A multi-level converged communication dispatching method and system

Abstract

This invention discloses a multi-level fusion communication scheduling method and system, relating to the field of industrial processing communication scheduling technology. It solves the technical problem in existing technologies where, for a single process, the communication needs of each stage cannot be met while avoiding resource idleness. Specifically, it employs a hierarchical progression from "overall process scheduling → specific scenario scheduling → risk and hazard scheduling," covering the communication needs of different dimensions of the industrial processing production line and forming a complete multi-level fusion scheduling system. All scheduling is based on "actual scenario parameters," avoiding the rigidity of static scheduling and achieving dynamic and precise allocation of communication resources, balancing transmission efficiency and stability. By optimizing communication scheduling, from three levels—"reducing unnecessary scheduling," "allocating resources on demand," and "avoiding risks and hazards"—it ultimately ensures the qualified operation, efficient control, and low-risk operation of the industrial production line, providing communication-level support for the overall efficiency of the production line.

Description

Technical Field

[0001] This invention relates to the field of industrial processing communication scheduling technology, specifically a multi-level fusion communication scheduling method and system. Background Technology

[0002] Multi-level converged communication is a communication system that integrates multiple types of communication technologies, cross-level network architectures, and multiple service requirements to achieve seamless interconnection and efficient scheduling between different levels (such as terminals, squads, regions, and headquarters). Its core is to break down "information silos" and ensure stable communication and collaborative command in multi-level scenarios. Multi-level converged communication scheduling method is a method that integrates multiple communication technologies, networks, and services to achieve efficient communication scheduling under a multi-level architecture.

[0003] However, in the existing technology, it is impossible to avoid using a unified communication strategy for all processes in the entire production line, resulting in unnecessary scheduling losses; for a single process, it is impossible to allocate and schedule communication resources in a targeted manner according to the process execution stage, which cannot both meet the communication needs of each stage and avoid resource idleness.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problems mentioned above by proposing a multi-level fusion communication scheduling method and system.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A multi-level fusion communication scheduling method is proposed, and the communication scheduling method is as follows:

[0008] S1: Overall production line communication scheduling:

[0009] S11: Multi-level process analysis, classifying processes by type;

[0010] S12: Dynamic demand matching analysis, performing demand matching analysis based on each type of process;

[0011] S13: Communication detection, perform communication detection based on the current communication settings;

[0012] S2: Production line local communication scheduling:

[0013] S21: Communication link start point generation, and allocation of communication resource parameters for instruction reception and feedback;

[0014] S22: Extension of process operation nodes, that is, scheduling and allocation based on existing communication resource parameters;

[0015] S23: Obtain the execution evaluation node and allocate and schedule it in a unified manner based on the communication resource parameters of the local process;

[0016] S3: Communication Risk Detection

[0017] S31: Production line process operation monitoring, with data collection added according to the operation stage;

[0018] S32: Communication scheduling data analysis, threshold comparison based on the collected communication scheduling data;

[0019] S33: Based on the comparison results, conduct communication scheduling and rectification.

[0020] Furthermore, the multi-level analysis process for process S11 is as follows:

[0021] The industrial processing line is divided into several processes. The transmission frequency of the fine-tuning parameters in each process stage is obtained, and the processes are divided into high-frequency processes and low-frequency processes based on the transmission frequency threshold. According to the current task requirements, the fine-tuning frequency of the corresponding fine-tuning parameters of the high-frequency processes and the fine-tuning span of the fine-tuning parameters of the low-frequency processes are collected. If the fine-tuning frequency of the corresponding fine-tuning parameters of the high-frequency processes does not exceed the set fine-tuning frequency, the high-frequency processes are marked as communication-free processes in the current scenario. If the fine-tuning span of the fine-tuning parameters of the low-frequency processes exceeds the set fine-tuning span, the low-frequency processes are marked as communication-required processes in the current scenario.

