Industrial data processing method and device, equipment and medium

Abstract

The embodiment of the invention provides an industrial data processing method and device, equipment and a medium. The method comprises the following steps: acquiring initial data of industrial equipment; determining a data algorithm corresponding to the initial data from an adaptive matching algorithm center, and performing data edge calculation on the initial data by adopting the data algorithm to obtain a data calculation result; determining a dynamic instruction matched with the data calculation result; and based on the dynamic instruction, controlling the industrial equipment to execute a corresponding instruction action. According to the method, the initial data is simply and conveniently calculated, the data processing speed and accuracy are improved, and flexible and efficient edge data calculation and data analysis are realized.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment and medium for processing industrial data. Background Art

[0002] With the advent of the Industrial 4.0 era, the deep integration of information technology (IT) and operational technology (OT) has not only broken down data silos, but also improved production flexibility and efficiency, and enhanced corporate competitiveness.

[0003] Currently, in industrial automation, smart manufacturing, the Internet of Things, and other scenarios that require data processing and analysis at the edge of the network, a large amount of data needs to be quickly processed at the edge of the OT network to meet real-time and security requirements.

[0004] However, existing edge computing technologies still have problems with low efficiency and reliance on the cloud when processing initial data collected by industrial equipment. Summary of the invention

[0005] The embodiments of the present application provide methods, devices, equipment and media for processing industrial data, which improve the speed and accuracy of data processing and realize flexible and efficient edge data calculation and data analysis.

[0006] In a first aspect, an embodiment of the present application provides a method for processing industrial data, including:

[0007] Obtain initial data of industrial equipment;

[0008] Determine a data algorithm corresponding to the initial data from the adaptive matching algorithm center, and use the data algorithm to perform data edge calculation on the initial data to obtain a data calculation result;

[0009] Determining a dynamic instruction that matches the data calculation result;

[0010] Based on the dynamic instruction, the industrial device is controlled to execute a corresponding instruction action.

[0011] In a possible implementation, the adaptive matching algorithm center includes a plurality of candidate algorithms and a plurality of first association relationships between the candidate algorithms and data types, and determining the data algorithm corresponding to the initial data from the adaptive matching algorithm center includes:

[0012] Determine the data type of the initial data;

[0013] Based on the first association relationship, a candidate algorithm having a first association relationship with the data type is determined from the adaptive matching algorithm center, and the candidate algorithm is used as the data algorithm corresponding to the initial data.

[0014] In a possible implementation manner, after performing data edge calculation on the initial data to obtain the data calculation result, the method further includes:

[0015] Determine or generate a user relationship mapping table according to the data type and the tag attribute corresponding to the initial data, wherein the tag attribute is used to indicate the data source and output range of the initial data, and the user relationship mapping table is used to indicate the channel starting point and channel end point of at least one virtualized channel;

[0016] Based on the at least one virtualization channel and the user relationship mapping table, multi-channel distribution processing is performed on the initial data and the data calculation result.

[0017] In a possible implementation, the determining the dynamic instruction that the data calculation result matches includes:

[0018] Loading instruction dynamic information into an instruction hash chain table, wherein the instruction dynamic information includes a plurality of dynamic instructions, and the hash chain table is used to indicate a third association relationship between an execution action and the dynamic instructions;

[0019] Determine an action to be performed corresponding to the data calculation result;

[0020] Based on the instruction hash list, dynamic instructions are matched for the actions to be executed.

[0021] In a possible implementation, the determining the dynamic instruction that the data calculation result matches includes:

[0022] Determine corresponding event attributes according to the initial data;

[0023] Based on the event attributes, determining whether the data calculation result satisfies a preset rule;

[0024] When the data calculation result satisfies the preset rule, the corresponding dynamic instruction is determined according to the pre-stored instruction dynamic information and event attributes.

[0025] In a possible implementation manner, before performing data edge calculation on the initial data to obtain the data calculation result, the method further includes:

[0026] Performing a first encryption process on the initial data;

[0027] The performing edge computing on the initial data to obtain a data computing result includes:

[0028] In the case where it is determined that data edge computing needs to be performed on the initial data, decrypting the initial data that has been subjected to the first encryption processing, and performing data edge computing on the initial data to obtain a data computing result;

[0029] Perform a second encryption process on the data calculation result to obtain the data calculation result after the second encryption process.

