Industrial perception data management system and method

Abstract

The application discloses an industrial perception data management system and method. The system comprises a management platform on a cloud side, an industrial device and an intelligent gateway on an edge side. The management platform is configured with an information model template, contains standard format nodes of multiple perception data types, and sends collection instructions through the intelligent gateway. The industrial device sends perception data of each measuring point carrying a dynamic measuring point identifier to the intelligent gateway in response to the instructions. The intelligent gateway matches and converts target perception data according to a gateway configuration template, and sends the target perception data to the management platform based on a preset protocol. The gateway configuration template stores a mapping relationship between the measuring point identifier and the information model node and a data format conversion mode. The management platform receives and stores the target perception data to corresponding information model nodes, and constructs an information model of the industrial device. The application solves the technical problem that, in an industrial device management scene, due to problems such as data format and transmission protocol, multi-source perception data is difficult to circulate and share.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to an industrial perception data management system and method. BACKGROUND

[0002] In the field of industrial internet and intelligent manufacturing, the rise of digital twin technology promotes the virtual management and optimization of physical devices. Digital twin relies on a large amount of perception data collected from industrial devices in real time, including device status, environmental conditions, operation parameters, etc. In order to accurately map the physical device in the virtual space, an efficient data modeling integration and expression method is needed to ensure the accuracy and real-time of the data, and to realize the smooth flow of information in various business systems and the whole industry chain. Currently, perception data is usually processed in a point-to-point manner in each business system, and there is a lack of unified data modeling integration mechanism, which leads to difficulties in data transmission and understanding between different systems. Due to the non-uniformity of data formats and protocols between different systems, complex conversion and adaptation are needed for information sharing, which increases the complexity and cost of data processing. The amount of perception data generated by industrial devices is huge, and traditional data processing and storage methods are difficult to cope with, especially in high real-time scenarios, the data processing efficiency is low.

[0003] At present, no effective solution has been proposed to solve the above problems. SUMMARY

[0004] The embodiments of the present application provide an industrial perception data management system and method to at least solve the technical problem that multi-source perception data is difficult to circulate and share due to data format, transmission protocol, etc. in the industrial device management scenario.

[0005] According to an aspect of the embodiments of the present application, an industrial perception data management system is provided, comprising: a management platform at a cloud side, an industrial device and an intelligent gateway at an edge side, wherein the management platform is configured to configure an information model template corresponding to the industrial device, wherein the information model template comprises: a plurality of information model nodes with a standard data format corresponding to a plurality of perception data types one by one; the intelligent gateway is configured to send a perception data collection instruction to the industrial device; the industrial device is configured to send perception data collected by each measuring point in the industrial device to the intelligent gateway in response to the perception data collection instruction, wherein each perception data carries a measuring point identifier of a corresponding measuring point; the intelligent gateway is configured to determine target perception data matched with the information model nodes from the received plurality of perception data according to a preset gateway configuration template, and perform format conversion on the target perception data, and send the converted target perception data to the management platform based on a preset transmission protocol, wherein the gateway configuration template stores a one-to-one mapping relationship between different measuring point identifiers and different information model nodes, and the mapping relationship comprises: a data format conversion mode; and the management platform is further configured to store the received target perception data in the corresponding information model node in the information model template to obtain an information model corresponding to the industrial device.

[0006] Optionally, in the information model template, the dimensions of the perception data comprise: a device attribute dimension, an event information dimension, a service capability dimension, and a subscription information dimension; the perception data type of the device attribute dimension comprises at least one of: static configuration information, running state information, the static configuration information comprises at least one of: a device identifier, a type, and a firmware version, and the running state information comprises at least one of: temperature, humidity, pressure, speed, vibration, current, and voltage; the perception data type of the event information dimension comprises at least one of: device startup, device shutdown, device alarm, device maintenance, fault occurrence, and production completion; the perception data type of the service capability dimension comprises at least one of: execution efficiency, energy consumption, fault rate, and production quality; and the perception data type of the subscription information dimension comprises at least one of: early warning information, maintenance demand, energy consumption trend, and production efficiency prediction information.

[0007] Optionally, the management platform is configured to send a perception data collection instruction to the industrial device through the intelligent gateway, wherein the perception data collection instruction comprises a data collection frequency and a data collection type; the industrial device is configured to determine target measuring points corresponding to the data collection type in response to the perception data collection instruction, and control each target measuring point to collect perception data according to the data collection frequency, and send all the collected perception data to the intelligent gateway.

[0008] Optionally, the smart gateway comprises a plurality of data interfaces corresponding to the plurality of information model nodes one by one, and the gateway configuration template stores configuration information of each data interface, the configuration information comprising a data format conversion mode, wherein the smart gateway is configured to determine target sensing data matched with the information model nodes from the received plurality of sensing data according to the gateway configuration template, determine a target data interface corresponding to the target sensing data from the plurality of data interfaces, determine target configuration information of the target data interface, convert the data format of the target sensing data into a data format specified by the corresponding information model node according to the target configuration information by calling the target data interface, and send the target sensing data after format conversion to the management platform based on a preset transmission protocol.

