Structural mechanics analysis method of architectural heritage based on multi-dimensional digital twin

Abstract

The present invention discloses a method for analyzing the structural mechanics of architectural heritage based on multi-dimensional digital twins, comprising the following steps: S1: collecting on-site data of architectural heritage to obtain its physical entity data; S2: obtaining the state information of the architectural heritage and combining them to obtain digital twin data; S3: constructing a geometric model and a physical model according to the digital twin data, constructing a behavior model and a rule model, and combining the models into a digital twin of the architectural heritage; S4: obtaining a multi-dimensional digital twin model of the architectural heritage by fusing the physical entity data, the digital twin data and the digital twin. The present invention overcomes the problems of the existing building data twin model, such as insufficient model authenticity and data richness, and inability to perform mechanical analysis on buildings. By collecting actual data of architectural heritage and combining the structural mechanics analysis mechanism, the present invention reveals the historical evolution of building performance and morphology, predicts the future structural change trend of buildings, and provides reasonable suggestions for the maintenance of architectural heritage.

Description

Technical Field

[0001] The present invention relates to the technical field of architectural heritage monitoring and protection, and in particular to an architectural heritage structural mechanics analysis method based on multi-dimensional digital twins. Background Art

[0002] Architectural heritage carries rich historical, cultural and artistic values, so it is very necessary to protect it. However, given its importance, protection work also faces many practical problems. Most of the existing architectural heritage has been in service for many years, and the internal structural characteristics have changed due to internal and external factors. Therefore, it is necessary to conduct structural analysis of architectural heritage according to actual conditions, identify structural damage and provide appropriate repair plans, and then take corresponding measures to avoid further damage to architectural heritage.

[0003] Traditional protection methods for architectural heritage rely on regular inspections and manual measurement and analysis, and cannot be monitored in real time, resulting in a strong lag in the grasp of information on the state of the building structure, and it is difficult to obtain comprehensive and reliable detection results. Therefore, digital twin technology can be used to assist or lead the detection of architectural heritage to obtain real-time monitoring data and have certain scientific analysis capabilities. However, conventional technology is not accurate enough in modeling buildings, and can only display the appearance shape of the image model, but cannot perform mechanical analysis on the building, and cannot analyze the intrinsic properties of the components such as material properties, connection methods and force characteristics. Chinese patent publication number CN117932970A, published on April 26, 2024, named "A method and system for digital simulation of smart buildings based on digital twin engine" discloses a method for constructing a digital model of a building, including: obtaining the architectural parameters of the target building, importing the architectural parameters into the digital twin engine, simulating the digital model of the target building and displaying it. This patent provides a basic method for obtaining a digital twin model of a building, so that staff can remotely manage the building based on the digital model and reduce labor costs. However, this patent only provides a basic model construction method. The twin model's mapping dimensions and data presentation accuracy for actual buildings are insufficient, and it is unable to achieve a detailed reproduction of the structural mechanics mechanism in the building, nor can it achieve mechanical behavior analysis and structural change deduction of architectural heritage structures. It is of very limited help in monitoring and maintaining architectural heritage. Summary of the invention

[0004] The present invention overcomes the problems of insufficient model authenticity and data richness of existing building data twin models, and inability to perform mechanical analysis of buildings. It provides a structural mechanics analysis method for architectural heritage based on multi-dimensional digital twins. By collecting the actual physical data, current status information and historical status information of the architectural heritage, combined with the structural mechanics analysis mechanism of building components, modeling and fusion are performed from multiple dimensions. The geometric structure of the architectural heritage, the physical properties of each component, the combination mode of the structure, and the mechanical interaction principle between the components can be intuitively displayed, so as to fully understand the view shape, construction combination method, and current mechanical state of the building, reveal the historical evolution process of building performance and form, predict the future structural changes of the building, and provide reasonable suggestions for architectural heritage maintenance.

[0005] In order to achieve the above object, the present invention adopts the following scheme:

[0006] The structural mechanics analysis method of architectural heritage based on multi-dimensional digital twins includes the following steps:

[0007] S1: Collect on-site data of architectural heritage to obtain its physical entity data;

[0008] S2: Acquire status information of architectural heritage, digitize the physical entity data and status information, and combine them into digital twin data;

[0009] S3: constructing a geometric model and a physical model according to the digital twin data, performing load and stress analysis on various structures of the architectural heritage using the digital twin data, constructing a behavior model and a rule model according to the analysis results, and combining the geometric model, the physical model, the behavior model and the rule model into a digital twin of the architectural heritage;

[0010] S4: A multidimensional digital twin model of the architectural heritage is obtained by fusing the physical entity data, the digital twin data and the digital twin. The multidimensional digital twin model is provided with a data interface for connecting and interacting and provides functional services for structural mechanics analysis of the architectural heritage based on the digital twin.

[0011] Preferably, in step S1, the data acquired through on-site data collection of architectural heritage includes: point cloud data of the building, GIS data, BIM data, CAD data, multi-spectral data, stress wave data, and photogrammetry data images.

