Industrial access control method and system for low-delay communication

Abstract

The invention relates to the technical field of industrial communication, and discloses an industrial access control method for low-delay communication, which is applied to a flexible production workshop scene, and the flexible production workshop scene comprises at least one core controller, a plurality of edge nodes and a plurality of heterogeneous industrial devices. The heterogeneous industrial equipment comprises high-priority equipment and low-priority equipment. The method comprises the following steps: S1, an edge node obtains real-time production task information and an equipment access request of a flexible production workshop; according to the industrial access control method and system for low-delay communication, the priority of equipment is dynamically identified through a task-equipment-data three-dimensional judgment model, and a time slot-bandwidth two-dimensional conflict pre-judgment mechanism and cooperative scheduling of a core controller and edge nodes are combined; the access delay of high-priority equipment such as a servo motor and a mechanical arm in a flexible production workshop can be controlled within the range of meeting the real-time requirements of key production tasks such as precision machining and material carrying.

Description

Technical Field

[0001] This invention relates to the field of industrial communication technology, specifically to an industrial access control method and system for low-latency communication. Background Technology

[0002] As smart manufacturing moves towards flexibility and collaboration, flexible production workshops have become a key scenario in the industrial manufacturing field. The heterogeneous industrial equipment inside needs to access the control system through an industrial network to complete tasks such as transmitting production instructions. However, in this scenario, the existing industrial access control solutions have particularly prominent problems with low efficiency in resource allocation and conflict handling.

[0003] The access of equipment in flexible production workshops is characterized by both "suddenness" and "heterogeneity." Taking a robotic arm as an example, when it grabs materials, it needs to transmit position data at high frequency, causing a surge in data traffic in a short period of time. When RFID readers scan materials, there will be a situation where a batch of devices access the network. Current solutions mostly adopt a "static resource allocation" mode, such as reserving fixed bandwidth for low-priority devices. This can easily lead to idle resources. For example, during non-environmental inspection periods, the bandwidth corresponding to temperature and humidity sensors is in a state of low utilization for a long time. Once devices are connected in a concentrated manner, the "conflict post-processing" mechanism becomes inadequate. High-priority devices, such as servo motors, often have access delays exceeding 50ms, while precision machining has strict real-time requirements and usually needs to control the delay within 20ms. As a result, the existing solutions simply cannot meet production needs and severely restrict production efficiency and product quality. Therefore, a low-latency communication industrial access control method and system are proposed to solve the problems mentioned above. Summary of the Invention

[0004] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides an industrial access control method and system for low-latency communication. It has advantages such as the ability to dynamically adapt to production tasks for equipment priority identification, efficient resource allocation and conflict prediction mechanisms, and collaborative scheduling capabilities between the core controller and edge nodes. It solves the problems of existing solutions, such as the mismatch between equipment priority and scenario requirements leading to delays in critical tasks, low efficiency in resource allocation and conflict handling causing excessive access latency for high-priority equipment, and insufficient collaborative scheduling capabilities affecting the access efficiency of critical production equipment. Ultimately, it achieves low-latency access and stable communication for industrial equipment in flexible production workshops.

[0005] (II) Technical Solution To achieve the aforementioned goals of efficient resource allocation and conflict prediction mechanisms, this invention provides the following technical solution: a low-latency communication industrial access control method applied to a flexible production workshop scenario. The flexible production workshop scenario includes at least one core controller, multiple edge nodes, and various heterogeneous industrial devices, including high-priority devices and low-priority devices. The method includes the following steps: S1: Edge nodes acquire real-time production task information and equipment access requests from the flexible production workshop. The real-time production task information includes task type, task priority, and equipment type required for the task. The equipment access request includes equipment identifier, equipment type, and data transmission requirements. S2: Edge nodes dynamically identify device priorities based on a preset priority determination model, combined with real-time production task information and device access requests. S21: If the device is a high-priority device, such as a servo motor or robotic arm, and the real-time production task is precision machining / material handling (level 1 task), it is determined to be a high-priority device, and the access response threshold is ≤20ms; S22: If the device is a low-priority device, such as a temperature and humidity sensor or an RFID reader, and the real-time production task is environmental inspection (level 3 task), then it is determined to be a low-priority device, and the access response threshold is ≤100ms. S23: If the device type does not match the task type, reduce the device priority by at least one priority level. S3: The core controller constructs a pre-allocated resource pool containing bandwidth, time slots, and computing resources, reserving 30%-50% of dynamically adjustable resources according to the needs of high-priority devices. The pre-allocated resource pool also includes resource partitions and spare resources set up for low-priority devices. S4: Edge nodes handle access requests based on device priority and pre-allocated resource pools using a conflict prediction mechanism. S41: When a high-priority device connects, the edge node queries the remaining dynamic resources. If there are enough, the resources are allocated directly. If there are not enough, the edge node requests scheduling from the core controller and calls the backup resources of the low-priority device to satisfy the needs first. S42: When a low-priority device accesses the network, the edge node will predict whether it will conflict with the high-priority device. If there is a conflict, the device will be cached in the local queue and the resource will be released. If there is no conflict, the device will be allocated from the low-priority resource partition. S5: Core controller and edge node collaborative scheduling: S51: The core controller synchronizes global production task priority update information in real time, and the edge nodes adjust the device priority accordingly. S52: Edge nodes provide feedback on device access status, and the core controller dynamically adjusts the proportion of the pre-allocated resource pool accordingly; S6: Edge nodes access devices through communication adapter interfaces and monitor latency. If the latency of a high-priority device exceeds 20ms, the core controller is triggered to perform emergency resource scheduling to ensure its communication stability.

