A digital twin modeling method based on a six-dimensional model three-layer architecture

Abstract

The application relates to a digital twin modeling method based on a six-dimensional model three-layer architecture, and belongs to the field of digital twin modeling. The method comprises the following steps: constructing a twin model; constructing a topology model through the twin model; combining the twin model and the topology model, and setting operation rules and data mapping rules by using a scene model designer to construct a scene model and store the model; the three-layer modeling architecture is formed by the twin model, the topology model and the scene model; a scene instance is created, twin instance data is given to the scene instance according to the rules of dynamic data mapping, the twin is dynamically analyzed, calculated and instantiated according to the topology model and the scene model, and a twin visual instance of the topology and the scene is rendered to support the twin application. The method can effectively manage and simulate the twin data, the network topology structure and the complex business scene, and improves the intelligent level of network operation and management.

Description

Technical Field

[0001] This invention belongs to the field of digital twin modeling, and in particular relates to a digital twin modeling method based on a six-dimensional model three-layer architecture. Background Technology

[0002] In the modern telecommunications industry, with the continuous increase in network scale and complexity, traditional network operation and maintenance methods are struggling to meet the demands for efficient and accurate maintenance. The management and maintenance of cloud network resources have become more complex, requiring an advanced technology that can comprehensively and accurately reflect network status and performance. Digital twin technology creates virtual models to map the actual physical network, thereby enabling real-time monitoring, analysis, and optimization of the network.

[0003] However, existing digital twin modeling methods have the following problems:

[0004] (1) Single model dimension: Existing digital twin models usually only focus on a specific dimension (such as topology or traffic data), which cannot fully reflect the complexity of the actual network.

[0005] (2) Difficulty in modeling complex scenarios: Unclear boundaries of model responsibilities lead to low scalability and flexibility, resulting in long construction cycles for complex scenarios. Complex scenarios typically involve data from multiple dimensions (such as physical attributes, logical relationships, operational states, and behavioral patterns) and multiple layers (such as device layer, network layer, and business layer). This requires the model to comprehensively and accurately reflect the relationships and interactions between various dimensions and layers, increasing the complexity of modeling. High coupling between models and data at different layers increases the difficulty of model maintenance and updates. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a digital twin modeling method based on a six-dimensional model and a three-layer architecture, so as to realize the effective management and simulation of twin data, network topology and complex business scenarios, and improve the intelligence level of network operation and maintenance and management.

[0007] This invention proposes a digital twin modeling method based on a six-dimensional model and a three-layer architecture, comprising:

[0008] S1, Constructing a twin model, including:

[0009] S11, Construct a twin catalog, wherein the twin catalog uses a 6-dimensional model to record the information of the twin, and the 6-dimensional model includes: information model, geometric model, rule model, operation model, behavior model and simulation model;

[0010] S12, construct a twin asset catalog, which records the inheritance information and template information of twin model assets; the twin model assets are data generated after the twin is instantiated under specified conditions, and the data of the twin model assets inherits...

[0011] It can inherit from twins and is expandable;

[0012] S2, Constructing a topology model through the twin model includes: combining the twin model assets using a topology model designer according to the point, line and surface relationships of the twin model, and combining them into a topology model according to a preset order or rules to achieve topological twinning;

[0013] S3, combine the twin model and the topology model, and use the scene model designer to set the running rules and data mapping rules to construct the scene model and store the models separately;

[0014] A three-layer modeling architecture consisting of a twin model, a topology model, and a scene model is provided, which supports the combination of some models in the 6-dimensional model.

[0015] S4 creates a scene instance. According to the rules of dynamic data mapping, the twin instance data is assigned to the scene instance. The twin is dynamically analyzed, calculated and instantiated according to the topology model and scene model. The twin is then rendered to form a visual twin instance of the topology and scene to support twin applications.

[0016] Furthermore, in S1,

[0017] The information model is used to store the basic attributes of the twin and its surrounding direct relationships;

[0018] The geometric model is used to store the visualization model;

[0019] The rule model is used to store the rules that constrain the twins;

[0020] The operation model is used for visualization and monitoring of the operation status, and triggers relevant operations in the behavior model according to the rule model, and receives feedback information.