[0012] Preferably, the point cloud data is obtained using the following method:

[0013] Multiple sites are set up inside and outside the architectural heritage to obtain single-site cloud data respectively. The single-site cloud data obtained from the internal sites are feature-aligned to obtain internal point cloud data. The single-site cloud data obtained from the external sites are overall aligned to obtain external point cloud data. The internal point cloud data and the external point cloud data are integrated to obtain the overall point cloud data inside and outside the architectural heritage.

[0014] Preferably, if there are holes in the acquired point cloud data, the holes are repaired in the following manner:

[0015] The hole contours of building column components are identified, and the polygonal holes therein are marked. The polygonal holes are segmented and repaired. The repair process includes: extracting and shrinking boundaries, and constructing triangular pieces based on the boundaries to repair the hole areas.

[0016] Preferably, the method of identifying the polygonal holes and performing regional segmentation is as follows: finding the vertex of the sudden change in curvature of the hole as the starting point, extending to the boundary area of ​​the hole, finding the characteristic polyline in the direction of the maximum dihedral angle, identifying the hole with the characteristic polyline as a polygonal hole, fitting and matching the characteristic curve in the polygonal hole area and discretizing it, taking the part of the curve segment truncated by the hole, connecting the two end points of the curve segment to form a chord, calculating the point on the curve segment farthest from the chord, and inserting the point into the curve segment to form two curve arcs, and iterating in this way until the chord length is less than the set threshold;

[0017] The method of extracting and shrinking the boundary and constructing triangles to repair the hole area is as follows: traverse the entire triangular mesh surface to obtain all the boundary edges of the hole, and calculate the optimal boundary point according to the minimum angle-curvature principle using the following formula:

[0018] λ=ω 1 cosθ i +ω 2 k

[0019] Among them, θ i is the boundary angle, ω 1 is the weight factor of the boundary edge angle, ω 2 is the weight factor of curvature, k is the variable that describes the curvature;

[0020] Compute the average of the cosines of the angles between each boundary edge: Where P 1 P 2 is one of the boundary edges;

[0021] Calculate the boundary shrinkage distance: Where n is the number of holes to be repaired, d n is the distance obtained by traversing all edges of the entire boundary ring;

[0022] A corresponding number of triangles are generated according to the angle between two adjacent boundaries to repair the hole area.

[0023] Preferably, the physical entity data includes geometric data, environmental conditions and physical characteristics of the building;

[0024] The state information data includes the current state information and historical evolution process of the building;

[0025] The digital twin data includes the three-dimensional model and shape information, material properties, real-time monitoring data, load information, environmental data and historical records of the building.

[0026] Preferably, the geometric model includes geometric parameter data and structural connection relationships;

[0027] The physical model includes the material properties, structural strength and load-bearing capacity of the building;

[0028] The behavior model includes the time evolution behavior, dynamic functional behavior and performance degradation behavior of the building;

[0029] The rule model includes standards and specifications in construction, and mechanical coupling mechanisms.

[0030] Preferably, the mechanical coupling mechanism comprises:

[0031] To calculate the external forces acting on the component, the following formula is used:

[0032]

[0033] Where N is the compressive bearing capacity of the component, f c is the design strength value of the component after aging, T 0 is the historical age; t is the expected service life, R is the radius, α is the exponential parameter considering the thickness of the metamorphic layer, d 0 is the actual metamorphic layer thickness, γ is the strength loss coefficient;

[0034] Apply the principle of static equilibrium: ∑F=0 and ∑M=0, calculate the transmission force of adjacent components, and use the following formula:

[0035] Equivalent Potency Formula F eq = k × F applied , stress formula Moment formula M = F × d, shear force formula V = Shape variable formula

[0036] where F eq is the equivalent force, k is the stress equivalent conversion coefficient, F applied is the stress of the component, M is the bending moment of the component, and EI is the stiffness coefficient of the component;

[0037] The structural response is calculated using the stiffness method, using the Heck's law formula Calculate the displacements of adjacent components.

[0038] Preferably, the data interface connection and interaction modes include interface transmission, user interface operation, real-time monitoring, external verification feedback mechanism and remote data access; the functional services provided include data analysis, visual management, simulation prediction and user interaction.

[0039] Preferably, the multidimensional digital twin model further includes a maturity evaluation mechanism, which evaluates the physical entity data, digital twin, digital twin data, connection interaction and functional service through the following items:

[0040] Evaluation items for physical entity data: the degree of intelligent control of the physical entity of the architectural heritage, the integrity of the sensors and data provided, the data interface provided and the accessibility of network equipment;

[0041] Evaluation items for digital twin data: interoperability between twin systems, applicable architectural heritage twin objects and scope, and delay characteristics of twin data transmission;

[0042] Evaluation items for digital twins: accuracy and completeness of the constructed multi-dimensional digital twin model, degree of model standardization, data interface and integration, mechanical analysis capability of the building, integrity and real-time performance of the twin model;

[0043] Evaluation items for connectivity and interaction: the richness, compatibility, accessibility, quality and updating frequency of the built heritage data provided;

[0044] Evaluation items for functional services: twin performance efficiency, intelligent analysis level and twin function coverage of architectural heritage.

