Digital twin simulation method, system, device and server

Abstract

The application provides a digital twin simulation method, system, device and server, and relates to the technical field of virtual simulation. The method comprises the following steps: acquiring static data and dynamic data generated by a plurality of test equipment executing a preset test scheme, wherein the static data is parameters of the test equipment, and the dynamic data is data generated when the test equipment is running; generating a data model of each test equipment according to the static data, wherein the data model is used for representing device parameters of each test equipment and parameters of a test range where the test equipment is located; modeling each test equipment according to the data model to obtain a geometric model of each test equipment; and generating a corresponding virtual twin scene of each test equipment according to the geometric model and the corresponding dynamic data, wherein the virtual twin scene comprises a corresponding virtual device of each test equipment and the corresponding dynamic data. The application can construct a virtual twin scene for the test equipment, thereby reducing the test cost.

Description

Technical Field

[0001] This invention relates to the field of virtual simulation technology, and more specifically, to a digital twin simulation method, system, device, and server. Background Technology

[0002] In recent years, with the continuous development of science and technology, the independent development of aircraft in my country has become a task of great strategic significance.

[0003] The development of aircraft involves numerous stages, each requiring rigorous testing and verification to ensure its correctness and safety. Test equipment is distributed across different ranges in various regions. To meet the testing needs of aircraft development, test equipment from multiple ranges needs to be combined to form a logical test range, enabling the completion of large-scale integrated testing tasks.

[0004] However, since a large number of tests are required during the development of aircraft, it would consume a lot of manpower and resources to conduct tests on the test equipment every time. Therefore, it is crucial to construct virtual twin scenarios for the test equipment and conduct simulation tests in the virtual twin scenarios. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of the prior art by providing a digital twin simulation method, system, device, and server to construct virtual twin scenarios for experimental equipment and reduce experimental costs.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows:

[0007] In a first aspect, embodiments of this application provide a digital twin simulation method, the method comprising:

[0008] Acquire static and dynamic data generated by multiple test devices executing a preset test plan, wherein the static data is the parameters of the test devices and the dynamic data is the data generated by the test devices during operation;

[0009] Data models for each of the test devices are generated based on the static data. The data models are used to represent the equipment parameters of each of the test devices and the parameters of the test range where the test devices are located.

[0010] Based on the data model, each of the experimental devices is modeled to obtain the geometric model of each of the experimental devices;

[0011] Based on the geometric models and corresponding dynamic data, virtual twin scenes are generated for each of the experimental devices, wherein the virtual twin scenes include virtual devices corresponding to each of the experimental devices and the corresponding dynamic data.

[0012] Optionally, before acquiring the static and dynamic data generated by multiple test devices executing a preset test plan, the method further includes:

[0013] Receive test start command and equipment combination command, wherein the test start command includes: the identifier of the preset test plan, and the equipment combination command includes: the equipment identifiers of multiple test devices, and the combination relationship between the multiple test devices;

[0014] A test event is generated based on the test start command and the device combination command;

[0015] The test event is triggered, and the multiple test devices are controlled to execute the preset test plan, generating the static data and the dynamic data.

[0016] Optionally, the step of modeling each of the experimental devices according to the data model to obtain the geometric model of each of the experimental devices includes:

[0017] Based on the equipment parameters of the test equipment in the data model, the test equipment is modeled to obtain a three-dimensional equipment model of the test equipment.

[0018] Based on the parameters of the test range where the test equipment is located in the data model, the test range is modeled to obtain a three-dimensional test range model of the test range where the test equipment is located. The geometric model of the test equipment includes: the three-dimensional equipment model and the three-dimensional test range model.

[0019] Optionally, the data model is further used to represent the environmental parameters of the test range where the test equipment is located, and the method further includes:

[0020] Based on the environmental parameters, the environment of the test range is modeled to obtain a three-dimensional environment model of the test range where the test equipment is located. The geometric model of the test equipment includes: the three-dimensional equipment model, the three-dimensional test range model, and the three-dimensional environment model.

[0021] Optionally, generating virtual twin scenes corresponding to each of the experimental devices based on each of the geometric models and corresponding dynamic data includes:

[0022] Based on each of the geometric models, generate virtual devices corresponding to each of the experimental devices;

[0023] Match the virtual device with the dynamic data;

[0024] The dynamic data matched by each virtual device is parsed to obtain dynamic sub-data with multiple attributes;

[0025] The virtual twin scene is generated by matching multiple attributes of the virtual device and dynamic sub-data of the multiple attributes.

[0026] Secondly, embodiments of this application also provide a digital twin simulation system, which includes: a physical layer, a data layer, a virtual layer, and an implementation layer;

[0027] The physical layer includes multiple test ranges, test equipment belonging to each test range, and multiple test schemes. The test equipment is used to execute the test schemes to generate static data and dynamic data. The static data is the parameters of the test equipment, and the dynamic data is the data generated by the test equipment during operation.

