CN116055525A - Data acquisition system based on edge calculation - Google Patents
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Abstract
The application is applicable to the technical field of data acquisition and provides a data acquisition system based on edge calculation. The system comprises a PLC (programmable logic controller) connected with and controlling industrial equipment, an edge gateway connected with the industrial equipment or the PLC, a cloud platform connected with the edge gateway and a client interacted with the cloud platform, wherein the cloud platform is used for generating a data acquisition task and transmitting the generated data acquisition task to the edge gateway; the edge gateway is used for collecting data through industrial equipment or PLC connected with the edge gateway according to the received data collection task, preprocessing the collected data and forwarding the preprocessed data to the cloud platform. In the data acquisition system based on edge calculation, the cloud platform centrally manages the edge gateway, so that dynamic issuing of data acquisition tasks is realized, the workload of data acquisition setting on equipment is reduced, and the acquisition efficiency of equipment data is improved.
Description
Technical Field
The application belongs to the technical field of data acquisition, and particularly relates to a data acquisition system based on edge calculation.
Background
Along with the continuous deepening of the integration degree of the new generation information technology and the fields of enterprise production operation and the like, informatization and digitalization become an important driving force for exciting ideation innovation, business innovation and management innovation of enterprises gradually, and the high-speed development of the Internet of things, big data, cloud services and artificial intelligence technology further promotes the conversion of equipment management operation and maintenance from traditional artificial operation and maintenance to intelligent operation and maintenance.
In an industrial system, the operation of the front end is realized by acquiring industrial equipment data through the edge gateway, so that the working pressure of a background can be greatly reduced, but because equipment forming the industrial system is distributed in different areas and has huge quantity, a plurality of edge gateways are required for equipment data acquisition, and the edge gateway in the traditional industrial system cannot be effectively managed, so that the industrial system cannot be effectively supervised; and when equipment types in the industrial system are more, the workload of data acquisition setting on equipment is larger, so that the acquisition efficiency of equipment data is low, and the use requirement of a user is difficult to meet.
Disclosure of Invention
The embodiment of the application provides a data acquisition system based on edge calculation, which reduces the workload of data acquisition setting on equipment and improves the acquisition efficiency of the equipment data.
In a first aspect, the present application provides a data acquisition system based on edge computing, the system comprising a programmable logic controller PLC connected to and controlling industrial equipment, an edge gateway connected to the industrial equipment or PLC, a cloud platform connected to the edge gateway, and a client interacting with the cloud platform; the cloud platform is used for generating a data acquisition task and issuing the data acquisition task to the edge gateway; and the edge gateway is used for carrying out data acquisition through the industrial equipment or the PLC according to the data acquisition task, preprocessing the acquired data and forwarding the preprocessed data to the cloud platform.
In one possible implementation manner, the cloud platform includes an application layer, a service layer, a data layer and a display layer, where the application layer is used to configure the data acquisition task, the service layer is used to provide technical service support for the cloud platform, the data layer is used to store the data forwarded by the edge gateway, and the display layer is used to display the data forwarded by the edge gateway.
In one possible implementation manner, the application layer includes device management, the device management provides device object model management, the device object model management is used for adding a device object model, and a data acquisition table of the device object model is configured based on data acquisition requirements of a device, the data acquisition table includes device object model identification, an acquisition mode, acquisition variables, variable descriptions, data types, acquisition frequencies and data units, the device object model is a three-dimensional model uploaded according to the type of the device, and the data acquisition task includes one or more data acquisition tables.
In one possible implementation manner, the equipment object model management is further used for setting an inter-frequency acquisition rule on the equipment object model, the inter-frequency acquisition rule includes an equipment object model identifier, one or more acquisition variables of the equipment object model corresponding to the equipment object model identifier, and judgment conditions corresponding to the one or more acquisition variables, and the data acquisition task includes the inter-frequency acquisition rule.
In one possible implementation manner, the edge gateway is specifically configured to: when the conditions of the different-frequency acquisition rules in the data acquisition task are met, the edge gateway automatically starts a high-frequency data acquisition function, records acquired data and forwards the acquired data to the cloud platform; and when the condition of the different-frequency acquisition rule in the data acquisition task is not met, the edge gateway automatically closes the high-frequency data acquisition function.
In one possible implementation manner, the equipment object model management is further used for setting alarm rules for the equipment object model, the alarm rules comprise equipment object model identifications, alarm generation conditions and alarm recovery conditions of the equipment object model corresponding to the equipment object model identifications, and the acquisition task table comprises the alarm rules.