[0030] In a second aspect, an embodiment of the present application provides an industrial data processing device, including:

[0031] An acquisition module, used to acquire initial data of industrial equipment;

[0032] A processing module, used to determine a data algorithm corresponding to the initial data from the adaptive matching algorithm center, and use the data algorithm to perform data edge calculation on the initial data to obtain a data calculation result;

[0033] The processing module is further used to determine the dynamic instructions that match the data calculation result;

[0034] The control module is used to control the industrial equipment to execute the corresponding instruction action based on the dynamic instruction.

[0035] In a possible implementation manner, the processing module further includes: a determination module;

[0036] A determination module, used to determine the data type of the initial data;

[0037] The determination module is also used to determine, based on the first association relationship, a candidate algorithm that has a first association relationship with the data type from the adaptive matching algorithm center, and use the candidate algorithm as the data algorithm corresponding to the initial data.

[0038] In a possible implementation, the processing module is further used to determine or generate a user relationship mapping table according to the data type and the tag attribute corresponding to the initial data, wherein the tag attribute is used to indicate the data source and output range of the initial data, and the user relationship mapping table is used to indicate the channel starting point and channel end point of at least one virtualized channel;

[0039] The processing module is further used to perform multi-channel distribution processing on the initial data and the data calculation result based on the at least one virtualization channel and the user relationship mapping table.

[0040] In one possible implementation, the processing module is also used to load instruction dynamic information into an instruction hash list, wherein the instruction dynamic information includes multiple dynamic instructions, and the hash list is used to indicate a third association relationship between an execution action and the dynamic instructions; determine the action to be executed corresponding to the data calculation result; and match dynamic instructions for the action to be executed based on the instruction hash list.

[0041] In a possible implementation, the processing module is also used to determine the corresponding event attributes based on the initial data; based on the event attributes, determine whether the data calculation results meet the preset rules; when the data calculation results meet the preset rules, determine the corresponding dynamic instructions based on the pre-stored instruction dynamic information and event attributes.

[0042] In a possible implementation, the device further includes an encryption and decryption module;

[0043] An encryption and decryption module, used for performing a first encryption process on the initial data;

[0044] In the case where it is determined that data edge computing needs to be performed on the initial data, the encryption and decryption module is further used to decrypt the initial data that has undergone the first encryption processing, and perform data edge computing on the initial data to obtain a data computing result;

[0045] The encryption and decryption module is also used to perform a second encryption process on the data calculation result to obtain the data calculation result after the second encryption process.

[0046] In a third aspect, an embodiment of the present application provides an industrial data processing device, including: a memory, a processor;

[0047] Memory stores computer-executable instructions;

[0048] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and various possible implementations of the first aspect.

[0049] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above first aspect and various possible implementation methods of the first aspect.

[0050] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and various possible implementation methods of the first aspect.

[0051] The embodiments of the present application provide a method, device, equipment and medium for processing industrial data. The method determines the data algorithm corresponding to the initial data from the adaptive matching algorithm center, performs data edge calculation on the initial data, matches dynamic instructions based on the results of the data edge calculation, and controls the device to execute corresponding instruction actions according to the dynamic instructions. The data is calculated simply and conveniently, the speed and accuracy of data processing are improved, and flexible and efficient edge data calculation and data analysis are realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0053] Figure 1 A schematic diagram of a process for processing industrial data provided in an embodiment of the present application Figure 1 ;

[0054] Figure 2 A schematic diagram of a process for processing industrial data provided in an embodiment of the present application Figure 2 ;

[0055] Figure 3 A schematic diagram of the structure of an industrial data processing device provided in an embodiment of the present application;

[0056] Figure 4 A schematic diagram of the structure of an industrial data processing device provided in an embodiment of the present application.

[0057] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0058] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0059] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0060] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein, for example, can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, products or devices.

[0061] "Plurality" means two or more, and other quantifiers are similar.

