A PLC configuration network intelligent management method, system, device and medium

Abstract

This application relates to the field of PLC configuration management, and in particular to a method, system, medium, and device for intelligent management of PLC configuration networks. The method includes: constructing a two-dimensional dynamic configuration interface, which includes a communication protocol classification module, a device configuration visualization module, and a network topology tree module. The communication protocol classification module displays at least two protocol icons in a grid layout. In response to a first operation of dragging a protocol icon to the device configuration visualization module, a multi-level topology structure is generated through a recursive rendering algorithm. The multi-level topology structure includes couplers and updates with the device connection status. In response to a second operation of double-clicking a device node in the network topology tree module or dragging a device node to the device configuration visualization module, a device addition operation is performed. The device configuration visualization module identifies the online and offline status of devices through color coding, displays abnormal devices through dynamic identification, and adjusts the topology diagram of the device configuration visualization module by combining a multi-dimensional perspective.

Description

Technical Field

[0001] This application relates to the field of PLC configuration management, and in particular to a method, system, device and medium for intelligent management of PLC configuration networks. Background Technology

[0002] In industrial automation production, PLCs, as core control devices, need to communicate with various sensors, actuators, and third-party systems. Traditional PLC configuration management suffers from the following pain points: Cumbersome operation procedures, requiring manual addition of devices and configuration of parameters at each level, relying on specialized communication knowledge, and novices are prone to system failures due to configuration errors; Insufficient visualization, with device topology and communication status not dynamically displayed in real time, and mixed display of devices with multiple protocols leading to information confusion, such as the lack of logical distinction between RS485 and EtherCAT protocol devices on the same interface; Limited scalability, with complex bus (such as EtherCAT) branch topology management lacking an adaptive generation mechanism, parameter configurations easily confusing with actual device port mappings, and time-consuming troubleshooting.

[0003] In existing technologies, some solutions improve intuitiveness by displaying partitioned protocols and device trees, but they do not achieve dynamic topology adaptive generation, multi-protocol parallel visual management, and intelligent parameter optimization. There is still room for improvement in device management efficiency and user experience. Summary of the Invention

[0004] To address the issues of cumbersome operation and unintuitive interface in traditional PLC configuration management, this application provides a method, system, device, and medium for intelligent management of PLC configuration networks.

[0005] Firstly, this application provides an intelligent management method for PLC configuration networks, including: A two-dimensional dynamic configuration interface is constructed, which includes a communication protocol classification module, a device configuration visualization module, and a network topology tree module. The communication protocol classification module displays at least two protocol icons in a grid layout. In response to the first operation of dragging the protocol icon to the device configuration visualization module, a multi-level topology structure is generated by a recursive rendering algorithm. The multi-level topology structure includes multiple couplers and is updated with the device connection status. In response to a second operation, such as double-clicking a device node in the network topology tree module or dragging the device node to the device configuration visualization module, a device addition operation is performed. The device configuration visualization module uses color coding to identify the online and offline status of devices and displays abnormal devices through dynamic identification. It also combines multiple perspectives to adjust the topology of the device configuration visualization module.

[0006] By adopting the above technical solutions, a two-dimensional dynamic configuration interface is constructed, incorporating a grid-like protocol classification, visualized device configuration, and a network topology tree, enabling intuitive management of multi-protocol devices. The drag-and-drop protocol icon interaction with device nodes simplifies the process of adding devices and associating them with protocols, reducing reliance on specialized communication knowledge and solving the problem of cumbersome manual device addition. Furthermore, compared to the list-based protocol stack of existing technologies, the grid layout more clearly displays the classification relationships of various protocols, reducing the number of steps users need to take to find protocols.

[0007] In one specific implementation scheme, the recursive rendering algorithm includes: Based on the communication protocol, and combined with the physical connection order and communication priority of the devices, the node arrangement of the multi-level topology is adjusted. The multi-level topology includes a master station, an I / O coupler, and slave stations. The number of sub-modules and communication load of the IO coupler are monitored in real time. When the number of sub-modules exceeds a first threshold or the communication load exceeds a second threshold, a cascading suggestion is output and the cascading path is displayed through the topology diagram.

[0008] By adopting the above technical solution, the recursive rendering algorithm, combined with communication protocols, physical connection order, and communication priorities, adjusts the topology node arrangement to determine a multi-level topology and optimize data transmission paths. Real-time monitoring of the number of submodules and communication load of the IO coupler triggers cascading suggestions, avoiding communication congestion or equipment failure due to excessive load, significantly enhancing system stability. The cascading path is displayed through a topology diagram, allowing users to intuitively understand the expansion scheme.