[0009] Optionally, the smart gateway is configured to periodically send a heartbeat signal to the management platform, wherein the heartbeat signal comprises at least one of the following: an identifier of the smart gateway, a sending timestamp, and a running state; the management platform is configured to determine the running state of the smart gateway according to the heartbeat signal; and when the heartbeat signal sent by the smart gateway is not received for a continuous preset number of cycles, it is determined that the smart gateway is running abnormally, and an abnormal prompt information is generated.

[0010] Optionally, the management platform is further configured to determine static sensing data and dynamic sensing data in the received target sensing data; store each type of static sensing data into a static sensing database according to a first preset data structure, wherein the first preset data structure comprises a relational database table; sort each type of dynamic sensing data according to time to obtain a dynamic sensing data sequence, and store each dynamic sensing data sequence into a time sequence sensing database according to a second preset data structure, wherein the second preset data structure comprises a time sequence database table.

[0011] Optionally, the management platform is further configured to manage information model templates of a plurality of industrial devices in the industrial system according to a three-level relationship of real object-template-unit when configuring the information model template, wherein the real object represents the industrial device, the template represents the information model template corresponding to the industrial device, and the unit is a set of information model templates corresponding to each set of industrial devices after the plurality of industrial devices in the industrial system are divided according to functions.

[0012] According to another aspect of the embodiments of this application, an industrial sensing data management method is also provided, comprising: forwarding a sensing data acquisition instruction from a management platform to an industrial device; receiving multiple sensing data from the industrial device, wherein each sensing data carries a measurement point identifier of a measurement point in the industrial device that collects the sensing data; determining a target sensing data matching an information model node from the multiple sensing data according to a preset gateway configuration template, and converting the target sensing data into a format, wherein the information model node is a node with a standard data format in the information model template configured by the management platform corresponding to the industrial device and corresponding to multiple sensing data types, and the gateway configuration template stores a one-to-one mapping relationship between different measurement point identifiers and different information model nodes, the mapping relationship including: a data format conversion method; and sending the converted target sensing data to the management platform according to a preset transmission protocol, wherein the management platform is used to store the received target sensing data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial device.

[0013] According to another aspect of the embodiments of this application, an industrial sensing data management method is also provided, comprising: configuring an information model template corresponding to industrial equipment, wherein the information model template includes: multiple information model nodes with standard data formats corresponding one-to-one to multiple sensing data types; issuing sensing data acquisition instructions to industrial equipment through a smart gateway, wherein the industrial equipment responds to the sensing data acquisition instructions by sending sensing data collected from various measuring points in the industrial equipment to the smart gateway, each sensing data carrying a measuring point identifier corresponding to the measuring point; the smart gateway determines the target sensing data matching the information model node from the received multiple sensing data according to a preset gateway configuration template, performs format conversion on the target sensing data, and sends the converted target sensing data to a management platform based on a preset transmission protocol, wherein the gateway configuration template stores a one-to-one mapping relationship between different measuring point identifiers and different information model nodes, the mapping relationship including: data format conversion method; storing the received target sensing data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

[0014] According to another aspect of the embodiments of this application, a computer program product is also provided, the computer program product comprising: a computer program, wherein the computer program, when executed by a processor, implements the above-described industrial sensing data management method.

[0015] According to another aspect of the embodiments of this application, an electronic device is also provided, the electronic device including: a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-described industrial sensing data management method through the computer program.

[0016] In this embodiment, the information model template configured on the management platform ensures a standardized representation of all sensed data. Through information model nodes corresponding one-to-one with various sensed data types, the system can uniformly process and organize complex data from different industrial devices. This standardized data model supports effective data integration, facilitating subsequent analysis and application. The sensed data acquisition commands issued by the smart gateway to the industrial devices precisely control the type and frequency of data acquisition. The industrial devices respond to these commands, acquiring data from various measuring points and sending it to the smart gateway. The measuring point identifiers ensure the traceability and accuracy of the data source, enhancing the controllability and efficiency of the data acquisition process. The intelligent gateway, based on a preset gateway configuration template, can filter out target sensing data that matches the information model nodes and perform necessary format conversions to ensure that the data meets the requirements of the information model. The intelligent gateway then sends the format-converted target sensing data to the management platform based on a preset transmission protocol. The management platform then stores this data in the corresponding information model nodes in the information model template, constructing an information model for the industrial equipment. Through the construction of the information model, different types of sensing data can flow smoothly within the system, supporting real-time monitoring of the status of industrial equipment and historical data analysis. This promotes data sharing and interoperability between different systems and components, thereby solving the technical problem in industrial equipment management scenarios where multi-source sensing data is difficult to circulate and share due to issues such as data format and transmission protocols. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 This is a schematic diagram of the structure of an optional industrial sensing data management system according to an embodiment of this application;