[0062] In the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0063] Edge computing technology is an open platform that integrates network, computing, storage, and application core capabilities to provide the nearest service at the side close to the source of objects or data. Its application is initiated at the edge side, resulting in faster network service response, meeting the basic needs of the industry in terms of real-time business, application intelligence, security and privacy protection, etc.

[0064] With the advent of the Industrial 4.0 era, the deep integration of Information Technology (IT) and Operational Technology (OT) has not only broken down data silos, but also improved production flexibility and efficiency, and enhanced corporate competitiveness.

[0065] Currently, in industrial automation, smart manufacturing, the Internet of Things, and other scenarios that require data processing and analysis at the edge of the network, edge computing is usually performed by sending orchestration rules from the cloud to install a script environment to achieve edge-cloud collaboration.

[0066] However, existing edge computing technologies still rely on the cloud and are inefficient when processing initial data collected by industrial equipment.

[0067] In response to the above problems, the present application provides a method for processing industrial data. The method adaptively matches the data algorithm according to the initial data, performs data edge calculation on the initial data, and matches dynamic instructions for the data calculation results based on the dynamic information of the instructions. The method solves the problem of low efficiency existing in the prior art by adaptively matching the data algorithm, and solves the problem of dependence on the cloud existing in the prior art by using dynamic information of the instructions, thereby realizing flexible and efficient edge data calculation and data analysis.

[0068] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0069] Figure 1 A schematic diagram of a process for processing industrial data provided in an embodiment of the present application Figure 1 .like Figure 1 As shown, the method includes:

[0070] S101. Acquire initial data of industrial equipment.

[0071] Among them, industrial equipment can be, for example, production equipment, monitoring equipment, intelligent equipment, etc.; initial data can be, for example, production data, monitoring data, intelligent IoT equipment data, etc.

[0072] Based on the usage environment, obtain the initial data of industrial equipment such as production equipment, monitoring equipment, intelligent equipment, such as production data, monitoring data, smart IoT equipment data, etc.

[0073] S102: Determine a data algorithm corresponding to the initial data from the adaptive matching algorithm center, and use the data algorithm to perform data edge calculation on the initial data to obtain a data calculation result.

[0074] Among them, the adaptive matching algorithm center includes a third-party algorithm module, a conventional mathematical calculation module, and a filtering algorithm module. Among them, the conventional mathematical calculation module mainly includes the mean algorithm, the weighted average algorithm, the variance algorithm, the mathematical matrix algorithm, etc.; data edge computing is to perform data processing near the industrial equipment that obtains the initial data.

[0075] Near the industrial equipment that obtains the initial data, the data algorithm corresponding to the initial data is determined from the adaptive matching algorithm center, and the data algorithm is used to perform data processing such as filtering, mean calculation, variance calculation, etc. on the initial data to obtain the data calculation results. Performing data processing near the industrial equipment that obtains the initial data effectively reduces the latency of data processing and improves the response speed of data processing.

[0076] Exemplarily, multiple monitoring data at the same time A collected by multiple monitoring devices are obtained, and the data algorithm corresponding to the multiple monitoring data at the same time A is determined from the adaptive matching algorithm center to be the mean algorithm. Then, based on the mean algorithm, the multiple monitoring data at the same time A are averaged to obtain the mean of the monitoring data.

[0077] S103: Determine a dynamic instruction that matches the data calculation result.

[0078] Among them, dynamic instructions are instructions for controlling the operation of devices and programs.

[0079] Data edge source supports dynamic instruction matching and execution, so the matching dynamic instructions are determined based on the data calculation results.

[0080] Exemplarily, it can be understood that the mean value of the monitoring data at A reflects the corresponding state at A. Therefore, the state reporting instruction is matched according to the mean value of the monitoring data.

[0081] S104: Based on the dynamic instruction, control the industrial equipment to execute a corresponding instruction action.

[0082] According to the dynamic instructions matched by the data calculation results, the industrial equipment is controlled to execute the corresponding instruction actions according to the dynamic instructions.

[0083] For example, according to the status reporting instruction matching the mean value of the monitoring data at A, the monitoring device is controlled to report the corresponding mean value of the monitoring data.

