Industrial equipment management method, equipment and storage medium based on identification resolution

Abstract

The present application discloses an industrial equipment management method, equipment, and storage medium based on identity resolution. The method includes: encoding industrial equipment based on preset encoding rules to determine the equipment identification code corresponding to each industrial equipment; determining a number of industrial equipment corresponding to an identity resolution terminal and a data acquisition module corresponding to each industrial equipment, and initializing the identity resolution terminal; receiving industrial data sent by the data acquisition module based on the identity resolution terminal, and preprocessing the industrial data to determine the standard data corresponding to the industrial data; inputting the standard data into a preset data model template to determine the corresponding data analysis model for the industrial equipment; inputting the data analysis model into a preset equipment management solution generation algorithm, analyzing the industrial equipment, and determining the equipment management solution for the corresponding industrial equipment. The present application realizes the management of industrial equipment by utilizing the industrial data corresponding to the industrial equipment through the above method.

Description

Technical Field

[0001] The present application relates to the field of industrial Internet technology, and in particular to an industrial equipment management method, equipment and storage medium based on identity resolution. Background Art

[0002] With the development of industrial informatization, industrial equipment management is no longer based on simple empirical judgment. Instead, it hopes to make better decisions based on data. Industrial equipment management solutions include a series of solutions for equipment use, maintenance, and scrapping. By analyzing and making decisions based on the corresponding industrial data of industrial equipment, the value of industrial equipment is maximized, thereby achieving the lowest cost and the highest work efficiency.

[0003] Therefore, how to use the industrial data corresponding to industrial equipment to make decisions on management plans for industrial equipment has become a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The embodiments of the present application provide an industrial equipment management method, equipment, and storage medium based on identity resolution to solve the following technical problem: how to manage industrial equipment by utilizing industrial data corresponding to industrial equipment.

[0005] In the first aspect, an embodiment of the present application provides an industrial equipment management method based on identity resolution, characterized in that the method includes: encoding industrial equipment based on preset coding rules to determine the equipment identification code corresponding to each industrial equipment; determining a number of industrial equipment corresponding to the identity resolution terminal and the data acquisition module corresponding to each industrial equipment, and initializing the identity resolution terminal; after the data acquisition module obtains the industrial data, receiving the industrial data sent by the data acquisition module based on the identity resolution terminal, and preprocessing the industrial data to determine the standard data corresponding to the industrial data; wherein the industrial data includes the industrial equipment identification data acquisition time and multiple parameter values; inputting the standard data into a preset data model template to determine the corresponding data analysis model of the industrial equipment; wherein the data model template is used to describe the data type required to determine the equipment management plan; inputting the data analysis model into a preset equipment management plan generation algorithm to analyze the industrial equipment to determine the equipment management plan corresponding to the industrial equipment.

[0006] An embodiment of the present application provides an industrial equipment management method based on identity resolution. An identity resolution terminal collects and preprocesses industrial data obtained by a data acquisition module corresponding to the industrial equipment data. The data acquisition module then adds a standardized identification code to the industrial data and converts it into standard data of the corresponding type. A data analysis model is then determined based on the standard data to analyze and obtain different management solutions. Different industrial equipment management solutions can then be determined based on the corresponding data analysis model to achieve effective management of the industrial equipment.

[0007] In one implementation of the present application, the identification resolution terminal is initialized, specifically including: determining the communication protocol corresponding to each data acquisition module, and establishing a communication link between the identification resolution terminal and each data acquisition module based on the communication protocol corresponding to each data acquisition module; determining the standard data conversion rules corresponding to each data acquisition module based on the data type and data format of each parameter value in the industrial data; determining the data preprocessing relationship table corresponding to each industrial equipment based on the device identification code, the communication protocol corresponding to each data acquisition module and the standard data conversion rules corresponding to each data acquisition module, and pre-placing the data preprocessing relationship table in the identification resolution terminal.

[0008] In one implementation of the present application, a communication link is established between the identification resolution terminal and each data acquisition module based on the communication protocol corresponding to each data acquisition module, specifically including: pre-setting a wireless network receiver in the identification resolution terminal, and pre-setting several different types of communication interfaces on the identification resolution terminal; adding the transmission address of the corresponding identification resolution terminal in each data acquisition module, and based on the corresponding communication protocol, establishing a communication link between the identification resolution terminal and each data acquisition module through the corresponding type of communication interface or through the wireless network receiver.

