Data collection methods and digital twin networks

Abstract

The present invention provides a data acquisition method and a digital twin network, which includes: a physical network and a twin network. The method includes: the twin network sends a data acquisition instruction to the physical network according to a data acquisition request; the physical network parses the data acquisition instruction, and performs data processing and / or knowledge representation on the original data corresponding to the data acquisition instruction; the physical network sends the target data obtained after data processing and / or knowledge representation to the twin network; in an embodiment of the present invention, the twin network sends data acquisition instructions to the physical network on demand, the physical network performs automated instruction parsing, uses the instructions to complete data processing and knowledge representation operations, and then returns the data after data processing and knowledge representation to the twin network, thereby realizing the construction of the twin network.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and in particular to a data acquisition method and a digital twin network. Background Art

[0002] A digital twin network is a network system that features physical network entities and virtual twins, with the two being able to interact and map in real time. Data is the cornerstone of building a digital twin network. Building a digital twin network requires real-time data collection from the physical network, modeling the twin network, and driving the twin network state in real time. However, collecting large amounts of data into the twin network in real time requires a large amount of storage space, and data processing and knowledge representation in the twin network modeling require powerful computing power. Furthermore, real-time data transmission consumes a large amount of bandwidth resources.

[0003] Existing solutions and methods for intelligent fault diagnosis and self-healing control systems for engineering equipment based on digital twins involve processing in a data acquisition module. Its primary function is to collect real-time operational data from the physical module regarding the engineering equipment and transmit this data to the digital twin module for digital twin simulation of the engineering equipment. This acquisition method, which collects all data from the physical system for modeling, fails to consider the potential challenges faced by the twin network due to the large amounts of data collected, such as insufficient storage resources, limited computing resources, low computational efficiency, and wasted bandwidth. Summary of the Invention

[0004] The purpose of the present invention is to provide a data acquisition method and a digital twin network to solve the problems of insufficient storage resources, tight computing resources, low computing efficiency and waste of bandwidth resources caused by the existing digital twin network collecting full data in the physical network for modeling.

[0005] In order to solve the above problems, an embodiment of the present invention provides a data collection method based on a digital twin network, wherein the digital twin network includes: a physical network and a twin network, and the data collection method includes:

[0006] The twin network sends a data collection instruction to the physical network according to the data collection request;

[0007] The physical network parses the data acquisition instruction and performs data processing and / or knowledge representation on the raw data corresponding to the data acquisition instruction;

[0008] The physical network sends the target data obtained after data processing and / or knowledge representation to the twin network.

[0009] The twin network includes: an instruction management center and at least one first data storage center; the physical network includes: at least one second data storage center;

[0010] The twin network sends a data collection instruction to the physical network according to the data collection request, including:

[0011] The instruction management center receives the data collection request sent by the first data storage center; the data collection request carries the data parameter information requested to be collected by the twin network;

[0012] The instruction management center configures the data collection instruction according to the data collection request;

[0013] The instruction management center searches for the target second data storage center in the registration information of the physical network according to the data parameter information;

[0014] The instruction management center sends the data collection instruction to the target second data storage center.

[0015] Wherein, before the instruction management center addresses the registration information of the physical network according to the data parameter information and determines the target second data storage center, the method further includes:

[0016] The instruction management center receives and stores the registration information sent by the at least one second data storage center; wherein the registration information includes at least one of the following:

[0017] the address of the second data storage center;

[0018] the data type of the second data storage center;

[0019] The indicator name of the data in the second data storage center;

[0020] The data source name of the second data storage center;

[0021] The data size of the second data storage center.

[0022] The data collection instruction includes at least one of the following:

[0023] Rule-based mathematical expressions;

[0024] executable files;

[0025] Dynamic data collection frequency;

[0026] Data parameter list;

[0027] m format program text file;

[0028] Text file with parameter configuration;

[0029] AI model.

