Protection, measurement and control integrated terminal supporting peer-to-peer communication and distributed intelligent collaboration

Abstract

The invention discloses a protection, measurement and control integrated terminal supporting peer-to-peer communication and distributed intelligent cooperation, and belongs to the technical field of industrial control. The system comprises a communication interaction module, a distributed cooperative processing module, a protection measurement and control execution module, a data storage module and a state monitoring module. The protection, measurement and control integrated terminal is constructed, the measurement and control response speed, the cooperative processing efficiency and the operation reliability of the terminal in a complex system are improved, multi-protocol adaptation, optimal link selection and data transmission optimization design are adopted, operation is enhanced through node dynamic management, task intelligent distribution and multiple verification mechanisms, and the system reliability is improved. According to the invention, accurate management and control are realized by combining multi-sensor acquisition and protection strategy self-optimization, the problems of poor terminal protocol compatibility, low resource utilization rate, insufficient measurement and control adaptability and the like are solved, the terminal has the capabilities of flexibly adapting to different scenes, resisting network interference and efficiently processing complex tasks, and omnibearing and multi-level monitoring and early warning of the terminal and associated equipment is realized.

Description

Technical Field

[0001] This invention relates to the field of industrial control technology, and in particular to an integrated protection and control terminal that supports peer-to-peer communication and distributed intelligent collaboration. Background Technology

[0002] In fields such as industrial automation, power system control, and intelligent manufacturing, protection and control terminals serve as core control equipment, undertaking critical tasks such as equipment status monitoring, fault protection, and command execution. However, traditional protection and control terminals have gradually revealed many limitations:

[0003] On the one hand, traditional terminals mostly adopt a single-point centralized processing architecture with limited computing resources. When faced with massive monitoring data and multi-dimensional measurement and control tasks in complex systems, they are prone to processing bottlenecks, resulting in measurement and control response delays and making it difficult to meet real-time control requirements. On the other hand, communication between terminals mostly relies on a single protocol and fixed links, resulting in poor compatibility and weak anti-interference capabilities. This makes it impossible to achieve efficient peer-to-peer communication between multiple terminals and devices, and the distributed collaborative processing capability is insufficient, making it difficult to adapt to the resource scheduling and task allocation requirements of large-scale distributed systems. In addition, the protection strategies of traditional terminals are mostly fixed configurations, lacking adaptive optimization capabilities. They are poorly adaptable to complex operating environments and equipment aging conditions, and data storage mostly adopts local storage mode, resulting in insufficient security and disaster recovery capabilities. Furthermore, they lack a comprehensive status monitoring and early warning mechanism for the terminal itself and related devices, which can easily lead to system shutdowns due to untimely handling of potential faults.

[0004] To address these issues, the industry has been exploring the application of distributed collaboration and multi-protocol communication technologies in protection and control terminals. However, existing technologies still have significant shortcomings: some distributed solutions only implement simple task splitting without considering dynamic resource balancing and scheduling, resulting in low resource utilization; communication protocol adaptation lacks flexibility and is difficult to be compatible with external devices from different manufacturers and of different types; protection logic optimization relies heavily on manual intervention and lacks adaptive adjustment capabilities; and the data storage and status monitoring system is incomplete, requiring improvement in data security and fault prediction capabilities. Summary of the Invention

[0005] The purpose of this invention is to provide an integrated protection and control terminal that supports peer-to-peer communication and distributed intelligent collaboration, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an integrated protection and control terminal that supports peer-to-peer communication and distributed intelligent collaboration, including a communication interaction module, a distributed collaborative processing module, a protection and control execution module, a data storage module, and a status monitoring module;

[0007] The communication interaction module is configured to enable peer-to-peer communication between the main terminal and other terminals, host computers and external devices, and to establish a stable data transmission link.

[0008] The distributed collaborative processing module is configured to perform distributed intelligent collaborative computing based on resource scheduling and task allocation of multiple terminal nodes.

[0009] The protection and control execution module is configured to perform real-time monitoring and protection control of the equipment operating status in power systems and industrial control scenarios.

[0010] The data storage module is configured to classify, store, and quickly retrieve communication data, collaborative computing data, measurement and control data, and equipment status data.

[0011] The status monitoring module is configured to collect the operating status parameters of the main terminal and associated devices in real time, and to perform anomaly warning and fault location.

