical contact refers to direct physical contact between two different components, where a heat conduction interface exists.

[0033] The physical partition cross-component edge graph structure refers to the graph structure after cross-component edge processing, where adjacent edges only connect nodes of the same component or cross-component nodes that have physical contact, and can reflect the actual heat conduction path. The specific implementation of cross-component edge processing can be described in detail in subsequent embodiments, and will not be repeated here.

[0034] S50. Based on the infrared visibility detection results of the target object, temperature nodes are marked on the graph nodes in the physical partition cross-component edge graph structure to obtain a marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated.

[0035] The infrared visibility detection result is determined by analyzing the relationship between the infrared camera's viewpoint and the normal vectors of the triangular facets on the surface of the three-dimensional mesh model of the target object, thus determining whether each triangular facet is visible to the infrared camera.

[0036] Specifically, if the angle between the normal vector of the triangular facet and the line of sight of the infrared camera is less than 90 degrees, and the triangular facet is not obscured by other facets, then the triangular facet is visible to the infrared camera; if the angle between the normal vector of the triangular facet and the line of sight of the infrared camera is greater than or equal to 90 degrees, or if the triangular facet is obscured by other facets, then the triangular facet is not visible to the infrared camera.

[0037] Optionally, the infrared visibility detection can be implemented as follows: For each triangular facet, calculate the angle between the normal vector of the triangular facet and the line-of-sight direction of the infrared camera. If the angle is greater than or equal to 90 degrees, the triangular facet is facing away from the infrared camera and is not visible. If the angle is less than 90 degrees, further determine whether the triangular facet is occluded by other triangular facets using a ray tracing method. Specifically, emit a ray from the position of the infrared camera towards the centroid of the triangular facet. If the ray intersects with other triangular facets before reaching the triangular facet, the triangular facet is occluded and is not visible; if the ray does not intersect with other triangular facets, the triangular facet is visible to the infrared camera. It should be noted that the specific implementation of the infrared visibility detection is not limited to the above ray tracing method; depth buffering methods or other visibility determination methods can also be used, and this application does not impose any restrictions on this.

[0038] The known temperature nodes are graph nodes whose corresponding triangular faces are visible to the infrared camera, and their temperature values ​​can be obtained by measuring the infrared camera. The nodes to be estimated are graph nodes whose corresponding triangular faces are not visible to the infrared camera, and their temperature values ​​need to be estimated through subsequent temperature propagation.

[0039] The labeled temperature graph structure can refer to a physical partition cross-component edge graph structure that labels the temperature node types, and can contain known temperature nodes and nodes to be estimated.

[0040] S60. Based on the adjacency relationship in the physical partition cross-component edge graph structure, perform temperature propagation estimation on each node to be estimated in the marked temperature graph structure to obtain the temperature estimation value corresponding to each node to be estimated.

[0041] Temperature propagation estimation is a process based on the adjacency relationship between nodes in a graph structure. It involves propagating the temperature value of a known temperature node along its adjacent edges to the node to be estimated, and then calculating the estimated temperature value of the node to be estimated.

[0042] In the temperature propagation estimation process, the influence weight of the node with known temperature can be determined by the graph distance and label similarity (which may include component type label similarity and material type label similarity) between graph nodes. The estimated temperature value of the node to be estimated is then obtained by weighted summation. The specific implementation of the temperature propagation estimation process can be described in detail in subsequent embodiments.

[0043] In this embodiment, a three-dimensional mesh model of the target object is obtained, and each triangular facet in the three-dimensional mesh model is used as a graph node in the graph structure. A mesh topology graph structure is constructed based on the spatial adjacency relationship between each triangular facet to obtain an initial graph structure. Further, based on the component segmentation information of the target object, physical partitioning and labeling processing is performed on each graph node in the initial graph structure to obtain a physical partitioning graph structure. Cross-component edge processing is then performed on the adjacent edges in the physical partitioning graph structure to obtain a physical partitioning cross-component edge graph structure. Thus, based on the infrared visibility detection results of the target object, temperature node marking is performed on the graph nodes in the physical partitioning cross-component edge graph structure to obtain a marked temperature graph structure including known temperature nodes and nodes to be estimated. Furthermore, based on the adjacency relationship in the physical partitioning cross-component edge graph structure, temperature propagation estimation is performed on each node to be estimated in the marked temperature graph structure to obtain the temperature estimation value corresponding to each node to be estimated. This helps improve the accuracy of temperature estimation for invisible areas of the three-dimensional temperature field.

[0044] In one possible implementation, when performing cross-component edge processing, adjacent edges can be judged and filtered based on the component type label corresponding to each graph node in the physical partition graph structure, so that the retained adjacent edges can reflect the actual heat conduction path. Specifically, a method for performing cross-component edge processing on adjacent edges in the physical partition graph structure to obtain a physical partition cross-component edge graph structure may include: A1. Obtain the component type label corresponding to each graph node in the physical partition graph structure; A2. For each adjacent edge in the physical partition graph structure, perform component type label judgment processing on the graph nodes at both ends of the adjacent edge, and after traversing each adjacent edge, obtain the physical partition cross-component edge graph structure. Specifically, for each adjacent edge in the physical partitioning graph structure, the component type label determination process for the graph nodes at both ends of the adjacent edge is performed, including: A21. Obtain the first adjacent edge currently being processed from the physical partitioning graph structure; A22. If the graph nodes at both ends of the first adjacent edge have the same component type label, then the first adjacent edge is retained. A23. If the graph nodes at both ends of the first adjacent edge have different component type labels, then perform physical contact judgment processing between the corresponding components of the graph nodes at both ends of the adjacent edge. A24. If there is physical contact between the components corresponding to the two end nodes of the first adjacent edge, then retain the first adjacent edge and label the first adjacent edge with a contact type label; A25. If there is no physical contact between the corresponding components of the graph nodes at both ends of the first adjacent edge, then delete the first adjacent edge.

[0045] Obtaining the component type label corresponding to each graph node in the physical partitioning graph structure provides input data for the subsequent step-by-step evaluation of each adjacent edge. The component type labels have already been labeled for each graph node during the physical partitioning annotation process, and each graph node carries a corresponding component type label.

[0046] For each adjacent edge in the physical partitioning graph structure, component type label determination is performed. Specifically, for each adjacent edge, the component type labels of its two endpoints are compared and determined. After traversing each adjacent edge, the cross-component edge graph structure of the physical partitioning is obtained. The specific determination process is as follows: The first adjacent edge currently being processed is obtained from the physical partitioning graph structure. The first adjacent edge can refer to the currently processed adjacent edge in the physical partitioning graph structure. Since the physical partitioning graph structure can contain multiple adjacent edges, they need to be processed one by one. It should be noted that "first" can refer to the currently processed edge, and is not limited to a specific adjacent edge; this application does not impose such a restriction. After performing component type label determination processing on an adjacent edge, the next adjacent edge can be obtained and processed until all adjacent edges in the physical partitioning graph structure have been processed.

[0047] If the two endpoints of a first adjacent edge have the same component type label, then that first adjacent edge is retained. The identical component type label at both endpoints indicates that the adjacent edge belongs to the same component. For example, if the component type label of both endpoints of the first adjacent edge is "iron core," then that adjacent edge can be considered a component-specific edge. Since components share the same internal material and continuous structure, heat conduction is smooth; therefore, this adjacent edge is retained to serve as a heat conduction path in subsequent temperature propagation estimations.