In one possible implementation manner, the edge gateway is specifically configured to: when the alarm generation condition of the alarm rule in the data acquisition task is met, the edge gateway generates alarm information and sends the alarm information to the cloud platform; and when the alarm recovery condition of the alarm rule in the data acquisition task is met, the edge gateway generates alarm recovery information and sends the alarm recovery information to the cloud platform.
In one possible implementation, the device management is further configured to manage PLC parameter information, where the PLC parameter information includes a PLC name, a communication protocol, a device address, a port number, a maximum connection number, a timeout period, a rack number, a slot number, a data block, a register, and a start address.
In one possible implementation, the device management further provides gateway management for automatically obtaining user-set edge gateway numbers, edge gateway field network protocol IP, and point location restriction information.
In one possible implementation manner, the cloud platform is specifically configured to: and generating the data acquisition task according to the PLC parameter information and the point position limiting information of the edge gateway.
Compared with the prior art, the embodiment of the application has the beneficial effects that:
1. the cloud platform centrally manages the edge gateway, the data acquisition task is dynamically issued, the system can intelligently generate a plurality of edge gateway acquisition task tables according to conditions such as on-site edge side PLC communication time delay, network stability, edge gateway acquisition point position limitation and the like, and can automatically issue the data acquisition task tables to the edge gateway, a user does not need to perform complex and complicated signal acquisition setting on site, the edge gateway is replaced under abnormal conditions only by issuing tasks again, the stability of the acquisition system can be greatly improved, the data acquisition effect is ensured, and the data acquisition efficiency is improved.
2. The system supports the different-frequency acquisition of equipment, a user can set a different-frequency acquisition rule of an equipment object model on a cloud platform, the system automatically transmits the different-frequency acquisition rule to an edge gateway, the edge gateway automatically starts automatic detection, when equipment signal conditions set by the system are met, the high-frequency acquisition is automatically started, the equipment is ensured to acquire key data fluctuation of the equipment after abnormality and failure occur, the recovery of the field equipment failure and the subsequent data information acquisition of the equipment after alarm are ensured, and the equipment failure and the equipment key information analysis capability after alarm are perfected. The inter-frequency acquisition function automatically ends after the inter-frequency acquisition time or the setting condition is set, so that the performance cost of the edge gateway is reduced.
3. The edge gateway combines and sends the acquired equipment data, and for single sensor signal acquisition, an optimized data structure is adopted for transmission, so that the number of network transmission packets can be effectively reduced, the network flow consumption is reduced, the network bandwidth utilization rate is improved, the acquired data are dynamically stored and compressed when the external network transmission is abnormal, automatic reissue is performed after the gateway recovers external connection, the internal storage space of the gateway is optimized, and the data acquisition stability is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic architecture diagram of an edge-computing-based data acquisition system according to an embodiment of the present application;
fig. 2 is a schematic architecture diagram of a cloud platform according to an embodiment of the present application;
FIG. 3 is a schematic diagram illustrating an operation of a system administrator in a system management module according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
Edge computing is an open platform integrating network, computing, storage, and application core capabilities on the side near the object or data source, providing near-end services. The application program is initiated at the edge side, and faster network service response is generated, so that the basic requirements of the industry in the aspects of real-time service, application intelligence, security, privacy protection and the like are met. Edge computation is between a physical entity and an industrial connection, or at the top of a physical entity. The cloud computing can still access the historical data of the edge computing.
Edge computing is a distributed computing model that brings computer data storage closer to the desired location. The computation is performed primarily or entirely on the distributed device nodes. Edge computing will facilitate applications, data, and computing power (services) closer to the user than to the centralized point. The goal of edge computing is an application or general function that requires an action source that is closer to the interaction of distributed system technology with the physical world. Unlike cloud computing, edge computing refers to decentralized data processing at the edge of a network. Edge application services reduce the amount of data that must be moved, the consequent traffic, and the distance that the data must be transmitted. This provides lower delay and reduces transmission costs.
At present, the traditional data acquisition system based on edge calculation is only developed for single products in batches, and under the scene that a large amount of equipment of a large-scale industrial system is highly concentrated, the data acquisition setting is complicated, and multiple equipment batch acquisition information setting is required to be carried out on each site, so that the workload of acquisition setting is very large under the condition of multiple equipment types and numbers.
