A method and system for processing safe production information based on industrial Internet

Abstract

The present application is applicable to the field of safe production technology, and in particular, relates to a safe production information processing method and system based on the industrial Internet. The safe production information processing method based on the industrial Internet includes: obtaining safe production information in an industrial production environment, and comprehensively understanding the safety status of each production link in order to achieve effective safety management; based on the obtained safe production information, forming multiple data node sets reflecting the data of multiple data collection points in the industrial Internet; based on the multiple data node sets of the industrial production environment, determining multiple security information paths reflecting the data association between data collection points; based on these security information paths, constructing a security information network that reflects the security risk association of the industrial production environment, so as to more comprehensively grasp the security situation of the production environment; finally, based on the security information network, timely and comprehensive risk management of the industrial production environment is carried out to improve the overall production safety level.

Description

Technical Field

[0001] The present application belongs to the field of safe production technology, and in particular, relates to a safe production information processing method and system based on the industrial Internet. Background Art

[0002] Industrial Internet refers to a new production method that deeply integrates Internet technology with traditional industrial fields. It uses technologies such as smart devices, the Internet of Things (IoT), big data analysis, and cloud computing to achieve comprehensive perception, real-time monitoring, precise control, and intelligent decision-making of industrial production processes.

[0003] In the current stage of industrial Internet, risk assessment in the production process often relies on manual experience, and each device and system usually operates independently, forming a "data island". There is a lack of systematic data interconnection and analysis mechanism, resulting in incomplete and untimely risk identification. Summary of the invention

[0004] The embodiments of the present application provide a method and system for processing safe production information based on the industrial Internet, which can solve the problem of incomplete and untimely risk identification due to the lack of a systematic data interconnection and analysis mechanism in the safe production processing process.

[0005] In a first aspect, an embodiment of the present application provides a method for processing safe production information based on the industrial Internet, including:

[0006] Acquire safety production information in an industrial production environment; wherein the safety production information is used to reflect the safety status of each link of the industrial production environment;

[0007] According to the safety production information in the industrial production environment, a plurality of data node sets of the industrial production environment are obtained; wherein the data node sets are used to reflect the collective data of a plurality of data collection points in the industrial Internet;

[0008] Based on the plurality of data node sets of the industrial production environment, a plurality of security information paths are determined; wherein the security information paths are used to reflect the association between the data of the data collection points;

[0009] According to the plurality of security information paths, a security information network of the industrial production environment is constructed; wherein the security information network is used to reflect the security risk association of the industrial production environment;

[0010] Based on the security information network of the industrial production environment, risk management is performed on the industrial production environment.

[0011] The industrial Internet-based production safety information processing method provided in the embodiment of the present application obtains production safety information in the industrial production environment and fully understands the safety status of each production link in order to achieve effective safety management. Based on the obtained production safety information, multiple data node sets reflecting the data of multiple data collection points in the industrial Internet are formed. Based on the multiple data node sets of the industrial production environment, multiple security information paths reflecting the data association between data collection points are determined. Based on these security information paths, a security information network reflecting the security risk association of the industrial production environment is constructed, so as to more comprehensively grasp the security situation of the production environment. Finally, based on the security information network, timely and comprehensive risk management of the industrial production environment is carried out to improve the overall production safety level.

[0012] In a second aspect, the embodiment of the present application provides a safe production information processing system based on the industrial Internet, including:

[0013] An acquisition unit, used to acquire safety production information in an industrial production environment; wherein the safety production information is used to reflect the safety status of each link of the industrial production environment;

[0014] A collection unit, used to obtain a plurality of data node sets of the industrial production environment according to the safety production information in the industrial production environment; wherein the data node set is used to reflect the collection data of multiple data collection points in the industrial Internet;

[0015] A path unit, used to determine a plurality of security information paths based on a plurality of data node sets of the industrial production environment; wherein the security information paths are used to reflect the association between the data of the data collection points;

[0016] A network unit, used to construct a security information network of the industrial production environment according to the plurality of security information paths; wherein the security information network is used to reflect the security risk association of the industrial production environment;

[0017] A management unit is used to perform risk management on the industrial production environment according to the security information network of the industrial production environment.

[0018] In the third aspect, an embodiment of the present application provides a safe production information processing device based on the industrial Internet, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method described in any one of the first aspects above.

[0019] In a fourth aspect, an embodiment of the present application provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute any one of the methods described in the first aspect.

[0020] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 It is a flowchart of a method for processing safe production information based on the industrial Internet provided by an embodiment of the present application;

[0023] Figure 2 It is a flowchart of step S200 in the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0024] Figure 3 It is a flowchart of step S230 of the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0025] Figure 4 It is a flowchart of step S300 of the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0026] Figure 5 It is a flowchart of step S310 of the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0027] Figure 6 It is a flowchart of step S320 of the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0028] Figure 7 It is a flowchart of step S323 of the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0029] Figure 8 It is a flowchart of step S400 of the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0030] Fig. 9It is a flowchart of step S500 of the industrial Internet-based production safety information processing method provided by an embodiment of the present application;

[0031] Fig.10 It is a structural diagram of a safe production information processing system based on the industrial Internet provided by an embodiment of the present application;

[0032] Fig.11 It is a structural diagram of a safe production information processing device based on the industrial Internet provided in one embodiment of the present application. DETAILED DESCRIPTION

[0033] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0034] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0035] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0036] As used in the specification of this application and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if it is determined" or "if the described condition or event is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce the described condition or event is detected" or "in response to detecting the described condition or event" depending on the context.

[0037] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0038] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0039] In the current stage of industrial Internet, risk assessment in the production process often relies on manual experience, and each device and system usually operates independently, forming a "data island". There is a lack of systematic data interconnection and analysis mechanism, resulting in incomplete and untimely risk identification.