[0030] The physical network parses the data acquisition instruction and performs data processing and / or knowledge representation on the raw data corresponding to the data acquisition instruction, including:

[0031] The target second data storage center parses the data acquisition instruction and obtains the original data corresponding to the data acquisition instruction;

[0032] The target second data storage center performs data processing and / or knowledge representation on the original data according to the data acquisition instruction.

[0033] The data processing includes at least one of data cleaning, data deduplication, missing value filling, data normalization, data association, automatic labeling and conflict verification.

[0034] The physical network sends the target data obtained after data processing and / or knowledge representation to the twin network, including:

[0035] The target second data storage center sends the destination data to the first data storage center of the twin network;

[0036] The first data storage center constructs a twin network based on the target data.

[0037] An embodiment of the present invention further provides a digital twin network, comprising: a physical network and a twin network;

[0038] The twin network is used to: send a data collection instruction to the physical network according to a data collection request;

[0039] The physical network is used to: parse the data acquisition instruction, and perform data processing and / or knowledge representation on the original data corresponding to the data acquisition instruction;

[0040] The physical network is also used to send the target data obtained after data processing and / or knowledge representation to the twin network.

[0041] The twin network includes: an instruction management center and at least one first data storage center; the physical network includes: at least one second data storage center;

[0042] The instruction management center is used to:

[0043] Receive a data collection request sent by the first data storage center; the data collection request carries data parameter information requested to be collected by the twin network;

[0044] configuring the data collection instruction according to the data collection request;

[0045] Addressing the data in the registration information of the physical network according to the data parameter information to determine the target second data storage center;

[0046] The data collection instruction is sent to the target second data storage center.

[0047] The instruction management center is further configured to:

[0048] Receive and store registration information sent by the at least one second data storage center; wherein the registration information includes at least one of the following:

[0049] the address of the second data storage center;

[0050] the data type of the second data storage center;

[0051] The indicator name of the data in the second data storage center;

[0052] The data source name of the second data storage center;

[0053] The data size of the second data storage center.

[0054] The data collection instruction includes at least one of the following:

[0055] Rule-based mathematical expressions;

[0056] executable files;

[0057] Dynamic data collection frequency;

[0058] Data parameter list;

[0059] m format program text file;

[0060] Text file with parameter configuration;

[0061] AI model.

[0062] Wherein, the target second data storage center is used for:

[0063] Parsing the data acquisition instruction to obtain original data corresponding to the data acquisition instruction;

[0064] The raw data is processed and / or represented according to the data acquisition instruction.

[0065] The data processing includes at least one of data cleaning, data deduplication, missing value filling, data normalization, data association, automatic labeling and conflict verification.

[0066] Wherein, the target second data storage center is further used for:

[0067] Sending the destination data to the first data storage center of the twin network;

[0068] The first data storage center is further used to: construct a twin network based on the target data.

[0069] An embodiment of the present invention also provides a digital twin network, comprising a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the data acquisition method based on the digital twin network as described above is implemented.

[0070] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the data acquisition method based on the digital twin network as described above.

[0071] The above technical solution of the present invention has at least the following beneficial effects:

[0072] In the data acquisition method and digital twin network of the embodiments of the present invention, the twin network sends data acquisition instructions to the physical network on demand, the physical network performs automatic instruction parsing, completes data processing and / or knowledge representation operations according to the instructions, and then returns the data after data processing and / or knowledge representation to the twin network, thereby realizing the construction of the twin network. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 A flowchart showing the steps of a data acquisition method based on a digital twin network provided by an embodiment of the present invention;

[0074] Figure 2 An example diagram showing a data acquisition method based on a digital twin network provided by an embodiment of the present invention;

[0075] Figure 3 A schematic diagram showing the structure of a digital twin network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0076] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0077] like Figure 1As shown, an embodiment of the present invention provides a data collection method based on a digital twin network, wherein the digital twin network includes: a physical network and a twin network, and the data collection method includes:

[0078] Step 101: The twin network sends a data collection instruction to the physical network according to the data collection request;

[0079] Step 102: the physical network parses the data acquisition instruction and performs data processing and / or knowledge representation on the raw data corresponding to the data acquisition instruction;

[0080] In step 103, the physical network sends the target data obtained after data processing and / or knowledge representation to the twin network.

