Tunnel electromechanical equipment edge control system and method compatible with multiple communication protocols

Abstract

The invention discloses a tunnel electromechanical equipment edge control system and method compatible with multiple communication protocols. The system comprises a self-adaptive protocol identification unit used for automatically identifying and adapting to multiple communication protocols; the intelligent protocol stack processing module is used for analyzing and packaging data packets of different protocols based on a deep learning algorithm to realize seamless conversion between the protocols; the real-time data processing center is used for analyzing and processing the collected data in real time; the environment self-adaption unit is used for monitoring tunnel environment parameters in real time and dynamically adjusting the working mode of the system according to the environment parameters; the intelligent control instruction generator is used for generating a control instruction according to a preset control strategy and a real-time data analysis result so as to optimize the working state of the electromechanical equipment; and the network communication optimization module is used for formulating a network communication optimization strategy according to the network state and continuously adjusting and optimizing the network communication strategy based on feedback. According to the invention, the overall intelligent level of tunnel monitoring is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of highway control, and particularly to an edge control system and method for tunnel electromechanical equipment compatible with multiple communication protocols. Background Art

[0002] Traditional tunnel electromechanical equipment usually uses a single communication protocol for control and monitoring, such as common protocols like MODBUS, CAN, BACnet, etc. Each electromechanical device communicates with the control system according to its specific communication protocol. The connection between the control system and the electromechanical device is relatively fixed, and the communication method and parameter settings are determined during equipment installation, lacking flexibility. Data processing and control instruction generation are often carried out on a centralized server or controller. Data transmission requires a long network path, increasing data transmission delay and having poor adaptability to the tunnel environment with high real-time requirements. For devices with different communication protocols, corresponding interfaces and driver programs need to be developed and maintained separately, making the system integration and expansion difficult.

[0003] It can be seen that in the existing technology, due to different electromechanical devices using different communication protocols, there are great compatibility difficulties in data exchange and coordinated control among multiple devices. When new devices are added or replaced, the entire control system may need to be reconfigured and developed, with high costs and low efficiency. The tunnel environment is special, and many electromechanical devices need to operate under conditions of high real-time requirements and unstable networks. The traditional scheme has a long data transmission path and large data transmission delay, unable to meet the real-time control requirements of devices, and prone to data loss or instruction execution failure during network fluctuations, affecting system reliability. Most existing systems only support a single communication protocol and are difficult to be compatible with multiple new devices and new technologies. With the continuous update and increase of tunnel electromechanical equipment, the system cannot be effectively expanded to meet new requirements, restricting the intelligent development of the tunnel monitoring system. Devices with different communication protocols require different operation and maintenance methods and tools, increasing the complexity and cost of operation and maintenance management. At the same time, due to the lack of a unified device management and data processing mechanism, it is difficult to diagnose faults and monitor the device status, which is not conducive to timely discovery and solution of problems. Summary of the Invention

[0004] The purpose of the present invention is to provide an edge control system and method for tunnel electromechanical equipment compatible with multiple communication protocols.

[0005] The technical solution adopted by the present invention is: An edge control system for tunnel electromechanical equipment compatible with multiple communication protocols, which includes an adaptive protocol recognition unit, an energy protocol stack processing module, a time data processing center, an environment adaptive unit, an intelligent control instruction generator, and a network communication optimization module; The adaptive protocol recognition unit is used to automatically recognize and adapt to multiple communication protocols including serial communication protocols, Ethernet communication protocols, and wireless communication protocols; Specifically, the adaptive protocol recognition unit adopts a combination of hardware and software, and through a preset communication protocol library and machine learning algorithms, automatically recognizes serial communication protocols, Ethernet communication protocols, and wireless communication protocols and dynamically adapts.

[0006] The intelligent protocol stack processing module is used to parse and encapsulate data packets of different protocols based on deep learning algorithms, realizing seamless conversion between protocols.

[0007] The real-time data processing center is used to perform real-time analysis and processing on the collected data to support rapid decision-making.

[0008] Specifically, the real-time data processing center innovatively realizes real-time cleaning, analysis, and storage of data through efficient data processing algorithms configured on edge computing nodes, providing support for rapid decision-making.

[0009] The environment adaptation unit is integrated with a microcontroller and several sensors for detecting environmental parameters. The environment adaptation unit is used to monitor tunnel environmental parameters in real time and dynamically adjust the working mode of the system according to the environmental parameters.