[0012] Furthermore, the communication interaction module includes a communication protocol adaptation unit, a link establishment and maintenance unit, and a data transmission optimization unit;

[0013] The communication protocol adaptation unit is configured to pre-store communication protocols and automatically complete protocol matching and adaptation based on the protocol type of the communication object.

[0014] The link establishment and maintenance unit is configured to determine the location of communication nodes through device authentication and network topology detection, select the optimal communication path based on node distance, network bandwidth and signal strength, establish a peer-to-peer communication link, and monitor the link transmission quality in real time. When a link is interrupted or the signal is attenuated, the link reconnection mechanism is automatically triggered to switch to a backup communication path.

[0015] The data transmission optimization unit is configured to perform data segmentation processing on the transmitted data and set transmission priorities for key measurement and control data.

[0016] Furthermore, the distributed collaborative processing module includes a node discovery and management unit, a task decomposition and allocation unit, and a collaborative computing unit;

[0017] The node discovery and management unit is configured to discover other terminal nodes in the network through multicast detection and heartbeat packet interaction mechanisms, obtain the hardware resource status, software running status and task load of each terminal node, establish a node resource information database and update it in real time.

[0018] The task decomposition and allocation unit is configured to decompose the overall task into multiple sub-tasks based on the complexity, real-time requirements and data processing volume of the measurement and control task. Combining the node load balancing, computing power and adaptability to the task in the node resource information database, the sub-tasks are allocated to the optimal terminal nodes. At the same time, a task scheduling queue is established to dynamically adjust the execution order of the sub-tasks.

[0019] The collaborative computing unit is configured to realize the interaction of computing data and the synchronization of results between nodes through peer-to-peer communication links, and to automatically migrate the sub-tasks undertaken by abnormal nodes during the computing process to backup nodes.

[0020] Furthermore, the cooperative computing unit is also used for:

[0021] The system monitors the computing resource usage of each node in real time. When a node becomes overloaded, it automatically migrates some of the unfinished subtasks of that node to nodes with available resources.

[0022] Once node resources are released, task allocation is readjusted, and dynamic balancing of computing resources is performed.

[0023] The calculation results of each node are locally verified through multiple verifications, and the calculation results of different nodes for the same subtask are compared through cross-node cross verification.

[0024] If discrepancies exist in the results, initiate the anomaly investigation process and reallocate the subtasks for computation.

[0025] Furthermore, once node resources are released, task allocation is readjusted, and dynamic balancing of computing resources is performed, specifically including:

[0026] After the resource release is confirmed, a resource release node information packet is generated and synchronized to the node resource information database through a peer-to-peer communication link;

[0027] Perform task status statistics for all unfinished subtasks, and record the remaining execution time, data processing volume, and hardware resource requirements of each subtask.

[0028] Based on the idle resources of released nodes in the node resource information database and the resource requirements of each unfinished subtask, an adaptability analysis is performed to calculate the adaptability score between each unfinished subtask and the released node.

[0029] Unfinished subtasks are sorted from highest to lowest according to their adaptation scores. The subtask with the highest adaptation score is assigned to the resource release node first. If the idle resources of the release node can accommodate multiple subtasks at the same time, they are assigned in turn until the resources are saturated.

[0030] Construct a subtask migration channel, perform data snapshot processing on the subtasks that need to be migrated, and record the current execution progress, intermediate calculation results and related configuration parameters of the task;

[0031] After receiving the subtask, the resource release node restores the task execution state based on the snapshot data and starts the subtask operation according to the preset execution priority.

[0032] After the task redistribution is completed, the computing resource dynamic scheduling subunit recalculates the load balance of each node. When the load balance of all nodes is in the range of [0.7, 1.3], the resource scheduling is considered balanced.

[0033] Furthermore, the measurement and control execution module includes a status acquisition unit, a protection logic judgment unit, and a control output unit;

[0034] The status acquisition unit is configured to acquire the operating parameters of the monitored equipment in real time through sensing devices. The operating parameters include voltage amplitude, current frequency, equipment temperature and operating vibration amplitude, and generate standardized status monitoring data.