[0081] In this embodiment of the present invention, the digital twin network is composed of a physical network and a twin network. The twin network sends data collection instructions to the physical network on demand. The physical network automatically interprets the instructions, completes data processing and / or knowledge representation operations according to the instructions, and then returns the processed and / or knowledge represented data to the twin network, thus realizing the construction of the twin network.

[0082] This data collection method reduces the data storage pressure in the twin network. By sending data collection instructions, the twin network reduces the twin network's demand for computing power to a certain extent. For the twin network, data processing, knowledge representation, etc. can all be completed in the physical network. In the physical network, because data is generally stored in a distributed manner, distributed computing can be performed in the physical network during data collection, which greatly reduces the computing power requirements of the twin network and can greatly improve the efficiency of data processing and knowledge representation. What is transmitted between the physical network and the twin network is data after data processing and knowledge representation, which greatly reduces the bandwidth resources consumed by data transmission.

[0083] In at least one embodiment of the present invention, the twin network includes: an instruction management center and at least one first data storage center; the physical network includes: at least one second data storage center; accordingly, step 101 includes:

[0084] The instruction management center receives the data collection request sent by the first data storage center; the data collection request carries the data parameter information requested to be collected by the twin network;

[0085] The instruction management center configures the data collection instruction according to the data collection request;

[0086] The instruction management center searches for the target second data storage center in the registration information of the physical network according to the data parameter information;

[0087] The instruction management center sends the data collection instruction to the target second data storage center.

[0088] In the embodiment of the present invention, an instruction management center and a first data storage center are constructed in the twin network. The instruction management center has the following two functions:

[0089] First, the instruction management center can generate, modify, combine, and delete data collection instructions as needed based on data collection requests, thereby realizing flexible and programmable operations of data collection instructions.

[0090] Second, the registration information of the second data storage center in the physical network can be managed, and the registration information can be intelligently searched according to the data collection request to address and determine the second data storage center corresponding to the data collection request (ie, the target second data storage center).

[0091] In an embodiment of the present invention, all data storage units in the physical network are defined as a second data storage center. On the one hand, the second data storage center can store data such as the topology structure, performance indicators, operating status, logs, traffic scheduling, business needs, etc. in the physical network. On the other hand, a new instruction parsing function is added to automatically parse the data collection instructions sent by the instruction management center in the twin network, and execute the data collection instructions based on local data to perform data processing and knowledge representation.

[0092] As an optional embodiment, before the instruction management center addresses the registration information of the physical network according to the data parameter information and determines the target second data storage center, the method further includes:

[0093] The instruction management center receives and stores the registration information sent by the at least one second data storage center; wherein the registration information includes at least one of the following:

[0094] the address of the second data storage center;

[0095] the data type of the second data storage center;

[0096] The indicator name of the data in the second data storage center;

[0097] The data source name of the second data storage center;

[0098] The data size of the second data storage center.

[0099] It should be noted that each second data storage center included in the physical network can send its own registration information to the instruction management center respectively.

[0100] As another optional embodiment, the data collection instruction carries at least one of the following:

[0101] Rule-based mathematical expressions;

[0102] executable files;

[0103] Dynamic data collection frequency;

[0104] Data parameter list;

[0105] m format program text file;

[0106] Text file with parameter configuration;

[0107] AI model.

[0108] Optionally, the executable file carried in the data collection instruction is an executable model in exe format. The data collection instructions mentioned in the embodiment of the present invention can be flexibly created, modified, combined, deleted, etc. according to data collection requirements, and are not specifically limited here.

[0109] In at least one embodiment of the present invention, step 102 includes:

[0110] The target second data storage center parses the data acquisition instruction and obtains the original data corresponding to the data acquisition instruction;

[0111] The target second data storage center performs data processing and / or knowledge representation on the original data according to the data acquisition instruction.

[0112] The data processing includes at least one of data cleaning, data deduplication, missing value filling, data normalization, data association, automatic labeling and conflict verification.

