High-concurrency-oriented digital twin platform

Abstract

The invention discloses a high-concurrency-oriented digital twin platform, and relates to the technical field of computers. The platform comprises a physical data acquisition and processing module, a digital virtual modeling module, a platform service integration module, a virtual simulation module and a physical entity monitoring module, the physical data acquisition and processing module is used for acquiring operation parameters of a physical entity and modeling data of the physical entity, and preprocessing the operation parameters and the modeling data to obtain target operation parameters; the digital virtual modeling module is used for utilizing preset three-dimensional modeling software to construct a three-dimensional model through the target operation parameters; the platform service integration module is used for deploying the three-dimensional model on a digital twin platform; the virtual simulation module inputs the simulation data into a three-dimensional model deployed on the digital twin platform and determines a simulation result of the three-dimensional model; and the physical entity monitoring module is used for determining the working risk level of the physical entity corresponding to the three-dimensional model according to the simulation result, thereby realizing prevention and control of the risk of the physical entity and ensuring the operation stability.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a high-concurrency digital twin platform. Background Art

[0002] The digital twin platform is a virtual platform corresponding to the real physical world created by digital technology. Its purpose is to simulate the real world through digital means. The digital twin platform has broad application prospects in many industries, such as manufacturing, smart cities, medical health, etc., and is of great significance to improving production efficiency, optimizing resource allocation, and improving service quality.

[0003] With the development of digital twin platforms, they can already simulate most scenarios. However, in existing technologies, digital twin platforms have not been effectively optimized for three-dimensional models, resulting in the inability to predict risks in the process of virtual simulation for problems and failures, and thus the inability to quickly prevent and control risks when they occur. Therefore, how to determine the working risks of physical entities through digital twin platforms has become an urgent problem to be solved. Summary of the invention

[0004] The present invention provides a high-concurrency digital twin platform to solve the problem of being unable to predict risks during virtual simulation.

[0005] According to one aspect of the present invention, a high-concurrency digital twin platform is provided, which includes: a physical data acquisition and processing module, a digital virtual modeling module, a platform service integration module, a virtual simulation module and a physical entity monitoring module;

[0006] The physical data acquisition and processing module is connected to the digital virtual modeling module, and is used to obtain the operating parameters of the physical entity and the modeling data of the physical entity, and pre-process the operating parameters and the modeling data to obtain the target operating parameters;

[0007] The digital virtual modeling module is used to construct a three-dimensional model using the target operating parameters using the preset three-dimensional modeling software;

[0008] The platform service integration module is connected to the digital virtual modeling module and the virtual simulation module respectively, and is used to deploy the three-dimensional model on the digital twin platform;

[0009] The virtual simulation module is used to input simulation data into the three-dimensional model deployed on the digital twin platform to determine the simulation result of the three-dimensional model;

[0010] The physical entity monitoring module is connected to the virtual simulation module and is used to determine the work risk level of the physical entity corresponding to the three-dimensional model according to the simulation result.

[0011] In one embodiment, the physical entity monitoring module is further used to determine a preset emergency plan corresponding to the work risk level according to the work risk level.

[0012] In one embodiment, the high-concurrency oriented digital twin platform further includes: a three-dimensional model optimization processing module;

[0013] The digital virtual modeling module is connected to the platform service integration module via the three-dimensional model optimization processing module, and the three-dimensional model optimization processing module is used to create a detail level of the three-dimensional model and perform parameter rendering on the three-dimensional model.

[0014] In one embodiment, the three-dimensional model optimization processing module is also used to identify simplifiable areas of the three-dimensional model, simplify the simplifiable areas according to preset simplification rules, and adjust the model texture of the three-dimensional model according to preset model texture processing rules.

[0015] In one embodiment, the high-concurrency digital twin platform further includes: a data security protection processing module;

[0016] The data security protection processing module is connected between the virtual simulation module and the physical entity monitoring module, and the data security protection processing module is used to encrypt the simulation data input into the virtual simulation module and the generated simulation results through a preset encryption algorithm.

[0017] In one embodiment, the preset encryption algorithm includes at least an RSA encryption algorithm and a message digest algorithm.

[0018] In one embodiment, the high-concurrency oriented digital twin platform further includes: a server optimization module;

[0019] The server optimization module is connected to the virtual simulation module, and the server optimization module is used to create a load balancing rule for the execution server of the virtual simulation module, so that the virtual simulation module distributes the simulation data to the execution server according to the load balancing rule to determine the corresponding simulation result.