[0019] Figure 2 This is a flowchart illustrating an optional industrial sensing data management method according to an embodiment of this application;

[0020] Figure 3 This is a flowchart illustrating another optional industrial sensing data management method according to an embodiment of this application;

[0021] Figure 4 This is a schematic diagram of the structure of an optional electronic device according to an embodiment of this application. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0023] It should be noted that the terms "first," "second," etc., used in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] To better understand the embodiments of this application, the following is a translation and explanation of some nouns or terms that appear in the description of the embodiments of this application:

[0025] Information modeling is a standardized and structured way of describing industrial equipment data. By defining equipment attributes, events, services, and subscriptions, it abstracts the information of physical equipment into computable elements, enabling data to flow smoothly across different business systems and the entire value chain. This achieves efficient data integration and management, supports the construction of digital twins, and improves the real-time and sequential nature of industrial data processing. In short, information modeling serves as a bridge between industrial data management and digital twin technology, ensuring the unified representation and effective utilization of data.

[0026] Sensing data: Data collected by sensing devices or sensory devices has six main characteristics: temporality, location, sequence, massive volume, real-time, and event triggering. It is the main processing object of digital twin technology. In the smart manufacturing environment, devices generate a large amount of sensing data. Achieving the smooth and orderly flow of this data within the enterprise is one of the important goals of enterprise informatization.

[0027] Example 1

[0028] According to embodiments of this application, an industrial sensing data management system is provided, such as... Figure 1 As shown, the industrial sensing data management system includes at least: a cloud-based management platform 11, edge-based industrial equipment 12, and a smart gateway 13, wherein...

[0029] Management platform 11 is used to configure information model templates corresponding to industrial equipment. The information model template includes: multiple information model nodes with standard data formats that correspond one-to-one with various types of sensing data; and sends sensing data acquisition instructions to industrial equipment through a smart gateway.

[0030] Industrial equipment 12 is used to respond to the sensing data acquisition command and send the sensing data collected from each measuring point in the industrial equipment to the intelligent gateway. Each sensing data carries the measuring point identifier of the corresponding measuring point.

[0031] The intelligent gateway 13 is used to determine the target sensing data that matches the information model node from multiple received sensing data according to the preset gateway configuration template, and to convert the target sensing data into a format. The converted target sensing data is then sent to the management platform according to the preset transmission protocol. The gateway configuration template stores a one-to-one mapping relationship between different measurement point identifiers and different information model nodes. The mapping relationship includes: data format conversion method.

[0032] The management platform 11 is also used to store the received target perception data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

[0033] The following section describes the functions of each component of the industrial sensing data management system in conjunction with the specific implementation process.

[0034] The management platform first needs to establish an information model template for each type of industrial equipment. This template contains all the types of sensing data that the equipment may generate or need, as well as the standardized expression of these data types.

[0035] The management platform configuration includes information model templates corresponding to industrial equipment, which contain multiple information model nodes with standard data formats that correspond one-to-one with various types of sensing data. These nodes define the data storage structure, data type, and data meaning, ensuring data consistency and understandability.

[0036] As an optional implementation, in the information model template, the dimensions of the perceived data include: device attribute dimension, event information dimension, service capability dimension, and subscription information dimension; the perceived data types of the device attribute dimension include at least one of the following: static configuration information and operating status information; static configuration information includes at least one of the following: device identifier, type, firmware version; operating status information includes at least one of the following: temperature, humidity, pressure, speed, vibration, current, and voltage; the perceived data types of the event information dimension include at least one of the following: device startup, device shutdown, device alarm, device maintenance, fault occurrence, and production completion; the perceived data types of the service capability dimension include at least one of the following: execution efficiency, energy consumption, failure rate, and production quality; the perceived data types of the subscription information dimension include at least one of the following: early warning information, maintenance requirements, energy consumption trends, and production efficiency prediction information.

[0037] As an optional implementation, the management platform can also manage the information model templates of multiple industrial devices in the industrial system according to a three-level relationship of physical object-template-unit when configuring information model templates. Here, physical object represents industrial equipment, template represents the information model template corresponding to the industrial equipment, and unit is the set of information model templates corresponding to each set of industrial equipment after dividing the multiple industrial equipment in the industrial system according to their functions.

[0038] For example, when configuring the information model template for a screw machine, the management platform first defines the machine's equipment attribute dimensions, including static configuration information such as equipment identification, type, and firmware version, as well as operating status information such as temperature and vibration. Next, it defines the event information dimension, such as equipment start-up and shutdown events, and the service capability dimension, such as execution efficiency and energy consumption. Finally, it defines the subscription information dimension, such as early warning information and maintenance requirements. When the actual operating data (sensored data) of the screw machine is collected and transmitted to the management platform, this data is standardized and classified according to its respective information model nodes. For example, the screw machine's temperature data is mapped to the equipment attribute dimension - temperature node, and the equipment start-up event is mapped to the event information dimension - equipment start-up node. In this way, all sensored data is organized in the corresponding information model template, realizing the modeling and structuring of data. Furthermore, if there are multiple screw machines in the factory, they will be grouped into the same unit and share the same information model template. Thus, even if the number of screw machines increases, the management platform can efficiently manage and process data from these devices, achieving unified data management and analysis.

