A heterogeneous industrial device resource description method for a cloud-edge collaboration scenario

Abstract

The application relates to a heterogeneous industrial equipment resource description method for a cloud edge collaborative scene and belongs to the technical field of industrial intelligentization.The application aims to solve the problems that various types of heterogeneous industrial equipment are difficult to be described by a general resource model due to different functions, and the sharing, management and configuration of equipment resources are difficult to be realized.The process is as follows: step one, constructing an equipment layer, a protocol layer and a network layer of the heterogeneous industrial equipment resource;step two, constructing a cloud edge double-layer resource description model based on the equipment layer, the protocol layer and the network layer of the heterogeneous industrial equipment resource;step three, constructing a heterogeneous industrial equipment resource ontology instance based on the cloud edge double-layer resource description model; and step four, registering and encapsulating the service of the heterogeneous industrial equipment resource based on the heterogeneous industrial equipment resource ontology instance.

Description

TECHNICAL FIELD

[0001] The application relates to a heterogeneous industrial equipment resource description method for a cloud-edge collaborative scene and belongs to the technical field of industrial intelligentization. BACKGROUND

[0002] Industrial Internet is a new type of infrastructure, application mode and industrial ecology of deep integration of new generation information communication technology and manufacturing industry. Through comprehensive connection of people, machines, objects and systems, a new manufacturing and service system covering the whole industry chain and the whole value chain is built, which provides an implementation approach for the digitalization, networking and intelligentization of industry and even industry. With the development of big data, cloud computing, intelligent manufacturing and other technologies, manufacturing resources under the background of industrial Internet show new characteristics of distribution, heterogeneity and correlation. A large number of industrial terminal devices are interconnected and networked to realize effective collection and analysis of production site data. Under the industrial Internet environment, the automation, digitization and intelligentization of industrial equipment need to be further improved. Therefore, cloud manufacturing technology uses technologies such as Internet of Things and cloud computing to virtualize and encapsulate various manufacturing resources and access the cloud platform to realize centralized management and scheduling configuration of resources and provide product manufacturing life cycle services for production and manufacturing tasks.

[0003] As the core element of intelligent manufacturing, equipment resources realize efficient management and resource sharing of heterogeneous industrial equipment, which is of great significance to improve production efficiency and reduce operating costs. Due to the variety of current heterogeneous industrial equipment and the difference in functions, it is difficult to build a general resource model to uniformly describe various types of equipment resources, which to some extent causes the difficulty of equipment resource sharing. On the other hand, edge equipment, as an industrial intelligent terminal on the edge side under the cloud-edge-end framework, undertakes tasks such as device access and edge computing in the cloud-edge collaborative scene, which brings new challenges to the management and configuration of equipment resources. Therefore, a formal modeling method based on cloud-edge-end integration is needed to provide a convenient and effective solution for the intelligent access and digital management of various types of equipment in various industries. SUMMARY

[0004] The purpose of the present application is to solve the problems that the current heterogeneous industrial equipment is of various types and functions, it is difficult to build a general resource model to uniformly describe various types of equipment resources, and it is difficult to realize the sharing, management and configuration of equipment resources. A heterogeneous industrial equipment resource description method for a cloud-edge collaborative scene is proposed.

[0005] The specific process of a heterogeneous industrial equipment resource description method for a cloud-edge collaborative scene is as follows:

[0006] Step 1, build the device layer, protocol layer and network layer of the heterogeneous industrial equipment resource;

[0007] Step two, based on the device layer, protocol layer and network layer of the heterogeneous industrial equipment resource, a cloud-edge double-layer resource description model is constructed.

[0008] Step three, based on the cloud-edge double-layer resource description model, a heterogeneous industrial equipment resource ontology instance is constructed.

[0009] Step four, based on the heterogeneous industrial equipment resource ontology instance, the registration and service encapsulation of the heterogeneous industrial equipment resource are carried out.