[0020] In one embodiment, the server optimization module is further used to determine the storage location of the simulation results.

[0021] In one embodiment, the high-concurrency oriented digital twin platform further includes: an emergency processing module;

[0022] The emergency processing module is connected to the physical entity monitoring module and is used to set a preset emergency plan corresponding to each work risk level.

[0023] In one embodiment, the high-concurrency digital twin platform further includes: a data feedback module;

[0024] The data feedback module is connected to the physical entity monitoring module and the physical data acquisition and processing module respectively, and is used to extract simulation data corresponding to the simulation results with a work risk level of no risk, and transmit the simulation data to the physical data acquisition and processing module, so that the physical data acquisition and processing module processes the simulation results as operating parameters.

[0025] The technical solution of the embodiment of the present invention is connected with the digital virtual modeling module through a physical data acquisition and processing module, which is used to obtain the operating parameters of the physical entity and the modeling data of the physical entity, and pre-process the operating parameters and the modeling data to obtain the target operating parameters. The digital virtual modeling module uses preset three-dimensional modeling software to build a three-dimensional model through the target operating parameters. The platform service integration module deploys the three-dimensional model on the digital twin platform. The virtual simulation module inputs simulation data into the three-dimensional model deployed on the digital twin platform to determine the simulation result of the three-dimensional model. The physical entity monitoring module determines the work risk level of the physical entity corresponding to the three-dimensional model according to the simulation result, so as to realize the early prediction of the operation risk of the physical entity, facilitate the prevention and control of work risks, and ensure the stability of the operation of the physical entity.

[0026] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 It is a structural schematic diagram of a high-concurrency digital twin platform provided according to the first embodiment of the present invention;

[0029] Figure 2 It is a structural schematic diagram of a high-concurrency digital twin platform provided according to the second embodiment of the present invention;

[0030] Figure 3This is a structural diagram of a high-concurrency digital twin platform provided according to Embodiment 3 of the present invention;

[0031] Figure 4 It is a structural schematic diagram of a high-concurrency digital twin platform provided according to Embodiment 4 of the present invention;

[0032] Figure 5 It is a structural schematic diagram of a high-concurrency digital twin platform provided according to Embodiment 5 of the present invention;

[0033] Figure 6 is a structural schematic diagram of a high-concurrency digital twin platform provided according to Embodiment 6 of the present invention;

[0034] Figure 7 is a structural diagram of a physical data acquisition and processing module provided according to Embodiment 6 of the present invention;

[0035] Figure 8 is a structural schematic diagram of a digital virtual modeling module provided according to Embodiment 6 of the present invention;

[0036] Fig. 9 is a structural schematic diagram of a three-dimensional model optimization processing module provided according to Embodiment 6 of the present invention;

[0037] Fig.10 is a structural diagram of a server optimization module provided according to Embodiment 6 of the present invention;

[0038] Fig.11 is a structural diagram of a server optimization module provided according to Embodiment 6 of the present invention;

[0039] Fig.12 is a structural schematic diagram of a security protection processing module provided according to Embodiment 6 of the present invention;

[0040] Fig.13 It is a structural diagram of a physical entity monitoring module provided according to Embodiment 6 of the present invention. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0042] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0043] Embodiment 1

[0044] Figure 1 is a schematic diagram of the structure of a high-concurrency digital twin platform provided according to the first embodiment of the present invention. This embodiment is applicable to the situation of risk warning for physical entities. Figure 1 As shown, the high-concurrency digital twin platform includes: a physical data acquisition and processing module 11, a digital virtual modeling module 12, a platform service integration module 13, a virtual simulation module 14 and a physical entity monitoring module 15.

[0045] The physical data acquisition and processing module 11 is connected to the digital virtual modeling module 12, and is used to obtain the operating parameters of the physical entity and the modeling data of the physical entity, and pre-process the operating parameters and the modeling data to obtain the target operating parameters;

[0046] A digital virtual modeling module 12 is used to construct a three-dimensional model by using a preset three-dimensional modeling software and target operating parameters;

[0047] The platform service integration module 13 is connected to the digital virtual modeling module 12 and the virtual simulation module 14 respectively, and is used to deploy the three-dimensional model on the digital twin platform;

[0048] The virtual simulation module 14 is used to input simulation data into the three-dimensional model deployed on the digital twin platform and determine the simulation result of the three-dimensional model;

[0049] The physical entity monitoring module 15 is connected to the virtual simulation module 14 and is used to determine the work risk level of the physical entity corresponding to the three-dimensional model according to the simulation result.