[0039] Through these steps, the management platform can ensure that the sensing data of all industrial equipment is modeled, providing a unified data representation and organization method for the Industrial Internet, and greatly improving the efficiency and value of data utilization.

[0040] The management platform issues sensing data acquisition instructions to industrial equipment through a smart gateway as an optional implementation method. The sensing data acquisition instructions include the data acquisition frequency and data acquisition type.

[0041] The industrial equipment responds to the sensing data acquisition command and sends the sensing data collected from each measuring point in the industrial equipment to the smart gateway. Each sensing data carries the measuring point identifier of the corresponding measuring point.

[0042] Specifically, as an optional implementation method, the industrial equipment responds to the sensing data acquisition command, determines the target measurement point corresponding to the data acquisition type, controls each target measurement point to acquire sensing data according to the data acquisition frequency, and sends all the acquired sensing data to the smart gateway.

[0043] For example, when industrial equipment receives a data acquisition command, it identifies which measurement points (i.e., data acquisition points) correspond to the data acquisition type specified in the command. For instance, a screw machine may have multiple measurement points such as temperature sensors and vibration sensors. Upon receiving a command to collect temperature data, the screw machine will only activate the temperature sensor for data acquisition. The industrial equipment will periodically collect sensing data from the target measurement points according to the frequency set in the command. For example, if the command requires collecting temperature data once per minute, the screw machine will ensure that temperature information is collected once per minute. Before each collected sensing data is sent to the smart gateway, a measurement point identifier corresponding to that data is attached. This is so that the smart gateway can accurately identify the data source and associate the data with the corresponding information model node. For example, the temperature data 123.4℃ will be accompanied by the unique identifier 01 of the temperature sensor, indicating that this is temperature data from measurement point 01 on the screw machine.

[0044] The intelligent gateway determines the target sensing data that matches the information model node from multiple received sensing data based on a preset gateway configuration template, performs format conversion on the target sensing data, and sends the converted target sensing data to the management platform based on a preset transmission protocol. The gateway configuration template stores a one-to-one mapping relationship between different measurement point identifiers and different information model nodes. The mapping relationship includes the data format conversion method, thereby ensuring that each sensing data received from the industrial equipment can be correctly identified and processed.

[0045] As an optional implementation, the smart gateway includes multiple data interfaces corresponding one-to-one with multiple information model nodes. The gateway configuration template stores the configuration information of each data interface, which includes the data format conversion method. Therefore, the smart gateway can determine the target sensing data that matches the information model node from the multiple received sensing data according to the gateway configuration template, determine the target data interface corresponding to the target sensing data from the multiple data interfaces, determine the target configuration information of the target data interface, call the target data interface to convert the data format of the target sensing data into the data format specified by the corresponding information model node according to the target configuration information, and send the format-converted target sensing data to the management platform according to the preset transmission protocol.

[0046] For example, temperature data 123.4℃ will match data interface 01, because interface 01 is used to process temperature data. If information model node 01 requires temperature data to be expressed in Fahrenheit, the smart gateway will convert the received Celsius temperature data into Fahrenheit.

[0047] The management platform stores the received target perception data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

[0048] The management platform receives target sensing data from the intelligent gateway. This data has been filtered and formatted to match preset information model nodes. For each piece of target sensing data, the management platform identifies the information model node to which it belongs. For example, the temperature data of the screw machine will be matched with the "temperature" attribute node in the information model. The management platform maps the target sensing data to the corresponding information model node in the information model template. This means that the data is inserted into the structure of the information model, forming associations with other data elements in the model (such as attributes, events, services, etc.), and constructing a virtual representation of the equipment. By storing all target sensing data in the corresponding information model nodes, the management platform gradually builds a complete information model of the industrial equipment. This model not only includes the static attributes of the equipment (such as model number and version number) but also reflects the real-time operating status of the equipment (such as dynamic data such as temperature and vibration).

[0049] As an optional implementation, the management platform can also identify static and dynamic sensing data in the received target sensing data. Static sensing data typically refers to basic equipment attributes such as equipment identification and type, which change relatively little during the equipment's lifecycle. Dynamic sensing data, on the other hand, is real-time data during equipment operation, such as temperature and vibration, which change rapidly over time. Each type of static sensing data is stored in a static sensing database according to a first preset data structure, which includes a relational database table. This relational database table allows for clear management and querying of basic equipment information, facilitating equipment management and maintenance. Each type of dynamic sensing data is sorted by time to obtain a dynamic sensing data sequence. Each dynamic sensing data sequence is then stored in a time-series sensing database according to a second preset data structure, which includes a time-series database table. This time-series database structure is particularly suitable for processing large amounts of time-series data and can effectively support historical data queries and real-time data analysis, such as equipment status monitoring and fault prediction.