[0009] In one implementation of the present application, before preprocessing the industrial data to determine the standard data corresponding to the industrial data, the method also includes: determining whether multiple parameter values ​​in the industrial data are greater than the corresponding first preset threshold; when it is determined that one or more parameter values ​​in the industrial data are greater than the corresponding first preset threshold, obtaining historical industrial data of the corresponding data acquisition module within a preset time interval; based on the K-means clustering algorithm, clustering analysis is performed on the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold and the parameter values ​​of the corresponding type in the historical industrial data to determine the clustering value of the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold; wherein the clustering value is used to describe the clustering effect of the industrial data; when the clustering value is greater than the second preset threshold, an adjustment coefficient for the parameter value in the industrial data that is greater than the corresponding first preset threshold is generated based on the clustering value, and the parameter value in the industrial data that is greater than the corresponding first preset threshold is adjusted based on the adjustment coefficient.

[0010] In one implementation of the present application, industrial data is preprocessed to determine the standard data corresponding to the industrial data, specifically including: replacing the industrial equipment identifier contained in the industrial data with the equipment identification code; and converting the industrial data based on the standard data conversion rules corresponding to the industrial data to determine the standard data corresponding to the industrial data.

[0011] In one implementation of the present application, before inputting the standard data into a preset data model template, the method also includes: determining several types of parameter values ​​and corresponding correlation coefficients in the standard data that are relevant to the equipment management plan through a preset regression algorithm; generating a relevant data table based on the data types of the several types of parameter values, and assigning weights to the data types in the relevant data table based on the corresponding correlation coefficients to obtain a data model template.

[0012] In one implementation of the present application, before inputting the data analysis model into a preset equipment management solution generation algorithm, the method also includes: determining several historical data analysis models based on historical industrial data; wherein the historical data analysis models are obtained by processing the corresponding industrial data obtained at the same historical time; based on the several historical data analysis models, training the preset equipment management solution generation network until a converged equipment management solution generation algorithm is obtained.

[0013] In one implementation of the present application, after determining the equipment management plan for the corresponding industrial equipment, the method also includes: encoding the equipment management plan based on the equipment identification code corresponding to the industrial equipment, and storing it in a node database; and sending the equipment management plan to a preset visualization device so that the staff can manage the industrial equipment based on the equipment management plan.

[0014] In a second aspect, an embodiment of the present application also provides an industrial equipment management device based on identity resolution, characterized in that the device includes: a processor; and a memory on which executable code is stored, and when the executable code is executed, the processor executes a method as claimed in any one of claims 1-8.

[0015] In a third aspect, an embodiment of the present application also provides a non-volatile computer storage medium for industrial equipment management based on identity resolution, which stores computer executable instructions, and is characterized in that the computer executable instructions are set to: encode industrial equipment based on preset coding rules to determine the equipment identification code corresponding to each industrial equipment; determine a number of industrial equipment corresponding to the identity resolution terminal and the data acquisition module corresponding to each industrial equipment, and initialize the identity resolution terminal; after the data acquisition module obtains the industrial data, receive the industrial data sent by the data acquisition module based on the identity resolution terminal, and pre-process the industrial data to determine the standard data corresponding to the industrial data; wherein the industrial data includes the industrial equipment identification data acquisition time and multiple parameter values; input the standard data into a preset data model template to determine the corresponding data analysis model of the industrial equipment; wherein the data model template is used to describe the data type required to determine the equipment management plan; input the data analysis model into a preset equipment management plan generation algorithm to analyze the industrial equipment to determine the equipment management plan corresponding to the industrial equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 A flowchart of an industrial equipment management method based on identity resolution provided in an embodiment of the present application;

[0018] Figure 2 A schematic diagram of the internal structure of an industrial equipment management device based on identity resolution provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0020] The embodiments of the present application provide an industrial equipment management method, equipment, and storage medium based on identity resolution to solve the following technical problem: how to manage industrial equipment by utilizing industrial data corresponding to industrial equipment.