[0009] In a specific feasible implementation, the intelligent management method for PLC configuration networks also includes: Based on the path optimization algorithm, the optimal deployment location of the secondary coupler is calculated. The secondary coupler is used to share the load of the I / O coupler. The cascading recommendations are displayed in the topology map using multiple identifiers, including marking the optimal deployment location, drawing the cascading path, and marking the expected benefits of the cascading recommendations.

[0010] By adopting the above technical solution, the optimal deployment location of the secondary coupler is calculated based on the path optimization algorithm, ensuring balanced load sharing and avoiding potential signal attenuation issues with the coupler. Multiple identifiers make cascading recommendations more specific, eliminating the need for users to calculate coupler locations and benefits themselves, thus reducing decision-making complexity.

[0011] In one specific implementation, the recursive rendering algorithm further includes: Each of the secondary couplers independently maintains the device list, communication parameters, and fault status of the sub-topology, and synchronizes data with the main topology according to a preset cycle. When a fault is detected in a certain stage coupler, the backup communication port of the downstream slave station of the faulty coupler is detected, and a new connection path is planned by combining the load margin of the normal coupler and the backup communication port. The fault coupler is identified in the topology diagram, and the connection path is displayed.

[0012] By adopting the above technical solution, the secondary coupler independently maintains its sub-topology and synchronizes data with the main topology, achieving modular management of the topology structure. The failure or adjustment of a single coupler will not affect the entire network, enhancing system scalability and anti-interference capabilities. In the event of a failure, the system automatically detects the backup communication ports of downstream slave stations and plans new paths, resolving local network paralysis caused by coupler failures and shortening fault recovery time. The identification of the faulty coupler and the display of the new path in the topology diagram enable maintenance personnel to quickly locate the fault point and perform repairs, further reducing the risk of system downtime.

[0013] In a specific feasible implementation, the intelligent management method for PLC configuration networks also includes: Decision support indicators are generated based on the multi-level topology, including load indicators, latency indicators, and cost indicators. The topology diagram displays the multi-level topology and variant structures, and labels the decision support indicators for each structure. The variant structures include the historical structure and virtual deployment structure of the multi-level topology. In response to a third user operation that adjusts the multi-level topology, the virtual deployment structure is generated, and the operating state is simulated for a preset period of time based on historical data to calculate the decision support index of the virtual deployment structure.

[0014] By adopting the above technical solutions, decision-making support indicators such as load, latency, and cost are generated. A topology diagram is used to display multi-level and variant topologies, providing users with quantitative optimization basis and avoiding the blindness of traditional experience-based topology adjustments. The virtual deployment structure's simulation operation function allows users to verify the effectiveness of adjustments before actual deployment, reducing costs caused by unreasonable solutions.

[0015] In a specific feasible implementation, the intelligent management method for PLC configuration networks also includes: The master station monitors the response status of the slave station. When the slave station's non-response time exceeds a third threshold, it sends an abnormal alarm and records the non-response time. When a failure of the master station is detected, the slave station with the highest priority is promoted to the master station based on the priority of each slave station, and the multi-level topology is updated.

[0016] By adopting the above technical solutions, the master station's response status monitoring and anomaly alarm mechanism for slave stations enables real-time monitoring of device communication status. Slave station offline issues can be detected promptly, preventing fault propagation. The function of automatically promoting the highest-priority slave station to master in the event of a master station failure solves the network paralysis problem caused by a single point of failure in existing technologies, significantly improving system redundancy and continuity.

[0017] In one specific implementation, the device addition operation includes: The intelligent decision engine outputs parameter optimization suggestions based on historical configuration data. The intelligent decision engine includes a deep learning model, which analyzes the correlation between protocol parameters and device operational stability in the historical configuration data and outputs the optimal parameter combination for adding the target device.

[0018] By adopting the above technical solutions, the intelligent decision engine outputs parameter optimization suggestions based on a deep learning model, overcoming the limitations of manually matching parameters. By analyzing the correlation between protocol parameters and device stability in historical data, the recommended optimal parameter combination can reduce device communication failure rates and decrease system debugging time caused by incorrect parameter configuration. The self-learning capability of the deep learning model can also continuously optimize the recommendation accuracy as the system runs, resulting in a sustained improvement in parameter configuration accuracy over long-term use.

[0019] Secondly, this application also provides a PLC configuration network intelligent management system, including: The interface configuration module is used to build a two-dimensional dynamic configuration interface that includes a communication protocol classification unit, a device configuration visualization unit, and a network topology tree unit. The topology generation module is used to execute the recursive rendering algorithm to generate a multi-level topology structure containing master station, IO coupler, and slave station based on the communication protocol; The cascading analysis module is used to monitor the number of sub-modules and communication load of the I / O coupler in real time and output cascading suggestions. The intelligent decision-making module includes an intelligent decision-making engine based on a deep learning model, which outputs the optimal combination of parameters when an operation is added to the device.