[0050] In the embodiment, the physical data acquisition and processing module 11 is connected to the digital virtual modeling module 12 , the platform service integration module 13 is respectively connected to the digital virtual modeling module 12 and the virtual simulation module 14 , and the physical entity monitoring module 15 is connected to the virtual simulation module 14 .

[0051] Among them, the physical data acquisition and processing module 11 is a module for collecting the operating parameters and modeling data of the physical entity and processing the operating parameters and modeling data. In the actual operation process, sensors can be installed to detect the operating parameters and modeling data of the physical entity, and the operating parameters and modeling data obtained by the sensors are extracted through the physical data acquisition and processing module 11. Generally speaking, a physical entity is an actual object that exists in the real world and has a material form and physical properties, such as a hardware structure produced in a factory, such as an operating device such as a motor. Operating parameters refer to the values ​​of various characteristics and indicators of a physical entity under a running state, such as parameters such as speed and pressure. Modeling data refers to a series of values ​​or data used to define and describe the appearance and shape characteristics of an object, such as the length, width, texture coordinates, and material properties of a physical entity. In one embodiment, the physical data acquisition and processing module 11 preprocesses the operating parameters and modeling data, which may include data cleaning, standardizing the data formats of the operating parameters and modeling data, and marking and replacing abnormal data. The target operating parameters may also be obtained by classifying the physical entities to which the operating parameters and modeling data belong.

[0052] The preset 3D modeling software can be understood as pre-set software for 3D modeling. For example, the preset modeling tool can include one or more of Autodesk 3ds Max, Maya, Blender, ZBrush, Cinema 4D, and SolidWorks. In the actual operation process, the digital virtual modeling module 12 can select the preset 3D modeling software, import the target operating parameters into the preset 3D modeling software, and build a 3D model.

[0053] The platform service integration module 13 can be connected to the digital virtual modeling module 12 and the virtual simulation module 14 respectively, and the three-dimensional model can be deployed on the digital twin platform through the platform service integration module 13. In the actual operation process, the three-dimensional model can be imported into the digital twin platform, and relevant configuration and mapping can be performed, and each part of the three-dimensional model can be associated with the target operating parameters of the physical entity to realize real-time data-driven three-dimensional model display and interaction.

[0054] Simulation data can be understood as data used for simulation or simulation. Simulation data can be data set according to user needs to simulate the work risk of inputting simulation data into a physical entity in advance before actual application. Generally speaking, simulation data can include operating parameters of the physical entity used for simulation, such as rotation speed, environmental data, etc. In the actual operation process, the virtual simulation module 14 can input simulation data into a three-dimensional model deployed on the digital twin platform, and obtain simulation results by running the simulation data through the three-dimensional model. Furthermore, the simulation data can be backed up regularly to prevent data loss. In the event of a fault or abnormal situation, the data can be quickly restored from the backup to ensure the normal operation and data integrity of the digital twin platform.

[0055] The work risk level refers to a method for evaluating the potential risk level in the work of a physical entity. Generally speaking, the work risk level can include multiple categories, such as no risk, low risk, medium risk and high risk. For each simulation result, a rule for judging the work risk level can be pre-set. Exemplarily, a work risk level threshold interval can be set for each simulation result, and when the simulation result is located in the corresponding work risk level threshold interval, the work risk level of the simulation result is determined. In one embodiment, when the work risk level can include no risk, low risk, medium risk and high risk, and the work risk level threshold interval of no risk is 0-10, the work risk level threshold interval of low risk is 10-20, the work risk level threshold interval of medium risk is 20-30 and the work risk level threshold interval of high risk is 30-40, the simulation result is 22, and the physical entity monitoring module 15 can confirm that the work risk level of the simulation result is medium risk.

[0056] In one embodiment, the physical data acquisition and processing module 11 can be used to obtain the operating parameters and modeling data of the physical entity, and the operating parameters and modeling data are cleaned, the data formats of the operating parameters and modeling data are standardized, the abnormal data are marked and replaced, and the target operating parameters are obtained by classifying the physical entities to which the operating parameters and modeling data belong, and the target operating parameters are obtained by pre-processing, and the target operating parameters are input into the digital virtual modeling module 12. The digital virtual modeling module 12 uses the preset three-dimensional modeling software to build a three-dimensional model, and then the three-dimensional model is deployed on the digital twin platform through the platform service integration module 13. When the digital twin platform is used for simulation, the virtual simulation module 14 can input the simulation data into the three-dimensional model deployed on the digital twin platform to determine the simulation result of the three-dimensional model. The physical entity monitoring module 15 can monitor the simulation result of the three-dimensional model to determine the work risk level of the physical entity corresponding to the three-dimensional model.