[0035] The protection logic judgment unit is configured to pre-store protection strategies and threshold ranges, perform logical operations based on status monitoring data and protection strategies, and determine that the equipment has an operational risk when the monitoring data exceeds the preset threshold or shows an abnormal trend, and generate a corresponding protection trigger signal.

[0036] The control output unit is configured to receive a protection trigger signal and output corresponding control commands according to preset control rules. The control commands include equipment shutdown commands, parameter adjustment commands, and alarm prompt commands. The control output unit enables rapid protection control of the monitored equipment through the actuator and simultaneously feeds back the control commands and execution results to the distributed collaborative processing module and the data storage module.

[0037] Furthermore, the protection logic judgment unit is also used for:

[0038] Based on historical measurement and control data, fault handling records, and changes in the equipment operating environment, the preset protection strategy is dynamically optimized and adjusted using machine learning algorithms.

[0039] Analyze the effectiveness and false trigger rate of different protection strategies in practical applications, adjust the protection threshold and logical judgment conditions, automatically generate personalized protection strategies for special operating environments or equipment aging states, and store the optimized personalized protection strategies in the strategy library.

[0040] Furthermore, the data storage module includes a data classification unit and a distributed storage unit;

[0041] The data classification unit is configured to classify communication data, collaborative computing data, measurement and control data and equipment status data by labeling them based on data type, generation time, importance and associated devices, and to assign corresponding storage priorities and retention periods to different types of data.

[0042] The distributed storage unit is configured to allocate the classified data to the local storage nodes and the distributed storage nodes of the associated terminals according to the storage priority through a multi-node redundant storage architecture.

[0043] Furthermore, the distributed storage unit is also used for:

[0044] Dynamic management of stored data is based on data retention period and access frequency;

[0045] For non-critical data that has exceeded its retention period and is accessed infrequently, it is automatically archived or deleted; for data that is accessed frequently, its storage location is optimized.

[0046] When data is lost or damaged on local or distributed storage nodes, backup data is obtained from other normal storage nodes based on the redundant storage architecture. Data is then completed through data interpolation and feature matching, and the cause of data loss and the recovery process are recorded.

[0047] Furthermore, the status monitoring module includes a terminal self-monitoring unit, a device monitoring unit, and an anomaly early warning unit;

[0048] The terminal self-monitoring unit is configured to collect the CPU operating load, memory usage, power supply voltage stability and communication module working status of each terminal in real time to assess the terminal's own operational health.

[0049] The equipment monitoring unit is configured to obtain real-time operating status parameters of the monitored equipment through data interaction with the protection and control execution module, and analyze the operating trend and potential fault risks of the equipment by combining historical operating data and fault case library;

[0050] The anomaly warning unit is configured to set multi-level warning thresholds based on the monitoring results of the terminal self-monitoring unit and the device monitoring unit. When the monitoring parameters exceed the warning thresholds, corresponding warning information is generated according to the severity of the anomaly. The warning information includes the warning level, anomaly type, location of occurrence, and suggested handling measures. The warning information is sent to the relevant management terminal and host computer through the communication interaction module.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] 1. This invention integrates and coordinates five major modules—communication interaction, distributed collaborative processing, protection and control execution, data storage, and status monitoring—to construct an integrated protection and control terminal. Each module has a clear division of labor and efficient linkage. The communication interaction module ensures stable communication in multiple scenarios, the distributed collaborative processing module achieves optimized resource scheduling, the protection and control execution module accurately responds to equipment needs, the data storage module ensures secure and efficient data management, and the status monitoring module proactively avoids operational risks. Overall, this significantly improves the terminal's measurement and control response speed, collaborative processing efficiency, and operational reliability in complex systems.

[0053] 2. The communication interaction module of this invention adopts multi-protocol adaptation, optimal link selection and data transmission optimization design. The distributed collaborative processing module strengthens operation through dynamic node management, intelligent task allocation and multi-verification mechanism. The protection and control execution module combines multi-sensor acquisition and protection strategy self-optimization to achieve precise control. It solves the pain points of poor terminal protocol compatibility, low resource utilization and insufficient measurement and control adaptability, so that the terminal has the ability to flexibly adapt to different scenarios, resist network interference and efficiently handle complex tasks.

