A coding identification method and system for the full life cycle circulation of industrial data

Abstract

The present invention discloses a coding identification method and system for the full life cycle circulation of industrial data, which relates to the field of computer technology, including: dimensioning and grading industrial data, generating label codes, JSON encoding the specific content of the collected data, and generating core codes; encrypting industrial data using an asymmetric encryption algorithm, and creating a multi-signature scheme for high-level industrial data; in the industrial data storage stage, identifying the label codes of industrial data, and classifying and storing industrial data according to the identification content; encoding the update time of updated industrial data, and attaching an update timestamp; deleting the label code, core code, public key, private key and timestamp of the industrial data to be destroyed. The advantages of the present invention are: triple encoding is performed on industrial data that is circulated in the life cycle, solving the problems of inconsistent industrial data formats, insufficient storage device capacity, and sensitive information leakage.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular to a coding recognition method and system for the full life cycle circulation of industrial data. Background Art

[0002] The data life cycle refers to the process from the generation to the destruction of a certain type of data. The full life cycle of industrial data is divided into the following stages: data collection, data storage, data processing, data update, data transmission and data destruction. Data collection refers to the collection of data from various sensors, devices or systems. These data can be various sensor data such as temperature, pressure, humidity, vibration, or production line status, equipment operation time, etc.; data transmission refers to the transmission of the collected data to a data storage or processing system; data storage refers to the safe storage of data and its subsequent access and analysis; data processing refers to various analysis and mining operations on data to extract insights and knowledge from the data; data update refers to the update and iteration of the stored data based on the dynamic transformation of industrial data; data destruction refers to the process of making the data completely disappear and unable to be recovered by any means through corresponding operations on the data and the data storage medium.

[0003] During the entire life cycle of industrial data, due to the large amount and high complexity of industrial data, problems such as inconsistent data formats, insufficient storage device capacity, and leakage of sensitive information may arise. Therefore, there is an urgent need for an improved technology and method to adapt to the characteristics and needs of industrial data. Summary of the invention

[0004] In order to solve the above technical problems, a coding and recognition method for the entire life cycle of industrial data is provided. This technical solution solves the problems raised in the above background technology, such as inconsistent data formats, insufficient storage device capacity, and leakage of sensitive information due to the large amount and high complexity of industrial data.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A coding identification method for the full life cycle circulation of industrial data, comprising:

[0007] In the industrial data collection stage, the industrial data is divided into dimensions and levels. The collected data dimensions and levels are uniquely encoded according to preset rules to form label codes. The specific content of the collected data is JSON-encoded to generate core codes.

[0008] In the industrial data transmission stage, industrial data is encrypted using an asymmetric encryption algorithm, and the same algorithm is used to generate private keys for users who need access. For high-level industrial data, a multi-signature scheme is created, requiring authorization with a specified number of user signatures to access;

[0009] In the stage of industrial data storage, the label codes of industrial data are identified, and the industrial data are classified and stored according to the identified content;

[0010] During the industrial data update phase, the updated industrial data is updated with an update time code and an update timestamp is added;

[0011] During the industrial data destruction phase, an inactivation instruction is issued to delete the label code, core code, public key, private key and timestamp of the industrial data to be destroyed.

[0012] Preferably, the dimensionalization and grading of industrial data includes: the industrial data classification dimension is based on five predetermined dimensions, namely, R&D data domain, production data domain, operation and maintenance data domain, management data domain and external data domain, and is further divided into several dimensions according to the characteristics of the industrial data; the industrial data classification level is graded from small to large according to the degree of impact on industrial production and economic benefits after being tampered with, destroyed, leaked or illegally used.

[0013] Preferably, the step of performing one-hot encoding on the dimensions and levels of the collected industrial data of different dimensions and levels according to preset rules comprises:

[0014] Create a data set based on the classification dimensions and classification levels of industrial data and import it into the coding library;

[0015] Obtain the dimensions and levels of the collected industrial data, perform unique-hot encoding on the dimensions and levels of the collected industrial data, and obtain several dimension codes and a level code;

[0016] The dimension code and the level code are arranged according to a preset rule to form a label code of the collected industrial data.