[0057] In an embodiment of the present invention, a physical data acquisition and processing module is connected to a digital virtual modeling module to obtain operating parameters of a physical entity and modeling data of the physical entity, and pre-process the operating parameters and modeling data to obtain target operating parameters. The digital virtual modeling module uses preset three-dimensional modeling software to construct a three-dimensional model through target operating parameters. The platform service integration module deploys the three-dimensional model on the digital twin platform. The virtual simulation module inputs simulation data into the three-dimensional model deployed on the digital twin platform to determine the simulation result of the three-dimensional model. The physical entity monitoring module determines the working risk level of the physical entity corresponding to the three-dimensional model according to the simulation result, thereby realizing early prediction of the operating risk of the physical entity, facilitating the prevention and control of working risks, and ensuring the stability of the operation of the physical entity.

[0058] In one embodiment, the physical entity monitoring module 15 is further used to determine a preset emergency plan corresponding to the work risk level according to the work risk level.

[0059] The preset emergency plan refers to the plan and measures formulated in advance for the work risk level, and the preset emergency plan corresponding to the work risk level can be found by the work risk level. For example, the preset emergency plan may include but is not limited to reducing the speed, increasing the voltage, etc.

[0060] In the embodiment, the preset emergency plan corresponding to the work risk level can be searched according to the work risk level through the physical entity monitoring module 15. In the actual operation process, the work risk level and the preset emergency plan can be stored in association. After the work risk level of the physical entity is determined, the preset emergency plan can be determined to achieve rapid control of the risk in the case of a high work risk and ensure the safety of the physical entity operation.

[0061] Embodiment 2

[0062] Figure 2 is a structural diagram of a high-concurrency digital twin platform provided according to Embodiment 2 of the present invention, such as Figure 2 As shown, the high-concurrency digital twin platform also includes: a three-dimensional model optimization processing module 16.

[0063] The digital virtual modeling module 12 is connected to the platform service integration module 13 via the three-dimensional model optimization processing module 16, and the virtual simulation module 14 is connected to the platform service integration module 13 via the three-dimensional model optimization processing module 16. The three-dimensional model optimization processing module 16 is used to create the detail level of the three-dimensional model and perform parameter rendering on the three-dimensional model.

[0064] Among them, the level of detail (LOD) includes multiple levels, such as high detail, heavy detail and low detail. Among them, high detail contains the richest and most accurate geometric shape, texture and material information, which is used to display when the physical entity is close to the observer or in a key position in the scene. The medium detail LOD is reduced in geometric and texture complexity, but still maintains a good visual effect, which is suitable for observation at a medium distance. The low-detail geometry is greatly simplified and the texture resolution is reduced. It is mainly used when the object is far away from the observer to reduce the amount of calculation and improve rendering efficiency. Exemplarily, in the construction of a three-dimensional model, for the structure of the physical entity, the detail level of the three-dimensional model can be established by the three-dimensional model optimization processing module 16. Generally speaking, when the physical entity in the three-dimensional model is far away from the display interface of the digital twin platform, low details can be set. As the physical entity is closer to the display interface, a higher level of detail can be set. At the same time, the three-dimensional model optimization processing module 16 can adjust the parameters in the three-dimensional model to achieve the final rendering effect. In the actual operation process, you can first determine the material parameters, lighting parameters, environmental parameters and other information in the target operating parameters, and adjust the material parameters, lighting parameters and environmental parameters to obtain a more realistic and more demand-oriented three-dimensional model.

[0065] In one embodiment, the 3D model optimization processing module 16 is further used to identify simplifiable areas of the 3D model, simplify the simplifiable areas according to preset simplification rules, and adjust the model texture of the 3D model according to preset model texture processing rules.

[0066] Among them, the simplifiable area can be understood as a pre-set area where the model can be simplified. For example, the simplifiable area can include the back and internal structure of the three-dimensional model. The preset simplification rules refer to the pre-set rules for simplifying the model. For example, the number of line segments in the model can be reduced, and the level of detail of the three-dimensional model can be reduced. The preset model texture processing rules refer to the pre-set rules for processing the model texture. In the actual operation process, the model texture of the three-dimensional model can be adjusted by compressing the texture, adjusting the texture color, or adjusting the texture contrast.