[0054] 3. The data storage module of this invention adopts a multi-node redundant storage, data classification management and intelligent life cycle control architecture. The status monitoring module realizes comprehensive and multi-level monitoring and early warning of the terminal itself and related devices, ensuring the secure storage and rapid retrieval of data, optimizing storage space utilization, realizing early prediction and rapid handling of potential faults, filling the shortcoming of traditional terminals that emphasize measurement and control but neglect monitoring. The two work together to provide a prerequisite guarantee and strong support for data interaction between various modules of the terminal, historical data traceability and long-term stable operation of the system. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the integrated protection and control terminal of the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Please see Figure 1 The present invention provides the following technical solutions:

[0058] An integrated protection and control terminal that supports peer-to-peer communication and distributed intelligent collaboration includes a communication interaction module, a distributed collaborative processing module, a protection and control execution module, a data storage module, and a status monitoring module.

[0059] The communication interaction module is configured to enable peer-to-peer communication between the main terminal and other terminals, host computers and external devices, and to establish a stable data transmission link.

[0060] The distributed collaborative processing module is configured to perform distributed intelligent collaborative computing based on resource scheduling and task allocation across multiple terminal nodes.

[0061] The protection and control execution module is configured to perform real-time monitoring and protection control of the operating status of equipment in power systems and industrial control scenarios.

[0062] The data storage module is configured to classify, store, and quickly retrieve communication data, collaborative computing data, measurement and control data, and equipment status data.

[0063] The status monitoring module is configured to collect real-time operating status parameters of the main terminal and associated devices, perform anomaly warnings and fault location, and improve the terminal's measurement and control response speed, collaborative processing efficiency and operational reliability in complex systems.

[0064] In the above embodiments, by integrating communication interaction, distributed collaborative processing, protection and control execution, data storage, and status monitoring, a closed-loop integrated protection and control terminal is constructed. The communication interaction module breaks through the limitations of traditional terminals' single communication protocol and unstable links, achieving multi-protocol adaptive and highly reliable peer-to-peer communication. The distributed collaborative processing module solves the problems of insufficient computing power and low resource utilization of single terminals through dynamic node management and intelligent task allocation. The protection and control execution module provides accurate monitoring and rapid response for power systems and industrial control scenarios, ensuring the safety of equipment operation. The data storage module's classified storage and distributed architecture achieve efficient data management and disaster recovery backup. The status monitoring module's comprehensive monitoring and hierarchical early warning proactively avoid operational risks for the terminal itself and related equipment, improving the terminal's measurement and control response speed, collaborative processing efficiency, and operational reliability in complex systems.

[0065] The communication interaction module includes a communication protocol adaptation unit, a link establishment and maintenance unit, and a data transmission optimization unit;

[0066] The communication protocol adaptation unit is configured to pre-store communication protocols and automatically complete protocol matching and adaptation based on the protocol type of the communication object, supporting dynamic expansion and updating of protocols;

[0067] The link establishment and maintenance unit is configured to determine the location of communication nodes through device authentication and network topology detection, select the optimal communication path based on node distance, network bandwidth and signal strength, establish a peer-to-peer communication link, and monitor the link transmission quality in real time. When a link is interrupted or the signal is attenuated, the link reconnection mechanism is automatically triggered to switch to a backup communication path to ensure communication continuity.

[0068] The data transmission optimization unit is configured to perform data segmentation, reduce transmission bandwidth usage by using data compression algorithms, ensure data transmission accuracy by adding check codes and data retransmission mechanisms, and set transmission priorities for key measurement and control data to achieve differentiated data transmission scheduling.

[0069] In the above embodiments, by supporting multi-protocol storage and dynamic updates, the industry pain point of incompatibility between communication protocols between different devices is solved, improving the versatility and scalability of the terminal. Through optimal path selection and automatic fault switching mechanisms, the continuity of communication links in harsh network environments is ensured, reducing the risk of data transmission interruption. Fragmentation compression, verification retransmission, and priority scheduling strategies reduce bandwidth consumption while ensuring the accuracy and timeliness of key measurement and control data transmission. Layered design and refined processing enable the terminal to flexibly adapt to different communication scenarios, resist network interference, and efficiently transmit data, providing stable and reliable communication support for distributed collaborative computing and precise protection and measurement and control.