[0045] The present invention has at least the following beneficial effects: (1) by collecting the actual physical data and status information of the architectural heritage and using them to construct geometric models and physical models, the geometric structure of the architectural heritage is digitally restored while the physical properties and performance status information of the building are given to the model, thereby improving the information richness and accuracy of the model presentation;

[0046] (2) By analyzing the load and force transfer characteristics of building components, the behavior model and rule model are integrated into the digital twin, so that the multi-dimensional digital twin model generated by the integration can perform mechanical analysis and simulation of the building structure, reducing the workload of manual analysis and providing efficient detection and maintenance capabilities that comply with building rules and mechanical mechanisms; (3) By comprehensively collecting architectural heritage information and repairing the defects in the point cloud data, the data integrity and accuracy of the digital twin model are guaranteed, and the accuracy of the analysis of building behavior and mechanical characteristics is guaranteed, which provides conditions for the digital twin model to control actual building maintenance work; (4) By integrating the maturity evaluation mechanism, the performance of various aspects of the digital twin model is evaluated from multiple dimensions. Based on the evaluation, self-feedback and model upgrade and optimization can be carried out to build a growth-oriented model to adapt to different architectural heritage types and environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of a method for analyzing architectural heritage structure mechanics based on multi-dimensional digital twins of the present invention;

[0048] Figure 2 A schematic diagram is constructed for a multi-dimensional digital twin model framework of the present invention;

[0049] Figure 3 A schematic diagram of a mechanical coupling mechanism of the present invention;

[0050] Figure 4 A schematic diagram of a point cloud data acquisition method of the present invention;

[0051] Figure 5 It is a schematic diagram of a triangular piece division method of the present invention. DETAILED DESCRIPTION

[0052] The present invention is further described in detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0053] like Figure 1 and Figure 2 As shown, the architectural heritage structural mechanics analysis method based on multi-dimensional digital twin provided by the present invention comprises the following steps:

[0054] S1: Conduct on-site data collection on architectural heritage to obtain its physical entity data; collect data on architectural heritage in multiple cities and regions, including: the geometric shape of the building, the type and properties of materials used in the components, the historical evolution of the building such as initial construction, reconstruction, maintenance and renovation, the construction environment and geographical conditions, etc. The physical entity data is the main part of the collected data, reflecting the basic actual conditions such as the shape characteristics, structural connection characteristics, material types and quality performance of the architectural heritage; when collecting data, use photogrammetry, BIM, CAD and other technologies to automatically extract the geometric shape and topological relationship of the building components, and carry out model conversion design from point cloud model, NURBS model or irregular triangulated network model to structural finite element analysis model, which can accurately extract the data that best conforms to the actual architectural heritage, so as to verify the applicability of interdisciplinary analysis model conversion in the structural mechanics analysis process of the digital twin model.

[0055] S2: Obtain the status information of the architectural heritage, digitize the physical entity data and status information and combine them into digital twin data; the status information includes additional information such as the material information of the building, the usage status of the components and the restoration history, part of which is obtained by on-site data collection, and by collecting historical documents, drawings and cultural relics related to the building, ensure that the complete cultural background of the architectural heritage is given in the digital twin model.

[0056] S3: Construct geometric models and physical models based on the digital twin data, use the digital twin data to perform load and stress analysis on the various structures of the architectural heritage, construct behavioral models and rule models based on the analysis results, and combine the geometric models, physical models, behavioral models and rule models into the digital twin of the architectural heritage; form a geometric model by three-dimensional modeling and connecting and assembling the various components of the building. The geometric model intuitively presents the overall shape of the building and the outline of the components, and is also the basic reference for the construction of the physical model. In the process of constructing the geometric model, it is very important to balance and improve its fidelity and simplicity. The visualization effect and analysis efficiency of the digital twin model for the building data in the virtual space can be improved by simplifying the geometric model and reducing redundant surfaces. The physical model is used to load the physical performance information of the building components, including the material type, material properties, mechanical properties, thermodynamic properties and other characteristics of each component. In the dimension of the physical model, the real-time wear and performance degradation state of the building components is analyzed by using the multi-physics field coupling model and the finite element model. The behavioral model analyzes the structural changes of building entities during the process of time change and environmental change, including the time of structural change, degree of change, whether the change is reversible, chain change, whether it is periodic, etc. By simulating the dynamic response of architectural heritage under different conditions, the performance and potential problems of the building are analyzed and predicted based on information such as building usage, environmental changes and external impacts. The focus of the construction of the behavioral model is to accurately analyze abnormal data and its correlation with other variables to ensure accurate prediction of dynamic behavior. The rule model incorporates the basic rules and specifications of the building and the mechanical effects and usage principles of each component in the mechanical analysis process. It can reveal the architectural and mechanical principles behind some of the behavioral changes identified by the behavioral model. The rule model can optimize the full life cycle data of the digital twin model so that it can more accurately simulate the mechanical behavior and response of the building structure. In the process of building the digital twin, multiple models of geometry, physics, behavior, and rules are comprehensively considered to fully reflect the characteristics of the architectural heritage.