[0010] The intelligent control instruction generator is used to generate control instructions according to preset control strategies and real-time data analysis results to optimize the working state of electromechanical equipment.

[0011] The network communication optimization module is used to formulate an optimized network communication strategy according to the monitored network status, and continuously adjust and optimize the network communication strategy based on the implementation results of the feedback network optimization strategy; specifically, QoS (Quality of Service) technology and redundant communication path design structure are adopted to ensure the real-time and reliability of data transmission.

[0012] A tunnel electromechanical equipment edge control method compatible with multiple communication protocols includes the following steps: Step 1, analyze the input data stream, and automatically recognize and adapt to the specific communication protocol used by the data stream; the communication protocol includes multiple communication protocols including serial communication protocols, Ethernet communication protocols, and wireless communication protocols; Further, in step 1, receive the original data stream from the adaptive protocol recognition unit, and the original data stream contains information of different protocols; analyze the input data stream, extract key features such as packet structure, control characters, specific sequences, etc.; match the extracted features with the protocol library built in the module to identify the specific communication protocol used by the data stream.

[0013] Step 2: Based on deep learning algorithms, analyze and encapsulate data packets of different protocols to convert the current protocol into the target protocol, achieving seamless conversion between protocols.

[0014] Further, Step 2 specifically includes the following steps: Step 2-1: Protocol conversion and processing: According to the identified protocol type, select an appropriate conversion strategy, which may involve converting one protocol format to another; perform conversion operations, including data packet recombination, format conversion, encoding / decoding, etc., to ensure seamless data transmission between different protocols; during the conversion process, if errors or data corruption are encountered, execute error detection and correction mechanisms to ensure data integrity.

[0015] Step 2-2: Output verification and feedback: Verify whether the converted data complies with the target protocol specifications to ensure data correctness and usability; output the converted data to the next processing module, such as a real-time data processing center; record the entire processing process, including performance metrics such as conversion time and error rate, for performance optimization and error prevention in subsequent modules.

[0016] Step 3: Identify the data type according to the target protocol, perform real-time analysis and processing on the collected data to obtain analysis results, and output the analysis results in the form of real-time monitoring, alarms, or reports; Further, Step 3 specifically includes the following steps: Step 3-1: Data collection and synchronization: Real-time collect data from data sources such as sensors and monitoring devices. Synchronize the collected data to ensure data consistency.

[0017] Step 3-2: Data processing and analysis: Perform real-time cleaning, filtering, and aggregation on the data to extract useful information. Apply data analysis algorithms, such as statistical analysis and machine learning models, to deeply analyze the data.

[0018] Step 3-3: Result output and application: Output the analysis results in the form of real-time monitoring, alarms, or reports. Apply the analysis results to control strategy adjustment or automated decision support.

[0019] Step 4: Real-time monitor the tunnel environmental parameters and dynamically adjust the working mode of the system according to the environmental parameters; Further, Step 4 specifically includes the following steps: Step 4-1: Environmental monitoring: Real-time monitor the environmental parameters in the tunnel, such as temperature, humidity, light, smoke, etc. Collect and record environmental data for subsequent analysis.

[0020] Step 4-2: Parameter analysis: Analyze the changing trends of environmental parameters and identify potential environmental problems. Evaluate the impact on system performance according to the changes in environmental parameters.

[0021] Step 4-3, Adaptive Adjustment: According to the environmental analysis results, adjust the working mode of the system, such as changing the ventilation frequency, lighting intensity, etc. Ensure that the system maintains optimal performance under changing environmental conditions.

[0022] Step 5, Generate control instructions based on the preset control strategy and the real-time data analysis results to optimize the working state of the electromechanical equipment.

[0023] Further, Step 5 specifically includes the following steps: Step 5-1, Data Integration: Integrate the data from the real-time data processing center and the environmental adaptation unit. Ensure the accuracy and integrity of the data.

[0024] Step 5-2, Control Strategy Formulation: According to the integrated data, apply control algorithms to formulate corresponding control strategies. Generate control instructions, such as switch control, adjustment parameters, etc.

[0025] Step 5-3, Instruction Verification and Execution: Verify whether the generated control instructions are reasonable to avoid potential safety risks. Send the verified instructions to the execution unit, such as the electromechanical equipment controller.