[0070] The distributed collaborative processing module includes a node discovery and management unit, a task decomposition and allocation unit, and a collaborative computing unit;

[0071] The node discovery and management unit is configured to discover other terminal nodes in the network through multicast detection and heartbeat packet interaction mechanisms, obtain the hardware resource status, software running status and task load of each terminal node, establish a node resource information database and update it in real time.

[0072] The task decomposition and allocation unit is configured to decompose the overall task into multiple sub-tasks based on the complexity, real-time requirements and data processing volume of the measurement and control task. Combining the node load balancing, computing power and adaptability to the task in the node resource information database, a weighted allocation algorithm is used to allocate the sub-tasks to the optimal terminal nodes. At the same time, a task scheduling queue is established to dynamically adjust the execution order of the sub-tasks.

[0073] The collaborative computing unit is configured to realize the interaction of computing data and the synchronization of results between nodes through peer-to-peer communication links. It adopts a distributed consensus algorithm to ensure the uniformity of computing results of multiple nodes and automatically migrates the sub-tasks undertaken by abnormal nodes in the computing process to backup nodes, thus ensuring the continuity and accuracy of collaborative computing.

[0074] In the above embodiments, multicast detection and heartbeat packet interaction enable real-time monitoring of the resource status of each node in the network, providing accurate data for task allocation. A weighted allocation algorithm based on task characteristics and node adaptability avoids resource overload or idleness, achieving global load balancing. Distributed consensus algorithms and abnormal node task migration mechanisms ensure the uniformity of multi-node operation results and the continuity of the operation process, solving the problems of difficult data synchronization and slow fault recovery in distributed systems. Through intelligent management of the entire process of nodes, tasks, and operations, the resource advantages of multi-terminal clusters are fully utilized, significantly improving the processing efficiency and stability of complex measurement and control tasks, and providing core technical support for the distributed deployment of large-scale industrial control systems.

[0075] The cooperative computing unit is also used for:

[0076] The system monitors the computing resource usage of each node in real time. When a node becomes overloaded, it automatically migrates some of the unfinished subtasks of that node to nodes with available resources.

[0077] Once node resources are released, task allocation is readjusted, and dynamic balancing of computing resources is performed.

[0078] The calculation results of each node are locally verified through multiple verifications, and the calculation results of different nodes for the same subtask are compared through cross-node cross verification.

[0079] If discrepancies exist in the results, initiate the anomaly investigation process, reallocate subtasks for computation, and ensure the accuracy and reliability of the final collaborative computation results.

[0080] This includes, once node resources are released, readjusting task allocation and dynamically balancing computing resources, specifically:

[0081] After resource release is confirmed, a resource release node information packet is generated. The node information packet contains the node identifier, the current amount of idle resources, the type of completed task, and the complexity of the task that the remaining resources can support. It is synchronized to the node resource information database through a peer-to-peer communication link.

[0082] Perform task status statistics for all incomplete subtasks, including subtasks to be executed, subtasks in execution but with insufficient resources, and subtasks that are paused. Record the remaining execution time, data processing volume, and hardware resource requirements of each subtask.

[0083] Based on the idle resources of released nodes in the node resource information database and the resource requirements of each unfinished subtask, an adaptability analysis is performed, and a resource requirement matching algorithm is used to calculate the adaptability score between each unfinished subtask and the released node.

[0084] When calculating the adaptation score, factors such as CPU requirement matching degree, memory requirement matching degree, task type compatibility and data transmission distance are comprehensively considered. Among them, CPU requirement matching degree accounts for 40%, memory requirement matching degree accounts for 30%, task type compatibility accounts for 20%, and data transmission distance accounts for 10%.

[0085] Unfinished subtasks are sorted from highest to lowest according to their adaptation scores. The subtask with the highest adaptation score is assigned to the resource release node first. If the idle resources of the release node can accommodate multiple subtasks at the same time, they are assigned in turn until the resources are saturated.

[0086] Construct a subtask migration channel, perform data snapshot processing on the subtasks that need to be migrated, and record the current execution progress, intermediate calculation results and related configuration parameters of the task;

[0087] After receiving the subtask, the resource release node restores the task execution state based on the snapshot data and starts the subtask operation according to the preset execution priority.

[0088] After the task redistribution is completed, the computing resource dynamic scheduling subunit recalculates the load balance of each node. When the load balance of all nodes is in the range of [0.7, 1.3], the resource scheduling is considered balanced.