[0057] S4: A multidimensional digital twin model of architectural heritage is obtained by fusing the physical entity data, digital twin data and digital twin. The multidimensional digital twin model is provided with a data interface for connection and interaction and provides functional services for structural mechanics analysis of architectural heritage based on the digital twin. Physical entity data, digital twin data and digital twin are the three basic dimensions of the digital twin model. They have their own functions and also serve as partial data sources for each other. Physical entity data is the original data of the building, digital twin data is the intermediate data after digital integration, and digital twin is the overall data model formed by multi-model fusion and reconstruction after the data is modeled according to functional blocks. The connection and interaction mode provided by the data interface provides users with a variety of optional ways to export and input model data through interface data transmission, data visualization interface and other methods. The functional service mode integrates functions such as data management and data analysis, and provides the model with data presentation effects and mechanical analysis capabilities for architectural heritage. A five-dimensional digital twin model is formed by fusing physical entity data, digital twin data, digital twin, connection and interaction mode and functional service mode, and the model maturity evaluation and optimization mechanism can be further introduced to construct as follows: Figure 2 The six-dimensional digital twin model shown.

[0058] This method is based on an innovatively designed multidimensional digital twin model framework to establish a twin model that truly reflects the actual state of architectural heritage, revealing the mechanical interaction rules of architectural heritage under load conditions, and providing an intelligent and efficient digital solution for the scientific protection of architectural heritage. Based on the original data of architectural heritage and the structural state information such as the overall damage of the current situation, the method uses high-precision surveying and mapping sensors to obtain multidimensional spatiotemporal data, establishes a new multidimensional digital twin model framework and structural state analysis model, and provides a new way to expand digital empowerment for architectural heritage, and provides a comprehensive, complete and accurate digital twin model for architectural heritage structural analysis. On the basis of high-precision geometric modeling and physical property modeling, a digital model that accurately reflects the actual state of architectural heritage is constructed, and the rule model is used to deeply identify the interaction between components, including mechanical connection, energy transfer, etc., and load and stress analysis is used to improve the accuracy of behavioral analysis of complex structures. By collecting the actual physical data and status information of the architectural heritage and using it to construct geometric models and physical models, the geometric structure of the architectural heritage is digitally restored while the model is endowed with the physical properties and performance status of the building, thereby improving the information richness and accuracy presented by the model. By analyzing the load and force transfer characteristics of building components, the behavioral model and rule model are integrated into the digital twin, so that the fused multi-dimensional digital twin model can perform mechanical analysis and simulation of the building structure, reducing the workload and errors of manual analysis, and providing efficient detection and maintenance capabilities in accordance with architectural rules and mechanical mechanisms for the protection of architectural heritage.

[0059] In another technical solution, in step S1, the data acquired by on-site data collection of architectural heritage includes: architectural point cloud data, GIS data, BIM data, CAD data, multi-spectral data, stress wave data, and photogrammetry data images. Multi-dimensional data sources and data structures make geometric models, physical models, and other models more precise and accurate. The fused multi-dimensional digital twin model can better simulate the real state of architectural heritage and ensure the accuracy of mechanical analysis and prediction.

[0060] like Figure 4 As shown, the point cloud data is obtained using the following method:

[0061] Multiple sites are set up inside and outside the architectural heritage to obtain single-site cloud data respectively. The single-site cloud data obtained from the internal site is feature-aligned to obtain internal point cloud data. The single-site cloud data obtained from the external site is overall aligned to obtain external point cloud data. The internal point cloud data and the external point cloud data are integrated to obtain the overall point cloud data inside and outside the architectural heritage. Point cloud data is an important data source for 3D modeling. The data integrity and accuracy during the acquisition process will affect the modeling accuracy. In the process of collecting architectural heritage point cloud data, point cloud scanning equipment is used to collect information inside and outside the architectural heritage separately. Through separate alignment and processing using the Rodrigues rotation formula matrix, the external point cloud data obtained is used as the overall shape information of the architectural heritage, and the internal point cloud data is used as the detailed shape information. After the two point cloud data are fused, comprehensive information about the architectural heritage is obtained, providing strong support for the construction of geometric models and physical models.