[0021] The technical solutions proposed in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0022] Figure 1 This is a flow chart of an industrial equipment management method based on identity resolution provided in an embodiment of the present application. Figure 1 As shown, an industrial equipment management method based on identity resolution provided by an embodiment of the present application specifically includes the following steps:

[0023] Step 101: Encode industrial equipment based on a preset encoding rule to determine a device identification code corresponding to each industrial equipment.

[0024] In one embodiment of the present application, since there are many industrial systems corresponding to the industrial Internet, different industrial systems have different coding rules for industrial equipment. Therefore, in order to achieve standard unification of industrial equipment, the present application first encodes the industrial equipment based on preset coding rules to determine the device identification code corresponding to each industrial equipment.

[0025] Specifically, the national secondary node determines the device identification code prefix corresponding to different enterprises or systems. Based on the internal division relationship and device number of each industrial device, each enterprise or system determines the device identification code suffix. Based on the device identification code prefix and suffix, the device identification code corresponding to each industrial device is determined.

[0026] Step 102: Determine a number of industrial devices corresponding to the identification resolution terminal and a data acquisition module corresponding to each industrial device, and initialize the identification resolution terminal.

[0027] In one embodiment of the present application, an identity resolution terminal is used to upload industrial data to a node database of the Industrial Internet; wherein the industrial data is obtained by a data acquisition module corresponding to an industrial device. In addition, the identity resolution terminal of the present application can simultaneously receive industrial data uploaded by multiple data acquisition modules. Therefore, before the identity resolution terminal receives the industrial data, it is necessary to determine the multiple industrial devices corresponding to the identity resolution terminal and initialize the identity resolution terminal.

[0028] Specifically, first determine the several industrial devices corresponding to the identification resolution terminal. Among them, the several industrial devices corresponding to each identification resolution terminal can be in the same area or the same system node. Since the data acquisition modules corresponding to each industrial device are set by the industrial device itself, after determining the several industrial devices corresponding to the identification resolution terminal, the data acquisition modules corresponding to each industrial device can be determined. After determining the data acquisition modules corresponding to the identification resolution terminal, determine the communication protocols corresponding to each data acquisition module, and establish a communication link between the identification resolution terminal and each data acquisition module based on the communication protocols corresponding to each data acquisition module; based on the data type and data format of the industrial data corresponding to each data acquisition module, determine the standard data conversion rules corresponding to each data acquisition module; based on the module identification code, the communication protocols corresponding to each data acquisition module and the standard data conversion rules corresponding to each data acquisition module, determine the data preprocessing relationship table corresponding to each industrial device, and pre-place the data preprocessing relationship table in the identification resolution terminal.

[0029] It should be noted that establishing a communication link first requires pre-installing a wireless network receiver in the identity resolution terminal and pre-installing several different types of communication interfaces on the identity resolution terminal. Each data collection module then adds the transmission address of the corresponding identity resolution terminal and establishes a communication link between the identity resolution terminal and each data collection module using the corresponding communication interface or wireless network receiver based on the corresponding communication protocol.

[0030] Step 103: After the data acquisition module obtains the industrial data, the terminal receives the industrial data sent by the data acquisition module based on the identifier resolution, and pre-processes the industrial data to determine the standard data corresponding to the industrial data.

[0031] In one embodiment of the present application, after initializing the identity resolution terminal, the data collection module can send the collected industrial data to the identity resolution terminal. After receiving the industrial data sent by the data collection module, the identity resolution terminal first determines whether multiple parameter values ​​in the industrial data contain abnormal data, and if so, corrects the abnormal data.

[0032] Specifically, determine whether multiple parameter values ​​in the industrial data are greater than the corresponding first preset threshold; when it is determined that one or more parameter values ​​in the industrial data are greater than the corresponding first preset threshold, obtain historical industrial data of the corresponding data acquisition module within a preset time interval; based on the K-means clustering algorithm, perform cluster analysis on the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold and the parameter values ​​of the corresponding type in the historical industrial data to determine the clustering value of the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold; wherein the clustering value is used to describe the clustering effect of the industrial data; when the clustering value is greater than the second preset threshold, generate an adjustment coefficient for the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold based on the clustering value, and adjust the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold based on the adjustment coefficient.

