Implementation method of industrial equipment marginal object model

Abstract

The invention relates to the technical field of industrial internet and the technical field of data processing, in particular to an implementation method of an industrial equipment edge object model. Comprising the steps of establishing an initial object model library; traversing all edge hardware devices, and establishing edge object models of the edge hardware devices in sequence; generating a device evaluation value of each edge hardware device, and setting an update time node of each edge object model according to all the device evaluation values; the object model is bound with edge hardware equipment, and the virtual object model is converted into actual physical equipment; the edge hardware equipment is endowed with different processing capabilities, and the universality of the hardware equipment is improved. The data processing capacity of edge hardware equipment is improved, the edge equipment is endowed with different functions according to different mapping models through edge object model hardware adaptation, the edge equipment executes the different functions according to object model attributes and operation strategies, and dynamic adjustment of the functions of the edge equipment based on object model driving is achieved.

Description

Technical Field

[0001] The present application relates to the fields of industrial Internet technology and data processing technology, and in particular to a method for implementing an edge object model of industrial equipment. Background Art

[0002] The physical model can better solve the problems encountered in the communication between industrial IoT devices and between devices and the cloud. The physical model is a digital description of the product, which defines the functions of the product. By functionally classifying physical devices and extracting data, the actual devices are abstracted and summarized through digital modeling to form a "standard physical model", which makes it easier for all parties to describe, control and understand product functions in a unified language.

[0003] However, there are still many problems in the use of physical model technology in industrial scenarios. Specifically, there are many types of equipment, different properties, and diverse communication protocols. Providing digital modeling and basic interactive capabilities for industrial equipment has become a challenge. Whether the physical model can match the equipment and reflect the actual status of the equipment directly affects the expansion of system functions and continuous use.

[0004] In industrial scenarios, edge computing devices can be closely integrated with industrial engineering equipment. With the improvement of edge device computing power, data collection and calculation can be completed by edge devices. In practical applications, it can effectively reduce the communication delay of cloud-edge collaboration and improve data processing efficiency. But at the same time, the improvement of edge computing power brings new problems: In cloud-edge collaboration scenarios: it is necessary to consider the collaboration between cloud and edge devices in the physical model design, and push some intelligent processing to edge devices to reduce latency and improve efficiency. Summary of the invention

[0005] The purpose of this application is: to solve the above-mentioned technical problems, this application provides a method for implementing an edge object model of industrial equipment, aiming to offline solidify and bind the object model with the edge hardware device to improve the versatility of the hardware device.

[0006] In some embodiments of the present application, the virtual physical model is converted into an actual physical device by binding the physical model to the edge hardware device; the edge hardware device is given different processing capabilities to improve the versatility of the hardware device. The data processing capability of the edge hardware device is improved, and different functions are given to the edge device according to different mapping models through the hardware adaptation of the edge physical model. The edge device performs different functions according to the physical model attributes and operation strategies, and realizes the dynamic adjustment of the edge device function driven by the physical model.

[0007] In some embodiments of the present application, different edge hardware devices can be equipped with multiple physical models to achieve elastic expansion and dynamic functional tuning of physical models in edge devices, and through edge physical model algorithm integration, dynamic updating of business algorithms can be achieved, and on-site algorithms can be dynamically changed and tuned according to different actual application scenarios.

[0008] In some embodiments of the present application, a method for implementing an edge object model of industrial equipment is provided, including:

[0009] Establishing an initial material model library;

[0010] Traverse all edge hardware devices and build edge object models for each edge hardware device in turn;

[0011] Generate device evaluation values ​​for each edge hardware device, and set the update time nodes for each edge object model based on all device evaluation values;

[0012] Among them, when traversing all edge hardware devices, including:

[0013] Establish an edge hardware device sequence A, A = (a1, a2...ai...an), where ai is the i-th edge hardware device; n is the number of edge hardware devices.