[0010] The beneficial effects of the application are:

[0011] The application provides a heterogeneous industrial equipment resource description method for cloud-edge collaborative scenarios for the virtualization of four kinds of device resources, i.e., sensing devices, execution devices, control devices and monitoring devices, under the background of industrial internet, a cloud-edge double-layer resource description model is established to realize the optimized configuration of device resources in the cloud-edge network layer, and the problems of the existing resource description methods, i.e., not comprehensive and not universal, are solved, which is beneficial to realize the intelligent management and control of industrial equipment.

[0012] The heterogeneous industrial equipment resource description method for cloud-edge collaborative scenarios is based on the cloud-edge-end collaborative application framework, studies the formal description method of heterogeneous industrial equipment resources, abstracts various physical devices as virtual network resources, considers the characteristics of various types of device resources and different functions in the field of industrial internet, guarantees the uniformity and integrity of device resource description, clearly expresses the complex relationship and concept between different device resources through clear semantics, comprehensively and accurately displays the characteristics of device resources, and has high flexibility and reconfigurability to facilitate the updating, maintenance and expansion of heterogeneous industrial equipment network. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 It is a heterogeneous industrial equipment resource description model diagram;

[0014] Figure 2 It is a three-layer architecture diagram of the device layer, the protocol layer and the network layer of the heterogeneous industrial equipment resource;

[0015] Figure 3 It is a part of the heterogeneous industrial equipment resource ontology instance diagram constructed in the protégé tool;

[0016] Figure 4 It is a device resource service cloud-edge collaborative application architecture diagram. DETAILED DESCRIPTION

[0017] Specific implementation one: the specific process of the heterogeneous industrial equipment resource description method for cloud-edge collaborative scenarios in this embodiment is:

[0018] Step one, constructing the device layer, protocol layer and network layer of the heterogeneous industrial equipment resource;

[0019] Step two, based on the device layer, protocol layer, network layer of heterogeneous industrial equipment resources, build a cloud-edge double-layer resource description model;

[0020] Step three, based on the cloud-edge double-layer resource description model, build a heterogeneous industrial equipment resource ontology instance;

[0021] Step four, based on the heterogeneous industrial equipment resource ontology instance, register and service encapsulation of heterogeneous industrial equipment resources.

[0022] Device resources refer to various hardware devices used in industrial environments. Device resource description refers to the detailed description and definition of the classification, attributes, and functions of devices. Through standardized device resource description methods, the form heterogeneity of heterogeneous industrial equipment resources is eliminated, enabling machines to recognize, classify, and manage these devices, thereby achieving the sharing, management, and configuration of device resources.

[0023] Specific implementation method two: The difference between this implementation method and the specific implementation method one is that in the step one, the device layer, protocol layer, and network layer of the heterogeneous industrial equipment are constructed.

[0024] The specific process is as follows:

[0025] The device layer includes four general types of devices: sensing devices, execution devices, control devices, and monitoring devices.

[0026] Among them,

[0027] Sensing devices are used to collect signal data in industrial production processes, such as temperature sensors, pressure sensors, voltage and current sensors, vibration sensors, etc.

[0028] Execution devices are used to perform specific production and manufacturing tasks, such as processing equipment, power equipment, assembly equipment, detection equipment, and logistics equipment.

[0029] Control devices are used to connect sensing devices and execution devices and control them to achieve data collection and communication transmission in the production process. Control devices include programmable logic controllers (PLC), distributed control systems (DCS), supervisory control and data acquisition systems (SCADA), etc.

[0030] Monitoring devices are used to monitor production processes and device status. Monitoring devices include cameras, displays, and industrial cameras.

[0031] The protocol layer includes industrial communication protocols and network transmission protocols.

[0032] Industrial communication protocols and network transmission protocols both include protocol name and protocol type information.

[0033] Among them, the industrial communication protocol defines how the device (sensing device, execution device, control device, monitoring device) accesses the network, such as serial communication, industrial Ethernet and wireless communication, etc.; the network transmission protocol defines the transmission mode of the device (sensing device, execution device, control device, monitoring device) in the network, such as TCP / IP, UDP, MQTT, HTTP, CoAP, etc.