[0033] In one embodiment of the present application, after the correct industrial data is determined, the industrial data is pre-processed to determine standard data corresponding to the industrial data.

[0034] Specifically, the industrial equipment identification contained in the industrial data is replaced with the equipment identification code; and based on the standard data conversion rules corresponding to the industrial data, the industrial data is converted to determine the standard data corresponding to the industrial data.

[0035] Step 104: Input the standard data into a preset data model template to determine a corresponding data analysis model for the industrial equipment.

[0036] In one embodiment of the present application, after determining the standard data corresponding to the industrial data, the parameter values ​​of the corresponding types in the standard data are input into the corresponding data model template to determine the corresponding data analysis model of the industrial equipment. It should be noted that the data model template is determined based on the preset equipment management plan. It is understandable that the data model template is not limited to one type, and several data model templates can be determined based on the equipment management plan, for example: a data model template corresponding to the equipment usage plan, a data model template corresponding to the equipment maintenance plan, and a data model template corresponding to the equipment scrapping plan. Different data model templates correspond to different types of parameter values.

[0037] In one embodiment of the present application, the data model template is generated by first determining several types of parameter values ​​and corresponding correlation coefficients that are relevant to the equipment management plan in the standard data through a preset regression algorithm. It should be noted that the specific regression algorithm used is not limited in this application, and different regression algorithms can be used to perform correlation judgment according to different equipment management plans. After determining several types of parameter values ​​and corresponding correlation coefficients that are relevant to the equipment management plan, a relevant data table is generated based on the data types of the several types of parameter values, and weights are assigned to the data types in the relevant data table based on the corresponding correlation coefficients to obtain a data model template.

[0038] Step 105: Input the data analysis model into a preset equipment management solution generation algorithm to analyze the industrial equipment to determine an equipment management solution for the corresponding industrial equipment.

[0039] In one embodiment of the present application, after the data analysis model is determined, the data analysis model is analyzed using a preset equipment management solution generation algorithm to determine a management solution for the corresponding industrial equipment.

[0040] In one embodiment of the present application, an equipment management solution generation algorithm is obtained through the following process: based on historical industrial data, several historical data analysis models are determined; wherein the historical data analysis models are obtained by processing the corresponding industrial data obtained at the same historical time; based on several historical data analysis models, a preset equipment management solution generation network is trained until a converged equipment management solution generation algorithm is obtained.

[0041] In one embodiment of the present application, after determining the equipment management plan for the corresponding industrial equipment, the equipment management plan is encoded based on the equipment identification code corresponding to the industrial equipment and stored in a node database; and the equipment management plan is sent to a preset visualization device so that the staff can manage the industrial equipment based on the equipment management plan.

[0042] Based on the same inventive concept, the embodiment of the present application also provides an industrial equipment management device based on identity resolution, the internal structure of which is as follows: Figure 2 shown.

[0043] Figure 2 This is a schematic diagram of the internal structure of an industrial equipment management device based on identity resolution provided in an embodiment of the present application. Figure 2 As shown, the device includes: a processor 201; a memory 202, on which executable instructions are stored. When the executable instructions are executed, the processor 201 executes the above-mentioned industrial equipment management method based on identity resolution.

[0044] In one embodiment of the present application, the processor 201 is used to encode industrial equipment based on preset coding rules to determine the equipment identification code corresponding to each industrial equipment; determine a number of industrial equipment corresponding to the identification resolution terminal and the data acquisition module corresponding to each industrial equipment, and initialize the identification resolution terminal; after the data acquisition module obtains the industrial data, the industrial data sent by the data acquisition module is received based on the identification resolution terminal, and the industrial data is pre-processed to determine the standard data corresponding to the industrial data; wherein the industrial data includes the industrial equipment identification data acquisition time and multiple parameter values; the standard data is input into a preset data model template to determine the corresponding data analysis model of the industrial equipment; wherein the data model template is used to describe the data type required to determine the equipment management plan; the data analysis model is input into a preset equipment management plan generation algorithm to analyze the industrial equipment to determine the equipment management plan corresponding to the industrial equipment.