[0014] In some embodiments of the present application, when establishing an edge object model of each edge hardware device, it includes:

[0015] According to the edge hardware device sequence A, the i-th edge hardware device is sequentially set as the target edge hardware device;

[0016] Establish an edge object model k of the target edge hardware device;

[0017] The multi-level data structure of the edge object model s is set according to the business scenario parameters and multi-source heterogeneous parameters of the target edge hardware device;

[0018] Establish a driver framework for target edge hardware devices;

[0019] Bind the edge object model k and the target edge hardware device through the driver framework;

[0020] Set the dynamic interpretation and execution process of the edge object model k;

[0021] Set the dynamic update strategy of edge object model k;

[0022] Build edge object models for each edge hardware device in turn;

[0023] Establish an edge object model sequence K, K = (k1, k2...ki...kn), where ki is the edge object model of the i-th edge hardware device.

[0024] In some embodiments of the present application, when setting the multi-level data structure of the edge object model s, it includes:

[0025] Build a physical parameter description hierarchy based on the device parameters of the target edge hardware device;

[0026] Build a business logic hierarchy based on the business data of the target edge hardware device;

[0027] Generate a heterogeneous interface hierarchy of edge object models;

[0028] A multi-level data structure is established based on the heterogeneous interface level, business logic level and physical parameter description level.

[0029] In some embodiments of the present application, the construction of the business logic hierarchy includes:

[0030] Traverse historical business data and establish multiple business categories;

[0031] Establish a service category sequence P, P = (p1, p2...pi...pm), where pi is the i-th service category; m is the number of service categories;

[0032] Generate business logic processes for each business category in sequence;

[0033] Establish a business logic process sequence B, B = (b1, b2...bi...bm), where bi is the business logic process of the i-th business category;

[0034] Set the calling model of the business logic process;

[0035] Construct the business logic hierarchy based on the call model and business logic process sequence B.

[0036] In some embodiments of the present application, when setting the calling model of the business logic process, it includes:

[0037] Obtain on-site business parameters of the target edge hardware device;

[0038] Extract characteristic indicators based on on-site business parameters;

[0039] Generate similarity evaluation values ​​for each business category based on all characteristic indicators;

[0040] Establish a similarity evaluation value sequence F, F = (f1, f2...fi...fm), where fi is the similarity evaluation value between the on-site business parameter and the i-th business category;

[0041] Call the business logic process of the business category corresponding to the maximum value fmax in the similar evaluation value sequence F.

[0042] In some embodiments of the present application, when establishing a driver framework for a target edge hardware device, the process includes:

[0043] Set up the basic framework and configuration files of the target edge hardware device;

[0044] Set the driving strategy for the target edge hardware device;

[0045] Construct the docking parameters of the edge object model s for the driving strategy of the target edge hardware device;

[0046] Generate a model interface management strategy for the target edge hardware device based on the docking parameters;

[0047] Build the driver framework of the target edge hardware device based on the basic framework, configuration files, driver strategy and model interface management strategy.

[0048] In some embodiments of the present application, when setting the dynamic interpretation execution process of the edge object model k, it includes:

[0049] Read the configuration file of the target edge hardware device and generate storage instructions for the configuration file;

[0050] Perform lexical analysis on the configuration file to generate multiple lexical units;

[0051] Preprocess all lexical units and build a syntax tree based on the preprocessing results;

[0052] Traversing the syntax tree, converting each syntax node into a program instruction, wherein the program instruction includes: a logic instruction and a driving instruction;

[0053] Execute instructions based on the interpretation results.

[0054] In some embodiments of the present application, when generating a device evaluation value of each edge hardware device, it includes:

[0055] Set the equipment evaluation index sequence J, J = (j1, j2...ji...jr), where ji is the i-th equipment evaluation index;

[0056] Obtain a target edge hardware device and generate a device evaluation value g of the target edge hardware device;

[0057]

[0058] Wherein, di is the reference value of the i-th device evaluation index of the target edge hardware device; βi is the influencing factor of the i-th device evaluation index;

[0059] Generate device evaluation values ​​for each edge hardware device in turn;

[0060] Establish a device evaluation value sequence G, G = (g1, g2...gi...gr), where gi is the device evaluation value of the i-th edge hardware device.