[0034] The network layer includes a cloud platform and an edge device;

[0035] The edge device refers to an edge gateway as the core of edge computing device. The edge device supports the access of sensing devices, execution devices, control devices and monitoring devices in the device layer through the protocol layer (industrial communication protocol of the protocol layer), and the edge device is connected to the cloud platform and the industrial digital system through the protocol layer (network transmission protocol of the protocol layer).

[0036] The other steps and parameters are the same as those in the first embodiment.

[0037] The third embodiment is different from the first or second embodiment in that the device layer, the protocol layer and the network layer based on the heterogeneous industrial device resources in the step two are used to build a cloud-edge double-layer resource description model.

[0038] The specific process is as follows:

[0039] According to the characteristics (functionality) of different types of device resources, an ontology description concept set containing class (device type), relationship (device relationship), object property (expressing the relationship between classes, such as control relationship, connection relationship, etc.), and data property (describing the data properties of resource individuals) is constructed, and a heterogeneous industrial device resource description model is established based on the ontology description concept set;

[0040] The resource description model uses a two-dimensional triple representation method of "resource-relationship-constraint" and "resource-property-value";

[0041] In combination with the specific use scene of various devices, the relationship and constraint of different types of devices are defined to realize the mapping of the physical connection of device resources to the model association, and the attribute and value of different types of devices are defined to realize the mapping of the physical entity of device resources to the information model;

[0042] The resource description model uses the seven-step method proposed by Gruber for modeling, and the steps include: defining the field and target, considering ontology reuse, listing concept terms, defining hierarchical relationships, defining attributes, creating instances, and generating models.

[0043] Step two, constructing a device resource type layer;

[0044] Step two, based on the built device resource type layer, build device resource attribute layer;

[0045] Step three, based on the built device resource attribute layer, build device resource instance layer; as Figure 3 shown;

[0046] Step four, based on the built device resource instance layer, build device resource encapsulation layer.

[0047] Other steps and parameters are the same as one or two of the specific embodiments.

[0048] Specific embodiment four: this embodiment is different from one to three of the specific embodiments in that: in the step two, build the device resource type layer;

[0049] The specific process is:

[0050] The device layer includes four types of devices: sensing devices, execution devices, control devices, and monitoring devices;

[0051] The characteristics of the sensing device are: sensing device type, measurement range, measurement frequency, and data format;

[0052] The characteristics of the execution device are: execution device type, functional characteristics, input and output, and control method;

[0053] The characteristics of the control device are: control device type, control method, communication interface, and supported protocol;

[0054] The characteristics of the monitoring device are: monitoring device type, data storage, data processing, and data transmission;

[0055] The characteristics of the sensing device are the sensing device resource type layer;

[0056] The characteristics of the execution device are the execution device resource type layer;

[0057] The characteristics of the control device are the control device resource type layer;

[0058] The characteristics of the monitoring device are the monitoring device resource type layer.

[0059] Other steps and parameters are the same as one to three of the specific embodiments.

[0060] Specific embodiment five: this embodiment is different from one to four of the specific embodiments in that: in the step two, based on the built device resource type layer, build the device resource attribute layer (device resource attributes include sensing device resource attributes, execution device resource attributes, control device resource attributes, and monitoring device resource attributes);

[0061] The specific process is:

[0062] The device resource attribute includes basic information, function information, control information and state information;

[0063] The device resource attribute layer is as follows:

[0064] The basic information refers to core attributes capable of uniquely identifying and describing the device, and the basic information includes device ID, device type, device brand, device model, device name, device cost, device management, storage location, maintenance record, etc.

[0065] The function information refers to core attributes capable of expressing device functions and operation characteristics, and the function information includes device configuration, device operation, device compatibility, function description, function parameters (including electrical parameters, mechanical parameters, physical parameters, etc.), function extension, etc.

[0066] The control information refers to core attributes capable of expressing device access and control methods, and the control information includes device interface, device protocol, device linkage, data format, control command, access permission, etc.