[0040] To solve the above problems, the embodiments of the present application provide a safe production information processing and system based on the industrial Internet. In this method, by obtaining safe production information in the industrial production environment, the safety status of each production link is fully understood in order to achieve effective safety management. Based on the obtained safe production information, multiple data node sets reflecting the data of multiple data collection points in the industrial Internet are formed. Based on the multiple data node sets of the industrial production environment, multiple security information paths reflecting the data association between data collection points are determined. Based on these security information paths, a security information network reflecting the security risk association of the industrial production environment is constructed, so as to more comprehensively grasp the security situation of the production environment. Finally, based on the security information network, timely and comprehensive risk management of the industrial production environment is carried out to improve the overall production safety level.

[0041] The industrial Internet-based production safety information processing method provided in the embodiment of the present application can be applied to a terminal device. At this time, the terminal device is the executor of the industrial Internet-based production safety information processing method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of the terminal device.

[0042] For example, the terminal device can be a mobile phone, tablet computer, wearable device, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), desktop computer, smart large screen, smart TV and other terminal devices, handheld devices with wireless communication function, computing devices or other processing devices connected to a wireless modem, vehicle-mounted equipment, Internet of Vehicles terminal, computer, laptop computer, handheld communication device, handheld computing device, satellite wireless device, etc.

[0043] In order to better understand the industrial Internet-based safe production information processing method provided in the embodiment of the present application, the specific implementation process of the industrial Internet-based safe production information processing method provided in the embodiment of the present application is exemplarily introduced below.

[0044] Figure 1 A schematic flowchart of a method for processing safe production information based on the industrial Internet provided in an embodiment of the present application is shown. The method for processing safe production information based on the industrial Internet includes:

[0045] S100, obtaining safe production information in an industrial production environment; wherein the safe production information is used to reflect the safety status of each link in the industrial production environment.

[0046] It can be understood that safety production information is the basis of the entire safety management process and is used to reflect the safety status of various aspects of the production environment. Safety production information in industrial production environments is multi-dimensional, covering a wide range of data from equipment operating status to environmental conditions. For example, the operating status information of the equipment may include parameters such as temperature, pressure, vibration, and operating time, while environmental condition information may include temperature, humidity, concentration of harmful gases, noise level, etc. This type of safety production information can be collected in real time through various sensors and monitoring equipment, and these data can be obtained automatically or semi-automatically. Safety production information can also include data related to personnel operations, such as whether workers operate in accordance with the prescribed operating procedures, whether there are any violations, and whether they wear necessary safety equipment. This type of safety production information can be collected and analyzed through video monitoring systems, behavior recognition algorithms, and handheld devices. Historical data can also be an important part of safety production information. Various types of safety accidents that have occurred in the past, their causes, processing processes, and results can be recorded, and these data can be included in the current safety information database. These historical information can not only help the system identify potential safety hazards that may exist at present, but also provide a basis for predicting and preventing future accidents. The acquisition of production safety information can include sensor data, manual input, reports generated by automated monitoring systems, and even relevant data obtained from external systems (such as supply chain management systems or customer feedback systems). The purpose of obtaining production safety information is to comprehensively and real-time reflect the safety status of each link in the production environment. By obtaining production safety information, the safety status of the entire industrial production environment can be dynamically understood, providing support for subsequent data analysis and decision-making.

[0047] S200, based on the production safety information in the industrial production environment, obtain multiple data node sets of the industrial production environment; wherein the data node sets are used to reflect the collective data of multiple data collection points in the industrial Internet.

[0048] It can be understood that multiple data node sets in the industrial production environment can be identified and established based on the safety production information that has been obtained. This process involves classifying and identifying the safety production information to determine the specific location and role of each data node in the entire industrial Internet. The data node set represents the overall overview of the data collected at different data collection points, which can reflect the safety status and potential risks in the production environment. First, all node identification data in the industrial production environment can be determined by classification and identification. Node identification data refers to the unique identifier of each data source, which can be a device ID, sensor number, location coordinates, etc. Through these identification data, the source and characteristics of each data node can be clarified, thereby providing a basis for the subsequent construction of node sets. The data source corresponding to each node identification data is determined as a data node. The huge data set is reasonably distributed and organized so that each data node can be correctly identified and managed throughout the process. By corresponding the data node to its identification data one by one, the data source and content of each node can be effectively tracked. Finally, based on all data nodes and node identification data, multiple data node sets in the industrial production environment can be constructed. These sets are highly abstract of the data distribution in the entire production environment, and they reflect the aggregation status of different categories of safety production information. These node collections lay the foundation for further analysis and processing, helping to identify potential associations and risk propagation pathways.

[0049] In one possible implementation, see Figure 2 S200, based on the safety production information in the industrial production environment, obtain a plurality of data node sets of the industrial production environment, including:

[0050] S210, classify and identify the safe production information in the industrial production environment to obtain all node identification data in the industrial production environment; wherein all node identification data includes identification information of all data sources of the safe production information.

[0051] It can be understood that the acquired safety production information can be classified and identified. Node identification data refers to the unique identifier of each data source, which may be the equipment ID, sensor number, coordinates of the monitoring point, etc. By classifying and identifying the acquired safety production information, the identity of each data source can be clearly identified, and the foundation for its management and analysis in the risk identification process can be laid. The safety production information can be preliminarily classified according to the pre-set classification rules. For example, it can be classified according to dimensions such as equipment type, data type (such as temperature, pressure, vibration, etc.), and data source (such as sensor, manual input, etc.). Then, one or more identifiers will be assigned to each data point, which will serve as the key basis for identifying and processing data in subsequent steps. These identification data include not only the identity information of each data node, but also the location information, type information, function information, etc. of the node. These data will be recorded in the database to provide basic data support for the subsequent node determination and the formation of data sets.

[0052] S220: Based on all node identification data in the industrial production environment, determine a data source corresponding to each node identification data as a data node in the industrial production environment.