[0048] If the two endpoints of the first adjacent edge have different component type labels, then a physical contact determination process is performed between the corresponding components of the two endpoints. Different component type labels at the two endpoints indicate that the adjacent edge is a cross-component edge, meaning the two endpoints belong to different components. For example, if the component type label of one endpoint of the first adjacent edge is "iron core" and the component type label of the other endpoint is "low-voltage winding," then this adjacent edge can be considered a cross-component edge.

[0049] Physical contact determination processing refers to the process of determining whether there is direct contact between two components based on their relative positions in three-dimensional space. Specifically, physical contact determination processing can include at least one of the following methods: Method 1: Check if the two components share vertices or edges at the contact surface. If the triangular faces corresponding to the nodes at both ends of the first adjacent edge share vertices or edges in the 3D mesh model, and these two triangular faces belong to different components, then it can be determined that there is physical contact between the two components. For example, when assembling the iron core and the low-voltage winding, the winding wire is directly wound around the iron core column. The triangular faces on the surface of the iron core and the triangular faces on the surface of the winding share edges at the contact surface, so it can be determined that there is physical contact between the iron core and the low-voltage winding.

[0050] Method two involves calculating the minimum distance between the surfaces of the two components. If the minimum distance is less than a contact threshold, then physical contact between the two components can be determined. The contact threshold can be determined based on the assembly precision and manufacturing tolerances between the components; for example, the contact threshold can be set to a value between 0.1 mm and 1 mm. For instance, if the fuel tank and radiator are connected by a flange, and the minimum distance between the surfaces of the two components is less than the contact threshold, then physical contact between the fuel tank and radiator can be determined.

[0051] If there is physical contact between the components corresponding to the nodes at both ends of the first adjacent edge, then the first adjacent edge is retained and labeled with a contact type label. The reason for retaining this adjacent edge is that there is a thermal interface between different physically contacting components, and heat can be conducted through the contact surface. The contact type label can be used to identify the adjacent edge as a cross-component contact edge, distinguishing it from edges within the same component. In subsequent temperature propagation estimation, cross-component contact edges can use a different weighting calculation method than edges within the same component to reflect the physical characteristic that the thermal conduction efficiency of cross-component contact surfaces is generally lower than the thermal conduction efficiency within the same component. Specifically, the similarity of component type labels corresponding to cross-component contact edges can be determined based on the contact type label, as detailed in the subsequent temperature propagation estimation embodiments, which will not be repeated here.

[0052] If there is no physical contact between the components corresponding to the nodes at both ends of the first adjacent edge, then the first adjacent edge is deleted. There may be air gaps or insulation layers between different components that do not have physical contact, preventing heat from being transferred between them through conduction. For example, transformer oil fills the space between the iron core and the tank. The triangular facets on the surface of the iron core and the triangular facets on the inner surface of the tank are separated by a layer of transformer oil rather than in direct contact. Therefore, there is no physical contact between the two components, and the adjacent edge connecting the iron core node and the tank node can be deleted. Deleting such adjacent edges prevents them from participating in subsequent temperature propagation estimation, avoiding erroneous temperature propagation between nodes without heat conduction paths.

[0053] Optionally, the contact type label includes at least one of the following: welded connection label, bolted connection label, riveted connection label, snap-fit ​​connection label, and adhesive connection label. Different contact type labels correspond to different heat conduction efficiencies. In the subsequent label similarity calculation, the similarity value of the component type label corresponding to the welded connection label is greater than that of the component type label corresponding to the bolted connection label, and the similarity value of the component type label corresponding to the bolted connection label is greater than that of the component type label corresponding to the adhesive connection label.

[0054] It should be noted that the reason for performing physical contact judgment is that although different components may be spatially adjacent, if there is an air gap between them, heat cannot be directly conducted through the air gap. Therefore, it is necessary to determine whether physical contact exists to decide whether to retain the adjacent edge. The above physical contact judgment is based on the following: For mechanical assemblies, physical contact between different components usually manifests as shared boundaries (such as shared vertices or edges) or surface compression after being connected by fasteners (such as contact surfaces caused by bolted connections). Therefore, the existence of physical contact can be determined by judging whether a shared boundary exists or whether the spatial distance is less than a contact threshold.

[0055] It should be noted that by traversing each adjacent edge in the physical partition graph structure and processing them one by one in the manner described above, the physical partition cross-component edge graph structure can be obtained.

[0056] In this embodiment, by obtaining the component type label corresponding to each graph node in the physical partition graph structure and performing component type label judgment processing on each adjacent edge, edges of the same component are retained, and edges across components are further judged for physical contact and then decided to retain or delete them. This can result in a physical partition cross-component edge graph structure that only contains the actual heat conduction path. This is beneficial to avoid the erroneous propagation of temperature values ​​between nodes that do not have heat conduction paths in subsequent temperature propagation estimation, thereby improving the physical consistency and accuracy of temperature estimation.

[0057] In one possible implementation, before performing temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, temperature data can be collected by physical temperature sensors deployed on the surface of the target object, and the collected temperature data can be bound to the corresponding graph node in the graph structure as a fixed temperature reference node in the temperature propagation estimation process. Specifically, a sparse constraint anchor point binding method may include: B1. Obtain the temperature measurement value collected by the physical temperature sensor deployed on the surface of the target object and the spatial position corresponding to the physical temperature sensor; B2. Based on the spatial location, determine the graph node corresponding to the physical temperature sensor from the physical partition cross-component edge graph structure; B3. Assign the temperature measurement value to the graph node corresponding to the physical temperature sensor, and mark the corresponding graph node as a constraint anchor point; the constraint anchor point serves as a fixed temperature reference node in the temperature propagation estimation process, and the temperature value remains unchanged in the temperature propagation estimation process.

[0058] Physical temperature sensors can refer to contact temperature measuring devices that are placed at specific locations on the surface of a target object to directly measure the temperature of the target object's surface. Types of physical temperature sensors may include PT100 platinum resistance temperature sensors, thermocouple temperature sensors, or thermistor temperature sensors, etc., and this application does not impose any limitations on these types.

[0059] The number of physical temperature sensors can be small and their distribution sparse, mainly placed in areas that cannot be directly observed by infrared cameras or at temperature-critical locations. For example, in power transformers, physical temperature sensors can be placed at critical locations that infrared cameras may not be able to directly observe, such as the upper part of the winding near the core column, the bottom of the inner wall of the oil tank, or the radiator inlet. This application does not limit the placement location and number of physical temperature sensors.

[0060] Temperature measurements refer to the real-time temperature data collected by a physical temperature sensor. Because the physical temperature sensor is in direct contact with the surface of the target object, the temperature measurement reflects the true surface temperature at the sensor's location, and its accuracy can be higher than the temperature value indirectly obtained by an infrared camera through radiation measurement. Spatial location refers to the three-dimensional coordinates of the physical temperature sensor on the target object's surface, used to subsequently map the physical temperature sensor to graph nodes in the physical partition cross-component edge graph structure.

