Digital twin modeling method based on six-dimensional model three-layer architecture

Abstract

The invention relates to a digital twinning modeling method based on a six-dimensional model three-layer architecture, and belongs to the field of digital twinning modeling. The method comprises the following steps: constructing a twinning body model; constructing a topological model through the twin model; combining the twin model and the topology model, setting an operation rule and a data mapping rule by using a scene model designer to construct a scene model, and storing the scene model in different models; a three-layer modeling architecture is formed by a twin model, a topology model and a scene model; and creating a scene instance, endowing twinborn instance data into the scene instance according to a dynamic data mapping rule, dynamically analyzing, calculating and instantiating the twinborn according to the topology model and the scene model, and rendering to form a twinborn visual instance of the topology and the scene so as to support twinborn applications. According to the method, the twinborn data, the network topology structure and the complex service scene can be effectively managed and simulated, and the intelligent level of network operation, maintenance and management is improved.

Description

Technical Field

[0001] The present 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 and a three-layer architecture. Background Art

[0002] In the modern telecommunications industry, as the scale and complexity of networks continue to increase, traditional network operation and maintenance methods are unable to meet the needs of efficient and accurate operation and maintenance. The management and maintenance of cloud network resources have become more complex, requiring an advanced technology that can fully and accurately reflect the status and performance of the network. Digital twin technology creates a virtual model to map the actual physical network, thereby achieving real-time monitoring, analysis, and optimization of the network.

[0003] However, the 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) and cannot fully reflect the complexity of the actual network.

[0005] (2) Difficulty in modeling complex scenarios: Unclear model responsibility boundaries lead to low model scalability and flexibility, and a long cycle for building complex scenarios. Complex scenarios usually involve data from multiple dimensions (such as physical properties, logical relationships, operating status, and behavior patterns) and multiple levels (such as device layer, network layer, and business layer). This requires the model to fully and accurately reflect the relationships and interactions between various dimensions and levels, which increases the complexity of modeling. The high degree of coupling between models and data at different levels increases the difficulty of model maintenance and updating. Summary of the invention

[0006] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a digital twin modeling method based on a six-dimensional model and a three-layer architecture, so as to realize effective management and simulation of twin data, network topology and complex business scenarios, and improve the intelligence level of network operation and management.

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

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

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

[0010] S12, constructing a twin asset catalog, wherein the twin asset catalog is used to record the inheritance information and template information of the twin model asset; the twin model asset is the data generated after the twin is instantiated under the specified conditions.

[0011] It can be twinned and expanded;

[0012] S2, constructing a topological model through the twin model, including: combining the twin model assets using a topological model designer according to the relationship between points, lines and surfaces of the twin model, and combining them into a topological model according to a preset order or rule to realize topological twinning;

[0013] S3, combining the twin model and the topology model, and using the scenario model designer to set operation rules and data mapping rules to construct a scenario model and store it in separate models;

[0014] A three-layer modeling architecture is formed by a twin model, a topology model, and a scene model, and the three-layer modeling architecture supports the combination of some models in the 6-dimensional model;

[0015] S4, creates a scene instance, assigns the twin instance data to the scene instance according to the rules of dynamic data mapping, dynamically analyzes, calculates and instantiates the twin according to the topology model and scene model, and renders the twin visual instance of the topology and scene to support the twin application.

[0016] Furthermore, in S1,

[0017] The information model is used to store the basic properties of the twin and the surrounding direct relationship of the twin;

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

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

[0020] The operation model is used to visualize and monitor the operation status, trigger relevant operations in the behavior model according to the rule model, and receive feedback information;

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

[0022] The simulation model is used to constrain the twin body to load 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 asset inherits the existing data of the twin, and supports the definition of its own private behavior and rule data, which is stored in the twin 6-dimensional model.

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

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

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

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

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

[0029] Furthermore, in S3, the scenario model includes: one image with multiple forms, spatial twins, and lifecycle management.

[0030] Furthermore, in S4, the twin instance data is matched with the template according to the 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 the twin visual instance of the topology and scene is rendered to realize twin visualization and capability sharing.

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

[0032] (1) Through information models, geometric models, rule models, operation models, behavioral models and simulation models, all aspects of the network can be fully and accurately reflected. Through the layered architecture of the twin model asset layer, topology model layer and scenario model layer, effective management and simulation of twin data, network topology structure and complex business scenarios can be achieved, thereby improving the intelligent level of network operation and management.