In addition, the traditional data acquisition system is single in acquisition mode, and because of different conditions of each device in a factory, different frequencies are needed to be adopted for data acquisition aiming at the working conditions of the devices, and particularly after the devices are abnormal and have faults, the traditional data acquisition system cannot acquire and restore on-site key data after the faults of the devices by adopting standard acquisition frequencies, so that the abnormal and damaged conditions of the devices cannot be effectively analyzed, and only limited data analysis can be carried out. Due to uncertainty of the field network environment, the field acquisition network is prone to accidental faults, delay fluctuation and the like are prone to occurrence in equipment acquisition network connection, efficient and stable acquisition and uploading of equipment data in an industrial system cannot be achieved, and use requirements of customers are difficult to meet.
In order to solve the technical problems that the data acquisition setting workload is large, the data acquisition efficiency is low, the high-speed acquisition of key data can not be realized when equipment fails in the traditional data acquisition system, the application provides a data acquisition system based on edge calculation, the field equipment is centrally managed through an equipment object model, the functions of dynamic issuing of acquisition tasks, real-time monitoring of gateway states, different-frequency acquisition of equipment data and the like are increased, the stability of data acquisition is effectively improved, the data acquisition effect is ensured, the data acquisition efficiency is improved, the key data fluctuation of the equipment is ensured after abnormality and failure occur, and the equipment key information analysis capability after equipment failure and alarm is perfected.
For easy understanding, the technical solutions of the present application will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic architecture diagram of an edge computing-based data acquisition system according to an embodiment of the present application, referring to fig. 1, the data acquisition system includes an industrial device, a programmable logic controller (programmable logic controller, PLC) connected to and controlling the industrial device, an edge gateway directly connected to the industrial device or the PLC, a cloud platform connected to the edge gateway, and a client interacting with the cloud platform.
The cloud platform is used for generating a data acquisition task and issuing the data acquisition task to the edge gateway; the edge gateway is used for collecting data through industrial equipment or PLC connected with the edge gateway according to the received data collection task, preprocessing the collected data and forwarding the preprocessed data to the cloud platform.
In one possible implementation manner, the cloud platform comprises an application layer, a service layer, a data layer and a display layer, wherein the application layer is used for configuring a data acquisition task, the service layer is used for providing technical service support for the cloud platform, the data layer is used for storing data forwarded by the edge gateway, and the display layer is used for displaying the data forwarded by the edge gateway.
In one possible implementation manner, the cloud platform automatically configures a data acquisition task table for the edge gateway according to PLC parameter information and point location limitation information of the edge gateway in the industrial field, and issues the data acquisition task table to the corresponding edge gateway.
As one example, the PLC parameter information includes a PLC name, a communication protocol, a device address, a port number, a maximum connection number, a timeout time, a rack number, a slot number, a data block, a register, a start address, and the like.
As an example, the data acquisition task table may include one or more of the data acquisition table, inter-frequency acquisition rules, alarm rules, and the like.
The data acquisition table comprises information such as equipment object model identification, acquisition mode, acquisition variable, variable description, data type, acquisition frequency, data unit and the like, the equipment object model is a three-dimensional model uploaded according to equipment types, and the equipment object model identification can be the name or number of the equipment object model.
Illustratively, the inter-frequency acquisition rule includes an equipment object model identification, one or more acquisition variables of the equipment object model corresponding to the equipment object model identification, and a judgment condition corresponding to the one or more acquisition variables.
Illustratively, the alarm rules include an equipment object model identification, an alarm generation condition and an alarm recovery condition for an equipment object model corresponding to the equipment object model identification.
In one possible implementation, the edge gateway performs data collection through a data collection module arranged in the industrial equipment or the PLC, and forwards the collected data to the cloud platform after preprocessing.
As an example, the preprocessing operation performed by the edge gateway on the acquired data may include data merging.
In one possible implementation manner, when the condition of the different-frequency acquisition rule in the data acquisition task issued by the cloud platform is met, the edge gateway automatically starts a high-frequency data acquisition function, records the acquired data and forwards the acquired data to the cloud platform; when the condition of the different-frequency acquisition rule in the data acquisition task is not met, the edge gateway automatically closes the high-frequency data acquisition function.
In one possible implementation manner, when an alarm generation condition of an alarm rule in a data acquisition task issued by a cloud platform is met, an edge gateway generates alarm information and sends the alarm information to the cloud platform; when the alarm recovery condition of the alarm rule in the data acquisition task is met, the edge gateway generates alarm recovery information and sends the alarm recovery information to the cloud platform, and the cloud platform can send the alarm information and the alarm recovery information to the client for the client to check.