[0089] In the above embodiments, by monitoring the resource occupancy status of nodes in real time, overloaded tasks are migrated and resources are released and reallocated, ensuring the load balance of the entire cluster and avoiding the impact of a single node bottleneck on global computing efficiency. The multi-verification mechanism, combining local verification and cross-node cross-verification, effectively identifies and corrects deviations in computing results, solving the problem of data inconsistency caused by node computing errors in distributed systems. The anomaly investigation and task reassignment process ensures the reliability of computing results, reduces the risk of measurement and control errors caused by node failures or computing errors, and enables the collaborative computing unit to have the ability of adaptive resource scheduling, accurate verification of computing results, and rapid self-healing of faults, further improving the robustness of distributed intelligent collaboration.

[0090] The protection and control execution module includes a status acquisition unit, a protection logic judgment unit, and a control output unit;

[0091] The status acquisition unit is configured to collect the operating parameters of the monitored equipment in real time through various sensing devices such as voltage sensors, current sensors, and temperature sensors. The operating parameters include voltage amplitude, current frequency, equipment temperature, and operating vibration amplitude. The acquired parameters are filtered and noise-reduced to remove abnormal data and generate standardized status monitoring data.

[0092] The protection logic judgment unit is configured to pre-store protection strategies and threshold ranges, and performs logical operations based on status monitoring data and protection strategies. When the monitoring data exceeds the preset threshold or shows an abnormal trend, it determines that the equipment has an operational risk and generates a corresponding protection trigger signal.

[0093] Based on historical measurement and control data, fault handling records, and changes in the equipment operating environment, the preset protection strategy is dynamically optimized and adjusted using machine learning algorithms.

[0094] Analyze the effectiveness and false trigger rate of different protection strategies in practical applications, adjust the protection threshold and logical judgment conditions, automatically generate personalized protection strategies for special operating environments or equipment aging states, store the optimized personalized protection strategies in the strategy library, realize the adaptive upgrade of protection logic, and improve the terminal's adaptability to complex operating scenarios.

[0095] The control output unit is configured to receive protection trigger signals and output corresponding control commands according to preset control rules. The control commands include equipment shutdown commands, parameter adjustment commands, and alarm prompt commands. The control output unit achieves rapid protection control of the monitored equipment through the actuator, and at the same time feeds back the control commands and execution results to the distributed collaborative processing module and the data storage module.

[0096] In the above embodiments, the protection and control execution module combines preset strategies with machine learning self-optimization, which not only ensures rapid response in normal scenarios, but also adapts to complex operating conditions such as special operating environments and equipment aging through personalized strategy generation. This reduces the false trigger rate and missed trigger rate of protection strategies. The diversified instructions and rapid execution mechanism enable timely protection and precise control of equipment. At the same time, the execution results are fed back in real time to form a closed-loop management, which meets the real-time requirements of protection and control, improves the terminal's adaptability to complex operating conditions, and effectively ensures the safe and stable operation of power systems and industrial control equipment.

[0097] The data storage module includes a data classification unit and a distributed storage unit;

[0098] The data classification unit is configured to categorize communication data, collaborative computing data, measurement and control data, and equipment status data based on data type, generation time, importance, and associated devices, and to assign corresponding storage priorities and retention periods to different types of data.

[0099] The distributed storage unit is configured to distribute the classified data to the local storage nodes and the distributed storage nodes of the associated terminals according to the storage priority through a multi-node redundant storage architecture, so as to realize the off-site backup and disaster recovery of the data. For critical data, an encrypted storage method is adopted, and the data is encrypted by a symmetric encryption algorithm to ensure the security of data storage.

[0100] Dynamic management of stored data is based on data retention period and access frequency;

[0101] For non-critical data that has exceeded its retention period and is accessed infrequently, it is automatically archived or deleted to free up storage space; for data that is accessed frequently, its storage location is optimized to improve read speed.

[0102] When data is lost or damaged on local or distributed storage nodes, backup data is obtained from other normal storage nodes based on the redundant storage architecture. The integrity of the recovered data is verified by a data consistency check algorithm. If some data is missing, data is filled in by data interpolation and feature matching to ensure the accuracy and integrity of data recovery. At the same time, the cause of data loss and the recovery process are recorded to provide a basis for subsequent storage system optimization.