[0028] The data layer is used to acquire the static data and dynamic data generated by multiple test devices executing a preset test plan through the physical layer, and to send the static data and dynamic data of the test devices to the virtual layer.

[0029] The virtual layer is used to generate data models for each of the test devices based on the static data. The data models represent the equipment parameters of each test device and the parameters of the test range where the test device is located. It is also used to model each of the test devices using the modeling tools provided by the implementation layer, based on the data models, to obtain geometric models of each test device. Furthermore, it is used to generate virtual twin scenes corresponding to each of the test devices based on the geometric models and corresponding dynamic data. The virtual twin scenes include virtual devices corresponding to each test device and the corresponding dynamic data.

[0030] Optionally, the virtual layer includes: a data parsing script, a device matching script, and an attribute matching script;

[0031] The data parsing script is used to parse the dynamic data obtained from the data layer to obtain the dynamic data corresponding to each of the test devices.

[0032] The device matching script is used to match the parsed dynamic data with the virtual device corresponding to the test device, and to send the dynamic data corresponding to the test device to the corresponding geometric model.

[0033] The attribute matching script is used to parse the dynamic data and match multiple attributes of the virtual device with the dynamic sub-data of multiple attributes.

[0034] Optionally, the digital twin simulation system further includes: a service layer;

[0035] The service layer communicates with the physical layer to manage the test equipment and test range in the physical layer;

[0036] The service layer communicates with the data layer to analyze and manage the data in the data layer.

[0037] Thirdly, embodiments of this application also provide a digital twin simulation device, the device comprising:

[0038] The data acquisition module is used to acquire static and dynamic data from multiple test devices, wherein the static data is the parameters of the test devices and the dynamic data is the data generated when the test devices are running.

[0039] A data model generation module is used to generate a data model for each of the test devices based on the static data. The data model is used to represent the equipment parameters of each of the test devices and the parameters of the test range where the test devices are located.

[0040] The geometric model generation module is used to model each of the experimental devices according to the data model to obtain the geometric model of each of the experimental devices;

[0041] The virtual twin scene generation module is used to generate virtual twin scenes corresponding to each of the aforementioned geometric models and corresponding dynamic data. The virtual twin scenes include virtual devices corresponding to each of the aforementioned experimental devices and the corresponding dynamic data.

[0042] Optionally, the device further includes:

[0043] The instruction receiving module is used to receive test start instructions and equipment combination instructions. The test start instructions include: the identifier of the preset test scheme, and the equipment combination instructions include: the equipment identifiers of multiple test devices, and the combination relationship between the multiple test devices.

[0044] The event generation module is used to generate test events based on the test start command and the device combination command;

[0045] The event triggering module is used to trigger the test event, control the multiple test devices to execute the preset test plan, and generate the static data and the dynamic data.

[0046] Optionally, the geometric model generation module includes:

[0047] The equipment modeling unit is used to model the test equipment according to the equipment parameters of the test equipment in the data model, so as to obtain a three-dimensional equipment model of the test equipment;

[0048] The target range modeling unit is used to model the test range according to the parameters of the test range where the test equipment is located in the data model, and obtain a three-dimensional target range model of the test range where the test equipment is located. The geometric model of the test equipment includes the three-dimensional equipment model and the three-dimensional target range model.

[0049] Optionally, the geometric model generation module may further include:

[0050] The environment modeling unit is used to model the environment of the test range according to the environmental parameters, and obtain a three-dimensional environment model of the test range where the test equipment is located. The geometric model of the test equipment includes: the three-dimensional equipment model, the three-dimensional test range model and the three-dimensional environment model.

[0051] Optionally, the virtual twin scene generation module includes:

[0052] The virtual device generation unit is used to generate virtual devices corresponding to each of the aforementioned geometric models.

[0053] Device data matching is used to match the virtual device with the dynamic data;

[0054] The data parsing unit is used to parse the dynamic data matched by each of the virtual devices to obtain dynamic sub-data with multiple attributes;

[0055] The virtual twin scene generation unit is used to match multiple attributes of the virtual device and dynamic sub-data of the multiple attributes to generate the virtual twin scene.

[0056] Fourthly, embodiments of this application also provide a server, including: a transceiver, a processor, and a storage medium;

[0057] The transceiver is used to receive and send data;

[0058] The storage medium stores program instructions executable by the processor;

[0059] The processor is used to invoke the program instructions stored in the storage medium to execute the steps of the digital twin simulation method as described in any of the first aspects.

[0060] Fifthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the digital twin simulation method as described in any of the first aspects.