[0006] Preferably, the priority determination model in S2 adopts a three-dimensional determination logic of "task-device-data": Task Dimension: Tasks are divided into Level 1, Level 2, and Level 3 tasks according to their importance. Level 1 tasks have the highest weight and can include precision machining and material handling. Level 2 tasks have the next highest weight and can include production data statistics. Level 3 tasks have the lowest weight and can include environmental inspection. Equipment dimension: According to the degree of impact of equipment on production tasks, servo motors and robotic arms have the highest weight, followed by RFID readers, and temperature and humidity sensors have the lowest weight. Data dimensions: Based on the real-time data transmission requirements of devices, devices with high transmission frequency have the highest weight, devices with medium transmission frequency have the next highest weight, and devices with low transmission frequency have the lowest weight. The output value of the priority determination model = task dimension weight × task priority coefficient + device dimension weight × device type coefficient + data dimension weight × data transmission coefficient. When the output value reaches the preset high priority threshold, it is determined to be a high priority device; when the output value is lower than the preset low priority threshold, it is determined to be a low priority device.

[0007] Preferably, the conflict prediction mechanism in S4 adopts a two-dimensional prediction method: "time slot-bandwidth". Time slot prediction: The edge node obtains the time slot allocation table of the connected devices, compares the requested time slot of the low-priority device with the allocated time slot of the high-priority device, and if the degree of overlap between the two reaches the preset conflict threshold, it is determined that there is a conflict. Bandwidth prediction: The edge node calculates the total bandwidth usage after low-priority devices are connected. If the total bandwidth usage reaches the preset threshold and the bandwidth usage ratio of high-priority devices meets the preset guarantee ratio, then a conflict is determined to exist.

[0008] Preferably, the data transmission requirements in the device access request include data transmission frequency and single data transmission volume. The data transmission frequency of high-priority devices is higher than that of low-priority devices, and the single data transmission volume of high-priority devices does not exceed the preset data volume limit. The proportion of the spare resources in the pre-allocated resource pool to the total proportion of the pre-allocated resource pool is a fixed range, and the spare resources are only called when the dynamic resources of high-priority devices are insufficient. After the call, the core controller needs to replenish the spare resources to the initial proportion within a preset time.

[0009] Preferably, in S51, the core controller synchronizes the global production task priority update information within a period not exceeding a preset synchronization period. In S52, the edge node feedback on the device access status includes the device access success / failure identifier, the current resource occupancy rate, and the device data transmission status. The communication adaptation interface supports at least three industrial communication protocols, enabling protocol adaptation and data format conversion between different types of heterogeneous industrial equipment and edge nodes.

[0010] A low-latency communication industrial access control system includes a core controller, multiple edge nodes, a communication adapter interface, and a status monitoring module. The core controller is connected to the edge nodes via a wired network, and the edge nodes are connected to heterogeneous industrial equipment via the communication adapter interface. The status monitoring module is deployed inside the edge nodes, and the number of edge nodes is consistent with the number of production units in a flexible production workshop.