[0045] Some embodiments of the present application provide corresponding Figure 1 A non-volatile computer storage medium for industrial equipment management based on identity resolution stores computer executable instructions, wherein the computer executable instructions are configured as follows:

[0046] Encode industrial equipment based on preset encoding rules to determine the equipment identification code corresponding to each industrial equipment;

[0047] Determine the number of industrial devices corresponding to the identification resolution terminal and the data acquisition modules corresponding to each industrial device, and initialize the identification resolution terminal;

[0048] After the data acquisition module obtains the industrial data, the identification resolution terminal receives the industrial data sent by the data acquisition module and pre-processes the industrial data to determine the standard data corresponding to the industrial data; wherein the industrial data includes the acquisition time of the industrial equipment identification data and multiple parameter values;

[0049] Input the standard data into a preset data model template to determine the corresponding data analysis model for the industrial equipment; wherein the data model template is used to describe the data type required to determine the equipment management solution;

[0050] The data analysis model is input into the preset equipment management solution generation algorithm to analyze the industrial equipment to determine the equipment management solution for the corresponding industrial equipment.

[0051] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from the other embodiments. In particular, the IoT device and media embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0052] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0053] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0054] 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 steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0055] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing 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.

[0057] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0058] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0059] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0060] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0061] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. An industrial equipment management method based on identity resolution, characterized in that: The method comprises: Encode industrial equipment based on preset encoding rules to determine the equipment identification code corresponding to each industrial equipment; Determine a number of industrial devices corresponding to the identification resolution terminal and a data acquisition module corresponding to each industrial device, and initialize the identification resolution terminal; After the data acquisition module obtains the industrial data, the identification resolution terminal receives the industrial data sent by the data acquisition module and pre-processes the industrial data to determine the standard data corresponding to the industrial data; wherein the industrial data includes the acquisition time of the industrial equipment identification data and multiple parameter values; Inputting the standard data into a preset data model template to determine a corresponding data analysis model for the industrial equipment; wherein the data model template is used to describe the data type required to determine the equipment management solution; Inputting the data analysis model into a preset equipment management solution generation algorithm to analyze the industrial equipment to determine an equipment management solution corresponding to the industrial equipment; Before preprocessing the industrial data to determine standard data corresponding to the industrial data, the method further includes: determining whether a plurality of parameter values ​​in the industrial data are greater than corresponding first preset thresholds; When it is determined that one or more parameter values ​​in the industrial data are greater than a corresponding first preset threshold, acquiring historical industrial data of the corresponding data acquisition module within a preset time interval; Based on the K-means clustering algorithm, cluster analysis is performed on parameter values ​​in the industrial data that are greater than a corresponding first preset threshold and parameter values ​​of corresponding types in the historical industrial data to determine a cluster value for the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold; wherein the cluster value is used to describe the clustering effect of the industrial data; When the cluster value is greater than the second preset threshold, an adjustment coefficient is generated for the parameter value in the industrial data that is greater than the corresponding first preset threshold based on the cluster value, and the parameter value in the industrial data that is greater than the corresponding first preset threshold is adjusted based on the adjustment coefficient.

2. The industrial equipment management method based on identity resolution according to claim 1, characterized in that: Initializing the identity resolution terminal specifically includes: Determining a communication protocol corresponding to each data acquisition module, and establishing a communication link between the identifier resolution terminal and each data acquisition module based on the communication protocol corresponding to each data acquisition module; Determine the standard data conversion rules corresponding to each data acquisition module based on the data type and data format of each parameter value in the industrial data; Based on the device identification code, the communication protocol corresponding to each data acquisition module and the standard data conversion rules corresponding to each data acquisition module, the data preprocessing relationship table corresponding to each industrial device is determined, and the data preprocessing relationship table is pre-placed in the identification resolution terminal.