It is to be understood that the system architecture shown in fig. 1 is merely one example of an edge computing-based data acquisition system provided herein, and in other embodiments of the present application, an edge computing-based data acquisition system may include more or fewer components than illustrated, or may combine certain components, or may split certain components, or may have a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware, and are not limited in this application.
Fig. 2 is a schematic architecture diagram of a cloud platform according to an embodiment of the present application. Referring to fig. 2, the cloud platform includes a presentation layer, an application layer, a service layer, and a data layer.
The data layer is used for data storage and comprises a plurality of relational databases and a plurality of non-relational databases. The data stored in the data layer can be used for data transmission, authentication verification, data calculation, data application and other services. For example, the data layer can enable storage of device data collected by an edge gateway.
The service layer is a main business logic basic service layer, is based on micro-service to carry out system architecture design, supports reusable data and application to integrate as services or functions, can access the services or functions through a network when required, and simultaneously the gateway service relies on cloud edge integrated architecture to expand the capabilities of data acquisition, artificial intelligence (Artificial Intelligence, AI) algorithm and the like of a cloud platform to an edge gateway so as to meet the basic requirements of industry in the aspects of real-time business, application intelligence, security, privacy protection and the like.
The service layer is used for providing cloud platform bottom micro-service support, including data service, gateway service, application service and the like. The data service is data management and control by means of data standard management, data quality management, data security management, metadata management and the like, and data support is provided for various applications. The gateway service is used for providing gateway support for various applications, and the application service is used for adding, changing and deleting application functions by a developer. For example, the service layer can implement configuration and issuing of data acquisition tasks.
The presentation layer is used for providing personal computer (personal computer, PC) end systems, application program end display systems and the like for various users, and the users can access and analyze data through various mobile ends. For example, the presentation layer is used to present device data forwarded by the edge gateway.
The application layer comprises modules such as system management, equipment management, project management and the like, and provides rich platform-based application for realizing the service functions of the system and particularly for landing.
In one possible implementation, system management provides functions such as user rights management, system menu management, organization management, and operation log management. The system management module provides different authorities and functions for common users and system administrators, and authorizes and verifies the identity of the system administrators and each common user through user authority management; menu management is used to manage the enabling/disabling of system menus; the operation log manages a user account number, a language version, operation details, specific operation time, and the like for recording and viewing operations.
In one possible implementation, as shown in fig. 3, a system administrator logs into a login system in the cloud platform, creates roles, employees, gateways, devices, projects, production lines, and clients, and performs role authorization and various binding operations on the employees.
As one example, binding operations that a system administrator can do in the cloud platform may include binding employees to items, gateways to devices, devices to line, line to customer, line to item, etc.
In another possible implementation manner, the common user logs in the cloud platform, the cloud platform verifies the user name and the password, after the verification is passed, the common user can only access the authorized data, and the data among different institutions are accessed and isolated.
Project management provides for affiliated user management, production line list management, equipment status management, maintenance management, and the like. The user management is used for managing the user with viewing and operating rights to the project; the production line list management is used for recording the related information of the production line corresponding to the project; the equipment list management is used for managing the related information of the connected equipment in the project production line; the equipment state management is used for recording the running state of equipment in the production line; the maintenance management is used for recording the faults and maintenance conditions of the equipment in the production line.
The equipment management provides functions of equipment model management, industrial equipment management, production line management, gateway management and the like.
In one possible implementation, equipment model management can be used to add equipment models.
As an example, uploading a three-dimensional model of a device according to the type of the device, and configuring a data acquisition table corresponding to the device object model based on the data acquisition requirement of the device, wherein the data acquisition table comprises the content such as device object model identification, acquisition mode, variable name, variable description, variable K value, data type, acquisition frequency, data unit, variable authority and the like.
In one possible implementation, the equipment object model management can be used for inter-frequency acquisition setting of the equipment object model, and the inter-frequency acquisition rule is entered.
As an example, according to the equipment type and the specific condition of the site, different frequency acquisition rules of different equipment object models are input, the equipment object models and a plurality of acquisition variables in the equipment object models are selected, different judgment conditions are added to the plurality of variables and are combined into the different frequency acquisition rules, a high-frequency data acquisition table under the rules is set, and the content of the high-frequency data acquisition table is consistent with the content of the data acquisition table.