[0026] Step 6, Formulate an optimized network communication strategy based on the monitored network status, and continuously adjust and optimize the network communication strategy based on the implementation results of the feedback network optimization strategy.

[0027] Further, Step 6 specifically includes the following steps: Step 6-1, Network Monitoring: Monitor the network status, including indicators such as bandwidth usage, latency, packet loss rate, etc. Identify bottlenecks and potential fault points in the network.

[0028] Step 6-2, Optimization Strategy Formulation: According to the network monitoring results, formulate optimization strategies, such as adjusting routing, QoS settings, network congestion control, etc. Select the best network configuration to improve communication efficiency.

[0029] Step 6-3, Strategy Implementation and Feedback: Implement the formulated optimization strategy and monitor the effect. Provide feedback based on the implementation results and continuously adjust and optimize the network communication strategy.

[0030] With the above technical solutions, the present invention can identify and convert data of multiple communication protocols through a multi-protocol conversion module, unifying them into a format recognizable by the edge control unit. Compared with traditional technologies that only support a single communication protocol, it can be compatible with various electromechanical devices using different communication protocols. Whether it is a device using protocols such as MODBUS, CAN, or BACnet, it can be connected to the system for effective control and management, greatly improving the compatibility of the system with different devices and facilitating the integration and upgrading of devices. The edge control unit of the present invention receives and processes data near the electromechanical device end, reducing the data transmission path and transmission delay, and can respond more quickly to changes in device status and generate control instructions, meeting the high requirements for real-time control of tunnel electromechanical devices. At the same time, during the data transmission process, corresponding monitoring and error handling mechanisms are available in links such as data reading and writing operations of communication interfaces and data conversion verification of the multi-protocol conversion module, ensuring the accurate transmission of data and the reliable execution of instructions, improving the overall reliability of the system and having more advantages than traditional technologies in an unstable network environment. The architecture design and technical solutions of the system of the present invention endow it with good scalability. When new devices are connected, the edge control unit can automatically identify the device type and communication protocol, select appropriate configurations for connection and management, without the need for large-scale changes to the entire system. It supports dynamic configuration of multiple communication protocols and device connection forms, can easily adapt to the increasing and updating needs of tunnel electromechanical devices, is conducive to the continuous intelligent upgrade of the tunnel monitoring system, and overcomes the problem of limited scalability of traditional technologies. The environmental monitoring module of the present invention can monitor the environmental parameters in the tunnel and verify the effectiveness and compatibility of the system, providing data support for operation and maintenance. The data processing module comprehensively analyzes and processes device data, including denoising, normalization, algorithm analysis, etc., can more accurately evaluate the device status, predict faults, and facilitate timely maintenance. Through the electromechanical physical model, the devices are standardized for management, the key information of the devices is recorded, and the unified management platform can display the device status and fault information in real time, improving the efficiency and accuracy of operation and maintenance management, reducing the operation and maintenance difficulty and cost, and forming a sharp contrast with the complex operation and maintenance methods of traditional technologies. The intelligent protocol stack based on multi-data source fusion of the present invention not only supports plug-and-play of devices, but also ensures collaborative communication between the cloud, edge, and end, realizing the effective integration and intelligent interaction of data. Through preset control strategies and data analysis algorithms, the system can automatically generate reasonable control instructions according to the device status and environmental parameters, realizing the intelligent control of tunnel electromechanical devices and improving the overall intelligent level of tunnel monitoring, while traditional technologies are relatively low in terms of intelligence level. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The following further elaborates on the present invention in detail in conjunction with the accompanying drawings and specific embodiments; Figure 1This is a schematic diagram of the principle architecture of an edge control system for tunnel electromechanical equipment that is compatible with multiple communication protocols in the present invention. Specific embodiments

[0032] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application.

[0033] As Figure 1 shown, the present invention discloses an edge control system for tunnel electromechanical equipment that is compatible with multiple communication protocols, which is used for the monitoring and control of electromechanical equipment in a tunnel environment. The system includes an adaptive protocol recognition unit, an intelligent protocol stack processing module, a real-time data processing center, an environment adaptation unit, an intelligent control instruction generator, and a network communication optimization module. The adaptive protocol recognition unit is used to automatically identify and adapt to multiple communication protocols including serial communication protocols, Ethernet communication protocols, and wireless communication protocols. Specifically, the adaptive protocol recognition unit adopts a combination of hardware and software, and through a preset communication protocol library and machine learning algorithms, automatically identifies serial communication protocols, Ethernet communication protocols, and wireless communication protocols and dynamically adapts to them.