[0033] (2) A six-dimensional model is adopted, and six dimensions, namely, information model, geometric model, rule model, operation model, behavior model and simulation model, are introduced to comprehensively cover all aspects of the twin, providing more accurate and comprehensive network resource description and management capabilities. Compared with the single or small number of dimensions in the prior art, the multi-dimensional model of the present invention ensures high accuracy of virtual-real mapping and interaction. Through the definition and application of the six-dimensional model, all aspects of the network, including physical properties, logical relationships, operation status and behavior patterns, are comprehensively and accurately reflected, solving the problem that the existing model has a single dimension and is difficult to fully reflect the complexity of the actual network.

[0034] (3) Through the three-layer architecture design of the twin model layer (including the twin model asset layer), the topology model layer, and the scenario model layer, hierarchical management of data, topology structure, 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, and can more efficiently respond to the modeling needs of complex scenarios.

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

[0036] (5) The clear three-layer architecture separates models and data at different levels, making model maintenance and updating easier and more efficient. Models at each layer can be updated and maintained independently, reducing the complexity and cycle of model updates, improving operation and maintenance efficiency, and solving the problem of model maintenance and updating difficulties 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, the rapid construction of digital twin visualization and simulation applications based on twins can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings are only used to illustrate specific embodiments and are not considered to limit the present invention. In the entire drawings, the same reference symbols represent the same components. Obviously, the drawings described below are only some embodiments recorded in the embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

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

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

[0041] Figure 3 A schematic diagram of twin modeling of an embodiment of the present invention;

[0042] Figure 4 Schematic diagram of a 6-dimensional twin model of an embodiment of the present invention;

[0043] Figure 5 A schematic diagram of creating a scene instance according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order 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 in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. It should be understood that these descriptions are only 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 ordinary technicians in the field without making creative work should fall within the scope of protection of the present invention.

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

[0046] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the orientation or position relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. The terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

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

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

[0049] PON networking: PON (Passive Optical Network) is a passive optical network, in which the optical distribution network (ODN) does not contain any electronic devices and electronic power supplies, and is entirely composed of passive devices such as optical splitters. PON is a point-to-multipoint fiber access technology, consisting of an optical line terminal (OLT) on the local side, an optical network unit (ONU) on the user side, and an optical distribution network (ODN).

[0050] IPRAN (Internet Protocol Radio Access Network) networking: mainly involves building a service bearer network based on IP / MPLS technology, which is particularly suitable for carrying mobile services. This network structure usually includes access layer, aggregation layer and core layer, among which the core layer is further divided into metropolitan core layer and provincial core layer. The construction and configuration of IPRAN network involves many aspects, including network protection technology, OAM (operation, administration and maintenance) functions, and interconnection through NNI (network node interface) and UNI (user network interface).

[0051] The present invention proposes a digital twin modeling method based on a six-dimensional model and a three-layer architecture. Figure 2 The method proposes a design of a three-layer architecture of a 6-dimensional model. The 6-dimensional model includes an information model, a geometric model, a rule model, an operation model, a behavior model, and a simulation model. The three-layer architecture is a twin model layer, a topology model layer, and a scenario model layer. The present invention constructs a twin model (including model assets) based on a 6-dimensional model, constructs a topology model through a twin model, and constructs a scenario model by combining a twin model and a topology model.

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

[0053] S1, build a twin model, where the twin model includes twins and twin asset information.

[0054] S11, build a twin directory, the twin directory uses a 6-dimensional model to record the information of the twin, the 6-dimensional model includes: information model, geometric model, rule model, operation model, behavior model and simulation model, such as Figure 4 shown.

[0055] (1) Information Model

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

[0057] (2) Geometric model

[0058] The geometric model is used to store the visual model. Specifically, the geometric model stores the visual model, such as appearance size, shape, texture mapping, etc., accurately describes the physical entity form and structure, and allows the physical object to be accurately mapped with the virtual model, such as the switch NE4000e BIM visual model. The geometric model can meet the geometric appearance management requirements for virtual-real mapping, and on this basis, support the virtual-real interactive data storage requirements.

[0059] (3) Rule Model

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

[0061] (4) Run the model

[0062] The operation model is used to visualize and monitor the operation status, trigger related operations in the behavior model according to the rule model, and receive feedback information. Specifically, the operation model manages twin operation, business, work order and other data, and supports twin optimization and fault hidden danger pre-processing according to business rules, such as traffic and performance data of devices or ports. The operation model can meet the needs of visualization and monitoring of the operation status, trigger related operations in the behavior model according to the rule model, and receive feedback information.

[0063] (5) Behavioral Model

[0064] The behavior model is used to store the control actions and result feedback that the twin can support, and receive the calculation results of the operation model and the rule model to trigger the corresponding behavior. Specifically, the behavior model stores the control actions and result feedback that the twin can support, including execution actions and action feedback, active feedback, passive feedback, simulation deduction feedback results, etc., such as switch instruction issuance, fault feedback, etc. The behavior model can receive the calculation results of the operation model and the rule model to trigger the corresponding behavior.