[0084] An embodiment of the present application provides a method for processing industrial data. The method determines a data algorithm corresponding to initial data from an adaptive matching algorithm center, performs data edge calculation on the initial data, matches dynamic instructions based on the results of the data edge calculation, and controls the device to execute corresponding instruction actions according to the dynamic instructions. The method calculates the data simply and conveniently, improves the speed and accuracy of data processing, and realizes flexible and efficient edge data calculation and data analysis.

[0085] Figure 2 A schematic diagram of a process for processing industrial data provided in an embodiment of the present application Figure 2 In this embodiment, the adaptive matching algorithm center includes multiple candidate algorithms and first association relationships between the multiple candidate algorithms and data types. Figure 2 As shown, in this embodiment Figure 1 Based on the embodiment, a method for processing industrial data is described in detail, and the method includes:

[0086] S201. Acquire initial data of industrial equipment.

[0087] Step S201 is similar to step S101 and will not be described again here.

[0088] S202: Determine the data type of the initial data.

[0089] The data type may be, for example, integer, floating point, character, etc.

[0090] Determine the data type corresponding to the initial data, such as integer, floating point, character, etc.

[0091] In a possible implementation, there is only one memory address of the initial data. In order to improve data utilization, the initial data memory address is transferred by operation to enable different channel users to use the initial data. The specific process is as follows:

[0092] A user relationship mapping table is determined or generated according to the data type and the tag attribute corresponding to the initial data; and multi-channel distribution processing is performed on the initial data and the data calculation results based on the virtualization channel and the user relationship mapping table.

[0093] The tag attribute is used to indicate the data source and output range of the initial data; the user relationship mapping table is used to indicate the channel start point and channel end point of at least one virtualized channel.

[0094] According to the data type and the tag attribute for indicating the data source and output range of the initial data, a user relationship mapping table for indicating the channel start point and channel end point of at least one virtualized channel is determined or generated. And according to the virtualized channel, the initial data and the data calculation result obtained according to the initial data are subjected to multi-channel distribution processing.

[0095] For example, the initial data obtained are all floating point types, and according to the data type, the data collected by industrial equipment A are all floating point types, so the data source of the initial data is determined. According to the output requirements of industrial equipment A, the output range is determined, and then the user relationship mapping table is determined or generated.

[0096] Different channels can process different types of data separately without affecting each other. Multi-user relationship mapping can realize flexible use of data and data sharing, which improves data utilization. It can realize data isolation, storage and differentiation processing, realize the localization of data processing at the operation layer, reduce the dependence on the central cloud IT, and improve the real-time performance of the system.

[0097] In a possible implementation, after the initial data is acquired, the initial data may be preprocessed, and a tag attribute corresponding to the preprocessed data may be determined, where the tag attribute is used to indicate a data source and an output range of the initial data.

[0098] Among them, preprocessing includes cleaning, standardization, and format conversion.

[0099] By cleaning, standardizing and formatting the initial data, data quality is ensured and invalid data transmission is reduced, so that heterogeneous, different hosts and different locations of equipment data channels can be cascaded. The cleaned, standardized and formatted data is pre-labeled to determine the corresponding label attributes.

[0100] In a possible implementation, in order to improve data utilization, the initial data may also be directly sent to different channel users. Therefore, in order to improve the security of the initial data, the initial data may be encrypted after being obtained to improve its security.

[0101] The specific encryption process is as follows:

[0102] Before performing data edge computing on the initial data to obtain the data computing result, the method further includes: performing a first encryption process on the initial data;

[0103] The adaptive matching algorithm center also includes a data encryption and decryption module.

[0104] Through the data encryption and decryption module in the adaptive matching algorithm center, the initial data is encrypted before the data edge calculation is performed on the initial data to obtain the data calculation result, which improves the data security during data transmission.

[0105] Based on the above process, a possible implementation method of performing data edge computing on the initial data to obtain the data computing result may be, for example:

[0106] In the case where it is determined that data edge computing needs to be performed on the initial data, decrypting the initial data that has been subjected to the first encryption processing, and performing data edge computing on the initial data to obtain a data computing result;

[0107] When it is determined that data edge calculation needs to be performed on the initial data, the data encryption and decryption module in the adaptive matching algorithm center is used to decrypt the initial data that has undergone the first encryption process, and then data edge calculation is performed on the decrypted initial data through the data algorithm in the adaptive matching algorithm center to obtain the data calculation result.