[0022] Furthermore, the process of S12 dynamic demand matching analysis is as follows:

[0023] Analysis of dynamic communication requirements matching between high-frequency and low-frequency processes;

[0024] Using bandwidth as a communication parameter, the initial bandwidth utilization ratio of the work logs corresponding to high-frequency and low-frequency processes is obtained when the production line is running, i.e., the bandwidth utilization ratio is the same under the static priority allocation of communication. When the production line is running continuously, the update frequency deviation of the work logs corresponding to high-frequency and low-frequency processes is obtained. If the update frequency deviation exceeds the set frequency deviation threshold, the high-frequency and low-frequency processes need to be optimized and scheduled for communication. The bandwidth utilization ratio is adjusted according to the standard fluctuation based on the log update frequency deviation. When the standard fluctuation stops, there is no data lag in the process communication under the current bandwidth utilization ratio setting scenario, which indicates that the current bandwidth utilization ratio is suitable, and the current bandwidth utilization ratio is set for communication.

[0025] Furthermore, the S13 communication detection process is as follows:

[0026] When the key parameters of the production line process are close to the boundary value of the allowable range of the process, the communication lag frequency of the production line after the communication priority of the current production line process instruction is obtained; at the same time, the increase in lag time caused by the fluctuation of the key parameters of the high-frequency process and the corresponding communication instruction, and the decrease in lag time caused by the fluctuation of the key parameters of the low-frequency process and the corresponding communication instruction are obtained, and the lag time ratio is achieved according to the lag time ratio.

[0027] If the communication lag frequency after adjusting the communication priority of the current production line process exceeds the set communication lag frequency, or the lag time ratio shows an increasing trend, then the communication of the current production line process will be scheduled and adjusted, and the bandwidth occupancy ratio of different processes will be rescheduled in a timely manner.

[0028] If the communication lag frequency after adjusting the communication priority of the current production line process instruction does not exceed the set communication lag frequency, and the lag time ratio shows an increasing trend, then the communication scheduling strategy of the current production line process will be maintained.

[0029] Furthermore, the process of local communication scheduling on the production line is as follows:

[0030] Obtain remote control of production line processes; manage the communication chain based on the execution process of the remote control processes, and schedule communication resources at each stage of the communication chain as the process progresses;

[0031] When a remotely controlled process needs to be executed, a communication chain is generated. The communication resource parameters are used to receive and respond to the process execution instructions at the current stage. When the process receives the instruction and responds to the feedback, the communication chain extends to the next node, i.e., the process operation node. At this time, the communication resource parameters are allocated according to the operation parameters of the execution equipment of the remotely controlled process, based on the allocation at the communication chain starting point. Communication resource parameters are reserved at the current node for monitoring and responding to the operation parameters. If the operation parameters reach the equipment operation setting range, the communication chain continues to extend; otherwise, the execution equipment is maintained. At this time, the communication resource parameters scheduled by the communication chain starting point are only used for transmitting process execution status parameters, and an execution status detection cycle is set.

[0032] Furthermore, apart from the communication resource parameters allocated at the starting point of the communication chain, all resources are used for the process operation nodes of the communication chain. If the data transmitted by the communication chain reflects that the process operation is qualified, then the communication chain extends to the evaluation node. At the stage where the evaluation node is located, the communication resource parameters required by the process operation node are scheduled. That is, the communication resource parameters for the single data transmission of the process operation node are retained, and the triggering condition for the secondary allocation of communication resource parameters is set. That is, the triggering condition is that the execution status corresponding to the starting point of the communication chain is abnormal, and the abnormality is determined by the occurrence of delay.

[0033] Furthermore, upon entering the stage of executing the evaluation node, the types of data transmitted increase, namely, dynamic image acquisition and sound collection are added to the original sensor detection data. Communication resource parameters are scheduled and adjusted at this stage. If the clarity of the acquired dynamic image is lower than the clarity threshold identified in the current scene, or if the audio compression state cannot accurately acquire waveform data, then communication resource parameters are scheduled according to the communication hardware equipped on the production line, increasing the allocated communication resource parameters for the current remote control process, and these are used for the acquisition data transmission of the evaluation node. If the clarity of the acquired dynamic image is higher than the clarity threshold identified in the current scene, and the audio compression state can accurately acquire waveform data, then in addition to the communication resource parameters allocated at the starting point of the communication chain and the backup communication resource parameters required for transmission by the process operation nodes, the remaining communication resource parameters are used for the acquisition data transmission of the evaluation node.