[0065] (6) Simulation model

[0066] The simulation model is used to constrain the twin body by loading predetermined parameters, algorithms or AI capabilities, simulating or deducing real operating results, and judging and analyzing the feasibility of predetermined parameters or scenarios. Specifically, the simulation model can constrain the twin body by loading predetermined parameters, algorithms or AI capabilities, simulating or deducing real operating results, and judging and analyzing the feasibility of predetermined parameters or scenarios, such as wireless coverage simulation. The simulation model topic supports simulation algorithms and AI capabilities, etc.

[0067] In this step, a twin directory is constructed: the modeling twin has the properties of being indivisible and of minimum granularity, and is a single object, similar to resource specifications. When modeling, both external visibility and internal operation are modeled and described.

[0068] S12, build a twin asset catalog, which 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 the specified conditions of installation, and the data of the twin model assets inherits the twin and is extensible.

[0069] The twin model asset inherits the existing data of the twin, including information, behavior, rules, simulation, geometry and other data, which are stored in the twin model asset. In addition, the twin model asset supports the definition of its own private behavior and rules and other data, which are stored in the twin 6D model.

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

[0071] Specifically, the smallest unit of the twin model is the twin specification. The smallest unit can also be understood as the basic unit. Twin object models at other levels inherit and expand on this basic specification.

[0072] For example, a network consists of multiple devices, and the devices are divided into two specifications: broad categories and subcategories. Broad categories of devices have common attributes, such as device code, device name, version, network access time, etc. Subcategories of devices have exclusive attributes based on this. For example, the attributes of a splitter include "splitting ratio", "splitting level ID", and "partition ID", and the attributes of a router include "CPU information", "hard disk configuration", "memory", and "baud rate".

[0073] refer to Figure 4 Taking the board as an example, the twin of the twin model and the 6-dimensional model storage information of the twin model asset. These model definitions require abstract extraction of the business, which is a long-term and continuous work. The following is an example:

[0074] (1) Information Model

[0075] Twin Model:

[0076] Specifications = Board

[0077] Twin model assets:

[0078] Inheritance Information:

[0079] Specifications = Board

[0080] Templated information:

[0081] Manufacturer Information

[0082] Model Information

[0083] (2) Geometric model

[0084] Twin Model:

[0085] Geometry 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 operating constraints (e.g. general load limits)

[0094] Twin model assets:

[0095] Inheritance Information:

[0096] Rules = General Operational Constraints

[0097] Templated information:

[0098] Traffic threshold information

[0099] (4) Run the model

[0100] Twin Model:

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

[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] Operation = Alarm Feedback = Elimination

[0110] Twin model assets:

[0111] Inheritance Information:

[0112] Operation = Alarm Feedback = Elimination

[0113] Templated information:

[0114] Operation = parameter delivery Feedback = status

[0115] (6) Simulation model

[0116] Twin Model:

[0117] Simulation algorithm = card traffic simulation algorithm

[0118] Twin model assets:

[0119] Inheritance Information:

[0120] Simulation algorithm = card traffic simulation algorithm

[0121] Templated information:

[0122] Simulation algorithm = parameter optimization simulation algorithm.

[0123] S2, building a topological model through the twin model, including: combining the twin model assets using the topological model designer according to the point, line and surface relationships of the twin model, and combining them into a topological model according to a preset order or rule to realize topological twinning.

[0124] Specifically, build a topology model: instantiate the twin model according to specified conditions, and realize topology twinning by combining twin model assets according to the relationship between points, lines, and surfaces, such as IPRAN networking topology.

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

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

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

[0128] S3, combines the twin model and the topology model, and uses the scenario model designer to set the operation rules and data mapping rules to build the scenario model and store it in separate models.

[0129] In the embodiments of the present invention, reference Figure 5 ,The scenario model designer includes : scenario agile construction, dynamic data mapping rules, scenario ,interaction configuration and scenario operation configuration.

[0130] The scenario model includes: one image with multiple forms, spatial twins and lifecycle management.

[0131] The following explains one graph with multiple forms, spatial twins, and lifecycle management respectively.

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

[0133] "One picture, multiple forms" means that through a digital twin picture, multi-level, multi-dimensional, and multi-perspective data and information expression can be achieved to meet the needs of different scenarios.

[0134] The characteristics of one picture with multiple forms are as follows:

[0135] Multi-level: supports switching between global and local, such as displaying a city panorama and the details of a certain device.

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

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

[0138] Application scenario: Smart city: Display urban traffic, environmental monitoring and emergency command information on the same map.

[0139] Industrial Park: Display equipment layout, real-time operation status and energy consumption analysis, etc.

[0140] (2) Space Twins:

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

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

[0143] Spatial modeling: Accurately restore the shape and layout of the physical space, such as building structure and equipment placement, through geometric models.