[0108] On the basis of the above process, a possible implementation method of performing multi-channel distribution processing on the initial data and the data calculation result may be, for example: performing a second encryption processing on the data calculation result to obtain the data calculation result after the second encryption processing.

[0109] The data calculation result is subjected to a second encryption process through the data encryption and decryption module in the adaptive matching algorithm center, and the initial data subjected to the first encryption process and the data calculation result subjected to the second encryption process are subjected to multi-channel distribution processing.

[0110] S203: Based on the first association relationship, determine a candidate algorithm that has a first association relationship with the data type from an adaptive matching algorithm center, and use the candidate algorithm as a data algorithm corresponding to the initial data.

[0111] The first association relationship between multiple candidate algorithms and data types is pre-set. Based on the first association relationship between multiple candidate algorithms and data types, a candidate algorithm that has a first association relationship with the data type of the initial data is determined from the adaptive matching algorithm center, and the candidate algorithm is used as the data algorithm corresponding to the initial data.

[0112] S204: Using the data algorithm, perform data edge calculation on the initial data to obtain a data calculation result.

[0113] The data algorithm corresponding to the initial data is used to perform data edge calculation on the initial data, such as mean calculation, variance calculation, etc., to obtain the data calculation result.

[0114] S205: Load the instruction dynamic information into the instruction hash linked list.

[0115] The instruction dynamic information includes multiple dynamic instructions. Before data processing, the instruction dynamic information is preloaded and stored for subsequent quick search and use; the hash linked list is used to indicate the third association relationship between the execution action and the dynamic instruction.

[0116] A plurality of dynamic instructions are obtained, each of which includes a dynamic instruction name and a dynamic instruction path, and the plurality of dynamic instructions are loaded into an instruction hash chain table indicating a third association relationship between an execution action and the dynamic instructions.

[0117] S206: Determine the action to be executed corresponding to the data calculation result.

[0118] The action to be executed may be, for example, an alarm action, a status reporting action, a control action, etc.

[0119] According to the data calculation results, the corresponding alarm action, status reporting action, control action and waiting action are determined. For example, according to the mean value of the monitoring data, the waiting action corresponding to the mean value of the monitoring data is determined to be the status reporting action.

[0120] S207: Match dynamic instructions for the actions to be executed based on the instruction hash list.

[0121] Based on the instruction hash chain table indicating the third association relationship between the execution action and the dynamic instruction, the dynamic instruction corresponding to the action to be executed is searched, and the search result is used as the dynamic instruction corresponding to the action to be executed.

[0122] The matching between execution actions and dynamic instructions is achieved through the instruction hash linked list, making the matching of execution actions more flexible and fast.

[0123] In one possible implementation, the instruction dynamic information supports an online update mode. When a new execution action is required, the corresponding instruction dynamic information is directly updated to add a new execution action. The execution details of the action are completely hidden and invisible, thereby protecting the privacy and security of industrial equipment. The instruction dynamic information supports an online update mode, making the matching of execution actions easy to maintain and expand.

[0124] In a possible implementation, dynamic instructions can also be determined by the data calculation results and the event attributes corresponding to the initial data. The specific process is as follows: determine the corresponding event attributes based on the initial data; based on the event attributes, judge whether the data calculation results meet the preset rules; when the data calculation results meet the preset rules, determine the corresponding dynamic instructions based on the pre-stored instruction dynamic information and event attributes.

[0125] For example, the event attribute corresponding to the initial data can be determined through pre-marking processing; the event attribute corresponding to the initial data can be determined through the source of the initial data.

[0126] Exemplarily, the initial data may be temperature monitoring data of industrial equipment, and the event attribute may be an alarm event. After edge computing is performed on the temperature monitoring device, the temperature data of the industrial equipment is obtained, and based on the alarm event, it is determined whether the temperature data reaches the alarm threshold. If the temperature data reaches the alarm threshold, the dynamic instruction is an alarm.

[0127] S208: Based on the dynamic instruction, control the industrial device to execute a corresponding instruction action.