[0020] By adopting the above technical solution, the system achieves intelligent operation of the entire PLC network configuration process, from protocol management, topology generation, load analysis to fault handling, through the collaborative work of the interface configuration module, topology generation module, and cascading analysis module. The system modules are finely divided, data interaction is efficient, and it can support complex functions such as multi-protocol parallel management, dynamic topology adaptive adjustment, and intelligent parameter optimization.

[0021] Thirdly, this application also provides an electronic device, including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that the electronic device can perform a PLC configuration network intelligent management method.

[0022] Fourthly, this application also provides a computer-readable storage medium storing multiple instructions adapted for loading and execution by a processor of a PLC configuration network intelligent management method.

[0023] In summary, this application includes at least one of the following beneficial effects: 1. This application transforms the cumbersome manual PLC configuration process through dynamic interface interaction and automation mechanisms. The communication protocol classification module simplifies the steps of adding devices and binding protocols from a multi-level menu operation to an intuitive drag-and-drop interaction, improving operational efficiency and reducing reliance on specialized communication knowledge. The dynamic topology structure generated by the recursive rendering algorithm updates in real time according to the device connection status, eliminating the need for manual drawing or adjustment of the topology diagram.

[0024] 2. This application addresses the information confusion caused by the mixed display of multiple protocol devices in the configuration by achieving precise differentiation between protocols and topology through a layered visualization design. The grid layout of the communication protocol classification module realizes the physical partitioning of communication protocols, allowing users to quickly locate the target protocol; the device configuration visualization module presents the device status in real time, and with the multi-dimensional perspective adjustment function, it improves the readability of complex topology structures.

[0025] 3. This application addresses the limited scalability of complex buses in configuration through dynamic topology generation and intelligent cascading mechanisms. The recursive rendering algorithm supports cascading expansion of couplers. When the number of submodules or the load exceeds a threshold, it generates optimal deployment suggestions for secondary couplers. Users do not need to manually calculate expansion schemes. The system can adaptively support topology expansion from single couplers to multi-level nested structures, meeting the needs of different scales from small device networks to large industrial control systems. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating an intelligent management method for PLC configuration networks provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of the two-dimensional dynamic configuration interface provided in the embodiments of this application; Figure 3 This is another structural schematic diagram of the two-dimensional dynamic configuration interface provided in the embodiments of this application; Figure 4 This is a schematic diagram of the device configuration parameters provided in the embodiments of this application; Figure 5This is a schematic diagram of the master-slave management parameters provided in the embodiments of this application. Detailed Implementation

[0027] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0028] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0029] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0030] refer to Figure 1 This application provides a PLC configuration network intelligent management method. This method can be implemented using a computer program, a microcontroller, or run on a PLC configuration network intelligent management system. The computer program can be integrated into a computer device or run as a standalone application. Specifically, the method includes steps S100 to S400, as follows: S100. Construct a two-dimensional dynamic configuration interface, which includes a communication protocol classification module, a device configuration visualization module, and a network topology tree module. The communication protocol classification module displays at least two protocol icons in a grid layout. refer to Figure 2 and Figure 3 In some embodiments, the two-dimensional dynamic configuration interface can adopt a three-region structure of left-middle-right, with each module operating independently and data synchronized in real time.

[0031] The left side of the two-dimensional dynamic configuration interface features a communication protocol classification module with a grid layout. Each grid cell corresponds to a communication protocol (such as RS232, EtherCAT, EtherNet, ModbusTCP, etc.). Communication protocols are displayed using icons and text; for example, the EtherCAT protocol icon is a yellow bus symbol labeled "EtherCAT". A brief description of the communication protocol can be displayed by hovering the mouse over it.

[0032] The device configuration visualization module is deployed in the middle area of ​​the two-dimensional dynamic configuration interface. The device configuration visualization module is the core operation area. The initial state is a blank canvas. When the user drags the protocol icon from the left or adds the device from the right, the corresponding topology diagram is automatically generated. The overall position can be adjusted by dragging with the mouse. It is displayed in a centered manner by default.

[0033] refer to Figure 4 The right side of the two-dimensional dynamic configuration interface features a network topology tree module. This module displays all device nodes corresponding to various protocols in a hierarchical tree structure. Users can expand collapsed device nodes to browse more devices, and quickly locate devices by entering their model number in the search box at the top. Clicking on a device displays its parameters.

[0034] In some embodiments, when a user clicks on a protocol icon (such as EtherCAT) in the left-hand mesh communication protocol classification module, the right-hand network topology tree module automatically expands the device node branch corresponding to that communication protocol, and the middle device configuration visualization module displays the default topology template of that protocol; when a user drags a protocol icon to the middle area, the initial topology of that protocol is generated directly at the drag position, and the device addition state is activated.