[0053] It can be understood that the data source corresponding to each identification data can be determined as a specific data node based on all the generated node identification data. That is, the abstract identification data is matched with the actual physical or virtual data source to form a complete data node. A data node refers to an independent unit that can collect, process or transmit data in an industrial production environment. Each identification data can be checked to confirm its source and type, and by comparing it with predefined standards, it is determined whether it meets the conditions of becoming a data node. For example, the identification data of a temperature sensor may contain information such as the sensor's ID, installation location, type, and monitoring range. By analyzing this information, it is determined whether the sensor can be managed as an independent data node. In the process of determining the data node, for example, a device may contain multiple sensors, each of which can be used as an independent data node. In addition, some virtual data nodes, such as predicted data nodes generated by calculation, can also be identified as independent nodes. Ultimately, all identification data are accurately mapped to specific data sources to form multiple data nodes in an industrial production environment. Each data node will serve as a basic unit for analysis and management in subsequent steps, and their accurate determination is crucial to the formation of the entire data node set.

[0054] S230, obtaining a plurality of data node sets of the industrial production environment according to all data nodes and all node identification data in the industrial production environment.

[0055] It can be understood that all previously identified and determined data nodes and node identification data can be integrated to form multiple data node sets. Data node sets are a way to manage a large number of data nodes in groups so that the massive data in the production environment can be processed and analyzed more efficiently. The formation of data node sets can be based on specific rules and standards, for example, grouping by dimensions such as device type, geographical location, functional use, etc. For example, in a complex production environment, there may be data nodes of multiple device types (such as temperature sensors, pressure sensors, vibration sensors), and these nodes can be grouped by device type to form different node sets. Similarly, groups can also be made based on the location of the node (such as workshop, production line, factory) or the function of the node (such as monitoring, control, early warning). The formation of data node sets not only helps the structured management of data, but also facilitates subsequent data analysis. For example, by analyzing the same type of data node set, the security risks of a specific type of equipment or area can be identified. In addition, the node set can also better understand the association between different data nodes, so that more targeted security management measures can be taken when necessary.

[0056] Optionally, S230, see Figure 3 , based on all data nodes and all node identification data in the industrial production environment, multiple data node sets of the industrial production environment are obtained, including:

[0057] S231, determining association relationship information between data nodes based on all data nodes and all node identification data in the industrial production environment; wherein the association relationship information is used to reflect the association status between different data nodes.

[0058] It can be understood that direct or indirect connections between different data nodes can be identified, which are critical to understanding the security dynamics in the production environment. The association information reflects the mutual influence between data nodes. They can be physical connections (such as cables, network connections) or functional dependencies (such as the data from one sensor affects the operation of another control device). The physical association between nodes can be preliminarily determined by analyzing the identification data and location data of the data nodes. For example, two physically adjacent sensors may aggregate data through the same controller. Such physical proximity can be regarded as an association relationship. Next, the functional relationship between data nodes can be analyzed. For example, the reading of a temperature sensor may directly affect the operating status of a heating device. This causal relationship is also an important association relationship. When determining the association relationship, the data nodes can be regarded as nodes in the graph and the association relationships between nodes can be regarded as edges in the graph by identifying the pre-established data source relationship mapping table and using graph theory or network analysis methods.

[0059] S232: Cluster all data nodes according to the association relationship information between the data nodes.

[0060] It can be understood that according to the determined association relationship information between data nodes, all data nodes can be clustered. Clustering is the process of grouping data nodes with similar characteristics or association relationships. Through clustering, a large number of data nodes can be divided into several groups, so that the data nodes in each group have a high degree of similarity in some aspects, while the differences between groups are large. The process of clustering analysis can be to use algorithms to identify similarities between data nodes. These similarities may be based on multiple dimensions such as physical proximity, functional similarity, and strength of association relationship. Commonly used clustering algorithms include K-means clustering, hierarchical clustering, DBSCAN, etc. A suitable algorithm can be selected according to the actual situation for clustering analysis. In an industrial production environment, clustering analysis helps to better understand the distribution and structure of data nodes. For example, it may be found that the sensor data of some equipment show similar change trends in the same time period, which may indicate that these equipment have some functional association. By clustering the sensor data nodes of these devices together, their operating status can be more effectively monitored, and coordinated control measures can be taken when necessary.

[0061] S233, based on the result of clustering all the data nodes, obtain multiple data node sets of the industrial production environment; wherein each data node set includes at least one data node.

[0062] It can be understood that based on the results of cluster analysis, the grouping of data nodes can be further refined and optimized, and finally multiple data node sets of the industrial production environment are formed. The data node set is a set of nodes that can be considered to have similarity or correlation in certain specific dimensions after cluster analysis. The task at this stage is to convert the results of cluster analysis into actual operation units. Each data node set will contain one or more data nodes, which may be classified into one category because of their close geographical location, similar functions, consistent data performance or indirect influence. Through this grouping, various types of safety production information in the industrial production environment can be managed and monitored more efficiently. These data node sets will be used for safety information path determination and safety information network construction in subsequent steps. For example, all sensor nodes on the same production line can be grouped into one set to better monitor the overall operation status of the production line. Similarly, it is also possible to group all sensor data nodes of the same type of equipment into one group according to the equipment type for unified performance evaluation and fault diagnosis.

[0063] S300, determining multiple security information paths based on multiple data node sets in an industrial production environment; wherein the security information paths are used to reflect the association between data at data collection points.

[0064] It can be understood that multiple data node sets can be used to further analyze the relationship between these sets and ultimately determine multiple safety information paths. A safety information path refers to one or more paths that reflect the relationship between data at data collection points in an industrial production environment. These paths can help understand the mutual influence between different data nodes and potential risk propagation pathways. Determining multiple safety information paths is to identify the correlation between data node sets. Each data node set may contain multiple nodes, and there are complex correlations between these nodes, such as data flow, causal relationships, or physical connections. By analyzing these relationships, the central node of each data node set and the connection paths between these central nodes can be determined.