[0067] The state information refers to core attributes capable of expressing device running state characteristics, and the state information includes working state, working load, performance index, device energy consumption, device life, device maintenance, etc.

[0068] The basic information and the function information constitute attribute characteristics of the cloud model;

[0069] The control information and the state information constitute attribute characteristics of the edge model;

[0070] The cloud model and the edge model are connected through a device resource unique identifier;

[0071] The cloud model is deployed on a cloud platform, and the edge model is deployed on an edge device.

[0072] Different models adopt different resource encapsulation modes.

[0073] The other steps and parameters are the same as one of the first to fourth embodiments.

[0074] The sixth embodiment is different from one of the first to fifth embodiments in that: in the steps two and three, a device resource instance layer is constructed based on the constructed device resource attribute layer; as shown in Figure 3 ;

[0075] The specific process is as follows:

[0076] Obtaining information of the industrial equipment (such as equipment ID, equipment energy consumption), dividing the obtained industrial equipment information according to the equipment resource attribute in step two, obtaining the specific value of the attribute of the basic information, the functional information, the control information and the state information in the equipment resource attribute layer;

[0077] For example, the specific value of the attribute of the equipment ID, the equipment type, the equipment brand, the equipment model, the equipment name, the equipment location, the equipment cost, the equipment management and the like in the basic information;

[0078] Inputting the attribute of the basic information, the functional information, the control information and the state information in the equipment resource attribute layer and the specific value of the attribute into the ontology modeling tool protégé, outputting the OWL document by the ontology modeling tool protégé, storing the equipment resource description instance in the OWL document (the OWL document stores the attribute of the basic information, the functional information, the control information and the state information in the multiple resource attribute layers and the specific value of the attribute), and importing the OWL document into the MySQL database through the Jena API to store the equipment resource description instance data.

[0079] The ontology modeling language OWL is used to express the resource formal description model according to the RDF description framework regulated by the W3C, and has perfect ontology reasoning function.

[0080] The other steps and parameters are the same as one of the first to fifth embodiments.

[0081] The seventh embodiment is different from one of the first to sixth embodiments in that the step two four is used to construct the equipment resource encapsulation layer based on the constructed equipment resource instance layer.

[0082] The specific process is as follows:

[0083] Step two four one is used to read the equipment resource description instance data stored in the MySQL database, register the resource in the network layer cloud platform, and integrate the functions such as information query, resource management and data transmission;

[0084] The specific process is as follows:

[0085] The equipment name, the equipment type, the equipment model, the storage location, the maintenance record and the like are obtained from the basic information in the equipment resource attribute layer;

[0086] The equipment interface, the data format and the like are obtained from the control information in the equipment resource attribute layer;

[0087] The protocol name and the protocol type are obtained from the protocol layer.

[0088] The acquired device name, device type, device model, storage location, maintenance record, device interface, data format, protocol name, and protocol type information are merged, and based on the merged information, device resource registration in the cloud platform is completed, and information query, resource management, data transmission, and other functions are integrated on the cloud platform;

[0089] Step two four two, based on the device resource description instance, complete the cloud model and edge model device resource encapsulation;

[0090] The cloud model and the edge model adopt different device resource encapsulation strategies. The device resource encapsulation of the cloud model focuses on resource management, state maintenance and capability evaluation, while the device resource encapsulation of the edge model focuses on device access, data processing and data transmission.

[0091] The cloud model is deployed on the cloud platform, stores resource information in the cloud database, supports information integration of multiple types of devices, considers cross-platform sharing and collaboration of information, supports rich ontology reasoning mechanisms to facilitate device resource management and sharing; the edge model is deployed on the edge device, stores resource information in the edge database, focuses on the access and control of edge devices, and adopts a lightweight description language and database to facilitate data transmission and synchronization with the cloud.