[0017] Preferably, the industrial data is encrypted using an asymmetric encryption algorithm, and a private key is generated using the same algorithm for the user who needs access, specifically including:

[0018] Encrypt industrial data using an asymmetric encryption algorithm to generate a public key and private key parameters;

[0019] Distribute the public key to every user and entity that needs access;

[0020] Based on the private key parameters, a private key is generated for each user who needs access using the asymmetric encryption algorithm.

[0021] Preferably, the multi-signature method is created for high-level industrial data, and the authorization of a specified number of user signatures is required for access, specifically including:

[0022] Preset level division rules to define the access method for industrial data at each level;

[0023] The access method includes evolving the number of signature authorizations for the encrypted industrial data from none to many according to the level from low to high;

[0024] The signature authorization refers to a user having a private key generated by the asymmetric encryption algorithm using the private key to authorize industrial data that requires access verification.

[0025] Preferably, the step of classifying and storing the industrial data according to the identified content further comprises:

[0026] The industrial data storage adopts a combination of database and distributed file system;

[0027] Identify the industrial data to be stored and determine whether it is structured data. Use a database to store structured data and semi-structured data, and use a distributed file system to store unstructured data.

[0028] Identify the tag code of the industrial data to be stored, and store the industrial data in a corresponding database or a node of a distributed file system.

[0029] Preferably, the updating time encoding of the updated industrial data and the appending of the update timestamp include:

[0030] Use the time function of the programming language to obtain the Unix timestamp of the current industrial data update;

[0031] Keep the Unix timestamp of each update and arrange them in chronological order.

[0032] Furthermore, a coding identification system for the full life cycle circulation of industrial data is proposed, which is used to implement the above-mentioned coding identification system for the full life cycle circulation of industrial data, and is characterized by comprising:

[0033] A data interception module, which is used to intercept industrial data that is undergoing life cycle circulation in real time;

[0034] A data classification module, the data classification module is electrically connected to the data interception module, and the data classification module is used to divide the industrial data into dimensions and grades;

[0035] A data encoding module, the data encoding module is electrically connected to the data interception module and the data classification module, and the data encoding module is used to encode the industrial data using different algorithms under different environments and conditions;

[0036] A data identification module, the data identification module is electrically connected to the data encoding module, and the data identification module is used to read the label code, the core code and the timestamp;

[0037] A data encryption module, the data encryption module is electrically connected to the data encoding module, the data identification module, and the data interception module, and the data encryption module is used to encrypt industrial data of different levels;

[0038] A data locating module, the data locating module is electrically connected to the data interception module and the data identification module, and the data locating module is used to locate the database and the distributed file system;

[0039] A data destruction module is electrically connected to the data interception module, and is used to generate a deactivation instruction to delete the label code, core code, public key, private key and timestamp of the industrial data to be destroyed.

[0040] Optionally, the data classification module includes:

[0041] Train with data of known dimensions and levels to obtain a trained decision tree;

[0042] The collected industrial data is classified according to the trained decision tree.

[0043] Optionally, the data encoding module includes:

[0044] A label encoding unit, wherein the label encoding unit contains a one-hot encoding algorithm, which is used to obtain the classification result of the data classification module, encode the classification result, and generate a label code;

[0045] A core coding unit, wherein the core coding unit contains a JSON coding algorithm for obtaining specific data content of the collected industrial data, encoding the specific data content, and generating core coding content;

[0046] A time coding unit includes a time function for obtaining the update time of the industrial data to be updated and generating a Unix timestamp.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] This solution improves data access efficiency by labeling and storing industrial data in categories; reduces storage costs by encoding the core content of industrial data; provides data consistency, traceability, sorting and filtering capabilities by time encoding industrial data, and also helps with caching and performance optimization; this solution also provides an encryption method for high-level industrial data to prevent sensitive information from being leaked. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of the coding identification method for the full life cycle circulation of industrial data of the present invention;