[0061] In some embodiments of the present application, when setting the update time node of each edge object model, it includes:

[0062] Obtain the device evaluation value g of the target edge hardware device;

[0063] Generate an update evaluation value h of the target edge hardware device at the current update time node;

[0064] h=e1*Q1*g+e2*Q2*U;

[0065] Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; U is the historical evaluation value of the target edge hardware device at the current update time node;

[0066] According to the update evaluation value h, the update cycle length t of the edge object model k of the target edge hardware device at the current update time node is set;

[0067] Set the next update time node of edge object model k according to the update cycle duration t;

[0068] When the update time node is reached, the dynamic update strategy of the edge object model k is executed;

[0069] Set the update time nodes of each edge object model in sequence.

[0070] In some embodiments of the present application, when setting the update cycle duration t, it includes:

[0071] Presetting a first updated evaluation value interval (H1, H2), a second updated evaluation value interval (H2, H3) and a third updated evaluation value interval (H3, H4);

[0072] If the update evaluation value h is within the preset first update evaluation value interval, the update cycle duration t is set to the preset first duration T1, that is, t=T1;

[0073] If the update evaluation value h is within the preset second update evaluation value interval, the update cycle duration t is set to the preset second duration T2, that is, t=T2;

[0074] If the update evaluation value h is in the preset third update evaluation value interval, the update cycle duration t is set to the preset third duration T3, that is, t=T3; and T1>T2>T3.

[0075] Compared with the prior art, the method for implementing an edge object model of industrial equipment in the embodiment of the present application has the following beneficial effects:

[0076] By binding the physical model with the edge hardware device, the virtual physical model is converted into an actual physical device; the edge hardware device is given different processing capabilities to improve the versatility of the hardware device. The data processing capabilities of the edge hardware device are improved. Through the hardware adaptation of the edge physical model, different functions are given to the edge device according to different mapping models. The edge device performs different functions according to the physical model attributes and operation strategies, realizing dynamic adjustment of edge device functions driven by the physical model.

[0077] Different edge hardware devices can be equipped with a variety of object models to achieve elastic expansion and dynamic function tuning of object models in edge devices, and through edge object model algorithm integration, dynamic updating of business algorithms can be achieved. According to different actual application scenarios, the on-site algorithms can be dynamically changed and tuned. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a flow chart of a method for implementing an edge object model of industrial equipment in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0079] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0080] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0081] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0082] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0083] like Figure 1 As shown, a method for implementing an industrial equipment edge object model in a preferred embodiment of the present application includes:

[0084] S101: Establishing an initial object model library;

[0085] S102: Traverse all edge hardware devices and establish edge object models of each edge hardware device in turn;

[0086] S103: Generate a device evaluation value for each edge hardware device, and set an update time node for each edge object model according to all device evaluation values;

[0087] Among them, when traversing all edge hardware devices, including:

[0088] Establish an edge hardware device sequence A, A = (a1, a2...ai...an), where ai is the i-th edge hardware device; n is the number of edge hardware devices.

[0089] Specifically, the initial object model library is a traditional type of object model established based on industrial equipment parameters, and the initial model library includes multiple object models.

[0090] Specifically, when establishing the edge object model of each edge hardware device, it includes:

[0091] According to the edge hardware device sequence A, the i-th edge hardware device is sequentially set as the target edge hardware device;

[0092] Establish an edge object model k of the target edge hardware device;

[0093] The multi-level data structure of the edge object model s is set according to the business scenario parameters and multi-source heterogeneous parameters of the target edge hardware device;

[0094] Establish a driver framework for target edge hardware devices;

[0095] Bind the edge object model k and the target edge hardware device through the driver framework;

[0096] Set the dynamic interpretation and execution process of the edge object model k;

[0097] Set the dynamic update strategy of edge object model k;

[0098] Build edge object models for each edge hardware device in turn;

[0099] Establish an edge object model sequence K, K = (k1, k2...ki...kn), where ki is the edge object model of the i-th edge hardware device.

[0100] Specifically, the physical model is reconstructed and optimized, and the edge hardware devices are adapted to build edge physical models of each edge hardware device. The virtual physical model is converted into an actual physical device, giving the edge hardware devices different processing capabilities and improving the versatility of the hardware devices.