[0021] The behavior model is used to store the control actions and result feedback that the twin can support, and to receive the calculation results of the running model and the rule model to trigger corresponding behaviors.

[0022] The simulation model is used to impose constraints on the twin with predetermined parameters, algorithms, or AI capabilities, simulate or deduce real operating results, and judge and analyze the feasibility of predetermined parameters or scenarios.

[0023] Furthermore, in S1, the twin model assets inherit the existing data of the twin and support the definition of their own private behavior and rule data, which are stored in the 6-dimensional twin model.

[0024] Furthermore, in S1, for the twin model, the twin data storage of the smallest single-object twin model is positioned as the twin specification; the basis for subsequent twin object models of other levels.

[0025] Furthermore, in S2, the topology model includes multiple twin model assets.

[0026] Furthermore, in S2, the topology model includes: 5G leased line topology model, PON leased line topology model, OTN leased line topology model, IPRAN leased line topology model, bare fiber leased line topology model, and other types of topology models.

[0027] Furthermore, in S2, the topology model designer includes: a node and line designer, a layout designer, an interaction designer, and a topology template.

[0028] Furthermore, in S3, the scene model designer includes: agile scene construction, dynamic data mapping rules, scene interaction configuration, and scene operation configuration.

[0029] Furthermore, in S3, the scenario model includes: one-map polymorphism, spatial twinning, and lifecycle management.

[0030] Furthermore, in S4, the twin instance data is matched with a template based on conditions, the twin instance data is loaded into the matched template, the twin data is calculated, the twin topology instance is generated, and then the topology instance is generated and rendered to form a twin visual instance of topology and scene, realizing twin visualization and capability sharing.

[0031] The beneficial effects of this invention are as follows:

[0032] (1) By using information models, geometric models, rule models, operation models, behavior models and simulation models, the network can be comprehensively and accurately reflected in all aspects. Through the hierarchical architecture of twin model asset layer, topology model layer and scenario model layer, the twin data, network topology and complex business scenarios can be effectively managed and simulated, thereby improving the intelligence level of network operation and maintenance.

[0033] (2) A six-dimensional model is adopted, introducing six dimensions: information model, geometric model, rule model, operation model, behavior model, and simulation model, comprehensively covering all aspects of the twin and providing more accurate and comprehensive network resource description and management capabilities. Compared with the single or few dimensions in existing technologies, the multi-dimensional model of this invention ensures a high degree of accuracy in virtual-real mapping and interaction. Through the definition and application of the six-dimensional model, all aspects of the network are comprehensively and accurately reflected, including physical attributes, logical relationships, operating status, and behavioral patterns, solving the problem that existing models have only one dimension and cannot fully reflect the complexity of actual networks.

[0034] (3) Through a three-layer architecture design—the twin model layer (including the twin model asset layer), the topology model layer, and the scenario model layer—layered management of data, topology, and business scenarios is achieved. This architecture not only simplifies the data collection and processing process but also improves the scalability and flexibility of the model, enabling it to more efficiently meet the modeling needs of complex scenarios.

[0035] (4) The three-layer architecture allows for flexible combination of some models in the six-dimensional model to meet the needs of different application scenarios. In this way, the model can be adjusted and extended according to actual needs, providing personalized and customized solutions, and realizing flexible combination and extension of the model.

[0036] (5) The clear three-tier architecture separates the model and data at different levels, making model maintenance and updates simpler and more efficient. Each layer of the model can be updated and maintained independently, reducing the complexity and cycle of model updates, improving operational efficiency, and solving the problem of difficult model maintenance and updates in existing technologies.

[0037] (6) It improves the comprehensive description and management of network resources, optimizes the modeling and simulation capabilities of complex scenarios, shortens the twin modeling cycle, and solves problems such as multi-dimensional and multi-level modeling requirements, high-complexity interactions and dependencies. Based on this method, it is possible to quickly build digital twin visualization and simulation applications based on twins. Attached Figure Description

[0038] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. It is obvious that the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings.