[0050] Figure 2 A flow chart of a method for performing one-hot encoding on the dimensions and levels of collected data according to the present invention;

[0051] Figure 3 A flow chart of a method for encrypting industrial data using an asymmetric encryption algorithm according to the present invention;

[0052] Figure 4 A flow chart of a method for classifying and storing industrial data according to identification content according to the present invention;

[0053] Figure 5 A flow chart of a method for updating time coding of updated industrial data according to the present invention;

[0054] Figure 6 This is a structural block diagram of the coding identification system for the full life cycle circulation of industrial data of the present invention. DETAILED DESCRIPTION

[0055] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0056] Example 1

[0057] Reference Figure 1 As shown, a coding identification method for the full life cycle circulation of industrial data includes:

[0058] S10: In the industrial data collection stage, the industrial data is divided into dimensions and grades, and the collected data dimensions and levels are uniquely encoded according to preset rules for industrial data of different dimensions and levels to form a label code, and the specific content of the collected data is JSON encoded to generate a core code;

[0059] Specifically, JSON stands for JavaScript Object Notation, which is a lightweight data exchange format. It is based on a subset of ECMAScript (js specification developed by the European Computer Association) and uses a text format that is completely independent of the programming language to store and represent data. This solution uses JSON encoding to unify the data format.

[0060] Furthermore, the industrial data is dimensioned and graded. The steps of this example also include: the industrial data classification dimension is based on five predetermined dimensions: R&D data domain, production data domain, operation and maintenance data domain, management data domain and external data domain. The industrial data classification dimension is further divided into several dimensions according to the characteristics of the industrial data. The industrial data classification level is graded from small to large according to the degree of impact on industrial production and economic benefits after tampering, destruction, leakage or illegal use.

[0061] Specifically, based on the five first-level dimensions of industrial data, further classification is carried out according to other characteristics contained in industrial data. For example, the first-level dimension research data domain can be divided into the second-level dimension R&D design data and development test data. The second-level dimension R&D design data can be divided into the third-level dimension product design files, product requirement documents, etc.

[0062] The degree of impact on industrial production and economic benefits is graded from small to large. For example, industrial data with little impact on the production and operation of industrial control systems and equipment, industrial Internet platforms, etc.; little negative impact on enterprises, or small direct economic losses; a small number of affected users and enterprises, a small production and living area, and a short duration; and a small cost to restore industrial data or eliminate negative impacts are classified into Level 1, and so on.

[0063] Further, such as Figure 2 As shown, the dimensions and levels of the collected data are uniquely encoded according to preset rules for industrial data of different dimensions and levels. Step S10 of this example also includes:

[0064] S11: Create a data set based on the classification dimensions and classification levels of industrial data and import it into the coding library;

[0065] S12: Obtain dimensions and levels of the collected industrial data, and perform unique-hot encoding on the dimensions and levels of the collected industrial data to obtain a plurality of dimension codes and a level code;

[0066] S13: The dimension code and the level code are arranged according to a preset rule to form a label code of the collected industrial data.

[0067] Specifically, one-hot encoding is a data encoding technique commonly used in data analysis for machine learning to convert categorical data into data form. The basic idea is to map each categorical value to a unique integer and create a new binary feature. This solution uses one-hot encoding to encode the dimensions and levels of industrial data and arrange them according to the preset arrangement rules to form a binary data set, which is recorded as the label code.