In addition, the data acquisition system supports that one equipment object model is provided with a plurality of different-frequency acquisition rules, and the different-frequency acquisition rules are independent and triggered according to corresponding signals.
In one possible implementation manner, a user performs equipment addition in the industrial equipment management module, selects a corresponding equipment object model and sets an equipment number, and the system can support multi-number management of industrial equipment, including equipment numbers, project numbers, equipment two-dimension codes and the like and can be imported in batches through an external table.
In one possible implementation manner, a user newly adds a device production line in the production line management module, establishes an association relation between the newly added production line and a corresponding client, performs device batch import after device number screening, and imports the device into the corresponding production line, so that the system can support the client with the association relation with the production line to check all attribution device information, abnormal alarm conditions and the like through the production line.
In one possible implementation manner, the user adds a PLC in the line management module, and sets PLC parameter information in the line management module, where the PLC parameter information includes a PLC name, a communication protocol, a device address, a port number, a maximum connection number, a timeout time, a rack number, a slot number, a data block, a register, a start address, and the like.
As an example, one production line supports the setup of multiple heterogeneous different types of PLCs.
As an example, after setting the PLC parameter information, the PLC may be managed by performing point table management, where a user only needs to sequentially add field devices or change the device sequence according to the field device acquisition sequence, and the system will automatically generate an acquisition set corresponding to the PLC, where the acquisition set includes a variable name, a variable K value, a data type, a data unit, an acquisition frequency, an acquisition authority, a device name, a device object model identifier, and the like. The number of points required to be acquired by the PLC can be determined according to the acquisition set corresponding to the PLC, so that the number of Input/output (I/O) modules required by the PLC can be configured.
In one possible implementation manner, after the user adds an edge gateway in the gateway management module and the production line configuration acquires the PLC and the device acquisition sequence, the user only needs to set parameters such as an edge gateway number, a gateway field IP and the like in the system, and the system can automatically acquire information such as edge gateway configuration, point location limitation and the like.
As one example, multiple edge gateways are configured in a single production line in a system.
In one possible implementation, the user may set alarm rules in the equipment object model management module.
As an example, the user selects a new alarm rule corresponding to the equipment object model, and selects an alarm generation condition and an alarm recovery condition corresponding to the configuration of the acquired information in the data acquisition table corresponding to the equipment object model, so that the setting of the alarm rule can be completed.
As an example, the system may support a single equipment model to set multiple alarm rules, and upon satisfaction of corresponding alarm conditions, the system forwards data to the corresponding presentation segments and to the particular user group according to the alarm rules.
In one possible implementation manner, after the PLC setting and the edge gateway setting are completed, the user may set an automatic issuing or manual issuing on the system, the cloud platform will automatically detect the network environment in the site, acquire the delay condition of the PLC in the production line, and perform the acquisition task division according to the connection delay of different PLCs and the edge gateways and the PLC parameter information, the point location limitation information of the edge gateway will automatically calculate the data acquisition task for each edge gateway and automatically issue to each edge gateway, and each edge gateway will perform the data acquisition after receiving the data acquisition task.
As an example, the cloud platform will detect the connection of the edge gateway and the data collection condition in real time, and only need to perform the task issuing once again when an abnormality occurs or the edge gateway is replaced.
In one possible implementation manner, when the edge gateway supports abnormal transmission of the external network, the edge gateway dynamically stores acquired data, optimizes the internal storage space, performs data zipper set processing on the data in the same signal for a period of time, saves about 30% of file size compared with the normal condition, improves data acquisition stability, and reduces gateway transmission flow.
In one possible implementation manner, according to the different-frequency acquisition rule in the data acquisition task table issued by the cloud platform, when the different-frequency acquisition rule condition is met, the edge gateway automatically starts a high-frequency data acquisition function, and records and forwards corresponding data to the cloud platform; when the condition is restored, the edge gateway will automatically shut down the function to save network traffic.