[0011] Preferably, the core controller includes a resource pool management module, a global scheduling module, and a task information synchronization module. The resource pool management module is used to manage the resource allocation and ratio adjustment of the pre-allocated resource pool, and the global scheduling module is used to receive resource scheduling requests from edge nodes and execute resource calls. The task information synchronization module is used to send global production task priority update information; The edge node includes a priority identification module, a conflict prediction module, and a buffer avoidance module. The priority identification module is used to execute a preset priority determination model, the conflict prediction module is used to execute a "time slot-bandwidth" dual-dimensional prediction logic, and the buffer avoidance module is used to store the access request cache queue of low-priority devices.

[0012] Preferably, the wired network between the core controller and the edge node is fiber optic Ethernet, and the communication delay between the two is ≤5ms; the production units managed by the edge node include precision machining units, material handling units and environmental inspection units, and each edge node only processes the device access requests and priority identification within the corresponding production unit.

[0013] Preferably, the industrial communication protocols supported by the communication adapter interface include the Industrial Ethernet protocol, the LoRa protocol, and the 5G-Industrial protocol. The communication adapter interface is provided with a protocol conversion unit and a data format conversion unit. The protocol conversion unit is used to convert between different communication protocols, and the data format conversion unit is used to unify the output data format of heterogeneous industrial equipment.

[0014] Preferably, the monitoring content of the status monitoring module includes device access delay, resource occupancy rate, and communication connection status. The transmission delay of the status monitoring module sending emergency dispatch signals to the core controller does not exceed a preset delay threshold. When the resource pool management module of the core controller adjusts the pre-allocated resource pool ratio, the resource ratio of high-priority devices is adjusted according to a preset high-priority ratio range, and the resource ratio of low-priority devices is adjusted according to a preset low-priority ratio range. Furthermore, the upper limit of the high-priority device resource ratio range is not lower than the upper limit of the low-priority device resource ratio range.

[0015] (III) Beneficial Effects Compared with existing technologies, the present invention provides an industrial access control method and system for low-latency communication, which has the following advantages: 1. This low-latency communication industrial access control method and system dynamically identifies equipment priority through a three-dimensional judgment model of "task-device-data". Combined with a two-dimensional conflict prediction mechanism of "time slot-bandwidth" and the collaborative scheduling of core controller and edge nodes, it can control the access latency of high-priority equipment such as servo motors and robotic arms in flexible production workshops within the range that meets the real-time requirements of key production tasks such as precision machining and material handling. This avoids the problem of excessive latency of high-priority equipment in existing solutions and ensures accurate transmission of production instructions and stability of equipment collaborative operation.

[0016] 2. The industrial access control method and system for low-latency communication supports dynamic adjustment of the resource ratio of high and low priority devices according to production tasks through the construction of a pre-allocated resource pool. At the same time, it avoids the resource idleness problem caused by the existing "static resource allocation" through the backup resource calling mechanism and the low priority device buffer avoidance mechanism. Compared with the existing solutions, the resource utilization rate of this solution is greatly improved, and the resource adjustment response is timely when switching production tasks, taking into account both the device access needs and the rationality of resource allocation. Attached Figure Description

[0017] Figure 1 This is a flowchart of the low-latency communication industrial access control method of the present invention; Figure 2 This is a schematic diagram of the industrial access control system for low-latency communication according to the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 Please see Figure 1 A low-latency communication industrial access control method is applied to a flexible production workshop scenario. The flexible production workshop scenario includes at least one core controller, multiple edge nodes, and various heterogeneous industrial devices, including high-priority devices and low-priority devices. The method includes the following steps: S1: Edge nodes acquire real-time production task information and equipment access requests from the flexible production workshop. The real-time production task information includes task type, task priority, and equipment type required for the task. The equipment access request includes equipment identifier, equipment type, and data transmission requirements. S2: Edge nodes dynamically identify device priorities based on a preset priority determination model, combined with real-time production task information and device access requests. S21: If the device is a high-priority device, such as a servo motor or robotic arm, and the real-time production task is precision machining / material handling (level 1 task), it is determined to be a high-priority device, and the access response threshold is ≤20ms; S22: If the device is a low-priority device, such as a temperature and humidity sensor or an RFID reader, and the real-time production task is environmental inspection (level 3 task), then it is determined to be a low-priority device, and the access response threshold is ≤100ms. S23: If the device type does not match the task type, reduce the device priority by at least one priority level. S3: The core controller constructs a pre-allocated resource pool containing bandwidth, time slots, and computing resources, reserving 30%-50% of dynamically adjustable resources according to the needs of high-priority devices. The pre-allocated resource pool also includes resource partitions and spare resources set up for low-priority devices. S4: Edge nodes handle access requests based on device priority and pre-allocated resource pools using a conflict prediction mechanism. S41: When a high-priority device connects, the edge node queries the remaining dynamic resources. If there are enough, the resources are allocated directly. If there are not enough, the edge node requests scheduling from the core controller and calls the backup resources of the low-priority device to satisfy the needs first. S42: When a low-priority device accesses the network, the edge node will predict whether it will conflict with the high-priority device. If there is a conflict, the device will be cached in the local queue and the resource will be released. If there is no conflict, the device will be allocated from the low-priority resource partition. S5: Core controller and edge node collaborative scheduling: S51: The core controller synchronizes global production task priority update information in real time, and the edge nodes adjust the device priority accordingly. S52: Edge nodes provide feedback on device access status, and the core controller dynamically adjusts the proportion of the pre-allocated resource pool accordingly; S6: Edge nodes access devices through communication adapter interfaces and monitor latency. If the latency of a high-priority device exceeds 20ms, the core controller is triggered to perform emergency resource scheduling to ensure its communication stability.