[0034] Furthermore, the process of communication risk detection is as follows:

[0035] The system collects the usage of communication resource parameters corresponding to key equipment parameters within a set range during production line operation. As the usage continues to increase, it obtains the rate of increase in the cumulative delay of the equipment key parameter collection and feedback closed-loop process. Simultaneously, it obtains the deviation values ​​of the corresponding communication resource parameter settings for different fault-sensitive frequency bands under different operating conditions of the same equipment.

[0036] Furthermore, if the rate of increase of the cumulative delay in the execution of the closed-loop process for collecting and feeding back key equipment parameters exceeds the rate of increase threshold, or if the deviation of the corresponding communication resource parameter settings under different fault-sensitive frequency bands of the same equipment does not exceed the deviation threshold, then according to the operating stage of the equipment covered by the production line process, the communication resource parameters are scheduled in conjunction with the fluctuation trend of the key equipment parameters. That is, during the increase phase of communication resource parameters, if the fluctuation trend of key parameters remains within a controllable range, the adjustment of communication resource parameters during the increase phase is either constant or adaptively reduced.

[0037] If the rate of increase in the cumulative delay of the closed-loop process for collecting and feeding back key equipment parameters does not exceed the rate of increase threshold, and the deviation of the corresponding communication resource parameter settings for different fault-sensitive frequency bands under different operating conditions of the same equipment exceeds the deviation threshold, then it is inferred that the current production line's integrated communication scheduling is efficient, and communication scheduling is carried out according to the current scheduling rhythm of communication resource parameters.

[0038] A multi-level converged communication scheduling system includes a communication scheduling platform, wherein the communication scheduling platform is communicatively connected to an overall production line communication scheduling unit, a local production line communication scheduling unit, and a communication risk detection unit;

[0039] The overall production line communication scheduling unit classifies processes by type, performs demand matching analysis based on each type of process, and conducts communication detection based on the current communication settings.

[0040] The production line local communication scheduling unit allocates communication resource parameters for instruction reception and feedback, performs scheduling allocation based on existing communication resource parameters, and uniformly allocates scheduling based on the communication resource parameters of local processes;

[0041] The communication risk detection unit collects data according to the operational phase; it compares the collected communication scheduling data with thresholds; and it performs communication scheduling rectification based on the comparison results.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] 1. Precisely match process communication needs: By dividing processes into high-frequency and low-frequency segments and dynamically marking scenarios, a unified communication strategy is avoided for all processes, reducing unnecessary scheduling losses and improving data transmission efficiency while ensuring the qualified operation of the production line; Dynamically optimize bandwidth resources: Using log update frequency deviation as the adjustment standard, the bandwidth occupancy ratio of high-frequency and low-frequency processes is dynamically adapted to ensure no data lag in communication, balancing communication stability and resource utilization; Real-time ensure communication reliability: By monitoring the "communication lag frequency" and "lag duration ratio", the communication strategy is adjusted in real time to avoid affecting the production line operation due to communication problems when key parameters are close to the process boundary.

[0044] 2. Focusing on remote control scenarios to improve process control efficiency: For remote control processes (such as hoisting), communication resources are scheduled in stages according to "communication chain start point → operation node → evaluation node" to ensure the accuracy of instruction reception, feedback, and parameter monitoring at each stage; resources are allocated on demand to avoid waste: resources are scheduled on demand at different communication chain nodes (such as reserving monitoring resources at operation nodes and dynamically allocating resources at evaluation nodes based on audio and video clarity), which not only meets the communication needs of each stage but also avoids resource idleness; ensuring the stability of remote processes: by setting execution status detection cycles and abnormal triggering conditions (such as delays), communication problems in remote control are detected and handled in a timely manner, reducing the risk of process execution.