[0092] The specific process is as follows:

[0093] The device resource description instances in the cloud model and the edge model are encapsulated as data interfaces of the cloud platform and the edge device respectively, so that the information in the device resource description instance is recognized and operated by the API of the cloud platform and the edge device;

[0094] By calling the data interface, the cloud platform and the edge device can manage the device resources according to the corresponding cloud model and edge model;

[0095] Among them, the cloud platform deploys device information query service based on field retrieval method to realize cloud management of device resources;

[0096] The edge device deploys device access management service based on knowledge reasoning method to realize edge access of device resources.

[0097] The other steps and parameters are the same as one of the first to sixth embodiments.

[0098] Embodiment eight: different from one of the first to seventh embodiments, the step three is based on the cloud-edge double-layer resource description model to construct the heterogeneous industrial device resource ontology instance;

[0099] The specific process is as follows:

[0100] Step three one, using the ontology reasoning engine Pallet plug-in to perform consistency check on the cloud-edge double-layer resource description model built in step two;

[0101] If there is no semantic rule conflict in the cloud-edge double-layer resource description model, execute step three two;

[0102] If there is semantic rule conflict in the cloud-edge double-layer resource description model, resolve the conflict by reviewing and modifying the semantic rules or setting priority, repeat step three one until there is no semantic rule conflict in the cloud-edge double-layer resource description model, and then execute step three two;

[0103] Step three two, using the ontology visualization tool Ontograf plug-in to display the cloud-edge double-layer resource description model.

[0104] The other steps and parameters are the same as one of the first to seventh embodiments.

[0105] The ninth embodiment is different from one of the first to eighth embodiments in that: in the step four, based on the heterogeneous industrial equipment resource ontology instance, the heterogeneous industrial equipment resource registration and service encapsulation are performed;

[0106] The specific process is as follows:

[0107] Step four one, according to the different types of industrial equipment and equipment resource attributes (basic information, function information, control information, state information), the resource registration of the heterogeneous industrial equipment of the manufacturing site access network is performed in the cloud-edge collaborative scene, and the resource registration information is represented as a set {ID, Address, RDM, RInf, RSI};

[0108] ID represents the resource registration mark number, which is used to uniquely identify the registered industrial equipment on the resource service platform, so as to locate and index the resource;

[0109] Address is the address where the resource is stored, which is stored in the form of a string;

[0110] RDM is the resource description template, which determines the equipment type and description method (i.e., whether to build in the cloud model or the edge model);

[0111] RInf is the resource description information, i.e., the equipment resource description information stored in the database (i.e., the information obtained from the equipment resource description model and imported into the equipment resource information table in the database, based on which the resource description model is built);

[0112] RSI is the resource service interface, which locates the protocol used for equipment communication transmission and accesses the resource service through the data interface;

[0113] Step four two, the increase, delete, query, modify in SPARQL and the transmission function between the cloud platform and the edge device based on MQTT protocol are integrated into resource application tools through JavaWeb technology, and the service encapsulation of heterogeneous industrial device resources is realized.

[0114] The information data in the resource ontology instance is obtained by adding, deleting, querying and modifying the OWL document stored in step two through SPARQL (SPARQL Protocol and RDF Query Language, a query language);

[0115] The information data in the resource ontology instance is transmitted between the cloud platform and the edge device through the MQTT protocol, and the device resource attribute (including basic information, function information, control information and state information) is updated.

[0116] The other steps and parameters are the same as one of the first to eighth embodiments.

[0117] Embodiment 1:

[0118] Taking the application scene of milling machine state monitoring and fault diagnosis based on cloud edge collaboration as an example, the implementation process of the heterogeneous device resource description method for this scene is as follows:

[0119] Step one, clarify the application scene, and build the device layer, protocol layer and network layer of the heterogeneous industrial device resources in the milling machine state monitoring and fault diagnosis application scene;

[0120] The specific process is as follows:

[0121] In this scene, the device layer includes: sensing devices such as vibration sensors, acoustic emission sensors, voltage sensors and current sensors, execution devices such as milling machines (mainly spindle and feed mechanism), control devices such as milling machine numerical control systems (CNC) and programmable logic controllers (PLC), and monitoring devices such as field monitoring cameras and milling processing human-machine interfaces (HMI).