[0144] Dynamic mapping: The real-time status of the physical space is obtained through sensors and mapped into the virtual space.

[0145] Interactive Operations: Simulate, predict, and optimize operations in real physical spaces in digital spaces.

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

[0147] Smart buildings: Monitor building energy use, personnel flow, and security risks through digital twins.

[0148] (3) Lifecycle management:

[0149] Lifecycle management covers the entire process of digital twin objects from design, manufacturing, operation to scrapping. Through the data integration of the twin at each stage, transparent and efficient management of the entire life cycle can be achieved.

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

[0151] Full process traceability: Data from every link from twin design to operation can be traced, facilitating problem troubleshooting and optimization.

[0152] Intelligent optimization: Combining AI and big data analysis to provide 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 scenarios: Intelligent manufacturing: Full process management of equipment from R&D, production to operation to improve production efficiency.

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

[0156] The three-layer modeling architecture is composed of a twin model, a topology model and a scenario model. The three-layer modeling architecture supports the combination of some models in the 6-dimensional model.

[0157] S4, creates a scene instance, assigns the twin instance data to the scene instance according to the rules of dynamic data mapping, dynamically analyzes, calculates and instantiates the twin according to the topology model and scene model, and renders the twin visual instance of the topology and scene to support the twin application.

[0158] Specifically, refer to Figure 5 , match the twin instance data with the template according to the conditions, load the twin instance data into the matched template, calculate the twin data, generate the twin topology instance, and then generate the topology instance, render the twin visual instance of the topology and scene, and realize the 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, rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the above embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or replacements that can be easily thought of by those skilled in the art within the technical scope disclosed in the present invention should be covered 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: include: S1, build a twin model, including: S11, constructing a twin directory, wherein the twin directory uses a 6-dimensional model to record information of the twin, and the 6-dimensional model includes: an information model, a geometric model, a rule model, an operation model, a behavior model, and a simulation model; S12, constructing a twin asset catalog, wherein the twin asset catalog is used to record the inheritance information and template information of the twin model asset; the twin model asset is the data generated after the twin is instantiated under the specified conditions, and the data of the twin model asset inherits the twin and is extensible; S2, constructing a topological model through the twin model, including: combining the twin model assets using a topological model designer according to the relationship between points, lines and surfaces of the twin model, and combining them into a topological model according to a preset order or rule to realize topological twinning; S3, combining the twin model and the topology model, and using the scenario model designer to set operation rules and data mapping rules to construct a scenario model and store it in separate models; A three-layer modeling architecture is formed by a twin model, a topology model, and a scene model, and the three-layer modeling architecture supports the combination of some models in the 6-dimensional model; S4, creates a scene instance, assigns the twin instance data to the scene instance according to the rules of dynamic data mapping, dynamically analyzes, calculates and instantiates the twin according to the topology model and scene model, and renders the twin visual instance of the topology and scene to support the twin application.

2. According to claim 1, a digital twin modeling method based on a six-dimensional model three-layer architecture is characterized in that: In S1, The information model is used to store the basic properties of the twin and the surrounding direct relationship of the twin; The geometric model is used to store the visualization model; The rule model is used to store rules constraining the twins; The operation model is used to visualize and monitor the operation status, trigger relevant 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 receive the calculation results of the operation model and the rule model to trigger corresponding behaviors; The simulation model is used to constrain the twin body to load predetermined parameters, algorithms or AI capabilities, simulate or deduce real operating results, and judge and analyze the feasibility of predetermined parameters or scenarios.

3. According to claim 1, a digital twin modeling method based on a six-dimensional model three-layer architecture is characterized in that: In S1, the twin model asset inherits the existing data of the twin, and supports the definition of its own private behavior and rule data, which is stored in the twin 6-dimensional model.

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

5. According to claim 1, a digital twin modeling method based on a six-dimensional model three-layer architecture is characterized in that: In S2, the topology model includes multiple twin model assets.

6. According to claim 1, a digital twin modeling method based on a six-dimensional model three-layer architecture is characterized in that: In S2, the topology models include: 5G dedicated line topology model, PON dedicated line topology model, OTN dedicated line topology model, IPRAN dedicated line topology model, bare fiber dedicated line topology model and other types of topology models.

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

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

9. The digital twin modeling method based on the six-dimensional model three-layer architecture according to claim 1 is characterized in that: In S3, the scenario model includes: one graph with multiple forms, spatial twins, and lifecycle management.

10. The digital twin modeling method based on the six-dimensional model three-layer architecture according to claim 1 is characterized in that: In S4, the twin instance data is matched with the template according to the 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 the twin visual instance of the topology and scene is rendered to realize twin visualization and capability sharing.

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