[0101] Specifically, different edge hardware devices can be equipped with multiple physical models to achieve elastic expansion and dynamic functional tuning of physical models in edge devices.

[0102] In a preferred embodiment of the present application, when setting the multi-level data structure of the edge object model s, it includes:

[0103] Build a physical parameter description hierarchy based on the device parameters of the target edge hardware device;

[0104] Build a business logic hierarchy based on the business data of the target edge hardware device;

[0105] Generate a heterogeneous interface hierarchy of edge object models;

[0106] A multi-level data structure is established based on the heterogeneous interface level, business logic level and physical parameter description level.

[0107] Specifically, according to the actual needs of industrial business scenarios and multi-source heterogeneous data, the edge object model is designed in the form of a nested description file, and a multi-level data structure is constructed. Through the organic combination of multi-level description structures, a complete edge object model is formed.

[0108] Specifically, each level of data is designed as a nested data structure, and the individual data contained therein is designed as a "key-value" model.

[0109] Specifically, the physical parameter description level is the attribute description of the physical device, which is composed of the basic device description table and the personalized parameter table. The basic description table contains its device identification ID, service types that can be provided, data access rights, built-in storage type and device type, etc. The personalized parameter table contains various indicator parameters of different types of industrial equipment: such as current, voltage, shaft temperature, lubrication, liquid level, opening and closing information, etc. Each personalized parameter contains nested multiple attributes, which are used to describe the attributes of physical services or logical services. The various parameters of the equipment are collected and counted from actual scene statistics when designers model the industrial equipment. Each parameter has a unique KEY value in the same level table structure to ensure the uniqueness of the parameters.

[0110] Specifically, the heterogeneous interface layer is mainly the communication protocol with heterogeneous hardware devices, including virtual abstract data and actual data paths of heterogeneous devices (such as UART, SPI, IIC, LAN, CAN and other low-speed interfaces). PL is a point-to-many feature, and the edge object model uses the interface layer data path. The heterogeneous peripheral parameters are sent to PL, and PL needs to feedback status data to the edge object model for interpretation and execution. The heterogeneous interface must be called internally by PL to access the registers through the heterogeneous interface, providing parameters to PL and reading back the status of PL to realize interface reading and writing and underlying register operations.

[0111] Specifically, when building the business logic layer, include:

[0112] Traverse historical business data and establish multiple business categories;

[0113] Establish a service category sequence P, P = (p1, p2...pi...pm), where pi is the i-th service category; m is the number of service categories;

[0114] Generate business logic processes for each business category in sequence;

[0115] Establish a business logic process sequence B, B = (b1, b2...bi...bm), where bi is the business logic process of the i-th business category;

[0116] Set the calling model of the business logic process;

[0117] Construct the business logic hierarchy based on the call model and business logic process sequence B.

[0118] Specifically, when setting the calling model of the business logic process, it includes:

[0119] Obtain on-site business parameters of the target edge hardware device;

[0120] Extract characteristic indicators based on on-site business parameters;

[0121] Generate similarity evaluation values ​​for each business category based on all characteristic indicators;

[0122] Establish a similarity evaluation value sequence F, F = (f1, f2...fi...fm), where fi is the similarity evaluation value between the on-site business parameter and the i-th business category;

[0123] Call the business logic process of the business category corresponding to the maximum value fmax in the similar evaluation value sequence F.

[0124] Specifically, the larger the similarity evaluation value, the more similar the actual on-site situation corresponding to the current edge hardware device is to the corresponding business category. The data processing capability of edge hardware devices can be improved by quickly calling the corresponding business logic process.

[0125] Specifically, the business logic process mainly relies on the hardware functions of the device to collect and analyze edge data and sub-devices. The business logic process can realize multiple functions, which are called by the specific business on-site of the edge device to analyze and calculate the input data, and feedback and output the edge calculation results. The business logic process is replaceable and can be issued and updated through the model, and dynamically adjusted and optimized according to the actual situation on site.