[0067] In an embodiment, the three-dimensional model optimization processing module 16 can identify areas that can be simplified, and simplify the back and internal structure of the three-dimensional model through preset simplification rules, thereby reducing the overall space occupancy rate of the three-dimensional model and reducing the complexity of the three-dimensional model; at the same time, the model texture of the three-dimensional model is adjusted through preset model texture processing rules to improve the texture details in the three-dimensional model and improve the quality of the three-dimensional model.

[0068] Embodiment 3

[0069] Figure 3is a structural diagram of a high-concurrency digital twin platform provided according to Embodiment 3 of the present invention, such as Figure 3 As shown, the high-concurrency digital twin platform also includes: a data security protection processing module 17.

[0070] The data security protection processing module 17 is connected between the virtual simulation module 14 and the physical entity monitoring module 15. The data security protection processing module 17 is used to encrypt the simulation data input into the virtual simulation module 14 and the generated simulation results through a preset encryption algorithm.

[0071] In one embodiment, the preset encryption algorithm includes at least an RSA encryption algorithm and a message digest algorithm.

[0072] The data security protection processing module 17 is respectively connected to the virtual simulation module 14 and the physical entity monitoring module 15. The data security protection processing module 17 can set a preset encryption algorithm to encrypt the simulation data input into the virtual simulation module 14 and the generated simulation results to avoid data leakage and ensure data security.

[0073] In one embodiment, the data security protection processing module 17 can establish an administrator identity authentication unit to authenticate the administrator's identity when performing data query. Only after the authentication is passed can the simulation data and simulation results be accessed, thereby improving the data security protection level.

[0074] Embodiment 4

[0075] Figure 4 is a structural diagram of a high-concurrency digital twin platform provided according to Embodiment 4 of the present invention, such as Figure 4 As shown, the high-concurrency digital twin platform also includes: a server optimization module 18.

[0076] The server optimization module 18 is connected to the virtual simulation module 14 and is used to create a load balancing rule for the execution server of the virtual simulation module so that the virtual simulation module distributes the simulation data to the execution server according to the load balancing rule to determine the corresponding simulation result.

[0077] In one embodiment, the server optimization module 18 is further used to determine the storage location of the simulation results.

[0078] Among them, the load balancing rule is a criterion for determining how to distribute network traffic and run tasks among multiple execution servers. In actual operation, the load balancing rule can set a weight for each execution server and distribute requests according to the weight ratio; or, the request can be distributed to each execution server in sequence in a loop; or, the new request can be distributed to the server with the least number of current connections. The storage location can include memory databases such as Redis and Memcached to cache simulation results and simulation data. In actual operation, the storage location can be associated with the execution server.

[0079] In an embodiment, the server optimization module 18 is used to create a load balancing rule for the execution server of the virtual simulation module 14. Through the load balancing rule, the simulation task of the simulation data can be assigned to the execution server so that the execution server performs simulation according to the simulation data to obtain the corresponding simulation result. In one embodiment, the asynchronous processing rules of the simulation data are set, such as asynchronous processing is realized through a message queue, so as to improve the reliability and scalability of the simulation of the digital twin platform. Further, the server optimization module 18 can establish a fault-tolerant recovery mechanism so that the digital twin platform can automatically expand or reduce computing resources according to the load situation. Exemplarily, various performance indicators of the digital twin platform can be continuously monitored, such as the CPU usage rate, memory usage, network traffic, message queue length, etc. By setting a threshold, when these indicators exceed or fall below a specific value, the execution server is redistributed. In order to achieve the high concurrency performance of the digital twin platform, a large number of concurrent requests or simulation tasks can be reasonably allocated and processed simultaneously, the simulation function of the virtual simulation module can be optimized, and the overall processing speed and concurrency of the digital twin platform can be improved, while avoiding the collapse of a single execution server due to too many requests.

[0080] Embodiment 5

[0081] Figure 5 is a structural diagram of a high-concurrency digital twin platform provided according to Embodiment 5 of the present invention, such as Figure 5 As shown, the high-concurrency digital twin platform also includes: an emergency processing module 19 and a data feedback module 20.

[0082] The emergency processing module 19 is connected to the physical entity monitoring module 15 and is used to set a preset emergency plan corresponding to each work risk level.