[0128] According to dynamic execution, control production equipment, monitoring equipment, intelligent equipment and other industrial equipment to execute corresponding command actions.

[0129] In one possible implementation, the dynamic instruction can be empty, and the corresponding instruction action is no action. During the processing, the no action processing outputs an event, which can be used for secondary development by users or for third-party IT platforms. Both parties implement demand expansion according to the pre-agreed event interface, which can meet the edge computing needs of different scenarios.

[0130] In one possible implementation, the data calculation results are synchronized with the cloud to achieve a higher level of data analysis and decision support.

[0131] Understandably, in order to ensure the standardization of edge computing platforms, so as to facilitate the compatibility and integration between different devices and systems, standardized interfaces and modular designs are adopted to ensure the standardization and compatibility of operation and calculation of different devices, and to follow the relevant industry standards.

[0132] An embodiment of the present application provides a method for processing industrial data. The method determines a data algorithm corresponding to initial data from an adaptive matching algorithm center based on the association between candidate algorithms and data types, performs data edge calculation on the initial data, matches dynamic instructions based on a hash list and the results of data edge calculation, calculates the data simply and conveniently, improves the speed and accuracy of data processing, and realizes flexible and efficient edge data calculation and data analysis.

[0133] Figure 3 A schematic diagram of the structure of an industrial data processing device provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, an industrial data processing device 30 provided in this embodiment includes:

[0134] An acquisition module 301 is used to acquire initial data of industrial equipment;

[0135] The processing module 302 is used to determine a data algorithm corresponding to the initial data from the adaptive matching algorithm center, and use the data algorithm to perform data edge calculation on the initial data to obtain a data calculation result;

[0136] The processing module 302 is further used to determine the dynamic instruction that matches the data calculation result;

[0137] The control module 303 is used to control the industrial device to execute a corresponding instruction action based on the dynamic instruction.

[0138] In a possible implementation, the processing module 302 further includes: a determination module 304;

[0139] A determination module 304, configured to determine a data type of the initial data;

[0140] The determination module 304 is further configured to determine, based on the first association relationship, a candidate algorithm having a first association relationship with the data type from the adaptive matching algorithm center, and use the candidate algorithm as a data algorithm corresponding to the initial data.

[0141] In a possible implementation, the processing module 302 is further used to determine or generate a user relationship mapping table according to the data type and the tag attribute corresponding to the initial data, wherein the tag attribute is used to indicate the data source and output range of the initial data, and the user relationship mapping table is used to indicate the channel starting point and channel end point of at least one virtualized channel;

[0142] The processing module 302 is further configured to perform multi-channel distribution processing on the initial data and the data calculation result based on the at least one virtualization channel and the user relationship mapping table.

[0143] In one possible implementation, the processing module 302 is also used to load instruction dynamic information into an instruction hash list, wherein the instruction dynamic information includes multiple dynamic instructions, and the hash list is used to indicate a third association relationship between an execution action and the dynamic instructions; determine the action to be executed corresponding to the data calculation result; and match dynamic instructions for the action to be executed based on the instruction hash list.

[0144] In a possible implementation, the processing module 302 is also used to determine the corresponding event attributes based on the initial data; based on the event attributes, determine whether the data calculation results meet the preset rules; when the data calculation results meet the preset rules, determine the corresponding dynamic instructions based on the pre-stored instruction dynamic information and event attributes.

[0145] In a possible implementation, the device further includes an encryption and decryption module 305;

[0146] The encryption and decryption module 305 is used to perform a first encryption process on the initial data;

[0147] In the case where it is determined that data edge calculation needs to be performed on the initial data, the encryption and decryption module 305 is further used to decrypt the initial data that has undergone the first encryption process, and perform data edge calculation on the initial data to obtain a data calculation result;

[0148] The encryption and decryption module 305 is further used to perform a second encryption process on the data calculation result to obtain the data calculation result after the second encryption process.

[0149] The present embodiment provides an industrial data processing device, which can execute the method provided by the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail in this embodiment.