[0035] S200, in response to the first operation of dragging the protocol icon to the device configuration visualization module, a multi-level topology structure is generated by a recursive rendering algorithm. The multi-level topology structure includes multiple couplers and is updated with the device connection status. Based on the above embodiments, as another optional embodiment, the recursive rendering algorithm may include: S201. Based on the communication protocol, and combined with the physical connection order and communication priority of the devices, adjust the node arrangement of the multi-level topology, which includes a master station, an IO coupler, and slave stations. refer to Figure 5Based on the selected communication protocol type, the basic hierarchical relationship of the multi-level topology is initialized, with different communication protocols corresponding to different topology frameworks. According to the actual wiring sequence of the devices, node positions are mapped sequentially in the basic framework to ensure consistency between the topology structure and physical connections. Based on the physical connection sequence and the preset communication priorities of the devices, the node arrangement is dynamically optimized to improve the communication efficiency of high-priority devices.

[0036] In this embodiment of the application, the master station refers to the core control node in the PLC configuration network, which is responsible for initiating communication requests, managing the network topology, allocating communication resources, and centrally controlling and interacting with slave devices; the IO coupler is an intermediate switching device connecting the master station and slave stations, mainly used to expand network interfaces, share the load of the master station, and support the cascading expansion of multiple sub-modules; the slave station is a terminal device in the network controlled by the master station, which responds to the master station's communication requests and executes specific tasks.

[0037] In some embodiments, the multi-level topology can correspond to the EtherCAT protocol. Specifically, the multi-level topology adopts a daisy-chain cascading framework of master station-IO coupler-slave station, with the master station as the root node, the IO coupler as the intermediate node, and the slave devices as the terminal nodes, supporting recursive nesting of IO couplers.

[0038] In some embodiments, the multi-level topology can also correspond to the EtherNet protocol. In this case, the multi-level topology adopts a master-slave star topology, with the master station in the center and the slave devices arranged radially according to their physical ports, without coupler cascading.

[0039] In some embodiments, the master station serves as the topology starting point, fixed on the left or top of the topology diagram. I / O couplers are arranged in the order of connection, and slave stations are arranged in the order of their physical ports. For example, in an EtherCAT network, the user first connects the I / O coupler to the EtherCAT port of the master station, then connects the servo motor to port 1 of the I / O coupler and the sensor to port 2. The topology is then arranged as master station - I / O coupler - servo motor - sensor. The servo motor and sensor are slave stations.

[0040] In some embodiments, the device's preset communication priority may include three levels: low, medium, and high. Users can manually set these levels in the device configuration interface, or the system can automatically assign them based on the device type. For example, a servo motor may be set to high communication priority, and a sensor to medium communication priority.

[0041] S202. Monitor the number of sub-modules and communication load of the IO coupler in real time. When the number of sub-modules is greater than a first threshold or the communication load is greater than a second threshold, output a cascading suggestion and display the cascading path through the topology diagram.

[0042] The system collects and analyzes the number of sub-modules and communication load of the I / O coupler in real time. Based on the hardware specifications and protocol characteristics of the I / O coupler, it presets a first threshold and a second threshold. Meeting either condition triggers a cascading suggestion. After the cascading suggestion is generated, the device configuration visualization module displays the cascading path in the topology diagram through multiple visual identifiers.

[0043] In this embodiment of the application, the number of sub-modules refers to the total number of slave devices and lower-level sub-modules of the target IO coupler, including physically connected devices and logically associated virtual nodes; the communication load is calculated by the real-time data flow of the IO coupler, and the load rate is calculated as: load rate = real-time data flow / maximum carrying data flow.

[0044] In some embodiments, the first threshold can be 7, and the second threshold can be 70%. A cascading suggestion is triggered when the I / O coupler connects 8 devices, or when the load rate of the I / O coupler is greater than 70%.

[0045] Based on the above embodiments, as another optional embodiment, the PLC configuration network intelligent management method may further include: S203. Based on the path optimization algorithm, calculate the optimal deployment location of the secondary coupler, which is used to share the load of the IO coupler; For complex bus protocols such as EtherCAT, a path optimization algorithm is employed. Using the target I / O coupler as the origin, calculations are performed based on physical distance, signal attenuation, and load coverage to determine the optimal deployment location of the secondary coupler. Here, physical distance refers to the distance to the upstream I / O coupler, used to measure signal transmission loss; signal attenuation is calculated using the link loss formula, referring to the signal attenuation rate of the cascaded path; and load coverage refers to the number of sub-modules that the secondary coupler can cover, used to maximize load sharing.