[0061] By acquiring the temperature measurements collected by physical temperature sensors deployed on the surface of the target object and the corresponding spatial location of the physical temperature sensors, the actual temperature data at a specific location on the surface of the target object can be obtained, providing input data for the subsequent binding of constraint anchor points.

[0062] Based on spatial location, the graph node corresponding to the physical temperature sensor is determined from the cross-component edge graph structure of the physical partition. This allows the position of the physical temperature sensor in three-dimensional space to be mapped to the graph structure, establishing the correspondence between the physical temperature sensor and the graph node.

[0063] Specifically, based on the spatial location of the physical temperature sensor, the graph node closest to that location can be found in the cross-component edge graph structure of the physical partition, and this graph node is identified as the graph node corresponding to the physical temperature sensor. The triangular facet corresponding to the graph node has a definite position in three-dimensional space, which can be represented by the centroid coordinates or vertex coordinates of the triangular facet. Therefore, the spatial location of the physical temperature sensor can be compared with the centroid coordinates of the triangular facet corresponding to each graph node, and the graph node with the smallest distance can be selected as the corresponding graph node.

[0064] It should be noted that the matching method between the physical temperature sensor and the graph node is not limited to the spatial nearest neighbor search described above; other methods can also be used. For example, the spatial location of the physical temperature sensor can be projected onto the surface of the 3D mesh model to determine which triangular facet it falls on, and the graph node corresponding to that triangular facet can be identified as the corresponding graph node. This application does not impose any restrictions on this.

[0065] By assigning the temperature measurement value to the graph node corresponding to the physical temperature sensor and marking the corresponding graph node as a constraint anchor point, the temperature data collected by the physical temperature sensor can be bound to the graph node in the graph structure, making the graph node a fixed reference point in the temperature propagation estimation process.

[0066] Constraint anchor points can refer to graph nodes marked as fixed temperature reference nodes. The difference between constraint anchor points and known temperature nodes obtained from infrared visibility detection is that the temperature values ​​of known temperature nodes come from the radiation measurements of infrared cameras, while the temperature values ​​of constraint anchor points come from the direct contact measurements of physical temperature sensors, resulting in higher accuracy and being unaffected by infrared obstruction.

[0067] The temperature value of the constraint anchor point remains unchanged during the temperature propagation estimation process; that is, the temperature value of the constraint anchor point does not change with each estimation iteration. It should be noted that the constraint anchor point, as a fixed temperature reference node in the temperature propagation estimation process, can provide a stable reference benchmark for the temperature propagation of surrounding nodes to be estimated, preventing the estimation results from diverging during iteration.

[0068] By deploying sparse physical temperature sensors on the surface of the target object, known temperature data can be supplemented in invisible areas that cannot be covered by infrared cameras, thereby improving the accuracy and reliability of temperature propagation estimation.

[0069] In this embodiment, by acquiring the temperature measurement values ​​and corresponding spatial positions collected by physical temperature sensors deployed on the surface of the target object, the corresponding graph node is determined from the physical partition cross-component edge graph structure based on the spatial position, and the temperature measurement value is assigned to the graph node as a constraint anchor point. This ensures that the constraint anchor point, as a fixed temperature reference node in the temperature propagation estimation process, maintains a constant temperature value during the estimation process. This is beneficial for supplementing known temperature data in invisible areas that cannot be covered by infrared cameras, providing a stable reference benchmark for temperature propagation estimation, thereby improving the accuracy and reliability of temperature estimation.

[0070] In one possible implementation, when performing temperature propagation estimation, the influence weight can be determined based on the adjacency relationships in the cross-component edge graph structure of the physical partition, combined with the graph distance and label similarity between the node to be estimated and its neighboring known temperature nodes. The estimated temperature value of the node to be estimated is then obtained by weighted summation. Specifically, a method for performing temperature propagation estimation on each node to be estimated in the labeled temperature graph structure based on the adjacency relationships in the cross-component edge graph structure of the physical partition, to obtain the estimated temperature value corresponding to each node to be estimated, may include: C1. Obtain the known temperature node of the first node to be estimated in the current processing from the marked temperature map structure; C2. Based on the adjacency relationship in the cross-component edge graph structure of the physical partition, calculate the graph distance between the first node to be estimated and each known temperature node to obtain the graph distance; C3. Based on the graph distance and the preset jump threshold, determine the neighboring known temperature nodes of the first node to be estimated from the known temperature nodes; C4. Based on the component type label and material type label corresponding to the first node to be estimated and each neighboring known temperature node, calculate the label similarity between the first node to be estimated and each neighboring known temperature node to obtain the label similarity. C5. Based on the graph distance and the label similarity, determine the influence weight between the first node to be estimated and each neighboring known temperature node; C6. Based on the influence weight, the temperature values ​​of the known temperature nodes in the neighborhood are weighted and summed to obtain the estimated temperature value of the first node to be estimated. C7. Traverse each node to be estimated in the marked temperature map structure to obtain the temperature estimate value corresponding to each node to be estimated.

[0071] The first node to be estimated can refer to the node currently being processed in the marked temperature map structure. Since the marked temperature map structure can contain multiple nodes to be estimated, and temperature propagation estimation needs to be performed one by one, it should be noted that the term "first" can be used to refer to the currently processed node to be estimated, and is not limited to a specific node to be estimated. This application does not impose any restrictions on this.

[0072] A known temperature node can refer to a graph node in a labeled temperature graph structure that has a known temperature value. Known temperature nodes can include those obtained through infrared visibility detection and those bound by constraint anchors.

[0073] For example, in a power transformer, if the triangular facet corresponding to the first node to be estimated is located on the back of the tank and is not visible to the infrared camera, then the following known temperature nodes may exist around the node to be estimated: known temperature nodes directly connected to the node to be estimated via one adjacent edge (e.g., the triangular facet corresponding to the known temperature node is located on the side of the tank, visible to the infrared camera, and the temperature value is obtained by the infrared camera measurement), and constraint anchor points reachable from the node to be estimated via three adjacent edges (e.g., the graph node corresponding to the constraint anchor point is bound to the temperature measurement value of a physical temperature sensor deployed near the back of the tank). Both the aforementioned known temperature nodes and constraint anchor points can serve as known temperature nodes for the node to be estimated and participate in subsequent graph distance calculations and neighborhood filtering.

[0074] Graph distance refers to the number of adjacent edges traversed by the shortest path between the first node to be estimated and the known temperature node in the cross-component edge graph structure of a physical partition. The neighboring known temperature node refers to a known temperature node determined from the known temperature nodes based on the graph distance and a preset hop count threshold. Specifically, known temperature nodes with a graph distance less than or equal to the preset hop count threshold can be selected as neighboring known temperature nodes. The hop count refers to the number of adjacent edges traversed from one graph node to another. The preset hop count threshold can be determined based on the mesh density and temperature distribution characteristics of the target object; this application does not impose any restrictions on this. It is understood that the smaller the graph distance, the closer the two nodes are topologically, and the greater the influence of the temperature value of the known temperature node on the node to be estimated.