[0065] In one possible implementation, see Figure 4 ,The safety production information includes historical safety production information ,S300, based on multiple data node sets of the industrial ,production environment, and determines multiple safety information paths, including:

[0066] S310, based on multiple data node sets in the industrial production environment, determine a central node of each data node set.

[0067] It can be understood that based on the previously formed data node set, the central node in each set is determined. The central node refers to the node with the highest relevance or importance in the data node set. The purpose of determining the central node is to further analyze the internal structure of the data node set and the relationship between them and other sets. The determination of the central node can be based on indicators such as the degree centrality, connection strength, and data flow of the node. For example, in a data node set, a node with a higher degree centrality usually has more connections with other nodes and is therefore regarded as the central node of the set. These indicators can be calculated using graph theory algorithms or network analysis techniques to determine the central node of each set. Central nodes play a key role in safety information path analysis because they are usually the core of data flow and information dissemination. In an industrial production environment, the central node may be a controller of a key device, an important sensor, or a data aggregation point. The operating status and security of these nodes directly affect the safety status of the entire data node set. By determining the central node of each data node set, the internal structure of these sets can be better understood and basic data can be provided for subsequent path analysis. The determination of the central node can also help optimize the design of the safety information network and ensure that information can be transmitted efficiently and reliably in the network.

[0068] Optionally, see Figure 5 , S310, based on multiple data node sets of the industrial production environment, determining a central node of each data node set, including:

[0069] S311, based on multiple data node sets in an industrial production environment, calculate the number of adjacent nodes of each data node in each data node set.

[0070] It can be understood that the number of adjacent nodes of each data node in each data node set can be calculated. The number of adjacent nodes refers to the number of other data nodes directly connected to a certain data node. The number of adjacent nodes is used to measure the degree of connection and importance of the data node in the set. The process of calculating the number of adjacent nodes usually involves analyzing the graph structure of the data node set. Each data node is regarded as a node in the graph, and the connection relationship between the nodes is regarded as the edge in the graph. By analyzing these connection relationships, the number of adjacent nodes of each data node can be calculated. The calculation result of the number of adjacent nodes reflects the position and role of the data node in the set. For example, a data node with a large number of adjacent nodes is usually located in the center of the set and has extensive connections with other nodes. Such nodes play an important role in information transmission and data processing, so they are usually given priority in the subsequent central node determination process.

[0071] S312, calculating the degree centrality of each data node in each data node set according to the number of adjacent nodes of each data node in each data node set; wherein the degree centrality is used to measure the importance of the data node.

[0072] It can be understood that the number of adjacent nodes of each data node can be calculated, and the central node of each data node set can be further determined. The central node is the node with the greatest influence and connectivity in the set, and it plays a core role in the collection, transmission and processing of data. The process of determining the central node is to evaluate the role and position of each data node in the set to identify the most important nodes. For an undirected graph, the degree centrality C of each node D (v) is the degree of the node (i.e., the number of edges directly connected to the node), which is calculated as: C D (v)=deg(v), deg(v) represents the degree of node v, that is, the number of other nodes connected to node v. To standardize the degree centrality (to make its value between 0 and 1), the following formula can be used: D (v) = deg(v) / n−1, where n is the total number of nodes in the network and n−1 represents the maximum possible degree of node v (i.e., it is connected to all other nodes in the network).

[0073] S313, determining the central node of each data node set according to the degree centrality of each data node in each data node set.

[0074] It can be understood that once the degree centrality calculation is completed, the degree centrality of all data nodes can be sorted. Nodes with higher degree centrality are usually key nodes in the network because they are directly connected to more nodes and can transmit information more effectively. In the set of data nodes, the node with the highest degree centrality can be regarded as the central node of the set. The role of this node in the network is crucial because it connects the most other nodes and can maximize the influence on the information flow and risk propagation of the entire network. Therefore, the central node of each data node set can be selected according to the degree centrality. By accurately identifying and managing the central nodes, the performance of the network can be optimized and the efficiency and effectiveness of risk management can be improved.

[0075] S320, determining a central association path of each data node set according to historical production safety information and the central node of each data node set.

[0076] It can be understood that the central node of each data node set can be used to analyze and determine the associations between these sets. The associations between multiple data node sets reflect how different sets influence each other and the data flow paths between them. The clarification of these relationships helps to build a comprehensive safety information network to support risk assessment and safety management in industrial production environments. First, the central node of each data node set can be used as the starting point for analysis to explore the direct or indirect connections between these nodes. The connection may be manifested as a physical connection (such as a network cable, communication channel), a logical connection (such as data dependency, control signal transmission), or a functional association (such as the output data of one node is used as input by another node). By analyzing these connections, the associations between different data node sets can be identified. Network analysis and graph theory algorithms can be used to construct a graph structure representing the relationship between multiple data node sets with the central node as the hub. In this graph, the node represents the central node of the data node set, and the edge represents the association between the sets. By analyzing the topological structure of the graph, the critical path, the influence of the node, and the potential bottleneck points can be identified. Determining the association between data node sets not only helps to understand the data flow pattern in the entire industrial production environment, but also helps to predict potential risk propagation paths. For example, if a central node in a data node set fails, the scope and extent of the possible impact of the failure can be predicted by analyzing its association with other sets, so that preventive measures can be taken in time.

[0077] Optionally, see Figure 6, S320, determining the central association path of each data node set according to the historical production safety information and the central node of each data node set, including:

[0078] S321, calculating the central correlation degree between each data node in each data node set and the central node according to the historical production safety information and the central node of each data node set.

[0079] It can be understood that the central relevance of each data node to the central node is calculated based on the historical safety production information and the central node of each data node set. The central relevance is used to measure the strength of the relationship between each data node and the central node, as well as the possible influence in the network. The central relevance is used to represent the relevance between one node and another node. In this step, the central relevance is used to represent the relationship between each data node and the central node in the set. The specific calculation method may include a distance-based algorithm (such as the shortest path), an information flow-based analysis (such as information flow), or a statistical analysis based on historical data (such as the frequency of historical simultaneous events). The distance-based central relevance can be calculated by calculating the path length between each node and the central node. The shorter the path, the higher the relevance. The information flow-based central relevance can determine the frequency and intensity of information transmission between nodes by analyzing the information flow pattern in the historical data. The statistical analysis-based central relevance can be calculated by counting the number of simultaneous events between the node and the central node in the historical data. The more times, the higher the relevance. The purpose of calculating the central relevance is to better understand the role of each node in the network, especially their role in the dissemination of safety production information and risk management.