[0020] In this embodiment, when the low-latency communication industrial access control method is applied to a flexible production workshop scenario, it accurately acquires production task and equipment access information through edge nodes and dynamically identifies equipment priorities using a preset model. This ensures that high-priority equipment such as servo motors and robotic arms can efficiently access critical production tasks with an access response threshold of ≤20ms, while also reasonably adjusting the priorities of mismatched equipment. The pre-allocated resource pool built by the core controller can flexibly reserve resources according to the needs of high-priority equipment. Combined with the conflict prediction mechanism of the edge nodes, it can not only prioritize the supply of resources for high-priority equipment (schedule backup resources when resources are insufficient), but also avoid conflicts between low-priority and high-priority equipment through caching and avoidance. In addition, the real-time collaborative scheduling between the core controller and edge nodes (synchronizing task information and feeding back access status to adjust resource ratios), as well as the monitoring and emergency scheduling of high-priority equipment latency, ultimately achieves low-latency access, efficient resource utilization, and stable communication for heterogeneous equipment in the flexible production workshop, effectively meeting the real-time requirements of critical production tasks such as precision machining and material handling.

[0021] Please see Figure 2 A low-latency communication industrial access control system includes a core controller, multiple edge nodes, a communication adapter interface, and a status monitoring module. The core controller is connected to the edge nodes via a wired network, and the edge nodes are connected to heterogeneous industrial equipment via the communication adapter interface. The status monitoring module is deployed inside the edge nodes, and the number of edge nodes is consistent with the number of production units in the flexible production workshop.

[0022] In this embodiment, the low-latency communication industrial access control system uses a wired network connection between the core controller and edge nodes, with the edge nodes connecting to heterogeneous industrial equipment via communication adapter interfaces. This is complemented by a status monitoring module deployed within the edge nodes, with the number of edge nodes matching the number of production units in the flexible production workshop. This achieves both the core controller's overall resource management and the edge nodes' precise management of equipment access in each production unit, avoiding the latency of centralized control and the information limitations of independent processing. Furthermore, the communication adapter interfaces ensure compatibility with different types of industrial equipment access, while the status monitoring modules provide real-time monitoring of equipment access status, thereby guaranteeing stable and low-latency equipment access. This effectively adapts to the access needs of multiple units and heterogeneous equipment in flexible production workshops, improving the overall efficiency and reliability of industrial communication.

[0023] Example 2 This embodiment uses a flexible manufacturing workshop for automotive parts as an application scenario. 1. System Deployment Environment Taking a flexible manufacturing workshop for automotive parts as an example, comprising three production units (precision machining: engine block / crankshaft machining; material handling: parts transfer and replenishment; environmental inspection: temperature, humidity / dust monitoring), the deployment is as follows: Core controller: 1 Siemens S7-1500 PLC, responsible for global resource scheduling and task management, and supports high-speed interaction with edge nodes; Edge nodes: 3 Huawei Atlas500, each corresponding to 1 production unit, integrating data acquisition, priority identification and conflict prediction functions; Heterogeneous equipment: 52 units in total – 12 high-priority units (8 servo motors: controlling precision machining spindles; 4 robotic arms: material handling); 40 low-priority units (25 temperature and humidity sensors: distributed throughout the workshop; 15 RFID readers: material inlets / assembly stations). Communication network: The core controller and edge nodes are connected via fiber optic Ethernet (1Gbps bandwidth, latency ≤3ms); the edge nodes and devices are connected via multiple protocols (Profinet for servo motors / robotic arms, LoRa for sensors, and 5G-Industrial for RFID), and the communication adapter interface realizes protocol and data format conversion.