[0075] It should be noted that if no neighboring nodes with known temperatures exist within the preset hop count threshold range for the first node to be estimated, the neighborhood search range can be expanded and the preset hop count threshold increased to find known temperature nodes at greater distances. If no neighboring nodes with known temperatures are found after expanding the search range, the node to be estimated can be marked as an unestimateable node and assigned a corresponding confidence level label. This confidence level label can be used to indicate the reliability of the temperature estimate for the node to be estimated.

[0076] For example, when the triangular facet corresponding to a node to be estimated is located in a large self-occupied area on the surface of a target object, and no physical temperature sensor is deployed in this area, causing the node to be estimated to still be unable to obtain a known temperature node in the neighborhood within the expanded search range, the confidence level of the node to be estimated can be set to a lower level to indicate that the estimation result of the node is for reference only.

[0077] It should also be noted that the above processing method is not limited to expanding the search range or marking nodes that cannot be estimated. It may also include grouping nodes with known temperatures according to physical partitions or material types and performing interpolation estimation within the same group. This application does not limit this.

[0078] Specifically, the graph distance can be calculated using a breadth-first search method. It should be noted that when adjacent edges in the physical partition cross-component edge graph structure have weights, the graph distance can also be calculated using Dijkstra's shortest path algorithm. The weights of adjacent edges can be determined based on the contact thermal conduction between the components at both ends of the adjacent edge; this application does not impose any restrictions on this. It should also be noted that since the physical partition cross-component edge graph structure has undergone cross-component edge processing, removing adjacent edges without physical contact, the graph distance reflects the number of hops on the actual heat conduction path between two nodes, rather than simply the spatial distance.

[0079] For example, if the triangular facet corresponding to the first node to be estimated is located on the iron core, and the triangular facet corresponding to a certain known temperature node is located on the inner wall of the oil tank, the straight-line distance between the two in three-dimensional space may be relatively close. However, since there is no physical contact between the iron core and the oil tank, the direct adjacent edges between the two have been deleted in the cross-component edge processing. Therefore, the graph distance between the two is not 1 hop. Heat needs to be conducted along the connection path of the components that actually have physical contact, that is, the graph distance between the first node to be estimated with the triangular facet located on the iron core and the known temperature node located on the inner wall of the oil tank is greater than 1 hop.

[0080] For example, if the first node to be estimated and a known temperature node are located within the same component and are directly connected by one adjacent edge, the graph distance between them is 1 hop; if the first node to be estimated and a known temperature node require two adjacent edges to reach each other, the graph distance between them is 2 hops. In other words, the graph distance reflects the number of adjacent edges traversed by heat along the actual heat conduction path, and may differ from the straight-line distance between the two nodes in three-dimensional space.

[0081] Label similarity refers to a numerical value used to quantify the degree of similarity between two graph nodes in terms of part type and material type. It can include part type label similarity and material type label similarity. Optionally, the calculation process for label similarity can be found in the following formula: in, Let i be the label similarity between the node to be estimated and the neighboring node j with known temperature; To estimate the similarity of component type labels between node i and its neighboring node j with known temperatures, when the component type labels of node i and node j are the same, The value can be 1, when the component type labels of node i and node j are different. This can be determined based on the contact type label of the adjacent edges between node i and node j. Optional, such as those corresponding to welded connections. The value can be set to the first preset value, corresponding to the bolt connection. The value can be a second preset value, where the first preset value is greater than the second preset value, and both the first and second preset values ​​are greater than 0 and less than 1. It should be noted that the above welding and bolting connections are illustrative examples; other contact types (such as riveting, snap-fit ​​connections, adhesive bonding, etc.) correspond to... The value can be determined based on the thermal conductivity characteristics of various contact types, and this application does not impose any restrictions on it.

[0082] in, For material type label similarity, when node i and node j have the same material type label, The value can be 1, when the material type labels of node i and node j are different. The thermal conductivity of the material corresponding to node i can be determined based on the ratio of the thermal conductivity of the material corresponding to node j. It should be noted that each triangular facet can correspond to a material type label, which can be the primary material of the corresponding area on the surface of the target object. When the area corresponding to a certain triangular facet involves multiple materials, the material with the largest area proportion can be determined as the material type label of that triangular facet, or the triangular facet can be divided into multiple sub-triangular facets, with each sub-triangular facet corresponding to a different material. This application does not impose any limitations on this.

[0083] in, and The weighting coefficients α and β satisfy α + β = 1, with α greater than β. This means the weight of the component type label is greater than the weight of the material type label, because the influence of component attribution on the heat conduction path can be greater than that of material differences. It should be noted that the specific values ​​of α and β can be determined based on the components and material characteristics of the target object; this application does not impose any restrictions on this. Optionally, when there are significant differences in heat conduction between different components of the target object, α can be taken as a larger value, allowing the component type label similarity to account for a larger proportion of the label similarity; when there are significant differences in material between different components of the target object, but the influence of component attribution on heat conduction is relatively small, β can be taken as a larger value. The specific values ​​of α and β can be determined through experimental calibration or numerical optimization methods; this application does not impose any restrictions on this.

[0084] Specifically, when node i and node j have different material type labels, the material type label similarity is... The calculation formula can be found below: in, The material type label similarity between node i to be estimated and neighboring node j with known temperature can be calculated. It can represent taking and The smaller of the two thermal conductivity values; The thermal conductivity of the material corresponding to node i can be... ， It can be the thermal conductivity of the material corresponding to node j; It can represent taking and The larger of the two thermal conductivity values.

[0085] It should be noted that thermal conductivity refers to a material's ability to conduct heat, and different materials have different thermal conductivity. The closer the value is to 1, the closer the thermal conductivity of the two materials is. The smaller the value, the greater the difference in thermal conductivity; when the two materials are exactly the same, min and max are equal, and the calculation result is equal to 1.

[0086] Two materials with similar thermal conductivity have more similar thermal conduction properties, and their material type label similarity can be higher. For example, copper has a thermal conductivity of approximately 401 W / (m·K), and aluminum has a thermal conductivity of approximately 237 W / (m·K). When node i corresponds to copper and node j corresponds to aluminum, A possible value is 237 / 401, approximately 0.59. It should be noted that the specific value of the thermal conductivity can be determined by referring to a material thermophysical property handbook; this application does not impose any restrictions on it.

[0087] It should be noted that the above material type label similarity calculation uses thermal conductivity as the material's thermophysical parameter, suitable for steady-state or quasi-steady-state temperature field estimation scenarios. In transient temperature field estimation scenarios, thermal diffusivity can also be used instead of thermal conductivity for calculating material type label similarity. Thermal diffusivity refers to an indicator of a material's ability to homogenize temperature in unsteady-state heat conduction, and can be calculated based on thermal conductivity, density, and specific heat capacity. This application does not restrict the selection of material thermophysical parameters. It should also be noted that since thermal conductivity can change with temperature, and The thermal conductivity of the corresponding material can be taken at a preset reference temperature, which can be the ambient temperature of the target object or the estimated operating temperature. In multiple iterative processing rounds, and The temperature estimate obtained from the previous iteration can be updated to improve the accuracy of the calculation of material type label similarity, and this application does not impose any restrictions on this.