[0068] S20: In the industrial data transmission stage, industrial data is encrypted using an asymmetric encryption algorithm, and the same algorithm is used to generate private keys for users who need access. For high-level industrial data, a multi-signature scheme is created, requiring authorization with a specified number of user signatures to access;

[0069] Further, such as Figure 3 As shown, the industrial data is encrypted using an asymmetric encryption algorithm, and the same algorithm is used to generate a private key for the user who needs access. Step S20 of this example also includes:

[0070] S21: Encrypt the industrial data using an asymmetric encryption algorithm to generate a public key and a private key parameter;

[0071] S22: Distribute the public key to each user and entity that needs access;

[0072] S23: Based on the private key parameters, a private key is generated for each user who needs access using the asymmetric encryption algorithm.

[0073] Specifically, an asymmetric encryption algorithm is an encryption technology that uses a pair of keys, including a public key and a private key, to encrypt and decrypt data. Some common asymmetric encryption algorithms include RSA (Rivest-Shamir-Adleman), DSA (Digital Signature Algorithm) and ECC (Elliptic Curve Cryptography). This solution uses an asymmetric encryption algorithm to encrypt industrial data, ensuring that all users and entities that need access have the same public key and different private keys. Only those with the correct public and private keys can access and obtain data.

[0074] Furthermore, for high-level industrial data, a multi-signature scheme is created, which requires authorization with a specified number of user signatures for access. The steps of this example also include: pre-setting level division rules to define access methods for industrial data at each level; the access method includes evolving the number of signature authorizations for encrypted industrial data from zero to many according to the level from low to high; signature authorization refers to the user who has the private key generated by the asymmetric encryption algorithm to authorize the industrial data that needs to be access verified using the private key.

[0075] Specifically, a multi-signature scheme is an encryption and security measure, and its main purpose is to ensure that when performing a certain operation or transaction, multiple authorized parties must sign together to complete it. This scheme creates a multi-signature scheme based on asymmetric encryption for high-level data, i.e. sensitive information. That is, on the basis of only one pair of public and private keys to access, high-level data also requires signature authorization of other private keys to access. The number of signature authorizations is proportional to the level, which further ensures the security of sensitive information.

[0076] S30: In the industrial data storage stage, the label code of the industrial data is identified, and the industrial data is classified and stored according to the identified content;

[0077] Further, such as Figure 4 As shown, the industrial data is classified and stored according to the identified content. Step S30 of this example also includes:

[0078] S31: Industrial data storage uses a combination of database and distributed file system;

[0079] S32: Identify the industrial data to be stored, determine whether it is structured data, use a database to store structured data and semi-structured data, and use a distributed file system to store unstructured data;

[0080] S33: Identify the tag code of the industrial data to be stored, and store the industrial data to be stored in a corresponding database or a node of a distributed file system.

[0081] Specifically, industrial data comes from many sources and is highly complex, including structured data, semi-structured data, and unstructured data. The storage method is usually a combination of databases and distributed file systems. Structured data is data stored in a clearly defined format, with clearly defined fields and values, as well as clear relationships and hierarchical structures. Semi-structured data does not have a clearly defined table structure, but contains tags or metadata about how the data is organized. Unstructured data refers to data that does not have a clearly defined format when it is stored or processed. This solution classifies and stores industrial data by identifying label codes, thereby improving data access efficiency.

[0082] S40: In the industrial data updating stage, the updated industrial data is updated with an update time code and an update timestamp is added;

[0083] Further, such as Figure 5 As shown, the updated industrial data is updated with an update time code and an update timestamp is added. Step S40 in this example also includes:

[0084] S41: using the time function of the programming language to obtain the Unix timestamp of the current industrial data update;

[0085] S42: retain the Unix timestamp of each update and arrange them in chronological order.

[0086] Specifically, the Unix timestamp is the number of seconds that have passed since 00:00:00 Greenwich Mean Time (GMT) on January 1, 1970, ignoring leap seconds. Based on the Unix timestamp, this solution time-codes each update of industrial data and arranges them in chronological order, providing additional data consistency, traceability, sorting, and filtering capabilities.

[0087] S50: During the industrial data destruction phase, a deactivation instruction is issued to delete the label code, core code, public key, private key and timestamp of the industrial data to be destroyed.