[0061] The beneficial effects of this application are:

[0062] This application provides a digital twin simulation method, system, device, and server. It utilizes static data generated by the test equipment to execute the test plan to construct a data model, and constructs a geometric model of the test equipment based on the data model. It then generates a virtual twin scene based on the dynamic data of the geometric model of the test equipment. This allows the state of multiple test equipment in multiple test ranges involved in the preset test plan to be mapped to the virtual twin scene. As a result, the equipment state of multiple test equipment can be restored and monitored in the virtual twin scene, and virtual simulation tests can be performed using virtual equipment and dynamic data in the virtual twin scene, thereby reducing test costs. Attached Figure Description

[0063] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a schematic diagram of the structure of the digital twin simulation system provided in the embodiments of this application;

[0065] Figure 2 A data communication architecture diagram provided for an embodiment of this application;

[0066] Figure 3 Flowchart of the digital twin simulation method provided in the embodiments of this application Figure 1 ;

[0067] Figure 4 Flowchart of the digital twin simulation method provided in the embodiments of this application Figure 2 ;

[0068] Figure 5 Flowchart of the digital twin simulation method provided in the embodiments of this application Figure 3 ;

[0069] Figure 6 Flowchart of the digital twin simulation method provided in the embodiments of this application Figure 4 ;

[0070] Figure 7 This is a schematic diagram of the structure of the digital twin simulation device provided in the embodiments of this application;

[0071] Figure 8 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0073] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0074] Furthermore, the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Additionally, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0075] It should be noted that, where there is no conflict, the features in the embodiments of this application can be combined with each other.

[0076] Before providing a detailed description of the digital twin simulation method, system, device, and server provided in the embodiments of this application, the technical field in which these embodiments are applied will first be described. These embodiments are applied to the field of aircraft testing. Aircraft testing involves multiple test devices, software, models, data, simulators, and technical personnel. These test resources are distributed across different test ranges in different regions. To meet diverse testing needs, the test resources from multiple test ranges need to be combined to form a logical test range for large-scale integrated testing. To meet the requirements of aircraft testing missions and virtual testing of logical test ranges, it is necessary to construct a virtual twin scenario corresponding to the real test scenario, so that virtual simulation testing of the test equipment can be conducted within the virtual twin scenario.

[0077] Please refer to Figure 1 This is a schematic diagram of the structure of the digital twin simulation system provided in the embodiments of this application, as shown below. Figure 1 As shown, the digital twin simulation system includes: a physical layer, a data layer, a virtual layer, and an implementation layer;

[0078] The physical layer includes multiple test ranges, test equipment belonging to each test range, and various test schemes. The test equipment is used to execute the test schemes and generate static and dynamic data. The static data consists of the parameters of the test equipment, and the dynamic data consists of the data generated by the test equipment during operation.

[0079] The data layer is used to acquire static and dynamic data generated by multiple test devices executing preset test schemes through the physical layer, and to send the static and dynamic data of the test devices to the virtual layer.

[0080] The virtual layer is used to generate data models for each test device based on static data. The data models represent the equipment parameters of each test device and the parameters of the test range where the test device is located. It is also used to model each test device using the modeling tools provided by the implementation layer based on the data models to obtain the geometric models of each test device. Furthermore, it is used to generate virtual twin scenes for each test device based on each geometric model and the corresponding dynamic data. The virtual twin scenes include the virtual devices corresponding to each test device and the corresponding dynamic data.

[0081] The service layer is used to manage the test equipment and test range in the physical layer; it is also used to analyze and manage the data in the data layer.

[0082] In this embodiment, as Figure 1 As shown, the physical layer is the foundation of the entire digital twin simulation system. Based on application scenarios and functional structures, the physical layer is divided into: the device layer (D... l ), target range layer (B) l ) and test layer (T l ), of which, the test layer (T) l ) used for multiple target range layers (B l ) is managed by, while the target range layer (B) l ) and also the equipment layer (D l Management is carried out at the device layer (D). l ), Target Range Layer (B) l ) and test layer (T l The relationship between them can be expressed as:

[0083]

[0084] Specifically, the device layer (D) l The physical layer is the foundation, consisting of test equipment and other test resources distributed across various test ranges. Test equipment can include, for example, theodolites, high-speed cameras, radar, and Global Positioning System (GPS); the test range layer (B) is the foundation. lThe test layer consists of test ranges distributed in different areas. A test range is a comprehensive system of test equipment and resources, and also the basic unit of the flight test process; l The test layer includes multiple test plans, each containing all the resources and information needed for a single test. Typically, a test involves one or more test ranges. l ) are typically deployed on a logic range testing platform, which can test the device layer (D) l ), Target Range Layer (B) l ) and test layer (T l The system manages and schedules multiple test devices in multiple test ranges to execute test plans by configuring or selecting test plans on the logical test range platform.

[0085] The data layer manages the data in the digital twin simulation system. The data in the data layer mainly includes: physical layer data, virtual layer data, and service layer data. Physical layer data includes static data of the experimental equipment and dynamic data generated during the operation of the experimental equipment. Static data includes the attribute parameters and geometric parameters of the experimental equipment, while dynamic data includes data generated during the operation of the experimental equipment and / or data collected during the operation. Virtual layer data includes the data model, geometric model, behavioral model, and real-time and historical data generated by the virtual twin scene. Service layer data consists of data obtained from different databases and data generated by the service layer through related calculations.