[0045] 3. Mitigating Communication Risks in Production Lines: Addressing the potential "abnormal transmission of risk signals / resource shortages" issues caused by increased data transmission volume in the previous two embodiments, this approach monitors indicators such as resource usage and latency growth to proactively identify inefficient communication scheduling risks. It also adapts to equipment operating conditions and optimizes resource scheduling: By considering the differences in fault-sensitive frequency bands under different equipment operating conditions (full load / no load), communication resource settings are adjusted to ensure timely transmission of fault risk signals and reduce communication delays caused by inappropriate operating condition adaptation. Finally, it balances resources and risks to ensure production line efficiency: Resources are dynamically adjusted based on scheduling efficiency inferences (high efficiency / low efficiency) (e.g., maintaining the pace during high efficiency and adjusting the rate of change based on parameter fluctuation trends during low efficiency), avoiding excessive resource consumption and preventing risks from impacting production line operations. Attached Figure Description

[0046] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0047] Figure 1 This is a flowchart of the method of the present invention;

[0048] Figure 2 This is a system principle block diagram of the present invention. Detailed Implementation

[0049] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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.

[0050] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0051] Industrial manufacturing is developing towards intelligence, digitalization, and networking. Problems such as poor information communication and limited production efficiency in traditional production processes urgently need to be solved. Enterprises need to use communication technologies to achieve real-time data interaction and communication between equipment, accelerate the collection, analysis, and processing of production data, optimize production processes, and improve production efficiency and quality control.

[0052] Example 1

[0053] Please see Figure 1 As shown, a multi-level fusion communication scheduling method is proposed, and the specific communication scheduling method is as follows:

[0054] Multi-level process analysis: In industrial processing scenarios, the parameter acquisition requirements for each process in the production line are different. Therefore, communication scheduling based on process characteristics can be carried out to improve the efficiency of data transmission by integrating communication scheduling under the premise that the production line is operating in a qualified manner.

[0055] The industrial processing line is divided into several processes. The transmission frequency of the fine-tuning parameters of each process is obtained, and the processes are divided into high-frequency processes and low-frequency processes based on the transmission frequency threshold. For example, the finishing stage requires high-frequency transmission of fine-tuning parameters such as tool speed and feed rate.

[0056] Analysis of changes in processing scenario requirements; further classification of processes based on processing scenario analysis; avoid dynamic matching and adjustment of process types when meeting the current static priority allocation, which would generate unnecessary communication scheduling; thereby improving communication stability. Here, static priority allocation means that all devices share bandwidth equally, or priority is divided only according to device type.

[0057] Based on the current task requirements, the fine-tuning frequency of the fine-tuning parameters corresponding to high-frequency processes and the fine-tuning span of the fine-tuning parameters of low-frequency processes are collected. If the fine-tuning frequency of the fine-tuning parameters corresponding to high-frequency processes does not exceed the set fine-tuning frequency, then the high-frequency processes are marked as communication-free processes in the current scenario. If the fine-tuning span of the fine-tuning parameters of low-frequency processes exceeds the set fine-tuning span, then the low-frequency processes are marked as communication-required processes in the current scenario. It should be noted that the span thresholds are all threshold parameters manually set in the actual processing scenario.

[0058] Dynamic demand matching analysis

[0059] A dynamic communication demand matching analysis was conducted for high-frequency and low-frequency processes. Among them, communication in high-frequency processes does not require communication resource allocation for processes without communication adjustments, while communication in low-frequency processes requires communication resource allocation for processes that need communication adjustments.

[0060] Using bandwidth as a communication parameter, the initial bandwidth utilization ratio of the work logs corresponding to high-frequency and low-frequency processes is obtained when the production line is running, that is, the bandwidth utilization ratio is the same under the static priority allocation of communication. When the production line is running continuously, the update frequency deviation of the work logs corresponding to high-frequency and low-frequency processes is obtained. If the update frequency deviation exceeds the set frequency deviation threshold, the high-frequency and low-frequency processes need to be optimized and scheduled for communication. The bandwidth utilization ratio is adjusted according to the standard fluctuation based on the log update frequency deviation. When the standard fluctuation stops, there is no data lag in the process communication under the current bandwidth utilization ratio setting scenario, which indicates that the current bandwidth utilization ratio is suitable, and the current bandwidth utilization ratio is set for communication.