3. The industrial equipment management method based on identity resolution according to claim 2, characterized in that: Establishing a communication link between the identifier resolution terminal and each data acquisition module based on the communication protocol corresponding to each data acquisition module specifically includes: Presetting a wireless network receiver in the identity resolution terminal, and presetting a plurality of different types of communication interfaces on the identity resolution terminal; The transmission address of the corresponding identification resolution terminal is added to each data acquisition module, and based on the corresponding communication protocol, a communication link between the identification resolution terminal and each data acquisition module is established through the corresponding type of communication interface or through the wireless network receiver.

4. The industrial equipment management method based on identity resolution according to claim 2 is characterized in that: Preprocessing the industrial data to determine standard data corresponding to the industrial data specifically includes: replacing the industrial equipment identification contained in the industrial data with the equipment identification code; The industrial data is converted based on standard data conversion rules corresponding to the industrial data to determine standard data corresponding to the industrial data.

5. The industrial equipment management method based on identity resolution according to claim 2 is characterized in that: Before inputting the standard data into the preset data model template, the method further includes: Determine, by a preset regression algorithm, several types of parameter values ​​and corresponding correlation coefficients that are relevant to the equipment management solution in the standard data; Based on the data types of the several types of parameter values, a related data table is generated, and based on the corresponding correlation coefficients, weights are assigned to the data types in the related data table to obtain a data model template.

6. The industrial equipment management method based on identity resolution according to claim 5, characterized in that: Before inputting the data analysis model into a preset device management solution generation algorithm, the method further includes: Based on the historical industrial data, several historical data analysis models are determined; wherein the historical data analysis models are obtained by processing the corresponding industrial data acquired at the same historical time; Based on the several historical data analysis models, a preset equipment management solution generation network is trained until a converged equipment management solution generation algorithm is obtained.

7. The industrial equipment management method based on identity resolution according to claim 1 is characterized in that: After determining the equipment management solution corresponding to the industrial equipment, the method further includes: Encoding the device management solution based on the device identification code corresponding to the industrial device and storing the solution in a node database; and The equipment management plan is sent to a preset visualization device so that a staff member can manage the industrial equipment based on the equipment management plan.

8. An industrial equipment management device based on identity resolution, characterized in that: The device comprises: processor; and a memory having executable codes stored thereon, which, when the executable codes are executed, enable the processor to perform a method according to any one of claims 1 to 7.

9. A non-volatile computer storage medium for industrial equipment management based on identity resolution, storing computer-executable instructions, characterized in that: The computer executable instructions are configured to: Encode industrial equipment based on preset encoding rules to determine the equipment identification code corresponding to each industrial equipment; Determine a number of industrial devices corresponding to the identification resolution terminal and a data acquisition module corresponding to each industrial device, and initialize the identification resolution terminal; After the data acquisition module obtains the industrial data, the identification resolution terminal receives the industrial data sent by the data acquisition module and pre-processes the industrial data to determine the standard data corresponding to the industrial data; wherein the industrial data includes the industrial equipment identification, the data acquisition module identification, the data acquisition time and the data value; Inputting the standard data into a preset data model template to determine a corresponding data analysis model for the industrial equipment; wherein the data model template is used to describe the data type required to determine the equipment management solution; Inputting the data analysis model into a preset equipment management solution generation algorithm to analyze the industrial equipment to determine an equipment management solution corresponding to the industrial equipment; Before pre-processing the industrial data to determine the standard data corresponding to the industrial data, the method further includes: determining whether a plurality of parameter values ​​in the industrial data are greater than corresponding first preset thresholds; When it is determined that one or more parameter values ​​in the industrial data are greater than a corresponding first preset threshold, acquiring historical industrial data of the corresponding data acquisition module within a preset time interval; Based on the K-means clustering algorithm, cluster analysis is performed on parameter values ​​in the industrial data that are greater than a corresponding first preset threshold and parameter values ​​of corresponding types in the historical industrial data to determine a cluster value for the parameter values ​​in the industrial data that are greater than the corresponding first preset threshold; wherein the cluster value is used to describe the clustering effect of the industrial data; When the cluster value is greater than the second preset threshold, an adjustment coefficient is generated for the parameter value in the industrial data that is greater than the corresponding first preset threshold based on the cluster value, and the parameter value in the industrial data that is greater than the corresponding first preset threshold is adjusted based on the adjustment coefficient.

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