[0034] The intelligent protocol stack processing module is used to parse and encapsulate data packets of different protocols based on deep learning algorithms to achieve seamless conversion between protocols.

[0035] The real-time data processing center is used to perform real-time analysis and processing on the collected data to support rapid decision-making.

[0036] Specifically, the real-time data processing center innovatively realizes the real-time cleaning, analysis, and storage of data through efficient data processing algorithms configured on edge computing nodes, providing support for rapid decision-making.

[0037] The environment adaptation unit is integrated with a microcontroller and several sensors for detecting environmental parameters. The environment adaptation unit is used to monitor tunnel environmental parameters in real time and dynamically adjust the working mode of the system according to the environmental parameters.

[0038] The intelligent control instruction generator is used to generate control instructions according to preset control strategies and real-time data analysis results to optimize the working state of electromechanical equipment.

[0039] The network communication optimization module is used to formulate an optimized network communication strategy according to the monitored network status, and continuously adjust and optimize the network communication strategy based on the implementation results of the feedback network optimization strategy; specifically, QoS (Quality of Service) technology and redundant communication path design structures are adopted to ensure the real-time and reliable data transmission.

[0040] The present invention innovatively realizes the automatic identification and adaptation of data streams, reduces manual intervention, and improves the automation level of the system. The present invention innovatively performs data processing at the edge, reduces latency, and improves the response speed. The present invention innovatively adjusts system parameters automatically according to environmental changes, enhances the environmental adaptability and stability of the system. The present invention innovatively combines the data analysis results and environmental parameters to generate optimal control instructions, improving the control effect. The present invention innovatively ensures the stability and reliability of data transmission by monitoring and optimizing the network state. The system of the present invention is applicable to a variety of complex tunnel environments, can effectively monitor and control electromechanical equipment, and improve the safety and efficiency of tunnel operation.

[0041] Furthermore, the present invention also discloses an edge control method for tunnel electromechanical equipment compatible with multiple communication protocols, which includes the following steps: Step 1, Adaptive protocol identification: Analyze the input data stream to automatically identify and adapt the specific communication protocol used by the data stream; the communication protocols include multiple communication protocols such as serial communication protocols, Ethernet communication protocols, and wireless communication protocols. Specifically, the adaptive protocol identification includes steps such as initializing the communication interface, identifying the protocol to which the data stream belongs, and configuring the protocol adapter, innovatively realizing the automatic identification and adaptation of the protocol.

[0042] Furthermore, in Step 1, receive the original data stream from the adaptive protocol identification unit, and the original data stream contains information of different protocols; analyze the input data stream, extract key features such as packet structure, control characters, specific sequences, etc.; match the extracted features with the protocol library built into the module to identify the specific communication protocol used by the data stream.

[0043] Step 2, Intelligent protocol stack processing: Analyze and encapsulate data packets of different protocols based on deep learning algorithms to convert the current protocol into the target protocol, realizing seamless conversion between protocols.

[0044] Specifically, the intelligent protocol stack processing includes steps such as protocol parsing, data encapsulation, and recording conversion logs, innovatively realizing seamless conversion between different protocols.

[0045] Furthermore, Step 2 specifically includes the following steps: Step 2-1, Protocol conversion and processing: According to the identified protocol type, select an appropriate conversion strategy, which may involve converting one protocol format to another; perform conversion operations, including packet reorganization, format conversion, encoding / decoding, etc., to ensure seamless data transmission between different protocols; during the conversion process, if an error or data corruption is encountered, execute an error detection and correction mechanism to ensure data integrity.

[0046] Step 2-2, Output Verification and Feedback: Verify whether the converted data conforms to the target protocol specifications to ensure the correctness and usability of the data; output the converted data to the next processing module, such as the real-time data processing center; record the entire processing process, including performance metrics such as conversion time and error rate, for performance optimization and error prevention in subsequent modules.

[0047] Step 3, Real-time Data Processing: Identify the data type according to the target protocol, perform real-time analysis and processing on the collected data to obtain the analysis results, and output the analysis results in the form of real-time monitoring, alarms, or reports; Specifically, real-time data processing includes steps such as data cleaning, analysis, and storage, and innovatively realizes fast data processing at the edge.