[0150] Figure 4 This is a schematic diagram of the structure of an industrial data processing device provided by this application. Figure 4 As shown, the electronic device 40 provided in this embodiment includes: at least one processor 401 and a memory 402. Optionally, the device 40 also includes a communication component 403. The processor 401, the memory 402 and the communication component 403 are connected via a bus 404.

[0151] In a specific implementation process, at least one processor 401 executes the computer-executable instructions stored in the memory 402, so that at least one processor 401 executes the above method.

[0152] The specific implementation process of the processor 401 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0153] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0154] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0155] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0156] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0157] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0158] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0159] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0160] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0161] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0162] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0163] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0164] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0165] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for processing industrial data, characterized in that: include: Obtain initial data of industrial equipment; Determine a data algorithm corresponding to the initial data from the adaptive matching algorithm center, and use the data algorithm to perform data edge calculation on the initial data to obtain a data calculation result; Determining a dynamic instruction that matches the data calculation result; Based on the dynamic instruction, the industrial device is controlled to execute a corresponding instruction action.

2. The method according to claim 1, characterized in that The adaptive matching algorithm center includes a plurality of candidate algorithms and a first association relationship between the plurality of candidate algorithms and data types, and the step of determining the data algorithm corresponding to the initial data from the adaptive matching algorithm center includes: Determine the data type of the initial data; Based on the first association relationship, a candidate algorithm having a first association relationship with the data type is determined from the adaptive matching algorithm center, and the candidate algorithm is used as the data algorithm corresponding to the initial data.

3. The method according to claim 2, characterized in that After performing data edge calculation on the initial data to obtain the data calculation result, the method further includes: Determine or generate a user relationship mapping table according to the data type and the tag attribute corresponding to the initial data, wherein the tag attribute is used to indicate the data source and output range of the initial data, and the user relationship mapping table is used to indicate the channel starting point and channel end point of at least one virtualized channel; Based on the at least one virtualized channel and the user relationship mapping table, multi-channel distribution processing is performed on the initial data and the data calculation result.

4. The method according to claim 1, characterized in that: The dynamic instruction for determining the matching of the data calculation result includes: Loading instruction dynamic information into an instruction hash chain table, wherein the instruction dynamic information includes a plurality of dynamic instructions, and the hash chain table is used to indicate a third association relationship between an execution action and the dynamic instructions; Determine an action to be performed corresponding to the data calculation result; Based on the instruction hash list, dynamic instructions are matched for the actions to be executed.

5. The method according to claim 1, characterized in that The dynamic instruction for determining the matching of the data calculation result includes: Determine corresponding event attributes according to the initial data; Based on the event attributes, determining whether the data calculation result satisfies a preset rule; When the data calculation result satisfies the preset rule, the corresponding dynamic instruction is determined according to the pre-stored instruction dynamic information and event attributes.

6. The method according to claim 1, characterized in that Before performing data edge calculation on the initial data to obtain the data calculation result, the method further includes: Performing a first encryption process on the initial data; The performing edge computing on the initial data to obtain a data computing result includes: In the case where it is determined that data edge computing needs to be performed on the initial data, decrypting the initial data that has been subjected to the first encryption processing, and performing data edge computing on the initial data to obtain a data computing result; Perform a second encryption process on the data calculation result to obtain the data calculation result after the second encryption process.

7. An industrial data processing device, characterized in that: include: An acquisition module, used to acquire initial data of industrial equipment; A processing module, used to determine a data algorithm corresponding to the initial data from the adaptive matching algorithm center, and use the data algorithm to perform data edge calculation on the initial data to obtain a data calculation result; The processing module is further used to determine the dynamic instructions that match the data calculation result; The control module is used to control the industrial equipment to execute the corresponding instruction action based on the dynamic instruction.

8. The device according to claim 7, characterized in that The adaptive matching algorithm center includes a plurality of candidate algorithms and a first association relationship between the plurality of candidate algorithms and data types. The processing module further includes: A determination module, used to determine the data type of the initial data; The determination module is further used to determine, based on the first association relationship, a candidate algorithm having a first association relationship with the data type from the adaptive matching algorithm center, and use the candidate algorithm as the data algorithm corresponding to the initial data.

9. An industrial data processing device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the industrial data processing method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the industrial data processing method according to any one of claims 1 to 6 when executed by a processor.

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