[0083] The data feedback module 20 is connected to the physical entity monitoring module 15 and the physical data acquisition and processing module 11 respectively, and is used to extract simulation data corresponding to the simulation results with a work risk level of no risk, and transmit the simulation data to the physical data acquisition and processing module, so that the physical data acquisition and processing module 11 processes the simulation results as operating parameters.

[0084] In the embodiment, the emergency processing module 19 is connected to the physical entity monitoring module 15, and the data feedback module 20 is connected to the physical entity monitoring module 15 and the physical data acquisition and processing module 11 respectively. The emergency processing module 19 can generate a corresponding preset emergency plan for each risk level, so that the physical entity monitoring module 15 determines the preset emergency plan corresponding to the work risk level according to the work risk level. The data feedback module 20 can determine the simulation data corresponding to the simulation result with a work risk level of no risk, and feed back the simulation data corresponding to the simulation result with no risk to the physical data acquisition and processing module 11 to process the simulation result as an operating parameter to optimize the three-dimensional model.

[0085] In the embodiment of the present invention, a preset emergency plan corresponding to each work risk level is set through the emergency processing module to facilitate rapid prevention and control of work risks; the simulation data corresponding to the simulation result of the work risk level being no risk is extracted through the data feedback module 2, and the simulation data is transmitted to the physical data acquisition and processing module, so that the physical data acquisition and processing module processes the simulation results as operating parameters, so as to adjust the operating parameters of the three-dimensional model and the physical entity corresponding to the three-dimensional model in a targeted manner, thereby improving its accuracy and reliability.

[0086] Embodiment 6

[0087] Figure 6 is a structural diagram of a high-concurrency digital twin platform provided according to Embodiment 6 of the present invention, such as Figure 6 As shown, the physical data acquisition and processing module 11 is connected to the digital virtual modeling module 12, the platform service integration module 13 is connected to the digital virtual modeling module 12 and the virtual simulation module 14 respectively, the physical entity monitoring module 15 is connected to the virtual simulation module 14, the digital virtual modeling module 15 is connected to the platform service integration module 13 via the three-dimensional model optimization processing module 16, the data security protection processing module 17 is connected between the virtual simulation module 14 and the physical entity monitoring module 15, the server optimization module 18 is connected to the virtual simulation module 14, the emergency processing module 19 is connected to the physical entity monitoring module 15, and the data feedback module 20 is connected to the physical entity monitoring module 15 and the physical data acquisition and processing module 11 respectively.

[0088] The physical data acquisition and processing module 11 transmits the processed modeling data and operating parameters of the physical entity to the digital virtual modeling module 12 for virtual modeling. The digital virtual modeling module 12 inputs the established three-dimensional model into the three-dimensional model optimization processing module 16 for processing the three-dimensional model to improve the overall performance and quality of the three-dimensional model. After the three-dimensional model is established, it provides digital twin platform services and imports the optimized three-dimensional model into the virtual simulation software for virtual simulation to form a virtual three-dimensional simulation scene. All kinds of information in the scene are consistent with the entity information in reality. At the same time, the server optimization module 18 can optimize the server to improve the platform's high concurrency performance. The data security protection processing module 17 performs security protection processing on various data in the virtual simulation process. The physical entity can be monitored and controlled through the established simulation scene. At the same time, the physical entity monitoring module 15 predicts its risks when monitoring the physical entity and generates corresponding emergency plans for backup. The data of the physical entity's work will be collected and fed back to the physical data acquisition and processing module 11.

[0089] Furthermore, Figure 7 is a structural diagram of a physical data acquisition and processing module provided according to Embodiment 6 of the present invention. Figure 7 As shown, the physical data acquisition and processing module 11 includes a physical operation parameter acquisition unit, a physical entity modeling data acquisition unit, a data concentration and integration unit, a data automatic cleaning unit, a data automatic conversion unit, an abnormal data detection unit, an abnormal data mark replacement unit, and a data automatic classification unit. Among them, the physical operation parameter acquisition unit is used to obtain the operation parameters of the physical entity, and the physical entity modeling data acquisition unit is used to obtain the modeling data of the physical entity; the data concentration and integration unit is used to concentrate the operation parameters and modeling data. The data automatic cleaning unit is used to clean the operation parameters and modeling data, and standardize the data format through the data automatic conversion unit, the abnormal data mark replacement unit marks and replaces the abnormal data, and the data automatic classification unit classifies the operation parameters and modeling data according to the physical entities to which they belong to obtain the target operation parameters.