[0050] As an optional implementation, the smart gateway periodically sends a heartbeat signal to the management platform. The heartbeat signal includes at least one of the following: the smart gateway's identifier, a sending timestamp, and its operating status. The purpose of the heartbeat signal is to inform the management platform that the smart gateway is currently online and operating normally. The management platform determines the operating status of the smart gateway based on the heartbeat signal. After receiving the heartbeat signal, the management platform checks the information in the signal to determine the operating status of the smart gateway, such as whether it is online or operating normally. If no heartbeat signal is received from the smart gateway for a preset number of consecutive periods, the management platform determines that the smart gateway is operating abnormally and generates an abnormal prompt message. This may also trigger a fault investigation and handling mechanism, such as remotely restarting the smart gateway or dispatching technical personnel for on-site inspection.

[0051] In this embodiment, the information model template configured on the management platform ensures a standardized representation of all sensed data. Through information model nodes corresponding one-to-one with various sensed data types, the system can uniformly process and organize complex data from different industrial devices. This standardized data model supports effective data integration, facilitating subsequent analysis and application. The sensed data acquisition commands issued by the smart gateway to the industrial devices precisely control the type and frequency of data acquisition. The industrial devices respond to these commands, acquiring data from various measuring points and sending it to the smart gateway. The measuring point identifiers ensure the traceability and accuracy of the data source, enhancing the controllability and efficiency of the data acquisition process. The intelligent gateway, based on a preset gateway configuration template, can filter out target sensing data that matches the information model nodes and perform necessary format conversions to ensure that the data meets the requirements of the information model. The intelligent gateway then sends the format-converted target sensing data to the management platform based on a preset transmission protocol. The management platform then stores this data in the corresponding information model nodes in the information model template, constructing an information model for the industrial equipment. Through the construction of the information model, different types of sensing data can flow smoothly within the system, supporting real-time monitoring of the status of industrial equipment and historical data analysis. This promotes data sharing and interoperability between different systems and components, thereby solving the technical problem in industrial equipment management scenarios where multi-source sensing data is difficult to circulate and share due to issues such as data format and transmission protocols.

[0052] Example 2

[0053] According to an embodiment of this application, an industrial sensing data management method is provided for use in the industrial sensing data management system of Embodiment 1. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0054] Figure 2 This is a flowchart illustrating an industrial sensing data management method according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0055] Step S202: Forward the sensing data acquisition command from the management platform to the industrial equipment;

[0056] Step S204: Receive multiple sensing data from industrial equipment, wherein each sensing data carries a measurement point identifier of the measurement point in the industrial equipment that collects the sensing data.

[0057] Step S206: Based on the preset gateway configuration template, determine the target sensing data that matches the information model node from multiple sensing data, and perform format conversion on the target sensing data. Here, the information model node is a node with a standard data format that corresponds one-to-one with multiple sensing data types in the information model template configured by the management platform and corresponding to the industrial equipment. The gateway configuration template stores a one-to-one mapping relationship between different measurement point identifiers and different information model nodes. The mapping relationship includes: data format conversion method.

[0058] Step S208: The converted target perception data is sent to the management platform based on a preset transmission protocol. The management platform is used to store the received target perception data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

[0059] The following section explains each step of the industrial sensing data management method in conjunction with a specific implementation process.

[0060] The smart gateway receives sensing data collection instructions from the cloud management platform. These instructions typically include the frequency and type of data collection. The smart gateway then forwards these instructions to the corresponding industrial equipment, instructing the equipment to start collecting data according to the instructions.

[0061] Industrial equipment responds to acquisition commands, collects sensing data from various measurement points, and sends this data back to the smart gateway. Each sensing data carries a unique identifier of its acquisition measurement point. The smart gateway parses these identifiers to understand the source and type of the data.

[0062] Based on a pre-configured gateway template, the intelligent gateway selects target perception data that matches the information model node from the received perception data set. The gateway template stores the mapping relationship between different measurement point identifiers and information model nodes, including specific data format conversion rules. The intelligent gateway calls the format conversion function corresponding to its data interface to convert the target perception data into the standardized format required by the information model node.

[0063] After the format conversion is completed, the smart gateway will send the target perception data to the management platform based on the preset transmission protocol. After receiving the data, the management platform will store it in the corresponding information model node to build a complete information model of the industrial equipment for purposes such as equipment status monitoring, fault prediction, and performance analysis.

[0064] The smart gateway also has a self-monitoring function. It periodically sends heartbeat signals to the management platform. The signals contain the gateway's operating status information, such as the identifier, timestamp, and current status. By parsing the heartbeat signals, the management platform can understand the smart gateway's operating status in real time. If the gateway fails to send heartbeat signals for an extended period of time, the management platform can detect the anomaly in a timely manner and take corresponding measures, such as re-establishing the connection or fault recovery.