[0062] If there are holes in the acquired point cloud data, the holes are repaired in the following way:

[0063] Identify the hole contours of building column components, mark the polygonal holes therein, perform regional segmentation and repair on the polygonal holes, and the repair process includes: extracting and shrinking the boundary, and constructing triangles to repair the hole area according to the boundary. The shrinkage direction of the repaired hole is determined according to the relationship between the normal vector angle, and the shrinkage distance is determined according to the distance relationship between the boundary edge and the adjacent edge. Then the boundary edge of the first shrinkage is optimized to obtain a closed boundary ring, and then a new triangle is constructed according to the given method, and it is continuously iterated until the given termination condition is met. Since the components of the architectural heritage have certain irregular shapes and the structures of many buildings are relatively complex, holes are likely to be generated during point cloud data collection, so it is necessary to repair the holes. The triangles used are triangular mesh facets, which are conventional units in the triangular mesh model used for point cloud data. Through the comprehensive collection of architectural heritage information, the defects of the point cloud data are repaired, and the triangles used to repair the holes by reasonable means can ensure the integrity of the point cloud data and the model restoration, ensure the data integrity and accuracy of the digital twin model, improve the accuracy of the analysis of building behavior and mechanical characteristics, and provide important conditions for the digital twin model to control the actual building maintenance work.

[0064] The method of identifying polygonal holes and performing regional segmentation is as follows: find the vertex of the sudden change in curvature of the hole as the starting point, extend to the boundary area of ​​the hole, find the characteristic polyline in the direction of the maximum dihedral angle, identify the hole with the characteristic polyline as a polygonal hole, fit the matching characteristic curve in the polygonal hole area and discretize it, take the part of the characteristic curve segment truncated by the hole, connect the two end points of the curve segment to form a chord, calculate the farthest point on the curve segment from the chord, and insert the point into the curve segment to form two curve arcs, and iterate in this way until the chord length is less than the set threshold. The threshold can be taken as the average length of each side of the hole polygon.

[0065] The method of extracting and shrinking the boundary and constructing triangles to repair the hole area is as follows: traverse the entire triangular mesh surface to obtain all the boundary edges of the hole, and calculate the optimal boundary point according to the minimum angle-curvature principle using the following formula:

[0066] λ=ω 1 cosθ i +ω 2 k

[0067] Among them, θ i is the boundary angle, ω 1 is the weight factor of the boundary edge angle, ω 2 is the weight factor of curvature, k is the variable that describes the curvature; N 1 (v i ) is the boundary point v i A triangular patch of a field; among them, is the normal vector of a domain triangle.

[0068] Compute the average of the cosines of the angles between each boundary edge: Where P 1 P 2 is one of the boundary edges;

[0069] Calculate the boundary shrinkage distance: Where n is the number of holes to be repaired, d n is the distance obtained by traversing all edges of the entire boundary ring;

[0070] According to the shrinkage characteristics of the boundary edge, the shrinkage direction and shrinkage distance are redefined. The normal vector of the triangular mesh face is a three-dimensional vector, including three coordinate components of x, y, and z. Suppose the normal vectors m and n of the two triangular faces are:

[0071]

[0072] Take the boundary point set D = {P 1 , P 2 , ..., P n}, connect the adjacent points in sequence to form a ring A. Set D includes two cases: containing only one element of D; containing two elements of D, that is, the boundary triangle patch. The vertices other than D contained in the triangular mesh patch composed of the elements in set D are recorded as D, = {P 1 , P 2 ,, ..., P n ,}, connect these vertices in turn to get ring A, and so on. Calculate cosθ for the angles of the boundary edges formed 1 、cosθ 2 、cosθ 3 、cosθ 4 , the average value of the cosine of these normal vector angles is: Suppose a new normal vector n x , let E(P 1 P 2 )=m·n x , then we can find n x , according to the normal vector n x and through the boundary edge P 1 P 2 These two conditions can be determined by n x The only plane with normal vector, the edge P in this plane 1 P 2 The normal direction of is the shrinkage direction of the hole boundary edge. Then calculate the shrinkage distance Among them, d n : Get the distance for all edges of the entire boundary ring.

[0073] Generate a corresponding number of triangles to fill the hole area according to the angle between two adjacent boundaries. When constructing triangles, calculate the angle between two adjacent boundaries, such as Figure 5 As shown, it is divided into the following cases: when θ≤90°, one triangle is generated; 90°<θ≤135°, two triangles are generated; 135°<θ≤200°, three triangles are generated; θ>200°

[0074] Generate four triangles.

[0075] The hole is repaired by iteratively detecting the boundary, calculating the shrinking direction and shrinking distance, shrinking the boundary again, and adding triangles until the farthest distance between the two boundary edges is less than or equal to the shrinking distance of the boundary. Then, the shrinking is stopped and a new triangle is constructed for this boundary.

[0076] In another technical solution, the physical entity data includes geometric data, environmental conditions and physical properties of the building; the expression of geometric data includes points, lines, surfaces and bodies, and the sources of the data structure used include point cloud models, NURBS models, and original finite element analysis models.