[0126] In a preferred embodiment of the present application, when establishing a driver framework for a target edge hardware device, the following steps are included:

[0127] Set up the basic framework and configuration files of the target edge hardware device;

[0128] Set the driving strategy for the target edge hardware device;

[0129] Construct the docking parameters of the edge object model s for the driving strategy of the target edge hardware device;

[0130] Generate a model interface management strategy for the target edge hardware device based on the docking parameters;

[0131] Build the driver framework of the target edge hardware device based on the basic framework, configuration files, driver strategy and model interface management strategy.

[0132] Specifically, the basic framework is set to master-slave mode. By setting the basic framework, the underlying hardware differences are shielded, hardware resources are abstracted, and a unified operating space is provided for sub-devices.

[0133] Specifically, the configuration file is a description file of the actual hardware peripheral, which contains various attribute information and operation data information of the physical peripheral.

[0134] Specifically, the driver strategy is a specific hardware peripheral driver, which is based on the peripheral driver framework to realize the actual hardware functions. The characteristics of the driver instance are: providing standardized device drivers, and the driver deployment can be completed through configuration; providing driver model abstraction, shielding the interaction between the driver and different system components, making the driver more universal.

[0135] Specifically, the model interface management strategy is a method for connecting the edge object model with the driving strategy, and the connection between the edge object model and the driving strategy is achieved through an agreed interface description file.

[0136] Specifically, when setting the dynamic interpretation and execution process of the edge object model k, it includes:

[0137] Read the configuration file of the target edge hardware device and generate storage instructions for the configuration file;

[0138] Perform lexical analysis on the configuration file to generate multiple lexical units;

[0139] Preprocess all lexical units and build a syntax tree based on the preprocessing results;

[0140] Traverse the syntax tree and convert each syntax node into program instructions. Program instructions include: logical instructions and drive instructions;

[0141] Execute instructions based on the interpretation results.

[0142] Specifically, logical instructions are executed inside the edge device, and driving instructions must call the model interface management to perform actual operations on various peripherals, thereby generating actual physical actions, such as opening and closing switches, reading and writing various industrial buses, network communications, writing files, etc.

[0143] Specifically, by establishing a dynamic interpretation and execution process, the data description file of the edge object model is directly converted into line-by-line running instructions without compiling into binary code, thereby realizing dynamic tuning of the object model interpretation and operation.

[0144] In a preferred embodiment of the present application, when generating the device evaluation value of each edge hardware device, it includes:

[0145] Set the equipment evaluation index sequence J, J = (j1, j2...ji...jr), where ji is the i-th equipment evaluation index;

[0146] Obtain a target edge hardware device and generate a device evaluation value g of the target edge hardware device;

[0147]

[0148] Wherein, di is the reference value of the i-th device evaluation index of the target edge hardware device; βi is the influencing factor of the i-th device evaluation index;

[0149] Generate device evaluation values ​​for each edge hardware device in turn;

[0150] Establish a device evaluation value sequence G, G = (g1, g2...gi...gr), where gi is the device evaluation value of the i-th edge hardware device.

[0151] Specifically, the equipment evaluation indicators include, but are not limited to, the level of edge hardware equipment, running time, executable business categories and quantity, computing power level and other parameters. The larger the equipment evaluation value, the stronger the processing capability of the current edge equipment hardware equipment, and the faster the corresponding edge object model update speed needs to be, so as to achieve self-optimization and elastic expansion effects.

[0152] Specifically, when setting the update time nodes of each edge object model, it includes:

[0153] Obtain the device evaluation value g of the target edge hardware device;

[0154] Generate an update evaluation value h of the target edge hardware device at the current update time node;

[0155] h=e1*Q1*g+e2*Q2*U;

[0156] Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; U is the historical evaluation value of the target edge hardware device at the current update time node;

[0157] According to the update evaluation value h, the update cycle length t of the edge object model k of the target edge hardware device at the current update time node is set;

[0158] Set the next update time node of edge object model k according to the update cycle duration t;

[0159] When the update time node is reached, the dynamic update strategy of the edge object model k is executed;

[0160] Set the update time nodes of each edge object model in sequence.