[0065] Before uploading data, the smart gateway may assist the management platform in performing preliminary data classification, categorizing the sensed data into static and dynamic types. Static data typically contains inherent device information, such as device identifier, type, and firmware version, while dynamic data reflects the device's operating status, such as temperature, humidity, pressure, and speed. This classification helps the management platform organize and store data more efficiently. Static data can be stored in relational database tables, while dynamic data is stored in time-series database tables, facilitating subsequent data analysis and querying.

[0066] The aforementioned functions of the smart gateway not only support real-time data acquisition, format standardization, and uploading, but also directly promote the construction of information models. The management platform can construct an information model that comprehensively reflects the status of industrial equipment through the data collected by the smart gateway, providing accurate data support for equipment management, monitoring, and maintenance.

[0067] It should be noted that each process step in the industrial sensing data management method in this application embodiment corresponds one-to-one with each implementation step of the industrial sensing data management system in embodiment 1. Since embodiment 1 has been described in detail, some details not shown in this embodiment can be referred to embodiment 1, and will not be elaborated further here.

[0068] Example 3

[0069] According to an embodiment of this application, an industrial sensing data management method is provided for use in the industrial sensing data management system of Embodiment 1. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0070] Figure 3 This is a flowchart illustrating an industrial sensing data management method according to an embodiment of this application, such as... Figure 3 As shown, the method includes the following steps:

[0071] Step S302: Configure the information model template corresponding to the industrial equipment. The information model template includes multiple information model nodes with standard data formats that correspond one-to-one with various types of sensing data.

[0072] Step S304: A sensing data acquisition command is sent to the industrial equipment through the intelligent gateway. The industrial equipment responds to the sensing data acquisition command by sending the sensing data collected from each measuring point in the industrial equipment to the intelligent gateway. Each sensing data carries a measuring point identifier corresponding to the measuring point. The intelligent gateway determines the target sensing data that matches the information model node from the received multiple sensing data according to a preset gateway configuration template, performs format conversion on the target sensing data, and sends the converted target sensing data to the management platform based on a preset transmission protocol. The gateway configuration template stores a one-to-one mapping relationship between different measuring point identifiers and different information model nodes. The mapping relationship includes: data format conversion method.

[0073] Step S306: Store the received target perception data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

[0074] The following section explains each step of the industrial sensing data management method in conjunction with a specific implementation process.

[0075] The management platform first creates an information model template based on the characteristics and needs of industrial equipment. This template contains information model nodes that correspond one-to-one with the data types sensed by the equipment. Each node has a predefined data format to ensure standardized data representation. The nodes cover dimensions such as equipment attributes, event information, service capabilities, and subscription information.

[0076] The management platform sends sensing data acquisition instructions to industrial equipment through the smart gateway. These instructions contain information on the frequency and type of data acquisition, guiding the industrial equipment to accurately collect the required sensing data from various measurement points. The measurement point identifiers carried in the data acquisition instructions are the key basis for the smart gateway to process the data subsequently.

[0077] The management platform receives target perception data uploaded by the smart gateway after format conversion. This data is filtered and converted from the original perception data sent by industrial equipment by the smart gateway according to the mapping relationship and data format conversion method in the gateway configuration template.

[0078] The management platform stores the received target sensing data into the corresponding information model nodes in the information model template. For different types of sensing data, such as static sensing data (e.g., inherent equipment information) and dynamic sensing data (e.g., equipment operating status information), the management platform uses a first preset data structure (e.g., a relational database table) and a second preset data structure (e.g., a time-series database table) for storage, respectively. This process constructs the equipment's information model, providing a comprehensive and standardized data view for equipment monitoring, analysis, and management.

[0079] When configuring information model templates, the management platform adopts a three-level relationship management approach of physical objects, templates, and units. Physical objects represent industrial equipment, templates represent the information model templates corresponding to the equipment, and units group different industrial equipment according to their functions. This management approach helps to organize and maintain complex information models of multiple devices and facilitates sliced ​​management and information retrieval.

[0080] The management platform can also monitor the operating status of industrial equipment through the heartbeat signals received by the smart gateway. Once an abnormality is detected, such as if no heartbeat signal is received for a preset number of consecutive cycles, the management platform will generate an abnormality prompt message and promptly notify maintenance personnel to take measures.

[0081] Through the above steps, the management platform not only achieves precise control and standardized management of industrial equipment sensing data, but also constructs a comprehensive information model reflecting the equipment status, providing a solid data foundation for real-time equipment monitoring, fault prediction, performance analysis, and full lifecycle management. The core function of the management platform is to ensure the interconnectivity of data throughout the system, improving the efficiency and accuracy of data processing and utilization.

[0082] It should be noted that each process step in the industrial sensing data management method in this application embodiment corresponds one-to-one with each implementation step of the industrial sensing data management system in embodiment 1. Since embodiment 1 has been described in detail, some details not shown in this embodiment can be referred to embodiment 1, and will not be elaborated further here.

[0083] Example 4

[0084] According to an embodiment of this application, a computer program product is also provided, which includes a computer program, wherein when the computer program is executed by a processor, it implements the industrial sensing data management method in embodiment 2 or embodiment 3.