[0039] Figure 1 This is a flowchart of a digital twin modeling method based on a six-dimensional model and a three-layer architecture, according to an embodiment of the present invention.

[0040] Figure 2This is a schematic diagram of a six-dimensional model according to an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of twin modeling in an embodiment of the present invention;

[0042] Figure 4 This is a schematic diagram of a 6-dimensional twin model according to an embodiment of the present invention;

[0043] Figure 5 This is a schematic diagram illustrating the creation of a scene example according to an embodiment of the present invention. Detailed Implementation

[0044] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0045] Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts disclosed in this invention.

[0046] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The terms "installed," "connected," and "linked" should be interpreted broadly; for example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0047] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of methods and systems consistent with some aspects of the invention as detailed in the appended claims.

[0048] The technical terms involved in this invention are explained below:

[0049] PON networking: PON (Passive Optical Network) is a type of passive optical network in which the optical distribution network (ODN) contains no electronic components or power supplies, and is entirely composed of passive devices such as optical splitters. PON is a point-to-multipoint fiber optic access technology, consisting of an optical line terminal (OLT) on the central office side, optical network units (ONUs) on the user side, and an optical distribution network (ODN).

[0050] IPRAN (Internet Protocol Radio Access Network) networking primarily involves building a service-bearing network based on IP / MPLS technology, particularly suitable for mobile service delivery. This network architecture typically includes an access layer, an aggregation layer, and a core layer, with the core layer further subdivided into metropolitan area core layers and provincial core layers. The construction and configuration of an IPRAN network involves multiple aspects, including network protection technologies, OAM (Operation, Administration, and Maintenance) functions, and interconnection achieved through NNI (Network Node Interface) and UNI (User Network Interface).

[0051] This invention proposes a digital twin modeling method based on a six-dimensional model and a three-layer architecture. (Reference) Figure 2 This method proposes a three-layer architecture for a 6-dimensional model. The 6-dimensional model includes an information model, a geometric model, a rule model, a runtime model, a behavioral model, and a simulation model. The three-layer architecture consists of a twin model layer, a topology model layer, and a scene model layer. This invention constructs a twin model (including model assets) based on the 6-dimensional model, builds a topology model through the twin model, and combines the twin model and the topology model to construct a scene model.

[0052] like Figures 1 to 3 As shown, the digital twin modeling method based on a six-dimensional model and a three-layer architecture of the present invention includes the following steps:

[0053] S1, Construct a twin model. The twin model includes the twin and twin asset information, etc.

[0054] S11, Construct a twin catalog. The twin catalog uses a 6-dimensional model to record the twin's information. The 6-dimensional model includes: an information model, a geometric model, a rule model, an operational model, a behavioral model, and a simulation model, such as... Figure 4 As shown.

[0055] (1) Information Model

[0056] The information model is used to store the basic attributes of the twin and its direct relationships with other twins. Specifically, the information model stores the basic attributes of the twin, such as ID, name, code, model, manufacturer, latitude and longitude, and location; it also stores the direct relationships with other twins, such as their relationships with other twins. The information model can meet the data storage requirements for virtual-physical mapping and, on this basis, support the data storage requirements for virtual-physical interactive data storage.

[0057] (2) Geometric Model

[0058] Geometric models are used to store visualization models. Specifically, geometric models store visualization models, such as appearance dimensions, shape, and texture maps, accurately describing the form and structure of physical entities, allowing for precise mapping between physical objects and virtual models, such as the BIM visualization model of the NE4000e switch. Geometric models can meet the geometric appearance management requirements for virtual-physical mapping and, on this basis, support the data storage requirements for virtual-physical interactive data.

[0059] (3) Rule Model

[0060] The rule model is used to store rules that constrain the twin. Specifically, the rule model stores rules that can act on the twin in dimensions such as interaction, operation, simulation, etc., and trigger state events, such as traffic thresholds. The rule model can constrain the twin.