[0048] Furthermore, Step 3 specifically includes the following steps: Step 3-1, Data Acquisition and Synchronization: Real-time collect data from data sources such as sensors and monitoring devices. Synchronize the collected data in terms of time to ensure data consistency.

[0049] Step 3-2, Data Processing and Analysis: Perform real-time cleaning, filtering, and aggregation on the data to extract useful information. Apply data analysis algorithms, such as statistical analysis and machine learning models, to deeply analyze the data.

[0050] Step 3-3, Result Output and Application: Output the analysis results in the form of real-time monitoring, alarms, or reports. Apply the analysis results to control strategy adjustment or automated decision support.

[0051] Step 4, Environment Adaptive Adjustment: Real-time monitor the tunnel environment parameters and dynamically adjust the working mode of the system according to the environment parameters; Specifically, environment adaptive adjustment includes steps such as collecting environment data, analyzing the data, and adjusting system parameters, and innovatively enables the system to automatically adjust the working mode according to environmental changes.

[0052] Furthermore, Step 4 specifically includes the following steps: Step 4-1, Environment Monitoring: Real-time monitor the environment parameters in the tunnel, such as temperature, humidity, light, smoke, etc. Collect and record the environment data for subsequent analysis.

[0053] Step 4-2, Parameter Analysis: Analyze the changing trends of the environment parameters and identify potential environmental problems. Evaluate the impact on system performance according to the changes in the environment parameters.

[0054] Step 4-3, Adaptive Adjustment: Adjust the working mode of the system according to the environment analysis results, such as changing the ventilation frequency and lighting intensity. Ensure that the system maintains optimal performance under changing environmental conditions.

[0055] Step 5, Intelligent Control Instruction Generation: Generate control instructions according to the preset control strategy and the real-time data analysis results to optimize the working state of the electromechanical equipment.

[0056] Specifically, the intelligent control instruction generation includes steps such as data integration, control strategy formulation, instruction verification and execution, and innovatively generates optimized control instructions based on real-time data and environmental parameters.

[0057] Further, Step 5 specifically includes the following steps: Step 5-1, Data Integration: Integrate the data from the real-time data processing center and the environmental adaptation unit. Ensure the accuracy and integrity of the data.

[0058] Step 5-2, Control Strategy Formulation: According to the integrated data, apply control algorithms to formulate corresponding control strategies. Generate control instructions such as switch control, adjustment parameters, etc.

[0059] Step 5-3, Instruction Verification and Execution: Verify whether the generated control instructions are reasonable to avoid potential safety risks. Send the verified instructions to the execution unit, such as the electromechanical equipment controller.

[0060] Step 6, Network Communication Optimization: Formulate an optimized network communication strategy according to the monitored network status, and continuously adjust and optimize the network communication strategy based on the implementation results of the feedback network optimization strategy.

[0061] Specifically, the network communication optimization includes steps such as network monitoring, optimization strategy formulation, strategy implementation and feedback, and innovatively ensures the real-time and reliability of data transmission.

[0062] Further, Step 6 specifically includes the following steps: Step 6-1, Network Monitoring: Monitor the network status, including indicators such as bandwidth usage, latency, packet loss rate, etc. Identify bottlenecks and potential fault points in the network.

[0063] Step 6-2, Optimization Strategy Formulation: According to the network monitoring results, formulate optimization strategies such as adjusting the routing, QoS settings, network congestion control, etc. Select the best network configuration to improve communication efficiency.

[0064] Step 6-3, Strategy Implementation and Feedback: Implement the formulated optimization strategy and monitor the effect. Provide feedback according to the implementation results and continuously adjust and optimize the network communication strategy.

[0065] With the above technical solutions, the present invention can identify and convert data of multiple communication protocols through the multi-protocol conversion module, unifying them into a format recognizable by the edge control unit. Compared with traditional technologies that only support a single communication protocol, it can be compatible with various electromechanical devices using different communication protocols. Whether it is a device using protocols such as MODBUS, CAN, or BACnet, it can be connected to the system for effective control and management, greatly improving the compatibility of the system with different devices and facilitating the integration and upgrading of devices.

[0066] The edge control unit of the present invention receives and processes data near the electromechanical device end, reducing the data transmission path and transmission delay, and can respond faster to changes in device status and generate control instructions, meeting the high requirements for real-time control of tunnel electromechanical devices. At the same time, during the data transmission process, such as data reading and writing operations of communication interfaces and data conversion verification of the multi-protocol conversion module, there are corresponding monitoring and error handling mechanisms to ensure the accurate transmission of data and the reliable execution of instructions, improving the overall reliability of the system and having more advantages compared with traditional technologies in an unstable network environment.

