Global mechanical state cloud picture construction method and system for key components of high-speed train

Abstract

The invention provides a global mechanical state cloud picture construction method and system for key components of a high-speed train, and relates to the technical field of train state monitoring, and the method comprises the steps: constructing a finite element model of the key components of the high-speed train; extracting geometric information of the finite element model, and reconstructing a three-dimensional contour of the finite element model to obtain a geometric model of the key component; reconstructing full-field strain and deformation data based on a full-field strain and deformation matrix obtained through finite element model simulation and a directly measured local strain value, and establishing a mapping relation between the strain and deformation data and colors; and coloring the geometric model according to the mapping relation between the full-field strain and the deformation data and the color to obtain a global mechanical state cloud picture. The method focuses on the global strain field and the deformation field of the key component of the high-speed train, and realizes efficient and accurate construction of the global mechanical state cloud picture of the key component of the high-speed train based on a global strain / deformation field reconstruction algorithm and a color mapping algorithm.

Description

Technical Field

[0001] This disclosure relates to the field of train condition monitoring technology, specifically to a method and system for constructing global mechanical state cloud maps of key components of high-speed trains. Background Technology

[0002] The ever-increasing speeds of high-speed trains, extreme operating environments, and other external disturbances can all cause damage to critical structures. When this damage accumulates to a certain extent, structural deformation or even fracture can occur, leading to unpredictable consequences. Therefore, monitoring the global mechanical state of critical train structures has become a major concern for researchers. Global strain and deformation are key indicators of the global mechanical state; thus, effectively monitoring the global strain distribution and global deformation attitude of critical components of high-speed trains is crucial to ensuring their safe and reliable operation.

[0003] Due to limitations in actual measurement conditions, sensors cannot fully acquire the strain and deformation values ​​across the entire structure. To address this, we can acquire local strain data of the structure and use reconstruction algorithms to inversely deduce the deformation and strain distribution of the structure, thereby achieving global mechanical state monitoring.

[0004] Currently, the methods for reconstructing the global strain field / deformation field of a structure include: 1) Curvature fitting method: based on the deflection equation of a beam, so this method is mainly used for the reconstruction of the deflection in a single direction of a beam structure, and is not applicable to the complex structure of a high-speed train; 2) Modal superposition theory: requires prior modal analysis, and modal truncation will affect the reconstruction accuracy; 3) Inverse finite element theory: computation is complex and shape function construction is difficult, so it is not applicable to the complex structure of a train.

[0005] Therefore, existing reconstruction methods cannot efficiently and accurately reconstruct the global strain field and deformation field of the complex structure of a train. Summary of the Invention

[0006] To address the aforementioned issues, this disclosure proposes a method and system for constructing global mechanical state cloud maps of key components of high-speed trains. Focusing on the global strain field and deformation field of key components of high-speed trains, it utilizes global strain / deformation field reconstruction algorithms and color mapping algorithms, combined with the VTK pipeline mechanism and structural finite element model, to achieve efficient and accurate construction of global mechanical state cloud maps of key components of high-speed trains.

[0007] According to some embodiments, the present disclosure adopts the following technical solutions: A method for constructing global mechanical state cloud maps of key components of high-speed trains, including: Construct finite element models of key components of high-speed trains; Extract the geometric information of the finite element model and use the geometric information to reconstruct the three-dimensional contour of the finite element model to obtain the geometric model of the key components. Based on the full-field strain and deformation matrix obtained from finite element model simulation and the directly measured local strain values, the full-field strain and deformation data are reconstructed through a linear superposition algorithm of loads, and a mapping relationship between strain and deformation data and color is established. Based on the mapping relationship between the full-field strain and deformation data and color, the geometric model is colored to obtain a global mechanical state cloud map.

[0008] According to some embodiments, the present disclosure adopts the following technical solutions: A global mechanical state cloud map construction system for key components of high-speed trains includes: The model building module is configured to: build finite element models of key components of high-speed trains; The contour reconstruction module is configured to: extract the geometric information of the finite element model and use the geometric information to reconstruct the three-dimensional contour of the finite element model to obtain the geometric model of the key components. The data reconstruction module is configured to: reconstruct the full-field strain and deformation data based on the full-field strain and deformation matrix obtained from the finite element model simulation and the directly measured local strain values, and establish a mapping relationship between the strain and deformation data and colors. The cloud map construction module is configured to color the geometric model based on the mapping relationship between the full-field strain and deformation data and colors, thereby obtaining a global mechanical state cloud map.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions: A computer program product includes a computer program that, when executed by a processor, implements a method for constructing a global mechanical state cloud map of a key component of a high-speed train.