[0090] Furthermore, Figure 8 is a structural diagram of a digital virtual modeling module provided according to Embodiment 6 of the present invention, such as Figure 8 As shown, the digital virtual modeling module 12 includes a modeling tool selection unit, an entity data import unit, a three-dimensional modeling unit, a digital twin construction unit and a three-dimensional model saving unit. Among them, the modeling tool selection unit is used to select a preset three-dimensional modeling software, the entity data import unit is used to import the target operating parameters into the three-dimensional modeling, the three-dimensional modeling unit is used to perform modeling, and the digital twin construction unit is used to build a digital twin of the three-dimensional unit, and the three-dimensional model is saved by the three-dimensional model saving unit.

[0091] Furthermore, Fig. 9 is a structural schematic diagram of a three-dimensional model optimization processing module provided according to Embodiment 6 of the present invention. Fig. 9 As shown, the three-dimensional model optimization processing module 16 includes a model coordinate unit unification unit, an error correction topology processing unit, an LOD level setting unit, a parameter rendering processing unit, and a model simplification and texture processing unit. Among them, the model coordinate unit unification unit is used to unify the various coordinates and units in the three-dimensional model, the error correction topology processing unit corrects the topology for the errors in the model, the LOD level setting unit performs LOD level setting, the parameter rendering processing unit renders the parameters of the three-dimensional model, and the model simplification and texture processing unit simplifies some areas that can be simplified in the three-dimensional model and processes the model texture to reduce the overall space occupancy of the three-dimensional model and improve the model quality.

[0092] Furthermore, Fig.10 is a structural diagram of a server optimization module provided according to Embodiment 6 of the present invention, such as Fig.10 As shown, the server optimization module 18 includes: a load balancing processing unit, a cache strategy processing unit, a data asynchronous processing unit, a fault-tolerant recovery mechanism establishment unit and a monitoring log system establishment unit. Among them, the load balancing processing unit performs balanced processing on the load server, mainly distributes and forwards requests, and realizes dynamic server weight adjustment, distributes requests according to the load situation of the server, and the cache strategy processing unit sets up memory databases such as Redis and Memcached to cache data, and automatically updates and clears the cached data at the same time; the data asynchronous processing unit sets up a message queue (such as Rabbit MQ, Kafka) to realize the processing of asynchronous tasks, which can greatly lock the processing time of asynchronous tasks; the fault-tolerant recovery mechanism establishment unit sets rules for automatically expanding or reducing computing resources according to the load situation, and sets the main and standby modes, load balancing, automatic fault switching and other technologies to ensure the high availability of the service. The fault tolerance of the system is ensured by technologies such as data redundancy, data backup, and exception handling. The monitoring log system establishment unit establishes a monitoring log system that mainly provides real-time operation data and performance indicators of the system. It can also record all operations and abnormal information to facilitate problem troubleshooting and performance analysis, and send alarm notifications to administrators in a timely manner when the system has abnormalities or performance bottlenecks.

[0093] Furthermore, Fig.11 is a structural diagram of a server optimization module provided according to Embodiment 6 of the present invention, such as Fig.11As shown, the platform service integration module 13 includes: a twin data service unit, a twin application service unit and a twin integration service unit. The digital twin platform service is provided through the twin data service unit, the digital twin platform application is provided through the twin application service unit, and the three-dimensional model is deployed on the digital twin platform through the twin integration service unit.

[0094] Furthermore, Fig.12 is a structural diagram of a security protection processing module provided according to Embodiment 6 of the present invention. Fig.12 As shown, the security protection processing module 17 includes a data multi-level encryption unit, an access control unit and an administrator identity authentication unit. Among them, the data multi-level encryption unit selects a suitable preset encryption algorithm to perform multi-level encryption on various data in the virtual simulation, the access control unit sets the preset access control rules, and the administrator identity authentication unit establishes the administrator identity. When querying data, all the above processes must be passed before the data can be accessed.

[0095] Furthermore, Fig.13 is a structural diagram of a physical entity monitoring module provided according to Embodiment 6 of the present invention, such as Fig.13 As shown, the physical entity monitoring module 15 includes a physical entity work monitoring module, a physical entity work risk prediction module and a risk level assessment module. The physical entity work monitoring module is used to monitor the physical entity work, the physical entity work risk prediction module predicts the physical entity work risk through virtual technology, and the risk level assessment module assesses the risk level. Among them, the virtual technology used includes artificial intelligence (AI) technology, cloud computing, Internet of Things technology, virtual reality technology (VR) and augmented reality technology (AR).