[0088] This solution uses unique-hot encoding for industrial data to generate multiple dimension codes and a level code to form a label code, thereby achieving classified management and storage of industrial data and improving the efficiency of data access. It also uses JSON encoding and core encoding for the content of all collected industrial data to ensure the uniformity of the format of industrial data from different data sources and reduce storage costs. Finally, by adding Unix timestamps based on the update time of industrial data, it also provides additional data consistency, traceability, sorting and filtering capabilities.

[0089] This solution also encrypts all industrial data using an asymmetric encryption algorithm, generates a public key and multiple private keys corresponding to the public key, and a pair of public keys and private keys can be used for decryption. Furthermore, based on the original asymmetric encryption algorithm, a multi-signature scheme is proposed. For higher-level industrial data, a specified number of private key signature authorizations are required on the basis of the original decryption before access can be made. In summary, this solution greatly improves data security and prevents the leakage of sensitive information.

[0090] Example 2

[0091] Based on the inventive concept of a coding identification method for the full life cycle circulation of industrial data in the aforementioned embodiment, as Figure 6 As shown, the present application provides a coding identification system for the full life cycle circulation of industrial data. The system and method embodiments in the present application are based on the same inventive concept. The system includes a data interception module, a data classification module, a data encoding module, a data encryption module, a data positioning module, a data destruction module and a data identification module.

[0092] The data interception module is used to intercept industrial data that is in the process of life cycle circulation in real time. Specifically, the data interception module contains database proxy tools such as MySQL Proxy, pgBouncer, etc., which can monitor and modify the data in the database communication process. The data interception module intercepts and modifies the data in the industrial data collection stage, transmission stage, storage stage, update stage and destruction stage respectively. The execution process of the data interception module is: intercept the industrial data in the industrial data collection stage and send it to the data classification module; intercept the industrial data in the industrial data update stage and send it to the data encoding module; receive the data packet of the data encryption module and the query path of the data positioning module; modify or replace the industrial data in the industrial data transmission and storage stage based on the data packet and query path; intercept the data packet of the industrial data in the industrial data destruction stage and send it to the data destruction module; receive the return information of the data destruction module; modify or replace the data in the industrial data destruction stage based on the return information.

[0093] The data classification module is electrically connected to the data interception module. The data classification module is used to divide the dimensions and classify the industrial data. The data classification module includes: training with data of known dimensions and levels to obtain a trained decision tree; classifying the collected industrial data according to the trained decision tree. Specifically, a data set containing data tags, in which each sample includes a set of features (or attributes) and related category labels, is used to train the decision tree, and the trained decision tree is retained and stored. The execution process of the data classification module is: obtaining the industrial data of the industrial data collection stage intercepted by the data interception module; inputting the obtained industrial data into the decision tree, outputting the classification dimension and level of the data; sending the classification and level of the data to the data encoding module.

[0094] The data encoding module is electrically connected to the data interception module and the data classification module. The data encoding module is used to encode the industrial data using different algorithms under different environments and conditions. The data encoding module includes: a label encoding unit, a core encoding unit and a time encoding unit. The label encoding unit contains a unique hot encoding algorithm, which is used to obtain the classification result of the data classification module, encode the classification result, and generate a label code; the core encoding unit contains a JSON encoding algorithm, which is used to obtain the specific data content of the collected industrial data, encode the specific data content, and generate the core encoding content; the time encoding unit contains a time function, which is used to obtain the update time of the industrial data to be updated and generate a Unix timestamp. The execution process of the data encoding module is as follows: the label encoding unit obtains the classification dimension and level of the data classification module, encodes it using one-hot encoding, and generates a label code; the core encoding unit obtains the industrial data in the industrial data collection phase intercepted by the data interception module, uses the JSON encoding algorithm to encode the specific content, and generates a core content code; the time encoding unit obtains the industrial data in the industrial data update phase intercepted by the data interception module, extracts the update time, encodes it using the time function, and generates a Unix timestamp; the label code, core code, and Unix timestamp are packaged and sent to the data encryption module and the data identification module.