[0067] The architecture design and technical solutions of the system of the present invention endow it with good scalability. When new devices are connected, the edge control unit can automatically identify the device type and communication protocol, select appropriate configurations for connection and management, without the need for large-scale modifications to the entire system. It supports dynamic configuration of multiple communication protocols and device connection forms, can easily adapt to the increasing and updating needs of tunnel electromechanical devices, and is conducive to the continuous intelligent upgrading of the tunnel monitoring system, overcoming the problem of limited scalability of traditional technologies.

[0068] The environmental monitoring module of the present invention can monitor environmental parameters in the tunnel and verify the effectiveness and compatibility of the system, providing data support for operation and maintenance. The data processing module comprehensively analyzes and processes device data, including denoising, normalization, algorithm analysis, etc., can more accurately evaluate the device status, predict faults, and facilitate timely maintenance. Through the electromechanical physical model, standardized management of devices is carried out, key device information is recorded, and the unified management platform can display device status and fault information in real time, improving the efficiency and accuracy of operation and maintenance management, reducing the operation and maintenance difficulty and cost, and forming a sharp contrast with the complex operation and maintenance methods of traditional technologies.

[0069] Based on the intelligent protocol stack integrating multiple data sources, the present invention not only supports plug-and-play of devices, but also ensures collaborative communication between the cloud, edge, and end, realizing effective integration and intelligent interaction of data. Through preset control strategies and data analysis algorithms, the system can automatically generate reasonable control instructions according to device status and environmental parameters, realizing intelligent control of tunnel electromechanical devices and improving the overall intelligent level of tunnel monitoring, while traditional technologies are relatively low in terms of intelligence.

[0070] Obviously, the described embodiments are some, but not all, of the embodiments of this application. Without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. Generally, the components of the embodiments of this application described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of this application is not intended to limit the scope of this application claimed, but merely represents selected embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

Claims

1. An edge control system for tunnel electromechanical equipment compatible with multiple communication protocols, characterized in that: It includes an adaptive protocol recognition unit, an intelligent protocol stack processing module, a real-time data processing center, an environment adaptation unit, an intelligent control instruction generator, and a network communication optimization module; The adaptive protocol recognition unit is used to automatically identify and adapt to multiple communication protocols including serial communication protocols, Ethernet communication protocols, and wireless communication protocols; The intelligent protocol stack processing module is used to parse and encapsulate data packets of different protocols based on deep learning algorithms to achieve seamless conversion between protocols; The real-time data processing center is used to perform real-time analysis and processing on the collected data to support rapid decision-making; The environment adaptation unit is integrated with a microcontroller and several sensors for detecting environmental parameters. The environment adaptation unit is used to monitor tunnel environmental parameters in real time and dynamically adjust the working mode of the system according to the environmental parameters; The intelligent control instruction generator is used to generate control instructions according to the preset control strategy and the real-time data analysis results to optimize the working state of the electromechanical equipment; The network communication optimization module is used to formulate an optimized network communication strategy according to the monitored network status and continuously adjust and optimize the network communication strategy based on the implementation results of the feedback network optimization strategy.

2. A method for edge control of tunnel electromechanical equipment compatible with multiple communication protocols, which adopts a system for edge control of tunnel electromechanical equipment compatible with multiple communication protocols as described in claim 1, and is characterized in that: The method includes the following steps: Step 1, analyze the input data stream to automatically identify and adapt to the specific communication protocol used by the data stream; the communication protocol includes multiple communication protocols including serial communication protocols, Ethernet communication protocols, and wireless communication protocols; Step 2, parse and encapsulate data packets of different protocols based on deep learning algorithms to convert the current protocol into the target protocol to achieve seamless conversion between protocols; Step 3, identify the data type according to the target protocol, perform real-time analysis and processing on the collected data to obtain an analysis result, and output the analysis result in the form of real-time monitoring, alarm, or report; Step 4, monitor tunnel environmental parameters in real time and dynamically adjust the working mode of the system according to the environmental parameters; Step 5, generate control instructions according to the preset control strategy and the real-time data analysis results to optimize the working state of the electromechanical equipment; Step 6, formulate an optimized network communication strategy according to the monitored network status and continuously adjust and optimize the network communication strategy based on the implementation results of the feedback network optimization strategy.