[0096] The present invention is provided with a server optimization module, which can realize the high-concurrency performance of the platform through multi-level processing, and can process a large number of concurrent requests or transactions at the same time, while maintaining the stability, responsiveness and scalability of the system to meet the data processing needs of the platform. At the same time, a three-dimensional model optimization processing module is provided in the platform. After the virtual digital three-dimensional model is established, it is optimized to improve its quality and reduce the failure rate and risk rate of the later model application. An integrated system is designed for the platform's services, which can concentrate different platform services and meet the service needs of a large amount of data and applications. The platform has a very high data security protection level to avoid data leakage and ensure data security. When the platform controls the physical entity, it can also predict the operation risk in advance and generate an early warning plan in advance. When the risk occurs, it can quickly prevent and control the risk to ensure the stability and safety of the physical entity operation.

[0097] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0098] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A high-concurrency digital twin platform, characterized in that: include: Physical data acquisition and processing module, digital virtual modeling module, platform service integration module, virtual simulation module and physical entity monitoring module; The physical data acquisition and processing module is connected to the digital virtual modeling module, and is used to obtain the operating parameters of the physical entity and the modeling data of the physical entity, and pre-process the operating parameters and the modeling data to obtain the target operating parameters; The digital virtual modeling module is used to construct a three-dimensional model using the target operating parameters using the preset three-dimensional modeling software; The platform service integration module is connected to the digital virtual modeling module and the virtual simulation module respectively, and is used to deploy the three-dimensional model on the digital twin platform; The virtual simulation module is used to input simulation data into the three-dimensional model deployed on the digital twin platform to determine the simulation result of the three-dimensional model; The physical entity monitoring module is connected to the virtual simulation module and is used to determine the work risk level of the physical entity corresponding to the three-dimensional model according to the simulation result.

2. The high-concurrency digital twin platform according to claim 1, characterized in that: The physical entity monitoring module is also used to determine a preset emergency plan corresponding to the work risk level according to the work risk level.

3. The high-concurrency digital twin platform according to claim 1, characterized in that: The high-concurrency oriented digital twin platform further includes: a three-dimensional model optimization processing module; The digital virtual modeling module is connected to the platform service integration module via the three-dimensional model optimization processing module, and the virtual simulation module is connected to the platform service integration module via the three-dimensional model optimization processing module; the three-dimensional model optimization processing module is used to create a detail level of the three-dimensional model and perform parameter rendering on the three-dimensional model.

4. The high-concurrency digital twin platform according to claim 3, characterized in that: The three-dimensional model optimization processing module is also used to identify the simplifiable area of ​​the three-dimensional model, simplify the simplifiable area according to preset simplification rules, and adjust the model texture of the three-dimensional model according to preset model texture processing rules.

5. The high-concurrency digital twin platform according to claim 1, characterized in that: The high-concurrency digital twin platform also includes: a data security protection processing module; The data security protection processing module is connected between the virtual simulation module and the physical entity monitoring module, and the data security protection processing module is used to encrypt the simulation data input into the virtual simulation module and the generated simulation results through a preset encryption algorithm.

6. The high-concurrency digital twin platform according to claim 5, characterized in that: The preset encryption algorithm includes at least an RSA encryption algorithm and a message digest algorithm.

7. The high-concurrency digital twin platform according to claim 1, characterized in that: The high-concurrency digital twin platform also includes: a server optimization module; The server optimization module is connected to the virtual simulation module, and the server optimization module is used to create a load balancing rule for the execution server of the virtual simulation module, so that the virtual simulation module distributes the simulation data to the execution server according to the load balancing rule to determine the corresponding simulation result.

8. The high-concurrency digital twin platform according to claim 7, characterized in that: The server optimization module is also used to determine the storage location of the simulation results.

9. The high-concurrency digital twin platform according to claim 1, characterized in that: The high-concurrency digital twin platform also includes: an emergency processing module; The emergency processing module is connected to the physical entity monitoring module and is used to set a preset emergency plan corresponding to each work risk level.

10. The high-concurrency digital twin platform according to claim 1, characterized in that: The high-concurrency digital twin platform further includes: a data feedback module; The data feedback module is connected to the physical entity monitoring module and the physical data acquisition and processing module respectively, and is used to extract simulation data corresponding to the simulation results with a work risk level of no risk, and transmit the simulation data to the physical data acquisition and processing module, so that the physical data acquisition and processing module processes the simulation results as operating parameters.

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