[0095] Data identification module, the data identification module is electrically connected to the data encoding module, and the data identification module is used to read the label code, core code and timestamp. Specifically, the data identification module contains a variety of code reading tools, which can read data codes in a variety of coding formats. The execution process of the data identification module is: obtain the label code of the data encoding module; use the code reading tool of the corresponding coding format to read the label code; send the reading result to the data encryption module and the data positioning module.

[0096] Data encryption module, the data encryption module is electrically connected to the data encoding module, the data identification module, and the data interception module. The data encryption module is used to encrypt industrial data of different levels. Specifically, the data encryption scheme contains an asymmetric encryption algorithm, and a preset multiple scheme script is used to encrypt industrial data of different levels. The execution process of the data encryption module is: obtain the label code, core code and Unix timestamp of the data encoding module; encrypt the three codes using an asymmetric encryption algorithm to generate a public key and several private keys; distribute a pair of public keys and private keys to each user entity that needs access; obtain the recognition result of the label code of the data identification module; based on the data level of the recognition result, use the preset multiple scheme script to set the permission authentication; return the encrypted data packet to the data interception module.

[0097] The data location module is electrically connected to the data interception module and the data identification module. The data location module is used to locate data in the database and the distributed file system. Specifically, the data location module contains an SQL query tool, which establishes a connection with the database and the distributed file system, and locates the data in the database and the distributed file system by writing SQL queries. The execution process of the data location module is: obtain the recognition result of the label code of the data identification module; based on the recognition result, write an SQL query; use the SQL query tool to locate the data with the same label code in the database and the distributed file system; return the query path to the data interception module.

[0098] The data destruction module is electrically connected to the data interception module. The data destruction module is used to generate an inactivation instruction to delete the label code, core code, public key, private key and timestamp of the industrial data to be destroyed. The execution process of the data destruction module is as follows: obtain the data packet of the industrial data in the industrial data destruction stage intercepted by the data interception module, which contains the label code, core code, public key, private key and timestamp of the data; based on the data packet, write a suitable SQL delete statement to generate an inactivation instruction; execute the inactivation instruction to delete the data packet; return null to the data interception module.

[0099] This solution provides a coding and identification system for the full life cycle circulation of industrial data, including a data interception module, a data classification module, a data coding module, a data encryption module, a data positioning module, a data destruction module and a data identification module. Each module has a specific execution process and execution tools, which are used to implement the coding and identification method for the full life cycle circulation of industrial data as described above, further solving the problems of inconsistent data formats, insufficient storage device capacity, and sensitive information leakage during the full life cycle circulation of industrial data due to the large amount and high complexity of industrial data.