[0113] Optionally, knowledge representation refers to representing raw data into a data structure that can be used for efficient computing through an instruction model. Such a representation result is closer to machine language, which is conducive to the rapid and accurate construction of the model.

[0114] In another optional embodiment of the present invention, step 103 includes:

[0115] The target second data storage center sends the destination data to the first data storage center of the twin network;

[0116] The first data storage center constructs a twin network based on the target data.

[0117] In the implementation of the present invention, the instruction management center of the twin network is mainly used to manage the registration information of the second data storage center in the physical network. The registration information mainly includes the IP address of the physical network data storage center, data type, name of each indicator in the data, name of the data source, data size and other key information; on the other hand, it is mainly used to adaptively configure data acquisition instructions according to the data acquisition needs of the first data storage center in the twin network, and address and send data acquisition instructions. The data acquisition instructions carry information including rule-based mathematical expressions, executable files, dynamic acquisition frequencies, parameter lists, .m format program text files, text files with parameter configurations and other types of files. The data acquisition instructions are flexible and programmable, and can be created, modified, combined, deleted and other operations at any time according to needs.

[0118] When the first data storage center of the twin network initiates a data collection request to the instruction management center, the instruction management center searches for the address of the second data storage center of the required physical network in the registration information based on the data type, data name and other key information corresponding to the data collection request, and configures the data collection instructions that can realize data processing and knowledge representation functions as needed, and sends the data collection instructions to the second data storage center in the physical network according to the address.

[0119] The first data storage center of the twin network is mainly used to store the valid information after data processing and knowledge representation returned by the second data storage center in the physical network.

[0120] In the implementation of the present invention, all data storage units in the physical network are defined as the second data storage center. On the one hand, the second data storage center can store data such as the topology structure, performance indicators, operating status, logs, traffic scheduling, business needs, etc. in the physical network. On the other hand, a new instruction parsing function is added to automatically parse the instructions sent by the instruction management center in the twin network, configure the operating environment for executing instructions according to the instruction requirements, and perform data processing and knowledge representation based on the instruction model and data. Data processing mainly includes data cleaning, deduplication, missing value filling, normalization, association, conflict verification, etc. Knowledge representation refers to the representation of raw data into a data structure that can be used for efficient calculation through the instruction model. Such a representation result is closer to machine language, which is conducive to the rapid and accurate construction of the model.

[0121] In order to more clearly describe the data collection method provided by the embodiment of the present invention, the following Figure 2 Provide detailed explanation.

[0122] Step 1: The second data storage center in the physical network registers with the instruction management center in the twin network. The registration information includes the address of the data storage center, data type, name of each indicator in the data, data source name, data size, etc.

[0123] Step 2: The first data storage center in the twin network sends a data collection request to the instruction management center;

[0124] Step 3: The instruction management center intelligently searches for registration information based on the data collection request to address it and configures the data collection instructions. The data collection instructions carry information including rule-based mathematical expressions, executable files, dynamic collection frequencies, parameter lists, .m format program text files, text files with parameter configurations, and other types of files, which can be flexibly created, modified, combined, and deleted according to needs.

[0125] Step 4: The instruction management center in the twin network sends the corresponding instruction to the second data storage center in the physical network according to the address;

[0126] Step 5: After receiving the instruction, the second data storage center in the physical network parses it and executes it according to the instruction, such as filling in missing data, data association, automatic labeling, knowledge representation, etc.

[0127] Step 6: The second data storage center in the physical network sends the processed and characterized data to the first data storage center in the twin network.

[0128] In summary, in an embodiment of the present invention, the twin network sends data acquisition instructions to the physical network on demand, the physical network performs automatic instruction parsing, completes data processing and / or knowledge representation operations according to the instructions, and then returns the data after data processing and / or knowledge representation to the twin network, thereby realizing the construction of the twin network.