[0086] In some embodiments, the data layer further includes: a historical database, a model database, and a general database, wherein historical data can be obtained from the historical database when performing simulation tests in a virtual twin scenario by synchronizing data from the real-time database to the historical database; the model database includes various models obtained by training the data.

[0087] The virtual layer, as a twin of the physical layer, consists of a data model (D). m ), geometric model (G) m ), Behavioral Model (B) m ) and virtual twin scenes (V s Composed of data models (D) m This is used to specify the format of static data, so as to convert the static data of the test equipment obtained from the data layer into a preset format, such as equipment size, equipment data, test range parameters, environmental parameters, etc.

[0088] Geometric model (G) m ) is used according to the data model (D) mThe data provided is used to model the test equipment. The geometric model describes the geometric information such as the appearance, structure and size of the test equipment. Specifically, the geometric model can include: equipment model, target range model and environment model. By performing three-dimensional rendering on the geometric model, the corresponding virtual equipment is generated.

[0089] Behavioral Model (B) m This is used to match dynamic data and virtual devices to generate virtual twin scenes (V). s ), among which, behavioral model (B m This includes: data parsing script, device matching script, and attribute matching script. The data parsing script can parse the dynamic data obtained from the data layer to obtain the dynamic data of each test device. The device matching script is used to match the dynamic data with the virtual device and allocate the dynamic data to the virtual device. The attribute matching script is used to parse the attributes of the dynamic data to obtain dynamic sub-data of multiple attributes and match the dynamic sub-data of multiple attributes with multiple attributes of the virtual device.

[0090] Data Model (D) m ), geometric model (G) m ), Behavioral Model (B) m ) and virtual twin scenes (V s The relationship between them can be expressed as:

[0091]

[0092] The implementation layer includes using 3D MAX modeling software to create three-dimensional models of each test device, obtaining geometric models of the test devices, and using Unity 3D technology to display the geometric models, thereby realizing the construction and display of virtual twins of the test devices.

[0093] In some embodiments, the implementation layer can also display the digital twin simulation system in the form of a web page through the design of a human-computer interface and interaction, and the digital twin simulation system can be accessed and operated through a client and a mobile device.

[0094] The service layer obtains data from the data layer and manages, visualizes, and analyzes the data. It can also reproduce experiments based on historical data.

[0095] In some embodiments, the service layer can also manage the devices of the physical layer and optimize the functions of the physical layer based on data analysis results.

[0096] Because flight tests in a logical test range often involve joint tests of multiple test devices across the range, the types of test devices involved are diverse, and the data acquisition interfaces and methods provided by different test devices vary significantly. Furthermore, the data formats of each test device are different, resulting in multi-source heterogeneous data. Therefore, different communication protocols are required for the test devices. Please refer to Table 1 for the communication protocols used in data communication and acquisition, and their characteristics.

[0097] Table 1 Communication Protocols and Their Characteristics

[0098]

[0099]

[0100] Please refer to Figure 2 This is a data communication architecture diagram provided in an embodiment of this application, such as... Figure 2 As shown, the data communication process includes:

[0101] The test equipment communicates with the target range data receiver via a short-range communication protocol, sending data from multiple test devices to the target range data receiver. After verifying and processing the data, the target range data receiver sends it to the local database at the target range for storage. Simultaneously, the target range data receiver sends data to the heterogeneous data acquisition interface of the cloud server via a network transmission protocol. The heterogeneous data acquisition interface organizes, summarizes, and processes the data before storing it in the cloud real-time database. The cloud real-time database provides a data consumption interface to drive the virtual layer to obtain static and dynamic data from the cloud real-time database through the data consumption interface.

[0102] It should be noted that the target range data receiver and the target range local database are located in the physical layer of the digital twin simulation system, while the cloud server and the cloud real-time database are located in the data layer of the digital twin simulation system.

[0103] In one possible implementation, since the flight test process requires the coordinated cooperation of multiple test ranges and test equipment, a large amount of real-time data will be generated during the test. In order to reduce the processing pressure and network burden of building virtual twin scenarios in the virtual layer, the heterogeneous data acquisition interface receives the test data and classifies the data into static data and dynamic data.

[0104] Static data refers to the parameters of the test equipment, the range parameters, and the environmental parameters in the test range. The parameters of the test equipment may include, for example, the basic parameters, geometric parameters, and basic operating parameters of the test equipment. The parameters of the test equipment and the range parameters generally only need to be acquired once when the system starts up. Environmental data can also be acquired periodically, instead of every time a virtual test is conducted, which can reduce the burden on the system.