[0024] 2. Method Implementation Steps This embodiment takes the "engine cylinder block precision machining + material supply coordination" task (level 1 task) as an example to explain the implementation process in detail. The task cycle is 2 hours. It requires the servo motor of the precision machining unit and the robotic arm of the material handling unit to work together. The environmental inspection unit only needs to collect data intermittently.

[0025] S1: Real-time production task information and equipment access request acquisition The core controller obtains the task information of "engine cylinder block precision machining + material supply coordination" through the workshop MES system, including task type (precision machining + material handling), task priority (level 1), and required equipment type (servo motor, robotic arm), and synchronizes the information to the corresponding edge nodes (precision machining unit edge node 1, material handling unit edge node 2) in real time through the task information synchronization module. Edge node 1 receives a precision machining unit equipment access request: servo motor M01 (equipment identifier: JM-001, equipment type: servo motor, data transmission requirements: transmission frequency 180Hz, single transmission data volume 128Byte, used for position control of cylinder boring process). Edge node 2 receives a material handling unit device access request: robotic arm R02 (device identifier: XB-002, device type: robotic arm, data transmission requirements: transmission frequency 120Hz, single transmission data volume 64Byte, used to transfer raw materials to the processing station). Edge node 3 (environmental inspection unit) receives access request from temperature and humidity sensor T05 (device identification: HJ-005, device type: temperature and humidity sensor, data transmission requirements: transmission frequency 15Hz, single transmission data volume 32Byte). S2: Dynamic Device Priority Identification Each edge node invokes the priority identification module to perform priority identification based on the "task-device-data" three-dimensional judgment logic: Servo motor M01 (edge ​​node 1): Task dimension (first-level task, highest weight) × task priority coefficient 1 + device dimension (servo motor, highest weight) × device type coefficient 1 + data dimension (transmission frequency 180Hz, high frequency, highest weight) × data transmission coefficient 1. When the output value reaches the preset high priority threshold, it is determined to be a high priority device, and the access response threshold is set to ≤20ms. Robotic arm R02 (edge ​​node 2): Task dimension (first-level task, highest weight) × task priority coefficient 1 + device dimension (robotic arm, highest weight) × device type coefficient 1 + data dimension (transmission frequency 120Hz, high frequency, highest weight) × data transmission coefficient 1. When the output value reaches the preset high priority threshold, it is determined to be a high priority device, and the access response threshold is set to ≤20ms. Temperature and humidity sensor T05 (edge ​​node 3): Task dimension (current global task is level 1, environmental inspection is level 3 task, lowest weight) × task priority coefficient 0.4 + device dimension (temperature and humidity sensor, lowest weight) × device type coefficient 1 + data dimension (transmission frequency 15Hz, low frequency, lowest weight) × data transmission coefficient 1. If the output value is lower than the preset low priority threshold and the device type (environmental monitoring device) does not match the current global task (precision machining + material handling), the priority level will be reduced by one level according to S23, and it will be finally determined as a low priority device. The access response threshold is set to ≤100ms. S3: Construction of Pre-allocated Resource Pool The core controller's resource pool management module constructs a pre-allocated resource pool based on the current primary task requirements (total bandwidth resources of 600Mbps, time slot resources divided into 10ms units, and computing resources divided according to CPU utilization): High-priority equipment resources: 300Mbps bandwidth (50%), 40 time slots (50%), and 40% CPU utilization (50%). Backup resources: 120Mbps bandwidth (20%), 8 time slots (10%), and 8% CPU utilization (10%). Low-priority device resources: 180Mbps bandwidth (30%), 32 time slots (40%), and 32% CPU utilization (40%). S4: Conflict Prediction and Device Access Request Processing Each edge node invokes the conflict prediction module to process access requests in conjunction with the pre-allocated resource pool: Servo motor M01 (high priority, edge node 1): Query the remaining high priority resources in the pre-allocated resource pool - 300Mbps bandwidth remaining and 40 time slots remaining. It meets the 100Mbps bandwidth and time slot requirements (5 consecutive time slots) required for its 180Hz transmission frequency. There is no conflict, so 100Mbps bandwidth (time slots 1-5) is directly allocated. The actual latency after connecting to the network is 9ms. Robotic arm R02 (high priority, edge node 2): Query the remaining high priority resources in the pre-allocated resource pool - 200Mbps bandwidth and 35 time slots remaining, which meet its 80Mbps bandwidth and time slot requirements for its 120Hz transmission frequency (4 consecutive time slots are required). There is no conflict, so 80Mbps bandwidth (time slots 6-9) is directly allocated. The actual latency after connecting to the network is 11ms. Temperature and humidity sensor T05 (low priority, edge node 3): Performs "time slot-bandwidth" dual-dimensional prediction - Time slot prediction: Requested time slots 10-12 do not overlap with time slots 1-9 already allocated to high-priority devices, and the degree of overlap does not reach the preset conflict threshold; Bandwidth prediction: After access, the total bandwidth utilization rate is (100+80+20) / 600≈33.3%, which does not reach the preset utilization threshold, and the bandwidth ratio of high-priority devices (180 / 300=60%) meets the preset guarantee ratio, so it is determined that there is no conflict, and 20Mbps bandwidth (time slots 10-12) is allocated from the low-priority resource partition. The actual measured latency after accessing the network is 42ms. S5: Core controller and edge node collaborative scheduling Task Priority Update and Response: One hour after the task is executed, the core controller receives an "Emergency Material Replenishment" instruction from the MES system (the task priority is still Level 1, and one more robotic arm R03 needs to be added). The updated information is sent to edge node 2 through the task information synchronization module. Based on the updated information, edge node 2 identifies robotic arm R03 as a high-priority device, checks the remaining high-priority bandwidth (300-80=220Mbps) and finds it sufficient. It then directly allocates 60Mbps of bandwidth (time slots 13-15). The entire adjustment process takes 80ms. Device access status feedback and resource adjustment: Edge node 1 reports the access status of servo motor M01 to the core controller every 30 seconds - access successful, resource utilization rate (100 / 300≈33.3%), data transmission normal; Edge node 2 reports the access status of robotic arms R02 and R03 - access successful, resource utilization rate (140 / 300≈46.7%), data transmission normal; Based on the feedback information, the core controller determines that there are still high-priority resources remaining, and there is no need to adjust the pre-allocated resource pool ratio. S6: Delay Monitoring and Emergency Resource Scheduling The status monitoring modules of edge nodes 1 and 2 monitor the latency of high-priority devices in real time. When the task was executed for 1 hour and 20 minutes, the data transmission frequency of servo motor M01 temporarily increased to 220Hz due to the change of machining process (from boring to milling the plane), and the access delay increased to 23ms (exceeding the 20ms threshold). The status monitoring module immediately sends an emergency dispatch signal to the core controller (transmission delay 4ms). The core controller calls the global dispatch module to allocate 20Mbps bandwidth from the backup resources to supplement the servo motor M01. After adjustment, the delay is reduced to 15ms, returning to within the threshold. The entire emergency dispatch process takes 12ms.