[0061] Communication detection

[0062] Based on the current communication settings, communication detection is performed during the multi-process coordinated operation phase;

[0063] When the key parameters of the production line process are close to the boundary value of the allowable range of the process, the communication lag frequency of the production line after the communication priority of the current production line process instruction is obtained; at the same time, the increase in lag time caused by the fluctuation of the key parameters of the high-frequency process and the corresponding communication instruction, and the decrease in lag time caused by the fluctuation of the key parameters of the low-frequency process and the corresponding communication instruction are obtained, and the lag time ratio is achieved according to the lag time ratio.

[0064] If the communication lag frequency after adjusting the communication priority of the current production line process exceeds the set communication lag frequency, or the lag time ratio shows an increasing trend, then the communication of the current production line process will be scheduled and adjusted, and the bandwidth occupancy ratio of different processes will be rescheduled in a timely manner.

[0065] If the communication lag frequency after adjusting the communication priority of the current production line process instruction does not exceed the set communication lag frequency, and the lag time ratio shows an increasing trend, then the communication scheduling strategy of the current production line process will be maintained.

[0066] Example 2

[0067] The previous embodiment analyzed the production line process as a whole and combined the process characteristics to coordinate the production line operation with communication scheduling. This embodiment, based on the previous embodiment, performs communication scheduling for specific execution scenarios of the production line process.

[0068] Obtain remote control of production line processes, such as remote control of hoisting processes;

[0069] Communication chain management is performed based on the execution process of the remote control procedure, and communication resources are scheduled at each stage of the communication chain as the procedure progresses. In this embodiment, bandwidth utilization ratio is still used as the communication resource parameter.

[0070] When a remotely controlled process needs to be executed, a communication chain is generated. The communication resource parameters at this stage are used to receive and respond to process execution instructions. Upon receiving and responding to the instruction, the communication chain extends to the next node, the process operation node. At this point, the communication resource parameters, allocated at the communication chain's starting point, are determined based on the operating parameters of the equipment executing the remotely controlled process. Communication resource parameters are reserved at the current node for monitoring and responding to operating parameters. If the operating parameters reach the equipment's set operating range, the communication chain continues to extend; otherwise, equipment maintenance is performed. These operating parameters refer to equipment operating parameters such as temperature and rotational speed.

[0071] At this time, the communication resource parameters scheduled by the communication chain start point are only used for the transmission of process execution status parameters, and the execution status detection cycle is set. The execution status is the instruction reception delay, instruction feedback delay, etc.

[0072] Apart from the communication resource parameters allocated at the starting point of the communication chain, all resources are used for the process operation nodes of the communication chain. If the data transmitted by the communication chain shows that the process operation is qualified, the communication chain extends to the evaluation node. At the stage where the evaluation node is located, the communication resource parameters required by the process operation node are scheduled. That is, the communication resource parameters of the process operation node for a single data transmission are retained, and the triggering condition for the secondary allocation of communication resource parameters is set. That is, the triggering condition is that the execution status corresponding to the starting point of the communication chain is abnormal, and the abnormality is determined by the occurrence of delay.

[0073] Upon entering the evaluation node stage, the types of data transmitted increase, adding dynamic image acquisition and sound collection to the existing sensor detection data. Communication resource parameters are then scheduled and adjusted. If the clarity of the acquired dynamic image is lower than the current scene's recognition threshold, or if the audio compression prevents accurate waveform data acquisition, communication resource parameters are adjusted based on the production line's communication hardware. This increases the allocated communication resource parameters for the current remote control process and is used for data transmission at the evaluation node. Conversely, if the clarity of the acquired dynamic image is higher than the current scene's recognition threshold, and the audio compression allows for accurate waveform data acquisition, the remaining communication resource parameters, after accounting for the communication resource parameters allocated at the communication chain's starting point and the backup communication resource parameters required for the process operation nodes, are used for data transmission at the evaluation node.