[0105] Dynamic data refers to the real-time data collected by various experimental devices and sensors during the experiment. Dynamic data mainly consists of two parts: one part is the data collected by the sensors, including environmental data such as current humidity, temperature, wind speed, and wind direction; the other part is the data collected and generated by each experimental device, including GPS latitude and longitude, magnetic declination, radar signal-to-noise ratio, radial velocity, and altitude, TSPI acceleration, angular acceleration, and position BLH coordinates, and theodolite horizontal angle, vertical angle, and half-turn angle. It should be noted that although the environmental data is generated by the sensors during operation, it actually participates in the construction of the environmental model as static data in the virtual layer.

[0106] Based on the above-described digital twin simulation system, the digital twin simulation method provided in the embodiments of this application will be described below.

[0107] Please refer to Figure 3 The flowchart illustrates the digital twin simulation method provided in this application embodiment. Figure 1 ,like Figure 3 As shown, the method may include:

[0108] S20: Acquire static and dynamic data generated by multiple test devices executing a preset test plan. The static data consists of the parameters of the test devices, and the dynamic data consists of the data generated when the test devices are running.

[0109] In this embodiment, a preset test plan is selected in the logical test range test platform. The preset test plan includes the identification of multiple test devices in multiple test ranges and test-related resource information. According to the preset test plan, the multiple test devices in multiple test ranges are controlled to execute the preset test plan and generate test data.

[0110] Test data generated by multiple test devices can be sent to the cloud server of the data layer through a multi-source heterogeneous acquisition interface. The cloud server performs preliminary classification of the test data to obtain static data and dynamic data, and stores the static data and dynamic data in the cloud real-time database respectively. The virtual layer retrieves the static data and dynamic data of multiple test devices from the cloud real-time database respectively.

[0111] In one possible implementation, a pre-set test plan can be sent to the logic test range platform of the physical layer via a digital twin simulation system.

[0112] S30: Generate data models for each test device based on static data. The data models are used to represent the equipment parameters of each test device and the parameters of the test range where the test device is located.

[0113] In this embodiment, the virtual layer pre-includes blank data models of multiple test devices. The blank data models specify the data, parameters, attributes, target range parameters, and other information included in the test devices. After the virtual layer obtains the static data of the test devices from the data layer, it reads the static data and writes the specific values ​​of the data, parameters, attributes, target range parameters, and other information in the static data into the blank data models to obtain the data models of the test devices.

[0114] S40: Based on the data model, model each test device to obtain the geometric model of each test device.

[0115] In this embodiment, based on the various data, parameters, and attributes of the test equipment included in the data model, three-dimensional modeling is performed on each test equipment to obtain the geometric model of each test equipment.

[0116] In some embodiments, the virtual layer can call the 3D MAX modeling software provided by the utility layer to model each test device according to the data model, thereby obtaining the geometric model of each test device.

[0117] S50: Based on each geometric model and its corresponding dynamic data, generate a virtual twin scene for each test device. The virtual twin scene includes the virtual device corresponding to each test device and its corresponding dynamic data.

[0118] In this embodiment, a preset display tool is used to drive the geometric model of each test device to display, thereby obtaining the virtual device corresponding to each test device. The dynamic data of each test device is matched with the virtual device corresponding to each test device through the behavior model in the virtual layer, generating a virtual twin scene including the virtual device and the corresponding dynamic data. This realizes the mapping of the state of multiple test devices in multiple test ranges involved in the preset test scheme to the virtual twin scene, so that the device state of multiple test devices can be restored and monitored in the virtual twin scene.

[0119] In some embodiments, in a virtual twin scenario, each virtual device can be driven to perform virtual simulation testing based on dynamic data and test data.

[0120] The following combination Figure 4 This paper describes one method for implementing a preset test plan using test equipment.

[0121] Please refer to Figure 4 The flowchart illustrates the digital twin simulation method provided in this application embodiment. Figure 2 ,like Figure 4 As shown, before acquiring the static and dynamic data generated by multiple test devices executing a preset test plan in S20, the method may further include:

[0122] S11: Receive test start command and equipment combination command. The test start command includes the identifier of the preset test plan. The equipment combination command includes the equipment identifiers of multiple test devices and the combination relationship between the multiple test devices.

[0123] In this embodiment, the test layer of the logic range test platform provides multiple test schemes. Testers can select a preset test scheme from the multiple test schemes, select multiple test devices from the test devices of multiple ranges, set combination relationships for multiple test devices, generate device combination instructions based on the combination relationships of multiple test devices, and generate test start instructions in response to the test start operation input by the testers. The test start instructions carry the identifier of the preset test scheme selected by the testers.

[0124] S12: Generate test events based on test start instructions and equipment combination instructions.

[0125] In this embodiment, a test event is generated based on the test start command and the equipment combination command. The test event is used to drive multiple test devices to execute a preset test plan. The format of the test event is defined as follows:

[0126] Event={Equipments,Props,Attirbutes,Time}

[0127] Among them, Event is the test event, Equipment is the equipment identifier of the test equipment involved in the test, Props is the combination relationship between test equipment, Attributes is the identifier of the preset test plan, and Time is the test start time.