[0088] Influence weight refers to the degree of influence of neighboring nodes with known temperatures on the estimated temperature value of the node to be estimated. Optionally, the calculation process for influence weight can be found in the following formula: in, Let be the influence weight between node i to be estimated and neighboring node j with known temperature; Let i be the label similarity between the node to be estimated and the neighboring node j with known temperature; Let i be the graph distance between the node to be estimated and the neighboring node j with known temperature. This is the attenuation coefficient, which can be used to control the degree to which graph distance attenuates the influence of the weights. Specifically, A value greater than 0 can be used to ensure that the greater the graph distance, the smaller the impact on the weight. The specific value can be selected by combining the mesh density and the thermal inertia characteristics of the object, for example, It can take values ​​between 0.5 and 2.0. When When the value is large, the attenuation effect of graph distance on the influence weight can be stronger, meaning that the influence of known temperature nodes that are farther away can attenuate more quickly; when When the value is small, the decay effect of graph distance on the weight can be relatively gradual. It should be noted that... The specific values ​​are not limited to the above range, and this application does not impose any restrictions on them.

[0089] The above formula reflects the principle that the smaller the graph distance and the higher the label similarity, the greater the influence weight. That is, the closer the nodes are in the topology and the more similar their physical properties are, the greater the influence of their temperature values ​​on the nodes to be estimated.

[0090] Optional, the calculation process for the weighted summation can be found in the following formula: in, The temperature estimate for node i is given. Let be the influence weight between node i to be estimated and neighboring node j with known temperature; Let be the temperature value of the known temperature node j in the neighborhood; the summation symbol Σ represents the summation of the known temperature nodes j in the neighborhood of the first node i to be estimated.

[0091] It should be noted that, due to the normalization process used in the weighted summation, the estimated temperature value of the node to be estimated can fall within the range of the temperature values ​​of the known temperature nodes in the neighborhood. That is, the estimated temperature value can be no greater than the maximum temperature value among the known temperature nodes in the neighborhood, and no less than the minimum temperature value among the known temperature nodes in the neighborhood. For areas close to the heat source and obstructed, their true temperature may be higher than the temperature values ​​of all known temperature nodes in the neighborhood obtained by infrared visibility detection. In this case, if physical temperature sensors are deployed in the area as constraint anchors, the measured temperature values ​​of the constraint anchors can be higher than the temperature values ​​obtained by infrared detection, thus allowing the estimated temperature value to reflect the higher true temperature of the area. If no physical temperature sensors are deployed in the area, the subsequent physical consistency verification step can combine the heat source location information to identify that the estimated temperature value of the node to be estimated may be too low, and perform corresponding adjustments.

[0092] The weighted average calculation ensures that the estimated temperature of the node to be estimated is influenced by the combined effects of all known temperature nodes in its neighborhood, with nodes having larger influence weights contributing more. If the first node to be estimated has a constraint anchor point as a known temperature node in its neighborhood, the fixed temperature value of the constraint anchor point can participate in the weighted summation calculation, and the temperature value of the constraint anchor point remains unchanged throughout multiple iterations. The calculation method for the constraint anchor point and the known temperature node obtained by infrared visibility detection in the weighted summation can be the same, but the temperature value of the constraint anchor point is the actual measured value from the physical sensor, which has higher reliability. Optionally, a higher reliability coefficient can be assigned to the influence weight corresponding to the constraint anchor point to reflect that the temperature measurement reliability of the constraint anchor point is higher than that of the temperature value obtained by infrared detection. It should be noted that whether to assign a higher reliability coefficient to the constraint anchor point can be determined according to the actual application requirements, and this application does not impose any restrictions on this.

[0093] Traverse each node to be estimated in the marked temperature map structure, and calculate the estimated temperature value for each node one by one according to steps C1 to C6. After the traversal is completed, the corresponding estimated temperature value can be obtained for all nodes to be estimated in the marked temperature map structure, so as to achieve a complete estimation of the temperature of the invisible area.

[0094] It should be noted that the temperature propagation estimation can be performed in multiple iterations. In the first iteration, the temperature propagation estimation of the node to be estimated can be performed solely based on the temperature values ​​of known temperature nodes and constraint anchor points. In subsequent iterations, the node to be estimated that has already been estimated in the previous round can participate in the temperature propagation estimation of the node to be estimated in the current round as a known temperature node, thereby gradually propagating the temperature information from the known area to a more distant, invisible area. In each iteration, the temperature value of the constraint anchor point remains unchanged and does not change with each iteration update. Simultaneously, the thermal conductivity used in the material type label similarity calculation can be updated based on the temperature estimation value obtained from the previous iteration to improve the accuracy of the material type label similarity calculation.

[0095] It should be further noted that nodes that have completed their estimation are allowed to update their temperature estimates in subsequent iterations. That is, nodes that have completed their estimation in the previous round can update their own temperature estimates based on the newly added known temperature nodes in the current round, while participating in the temperature propagation estimation as known temperature nodes, until the iteration termination condition is met.

[0096] Optionally, the termination condition of the iteration is at least one of the following: all nodes to be estimated have obtained temperature estimates; the change in the temperature estimates of all nodes to be estimated is less than a preset change threshold in two consecutive iterations; the number of iterations reaches a preset maximum number of iterations. The preset change threshold can be determined according to the temperature measurement accuracy, for example, set to a value between 0.1℃ and 1℃.

[0097] In this embodiment, by obtaining the known temperature nodes of the first node to be estimated, calculating the graph distance and label similarity, determining the influence weight, and obtaining the temperature estimate by weighted summation, and obtaining all temperature estimates after traversing all nodes to be estimated, it is beneficial to combine graph topological distance and physical attribute similarity to estimate temperature propagation, making the estimation result more consistent with the actual heat conduction law, thereby improving the accuracy of temperature estimation in the invisible area of ​​the three-dimensional temperature field.

[0098] In one possible implementation, after obtaining the temperature estimate of the node to be estimated through temperature propagation estimation, a physical consistency check can be performed on the temperature estimate to correct unreasonable estimation results and obtain a corrected temperature estimate. Specifically, a physical consistency check method may include: D1. Calculate the temperature gradient between adjacent graph nodes based on the adjacency relationship in the physical partition cross-component edge graph structure and the temperature estimate of the node to be estimated. D2. Based on the temperature gradient, perform a physical reasonable range judgment process for the temperature gradient to obtain the temperature gradient judgment result; D3. Based on the location of the heat source of the target object, perform temperature estimation and heat source distribution pattern judgment processing to obtain the heat source distribution pattern judgment result; D4. If the temperature gradient judgment result indicates that the temperature gradient exceeds the physical reasonable range, or the heat source distribution law judgment result indicates that the temperature estimate distribution does not conform to the heat source distribution law, then the adjacent edges in the physical partition cross-component edge graph structure are adjusted to obtain the adjusted graph structure. D5. Based on the adjusted graph structure, re-estimate the temperature propagation to obtain the corrected temperature estimate.

[0099] The temperature gradient can refer to the temperature change per unit spatial distance between two adjacent graph nodes. Optionally, the calculation process for the temperature gradient can be found in the following formula: in, This can be the temperature gradient corresponding to the adjacent edge between node i and node j; This can be the temperature value of node i. It can be the temperature value of node j; when both node i and node j are nodes to be estimated. and These can be the corresponding temperature estimates, when one of nodes i and j is the node to be estimated and the other is a node with a known temperature. and These can be the corresponding estimated temperature value and the known temperature value, respectively; It can be the three-dimensional spatial distance between the centroids of the triangular faces corresponding to nodes i and j, where the centroid of the triangular face can refer to the average of the coordinates of the three vertices of the triangular face; |·| can represent the operation of taking the absolute value.