[0046] S204. The cascading recommendations are displayed in the topology map using multiple identifiers, including marking the optimal deployment location, drawing the cascading path, and marking the expected benefits of the cascading recommendations.

[0047] In some embodiments, the optimal deployment location of the secondary coupler can be marked with a dashed box in the topology diagram. The size of the dashed box is adjusted according to the number of sub-modules to be covered, and the icon of the secondary coupler is displayed inside the box. When the user hovers the mouse over the dashed box, a text tooltip pops up, which includes the physical distance between the location and the parent I / O coupler, the signal attenuation rate, and the number of sub-modules that can be covered.

[0048] In some embodiments, the main path from the upper-level I / O coupler to the secondary coupler can be drawn as a solid line, with the line width positively correlated with the communication bandwidth; the branch paths from the secondary coupler to the submodule can be drawn as dashed lines, with arrows pointing in the direction of data transmission. When multiple candidate paths exist, they are distinguished by different color gradients, and the differences in transmission delay of each path are marked.

[0049] In some embodiments, the expected benefits may include load optimization following the adoption of cascading recommendations, such as the rate of decrease in load on the upper-level I / O coupler; and the decrease in the average communication latency of the multi-level topology.

[0050] Based on the above embodiments, as another optional embodiment, the recursive rendering algorithm may further include: S205. Each of the secondary couplers independently maintains the device list, communication parameters and fault status of the sub-topology, and synchronizes the data with the main topology according to a preset cycle. In some embodiments, each secondary coupler acts as an independent sub-module management node, autonomously maintaining its information. The device list may include records of slave devices connected to the secondary coupler, along with the model, physical address, and logical number of each slave device, supporting real-time updates when devices are added or removed. Communication parameters include protocol parameters storing the sub-topology; parameter modifications only affect the sub-topology and do not impact the main topology. Fault status includes anomalies such as device offline status and communication errors within the sub-topology, used to generate fault logs.

[0051] In some embodiments, the secondary coupler has local processing capabilities and can independently respond to communication requests from slave stations within the sub-topology without relying on the master station for forwarding, thus reducing the load on the master topology. For example, a secondary coupler using the EtherCAT protocol can directly interact with servo motors in real time, only synchronizing the summarized results to the master station. Communication requests may include data acquisition and command execution.

[0052] The secondary coupler automatically transmits data from the sub-topology to the main topology at preset intervals (e.g., 1ms). In some embodiments, when a device change or failure occurs in the sub-topology, the secondary coupler immediately and actively synchronizes with the main topology.

[0053] S206. When a fault is detected in a certain stage coupler, the backup communication port of the downstream slave station of the faulty coupler is detected, and a new connection path is planned by combining the load margin of the normal coupler and the backup communication port. In some embodiments, the main topology maintains periodic heartbeat interactions with each level of coupler. If no heartbeat response is received from a certain level of coupler three times consecutively, that coupler is determined to be faulty. The faulty coupler is identified in the topology diagram, and the downstream slave station is located through the device configuration visualization module.

[0054] Extract the parameters of the backup communication port using the preset configuration of the slave device. Send test data packets to the backup communication port to verify its availability and protocol compatibility with the target coupler, and filter out the valid backup ports. The communication port parameters may include port type, supported protocols, maximum carrying rate, etc.

[0055] Count the number of connected submodules and communication load of the currently functioning coupler, and calculate the remaining capacity. For example, if a secondary coupler can connect a maximum of ten submodules, and currently has six connected submodules with a communication load of 40%, then the communication load margin is 60%, allowing for the addition of four more submodules.

[0056] Prioritize connecting downstream slave stations to the nearest normal coupler with sufficient load margin (e.g., greater than 30%) via backup communication ports to ensure minimal data transmission latency.

[0057] S207. Identify the fault coupler in the topology diagram and display the connection path.

[0058] Based on the above embodiments, as another optional embodiment, the PLC configuration network intelligent management method further includes: S208. The master station monitors the response status of the slave station. When the slave station's non-response time exceeds a third threshold, an abnormal alarm is sent, and the non-response time is recorded. The timer starts counting from the moment the master station sends the command. If no valid response is received from the slave station, the non-response time is accumulated. If the slave station responds, the timer is reset to zero. When the slave station's non-response time continues to exceed the third threshold (e.g., 30ms), the master station immediately triggers an abnormal alarm. The system automatically records the slave station's non-response time and synchronizes it to the master station.

[0059] After the master station triggers an abnormal alarm, it transmits the alarm signal to the device configuration visualization module of the configuration unit in real time. Based on the slave station's non-response time, it performs recovery operations. After each operation, it waits for a preset time (e.g., 30ms) to monitor whether the slave station has recovered its response. If successful, it stops subsequent operations. The recovery operations include automatically sending a communication parameter reset command to reinitialize the slave station's communication port configuration; triggering a slave station reset command to restart the slave station's communication module and retaining core control parameters.