[0128] S13: Trigger test events, control multiple test devices to execute preset test plans, and generate static and dynamic data.

[0129] In this embodiment, the test events are sent to the server of the digital twin simulation system through a message queue. After the test initialization is completed, multiple test devices in multiple test ranges are controlled to execute the preset test plan and generate static and dynamic data.

[0130] After multiple testing devices generate static and dynamic data, the target range data receiver acquires the static and dynamic data via serial port, Bluetooth, Wi-Fi, or LAN, and sends the data to a local database for storage. The server uses WebService technology to call the heterogeneous data acquisition interface, reads data from various local databases to the server, and stores it in a cloud database, achieving real-time data acquisition. The virtual layer uses WebService technology to call the data push interface, reading static and dynamic data from the cloud database in the form of eXtensible Markup Language (XML) documents.

[0131] The following combination Figure 5 This paper provides a detailed explanation of one implementation method for modeling experimental equipment based on a data model to obtain a set model.

[0132] Please refer to Figure 5 The flowchart illustrates the digital twin simulation method provided in this application embodiment. Figure 3 ,like Figure 5 As shown, the process in S40 above, which involves modeling each test device according to the data model to obtain the geometric model of each test device, may include:

[0133] S41: Based on the equipment parameters of the test equipment in the data model, model the test equipment to obtain a three-dimensional equipment model of the test equipment.

[0134] In this embodiment, among the various parameters of the test equipment included in the data model, the equipment parameters of the test equipment are obtained. The equipment parameters may include: the size, structure, appearance, basic attribute parameters, working parameters, etc. of the test equipment. Based on the size, structure, and appearance of the test equipment, a three-dimensional model of the test equipment is performed to obtain a three-dimensional equipment model of the test equipment. Based on the basic attribute parameters and working parameters of the test equipment, the basic attribute parameters and working parameters of the three-dimensional equipment model are set.

[0135] S42: Based on the parameters of the test range where the test equipment is located in the data model, model the test range to obtain a three-dimensional test range model of the test range where the test equipment is located.

[0136] In this embodiment, among the various parameters of the test equipment included in the data model, the range parameters of the test range where the test equipment is located are obtained. The range parameters may include: the area size of the test range. Based on the area size of the test range, a three-dimensional model of the test range is performed to obtain a three-dimensional range model of the test range.

[0137] S43: Based on environmental parameters, model the environment of the test range to obtain a three-dimensional environmental model of the test range where the test equipment is located.

[0138] In this embodiment, among the various parameters of the test equipment included in the data model, environmental parameters surrounding the test range where the test equipment is located are obtained. These environmental parameters may include weather parameters of the test range, information on the surrounding mountains and vegetation, etc. Based on the weather parameters and the surrounding mountain and vegetation information, a three-dimensional model of the environment surrounding the test range is performed to obtain a three-dimensional environmental model of the test range. The geometric model of the test equipment includes: a three-dimensional equipment model, a three-dimensional test range model, and a three-dimensional environmental model.

[0139] The following combination Figure 6 This paper provides a detailed explanation of one implementation method for generating virtual twin scenes based on geometric models and dynamic data.

[0140] Please refer to Figure 6 The flowchart illustrates the digital twin simulation method provided in this application embodiment. Figure 4 ,like Figure 6 As shown, the process in S50 above, which generates virtual twin scenes for each test device based on each geometric model and its corresponding dynamic data, may include:

[0141] S51: Generate virtual devices corresponding to each experimental device based on each geometric model.

[0142] In this embodiment, a preset display tool is used to drive the display of the geometric models of each test device, thereby obtaining the virtual device corresponding to each test device. For example, the preset display driving tool can be a Unity 3D tool provided by the implementation layer.

[0143] S52: Match virtual devices and dynamic data.

[0144] In this embodiment, dynamic data is read from the cloud database in XML document format through the behavior model of the virtual layer. The data parsing script in the behavior model parses the XML document to obtain the dynamic data of multiple test devices. The data parsing script sends the obtained dynamic data of multiple test devices to the device matching script, which matches the dynamic data of multiple test devices with the virtual devices corresponding to the multiple dynamic devices.

[0145] S53: Parse the dynamic data matched by each virtual device to obtain dynamic sub-data of multiple attributes.

[0146] In this embodiment, after the dynamic data is matched with the virtual device, the attribute matching script corresponding to each virtual device parses the dynamic data and parses it into dynamic sub-data of multiple attributes.

[0147] S54: Match multiple attributes of the virtual device and dynamic sub-data of multiple attributes to generate a virtual twin scene.