[0122] In this scenario, the sensor collects the data generated by the milling machine during processing. The sensor collects signals generated by the milling machine during processing, including acceleration signals, acoustic emission signals, voltage, current and power. The signals are transmitted through the Modbus communication protocol, received and parsed by the communication module of the PLC as voltage signals. The processing process is recorded by the monitoring camera and controlled by the numerical control system. The collected signals are preprocessed on the server of the edge device, and TCP / IP connection is established between the edge device and the cloud platform through the MQTT protocol for data and information exchange. The cloud platform monitors the state of the milling machine and analyzes the fault based on these data. The above process involves protocols such as Modbus and MQTT, and cloud platforms and edge devices at the network layer.

[0123] Step two, determine the characteristics of the equipment, and build a cloud-edge double-layer resource description model for the milling machine state monitoring and fault diagnosis application scenario;

[0124] The specific process is as follows:

[0125] Obtain the industrial equipment information document, and divide the main industrial equipment into sensing equipment, execution equipment, control equipment and monitoring equipment. Establish the relationship attributes between different types of equipment, as shown in Table 1. Classify the industrial equipment information, sort, filter and classify the industrial equipment information based on the device resource attribute layer set, and add attribute labels to the industrial equipment information according to the cloud-edge resource information classification method.

[0126] Table 1 General equipment object attribute table

[0127]

[0128] Step three, build a resource ontology instance for the industrial equipment resources in the milling machine state monitoring and fault diagnosis application scenario;

[0129] The specific process is as follows:

[0130] Combine the resource description model with the industrial equipment information through protege software, add corresponding values and constraints to the attribute labels, and thus establish the ontology instance of all sensing equipment, execution equipment, control equipment and monitoring equipment in this scenario. When constructing the formal description ontology model of the device resources, ontology reasoning is needed to automatically deduce new knowledge or update the existing knowledge base. For example, the following several ontology reasoning methods can be applied:

[0131] “Classification reasoning”: according to the attributes and functions of the equipment, determine its belonging to the equipment category. For example, a device that can collect vibration signals can be classified as “sensing equipment”;

[0132] "Attribute inference": based on the classification and association of devices, the attributes that the device may have are deduced.For example, a device can be controlled by another device, so the device may have a "control interface" attribute;

[0133] "Relationship inference": based on the category and attribute of the device, the relationship that may exist between the devices is deduced.For example, an edge device has Ethernet, serial port and other interfaces, and another device can communicate through Ethernet and 4G network, so the two devices may have a "connection relationship";

[0134] The device instance after the ontology inference is exported as an OWL description document, based on the ontology instance and structured device information data stored in the OWL document, the Neo4j graph database is used for visual display, and the Jena API is used for import into the MySQL database.

[0135] Step four, build an industrial device resource service platform, based on Figure 4 The device resource registration and service encapsulation in the application scenario of milling machine tool state monitoring and fault diagnosis are completed.

[0136] The specific process is as follows:

[0137] The device resource information is called from the MySQL database, and the device resources are classified according to the cloud model and the edge model according to the attribute tags of the device resource information, wherein the basic information and functional information of the device resources of the cloud model are integrated for registering the corresponding device resources on the industrial device resource service platform, the control information and state information of the device resources of the edge model are integrated for deploying edge intelligent services on the edge device, and the industrial device resource service platform can establish a TCP / IP connection with the edge device through the MQTT protocol for data transmission.For example, on the industrial device resource service platform, the milling machine tool device resources that can be used for production and processing are registered, and the model, function, configuration and parameter information of the milling machine tool are obtained through an ontology-based query statement;On the edge device, the interface information, control command, energy consumption information and maintenance information of the milling machine tool are encapsulated as an information library interface, which can be used for quick retrieval of device resource control information and update and maintenance of state information.

[0138] The present application also has other various embodiments, and those skilled in the art can make various corresponding changes and modifications according to the present application without departing from the spirit and essence of the present application, but these corresponding changes and modifications should all belong to the protection scope of the claims attached to the present application.