[0074] Communication resource parameters are allocated and scheduled according to different nodes in the communication chain to meet the communication needs at different stages and improve process control efficiency.

[0075] Example 3

[0076] Combining the process communication scheduling of Embodiment 1 and Embodiment 2, this embodiment performs production line risk communication scheduling on the basis of the previous embodiment. That is, a large amount of transmission data is generated through Embodiment 1 and Embodiment 2, which increases the occupation of communication resource parameters. This is to prevent abnormal transmission of production line risk signals or failure to allocate communication resource parameters for risk signals, which would cause untimely signal transmission and communication lag, and reduce the operating efficiency of the production line.

[0077] The system collects the communication resource occupancy of key equipment parameters within a set range during production line operation. As the occupancy continues to increase, it obtains the rate of increase in the cumulative delay of the equipment key parameter collection and feedback closed-loop process.

[0078] At the same time, the deviation values ​​of the corresponding communication resource parameter settings are obtained for different fault-sensitive frequency bands under different operating conditions of the same equipment; different operating conditions are represented as full-load operation and no-load debugging; for example, the fault-sensitive frequency band of the spindle bearing is 1-2kHz under full load and 0.5-1kHz under no-load.

[0079] The rate of increase in the cumulative delay of the closed-loop process for collecting and feeding back key equipment parameters, and the deviation of the corresponding communication resource parameter settings for different fault-sensitive frequency bands under different operating conditions of the same equipment, are compared with the rate of increase threshold and the deviation threshold, respectively.

[0080] If the cumulative delay of the closed-loop process for collecting and feeding back key equipment parameters increases at a rate exceeding the increase threshold, or if the deviation of the corresponding communication resource parameter settings does not exceed the deviation threshold under different operating conditions of the same equipment in different fault-sensitive frequency bands, it is inferred that the current integrated communication scheduling of the production line is inefficient. Based on the operating stage of the equipment covered by the production line process, the communication resource parameter scheduling is combined with the fluctuation trend of the key equipment parameters, i.e., the communication resource parameter increase stage. If the fluctuation trend of the key parameters is continuously within a controllable range, the adjustment of the communication resource parameters during the increase stage is constant or adaptively reduced.

[0081] If the rate of increase in the cumulative delay of the closed-loop process for collecting and feeding back key equipment parameters does not exceed the rate of increase threshold, and the deviation of the corresponding communication resource parameter settings for different fault-sensitive frequency bands under different operating conditions of the same equipment exceeds the deviation threshold, then it is inferred that the current production line's integrated communication scheduling is efficient, and communication scheduling is carried out according to the current scheduling rhythm of communication resource parameters.

[0082] Example 4

[0083] Please see Figure 2 As shown, a multi-level converged communication scheduling system includes a communication scheduling platform, wherein the communication scheduling platform is communicatively connected to an overall production line communication scheduling unit, a local production line communication scheduling unit, and a communication risk detection unit;

[0084] The overall production line communication scheduling unit classifies processes by type, performs demand matching analysis based on each type of process, and conducts communication detection based on the current communication settings.

[0085] The production line local communication scheduling unit allocates communication resource parameters for instruction reception and feedback, performs scheduling allocation based on existing communication resource parameters, and uniformly allocates scheduling based on the communication resource parameters of local processes;

[0086] The communication risk detection unit collects data according to the operational phase; it compares the collected communication scheduling data with thresholds; and it performs communication scheduling rectification based on the comparison results.

[0087] Thresholds, preset values, preset ranges, etc. are set for result comparison and analysis to determine whether they are good or bad. The value of these thresholds is determined by a combination of large-scale model analysis of sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influencing factors.

[0088] Furthermore, the settings for weighting ratios, influence factors, etc., are based on the magnitude of each parameter's influence on the results. The specific values ​​are allocated to ultimately reflect the impact on the results. The settings for input and storage are also determined by a combination of large-scale model analysis of sample data and human experience. Appropriate adjustments can also be made based on seasonal or rational influence conditions.