[0148] In this embodiment, since the data model contains multiple attributes of the experimental equipment, after generating a geometric model based on the data model and then driving the display of the virtual device based on the geometric model, the virtual device also contains multiple attributes. After matching the dynamic sub-data of multiple attributes with the multiple attributes of the virtual device, the virtual device is driven to display the dynamic sub-data of multiple attributes through a data display script, thereby generating a virtual twin scene.

[0149] The digital twin simulation method provided in the above embodiments uses static data generated by the test equipment executing the test plan to construct a data model, and constructs a geometric model of the test equipment based on the data model. It then generates a virtual twin scene based on the dynamic data of the geometric model of the test equipment, thereby mapping the state of multiple test equipment in multiple test ranges involved in the preset test plan to the virtual twin scene. This allows the equipment state of multiple test equipment to be restored and monitored in the virtual twin scene, and virtual simulation tests can be performed using virtual equipment and dynamic data in the virtual twin scene, reducing test costs.

[0150] Please refer to Figure 7 This is a schematic diagram of the structure of the digital twin simulation device provided in the embodiments of this application, as shown below. Figure 7 As shown, the device includes:

[0151] Data acquisition module 10 is used to acquire static and dynamic data of multiple test devices. The static data is the parameters of the test devices, and the dynamic data is the data generated when the test devices are running.

[0152] The data model generation module 20 is used to generate data models for each test device based on static data. The data models are used to represent the equipment parameters of each test device and the parameters of the test range where the test device is located.

[0153] The geometric model generation module 30 is used to model each test device according to the data model and obtain the geometric model of each test device;

[0154] The virtual twin scene generation module 40 is used to generate virtual twin scenes corresponding to each test device based on each geometric model and the corresponding dynamic data. The virtual twin scene includes the virtual device corresponding to each test device and the corresponding dynamic data.

[0155] Optionally, the device may also include:

[0156] The instruction receiving module is used to receive test start instructions and equipment combination instructions. The test start instructions include: the identifier of the preset test plan, and the equipment combination instructions include: the equipment identifiers of multiple test devices, and the combination relationship between the multiple test devices.

[0157] The event generation module is used to generate test events based on the test start command and the equipment combination command;

[0158] The event triggering module is used to trigger test events, control multiple test devices to execute preset test plans, and generate static and dynamic data.

[0159] Optionally, the geometry model generation module 30 includes:

[0160] The equipment modeling unit is used to model the test equipment based on the equipment parameters of the test equipment in the data model, and obtain a three-dimensional equipment model of the test equipment.

[0161] The target range modeling unit is used to model the target range based on the parameters of the target range where the test equipment is located in the data model, and obtain a three-dimensional target range model of the target range where the test equipment is located. The geometric model of the test equipment includes a three-dimensional equipment model and a three-dimensional target range model.

[0162] Optionally, the geometry model generation module 30 may also include:

[0163] The environmental modeling unit is used to model the environment of the test range based on environmental parameters, and obtain a three-dimensional environmental model of the test range where the test equipment is located. The geometric model of the test equipment includes: a three-dimensional equipment model, a three-dimensional test range model, and a three-dimensional environment model.

[0164] Optionally, the virtual twin scene generation module 40 includes:

[0165] The virtual device generation unit is used to generate virtual devices corresponding to each experimental device based on each geometric model.

[0166] Device data matching is used to match virtual devices with dynamic data;

[0167] The data parsing unit is used to parse the dynamic data matched by each virtual device to obtain dynamic sub-data with multiple attributes;

[0168] The virtual twin scene generation unit is used to match multiple attributes of a virtual device and dynamic sub-data of multiple attributes to generate a virtual twin scene.

[0169] The above-described device is used to execute the method provided in the foregoing embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

[0170] These modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more microprocessors, or one or more Field Programmable Gate Arrays (FPGAs). Alternatively, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together as a system-on-a-chip (SOC).

[0171] Please refer to Figure 8 This is a schematic diagram of the structure of a server provided in an embodiment of this application, as shown below. Figure 8 As shown, the server 100 includes a transceiver 101, a processor 102, and a storage medium 103. The transceiver 101 is used to receive and send data, and the storage medium 103 stores program instructions executable by the processor 102. The processor 102 executes the program instructions to perform the steps of the above method embodiment. The specific implementation and technical effects are similar, and will not be described in detail here.

[0172] Optionally, the present invention also provides a program product, such as a computer-readable storage medium, including a program that, when executed by a processor, is used to perform the above-described method embodiments.