[0061] (4) Operational Model

[0062] The operational model is used for visualization and monitoring of operational status, triggering relevant operations in the behavioral model based on the rule model, and receiving feedback information. Specifically, the operational model manages data such as the twin's operation, business processes, and work orders. Based on business rules, it supports twin optimization and proactive handling of potential faults, such as data on device or port traffic and performance. The operational model can fulfill the requirements for visualization and monitoring of operational status, triggering relevant operations in the behavioral model based on the rule model, and receiving feedback information.

[0063] (5) Behavioral Model

[0064] The behavioral model stores the control actions and feedback results that the twin can support, and receives calculation results from the runtime model and rule model to trigger corresponding behaviors. Specifically, the behavioral model stores the control actions and feedback results that the twin can support, including executed actions and action feedback, active feedback, passive feedback, simulation deduction feedback results, etc., such as switch command issuance, fault feedback, etc. The behavioral model can receive calculation results from the runtime model and rule model to trigger corresponding behaviors.

[0065] (6) Simulation Model

[0066] Simulation models are used to constrain twins by loading predetermined parameters, algorithms, or AI capabilities, simulating or deriving realistic operating results, and assessing the feasibility of predetermined parameters or scenarios. Specifically, simulation models can constrain twins by loading predetermined parameters, algorithms, or AI capabilities, simulating or deriving realistic operating results, and assessing the feasibility of predetermined parameters or scenarios, such as wireless coverage simulation. The simulation model section supports simulation algorithms and AI capabilities.

[0067] In this step, a twin catalog is constructed: the modeled twin has the properties of being indivisible and having the smallest granularity. It is a single object, similar to a resource specification. During modeling, both the external visibility and internal operation are described simultaneously.

[0068] S12, construct the twin asset catalog. The twin asset catalog is used to record the inheritance information and template information of the twin model assets. The twin model assets are the data generated after the twin is instantiated under specified conditions. The data of the twin model assets inherits from the twin and is extensible.

[0069] The twin model asset inherits existing data from the twin entity, including information, behavior, rules, simulation, and geometry data, which are stored within the twin model asset. Furthermore, the twin model asset supports defining its own private behavior and rule data, which are stored within the twin's 6D model.

[0070] In an embodiment of the present invention, for a twin model, the twin data storage of the smallest single-object twin model is positioned as the twin specification; the basis for subsequent twin object models of other levels.

[0071] Specifically, the smallest unit of the twin model is the twin specification, which can also be understood as the basic unit. Other levels of twin object models inherit and extend from this basic specification.

[0072] For example, a network consists of various devices, which are categorized into broad categories and specific categories. Broad category devices have common attributes, such as device code, device name, version, and network access time. Specific category devices have unique attributes in addition to these. For example, the attributes of an optical splitter include "split ratio," "split level ID," and "zone ID," while the attributes of a router include "CPU information," "hard drive configuration," "memory," and "baud rate."

[0073] refer to Figure 4 Taking a circuit board as an example, the twin model stores information in 6D models of the twin itself and the twin model assets. Defining these models requires abstracting and extracting business logic, which is a long-term, ongoing process. The following is an example:

[0074] (1) Information Model

[0075] Twin model:

[0076] Specifications = Circuit board

[0077] Twin model assets:

[0078] Inheritance information:

[0079] Specifications = Circuit board

[0080] Templated information:

[0081] Manufacturer Information

[0082] Model Information

[0083] (2) Geometric Model

[0084] Twin model:

[0085] Geometric description = Standard board geometry (no additional features)

[0086] Twin model assets:

[0087] Inheritance information:

[0088] Geometric description = standard board geometry

[0089] Templated information:

[0090] Length, width and height information

[0091] (3) Rule Model

[0092] Twin model:

[0093] Rules = General operational constraints (e.g., general load limits)

[0094] Twin model assets:

[0095] Inheritance information:

[0096] Rule = General Operational Constraint

[0097] Templated information:

[0098] Traffic threshold information

[0099] (4) Operational Model

[0100] Twin model:

[0101] Running status data = default state (e.g., idle) twin model assets:

[0102] Inheritance information:

[0103] Running status data = default status

[0104] Templated information:

[0105] Run log information

[0106] Performance indicators

[0107] (5) Behavioral Model

[0108] Twin model:

[0109] Action = Alarm Feedback = Elimination

[0110] Twin model assets:

[0111] Inheritance information:

[0112] Action = Alarm Feedback = Elimination

[0113] Templated information:

[0114] Operation = Parameter Submission Feedback = Status

[0115] (6) Simulation Model

[0116] Twin model:

[0117] Simulation algorithm = board flow simulation algorithm

[0118] Twin model assets:

[0119] Inheritance information:

[0120] Simulation algorithm = board flow simulation algorithm

[0121] Templated information:

[0122] Simulation algorithm = parameter optimization simulation algorithm.