[0026] S7: Dynamic Update of Device Priority Two hours after the task was completed, the "engine cylinder block precision machining + material supply coordination" task was completed, and the core controller sent a task completion signal to edge nodes 1 and 2: The priority identification module of edge node 1 reduces the priority of servo motor M01 to a low priority, releasing 100Mbps bandwidth and 5 time slots to the spare resource partition of the pre-allocated resource pool. The priority identification module of edge node 2 lowers the priority of robotic arms R02 and R03 to a low priority, releasing 140Mbps bandwidth and 9 time slots to the spare resource partition for subsequent tasks to call.

[0027] 3. Implementation effect verification This embodiment compares the key performance indicators of this solution with the existing "fixed priority + static resource allocation" solution under the same production task through comparative experiments. The results are as follows: Therefore, in flexible production workshop scenarios, this solution can effectively solve the problem of low efficiency in resource allocation and conflict handling of existing solutions, achieve low-latency access for high-priority devices and efficient resource utilization, adapt to dynamic changes in production tasks, and meet the real-time and stability requirements of intelligent manufacturing for industrial communication.

[0028] In summary, this low-latency communication industrial access control method and system dynamically identifies device priorities through a three-dimensional "task-device-data" judgment model. Combined with a two-dimensional "time slot-bandwidth" conflict prediction mechanism and collaborative scheduling between the core controller and edge nodes, it can control the access latency of high-priority devices such as servo motors and robotic arms in flexible production workshops within the range that meets the real-time requirements of key production tasks such as precision machining and material handling. This avoids the problem of excessive latency for high-priority devices in existing solutions and ensures accurate transmission of production instructions and stability of equipment collaborative operation.

[0029] Furthermore, the pre-allocated resource pool supports dynamic adjustment of the resource ratio of high and low priority devices according to production tasks. At the same time, the backup resource call mechanism and the low priority device buffer avoidance mechanism avoid the resource idle problem caused by the existing "static resource allocation". Compared with the existing solution, the resource utilization rate is greatly improved, and the resource adjustment response is timely when switching production tasks, taking into account both the device access needs and the rationality of resource allocation.

[0030] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0031] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A low-latency communication industrial access control method, characterized in that: The method, applied to a flexible manufacturing workshop scenario, includes at least one core controller, multiple edge nodes, and various heterogeneous industrial devices, comprising high-priority and low-priority devices, and comprises the following steps: S1: Edge nodes acquire real-time production task information and equipment access requests from the flexible production workshop. The real-time production task information includes task type, task priority, and equipment type required for the task. The equipment access request includes equipment identifier, equipment type, and data transmission requirements. S2: Edge nodes dynamically identify device priorities based on a preset priority determination model, combined with real-time production task information and device access requests. S21: If the device is a high-priority device, such as a servo motor or robotic arm, and the real-time production task is precision machining / material handling (level 1 task), it is determined to be a high-priority device, and the access response threshold is ≤20ms; S22: If the device is a low-priority device, such as a temperature and humidity sensor or an RFID reader, and the real-time production task is environmental inspection (level 3 task), then it is determined to be a low-priority device, and the access response threshold is ≤100ms. S23: If the device type does not match the task type, reduce the device priority by at least one priority level. S3: The core controller constructs a pre-allocated resource pool containing bandwidth, time slots, and computing resources, reserving 30%-50% of dynamically adjustable resources according to the needs of high-priority devices. The pre-allocated resource pool also includes resource partitions and spare resources set up for low-priority devices. S4: Edge nodes handle access requests based on device priority and pre-allocated resource pools using a conflict prediction mechanism. S41: When a high-priority device connects, the edge node queries the remaining dynamic resources. If there are enough, the resources are allocated directly. If there are not enough, the edge node requests scheduling from the core controller and calls the backup resources of the low-priority device to satisfy the needs first. S42: When a low-priority device accesses the network, the edge node will predict whether it will conflict with the high-priority device. If there is a conflict, the device will be cached in the local queue and the resource will be released. If there is no conflict, the device will be allocated from the low-priority resource partition. S5: Core controller and edge node collaborative scheduling: S51: The core controller synchronizes global production task priority update information in real time, and the edge nodes adjust the device priority accordingly. S52: Edge nodes provide feedback on device access status, and the core controller dynamically adjusts the proportion of the pre-allocated resource pool accordingly; S6: Edge nodes access devices through communication adapter interfaces and monitor latency. If the latency of a high-priority device exceeds 20ms, the core controller is triggered to perform emergency resource scheduling to ensure its communication stability.

2. The industrial access control method for low-latency communication according to claim 1, characterized in that: The priority determination model in S2 adopts a three-dimensional determination logic of "task-device-data": Task Dimensions: Tasks are divided into Level 1, Level 2, and Level 3 tasks based on their importance. Level 1 tasks have the highest weight and can include precision machining or material handling. Level 2 tasks have the next highest weight and can include production data statistics. Level 3 tasks have the lowest weight and can include environmental inspection. Equipment dimension: According to the degree of impact of equipment on production tasks, servo motors and robotic arms have the highest weight, followed by RFID readers, and temperature and humidity sensors have the lowest weight. Data dimensions: Based on the real-time data transmission requirements of devices, devices with high transmission frequency have the highest weight, devices with medium transmission frequency have the next highest weight, and devices with low transmission frequency have the lowest weight. The output value of the priority determination model = task dimension weight × task priority coefficient + device dimension weight × device type coefficient + data dimension weight × data transmission coefficient. When the output value reaches the preset high priority threshold, it is determined to be a high priority device; when the output value is lower than the preset low priority threshold, it is determined to be a low priority device.