[0100] It should be noted that here This refers to the three-dimensional spatial distance, compared to the distance shown in the diagram in the aforementioned embodiment. Unlike graphs, graph distance reflects the number of hops on a topological path, while... It reflects the straight-line distance between the centroids of the two triangular facets in three-dimensional physical space.

[0101] The physically reasonable range refers to the reasonable temperature gradient interval determined based on the thermophysical properties of the target object's material and its operating conditions. Specifically, according to Fourier's law, the temperature gradient is related to heat flux density and the material's thermal conductivity, and can be expressed as | T|=q / k, where q is the heat flux density and k is the thermal conductivity. Therefore, the upper limit of the physically reasonable range can be determined based on the maximum expected heat flux density of the target object and the corresponding material's thermal conductivity. It is understood that different materials have different upper limits for temperature gradients at the same heat flux density; materials with lower thermal conductivity can tolerate larger temperature gradients, while materials with higher thermal conductivity can have smaller upper limits for temperature gradients. The upper and lower limits of the physically reasonable range can be determined based on factors such as the target object's material properties, rated power, and ambient temperature; this application does not impose any restrictions on these.

[0102] Temperature gradient assessment results can be used to indicate whether a temperature gradient exceeds a physically reasonable range. For example, the temperature gradient assessment results can include two types: "exceeds the physically reasonable range" and "does not exceed the physically reasonable range." When the temperature gradient of an adjacent edge is greater than the upper limit of the physically reasonable range, the temperature gradient assessment result indicates that the temperature gradient exceeds the physically reasonable range; when the temperature gradient of an adjacent edge is less than or equal to the upper limit of the physically reasonable range, the temperature gradient assessment result indicates that the temperature gradient does not exceed the physically reasonable range.

[0103] The location of a heat source can refer to the location of a component within a target object that generates heat. For example, in a power transformer, the heat source can include the core (which generates heat due to core losses) and the windings (which generate heat due to winding losses). The location of the heat source can include the spatial positions of the core and windings in a three-dimensional mesh model. It should be noted that the location of the heat source can be determined based on the design drawings or operating parameters of the target object, and this application does not impose any restrictions on this.

[0104] The heat source distribution pattern refers to the relationship between the surface temperature distribution of a target object and the location of the heat source. It can be understood that areas closer to the heat source tend to have higher temperatures, while areas farther away tend to have lower temperatures. Specifically, when determining the heat source distribution pattern for temperature estimation, one can compare the estimated temperature value of the node to be estimated with the spatial distance from that node to the nearest heat source to see if the relationship conforms to the rule that temperature decreases with distance.

[0105] For example, in a power transformer, if the triangular facet corresponding to a node to be estimated is located at the top of the tank, away from the core and windings, and the estimated temperature of the node to be estimated is 80°C, while the temperature of a known temperature node near the windings is 55°C, then the heat source distribution law judgment result can indicate that the temperature estimated value distribution of the node to be estimated does not conform to the heat source distribution law, because the temperature of the area far from the heat source should not be higher than the temperature of the area near the heat source.

[0106] Adjustment processing may include, but is not limited to, weight adjustment processing or edge removal processing. Weight adjustment processing can refer to reducing the influence weight of adjacent edges whose temperature gradients exceed physically reasonable limits. That is, the influence weight between the first node to be estimated and the neighboring nodes with known temperatures, connected by adjacent edges where the temperature gradient exceeds the physically reasonable range. The reduction process is performed to minimize the impact of the known temperature nodes in the neighborhood on the temperature estimate of the first node to be estimated. Edge deletion can refer to removing the adjacent edge from the physical partition cross-component edge graph structure, so that the first node to be estimated at both ends of the adjacent edge and the known temperature nodes in the neighborhood no longer participate in subsequent temperature propagation estimations through that adjacent edge.

[0107] Specifically, for adjacent edges where the temperature gradient assessment result indicates that the temperature gradient exceeds the physically reasonable range, the influence weight between the first node to be estimated and the known temperature node can be reduced. Alternatively, the adjacent edge can be removed from the physical partition cross-component edge graph structure. For example, if the estimated temperature of the first node to be estimated is 85℃, and the temperature of the adjacent known temperature node is 40℃, and the three-dimensional spatial distance between the centroids of their corresponding triangular faces is 0.01 meters, then the temperature gradient corresponding to this adjacent edge is |85-40| / 0.01 = 4500℃ / m. If the upper limit of the physically reasonable range is 3000℃ / m, then the temperature gradient judgment result indicates that the temperature gradient 4500℃ / m exceeds the physically reasonable range. In this case, the influence weight corresponding to the adjacent edge can be reduced, or the adjacent edge can be removed from the physical partition cross-component edge graph structure. It should be noted that the specific adjustment methods are not limited to reducing weight or deleting edges as described above, and this application does not impose any restrictions on this.

[0108] The adjusted graph structure refers to the graph structure obtained after adjusting some adjacent edges in the cross-component edge graph structure of the physical partition. After the adjustment is completed, temperature propagation can be re-estimated based on the adjusted graph structure to obtain a corrected temperature estimate. It is understandable that, since the adjustment may change the adjacency relationships or affect the weights in the graph structure, the re-estimated corrected temperature estimate may be more consistent with the actual heat conduction laws than the original temperature estimate.

[0109] Optionally, before re-estimating the temperature propagation based on the adjusted graph structure, the temperature estimates of all nodes to be estimated are reset to an unknown state, and only the temperature values ​​of known temperature nodes and constraint anchor points are retained as known temperature data. All steps of the temperature propagation estimation are then re-executed to obtain the corrected temperature estimates.

[0110] In this embodiment, by calculating the temperature gradient between adjacent graph nodes, judging the physical reasonable range of the temperature gradient, and judging the heat source distribution law of the temperature estimate, the adjacent edges whose temperature gradient exceeds the physical reasonable range or does not conform to the heat source distribution law are adjusted. The temperature propagation is re-estimated based on the adjusted graph structure, which helps to eliminate abnormal estimation results that do not conform to physical laws, and makes the corrected temperature estimate more consistent with the actual heat conduction characteristics, thereby further improving the accuracy and reliability of temperature estimation in the invisible area of ​​the three-dimensional temperature field.

[0111] For examples consistent with the above embodiments, please refer to... Figure 3 , Figure 3 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application, such as... Figure 3 As shown, it includes a processor, an input device, an output device, and a memory, which are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions. The program includes instructions for performing the following steps. Obtain the 3D mesh model of the target object; Each triangular facet in the three-dimensional mesh model is used as a graph node in the graph structure. A mesh topology graph structure is constructed based on the spatial adjacency relationship between each triangular facet to obtain the initial graph structure. Based on the component segmentation information of the target object, each graph node in the initial graph structure is physically partitioned and labeled to obtain a physical partition graph structure; Perform cross-component edge processing on the adjacent edges in the physical partition graph structure to obtain a physical partition cross-component edge graph structure; Based on the infrared visibility detection results of the target object, temperature nodes are marked on the graph nodes in the physical partition cross-component edge graph structure to obtain a marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated. Based on the adjacency relationship in the physical partition cross-component edge graph structure, temperature propagation estimation is performed on each node to be estimated in the marked temperature graph structure to obtain the temperature estimation value corresponding to each node to be estimated.