[0089] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A multi-level fusion communication scheduling method, characterized in that, The communication scheduling method is as follows: S1: Overall production line communication scheduling: S11: Multi-level process analysis, classifying processes by type; S12: Dynamic demand matching analysis, performing demand matching analysis based on each type of process; S13: Communication detection, perform communication detection based on the current communication settings; S2: Production line local communication scheduling: S21: Communication link start point generation, and allocation of communication resource parameters for instruction reception and feedback; S22: The process operation node is extended and scheduled and allocated according to the existing communication resource parameters; S23: Obtain the execution evaluation node and allocate and schedule it in a unified manner based on the communication resource parameters of the local process; S3: Communication Risk Detection S31: Production line process operation monitoring, with data collection added according to the operation stage; S32: Communication scheduling data analysis, threshold comparison based on the collected communication scheduling data; S33: Based on the comparison results, conduct communication scheduling and rectification.

2. The multi-level fusion communication scheduling method according to claim 1, characterized in that, The multi-level analysis process for process S11 is as follows: The industrial processing line is divided into several processes. The transmission frequency of the fine-tuning parameters in each process stage is obtained, and the processes are divided into high-frequency processes and low-frequency processes based on the transmission frequency threshold. According to the current task requirements, the fine-tuning frequency of the corresponding fine-tuning parameters of the high-frequency processes and the fine-tuning span of the fine-tuning parameters of the low-frequency processes are collected. If the fine-tuning frequency of the corresponding fine-tuning parameters of the high-frequency processes does not exceed the set fine-tuning frequency, the high-frequency processes are marked as communication-free processes in the current scenario. If the fine-tuning span of the fine-tuning parameters of the low-frequency processes exceeds the set fine-tuning span, the low-frequency processes are marked as communication-required processes in the current scenario.

3. The multi-level fusion communication scheduling method according to claim 2, characterized in that, The process of S12 dynamic demand matching analysis is as follows: Analysis of dynamic communication requirements matching between high-frequency and low-frequency processes; Using bandwidth as a communication parameter, the initial bandwidth utilization ratio of the work logs corresponding to high-frequency and low-frequency processes is obtained when the production line is running, i.e., the bandwidth utilization ratio is the same under the static priority allocation of communication. When the production line is running continuously, the update frequency deviation of the work logs corresponding to high-frequency and low-frequency processes is obtained. If the update frequency deviation exceeds the set frequency deviation threshold, the high-frequency and low-frequency processes need to be optimized and scheduled for communication. The bandwidth utilization ratio is adjusted according to the standard fluctuation based on the log update frequency deviation. When the standard fluctuation stops, there is no data lag in the process communication under the current bandwidth utilization ratio setting scenario, which indicates that the current bandwidth utilization ratio is suitable, and the current bandwidth utilization ratio is set for communication.

4. The multi-level fusion communication scheduling method according to claim 3, characterized in that, The S13 communication detection process is as follows: When the key parameters of the production line process are close to the boundary value of the allowable range of the process, the communication lag frequency of the production line after the communication priority of the current production line process instruction is obtained; at the same time, the increase in lag time caused by the fluctuation of the key parameters of the high-frequency process and the corresponding communication instruction, and the decrease in lag time caused by the fluctuation of the key parameters of the low-frequency process and the corresponding communication instruction are obtained, and the lag time ratio is achieved according to the lag time ratio. If the communication lag frequency after adjusting the communication priority of the current production line process exceeds the set communication lag frequency, or the lag time ratio shows an increasing trend, then the communication of the current production line process will be scheduled and adjusted, and the bandwidth occupancy ratio of different processes will be rescheduled in a timely manner. If the communication lag frequency after adjusting the communication priority of the current production line process instruction does not exceed the set communication lag frequency, and the lag time ratio shows an increasing trend, then the communication scheduling strategy of the current production line process will be maintained.