3. The industrial access control method for low-latency communication according to claim 1, characterized in that: The conflict prediction mechanism in S4 adopts a two-dimensional prediction method: "time slot-bandwidth". Time slot prediction: The edge node obtains the time slot allocation table of the connected devices, compares the requested time slot of the low-priority device with the allocated time slot of the high-priority device, and if the degree of overlap between the two reaches the preset conflict threshold, it is determined that there is a conflict. Bandwidth prediction: The edge node calculates the total bandwidth usage after low-priority devices are connected. If the total bandwidth usage reaches the preset threshold and the bandwidth usage ratio of high-priority devices meets the preset guarantee ratio, then a conflict is determined to exist.

4. The industrial access control method for low-latency communication according to claim 1, characterized in that: The data transmission requirements in the device access request include the data transmission frequency and the amount of data transmitted in a single transmission. The data transmission frequency of high-priority devices is higher than that of low-priority devices, and the amount of data transmitted in a single transmission by high-priority devices does not exceed the preset data volume limit. The proportion of the reserve resources in the pre-allocated resource pool to the total pre-allocated resource pool is a fixed range, and the reserve resources are only called when the dynamic resources of high-priority devices are insufficient. After the call, the core controller needs to replenish the reserve resources to the initial proportion within a preset time.

5. The industrial access control method for low-latency communication according to claim 1, characterized in that: In S51, the core controller synchronizes the global production task priority update information within a period not exceeding a preset synchronization period. In S52, the edge node feedback on the device access status includes the device access success / failure identifier, current resource occupancy rate, and device data transmission status. The communication adaptation interface supports at least three industrial communication protocols, enabling protocol adaptation and data format conversion between different types of heterogeneous industrial equipment and edge nodes.

6. A low-latency communication industrial access control system, applying the low-latency communication industrial access control method described in claims 1-5, characterized in that: It includes a core controller, multiple edge nodes, communication adapter interfaces, and a status monitoring module. The core controller is connected to the edge nodes via a wired network, and the edge nodes are connected to heterogeneous industrial equipment via communication adapter interfaces. The status monitoring module is deployed inside the edge nodes, and the number of edge nodes is consistent with the number of production units in the flexible production workshop.

7. The low-latency communication industrial access control system according to claim 6, characterized in that: The core controller includes a resource pool management module, a global scheduling module, and a task information synchronization module. The resource pool management module is used to manage the resource allocation and ratio adjustment of the pre-allocated resource pool, and the global scheduling module is used to receive resource scheduling requests from edge nodes and execute resource calls. The task information synchronization module is used to send global production task priority update information; The edge node includes a priority identification module, a conflict prediction module, and a buffer avoidance module. The priority identification module is used to execute a preset priority determination model, the conflict prediction module is used to execute a "time slot-bandwidth" dual-dimensional prediction logic, and the buffer avoidance module is used to store the access request cache queue of low-priority devices.

8. The low-latency communication industrial access control system according to claim 6, characterized in that: The wired network between the core controller and the edge nodes is fiber optic Ethernet, and the communication latency between them is ≤5ms. The production units managed by the edge nodes include precision machining units, material handling units, and environmental inspection units. Each edge node only processes the device access requests and priority identification within the corresponding production unit.

9. The low-latency communication industrial access control system according to claim 6, characterized in that: The communication adapter interface supports industrial communication protocols including Industrial Ethernet, LoRa, and 5G-Industrial. The communication adapter interface is equipped with a protocol conversion unit and a data format conversion unit. The protocol conversion unit is used to convert between different communication protocols, and the data format conversion unit is used to unify the output data format of heterogeneous industrial equipment.

10. An industrial access control system for low-latency communication according to claim 6, characterized in that: The monitoring content of the status monitoring module includes device access delay, resource occupancy rate and communication connection status. The transmission delay of the status monitoring module sending emergency dispatch signals to the core controller does not exceed a preset delay threshold. When the resource pool management module of the core controller adjusts the pre-allocated resource pool ratio, the resource ratio of high-priority devices is adjusted according to a preset high-priority ratio range, and the resource ratio of low-priority devices is adjusted according to a preset low-priority ratio range. Moreover, the upper limit of the resource ratio range of high-priority devices is not lower than the upper limit of the resource ratio range of low-priority devices.

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