[0010] According to some embodiments, the present disclosure adopts the following technical solutions: A non-transitory computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement the method for constructing a global mechanical state cloud map of key components of a high-speed train.

[0011] According to some embodiments, the present disclosure adopts the following technical solutions: An electronic device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement the global mechanical state cloud map construction method for key components of high-speed trains.

[0012] Compared with the prior art, the beneficial effects of this disclosure are as follows: This invention utilizes the VTK pipeline mechanism and structural finite element model information to reconstruct the three-dimensional contour of a structure; it reconstructs the global strain and deformation fields of the structure using a linear superposition method and FBG sensors; it uses the reconstructed strain and deformation values ​​as data attributes of all nodes in the geometric model, and further implements model coloring through a VTK color lookup table and a centroid coordinate interpolation algorithm. The specific advantages are: (1) The present invention can accurately reproduce the three-dimensional contour of the structure. Based on the VTK pipeline mechanism, the reconstruction time is less than 1 second.

[0013] (2) The present invention can realize the dynamic display of strain field / deformation field cloud map, with a rendering time of less than 50 ms, and can realize the real-time dynamic refresh of train structure status.

[0014] (3) The strain field / deformation field reconstructed by the linear superposition algorithm of loads maintains a high degree of consistency with the simulation results of Abaqus professional finite element software in terms of color gradient, with an average relative error of less than 5%, which can realize accurate monitoring of the global mechanical state of the structure. Attached Figure Description

[0015] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0016] Figure 1 This is a flowchart of the standard reconstruction process. Figure 2 This is a flowchart of the method in Example 1.

[0017] Figure 3 This is a schematic diagram of the VTK pipeline mechanism in Example 1.

[0018] Figure 4 This is a flowchart of the three-dimensional contour reconstruction process in Example 1.

[0019] Figure 5 This is a flowchart of the linear superposition method of loads in Example 1.

[0020] Figure 6 This is a schematic diagram of the color mapping principle in Example 1.

[0021] Figure 7 This is an example diagram of a triangular facet from Example 1.

[0022] Figure 8 This is a flowchart of the cloud map coloring process for Example 1. Detailed Implementation

[0023] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0024] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0025] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0026] Example 1 One embodiment of this disclosure provides a method for constructing a global mechanical state cloud map of key components of a high-speed train, including: Step S1: Construct finite element models of key components of high-speed trains; Step S2: Extract the geometric information of the finite element model and use the geometric information to reconstruct the three-dimensional contour of the finite element model to obtain the geometric model of the key components. Step S3: Based on the full-field strain and deformation matrix obtained from the finite element model simulation and the directly measured local strain values, the full-field strain and deformation data are reconstructed using the linear superposition algorithm of loads, and a mapping relationship between strain and deformation data and color is established. Step S4: Based on the mapping relationship between the full-field strain and deformation data and colors, color the geometric model to obtain the global mechanical state cloud map.

[0027] As one embodiment, the global mechanical state cloud map construction method for key components of high-speed trains disclosed herein focuses on the global strain field and deformation field of key components of high-speed trains. Based on the global strain / deformation field reconstruction algorithm and color mapping algorithm, and combined with the VTK pipeline mechanism and structural finite element model, it realizes the efficient and accurate construction of the global mechanical state cloud map of key components of high-speed trains.

[0028] In the current condition monitoring of key components of high-speed trains, due to limitations in actual measurement conditions, sensors cannot fully acquire the strain and deformation values ​​across the entire structural domain. To overcome this limitation, such as... Figure 1 As shown, typically, by collecting local strain data of the structure and using a reconstruction algorithm, the deformation and strain distribution of the structure are inversely deduced. This embodiment also adopts this method, but the reconstruction algorithm has been improved, such as... Figure 2 As shown, the specific process is as follows: Step 1: Use modeling software and finite element software to perform detailed modeling of key components of high-speed trains, obtain their finite element models, and perform mesh generation.

[0029] The modeling and finite element software used here can be existing software. Of course, those skilled in the art can choose the appropriate modeling and finite element software according to their own circumstances and needs, and are not limited to the above examples.

[0030] This embodiment uses SolidWorks and Abaqus as examples. First, a high-precision 3D model of the key components of the high-speed train is constructed using the professional CAD software SolidWorks, providing an accurate geometric basis for subsequent analysis. Then, the model is imported into the professional CAE software Abaqus to obtain a finite element model. The powerful mesh generation function of the finite element software is then used to discretize the model, generating the computational mesh required for finite element analysis.