[0129] like Figure 3 As shown, an embodiment of the present invention further provides a digital twin network, which includes: a physical network 300 and a twin network 310;

[0130] The twin network 310 is used to: send a data collection instruction to the physical network according to the data collection request;

[0131] The physical network 300 is used to: parse the data acquisition instruction, and perform data processing and / or knowledge representation on the raw data corresponding to the data acquisition instruction;

[0132] The physical network 300 is also used to send the target data obtained after data processing and / or knowledge representation to the twin network.

[0133] As an optional embodiment, the twin network includes: an instruction management center and at least one first data storage center; the physical network includes: at least one second data storage center;

[0134] The instruction management center is used to:

[0135] Receive a data collection request sent by the first data storage center; the data collection request carries data parameter information requested to be collected by the twin network;

[0136] configuring the data collection instruction according to the data collection request;

[0137] Addressing the data in the registration information of the physical network according to the data parameter information to determine the target second data storage center;

[0138] The data collection instruction is sent to the target second data storage center.

[0139] As an optional embodiment, the instruction management center is further configured to:

[0140] Receive and store registration information sent by the at least one second data storage center; wherein the registration information includes at least one of the following:

[0141] the address of the second data storage center;

[0142] the data type of the second data storage center;

[0143] The indicator name of the data in the second data storage center;

[0144] The data source name of the second data storage center;

[0145] The data size of the second data storage center.

[0146] As an optional embodiment, the data collection instruction carries at least one of the following:

[0147] Rule-based mathematical expressions;

[0148] executable files;

[0149] Dynamic data collection frequency;

[0150] Data parameter list;

[0151] m format program text file;

[0152] Text file with parameter configuration;

[0153] AI model.

[0154] As an optional embodiment, the target second data storage center is used to:

[0155] Parsing the data acquisition instruction to obtain original data corresponding to the data acquisition instruction;

[0156] The raw data is processed and / or represented according to the data acquisition instruction.

[0157] The data processing includes at least one of data cleaning, data deduplication, missing value filling, data normalization, data association, automatic labeling and conflict verification.

[0158] As an optional embodiment, the target second data storage center is further configured to:

[0159] Sending the destination data to the first data storage center of the twin network;

[0160] The first data storage center is further used to: construct a twin network based on the target data.

[0161] In an embodiment of the present invention, the twin network sends data collection instructions to the physical network on demand, the physical network performs automatic instruction parsing, completes data processing and / or knowledge representation operations according to the instructions, and then returns the data after data processing and / or knowledge representation to the twin network, thereby realizing the construction of the twin network.

[0162] It should be noted that the digital twin network provided in the embodiment of the present invention is a digital twin network capable of executing the above-mentioned data acquisition method. All embodiments of the above-mentioned data acquisition method are applicable to the digital twin network and can achieve the same or similar beneficial effects.

[0163] An embodiment of the present invention also provides a digital twin network, including a memory, a processor, and a computer program stored on the memory and runnable on the processor. When the processor executes the program, the various processes in the embodiment of the data acquisition method based on the digital twin network as described above are implemented, and the same technical effect can be achieved. To avoid repetition, they will not be described here.

[0164] The embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the various processes in the embodiment of the data acquisition method based on the digital twin network described above are implemented, and the same technical effects are achieved. To avoid repetition, the details are not described here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0165] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to magnetic disk storage and optical storage, etc.) containing computer-usable program code.

[0166] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 means for performing functions specified in one or more processes and / or one or more blocks.

[0167] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable storage medium produce a paper product including an instruction device that implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0168] These computer program instructions can also be loaded onto a computer or other programmable data processing device to cause the computer or other programmable device to execute a series of operating steps to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0169] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A data acquisition method based on a digital twin network, characterized in that: The digital twin network includes: a physical network and a twin network, and the data collection method includes: The twin network sends a data collection instruction to the physical network according to the data collection request; The physical network parses the data acquisition instruction and performs data processing and / or knowledge representation on the raw data corresponding to the data acquisition instruction; The physical network sends the target data obtained after data processing and / or knowledge representation to the twin network; The twin network includes: an instruction management center and at least one first data storage center; the physical network includes: at least one second data storage center; The twin network sends a data collection instruction to the physical network according to the data collection request, including: The instruction management center receives the data collection request sent by the first data storage center; the data collection request carries the data parameter information requested to be collected by the twin network; The instruction management center configures the data collection instruction according to the data collection request; The instruction management center searches for the target second data storage center in the registration information of the physical network according to the data parameter information; The instruction management center sends the data collection instruction to the target second data storage center.