Claims

1. A method for describing heterogeneous industrial equipment resources in cloud-edge collaborative scenarios, characterized in that: The specific process of the method is as follows: Step 1: Construct the device layer, protocol layer, and network layer of heterogeneous industrial equipment resources; Step 2: Based on the device layer, protocol layer, and network layer of heterogeneous industrial equipment resources, construct a cloud-edge dual-layer resource description model; Step 3: Based on the cloud-edge dual-layer resource description model, construct heterogeneous industrial equipment resource ontology instances; Step 4: Based on the heterogeneous industrial equipment resource ontology instance, perform heterogeneous industrial equipment resource registration and service encapsulation; Step one involves constructing the device layer, protocol layer, and network layer of heterogeneous industrial equipment; the specific process is as follows: The equipment layer includes four types of equipment: sensing devices, execution devices, control devices, and monitoring devices. in, Sensing devices are used to collect signal data during industrial production processes; The equipment is used to perform specific production and manufacturing tasks; Control equipment is used to connect and control sensing and execution equipment, and to realize data acquisition and communication transmission in the production process. Control equipment includes programmable logic controllers, distributed control systems, and monitoring and data acquisition systems. Monitoring equipment is used to monitor the production process and equipment status. Monitoring equipment includes cameras, monitors, and industrial cameras. The protocol layer includes industrial communication protocols and network transmission protocols; Both industrial communication protocols and network transmission protocols include protocol name and protocol type information; Among them, the industrial communication protocol defines how devices access the network; the network transmission protocol defines how devices transmit data within the network. The network layer includes cloud platforms and edge devices; Edge devices refer to edge computing devices with edge gateways as their core. Edge devices support the access of sensing devices, execution devices, control devices, and monitoring devices at the device layer through the protocol layer, and connect to cloud platforms and factory digital systems through the protocol layer. In step two, a cloud-edge dual-layer resource description model is constructed based on the device layer, protocol layer, and network layer of heterogeneous industrial equipment resources; the specific process is as follows: Step 2: Construct the device resource type layer; Step 22: Based on the constructed device resource type layer, construct the device resource attribute layer; Steps 2 and 3: Based on the constructed device resource attribute layer, construct the device resource instance layer; Step 24: Based on the constructed device resource instance layer, construct the device resource encapsulation layer; Step 2.1 involves constructing the device resource type layer; the specific process is as follows: The equipment layer includes four types of equipment: sensing devices, execution devices, control devices, and monitoring devices. The characteristics of a sensing device are: sensing device type, measurement range, measurement frequency, and data format; The characteristics of an actuator are: actuator type, functional features, inputs and outputs, and control method; The characteristics of control equipment include: control equipment type, control method, communication interface, and supported protocols; The characteristics of surveillance equipment include: surveillance equipment type, data storage, data processing, and data transmission; The sensor device is characterized by a sensor device resource type layer; The characteristics of the execution device are defined as the execution device resource type layer; The control equipment is characterized by a control equipment resource type layer; The monitoring equipment is characterized by a monitoring equipment resource type layer; In step two, a device resource attribute layer is constructed based on the constructed device resource type layer; the specific process is as follows: Equipment resource attributes include basic information, functional information, control information, and status information; The device resource attribute layer is as follows: Basic information includes: equipment ID, equipment type, equipment brand, equipment model, equipment name, equipment cost, equipment management, storage location, and maintenance records; Functional information includes: device configuration, device operation, device compatibility, function description, function parameters, and function extensions; Control information includes: device interface, device protocol, device linkage, data format, control commands, and access permissions; Status information includes: operating status, workload, performance indicators, equipment energy consumption, equipment lifespan, and equipment maintenance; The basic information and functional information constitute the attribute features of the cloud model; Control information and state information constitute the attribute features of the edge model; The cloud model is deployed on the cloud platform, while the edge model is deployed on edge devices; In steps two and three, a device resource instance layer is constructed based on the constructed device resource attribute layer; the specific process is as follows: Obtain information about industrial equipment, and divide the obtained industrial equipment information according to the equipment resource attributes in step 22 to obtain the specific values ​​of the attributes of basic information, functional information, control information and status information in the equipment resource attribute layer; Input the attributes and specific values ​​of basic information, functional information, control information and status information in the device resource attribute layer into the ontology modeling tool protégé. The ontology modeling tool protégé outputs an OWL document. The OWL document stores device resource description instances. Import the OWL document into a MySQL database through the Jena API to store the device resource description instance data. In step two of the above steps, a device resource encapsulation layer is constructed based on the constructed device resource instance layer; the specific process is as follows: Step 241: Read the device resource description instance data stored in the MySQL database, register the resource in the cloud platform at the network layer, and integrate information query, resource management, and data transmission functions; the specific process is as follows: Obtain the following information from the basic information in the equipment resource attribute layer: equipment name, equipment type, equipment model, storage location, and maintenance records; Obtain the following from the control information in the device resource attribute layer: device interface and data format; Retrieve from the protocol layer: Protocol name, Protocol type; The acquired information, including device name, device type, device model, storage location, maintenance records, device interface, data format, protocol name, and protocol type, is merged. Based on the merged information, the device resource registration in the cloud platform is completed, and information query, resource management, and data transmission functions are integrated into the cloud platform. Step 242: Based on the device resource description instance, complete the encapsulation of device resources in the cloud model and edge model; the specific process is as follows: The device resource description instances in the cloud model and edge model are encapsulated as data interfaces for the cloud platform and edge devices, respectively, so that the information in the device resource description instances can be recognized and manipulated by the APIs of the cloud platform and edge devices. By calling data interfaces, the cloud platform and edge devices can manage device resources according to the corresponding cloud model and edge model; Among them, the cloud platform deploys equipment information query services based on field retrieval methods to achieve cloud management of equipment resources; Edge devices deploy device access management services based on knowledge reasoning methods to achieve edge access to device resources.