[0080] S322, compare the central relevance of each data node in each data node set with the central node, and determine the central relevance order of each data node set; wherein the central relevance order is used to reflect the relationship between each data node and the central node from large to small.

[0081] It can be understood that the central relevance of each data node with the central node can be compared, and the central relevance order in each data node set can be determined based on these relevances. The central relevance order is used to reflect the strength ranking of the relationship between each data node and the central node, thereby revealing the most important path in the information dissemination process. The central relevance order can be determined by sorting the relevance of each data node. Nodes with higher relevance are ranked higher in the order, indicating that they have a closer relationship with the central node and have a greater impact on the overall information dissemination. This sorting is of great significance for understanding the network structure and optimizing the information flow path. Based on the calculated central relevance, each data node can be sorted from high to low by relevance. The central relevance order can help identify nodes that need to be prioritized in emergency situations and the most critical nodes in information dissemination.

[0082] S323, obtaining the center association path of each data node set according to the center association degree order of each data node set.

[0083] It can be understood that according to the central correlation order of each data node set, the central correlation path of each data node set is obtained. The central correlation path is gradually constructed based on the central correlation order determined in the previous step, reflecting the dominant relationship of the data node in the process of security information dissemination and the main direction of information flow. Through the construction of this path, the key nodes and key paths in the industrial production environment can be identified for better safety management and risk control. First, the central correlation order of each data node set is determined as the central correlation path order. The central correlation order reflects the importance ranking of each node relative to the central node, so it is directly converted into a path order to ensure that information is transmitted in the network in the optimal order. The system gradually establishes connections based on the correlation between the central node and other nodes, starting from the node with the highest correlation and connecting to the nodes with lower correlation in turn. This process ensures that the information can pass through the most important nodes first when flowing in the path, and maximizes the integrity and reliability of the information. Next, according to the central correlation path order, the data nodes will be connected one by one to form a complete central correlation path. The nodes can be arranged in sequence, and the path can be gradually constructed according to the correlation between these nodes. In the process of constructing the path, not only the size of the correlation is taken into account, but also the historical safety production information, the physical or logical connection between nodes, and the potential safety risk factors. These factors work together to ensure that the constructed path is not only the optimal path in theory, but also the best information dissemination path that adapts to the needs of the actual production environment. Finally, according to the central association path of each data node set, all nodes are organically connected together to form a coherent and practical central association path. This path reflects the process of how safety information starts from the central node and gradually expands to other nodes in the industrial production environment. In this way, the logical chain of information dissemination can be clearly presented, providing a solid foundation for the subsequent construction of a safety information network. This path is not only used for daily information transmission management, but also can be used as a basis for rapid response in emergency situations, so that necessary actions can be taken in the shortest time to avoid potential safety risks.

[0084] For example, see Figure 7 , S323, according to the central association degree order of each data node set, obtain the central association path of each data node set, including:

[0085] S3231, determining the center association degree order of each data node set as the center association path order of each data node set.

[0086] It can be understood that the previously determined center association order can be directly used to construct the center association path order of each data node set. This process is based on the sorting results of the center association, reflecting the relative importance of each node in the entire set. The center association order is determined by calculating the association relationship between each node and the center node. The nodes with higher associations are ranked higher in the order, which means that these nodes play a more prominent role in information dissemination and risk management. The association analysis can be performed on all nodes of each data node set first, and the association values ​​of all nodes are sorted from high to low. This sorting process is not just a simple arrangement, but also involves evaluating the actual significance of the association. For example, in an industrial production environment with a complex network structure, some nodes may have a high association due to their high frequency of information interaction, and these nodes will be given priority in the sorting process. The key to determining the center association path order is to ensure that information can be effectively propagated along these high-association node paths. Nodes with higher associations are usually the core points of information transmission, which means that these nodes are more likely to become key forwarding nodes during information dissemination. Therefore, using the relevance order directly as the path order can ensure that information is transmitted in the network along the best route, thereby minimizing the delay and loss in the process of information transmission.

[0087] S3232, obtaining the central association path of each data node set according to the central association path sequence of each data node set.

[0088] It can be understood that the central association path of each data node set can be actually constructed based on the determined central association path sequence. The previous theoretical order is converted into an actual path connection to ensure that all data nodes can interact and transmit information in a pre-set order. The nodes in each data node set are gradually connected to form a complete path in the path sequence. This path is not only a physical connection between data nodes, but also represents the order and logical relationship of information propagation between these nodes. Through the construction of this path, it can be ensured that the flow of information in the network is efficient and seamless, thereby minimizing interruptions and delays in the information transmission process. After the path is constructed, the central association path of each data node set will become the main channel for information transmission in the set. This path is not only used for daily security information transmission, but also can be used as a rapid response channel in emergency situations to avoid potential security risks.

[0089] S330, obtaining multiple security information paths according to the central association path of each data node set.

[0090] It can be understood that the safety information path is a key channel for transmitting, monitoring and managing safety production information. The design and optimization of these paths directly affect the efficiency and reliability of the entire safety management process. The central node of each data node set can be regarded as the key point in the path, and the optimal connection path between these key points can be determined based on the analyzed central association path. The determination of the safety information path also involves the security assessment of each node on the path. It is necessary to ensure that all nodes on the path have sufficient security and stability to support efficient information transmission. For nodes that may have security risks, additional protection measures need to be taken, such as increasing monitoring, strengthening data encryption, or restricting access rights, to prevent information leakage or tampering. Once the safety information path is determined, these paths can be recorded in the database and deployed in actual operations. By monitoring the data flow on the path in real time, potential problems can be discovered and solved in a timely manner to ensure the continuity and reliability of information transmission.