[0085] According to an embodiment of this application, a non-volatile storage medium is also provided, which includes a stored computer program, wherein the device containing the non-volatile storage medium executes the industrial sensing data management method in embodiment 2 or embodiment 3 by running the computer program.

[0086] According to an embodiment of this application, a processor is also provided for running a computer program, wherein the computer program executes the industrial sensing data management method in embodiment 2 or embodiment 3 during runtime.

[0087] According to an embodiment of this application, an electronic device is also provided, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the industrial sensing data management method of embodiment 2 or embodiment 3 through the computer program.

[0088] Specifically, the computer program can execute the following steps during runtime: forwarding the sensing data acquisition command from the management platform to the industrial equipment; receiving multiple sensing data from the industrial equipment, wherein each sensing data carries a measurement point identifier of the measurement point in the industrial equipment that collected the sensing data; determining the target sensing data that matches the information model node from the multiple sensing data according to a preset gateway configuration template, and converting the target sensing data into a format, wherein the information model node is a node with a standard data format in the information model template configured by the management platform corresponding to the industrial equipment, which corresponds one-to-one with multiple sensing data types, and the gateway configuration template stores a one-to-one mapping relationship between different measurement point identifiers and different information model nodes, including: data format conversion method; sending the converted target sensing data to the management platform according to a preset transmission protocol, wherein the management platform is used to store the received target sensing data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

[0089] Specifically, the computer program can execute the following steps during runtime: Configure an information model template corresponding to the industrial equipment, wherein the information model template includes multiple information model nodes with standard data formats that correspond one-to-one with various types of sensing data; issue sensing data acquisition instructions to the industrial equipment through a smart gateway, wherein the industrial equipment responds to the sensing data acquisition instructions by sending sensing data collected from various measuring points in the industrial equipment to the smart gateway, with each sensing data carrying a measuring point identifier corresponding to the measuring point; the smart gateway determines the target sensing data matching the information model node from the received multiple sensing data according to a preset gateway configuration template, performs format conversion on the target sensing data, and sends the converted target sensing data to the management platform based on a preset transmission protocol, wherein the gateway configuration template stores a one-to-one mapping relationship between different measuring point identifiers and different information model nodes, the mapping relationship including: data format conversion method; store the received target sensing data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

[0090] As an alternative implementation, the above-mentioned electronic device may exist in the form of a mobile terminal, a computer terminal, or a similar computing device. Figure 4 A hardware block diagram of an electronic device for implementing an industrial sensing data management method is shown. Figure 4As shown, the electronic device 40 may include one or more processors 402 (shown as 402a, 402b, ..., 402n in the figure) 402 (processor 402 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 404 for storing data, and a transmission device 406 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 4 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, electronic device 40 may also include... Figure 4 The more or fewer components shown, or having the same Figure 4 The different configurations shown.

[0091] It should be noted that the aforementioned one or more processors 402 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element of the electronic device 40. As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0092] The memory 404 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the industrial sensing data management method in this embodiment. The processor 402 executes various functional applications and data processing by running the software programs and modules stored in the memory 404, thereby implementing the aforementioned application vulnerability detection method. The memory 404 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 404 may further include memory remotely located relative to the processor 402, and these remote memories can be connected to the electronic device 40 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0093] The transmission device 406 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the electronic device 40. In one example, the transmission device 406 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 406 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0094] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the electronic device 40.

[0095] The sequence numbers of the above embodiments are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0096] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0098] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0100] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0101] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. An industrial sensing data management system, characterized in that, include: The cloud-based management platform, edge-based industrial equipment, and smart gateways, among which... The management platform is used to configure an information model template corresponding to the industrial equipment, wherein the information model template includes: multiple information model nodes with standard data formats that correspond one-to-one with various types of sensing data; and to issue sensing data acquisition instructions to the industrial equipment through the smart gateway; The industrial equipment is used to respond to the sensing data acquisition command and send the sensing data collected by each measuring point in the industrial equipment to the smart gateway, wherein each sensing data carries a measuring point identifier corresponding to the measuring point. The intelligent gateway is used to determine the target sensing data that matches the information model node from multiple received sensing data according to a preset gateway configuration template. The gateway configuration template stores a one-to-one mapping relationship between different measurement point identifiers and different information model nodes. The intelligent gateway includes multiple data interfaces that correspond one-to-one with the multiple information model nodes. The gateway configuration template also stores the configuration information of each data interface, which includes: data format conversion method. From multiple data interfaces, determine the target data interface corresponding to the target perception data, determine the target configuration information of the target data interface, call the target data interface to convert the data format of the target perception data into the data format specified by the corresponding information model node according to the target configuration information, and send the converted target perception data to the management platform based on a preset transmission protocol. The management platform is also used to store the received target perception data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

2. The system according to claim 1, characterized in that, In the information model template, the dimensions of the perceived data include: device attribute dimension, event information dimension, service capability dimension, and subscription information dimension; The perceived data types of the device attribute dimension include at least one of the following: static configuration information and operating status information. The static configuration information includes at least one of the following: device identifier, type, and firmware version. The operating status information includes at least one of the following: temperature, humidity, pressure, speed, vibration, current, and voltage. The perceived data types of the event information dimension include at least one of the following: equipment startup, equipment shutdown, equipment alarm, equipment maintenance, fault occurrence, and production completion; The perceived data types of the service capability dimension include at least one of the following: execution efficiency, energy consumption, failure rate, and production quality; The data types of the subscription information dimension include at least one of the following: early warning information, maintenance requirements, energy consumption trends, and production efficiency prediction information.