[0112] The above mainly describes the solutions of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, the terminal includes the corresponding hardware structure and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0113] This application embodiment can divide the terminal into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0114] For those consistent with the above, please refer to Figure 4 , Figure 4 This application provides a schematic diagram of a three-dimensional temperature estimation device based on mesh topology and physical partitioning, as an embodiment of the present application. Figure 4 As shown, the device includes: Acquisition unit 101 is used to acquire the three-dimensional mesh model of the target object; Construction unit 102 is used to take each triangular facet in the three-dimensional mesh model as a graph node in the graph structure, and construct a mesh topology graph structure according to the spatial adjacency relationship between each triangular facet to obtain an initial graph structure; The first processing unit 103 is used to perform physical partitioning and labeling processing on each graph node in the initial graph structure according to the component segmentation information of the target object, so as to obtain a physical partitioning graph structure. The second processing unit 104 is used to perform cross-component edge processing on the adjacent edges in the physical partition graph structure to obtain a physical partition cross-component edge graph structure. The third processing unit 105 is used to mark the graph nodes in the physical partition cross-component edge graph structure with temperature nodes according to the infrared visibility detection results of the target object, so as to obtain a marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated. The fourth processing unit 106 is used to perform temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, so as to obtain the temperature estimation value corresponding to each node to be estimated.

[0115] In one possible implementation, the second processing unit 104 is configured to perform cross-component edge processing on the adjacent edges in the physical partitioning graph structure to obtain a physical partitioning cross-component edge graph structure, specifically for: Obtain the component type label corresponding to each graph node in the physical partition graph structure; For each adjacent edge in the physical partition graph structure, the component type label of the graph nodes at both ends of the adjacent edge is determined. After traversing each adjacent edge, the physical partition cross-component edge graph structure is obtained. The second processing unit is used to determine the component type label of the graph nodes at both ends of each adjacent edge in the physical partition graph structure, specifically for: Obtain the first adjacent edge currently being processed from the physical partitioning graph structure; If the graph nodes at both ends of the first adjacent edge have the same component type label, then the first adjacent edge is retained; If the graph nodes at both ends of the first adjacent edge have different component type labels, then physical contact determination processing is performed between the corresponding components of the graph nodes at both ends of the adjacent edge. If there is physical contact between the components corresponding to the two graph nodes at the two ends of the first adjacent edge, then the first adjacent edge is retained and a contact type label is marked on the first adjacent edge; If there is no physical contact between the corresponding components of the graph nodes at both ends of the first adjacent edge, then delete the first adjacent edge.

[0116] In one possible implementation, the fourth processing unit 106, before performing temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, is further configured to: Acquire the temperature measurement value collected by the physical temperature sensor deployed on the surface of the target object and the spatial position corresponding to the physical temperature sensor; Based on the spatial location, determine the graph node corresponding to the physical temperature sensor from the physical partition cross-component edge graph structure; The temperature measurement value is assigned to the graph node corresponding to the physical temperature sensor, and the corresponding graph node is marked as a constraint anchor point; the constraint anchor point serves as a fixed temperature reference node in the temperature propagation estimation process, and the temperature value remains unchanged in the temperature propagation estimation process.

[0117] In one possible implementation, the fourth processing unit 106 is used to perform temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, to obtain the temperature estimation value corresponding to each node to be estimated, specifically for: From the marked temperature map structure, obtain the known temperature node of the first node to be estimated currently being processed; Based on the adjacency relationships in the cross-component edge graph structure of the physical partition, the graph distance between the first node to be estimated and each known temperature node is calculated to obtain the graph distance; Based on the graph distance and the preset jump threshold, the neighboring known temperature nodes of the first node to be estimated are determined from the known temperature nodes; based on the component type label and material type label corresponding to the first node to be estimated and each neighboring known temperature node, the label similarity between the first node to be estimated and each neighboring known temperature node is calculated to obtain the label similarity. Based on the graph distance and the label similarity, the influence weight between the first node to be estimated and each neighboring known temperature node is determined; Based on the influence weights, the temperature values ​​of the known temperature nodes in the neighborhood are weighted and summed to obtain the estimated temperature value of the first node to be estimated. By traversing each node to be estimated in the marked temperature map structure, the estimated temperature value corresponding to each node to be estimated is obtained.

[0118] In one possible implementation, after obtaining the temperature estimate corresponding to each of the nodes to be estimated, the fourth processing unit 106 is further configured to: Based on the adjacency relationship in the physical partition cross-component edge graph structure and the temperature estimate of the node to be estimated, calculate the temperature gradient between adjacent graph nodes; Based on the temperature gradient, a physical reasonable range of the temperature gradient is determined to obtain the temperature gradient determination result. Based on the location of the heat source of the target object, the heat source distribution pattern is determined by temperature estimation, and the heat source distribution pattern determination result is obtained. If the temperature gradient judgment result indicates that the temperature gradient exceeds the physical reasonable range, or the heat source distribution law judgment result indicates that the temperature estimate distribution does not conform to the heat source distribution law, then the adjacent edges in the physical partition cross-component edge graph structure are adjusted to obtain the adjusted graph structure. Based on the adjusted graph structure, the temperature propagation is re-estimated to obtain the corrected temperature estimate.

[0119] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the three-dimensional temperature estimation methods based on grid topology and physical partitioning described in the above method embodiments.

[0120] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps of any of the three-dimensional temperature estimation methods based on grid topology and physical partitioning described in the above method embodiments.

[0121] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0122] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0123] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0124] 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; that is, 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 according to actual needs.

[0125] Furthermore, the functional units in the various embodiments of the application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0126] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0127] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory, a random access memory, a magnetic disk, or an optical disk, etc.

[0128] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A three-dimensional temperature estimation method based on mesh topology and physical partitioning, characterized in that, The method includes: Obtain the 3D mesh model of the target object; Each triangular facet in the three-dimensional mesh model is used as a graph node in the graph structure. A mesh topology graph structure is constructed based on the spatial adjacency relationship between each triangular facet to obtain the initial graph structure. Based on the component segmentation information of the target object, each graph node in the initial graph structure is physically partitioned and labeled to obtain a physical partition graph structure; Perform cross-component edge processing on the adjacent edges in the physical partition graph structure to obtain a physical partition cross-component edge graph structure; Based on the infrared visibility detection results of the target object, temperature nodes are marked on the graph nodes in the physical partition cross-component edge graph structure to obtain a marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated. Based on the adjacency relationship in the physical partition cross-component edge graph structure, temperature propagation estimation is performed on each node to be estimated in the marked temperature graph structure to obtain the temperature estimation value corresponding to each node to be estimated.