[0123] S2, constructing a topology model through a twin model, including: combining twin model assets using a topology model designer based on the point, line and surface relationships of the twin model, and combining them into a topology model according to a preset order or rules to achieve topological twinning.

[0124] Specifically, topology model construction: Based on the twin model, instantiation is performed according to specified conditions. The topology model is realized by combining the twin model assets according to the relationship between points, lines, and surfaces, such as IPRAN network topology.

[0125] In embodiments of the present invention, the topology model includes multiple twin model assets.

[0126] The topology models include: 5G leased line topology model, PON leased line topology model, OTN leased line topology model, IPRAN leased line topology model, bare fiber leased line topology model, and other types of topology models.

[0127] refer to Figure 5 The topology model designer includes: node and line designer, layout designer, interaction designer, and topology template.

[0128] S3 combines twin models and topological models, and uses the scene model designer to set running rules and data mapping rules to build scene models and store them separately.

[0129] In an embodiment of the present invention, reference is made to... Figure 5 The scene model designer includes: agile scene building, dynamic data mapping rules, scene interaction configuration, and scene runtime configuration.

[0130] The scenario models include: one map with multiple forms, spatial twins, and lifecycle management.

[0131] The following sections will explain polymorphism in a single diagram, spatial twinning, and lifecycle management.

[0132] (1) One image has multiple forms:

[0133] "One image, multiple forms" refers to using a single digital twin image to express data and information in multiple levels, dimensions, and perspectives, meeting the needs of different scenarios.

[0134] The characteristics of polymorphism in a single image are as follows:

[0135] Multi-layered: Supports switching between global and local views, such as displaying a city panorama and details of a specific device.

[0136] Multi-dimensional: Geographic information, operational data, business status and other multi-dimensional data can be overlaid and displayed on the same map.

[0137] Multiple perspectives: Different roles or users can view information at different levels or of different types based on their permissions. For example, maintenance personnel can view the status of equipment, while decision-makers can focus on the overall operational status.

[0138] Application scenario: Smart city: Displaying urban traffic, environmental monitoring and emergency command information through a single map.

[0139] Industrial Park: Showcases equipment layout, real-time operating status, and energy consumption analysis.

[0140] (2) Spatial twin:

[0141] Spatial twins focus on the virtualization and digitization of physical space, achieving real-time mapping and interaction of spatial dynamics through the combination of high-precision geometric modeling and IoT data.

[0142] The characteristics of spatial twins are as follows:

[0143] Spatial modeling: accurately recreating the form and layout of physical space through geometric models, such as building structure and equipment placement.

[0144] Dynamic mapping: The real-time state of the physical space is acquired through sensors and mapped to the virtual space.

[0145] Interactive operation: Simulating, predicting, and optimizing operations in the actual physical space within the digital space.

[0146] Application scenario: Smart factory: Virtual factory layout and equipment operation status to optimize production scheduling.

[0147] Smart buildings: Monitoring building energy use, personnel movement, and safety risks through digital twins.

[0148] (3) Lifecycle Management:

[0149] Lifecycle management covers the entire process of digital twin objects from design, manufacturing, operation to disposal. Through the data connection of the twin at each stage, it achieves transparency and efficient management of the entire lifecycle.

[0150] The characteristics of lifecycle management are as follows:

[0151] End-to-end traceability: Data from every stage of the twin design to operation is traceable, facilitating troubleshooting and optimization.

[0152] Intelligent optimization: Combining AI and big data analytics, it provides predictive maintenance and optimization suggestions during the operation phase.