5. The multi-level fusion communication scheduling method according to claim 1, characterized in that, The process of local communication scheduling on the production line is as follows: Obtain remote control of production line processes; manage the communication chain based on the execution process of the remote control processes, and schedule communication resources at each stage of the communication chain as the process progresses; When a remotely controlled process needs to be executed, a communication chain is generated. The communication resource parameters are used to receive and respond to the process execution instructions at the current stage. When the process receives the instruction and responds to the feedback, the communication chain extends to the next node, i.e., the process operation node. At this time, the communication resource parameters are allocated according to the operation parameters of the execution equipment of the remotely controlled process, based on the allocation at the communication chain starting point. Communication resource parameters are reserved at the current node for monitoring and responding to the operation parameters. If the operation parameters reach the equipment operation setting range, the communication chain continues to extend; otherwise, the execution equipment is maintained. At this time, the communication resource parameters scheduled by the communication chain starting point are only used for transmitting process execution status parameters, and an execution status detection cycle is set.

6. The multi-level fusion communication scheduling method according to claim 5, characterized in that, Apart from the communication resource parameters allocated at the starting point of the communication chain, all resources are used for the process operation nodes of the communication chain. If the data transmitted by the communication chain shows that the process operation is qualified, the communication chain extends to the evaluation node. At the stage where the evaluation node is located, the communication resource parameters required by the process operation node are scheduled. That is, the communication resource parameters of the process operation node for a single data transmission are retained, and the triggering condition for the secondary allocation of communication resource parameters is set. That is, the triggering condition is that the execution status corresponding to the starting point of the communication chain is abnormal, and the abnormality is determined by the occurrence of delay.

7. The multi-level fusion communication scheduling method according to claim 6, characterized in that, Upon entering the evaluation node stage, the types of data transmitted increase, adding dynamic image acquisition and sound collection to the existing sensor detection data. Communication resource parameters are scheduled and adjusted at this stage. If the clarity of the acquired dynamic image is lower than the clarity threshold identified in the current scene, or if the audio compression status prevents accurate waveform data acquisition, communication resource parameters are scheduled based on the communication hardware equipped on the production line. This increases the allocated communication resource parameters for the current remote control process and is used for data transmission at the evaluation node. If the clarity of the acquired dynamic image is higher than the clarity threshold identified in the current scene, and the audio compression status allows for accurate waveform data acquisition, then in addition to the communication resource parameters allocated at the beginning of the communication chain and the backup communication resource parameters required for transmission at the process operation nodes, the remaining communication resource parameters are used for data transmission at the evaluation node.

8. The multi-level fusion communication scheduling method according to claim 1, characterized in that, The process of communication risk detection is as follows: The system collects the usage of communication resource parameters corresponding to key equipment parameters within a set range during production line operation. As the usage continues to increase, it obtains the rate of increase in the cumulative delay of the equipment key parameter collection and feedback closed-loop process. Simultaneously, it obtains the deviation values ​​of the corresponding communication resource parameter settings for different fault-sensitive frequency bands under different operating conditions of the same equipment.

9. A multi-level fusion communication scheduling method according to claim 8, characterized in that, If the rate of increase of the cumulative delay in the execution of the closed-loop process for collecting and feeding back key equipment parameters exceeds the increase rate threshold, or if the deviation of the communication resource parameter settings corresponding to different fault-sensitive frequency bands under different operating conditions of the same equipment does not exceed the deviation threshold, then the communication resource parameter scheduling will be combined with the fluctuation trend of the key equipment parameters according to the operating stage of the equipment covered by the production line process. That is, during the communication resource parameter increase stage, if the fluctuation trend of the key parameters remains within a controllable range, the adjustment of the communication resource parameters during the increase stage will be constant or adaptively reduced. If the rate of increase of the cumulative delay in the execution of the closed-loop process for collecting and feeding back key equipment parameters does not exceed the increase rate threshold, and the deviation of the communication resource parameter settings corresponding to different fault-sensitive frequency bands under different operating conditions of the same equipment exceeds the deviation threshold, then communication scheduling will be carried out according to the current communication resource parameter scheduling rhythm.

10. A multi-level converged communication scheduling system, characterized in that, The system program is configured to implement the steps of a multi-level converged communication scheduling method as described in any one of claims 1 to 9.

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