3. A method for edge control of tunnel electromechanical equipment compatible with multiple communication protocols according to claim 2, characterized in that: In Step 1, receive the original data stream from the adaptive protocol recognition unit, analyze the input data stream to extract key features; match the extracted features with the built-in protocol library to identify the specific communication protocol used by the data stream; among them, the original data stream contains information of different protocols; the key features include packet structure, control characters, and specific sequences.

4. A method for edge control of tunnel electromechanical equipment compatible with multiple communication protocols according to claim 2, characterized in that: Step 2 specifically includes the following steps: Step 2-1, protocol conversion and processing: select an appropriate conversion strategy according to the identified protocol type to convert one protocol format to another protocol format; perform the conversion operation to ensure seamless data transmission between different protocols; and execute an error detection and correction mechanism when an error or data corruption occurs during the conversion process to ensure data integrity; the conversion operation includes packet recombination, format conversion, encoding / decoding; Step 2-2, Output Verification and Feedback: Verify whether the converted data conforms to the target protocol specifications to ensure the correctness and usability of the data; output the converted data to the next processing module; record the entire processing process for performance optimization and error prevention of subsequent modules, and the recorded content includes performance metrics such as conversion time and error rate.

5. The edge control method for tunnel electromechanical equipment compatible with multiple communication protocols according to claim 2, characterized in that: Step 3 specifically includes the following steps: Step 3-1, Data Collection and Synchronization: Collect data from the data source in real time and synchronize the collected data in terms of time to ensure data consistency; Step 3-2, Data Processing and Analysis: Clean, filter, and aggregate the data in real time to extract useful information; apply data analysis algorithms to conduct in-depth analysis of the data; Step 3-3, Result Output and Application: Output the analysis results in the form of real-time monitoring, alarms, or reports; at the same time, apply the analysis results to control strategy adjustment or automated decision-making support.

6. The edge control method for tunnel electromechanical equipment compatible with multiple communication protocols according to claim 2, wherein: Step 4 specifically includes the following steps: Step 4-1, Environment Monitoring: Monitor the environmental parameters in the tunnel in real time, collect and record the environmental data for subsequent analysis; Step 4-2, Parameter Analysis: Analyze the change trends of the environmental parameters to identify potential environmental problems; evaluate the impact on system performance based on the changes in the environmental parameters; Step 4-3, Adaptive Adjustment: Adjust the working mode of the system according to the environmental analysis results to ensure that the system maintains optimal performance under changing environmental conditions.

7. A method for edge control of tunnel electromechanical equipment compatible with multiple communication protocols according to claim 6, characterized in that: The environmental parameters in Step 4-1 include temperature, humidity, light, and smoke.

8. A method for edge control of tunnel electromechanical equipment compatible with multiple communication protocols according to claim 6, characterized in that: Adjusting the working mode of the system in Step 4-3 includes changing the ventilation frequency and lighting intensity.

9. The edge control method for tunnel electromechanical equipment compatible with multiple communication protocols according to claim 2, characterized in that: Step 5 specifically includes the following steps: Step 5-1, Data Integration: Integrate the data from the real-time data processing center and the environmental adaptive unit to ensure the accuracy and integrity of the data; Step 5-2, Control Strategy Formulation: Apply control algorithms according to the integrated data to formulate corresponding control strategies for generating control instructions; Step 5-3, Instruction Verification and Execution: Verify whether the generated control instructions are reasonable to avoid potential safety risks; and send the verified instructions to the execution unit for execution.

10. A method for edge control of tunnel electromechanical equipment compatible with multiple communication protocols according to claim 2, characterized in that: Step 6 specifically includes the following steps: Step 6-1, Network Monitoring: Monitor the network status, identify bottlenecks and potential fault points in the network; the network status includes bandwidth usage, latency, and packet loss rate metrics; Step 6-2, Optimization Strategy Formulation: Formulate optimization strategies based on the network monitoring results, and select the best network configuration to improve communication efficiency; the optimization strategies include adjusting routing, QoS settings, and network congestion control; Step 6-3, Strategy Implementation and Feedback: Implement the formulated optimization strategies and monitor the effects, and then continuously adjust and optimize the network communication strategies according to the feedback implementation results.

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