[0161] Specifically, the more updated content of its edge object model, the higher the corresponding historical evaluation value.

[0162] Specifically, when executing the dynamic update strategy, the network communication function is realized through the edge device peripheral interface (such as UART, IIC, SPI, CAN, USB Modem and other interfaces). The edge hardware device pulls the edge object model iteration data packet from the server through the network, and then sends the edge object model iteration data packet to the CPU through the communication interface with the agreed communication protocol. The CPU is responsible for the analysis, decryption, storage, update and other operations of the edge object model, and finally completes the dynamic update function of the edge object model. Realize offline storage and device binding.

[0163] Specifically, when setting the update cycle duration t, it includes:

[0164] Presetting a first updated evaluation value interval (H1, H2), a second updated evaluation value interval (H2, H3) and a third updated evaluation value interval (H3, H4);

[0165] If the update evaluation value h is within the preset first update evaluation value interval, the update cycle duration t is set to the preset first duration T1, that is, t=T1;

[0166] If the update evaluation value h is within the preset second update evaluation value interval, the update cycle duration t is set to the preset second duration T2, that is, t=T2;

[0167] If the update evaluation value h is in the preset third update evaluation value interval, the update cycle duration t is set to the preset third duration T3, that is, t=T3; and T1>T2>T3.

[0168] Specifically, by dynamically adjusting the update cycle duration, dynamic updating of each edge object model is achieved to ensure the operating efficiency of each edge object model.

[0169] According to the first concept of this application, by binding the physical model with the edge hardware device, the virtual physical model is converted into an actual physical device; the edge hardware device is given different processing capabilities to improve the versatility of the hardware device. The data processing capabilities of the edge hardware device are improved, and different functions are given to the edge device according to different mapping models through edge physical model hardware adaptation. The edge device performs different functions according to the physical model attributes and operation strategies, realizing dynamic adjustment of edge device functions driven by the physical model.

[0170] According to the second concept of the present application, different edge hardware devices can be equipped with multiple object models to achieve elastic expansion and dynamic functional tuning of object models in edge devices and integrate edge object model algorithms to achieve dynamic updating of business algorithms. According to different actual application scenarios, the on-site algorithms can be dynamically changed and tuned.

[0171] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. A method for implementing an edge object model of industrial equipment, characterized in that: include: Establishing an initial material model library; Traverse all edge hardware devices and build edge object models for each edge hardware device in turn; Generate device evaluation values ​​for each edge hardware device, and set the update time nodes for each edge object model based on all device evaluation values; Among them, when traversing all edge hardware devices, including: Establish an edge hardware device sequence A, A = (a1, a2...ai...an), where ai is the i-th edge hardware device; n is the number of edge hardware devices.

2. The method for implementing the industrial equipment edge object model according to claim 1, characterized in that: When building the edge object model of each edge hardware device, include: According to the edge hardware device sequence A, the i-th edge hardware device is sequentially set as the target edge hardware device; Establish an edge object model k of the target edge hardware device; The multi-level data structure of the edge object model s is set according to the business scenario parameters and multi-source heterogeneous parameters of the target edge hardware device; Establish a driver framework for target edge hardware devices; Bind the edge object model k and the target edge hardware device through the driver framework; Set the dynamic interpretation and execution process of the edge object model k; Set the dynamic update strategy of edge object model k; Build edge object models for each edge hardware device in turn; Establish an edge object model sequence K, K = (k1, k2...ki...kn), where ki is the edge object model of the i-th edge hardware device.

3. The method for implementing the edge object model of industrial equipment according to claim 2, characterized in that: When setting the multi-level data structure of the edge object model s, it includes: Build a physical parameter description hierarchy based on the device parameters of the target edge hardware device; Build a business logic hierarchy based on the business data of the target edge hardware device; Generate a heterogeneous interface hierarchy of edge object models; A multi-level data structure is established based on the heterogeneous interface level, business logic level and physical parameter description level.