2. The three-dimensional temperature estimation method based on mesh topology and physical partitioning according to claim 1, characterized in that, The step of performing cross-component edge processing on adjacent edges in the physical partitioning graph structure to obtain a physical partitioning cross-component edge graph structure includes: Obtain the component type label corresponding to each graph node in the physical partition graph structure; For each adjacent edge in the physical partition graph structure, the component type label of the graph nodes at both ends of the adjacent edge is determined. After traversing each adjacent edge, the physical partition cross-component edge graph structure is obtained. Specifically, for each adjacent edge in the physical partitioning graph structure, the component type label determination process for the graph nodes at both ends of the adjacent edge is performed, including: Obtain the first adjacent edge currently being processed from the physical partitioning graph structure; If the graph nodes at both ends of the first adjacent edge have the same component type label, then the first adjacent edge is retained; If the graph nodes at both ends of the first adjacent edge have different component type labels, then physical contact determination processing is performed between the corresponding components of the graph nodes at both ends of the adjacent edge. If there is physical contact between the components corresponding to the two end nodes of the first adjacent edge, then the first adjacent edge is retained and a contact type label is marked on the first adjacent edge; If there is no physical contact between the corresponding components of the graph nodes at both ends of the first adjacent edge, then delete the first adjacent edge.

3. The three-dimensional temperature estimation method based on mesh topology and physical partitioning according to claim 2, characterized in that, Before performing temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, the method further includes: Acquire the temperature measurement value collected by the physical temperature sensor deployed on the surface of the target object and the spatial position corresponding to the physical temperature sensor; Based on the spatial location, determine the graph node corresponding to the physical temperature sensor from the physical partition cross-component edge graph structure; The temperature measurement value is assigned to the graph node corresponding to the physical temperature sensor, and the corresponding graph node is marked as a constraint anchor point; the constraint anchor point serves as a fixed temperature reference node in the temperature propagation estimation process, and the temperature value remains unchanged in the temperature propagation estimation process.

4. The three-dimensional temperature estimation method based on mesh topology and physical partitioning according to claim 3, characterized in that, The step of performing temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the cross-component edge graph structure of the physical partition to obtain the temperature estimation value corresponding to each node to be estimated includes: From the marked temperature map structure, obtain the known temperature node of the first node to be estimated currently being processed; Based on the adjacency relationships in the cross-component edge graph structure of the physical partition, the graph distance between the first node to be estimated and each known temperature node is calculated to obtain the graph distance; Based on the graph distance and the preset jump threshold, the neighboring known temperature nodes of the first node to be estimated are determined from the known temperature nodes; Based on the component type label and material type label corresponding to the first node to be estimated and each neighboring known temperature node, calculate the label similarity between the first node to be estimated and each neighboring known temperature node to obtain the label similarity. Based on the graph distance and the label similarity, the influence weight between the first node to be estimated and each neighboring known temperature node is determined; Based on the influence weights, the temperature values ​​of the known temperature nodes in the neighborhood are weighted and summed to obtain the estimated temperature value of the first node to be estimated. By traversing each node to be estimated in the marked temperature map structure, the estimated temperature value corresponding to each node to be estimated is obtained.

5. The three-dimensional temperature estimation method based on mesh topology and physical partitioning according to claim 4, characterized in that, After obtaining the temperature estimate for each node to be estimated, the method further includes: Based on the adjacency relationship in the physical partition cross-component edge graph structure and the temperature estimate of the node to be estimated, calculate the temperature gradient between adjacent graph nodes; Based on the temperature gradient, a physical reasonable range of the temperature gradient is determined to obtain the temperature gradient determination result. Based on the location of the heat source of the target object, the heat source distribution law is judged by the temperature estimation value, and the heat source distribution law judgment result is obtained. If the temperature gradient judgment result indicates that the temperature gradient exceeds the physical reasonable range, or the heat source distribution law judgment result indicates that the temperature estimate distribution does not conform to the heat source distribution law, then the adjacent edges in the physical partition cross-component edge graph structure are adjusted to obtain the adjusted graph structure. Based on the adjusted graph structure, the temperature propagation is re-estimated to obtain the corrected temperature estimate.

6. A three-dimensional temperature estimation device based on mesh topology and physical partitioning, characterized in that, The device includes: Acquisition unit, used to acquire the 3D mesh model of the target object; A construction unit is used to take each triangular facet in the three-dimensional mesh model as a graph node in the graph structure, and construct a mesh topology graph structure according to the spatial adjacency relationship between each triangular facet to obtain an initial graph structure; The first processing unit is used to perform physical partitioning and labeling processing on each graph node in the initial graph structure according to the component segmentation information of the target object, so as to obtain a physical partitioning graph structure. The second processing unit is used to perform cross-component edge processing on the adjacent edges in the physical partition graph structure to obtain a physical partition cross-component edge graph structure. The third processing unit is used to mark the graph nodes in the physical partition cross-component edge graph structure with temperature nodes according to the infrared visibility detection results of the target object, so as to obtain a marked temperature graph structure; the marked temperature graph structure includes known temperature nodes and nodes to be estimated; The fourth processing unit is used to perform temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, so as to obtain the temperature estimation value corresponding to each node to be estimated.

7. The three-dimensional temperature estimation device based on mesh topology and physical partitioning according to claim 6, characterized in that, The second processing unit is used to perform cross-component edge processing on the adjacent edges in the physical partitioning graph structure to obtain a physical partitioning cross-component edge graph structure, specifically for: Obtain the component type label corresponding to each graph node in the physical partition graph structure; For each adjacent edge in the physical partition graph structure, the component type label of the graph nodes at both ends of the adjacent edge is determined. After traversing each adjacent edge, the physical partition cross-component edge graph structure is obtained. The second processing unit is used to determine the component type label of the graph nodes at both ends of each adjacent edge in the physical partition graph structure, specifically for: Obtain the first adjacent edge currently being processed from the physical partitioning graph structure; If the graph nodes at both ends of the first adjacent edge have the same component type label, then the first adjacent edge is retained; If the graph nodes at both ends of the first adjacent edge have different component type labels, then physical contact determination processing is performed between the corresponding components of the graph nodes at both ends of the adjacent edge. If there is physical contact between the components corresponding to the two end nodes of the first adjacent edge, then the first adjacent edge is retained and a contact type label is marked on the first adjacent edge; If there is no physical contact between the corresponding components of the graph nodes at both ends of the first adjacent edge, then delete the first adjacent edge.

8. The three-dimensional temperature estimation device based on mesh topology and physical partitioning according to claim 7, characterized in that, The fourth processing unit, before performing temperature propagation estimation on each node to be estimated in the marked temperature graph structure based on the adjacency relationship in the physical partition cross-component edge graph structure, is further configured to: Acquire the temperature measurement value collected by the physical temperature sensor deployed on the surface of the target object and the spatial position corresponding to the physical temperature sensor; Based on the spatial location, determine the graph node corresponding to the physical temperature sensor from the physical partition cross-component edge graph structure; The temperature measurement value is assigned to the graph node corresponding to the physical temperature sensor, and the corresponding graph node is marked as a constraint anchor point; the constraint anchor point serves as a fixed temperature reference node in the temperature propagation estimation process, and the temperature value remains unchanged in the temperature propagation estimation process.

9. A terminal, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the three-dimensional temperature estimation method based on mesh topology and physical partitioning as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the three-dimensional temperature estimation method based on mesh topology and physical partitioning as described in any one of claims 1-5.

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