[0077] The state information data includes the current state information and historical evolution process of the building;

[0078] The digital twin data includes the three-dimensional model and shape information, material properties, real-time monitoring data, load information, environmental data and historical records of the building.

[0079] The geometric model includes geometric parameter data and structural connection relationships; the geometric model provides a detailed description of the spatial structure and form of the building, including the size, shape and relative position of each component, so as to achieve high-precision three-dimensional visualization. The accurate geometric data required to build the geometric model is obtained by conducting on-site surveys of the building using laser scanning, photogrammetry and traditional measurement tools. These data include the shape, size, angle and relative position of the building. In the process of building the geometric model, a modeling tool such as Revit, SketchUp or AutoCAD is selected to establish a hybrid three-dimensional model integrating a triangular mesh model and a parametric model based on the point cloud data obtained by scanning to achieve model fusion. Different parts of the architectural heritage, such as walls, columns, beams, roofs and windows, are modeled separately to ensure that each component is realistically presented in the three-dimensional model.

[0080] The physical model includes the material properties, structural strength and bearing capacity of the building; the physical model contains relevant physical parameters, characteristics and constraints. The characteristics and constraints include structural standards and specifications, material performance constraints, and environmental constraints. Physical parameters include the size, shape and structural layout of the building, mechanical properties, vibration characteristics, environmental parameters, etc. The physical model is used to describe the actual physical properties of the building, including material properties, structural strength and bearing capacity, to ensure the reliability of the model in engineering and safety assessment. As an example, the physical properties of the architectural heritage wood structure and its impact on the building performance are recommended to be obtained in Table 1 below:

[0081] Table 1

[0082]

[0083]

[0084] The above physical properties are the considerations for architectural heritage wooden structures. For other different materials and structures, there are corresponding physical properties that need to be obtained according to their characteristics.

[0085] The behavioral model includes the time evolution behavior, dynamic functional behavior and performance degradation behavior of the building; the time evolution behavior reflects the strength, fatigue and aging of the material under stress and deformation at different time points. The dynamic functional behavior reflects the vibration characteristics and frequency response of the building under external loads such as wind and earthquake, and is the response of the building to static and dynamic loads under different use conditions; the performance degradation behavior includes material aging, structural damage, fatigue failure, strength change, etc. The behavioral model simulates the dynamic response of the building under different conditions, including usage, environmental changes and external impacts, and can predict the performance and potential problems of the building.

[0086] The rule model includes standards and specifications in construction, and mechanical coupling mechanisms. The rule model sets the design standards and constraints of the building, including building specifications, laws and regulations, and mechanical rules. For example, the building reliability appraisal standards, building structure safety appraisal technical specifications, building structure maintenance and reinforcement technical specifications, etc. in the industry. The mechanical coupling mechanism establishes a model through the KU=F formula and applies meshing and multi-scale modeling techniques, and uses multi-physics field coupling analysis to process structural interactions through structural dynamics equations. In terms of material behavior, appropriate stress-strain relationships such as Hooke's law and more complex nonlinear models, such as plasticity, viscoelasticity, damage and other models are used to describe the behavior of materials under different conditions, and the connection relationship between components, such as boundaries and material properties, is clarified through the mechanical coupling mechanism.

[0087] In another technical solution, Figure 3 As shown, the mechanical coupling mechanism includes:

[0088] To calculate the external forces acting on the component, the following formula is used:

[0089]

[0090] Where N is the compressive bearing capacity of the component, f c is the design strength value of the component after aging, T 0 is the historical age; t is the expected service life, R is the radius, α is the exponential parameter considering the thickness of the metamorphic layer, d 0 is the actual thickness of the metamorphic layer, and γ is the strength loss coefficient. In the calculation of strength loss coefficient, γ=γ 1 ×γ 2 ×γ 3 , where γ 1 is the strength adjustment coefficient of the open-air structure, γ 2 is the adjustment coefficient of the structure, γ 3 It is the adjustment reduction factor for the years elapsed.

[0091] Apply the principle of static equilibrium: ∑F=0 and ∑M=0, calculate the transmission force of adjacent components, and use the following formula:

[0092] Equivalent Potency Formula F eq = k × F applied , stress formula Moment formula M = F × d, shear force formula V = Shape variable formula

[0093] where F eq is the equivalent force, k is the stress equivalent conversion coefficient, F applied is the stress on the component, M is the bending moment of the component, and EI is the stiffness coefficient of the component; in the stress formula, σ represents stress in Pascal (Pa), F represents the external force acting on the material in Newton (N), and A represents the area of ​​action of the force in square meters (m 2 ); in the moment formula, F is the resultant force acting on the member, and d is its lever arm; in the shear force formula, V represents the shear force at the analysis point or analysis surface on the member, M represents the bending moment at the analysis point or analysis surface, and x represents the corresponding position along the length of the member. The mechanical analysis process involves calculating the transmission force of adjacent members, determining the equivalent force acting on adjacent members, and calculating the pressure transmission and the transmission of bending moment and shear force through beams or columns.