4. The method for implementing the edge object model of industrial equipment according to claim 3, characterized in that: The construction of the business logic layer includes: Traverse historical business data and establish multiple business categories; Establish a service category sequence P, P = (p1, p2...pi...pm), where pi is the i-th service category; m is the number of service categories; Generate business logic processes for each business category in sequence; Establish a business logic process sequence B, B = (b1, b2...bi...bm), where bi is the business logic process of the i-th business category; Set the calling model of the business logic process; Construct the business logic hierarchy based on the call model and business logic process sequence B.

5. The method for implementing the edge object model of industrial equipment according to claim 4, characterized in that: When setting the calling model of the business logic process, include: Obtain on-site business parameters of the target edge hardware device; Extract characteristic indicators based on on-site business parameters; Generate similarity evaluation values ​​for each business category based on all characteristic indicators; Establish a similarity evaluation value sequence F, F = (f1, f2...fi...fm), where fi is the similarity evaluation value between the on-site business parameter and the i-th business category; Call the business logic process of the business category corresponding to the maximum value fmax in the similar evaluation value sequence F.

6. The method for implementing the edge object model of industrial equipment according to claim 4, characterized in that: When establishing the driver framework for the target edge hardware device, include: Set up the basic framework and configuration files of the target edge hardware device; Set the driving strategy for the target edge hardware device; Construct the docking parameters of the edge object model s for the driving strategy of the target edge hardware device; Generate a model interface management strategy for the target edge hardware device based on the docking parameters; Build the driver framework of the target edge hardware device based on the basic framework, configuration files, driver strategy and model interface management strategy.

7. The method for implementing the edge object model of industrial equipment according to claim 6, characterized in that: When setting the dynamic interpretation execution process of the edge object model k, it includes: Read the configuration file of the target edge hardware device and generate storage instructions for the configuration file; Perform lexical analysis on the configuration file to generate multiple lexical units; Preprocess all lexical units and build a syntax tree based on the preprocessing results; Traversing the syntax tree, converting each syntax node into a program instruction, wherein the program instruction includes: a logic instruction and a driving instruction; Execute instructions based on the interpretation results.

8. The method for implementing the edge object model of industrial equipment according to claim 7, characterized in that: When generating the device evaluation value of each edge hardware device, it includes: Set the equipment evaluation index sequence J, J = (j1, j2...ji...jr), where ji is the i-th equipment evaluation index; Obtain a target edge hardware device and generate a device evaluation value g of the target edge hardware device; Wherein, di is the reference value of the i-th device evaluation index of the target edge hardware device; βi is the influencing factor of the i-th device evaluation index; Generate device evaluation values ​​for each edge hardware device in turn; Establish a device evaluation value sequence G, G = (g1, g2...gi...gr), where gi is the device evaluation value of the i-th edge hardware device.

9. The method for implementing the edge object model of industrial equipment according to claim 8, characterized in that: When setting the update time nodes of each edge object model, include: Obtain the device evaluation value g of the target edge hardware device; Generate an update evaluation value h of the target edge hardware device at the current update time node; h=e1*Q1*g+e2*Q2*U; Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; U is the historical evaluation value of the target edge hardware device at the current update time node; According to the update evaluation value h, the update cycle length t of the edge object model k of the target edge hardware device at the current update time node is set; Set the next update time node of edge object model k according to the update cycle duration t; When the update time node is reached, the dynamic update strategy of the edge object model k is executed; Set the update time nodes of each edge object model in sequence.

10. The method for implementing the edge object model of industrial equipment according to claim 9, characterized in that: When setting the update cycle duration t, it includes: Presetting a first updated evaluation value interval (H1, H2), a second updated evaluation value interval (H2, H3) and a third updated evaluation value interval (H3, H4); If the update evaluation value h is within the preset first update evaluation value interval, the update cycle duration t is set to the preset first duration T1, that is, t=T1; If the update evaluation value h is within the preset second update evaluation value interval, the update cycle duration t is set to the preset second duration T2, that is, t=T2; If the update evaluation value h is in the preset third update evaluation value interval, the update cycle duration t is set to the preset third duration T3, that is, t=T3; and T1>T2>T3.

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