[0060] S209. When a fault is detected in the master station, based on the priority of each slave station, the slave station with the highest priority is promoted to the master station, and the multi-level topology is updated.

[0061] In some embodiments, the system determines the status of the master station by monitoring the periodic heartbeat signals from the slave station to the master station. If the slave station fails to receive a heartbeat response from the master station three times consecutively and its reconnection attempt fails, the master station is deemed to be faulty.

[0062] When a master station failure is determined, the slave station with the highest priority is selected from the device communication priority ranking list and identified as a candidate device for the new master station. If multiple highest priority slave stations exist, they are further selected based on the principle of being closest to the master station in terms of physical connection.

[0063] The recursive rendering algorithm automatically adjusts the multi-level topology based on the location and connection relationships of the new master station. The new master station node is migrated from its original slave station location to the starting position of the topology graph, the connection links between the original master station and other slave stations are deleted, and the other slave station nodes are rearranged according to their physical connection order and communication priority.

[0064] In some embodiments, the new master station synchronizes historical data such as fault logs and device status records from the original master station to ensure the continuity of network management. Users can view the complete records in the historical data of the topology diagram.

[0065] S300, in response to the second operation of double-clicking a device node in the network topology tree module or dragging the device node to the device configuration visualization module, a device addition operation is performed; In some embodiments, when a user double-clicks a device node in the network topology tree module, the system verifies whether the device is compatible with the topology protocol in the current device configuration visualization module. If it is not compatible, a prompt box will pop up; if it is compatible, the system will proceed with the addition process.

[0066] The system automatically generates an instantiated node for the device in the topology diagram and matches the basic parameters based on the preset rules of the protocol mapping controller. After the device node is added, the new device is displayed in the topology diagram, and the connection links with the parent node (such as the IO coupler or the master station) are automatically drawn.

[0067] In some embodiments, the user long-presses a device node in the network topology tree module, drags it to the target location in the device configuration visualization module, and releases the mouse to complete the trigger. If the dragged location of the new device is not explicitly associated with a parent node, the system pops up a floating menu displaying available parent nodes, which the user can select to complete the parent relationship configuration.

[0068] After the device addition operation is completed, the status of the corresponding node in the network topology tree module is updated, the topology diagram in the device configuration visualization module is automatically adjusted, and the device quantity statistics for the corresponding protocol in the communication protocol classification module increase.

[0069] Based on the above embodiments, as another optional embodiment, the PLC configuration network intelligent management method further includes: S301. Generate decision support indicators based on the multi-level topology, including load indicators, latency indicators, and cost indicators; The system monitors nodes at all levels in real time using a recursive rendering algorithm and generates decision support indicators. These indicators include: load indicators (total number of connected devices and communication load); latency indicators (time difference between the master station sending control commands and the slave station receiving them, and time difference between the slave station sending response data and the master station receiving it); and cost indicators (hardware cost and power consumption of each device).

[0070] S302. Display the multi-level topology and variant structures through the topology diagram, and label the decision support indicators of each structure. The variant structures include the historical structure and virtual deployment structure of the multi-level topology. Using topology graphs and recursive rendering algorithms, the current multi-level topology is displayed in the device configuration visualization module. Decision support indicators are labeled next to the current topology in the form of floating text or data labels.

[0071] The system automatically saves a snapshot of the current multi-level topology at a preset period (e.g., every 30 minutes), or triggers a snapshot save when the user manually adjusts the topology. The snapshot includes the topological node relationships, device parameters, and decision indicators of the multi-level topology at that point in time, and is stored in a local database. Users can access historical topology data and select historical structures for retrieval.

[0072] After accessing the historical structure, the topology diagram displays the nodes and links at that point in time, as well as the decision support indicators of that historical structure, and compares them with the current decision support indicators.

[0073] S303. In response to the user's third operation of adjusting the multi-level topology, generate the virtual deployment structure, simulate the running state for a preset time based on historical data, and calculate the decision support index of the virtual deployment structure.

[0074] In some embodiments, the third operation may include dragging an existing device node to a new location, modifying link connection relationships, or modifying device parameters.

[0075] In response to the third operation, the system generates a virtual structure on a separate layer of the topology diagram. Virtual nodes in the virtual structure are distinguished from actual nodes by dashed borders, and virtual links are displayed with dashed lines. The virtual structure retains the node relationships adjusted by the user, inherits the basic attributes of the actual devices, and does not affect the operation of the actual physical network.