[0173] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0174] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0175] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0176] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0177] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A digital twin simulation method, characterized in that, The method comprises: acquiring static data and dynamic data generated by a plurality of test equipment executing a preset test scheme, the static data being parameters of the test equipment, and the dynamic data being data generated by the test equipment when running; wherein the plurality of test equipment is test equipment in a plurality of test ranges; generating a data model of each test equipment according to the static data, the data model being used to represent equipment parameters of each test equipment, range parameters of a test range where the test equipment is located, and environmental parameters; modeling each test equipment according to the data model to obtain a geometric model of each test equipment, the geometric model comprising: a three-dimensional equipment model, a three-dimensional range model, and a three-dimensional environmental model; the modeling each test equipment according to the data model to obtain a geometric model of each test equipment comprises: modeling the test equipment according to equipment parameters of the test equipment in the data model to obtain the three-dimensional equipment model of the test equipment; modeling the test range according to parameters of the test range where the test equipment is located in the data model to obtain the three-dimensional range model of the test range where the test equipment is located; modeling the environment of the test range according to the environmental parameters to obtain the three-dimensional environmental model of the test range where the test equipment is located; generating a corresponding virtual twin scene of each test equipment according to each geometric model and corresponding dynamic data, wherein the virtual twin scene comprises a corresponding virtual equipment of each test equipment and corresponding dynamic data; before the acquiring static data and dynamic data generated by a plurality of test equipment executing a preset test scheme, the method further comprises: receiving a test start instruction and a device combination instruction, the test start instruction comprising an identifier of the preset test scheme, and the device combination instruction comprising device identifiers of a plurality of test equipment and combination relationships between the plurality of test equipment; generating a test event according to the test start instruction and the device combination instruction; triggering the test event to control the plurality of test equipment to execute the preset test scheme to generate the static data and the dynamic data; the generating a corresponding virtual twin scene of each test equipment according to each geometric model and corresponding dynamic data comprises: generating a corresponding virtual equipment of each test equipment according to each geometric model; matching the virtual equipment and the dynamic data; analyzing dynamic sub-data of a plurality of attributes of the dynamic data matched by each virtual equipment; matching a plurality of attributes of the virtual equipment and the dynamic sub-data of a plurality of attributes to generate the virtual twin scene.

2. A digital twin simulation system, characterized in that, The digital twin simulation system is used to execute the digital twin simulation method according to claim 1, and comprises a physical layer, a data layer, a virtual layer, and an implementation layer. The physical layer comprises a plurality of test ranges, test equipment belonging to each of the test ranges, and a plurality of test schemes, the test equipment being configured to execute the test schemes to generate static data and dynamic data, the static data being parameters of the test equipment, and the dynamic data being data generated when the test equipment is in operation; The data layer is configured to acquire the static data and the dynamic data generated by the plurality of test equipment executing a preset test scheme through the physical layer, and send the static data and the dynamic data of the test equipment to the virtual layer; The virtual layer is configured to generate a data model of each of the test equipment according to the static data, the data model being configured to represent device parameters of each of the test equipment and parameters of the test range where the test equipment is located, and to model each of the test equipment by using a modeling tool provided by the implementation layer according to the data model, to obtain a geometric model of each of the test equipment, and to generate a corresponding virtual twin scene of each of the test equipment according to each of the geometric models and corresponding dynamic data, wherein the virtual twin scene comprises a corresponding virtual device of each of the test equipment and corresponding dynamic data.

3. The digital twin simulation system of claim 2, wherein, The virtual layer comprises a data analysis script, a device matching script, and an attribute matching script; The data analysis script is configured to analyze the dynamic data acquired from the data layer to obtain corresponding dynamic data of each of the test equipment; The device matching script is configured to match the analyzed dynamic data with a corresponding virtual device of the test equipment, and send the dynamic data of the test equipment to the corresponding geometric model; The attribute matching script is configured to analyze each of the dynamic data, and match a plurality of attributes of the virtual device with a plurality of dynamic sub-data of the attributes.

4. The digital twin simulation system of claim 3, wherein, The digital twin simulation system further comprises a service layer; The service layer communicates with the physical layer, and is configured to manage the test equipment and the test range in the physical layer; The service layer communicates with the data layer, and is configured to analyze and manage data in the data layer.

5. A digital twin simulation apparatus, characterized by, The digital twin simulation apparatus is configured to implement the digital twin simulation method according to claim 1, and the apparatus comprises: A data acquisition module is configured to acquire static data and dynamic data generated by a plurality of test equipment executing a preset test scheme, the static data being parameters of the test equipment, and the dynamic data being data generated when test equipment is in operation; A data model generation module is configured to generate a data model of each of the test equipment according to the static data, and the data model is configured to represent device parameters of each of the test equipment and parameters of the test range where the equipment is located; A geometric model generation module is configured to model each of the test equipment according to the data model, to obtain a geometric model of each of the test equipment; A virtual twin scene generation module is configured to generate a corresponding virtual twin scene of each of the test equipment according to each of the geometric model and corresponding dynamic data, wherein the virtual twin scene comprises a corresponding virtual device of each of the equipment and corresponding dynamic data.

6. A server, characterized by Comprise: a transceiver, a processor, and a storage medium; the transceiver is configured to receive and transmit data; the storage medium stores program instructions executable by the processor; the processor is configured to invoke the program instructions stored in the storage medium to perform the steps of the digital twin simulation method according to claim 1.

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