[0091] S400, constructing a security information network for the industrial production environment based on multiple security information paths; wherein the security information network is used to reflect the security risk association status of the industrial production environment.

[0092] It can be understood that a complete safety information network can be further constructed based on the determined multiple safety information paths. The safety information network is a data transmission and safety management system covering the entire industrial production environment. It is responsible for real-time monitoring and transmission of various types of safety production information and providing decision support when necessary. All determined safety information paths can be integrated to form a structured network diagram. In this network diagram, nodes represent various types of equipment, sensors, and data processing units in the production environment, and paths represent data transmission channels between these nodes. By optimizing and configuring these paths, it can be ensured that all safety production information can be transmitted efficiently and reliably through the network.

[0093] In one possible implementation, see Figure 8 ,S400, builds a safety information network for industrial production environments based on multiple safety information paths, including:

[0094] S410, determining, according to multiple security information paths, a connection relationship between each data node in each security information path.

[0095] It can be understood that, based on the constructed security information network, the specific connection relationship between each data node in each security information path can be deeply analyzed and determined, and the data transmission chain on each path can be identified, thereby laying the foundation for subsequent security management and risk analysis. Based on the existing security information network structure, all data nodes on the path can be combed one by one from the starting node of the path. The connection relationship between these nodes may involve various forms, including physical connection (such as network cable or wireless signal transmission), logical connection (such as data call at the software level), and functional connection (such as control signal transmission between devices). For each connection, its type, characteristics and transmission method will be recorded in detail. In the combing process, attention can be paid to the transmission protocol and data format between nodes. In a complex industrial production environment, different nodes may use different communication protocols and data formats for information exchange. In order to ensure that data can be transmitted smoothly in the path, these protocols and formats can be analyzed and adapted. Through technical means such as protocol conversion and data format standardization, seamless data transmission between different nodes can be achieved to avoid data loss or mistransmission due to incompatibility. In order to further improve the security of the path, a security audit can be performed on each connection point. The audit content includes but is not limited to: data encryption methods, authentication mechanisms, firewall settings, and potential network threats. Through comprehensive security audits, potential security vulnerabilities can be discovered and repaired in a timely manner to ensure the security of data transmission. After determining the connection relationship of each path, a detailed connection diagram can be generated and stored in the database. These connection diagrams not only provide an important reference for subsequent risk analysis and emergency response, but also provide data support for subsequent maintenance and optimization. Finally, all connection relationships can be dynamically monitored. Due to the highly dynamic nature of the industrial production environment, the connection relationship between nodes may change over time or as production conditions change.

[0096] S420, constructing a network topology structure of the industrial production environment according to the connection relationship between each data node in each security information path.

[0097] It can be understood that the network topology is the core framework of the security information network, which determines how data is transmitted, processed and stored in the entire production environment. All security information paths can be integrated to generate a global network topology diagram. In this diagram, nodes represent data collection points, processing units or control devices, and edges represent the connection relationship between these nodes. By analyzing the structure of the topology diagram, it is possible to identify the key nodes in the network, the trunk path of data flow, and possible bottlenecks. When building a network topology, you can choose the topology mode that best suits the current production environment. Common topology modes include star, ring, bus, tree and mesh structures. Each topology has its own unique advantages and disadvantages. You can choose the most suitable topology based on actual needs, node distribution, data traffic and other factors. For example, in a highly distributed production environment, a mesh structure may be more suitable because it can provide higher fault tolerance and path redundancy; while in a centralized production environment, a star structure may be more efficient. After the topology is built, it can be fully simulated and tested. By simulating various production scenarios and abnormal situations, the reliability, response speed and fault tolerance of the network can be evaluated. Finally, an efficient, stable and flexible network topology is constructed. Through the topology, it is possible to ensure efficient transmission of safety information in the entire industrial production environment, providing strong support for the monitoring and management of safe production.

[0098] S430, obtaining a security information network of the industrial production environment according to the network topology of the industrial production environment.

[0099] It can be understood that based on the network topology of the constructed industrial production environment, a complete safety information network is eventually formed. The safety information network is the nervous system of the entire industrial production environment. It is responsible for real-time monitoring, transmission and management of various types of safety production information to ensure the smooth progress of the production process. The configuration of nodes and paths can be further optimized based on the existing network topology. The construction of a safety information network is not just a simple node connection, but also needs to take into account the overall performance and security of the network. The key nodes and paths in the topology can be monitored and optimized. For example, for those nodes that carry key data flows, higher bandwidth, high-level firewall protection and faster response time can be configured to ensure that these nodes can still maintain stable operation under high load. Connect various types of safety production information to this network. Different safety information may come from different data sources, such as sensors, monitoring equipment, control systems, etc. A dedicated channel can be assigned to each type of information and the corresponding priority can be set. For example, alarm information with high real-time requirements will be transmitted first, while historical records with large data volumes may be transmitted in batches through channels with lower priorities. Through the safety information network, network resources can be reasonably scheduled to ensure the timely delivery of important information.

[0100] S500, conducts risk management for industrial production environments based on their security information networks.