[0094] The structural response is calculated using the stiffness method, using the Hooke's law formula Calculate the displacements of adjacent components, taking into account boundary conditions and continuity.

[0095] In another embodiment, the data interface connection and interaction methods include interface transmission, user interface operation, real-time monitoring, external verification feedback mechanism and remote data access; the functional services provided include data analysis, visual management, simulation prediction and user interaction.

[0096] like Figure 2 As shown, the multidimensional digital twin model also includes a maturity evaluation mechanism, which evaluates the physical entity data, digital twin, digital twin data, connection interaction and functional services through the following items:

[0097] Evaluation items for physical entity data: the degree of intelligent control of the physical entity of the architectural heritage, the integrity of the sensors and data provided, the data interface provided and the accessibility of network equipment;

[0098] Evaluation items for digital twin data: interoperability between twin systems, applicable architectural heritage twin objects and scope, and delay characteristics of twin data transmission;

[0099] Evaluation items for digital twins: accuracy and completeness of the constructed multi-dimensional digital twin model, degree of model standardization, data interface and integration, mechanical analysis capability of the building, integrity and real-time performance of the twin model;

[0100] Evaluation items for connectivity and interaction: the richness, compatibility, accessibility, quality and updating frequency of the built heritage data provided;

[0101] Evaluation items for functional services: twin performance efficiency, intelligent analysis level and twin function coverage of architectural heritage.

[0102] like Figure 2 As shown in the figure, the maturity evaluation mechanism of the multidimensional digital twin model is divided into the following five progressive levels according to the model performance:

[0103] The model simulates the real thing by using the virtual to simulate the real thing. It has the basic data of the architectural entity and can perform basic simulation displays and simple simulation designs, but it lacks detailed presentation and is not able to restore the real building to its truest degree.

[0104] The model reflects the real world with a large amount of data about the building entity. It can achieve a high degree of restoration of nearly all details and is a digital mapping of the building entity. Through the model, various accurate data of the building entity can be quickly obtained.

[0105] By controlling the real with the virtual, you can not only view the data and structural images of the building entity through the model, but also perform remote maintenance of the building by manipulating on-site tools through the model.

[0106] By predicting the real from the virtual, we can use models to analyze the structural changes of buildings and make timely preparations for possible abnormal situations.

[0107] By using the virtual to improve the real, we can analyze the defects in the architectural heritage and the problems that may arise in the future, propose possible repair plans based on the current status of the building and the mechanical analysis mechanism, and perform operational simulations on the repair plans to judge the repair effects and select the best repair plan.

[0108] By integrating the maturity evaluation mechanism, the performance of the digital twin model can be evaluated from multiple dimensions. Based on the evaluation, self-feedback and model upgrade and optimization can be carried out to build a growth model to adapt to different types and environments of architectural heritage. Combined with the maturity evaluation level, a multi-dimensional digital twin model of architectural heritage structure is established, and digital twin technology is used to achieve a comprehensive and scientific mechanical analysis of architectural heritage, promoting the digitalization and intelligent management of heritage protection.

[0109] It should be noted that, although the above describes the various steps in a specific order, it does not mean that the various steps must be performed in the above specific order. In fact, some of these steps can be performed concurrently or even in a different order, as long as the required functions can be achieved. The number of devices and processing scales described here are used to simplify the description of the present invention, and the application, modification and variation of the present invention are obvious to those skilled in the art.

[0110] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the implementation modes, and they can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and the illustrations shown and described herein.

Claims

1. A structural mechanics analysis method for architectural heritage based on multi-dimensional digital twins, characterized by: The following steps are involved: S1: Collect on-site data of architectural heritage to obtain its physical entity data; S2: Acquire status information of architectural heritage, digitize the physical entity data and status information, and combine them into digital twin data; S3: constructing a geometric model and a physical model according to the digital twin data, performing load and stress analysis on various structures of the architectural heritage using the digital twin data, constructing a behavior model and a rule model according to the analysis results, and combining the geometric model, the physical model, the behavior model and the rule model into a digital twin of the architectural heritage; S4: A multidimensional digital twin model of the architectural heritage is obtained by fusing the physical entity data, the digital twin data and the digital twin, wherein the multidimensional digital twin model is provided with a data interface for connection and interaction and provides a functional service of structural mechanics analysis of the architectural heritage based on the digital twin; The geometric model includes geometric parameter data and structural connection relationships; The physical model includes the material properties, structural strength and load-bearing capacity of the building; The behavior model includes the time evolution behavior, dynamic functional behavior and performance degradation behavior of the building; The rule model includes standards and specifications in construction, and mechanical coupling mechanisms; The mechanical coupling mechanism includes: To calculate the external forces acting on the component, the following formula is used: Where N is the compressive bearing capacity of the component, f c is the strength design value of the component after aging, T0 is the historical age; t is the expected service life, R is the radius of the column component, α is the index parameter considering the thickness of the deteriorated layer, d0 is the actual thickness of the deteriorated layer, is the strength loss coefficient; Apply the principle of static balance: and , calculate the transmission force of adjacent components, using the following formula: Equivalent Potency Formula , stress formula , torque formula , shear force formula , , deformation deflection differential equation ; in is the equivalent force, k is the stress equivalent conversion coefficient, is the stress of the component, M is the bending moment of the component, and EI is the stiffness coefficient of the component; The structural response is calculated using the stiffness method, using the Heck's law formula Calculate the displacements of adjacent components.