2. The method according to claim 1, characterized in that Before the instruction management center addresses the registration information of the physical network according to the data parameter information and determines the target second data storage center, the method further includes: The instruction management center receives and stores the registration information sent by the at least one second data storage center; wherein the registration information includes at least one of the following: the address of the second data storage center; the data type of the second data storage center; The indicator name of the data in the second data storage center; The data source name of the second data storage center; The data size of the second data storage center.

3. The method according to claim 1, characterized in that The data collection instruction carries at least one of the following: Rule-based mathematical expressions; executable files; Dynamic data collection frequency; Data parameter list; m format program text file; Text file with parameter configuration; AI model.

4. The method according to claim 1, wherein The physical network parses the data acquisition instruction and performs data processing and / or knowledge representation on the original data corresponding to the data acquisition instruction, including: The target second data storage center parses the data acquisition instruction and obtains the original data corresponding to the data acquisition instruction; The target second data storage center performs data processing and / or knowledge representation on the original data according to the data acquisition instruction.

5. The method according to claim 4, characterized in that The data processing includes at least one of data cleaning, data deduplication, missing value filling, data normalization, data association, automatic labeling and conflict verification.

6. The method according to claim 1, characterized in that The physical network sends the target data obtained after data processing and / or knowledge representation to the twin network, including: The target second data storage center sends the destination data to the first data storage center of the twin network; The first data storage center constructs a twin network based on the target data.

7. A digital twin network, characterized in that: The digital twin network includes: a physical network and a twin network; The twin network is used to: send a data collection instruction to the physical network according to a data collection request; The physical network is used to: parse the data acquisition instruction, and perform data processing and / or knowledge representation on the original data corresponding to the data acquisition instruction; The physical network is further used to: send the target data obtained after data processing and / or knowledge representation to the twin network; The twin network includes: an instruction management center and at least one first data storage center; the physical network includes: at least one second data storage center; The instruction management center is used to: Receive a data collection request sent by the first data storage center; the data collection request carries data parameter information requested to be collected by the twin network; configuring the data collection instruction according to the data collection request; Addressing the data in the registration information of the physical network according to the data parameter information to determine the target second data storage center; The data collection instruction is sent to the target second data storage center.

8. The digital twin network according to claim 7, characterized in that: The instruction management center is further used to: Receive and store registration information sent by the at least one second data storage center; wherein the registration information includes at least one of the following: the address of the second data storage center; the data type of the second data storage center; The indicator name of the data in the second data storage center; The data source name of the second data storage center; The data size of the second data storage center.

9. The digital twin network according to claim 7, characterized in that: The data collection instruction carries at least one of the following: Rule-based mathematical expressions; executable files; Dynamic data collection frequency; Data parameter list; m format program text file; Text file with parameter configuration; AI model.

10. The digital twin network according to claim 7, characterized in that: The target second data storage center is used for: Parsing the data acquisition instruction to obtain original data corresponding to the data acquisition instruction; The raw data is processed and / or represented according to the data acquisition instruction.

11. The digital twin network according to claim 10, characterized in that: The data processing includes at least one of data cleaning, data deduplication, missing value filling, data normalization, data association, automatic labeling and conflict verification.

12. The digital twin network according to claim 7, characterized in that: The target second data storage center is further used for: Sending the destination data to the first data storage center of the twin network; The first data storage center is further used to: construct a twin network based on the target data.

13. A digital twin network, comprising a memory, a processor, and a program stored in the memory and executable on the processor; characterized in that: When the processor executes the program, it implements the data acquisition method based on the digital twin network as described in any one of claims 1 to 6.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the data acquisition method based on the digital twin network as described in any one of claims 1 to 6 are implemented.

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