[0031] Step 2: Obtain key data from the finite element model, including mesh element number, associated node number, and three-dimensional spatial coordinate information of each node.

[0032] In this context, a mesh is a cubic unit, such as a tetrahedral mesh, which contains 4 associated nodes, namely the 4 vertices of the tetrahedral mesh.

[0033] After meshing in Abaqus finite element software, an INP format file is exported. By parsing the INP file, the node coordinates and element connection relationship data are identified and extracted, thereby realizing the digital extraction of the model's geometric contour information.

[0034] Step 3: The mesh cell number, associated node number, and three-dimensional spatial coordinate information of each node extracted in Step 2 are used as a dataset, and the three-dimensional contour reconstruction of the structure is achieved through the VTK pipeline.

[0035] VTK pipeline mechanism such as Figure 3 As shown, it includes: 1) Data Source and Filter: In the 3D contour reconstruction of the key structure of the train, this embodiment uses a manual method to create an unstructured mesh dataset. This dataset records all the information of the model in detail, covering volume mesh element data, specifically including element numbers and their corresponding node numbers; it also includes node data, i.e., node numbers and 3D spatial coordinate values, thus completely describing the geometric features of the model.

[0036] 2) Mapper: The mapper is responsible for mapping the data in the dataset into geometric elements. These vertices are located in the 3D scene using xyz spatial coordinates, and then the vertices are connected according to the geometric topology information in the unstructured mesh dataset to form elements.

[0037] 3) Performer: When data is rendered in a scene, it cannot be directly added to the rendering scene. It is necessary to use a support, that is, first map the data onto the support, and then add it to the rendering scene. Performers are usually used as data supports to represent the geometry and attributes of data objects in the rendering scene.

[0038] 4) Renderer: Responsible for managing the rendering process of the scene, converting data objects, cameras, lights and other factors into images displayed on the screen.

[0039] 5) Rendering window: Renderers need to be displayed in the rendering window, and multiple renderers can be placed in the same rendering window.

[0040] 6) Window Interactor: Provides platform-independent interaction mechanisms for user events such as mouse, keyboard, and time.

[0041] The overall process of 3D contour reconstruction based on the above VTK pipeline mechanism is as follows: Figure 4 As shown, it includes: (1) Input the extracted geometric contour information of the model; (2) Construct unstructured mesh instances as a dataset for 3D shape geometry reconstruction; (3) Store the grid cell data and node data in the model geometry information into an unstructured grid instance; (4) Construct a vtkMapper instance as a mapper for the VTK visualization pipeline; (5) Map the dataset into geometric elements using the "vertex connection" method; (6) Construct a vtkActor instance to serve as the performer in the VTK visualization pipeline; (7) Associate the mapper with the performer; (8) Construct a vtkRender instance as the renderer for the VTK visualization pipeline; (9) Add a performer instance to the renderer instance; (10) Set the vtkCamera light instance and vtkLight camera instance to the default values; (11) Construct a vtkRenderWindow instance as the VTK rendering window; (12) Add a renderer to the rendering window; (13) Whether the user is performing an operation in the rendering window; otherwise, proceed to (15). (14) Update the camera, object positions, etc. through the window interactor; (15) Display the three-dimensional geometry of the model in the front view window.

[0042] Step 4: Attach the strain sensor to the actual component and obtain the strain value at the measuring point.

[0043] FBG sensors are attached to key components of high-speed trains to obtain strain values ​​at the measurement points.

[0044] Step 5: Reconstruct the global strain field / deformation field using the algorithm for local strain reconstruction, and combine it with the local strain values ​​from Step 4 to reconstruct the strain / deformation values ​​of all nodes in the structural finite element model. Specifically, this is achieved through a global strain field / deformation field recalculation algorithm based on linear load superposition. The principle of the linear load superposition algorithm is as follows: The linear superposition algorithm for loads is an improvement upon the modal superposition algorithm mentioned in the research background. This algorithm avoids the limitation of modal truncation in traditional modal superposition algorithms. The core principle of the linear superposition algorithm for loads is that the complex dynamic response of a system can be decomposed into a linear superposition of the responses under each sub-load. Therefore, the strain values ​​at the structural measuring points... The decomposition expression is as follows: (1) Where k is the number of different types of loads; The strain values ​​at the measuring points of the structure under multiple loads can be obtained through sensors. The strain matrix for measuring points under k individual loads is obtained through on-site calibration. This is the load-strain weight vector. Similarly, the strain values ​​of all nodes in the structure The decomposition expression is as follows: (2) Where k is the number of different types of loads; Let be the total strain value of the structure under multiple loads simultaneously, and be the target quantity to be determined. The full-field strain matrix under k individual loads is obtained through finite element model simulation analysis. This is the load-strain weight vector.