3. The system according to claim 1, characterized in that, The management platform is used to issue sensing data acquisition instructions to the industrial equipment through the smart gateway, wherein the sensing data acquisition instructions include data acquisition frequency and data acquisition type; The industrial equipment is used to respond to the sensing data acquisition command, determine the target measurement point corresponding to the data acquisition type, control each target measurement point to acquire sensing data according to the data acquisition frequency, and send all the acquired sensing data to the smart gateway.

4. The system according to claim 1, characterized in that, The smart gateway is used to periodically send heartbeat signals to the management platform, wherein the heartbeat signal includes at least one of the following: the identifier of the smart gateway, the sending timestamp, and the running status; The management platform is used to determine the operating status of the smart gateway based on the heartbeat signal; if the smart gateway fails to receive the heartbeat signal from the smart gateway for a preset number of consecutive cycles, it determines that the smart gateway is operating abnormally and generates an abnormal prompt message.

5. The system according to claim 1, characterized in that, The management platform is further configured to determine static and dynamic sensing data in the received target sensing data; store each type of static sensing data in a static sensing database according to a first preset data structure, wherein the first preset data structure includes a relational database table; sort each type of dynamic sensing data according to time to obtain a dynamic sensing data sequence, and store each dynamic sensing data sequence in a time-series sensing database according to a second preset data structure, wherein the second preset data structure includes a time-series database table.

6. The system according to claim 1, characterized in that, The management platform is also used to manage the information model templates of multiple industrial devices in the industrial system according to a three-level relationship of physical object-template-unit when configuring information model templates. The physical object represents the industrial device, the template represents the information model template corresponding to the industrial device, and the unit is the set of information model templates corresponding to each set of industrial devices after the multiple industrial devices in the industrial system are divided according to their functions.

7. An industrial sensing data management method, applied to a smart gateway, characterized in that, include: Forward the sensor data acquisition instructions from the management platform to the industrial equipment; Receive multiple sensing data fed back by the industrial equipment, wherein each sensing data carries a measurement point identifier of the measurement point in the industrial equipment that collected the sensing data; The system determines target sensing data that matches the information model node from the multiple sensing data based on a preset gateway configuration template. The information model node is a node with a standard data format that corresponds one-to-one with multiple sensing data types in the information model template configured by the management platform for the industrial equipment. The gateway configuration template stores a one-to-one mapping relationship between different measurement point identifiers and different information model nodes. The smart gateway includes multiple data interfaces that correspond one-to-one with the multiple information model nodes. The gateway configuration template also stores configuration information for each data interface, including: data format conversion method. From multiple data interfaces, determine the target data interface corresponding to the target perception data, determine the target configuration information of the target data interface, call the target data interface to convert the data format of the target perception data into the data format specified by the corresponding information model node according to the target configuration information, and send the converted target perception data to the management platform based on a preset transmission protocol. The converted target perception data is sent to the management platform based on a preset transmission protocol. The management platform is used to store the received target perception data into the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

8. An industrial sensing data management method, applied to a management platform, characterized in that, include: Configure an information model template corresponding to industrial equipment, wherein the information model template includes: multiple information model nodes with standard data formats that correspond one-to-one with various types of sensory data; A smart gateway issues a sensing data acquisition command to the industrial equipment. The industrial equipment responds to the command by sending sensing data collected from various measuring points to the smart gateway. Each sensing data point carries a corresponding measuring point identifier. The smart gateway determines the target sensing data matching the information model node from the received sensing data based on a preset gateway configuration template. The gateway configuration template stores a one-to-one mapping between different measuring point identifiers and different information model nodes. The smart gateway includes multiple data interfaces corresponding to the multiple information model nodes. The gateway configuration template also stores configuration information for each data interface, including data format conversion methods. The smart gateway further determines the target data interface corresponding to the target sensing data from the multiple data interfaces, determines the target configuration information of the target data interface, calls the target data interface to convert the data format of the target sensing data to the data format specified by the corresponding information model node based on the target configuration information, and sends the converted target sensing data to the management platform based on a preset transmission protocol. The received target perception data is stored in the corresponding information model node in the information model template to obtain the information model corresponding to the industrial equipment.

9. An electronic device, characterized in that, include: A memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the industrial sensing data management method of claim 7 or 8 through the computer program.

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