According to the technical scheme, the cloud platform in the data acquisition system based on edge calculation centrally manages the edge gateway, data acquisition tasks are issued dynamically, a user does not need to perform complex and complicated acquisition setting on site, and only needs to issue tasks again when the edge gateway is replaced under abnormal conditions, so that the stability of the acquisition system can be greatly improved, the data acquisition effect is ensured, and the data acquisition efficiency is improved; meanwhile, the system supports equipment inter-frequency acquisition, a user can set an inter-frequency acquisition rule of an equipment object model on the cloud platform, the system automatically transmits the inter-frequency acquisition rule to the edge gateway, and when the condition of the inter-frequency acquisition rule is met, the edge gateway automatically starts high-frequency acquisition, so that fluctuation of key data of equipment is ensured to be acquired, the fault of field equipment is effectively reduced, and the equipment fault and the equipment key information analysis capability after alarm are improved. The inter-frequency acquisition function automatically ends after the set inter-frequency acquisition time or the set condition is ended, so that the performance cost of the edge gateway is reduced; further, the edge gateway combines and sends the acquired equipment data, and for single sensor signal acquisition, an optimized data structure is adopted for transmission, so that the number of network transmission packets can be effectively reduced, the network flow consumption is reduced, the network bandwidth utilization rate is improved, the acquired data are dynamically stored and compressed when the external network transmission is abnormal, automatic reissue is performed after the gateway recovers external connection, the internal storage space of the gateway is optimized, and the data acquisition stability is improved.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. The data acquisition system based on edge calculation is characterized by comprising a Programmable Logic Controller (PLC) connected with and controlling industrial equipment, an edge gateway connected with the industrial equipment or the PLC, a cloud platform connected with the edge gateway and a client side interacting with the cloud platform;
the cloud platform is used for generating a data acquisition task and issuing the data acquisition task to the edge gateway;
and the edge gateway is used for carrying out data acquisition through the industrial equipment or the PLC according to the data acquisition task, preprocessing the acquired data and forwarding the preprocessed data to the cloud platform.
2. The edge computing-based data acquisition system of claim 1, wherein the cloud platform comprises an application layer, a service layer, a data layer and a presentation layer, the application layer is used for configuring the data acquisition task, the service layer is used for providing technical service support for the cloud platform, the data layer is used for storing data forwarded by the edge gateway, and the presentation layer is used for presenting the data forwarded by the edge gateway.
3. The edge computing-based data acquisition system of claim 2, wherein the application layer comprises a device management providing a device object model management for adding a device object model and configuring a data acquisition table of the device object model based on data acquisition requirements of a device, the data acquisition table comprising a device object model identification, an acquisition mode, an acquisition variable, a variable description, a data type, an acquisition frequency, and a data unit, the device object model being a three-dimensional model uploaded according to a device category, the data acquisition task comprising one or more of the data acquisition tables.
4. The edge computing-based data acquisition system of claim 3, wherein the equipment object model management is further configured to perform an inter-frequency acquisition rule setting on an equipment object model, the inter-frequency acquisition rule including an equipment object model identifier, one or more acquisition variables of the equipment object model corresponding to the equipment object model identifier, and a judgment condition corresponding to the one or more acquisition variables, and the data acquisition task includes the inter-frequency acquisition rule.
5. The edge computing-based data acquisition system of claim 4, wherein the edge gateway is specifically configured to:
when the conditions of the different-frequency acquisition rules in the data acquisition task are met, the edge gateway automatically starts a high-frequency data acquisition function, records acquired data and forwards the acquired data to the cloud platform; and when the condition of the different-frequency acquisition rule in the data acquisition task is not met, the edge gateway automatically closes the high-frequency data acquisition function.
6. The edge computing-based data acquisition system of claim 3, wherein the equipment object model management is further configured to set alarm rules for equipment object models, the alarm rules including equipment object model identifications, alarm generation conditions and alarm recovery conditions for equipment object models corresponding to the equipment object model identifications, and the acquisition task table including the alarm rules.
7. The edge computing-based data acquisition system of claim 6, wherein the edge gateway is specifically configured to:
when the alarm generation condition of the alarm rule in the data acquisition task is met, the edge gateway generates alarm information and sends the alarm information to the cloud platform; and when the alarm recovery condition of the alarm rule in the data acquisition task is met, the edge gateway generates alarm recovery information and sends the alarm recovery information to the cloud platform.
8. The edge computing-based data acquisition system of claim 3 wherein the device management is further configured to manage PLC parameter information including PLC name, communication protocol, device address, port number, maximum connection number, timeout time, rack number, slot number, data block, register, and start address.
9. The edge computing-based data acquisition system of claim 3 wherein the device management further provides gateway management for automatically obtaining user-set edge gateway numbers, edge gateway field network protocol IP, and point location restriction information.
10. The edge computing-based data acquisition system of claim 8 or 9, wherein the cloud platform is specifically configured to:
and generating the data acquisition task according to the PLC parameter information and the point position limiting information of the edge gateway.
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