[0045] Multiply both sides of equation (1) by We can obtain: (3) The inverse transformation of equation (3) yields: (4) Substituting equation (4) into equation (2), we obtain the strain values ​​of all nodes in the structure, i.e., the total strain values: (5) Similarly, the deformation values ​​of all nodes in the structure can be expressed as: (6) Where k is the number of different types of loads; Let be the total deformation value of the structure under multiple loads acting simultaneously, and be the target quantity to be determined. The full-field deformation matrix under k individual loads is obtained through finite element model simulation analysis. This is the load-deformation weight vector.

[0046] From an energy perspective, and They are different manifestations of the same energy, therefore equal ,Right now: (7) Substituting equations (4) and (7) into equation (6), we obtain the deformation values ​​of all nodes of the structure, i.e., the total deformation values: (8) Thus, the full-field strain and deformation matrix obtained through finite element model simulation, along with the strain values ​​and strain matrix of local measuring points directly measured by the structure, can simultaneously reconstruct the full-field strain and deformation of the structure.

[0047] In summary, the process of the linear superposition method of loads is as follows: Figure 5 As shown, specifically: A unified load application surface division was performed on the key components and finite element model of a real high-speed train. Based on the divided load application surface, experiments and simulations were conducted. The experiments involved direct measurement of the key components of a real high-speed train to obtain strain values ​​at local measuring points. and strain matrix Simulation involves performing simulation analysis on a finite element model to obtain the full-field strain matrix. and the full-field deformation matrix .

[0048] Based on the above four data points, the load-strain weight vector is first calculated in real time using formula (4). Then, calculate the total strain value and total deformation value according to formulas (5) and (8) respectively.

[0049] Step 6: Using the VTK color lookup table, associate the full-field strain and full-field deformation values ​​obtained in Step 5 with the colors.

[0050] The coordinated operation of full-field strain and deformation values ​​with a color lookup table is the core mechanism of color mapping. Taking a color lookup table containing 256 colors as an example, its index values ​​cover the integer range of 0 to 255. Scalar data is converted into color index values ​​based on this lookup table. The color mapping logic is as follows: Figure 6 As shown: The minimum threshold (min) and maximum threshold (max) represent the lower and upper limits of a scalar value, which is linearly mapped to a color index value. When a scalar value exceeds a preset range, the mapped index value will be fixed at 0 or 255. Therefore, scientifically setting the scalar mapping range can accurately reflect the differences in the entire data field and improve the recognition and accuracy of the color mapping effect.

[0051] Step 7: Use the centroid coordinate interpolation algorithm to render the color of the entire surface of the model component.

[0052] To display the global strain and deformation fields of the structure in the form of a cloud map, it is necessary to calculate the color of points within each surface element. This embodiment uses the centroid coordinate method as an interpolation algorithm to achieve this purpose. Figure 7 Using triangular elements as an example, the algorithm works as follows: Consider a triangular facet in space, whose boundary is defined by three points: vertex V1 (x1, y1, z1), vertex V2 (x2, y2, z2), and vertex V3 (x3, y3, z3). Based on these three vertices, the normal vector of this triangular facet can be further derived as follows: (9) The total area of ​​the triangular facet is: (10) Within the triangular element, select any point P with spatial coordinates (x, y, z). Connect this point to the three vertices of the triangular element, thus constructing three sub-triangles, denoted as A1, A2, and A3. Each of these three newly formed sub-triangles has a specific area value, as follows: (11) The centroid coefficient can be understood as the weight of the three vertex colors at point P: (12) The color value S of point P can be obtained by weighting the color values ​​S1, S2, and S3 of the three vertices: (13) In summary, firstly, the VTK color lookup table is used to map the attribute values ​​of each node in the model to their corresponding colors, completing the basic mapping. Then, a centroid coordinate interpolation algorithm is introduced to calculate and process the entire structure, achieving a visual mapping of strain and deformation data, ultimately generating a complete full-field cloud map. This method has good versatility; this process can be used to complete the shading and rendering of surface elements with different geometric shapes. The dynamic display process of the cloud map is as follows: Figure 8 As shown.