[0101] It can be understood that risk management of industrial production environment can be carried out based on the complete safety information network constructed. Risk management is the core activity to ensure production safety. Through the analysis and utilization of the safety information network, possible safety risks can be identified, evaluated and responded to, thereby maintaining the smooth progress of the production process. Risk identification can be carried out using various data collected in the safety information network. The safety information network provides comprehensive production environment data, including equipment operating status, environmental parameters, sensor readings, alarm information, etc. Through the analysis of these data, potential safety hazards such as equipment failure, abnormal environmental conditions, and operational errors can be identified. Risk identification usually involves data mining and pattern recognition technology. Through the analysis of historical data and real-time data by algorithm models, abnormal situations and potential risks can be accurately detected and risk assessment can be carried out. The purpose of risk assessment is to classify and quantify the identified risks and determine their potential impact on the production process. Risks can be scored and ranked according to factors such as the severity of the risk, the probability of occurrence, and the scope of impact. The results of risk assessment will help managers understand which risks are the most serious and which risks need to be handled first. During the assessment process, a variety of tools and methods can be used, such as risk matrix, failure mode effect analysis (FMEA), fault tree analysis (FTA), etc., to ensure the comprehensiveness and accuracy of the assessment. Risk management is a dynamic process, and the production environment and risk conditions may change over time. Therefore, it is necessary to monitor various data in the production process in real time to promptly discover and deal with new risks. By accurately identifying and assessing risks, the safety and stability of the production process can be effectively protected and the smooth progress of production activities can be ensured.

[0102] In one possible implementation, see Fig. 9 , S500, based on the safety information network of the industrial production environment, conducts risk management for the industrial production environment, including:

[0103] S510, obtaining a security risk propagation path of the industrial production environment according to the security information network of the industrial production environment.

[0104] It can be understood that the constructed safety information network can be used to determine the safety risk propagation path in the industrial production environment. The safety risk propagation path refers to the path from the source to the impact point in the production environment, so as to understand how the risk propagates in the network and formulate effective prevention and control measures. The nodes and connection relationships in the safety information network can be analyzed in detail. Each node represents a data collection point, equipment or control system, and each connecting line represents the path of data flow. Through the comprehensive analysis of these nodes and connecting lines, the potential risk propagation path can be identified. The identification of the risk propagation path can be a path algorithm in graph theory, such as the shortest path algorithm, the minimum spanning tree algorithm, etc., to find the most likely path from the risk source to the potential impact point. After determining the risk propagation path, the propagation speed and impact range of each path can be evaluated. The propagation speed involves the speed of risk propagation in the path, which is related to factors such as data transmission rate, device response time, and network bandwidth. The impact range refers to the nodes and areas that the risk may involve in the process of propagation. Through the analysis of these factors, the possible impact of the risk can be predicted and prepared in advance.

[0105] S520, conduct risk management of the industrial production environment based on the safety risk propagation path of the industrial production environment.

[0106] It can be understood that, based on the determined safety risk propagation path, the focus of risk management for the industrial production environment is to formulate and implement specific risk control and response measures based on the identified risk propagation path to reduce the impact of risks on the production environment and ensure the safety and stability of the production process. The safety risk propagation path can be combined with the actual production environment to analyze the specific risk points that may exist on each path. This includes key nodes, equipment, sensors, etc. in the path, which may become the source or propagation path of risks. Specific control measures can be formulated based on the nature of the path and the characteristics of the risk points. For example, for the path of transmitting data, data encryption and verification can be added; for key equipment, monitoring and maintenance can be strengthened to prevent equipment failure. When a risk is found in a certain path node, the entire path and related paths can be monitored and fed back in real time based on the safety risk path. By monitoring the data flow, equipment operating status and environmental parameters in the system, it is possible to promptly discover abnormal situations related to risk situations, and promptly discover and deal with potential risk issues based on actual conditions. It is possible to systematically interconnect and analyze various safety data, comprehensively and timely identify possible transmission paths of safety risks, ensure the safety and stability of the industrial production environment, effectively respond to various potential risks, and protect the smooth progress of the production process.

[0107] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0108] Corresponding to the industrial Internet-based safety production information processing method described in the above embodiment, the embodiment of the present application also provides an industrial Internet-based safety production information processing system, and each unit of the system can implement each step of the industrial Internet-based safety production information processing method. Fig.10 A structural block diagram of an industrial Internet-based safe production information processing system provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0109] Reference Fig.10 , the industrial Internet-based safe production information processing system includes:

[0110] An acquisition unit, used to acquire safety production information in an industrial production environment; wherein the safety production information is used to reflect the safety status of each link of the industrial production environment;

[0111] A collection unit, used to obtain a plurality of data node sets of the industrial production environment according to the safety production information in the industrial production environment; wherein the data node set is used to reflect the collection data of multiple data collection points in the industrial Internet;

[0112] A path unit, used to determine a plurality of security information paths based on a plurality of data node sets of the industrial production environment; wherein the security information paths are used to reflect the association between the data of the data collection points;

[0113] A network unit, used to construct a security information network of the industrial production environment according to the plurality of security information paths; wherein the security information network is used to reflect the security risk association of the industrial production environment;

[0114] A management unit is used to perform risk management on the industrial production environment according to the security information network of the industrial production environment.

[0115] It should be noted that the information interaction, execution process, etc. between the above-mentioned systems / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0116] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit module can exist physically separately, or two or more unit modules can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0117] The present application also provides a safety production information processing device based on the industrial Internet. Fig.11 This is a schematic diagram of the structure of a safe production information processing device based on the industrial Internet provided in one embodiment of the present application. Fig.11 As shown, the industrial Internet-based safe production information processing device 6 of this embodiment includes: at least one processor 60 ( Fig.11 Only one is shown), at least one memory 61 ( Fig.11 Only one is shown in the figure) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, the industrial Internet-based production safety information processing device 6 implements the steps in any of the above-mentioned industrial Internet-based production safety information processing method embodiments, or enables the industrial Internet-based production safety information processing device 6 to implement the functions of each unit in the above-mentioned system embodiments.

[0118] Exemplarily, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 62 in the industrial Internet-based safety production information processing device 6.

[0119] The industrial Internet-based safe production information processing device 6 can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The industrial Internet-based safe production information processing device can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that Fig.11 It is only an example of the safe production information processing device 6 based on the industrial Internet and does not constitute a limitation on the safe production information processing device 6 based on the industrial Internet. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, buses, etc.