2. The method for describing heterogeneous industrial equipment resources in a cloud-edge collaborative scenario according to claim 1, characterized in that: In step three, a heterogeneous industrial equipment resource ontology instance is constructed based on the cloud-edge dual-layer resource description model; the specific process is as follows: Step 3:

1. Use the Pallet plugin of the ontology reasoning engine to perform a consistency check on the cloud-edge two-layer resource description model constructed in Step 2; If there are no semantic rule conflicts in the cloud-edge two-layer resource description model, proceed to step three-two; If there are semantic rule conflicts in the cloud-edge dual-layer resource description model, the conflicts are resolved by reviewing, modifying the semantic rules, or setting priorities. Step 31 is repeated until there are no semantic rule conflicts in the cloud-edge dual-layer resource description model, and then step 32 is executed. Step 3.2: Use the Ontograf plugin, an ontology visualization tool, to display the cloud-edge two-layer resource description model.

3. The method for describing heterogeneous industrial equipment resources in a cloud-edge collaborative scenario according to claim 2, characterized in that: In step four, heterogeneous industrial equipment resource registration and service encapsulation are performed based on heterogeneous industrial equipment resource ontology instances; the specific process is as follows: Step 41: Based on the different types of industrial equipment and their resource attributes, register the resources of the heterogeneous industrial equipment connected to the network at the manufacturing site. The resource registration information is represented as a set {ID, Address, RDM, RInf, RSI}. The ID represents the resource registration identifier, which is used to uniquely identify industrial equipment registered on the resource service platform, thereby locating and indexing resources; Address is the address where the resource is stored, and it is stored as a string. RDM is a resource description template that determines the device type and description method. RInf contains resource description information, which is the device resource description information stored in the database; RSI stands for Resource Service Interface, which identifies the protocol used for device communication and accesses resource services through the data interface. Step 42: Integrate the add, delete, query, modify functions in SPARQL and the transmission functions between the cloud platform and edge devices based on the MQTT protocol into a resource application tool using Java Web technology to realize the service encapsulation of heterogeneous industrial equipment resources.

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