[0100] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A coding identification method for the full life cycle circulation of industrial data, characterized in that: include: In the industrial data collection stage, the industrial data is divided into dimensions and levels. The collected data dimensions and levels are uniquely encoded according to preset rules to form label codes. The specific content of the collected data is JSON-encoded to generate core codes. In the industrial data transmission stage, industrial data is encrypted using an asymmetric encryption algorithm, and the same algorithm is used to generate private keys for users who need access. For high-level industrial data, a multi-signature scheme is created, requiring authorization with a specified number of user signatures to access; In the stage of industrial data storage, the label codes of industrial data are identified, and the industrial data are classified and stored according to the identified content; During the industrial data update phase, the updated industrial data is updated with an update time code and an update timestamp is added; During the industrial data destruction phase, a deactivation instruction is issued to delete the label code, core code, public key, private key and timestamp of the industrial data to be destroyed; The industrial data is divided into dimensions and grades, including: the industrial data classification dimension is based on the five predetermined dimensions of R&D data domain, production data domain, operation and maintenance data domain, management data domain and external data domain, and is further divided into several dimensions according to the characteristics of the industrial data; the industrial data classification level is graded from small to large according to the degree of impact on industrial production and economic benefits after being tampered, destroyed, leaked or illegally used; The step of performing unique-hot encoding on the dimensions and levels of the collected industrial data of different dimensions and levels according to preset rules includes: Create a data set based on the classification dimensions and classification levels of industrial data and import it into the coding library; Obtain the dimensions and levels of the collected industrial data, perform unique-hot encoding on the dimensions and levels of the collected industrial data, and obtain several dimension codes and a level code; The dimension code and the level code are arranged according to a preset rule to form a label code for the collected industrial data; The method of encrypting industrial data using an asymmetric encryption algorithm and generating a private key for a user who needs access using the same algorithm specifically includes: Encrypt industrial data using an asymmetric encryption algorithm to generate a public key and private key parameters; Distribute the public key to every user and entity that needs access; Based on the private key parameters, a private key is generated for each user who needs access using the asymmetric encryption algorithm; For high-level industrial data, a multi-signature method is created, which requires authorization of a specified number of user signatures to access, including: Preset level division rules to define the access method for industrial data at each level; The access method includes evolving the number of signature authorizations for the encrypted industrial data from none to many according to the level from low to high; The signature authorization refers to a user having a private key generated by the asymmetric encryption algorithm using the private key to authorize industrial data that requires access verification.

2. A coding identification method for the full life cycle circulation of industrial data according to claim 1, characterized in that: The classifying and storing the industrial data according to the identified content also includes: The industrial data storage adopts a combination of database and distributed file system; Identify the industrial data to be stored and determine whether it is structured data. Use a database to store structured and semi-structured data, and use a distributed file system to store unstructured data. Identify the tag code of the industrial data to be stored, and store the industrial data in a corresponding database or a node of a distributed file system.

3. A coding identification method for the full life cycle circulation of industrial data according to claim 2, characterized in that: The updating time coding of the updated industrial data and the adding of the updating timestamp include: Use the time function of the programming language to obtain the Unix timestamp of the current industrial data update; Keep the Unix timestamp of each update and arrange them in chronological order.

4. A coding identification system for the full life cycle circulation of industrial data, used to implement the coding identification method for the full life cycle circulation of industrial data as described in any one of claims 1 to 3, characterized in that: include: A data interception module, which is used to intercept industrial data that is undergoing life cycle circulation in real time; A data classification module, the data classification module is electrically connected to the data interception module, and the data classification module is used to divide the industrial data into dimensions and grades; A data encoding module, the data encoding module is electrically connected to the data interception module and the data classification module, and the data encoding module is used to encode the industrial data using different algorithms under different environments and conditions; A data identification module, the data identification module is electrically connected to the data encoding module, and the data identification module is used to read the label code, the core code and the timestamp; A data encryption module, the data encryption module is electrically connected to the data encoding module, the data identification module, and the data interception module, and the data encryption module is used to encrypt industrial data of different levels; A data locating module, the data locating module is electrically connected to the data interception module and the data identification module, and the data locating module is used to locate the database and the distributed file system; A data destruction module is electrically connected to the data interception module, and is used to generate a deactivation instruction to delete the label code, core code, public key, private key and timestamp of the industrial data to be destroyed.

5. A coding identification system for the full life cycle circulation of industrial data according to claim 4, characterized in that: The data classification module comprises: Train with data of known dimensions and levels to obtain a trained decision tree; The collected industrial data is classified according to the trained decision tree.

6. A coding identification system for the full life cycle circulation of industrial data according to claim 5, characterized in that: The data encoding module comprises: A label encoding unit, wherein the label encoding unit contains a one-hot encoding algorithm, which is used to obtain the classification result of the data classification module, encode the classification result, and generate a label code; A core coding unit, wherein the core coding unit contains a JSON coding algorithm for obtaining specific data content of the collected industrial data, encoding the specific data content, and generating core coding content; A time coding unit includes a time function for obtaining the update time of the industrial data to be updated and generating a Unix timestamp.

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