[0076] Historical data is extracted from the system database for simulation operation. This historical data may include communication load and response time under different device configuration parameters. The dynamic simulation module in the recursive rendering algorithm is used to simulate the operation of the virtual structure periodically (e.g., 10ms / cycle) at preset intervals. Based on the full-cycle data generated from the simulation, decision support indicators are calculated.

[0077] S400. The device configuration visualization module identifies the online and offline status of the device through color coding and displays abnormal devices through dynamic identification. It also adjusts the topology diagram of the device configuration visualization module by combining multiple perspectives.

[0078] In some embodiments, the device configuration visualization module uses different colors to distinguish device status. Online devices and connection links are displayed in green, while offline devices and links are displayed in red.

[0079] In some embodiments, the device configuration visualization module includes a topology graph drawing engine, which uses Graphics Device Interface (GDI+) technology to render device connection relationships and status animations in real time. Dynamic identification of abnormal devices includes icon flashing.

[0080] In some embodiments, the multi-dimensional view may include a logical view and a planar view. The logical view arranges the devices according to logical relationships, including the order of master station-IO coupler-slave station; the planar view arranges the devices according to their actual installation locations.

[0081] Based on the above embodiments, as another optional embodiment, the device addition operation includes: outputting parameter optimization suggestions based on historical configuration data through an intelligent decision engine; the intelligent decision engine includes a deep learning model, which analyzes the correlation between protocol parameters in the historical configuration data and device operation stability, and outputs the optimal parameter combination for the target device to be added.

[0082] When a device is added, the intelligent decision engine retrieves the protocol parameters of similar devices from the historical configuration database. These protocol parameters may include baud rate and communication cycle.

[0083] Based on an LSTM neural network model, the correlation between protocol parameters and device operational stability in historical data is analyzed. For each target device, the optimal parameter combination is calculated, and parameter optimization suggestions are displayed and annotated in the device configuration interface.

[0084] This application also provides a PLC configuration network intelligent management system, based on a PLC configuration network intelligent management method, wherein the system includes: The interface configuration module is used to build a two-dimensional dynamic configuration interface that includes a communication protocol classification unit, a device configuration visualization unit, and a network topology tree unit. The topology generation module is used to execute the recursive rendering algorithm to generate a multi-level topology structure containing master station, IO coupler, and slave station based on the communication protocol; The cascading analysis module is used to monitor the number of sub-modules and communication load of the I / O coupler in real time and output cascading suggestions. The intelligent decision-making module includes an intelligent decision-making engine based on a deep learning model, which outputs the optimal combination of parameters when an operation is added to the device.

[0085] In some embodiments, the system may also include a master-slave configuration module, which is used to monitor the response status of the master station to the slave station, trigger an abnormal alarm and record the duration when the slave station does not respond for a longer time than a third threshold, and automatically upgrade the highest priority slave station to the master station when the master station fails, and synchronously update the multi-level topology. In some embodiments, the system may also include a fault handling module for monitoring the coupler fault status. When a fault is detected in a certain level of coupler, the module retrieves the backup communication port of the downstream slave station, plans a new connection path in combination with the load margin of the normal coupler, and identifies the faulty coupler and the new path in the topology diagram. In some embodiments, the system may further include an interactive management module, which is used to respond to double-clicking or dragging device nodes in a network topology tree unit, perform device addition, support user adjustment operations on multi-level topology structures, and generate virtual deployment structures and corresponding decision support indicators.

[0086] Based on the above embodiments, as another optional embodiment, this application embodiment may further include a computer storage medium, which may store multiple instructions. The instructions are adapted to be loaded by a processor and executed by a PLC configuration network intelligent management method of the above embodiments. For the specific execution process, please refer to the detailed description of the above embodiments, which will not be repeated here.

[0087] Based on the above embodiments, as another optional embodiment, this application embodiment may further include an electronic device. The electronic device may include: at least one processor, at least one communication bus, a user interface, at least one network interface, and a memory.

[0088] The communication bus is used to enable communication between these components.

[0089] The user interface may include a display screen and a camera. Optional user interfaces may also include standard wired interfaces and wireless interfaces.

[0090] The network interface may include standard wired interfaces and wireless interfaces (such as Wi-Fi interfaces).

[0091] The processor may include one or more processing cores. It connects to various parts of the server via various interfaces and lines, executing instructions, programs, code sets, or instruction sets stored in memory, and accessing data stored in memory to perform various server functions and process data. Optionally, the processor may be implemented using at least one of the following hardware forms: Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor may integrate one or more of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor.

[0092] The memory may include random access memory (RAM) or read-only memory. Optionally, the memory may include a non-transitory computer-readable storage medium. The memory can be used to store instructions, programs, code, code sets, or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor. As a computer storage medium, the memory may include an operating system, a network communication module, a user interface module, and an application program for a PLC configuration network intelligent management method.