[0053] Example 2 One embodiment of this disclosure provides a global mechanical state cloud map construction system for key components of high-speed trains, including: The model building module is configured to: build finite element models of key components of high-speed trains; The contour reconstruction module is configured to: extract the geometric information of the finite element model and use the geometric information to reconstruct the three-dimensional contour of the finite element model to obtain the geometric model of the key components. The data reconstruction module is configured to: reconstruct the full-field strain and deformation data based on the full-field strain and deformation matrix obtained from the finite element model simulation and the directly measured local strain values, and establish a mapping relationship between the strain and deformation data and colors. The cloud map construction module is configured to color the geometric model based on the mapping relationship between the full-field strain and deformation data and colors, thereby obtaining a global mechanical state cloud map.

[0054] Example 3 One embodiment of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the method for constructing a global mechanical state cloud map of key components of a high-speed train.

[0055] Example 4 One embodiment of this disclosure provides a non-transitory computer-readable storage medium for storing computer instructions. When these computer instructions are executed by a processor, they implement the method for constructing a global mechanical state cloud map of key components of a high-speed train.

[0056] Example 5 One embodiment of this disclosure provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to execute the method for constructing a global mechanical state cloud map of key components of a high-speed train.

[0057] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams.Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0058] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 Figure 1 The steps of the function specified in one or more boxes.

[0059] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A method for constructing a global mechanical state cloud map of key components of a high-speed train, characterized in that, include: Constructing finite element models of key components of high-speed trains; Extract the geometric information of the finite element model and use the geometric information to reconstruct the three-dimensional contour of the finite element model to obtain the geometric model of the key components. Based on the full-field strain and deformation matrix obtained from finite element model simulation and the directly measured local strain values, the full-field strain and deformation data are reconstructed through a linear superposition algorithm of loads, and a mapping relationship between strain and deformation data and color is established. Based on the mapping relationship between the full-field strain and deformation data and color, the geometric model is colored to obtain a global mechanical state cloud map.

2. The method for constructing a global mechanical state cloud map of key components of a high-speed train as described in claim 1, characterized in that, The aforementioned finite element model for constructing key components of a high-speed train is a three-dimensional model of the key components of a high-speed train, which is generated by meshing the three-dimensional model using finite element software. The extraction of geometric information from the finite element model of key components of high-speed trains involves identifying and extracting the node coordinates and element connection relationships of the finite element model to obtain geometric information.

3. The method for constructing a global mechanical state cloud map of key components of a high-speed train as described in claim 1, characterized in that, The method of reconstructing the three-dimensional contour of the finite element model using geometric information involves using the geometric information as a dataset and reconstructing the three-dimensional contour of the finite element model through the VTK pipeline mechanism to obtain the geometric model of the key components.

4. The method for constructing a global mechanical state cloud map of key components of a high-speed train as described in claim 1, characterized in that, The directly measured local strain value is obtained by using an FBG sensor attached to the actual critical component.

5. The method for constructing a global mechanical state cloud map of key components of a high-speed train as described in claim 1, characterized in that, The method described above, which reconstructs full-field strain and deformation data using a linear superposition algorithm of loads, decomposes the dynamic response into a linear superposition of responses under each sub-load, uses local strain values ​​to update load weights in real time, and then calculates full-field strain and deformation data.

6. The method for constructing a global mechanical state cloud map of key components of a high-speed train as described in claim 1, characterized in that, The coloring of the geometric model is achieved by using the VTK color lookup table and the centroid coordinate interpolation algorithm to calculate the color of the entire structural domain of key components, realize the visualization mapping of strain and deformation data, and finally generate a complete full-field cloud map.

7. A global mechanical state cloud map construction system for key components of high-speed trains, characterized in that, include: The model building module is configured to: build finite element models of key components of high-speed trains; The contour reconstruction module is configured to: extract the geometric information of the finite element model and use the geometric information to reconstruct the three-dimensional contour of the finite element model to obtain the geometric model of the key components. The data reconstruction module is configured to: reconstruct the full-field strain and deformation data based on the full-field strain and deformation matrix obtained from the finite element model simulation and the directly measured local strain values, and establish a mapping relationship between the strain and deformation data and colors. The cloud map construction module is configured to color the geometric model based on the mapping relationship between the full-field strain and deformation data and colors, thereby obtaining a global mechanical state cloud map.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the global mechanical state cloud map construction method for key components of high-speed trains as described in any one of claims 1-6.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium is used to store computer instructions, which, when executed by a processor, implement the global mechanical state cloud map construction method for key components of high-speed trains as described in any one of claims 1-6.

10. An electronic device, characterized in that, include: The device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement the global mechanical state cloud map construction method for key components of high-speed trains as described in any one of claims 1-6.

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