2. The architectural heritage structural mechanics analysis method based on multidimensional digital twin according to claim 1 is characterized in that: In step S1, the data acquired through on-site data collection of architectural heritage includes: point cloud data of the building, GIS data, BIM data, CAD data, multi-spectral data, stress wave data, and photogrammetry data images.

3. The architectural heritage structural mechanics analysis method based on multidimensional digital twin according to claim 2 is characterized in that: Use the following method to obtain the point cloud data: Multiple sites are set up inside and outside the architectural heritage to obtain single-site cloud data respectively. The single-site cloud data obtained from the internal sites are feature-aligned to obtain internal point cloud data. The single-site cloud data obtained from the external sites are overall aligned to obtain external point cloud data. The internal point cloud data and the external point cloud data are integrated to obtain the overall point cloud data inside and outside the architectural heritage.

4. The architectural heritage structural mechanics analysis method based on multidimensional digital twin according to claim 3 is characterized in that: If there are holes in the acquired point cloud data, the holes are repaired in the following way: The hole contours of building column components are identified, and the polygonal holes therein are marked. The polygonal holes are segmented and repaired. The repair process includes: extracting and shrinking boundaries, and constructing triangular pieces based on the boundaries to repair the hole areas.

5. The architectural heritage structural mechanics analysis method based on multidimensional digital twin according to claim 4 is characterized in that: The method of identifying polygonal holes and performing regional segmentation is as follows: finding the vertex of the sudden change in curvature of the hole as the starting point, extending to the boundary area of ​​the hole, finding the characteristic polyline in the direction of the maximum dihedral angle, identifying the hole with the characteristic polyline as a polygonal hole, fitting and matching the characteristic curve in the polygonal hole area and discretizing it, taking the part of the curve segment truncated by the hole, connecting the two end points of the curve segment to form a chord, calculating the farthest point on the curve segment from the chord, and inserting the point into the curve segment to form two curve arcs, and iterating in this way until the chord length is less than the set threshold; The method of extracting and shrinking the boundary and constructing triangles to repair the hole area is as follows: traverse the entire triangular mesh surface to obtain all the boundary edges of the hole, and calculate the optimal boundary point according to the minimum angle-curvature principle using the following formula: in, is the boundary edge angle, is the weight factor of the boundary edge angle, is the weight factor of curvature, k is the variable that describes the curvature; Compute the average of the cosines of the angles between each boundary edge: , where P1P2 is one of the boundary edges; Calculate the boundary shrinkage distance: , where n is the number of holes to be repaired, d n is the distance obtained by traversing all edges of the entire boundary ring; A corresponding number of triangles are generated according to the angle between two adjacent boundaries to repair the hole area.

6. The architectural heritage structural mechanics analysis method based on multidimensional digital twin according to claim 1 is characterized in that: The physical entity data includes geometric data, environmental conditions and physical characteristics of the building; The state information data includes the current state information and historical evolution process of the building; The digital twin data includes the three-dimensional model and shape information, material properties, real-time monitoring data, load information, environmental data and historical records of the building.

7. The architectural heritage structural mechanics analysis method based on multidimensional digital twin according to claim 1 is characterized in that: The data interface connection and interaction modes include interface transmission, user interface operation, real-time monitoring, external verification feedback mechanism and remote data access; the functional services provided include data analysis, visual management, simulation prediction and user interaction.

8. The architectural heritage structural mechanics analysis method based on multidimensional digital twin according to claim 1 is characterized in that: The multidimensional digital twin model also includes a maturity evaluation mechanism, which evaluates the physical entity data, digital twin, digital twin data, connection interaction and functional service through the following items: Evaluation items for physical entity data: the degree of intelligent control of the physical entity of the architectural heritage, the integrity of the sensors and data provided, the data interface provided and the accessibility of network equipment; Evaluation items for digital twin data: interoperability between twin systems, applicable architectural heritage twin objects and scope, and delay characteristics of twin data transmission; Evaluation items for digital twins: accuracy and completeness of the constructed multi-dimensional digital twin model, degree of model standardization, data interface and integration, mechanical analysis capability of the building, integrity and real-time performance of the twin model; Evaluation items for connectivity and interaction: the richness, compatibility, accessibility, quality and updating frequency of the built heritage data provided; Evaluation items for functional services: twin performance efficiency, intelligent analysis level and twin function coverage of architectural heritage.

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