[0093] In electronic devices, the user interface is primarily used to provide an input interface for users and to acquire user input data. The processor can be used to call an application program stored in memory that represents a PLC configuration network intelligent management method. When executed by one or more processors, this causes the electronic device to perform one or more methods as described in the above embodiments. It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps can be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0094] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0095] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only 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 coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0096] 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 network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0097] 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.

[0098] 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 device (CMD). 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 memory 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 memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0099] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will readily conceive of those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0100] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for intelligent management of PLC configuration networks, characterized in that, include: A two-dimensional dynamic configuration interface is constructed, which includes a communication protocol classification module, a device configuration visualization module, and a network topology tree module. The communication protocol classification module displays at least two protocol icons in a grid layout. In response to the first operation of dragging the protocol icon to the device configuration visualization module, a multi-level topology structure is generated by a recursive rendering algorithm. The multi-level topology structure includes multiple couplers and is updated with the device connection status. In response to a second operation, such as double-clicking a device node in the network topology tree module or dragging the device node to the device configuration visualization module, a device addition operation is performed. The device configuration visualization module uses color coding to identify the online and offline status of devices and displays abnormal devices through dynamic identification. It also combines multiple perspectives to adjust the topology of the device configuration visualization module.

2. The PLC configuration network intelligent management method according to claim 1, characterized in that, The recursive rendering algorithm includes: Based on the communication protocol, and combined with the physical connection order and communication priority of the devices, the node arrangement of the multi-level topology is adjusted. The multi-level topology includes a master station, an I / O coupler, and slave stations. The number of sub-modules and communication load of the IO coupler are monitored in real time. When the number of sub-modules exceeds a first threshold or the communication load exceeds a second threshold, a cascading suggestion is output and the cascading path is displayed through the topology diagram.

3. The PLC configuration network intelligent management method according to claim 2, characterized in that, Also includes: Based on the path optimization algorithm, the optimal deployment location of the secondary coupler is calculated. The secondary coupler is used to share the load of the I / O coupler. The cascading recommendations are displayed in the topology map using multiple identifiers, including marking the optimal deployment location, drawing the cascading path, and marking the expected benefits of the cascading recommendations.

4. The PLC configuration network intelligent management method according to claim 3, characterized in that, The recursive rendering algorithm also includes: Each of the secondary couplers independently maintains the device list, communication parameters, and fault status of the sub-topology, and synchronizes data with the main topology according to a preset cycle. When a fault is detected in a certain stage coupler, the backup communication port of the downstream slave station of the faulty coupler is detected, and a new connection path is planned by combining the load margin of the normal coupler and the backup communication port. The fault coupler is identified in the topology diagram, and the connection path is displayed.

5. The PLC configuration network intelligent management method according to claim 2, characterized in that, Also includes: Decision support indicators are generated based on the multi-level topology, including load indicators, latency indicators, and cost indicators. The topology diagram displays the multi-level topology and variant structures, and labels the decision support indicators for each structure. The variant structures include the historical structure and virtual deployment structure of the multi-level topology. In response to a third user operation that adjusts the multi-level topology, the virtual deployment structure is generated, and the operating state is simulated for a preset period of time based on historical data to calculate the decision support index of the virtual deployment structure.

6. The PLC configuration network intelligent management method according to claim 2, characterized in that, Also includes: The master station monitors the response status of the slave station. When the slave station's non-response time exceeds a third threshold, it sends an abnormal alarm and records the non-response time. When a failure of the master station is detected, the slave station with the highest priority is promoted to the master station based on the priority of each slave station, and the multi-level topology is updated.

7. The PLC configuration network intelligent management method according to claim 1, characterized in that, The device addition operation includes: The intelligent decision engine outputs parameter optimization suggestions based on historical configuration data. The intelligent decision engine includes a deep learning model, which analyzes the correlation between protocol parameters and device operational stability in the historical configuration data and outputs the optimal parameter combination for adding the target device.

8. A PLC configuration network intelligent management system, based on the PLC configuration network intelligent management method as described in claims 1-7, characterized in that, include: The interface configuration module is used to build a two-dimensional dynamic configuration interface that includes a communication protocol classification unit, a device configuration visualization unit, and a network topology tree unit. The topology generation module is used to execute the recursive rendering algorithm to generate a multi-level topology structure containing master station, IO coupler, and slave station based on the communication protocol; The cascading analysis module is used to monitor the number of sub-modules and communication load of the I / O coupler in real time and output cascading suggestions. The intelligent decision-making module includes an intelligent decision-making engine based on a deep learning model, which outputs the optimal combination of parameters when an operation is added to the device.

9. An electronic device, characterized in that, It includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores multiple instructions suitable for being loaded by a processor and executed as described in any one of claims 1-7.

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