[0120] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0121] In some embodiments, the memory 61 may be an internal storage unit of the industrial Internet-based production safety information processing device 6, such as a hard disk or memory of the industrial Internet-based production safety information processing device 6. In other embodiments, the memory 61 may also be an external storage device of the industrial Internet-based production safety information processing device 6, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the industrial Internet-based production safety information processing device 6. Further, the memory 61 may also include both the internal storage unit of the industrial Internet-based production safety information processing device 6 and an external storage device. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0122] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0123] An embodiment of the present application provides a computer program product. When the computer program product runs on a safe production information processing device based on the industrial Internet, the safe production information processing device based on the industrial Internet implements the steps in any of the above-mentioned method embodiments.

[0124] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the industrial Internet-based safety production information processing equipment, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0125] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0126] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0127] In the embodiments provided in the present application, it should be understood that the disclosed industrial Internet-based production safety information processing system / industrial Internet-based production safety information processing device and method can be implemented in other ways. For example, the above-described industrial Internet-based production safety information processing system / industrial Internet-based production safety information processing device embodiment is merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0128] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0129] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for processing safe production information based on industrial Internet, characterized in that: include: Acquire safety production information in an industrial production environment; wherein the safety production information is used to reflect the safety status of each link of the industrial production environment; According to the safety production information in the industrial production environment, a plurality of data node sets of the industrial production environment are obtained; wherein the data node sets are used to reflect the collective data of a plurality of data collection points in the industrial Internet; Based on the plurality of data node sets of the industrial production environment, a plurality of security information paths are determined; wherein the security information paths are used to reflect the association between the data of the data collection points; According to the plurality of security information paths, a security information network of the industrial production environment is constructed; wherein the security information network is used to reflect the security risk association of the industrial production environment; Performing risk management on the industrial production environment according to the security information network of the industrial production environment; Wherein, the multiple data node sets of the industrial production environment are obtained based on the production safety information in the industrial production environment, including: Classify and identify the production safety information in the industrial production environment to obtain all node identification data in the industrial production environment; wherein the all node identification data includes identification information of all data sources of the production safety information; Based on all the node identification data in the industrial production environment, determining a data source corresponding to each node identification data as a data node in the industrial production environment; According to all the data nodes and all the node identification data in the industrial production environment, a plurality of data node sets of the industrial production environment are obtained; The safety production information includes historical safety production information, and based on the plurality of data node sets of the industrial production environment, a plurality of safety information paths are determined, including: Based on the multiple data node sets of the industrial production environment, determine the central node of each data node set; Determine a central association path of each data node set according to the historical production safety information and the central node of each data node set; Obtaining a plurality of security information paths according to the central association path of each of the data node sets; The step of constructing a security information network for the industrial production environment according to the plurality of security information paths includes: Determining, according to the plurality of security information paths, a connection relationship between each of the data nodes in each of the security information paths; Constructing a network topology structure of the industrial production environment according to the connection relationship between each of the data nodes in each of the security information paths; According to the network topology of the industrial production environment, a security information network of the industrial production environment is obtained; The step of performing risk management on the industrial production environment according to the security information network of the industrial production environment comprises: Obtaining a security risk propagation path of the industrial production environment according to the security information network of the industrial production environment; Risk management is performed on the industrial production environment based on the safety risk propagation path of the industrial production environment.

2. The method for processing safe production information based on the industrial Internet according to claim 1, characterized in that: The step of obtaining a plurality of data node sets of the industrial production environment based on all the data nodes and all the node identification data in the industrial production environment includes: Determine the association relationship information between the data nodes based on all the data nodes and all the node identification data in the industrial production environment; wherein the association relationship information is used to reflect the association status between different data nodes; Clustering all the data nodes according to the association relationship information between the data nodes; Based on the result of clustering all the data nodes, a plurality of data node sets of the industrial production environment are obtained; wherein each of the data node sets includes at least one data node.

3. The method for processing safe production information based on the industrial Internet according to claim 1, characterized in that: The step of determining a central node of each of the plurality of data node sets based on the industrial production environment includes: Based on the plurality of data node sets of the industrial production environment, calculating the number of adjacent nodes of each data node in each of the data node sets; According to the number of adjacent nodes of each data node in each data node set, the degree centrality of each data node in each data node set is calculated; wherein the degree centrality is used to measure the importance of the data node; According to the degree centrality of each data node in each data node set, a central node of each data node set is determined.

4. The method for processing safe production information based on the industrial Internet according to claim 3, characterized in that: The determining, according to the historical production safety information and the central node of each data node set, a central association path of each data node set comprises: Calculate the central relevance between each data node in each data node set and the central node according to the historical production safety information and the central node of each data node set; Comparing the central relevance between each data node in each data node set and the central node, and determining the central relevance order of each data node set; wherein the central relevance order is used to reflect the relationship between each data node and the central node from large to small; According to the center association degree order of each data node set, the center association path of each data node set is obtained.

5. The method for processing safe production information based on the industrial Internet according to claim 4, characterized in that: The step of obtaining the center association path of each data node set according to the center association degree order of each data node set includes: Determine the center association degree order of each data node set as the center association path order of each data node set; The central association path of each data node set is obtained according to the central association path sequence of each data node set.

6. A safe production information processing system based on industrial Internet, characterized in that: For implementing the method according to any one of claims 1 to 5, the industrial Internet-based safe production information processing system comprises: An acquisition unit, used to acquire production safety information in an industrial production environment; wherein the production safety information is used to reflect the safety status of each link of the industrial production environment; A collection unit, used to obtain a plurality of data node sets of the industrial production environment according to the safety production information in the industrial production environment; wherein the data node set is used to reflect the collection data of multiple data collection points in the industrial Internet; A path unit, used to determine a plurality of security information paths based on a plurality of data node sets of the industrial production environment; wherein the security information paths are used to reflect the association between the data of the data collection points; A network unit, used to construct a security information network of the industrial production environment according to the plurality of security information paths; wherein the security information network is used to reflect the security risk association of the industrial production environment; A management unit is used to perform risk management on the industrial production environment according to the security information network of the industrial production environment.

Images