[0153] Collaborative Management: Supports collaboration among multiple departments such as design, manufacturing, and operation and maintenance to improve resource utilization.

[0154] Application scenario: Intelligent manufacturing: Management of the entire process of equipment from R&D, production to operation, to improve production efficiency.

[0155] Intelligent transportation: the full life-cycle management of transportation facilities, such as the construction, operation and maintenance of bridges.

[0156] The modeling architecture consists of a twin model, a topology model, and a scene model. This three-layer modeling architecture supports the combination of some models from the 6-dimensional model.

[0157] S4 creates a scene instance. According to the rules of dynamic data mapping, the twin instance data is assigned to the scene instance. The twin is dynamically analyzed, calculated and instantiated according to the topology model and scene model. The twin is then rendered to form a visual twin instance of the topology and scene to support twin applications.

[0158] For details, please refer to Figure 5 The process involves matching twin instance data to a template based on conditions, loading the twin instance data into the matched template, calculating the twin data, generating a twin topology instance, and then rendering the topology and scene to form a twin visual instance, thereby achieving twin visualization and capability sharing.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A digital twin modeling method based on a six-dimensional model three-layer architecture, characterized in that, Comprise: S1, construct a twin model, comprising: S11, construct a twin catalog, which records the information of the twin with a 6-dimensional model, the 6-dimensional model comprising: an information model, a geometric model, a rule model, a running model, a behavior model and a simulation model; S12, construct a twin asset catalog, which is used to record the inheritance information and templating information of the twin model asset; the twin model asset is data generated after the twin is instantiated under specified conditions, and the data of the twin model asset inherits the twin and is extensible; S2, construct a topology model through the twin model, comprising: combining the twin model asset according to the point, line and surface relationship of the twin model, and combining the twin model asset into a topology model in a preset order or rule to realize topology twin through a topology model designer; S3, combine the twin model and the topology model, and set running rules and data mapping rules through a scene model designer to construct a scene model and store the model separately; The three-layer modeling architecture is composed of the twin model, the topology model and the scene model, and the three-layer modeling architecture supports the combination of part of the 6-dimensional model; S4, create a scene instance, assign the twin instance data to the scene instance according to the rules of dynamic data mapping, dynamically analyze, calculate and instantiate the twin according to the topology model and the scene model, and render the twin visual instance of the topology and the scene to support the twin application.

2. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S1, The information model is used to store the basic attributes of the twin and the direct relationship of the twin; The geometric model is used to store the visual model; The rule model is used to store the rules that constrain the twin; The running model is used to visualize and monitor the running state, trigger the related operations in the behavior model according to the rule model, and receive feedback information; The behavior model is used to store the control actions and result feedback that the twin can support, and trigger the corresponding behavior by receiving the calculation results of the running model and the rule model; The simulation model is used to load predetermined parameters, algorithms or AI capabilities to constrain the twin, simulate or deduce the real running result, and judge the feasibility of the predetermined parameters or scene.

3. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S1, the twin model asset inherits the existing data of the twin, and supports defining private behavior and rule data, which are saved in the 6-dimensional model of the twin.

4. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S1, for the twin model, the twin data stored by the smallest single object twin model is defined as a twin specification, and the twin specification is used as the basis of other levels of twin object models.

5. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S2, the topology model comprises a plurality of twin model assets.

6. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S2, the topology model comprises: a 5G private line topology model, a PON private line topology model, an OTN private line topology model, an IPRAN private line topology model and a bare optical fiber private line topology model.

7. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S2, the topology model designer comprises: a node and line designer, a layout designer, an interaction designer and a topology template.

8. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S3, the scene model designer comprises: scene agile construction, dynamic data mapping rules, scene interaction configuration and scene running configuration.

9. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S3, the scene model comprises: a graph polymorphism, space twinning and life cycle management.

10. The digital twin modeling method based on a six-dimensional model three-layer architecture according to claim 1, characterized in that, In S4, the twin instance data is matched according to a condition, the twin instance data is loaded into a matched template, twin data is calculated, a twin topology instance is generated, a topology instance is generated, a twin visual instance forming a topology and a scene is rendered, and twin visualization and capability sharing are realized.

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