[0103] In the above embodiments, the data storage module enables differentiated storage management of data of different types and importance through multi-dimensional tag-based classification, thereby improving data retrieval efficiency. The multi-node redundant architecture and symmetric encryption technology enable off-site backup and disaster recovery of data, ensuring the storage security of critical data and solving the problems of easy loss and weak risk resistance of local storage. By differentiating the processing of data with different access frequencies and retention periods, the storage space utilization is optimized and the reading speed of high-frequency data is improved. Integrity verification and missing data completion technology ensure rapid and accurate recovery after data loss or damage.

[0104] The status monitoring module includes a terminal self-monitoring unit, an equipment monitoring unit, and an anomaly early warning unit;

[0105] The terminal self-monitoring unit is configured to collect data in real time on the CPU load, memory usage, power supply voltage stability, and communication module operating status of each terminal to assess the terminal's own operational health.

[0106] The equipment monitoring unit is configured to obtain real-time operating status parameters of the monitored equipment through data interaction with the protection and control execution module, and analyze the operating trend and potential fault risks of the equipment by combining historical operating data and fault case library;

[0107] The anomaly early warning unit is configured to set multi-level early warning thresholds based on the monitoring results of the terminal self-monitoring unit and the equipment monitoring unit. When the monitored parameters exceed the early warning thresholds, corresponding early warning information is generated according to the severity of the anomaly. The early warning information includes the early warning level, anomaly type, location of occurrence, and suggested handling measures. The early warning information is sent to relevant management terminals and host computers through the communication interaction module, and the local audible and visual alarm device is triggered simultaneously. In case of severe anomalies, the automatic linkage protection and control execution module takes emergency protection measures.

[0108] In the above embodiments, the status monitoring module collects core parameters such as CPU load and memory usage in real time to promptly detect potential operational problems in the terminal itself, ensuring the stable operation of the terminal hardware and software. Combined with real-time operating data and historical case database, it deeply analyzes the operating trends of related devices, enabling early prediction of potential faults. Multi-level threshold settings and refined early warning information generation enable maintenance personnel to quickly grasp the severity, location, and handling suggestions of abnormal situations, improving fault handling efficiency. The protection and control linkage mechanism in the case of severe abnormalities achieves seamless connection between early warning and handling, preventing the escalation of faults and realizing full-chain risk management from the terminal itself to related devices.

[0109] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A protection and control integrated terminal supporting peer-to-peer communication and distributed intelligent collaboration, characterized in that: It includes a communication interaction module, a distributed collaborative processing module, a protection and control execution module, a data storage module, and a status monitoring module; The communication interaction module is configured to enable peer-to-peer communication between the main terminal and other terminals, host computers and external devices, and to establish a stable data transmission link. The distributed collaborative processing module is configured to perform distributed intelligent collaborative computing based on resource scheduling and task allocation of multiple terminal nodes. The protection and control execution module is configured to perform real-time monitoring and protection control of the equipment operating status in power systems and industrial control scenarios. The data storage module is configured to classify, store, and quickly retrieve communication data, collaborative computing data, measurement and control data, and equipment status data. The status monitoring module is configured to collect the operating status parameters of the main terminal and associated devices in real time, and to perform anomaly warning and fault location.

2. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 1, characterized in that, The communication interaction module includes a communication protocol adaptation unit, a link establishment and maintenance unit, and a data transmission optimization unit. The communication protocol adaptation unit is configured to pre-store communication protocols and automatically complete protocol matching and adaptation based on the protocol type of the communication object. The link establishment and maintenance unit is configured to determine the location of communication nodes through device authentication and network topology detection, select the optimal communication path based on node distance, network bandwidth and signal strength, establish a peer-to-peer communication link, and monitor the link transmission quality in real time. When a link is interrupted or the signal is attenuated, the link reconnection mechanism is automatically triggered to switch to a backup communication path. The data transmission optimization unit is configured to perform data segmentation processing on the transmitted data and set transmission priorities for key measurement and control data.

3. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 1, characterized in that, The distributed collaborative processing module includes a node discovery and management unit, a task decomposition and allocation unit, and a collaborative computing unit. The node discovery and management unit is configured to discover other terminal nodes in the network through multicast detection and heartbeat packet interaction mechanisms, obtain the hardware resource status, software running status and task load of each terminal node, establish a node resource information database and update it in real time. The task decomposition and allocation unit is configured to decompose the overall task into multiple sub-tasks based on the complexity, real-time requirements and data processing volume of the measurement and control task. Combining the node load balancing, computing power and adaptability to the task in the node resource information database, the sub-tasks are allocated to the optimal terminal nodes. At the same time, a task scheduling queue is established to dynamically adjust the execution order of the sub-tasks. The collaborative computing unit is configured to realize the interaction of computing data and the synchronization of results between nodes through peer-to-peer communication links, and to automatically migrate the sub-tasks undertaken by abnormal nodes during the computing process to backup nodes.

4. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 3, characterized in that, The collaborative computing unit is also used for: The system monitors the computing resource usage of each node in real time. When a node becomes overloaded, it automatically migrates some of the unfinished subtasks of that node to nodes with available resources. Once node resources are released, task allocation is readjusted, and dynamic balancing of computing resources is performed. The calculation results of each node are locally verified through multiple verifications, and the calculation results of different nodes for the same subtask are compared through cross-node cross verification. If discrepancies exist in the results, initiate the anomaly investigation process and reallocate the subtasks for computation.

5. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 4, characterized in that, Once node resources are released, task allocation is readjusted, and dynamic balancing of computing resources is performed, specifically including: After the resource release is confirmed, a resource release node information packet is generated and synchronized to the node resource information database through a peer-to-peer communication link; Perform task status statistics for all unfinished subtasks, and record the remaining execution time, data processing volume, and hardware resource requirements of each subtask. Based on the idle resources of released nodes in the node resource information database and the resource requirements of each unfinished subtask, an adaptability analysis is performed to calculate the adaptability score between each unfinished subtask and the released node. Unfinished subtasks are sorted from highest to lowest according to their adaptation scores. The subtask with the highest adaptation score is assigned to the resource release node first. If the idle resources of the release node can accommodate multiple subtasks at the same time, they are assigned in turn until the resources are saturated. Construct a subtask migration channel, perform data snapshot processing on the subtasks that need to be migrated, and record the current execution progress, intermediate calculation results and related configuration parameters of the task; After receiving the subtask, the resource release node restores the task execution state based on the snapshot data and starts the subtask operation according to the preset execution priority. After the task redistribution is completed, the computing resource dynamic scheduling subunit recalculates the load balance of each node. When the load balance of all nodes is in the range of [0.7, 1.3], the resource scheduling is considered balanced.

6. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 1, characterized in that, The measurement and control execution module includes a status acquisition unit, a protection logic judgment unit, and a control output unit; The status acquisition unit is configured to acquire the operating parameters of the monitored equipment in real time through sensing devices. The operating parameters include voltage amplitude, current frequency, equipment temperature and operating vibration amplitude, and generate standardized status monitoring data. The protection logic judgment unit is configured to pre-store protection strategies and threshold ranges, perform logical operations based on status monitoring data and protection strategies, and determine that the equipment has an operational risk when the monitoring data exceeds the preset threshold or shows an abnormal trend, and generate a corresponding protection trigger signal. The control output unit is configured to receive a protection trigger signal and output corresponding control commands according to preset control rules. The control commands include equipment shutdown commands, parameter adjustment commands, and alarm prompt commands. The control output unit enables rapid protection control of the monitored equipment through the actuator and simultaneously feeds back the control commands and execution results to the distributed collaborative processing module and the data storage module.

7. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 6, characterized in that, The protection logic judgment unit is also used for: Based on historical measurement and control data, fault handling records, and changes in the equipment operating environment, the preset protection strategy is dynamically optimized and adjusted using machine learning algorithms. Analyze the effectiveness and false trigger rate of different protection strategies in practical applications, adjust the protection threshold and logical judgment conditions, automatically generate personalized protection strategies for special operating environments or equipment aging states, and store the optimized personalized protection strategies in the strategy library.

8. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 1, characterized in that, The data storage module includes a data classification unit and a distributed storage unit; The data classification unit is configured to classify communication data, collaborative computing data, measurement and control data and equipment status data by labeling based on data type, generation time, importance and associated devices, and to assign corresponding storage priorities and retention periods to different types of data. The distributed storage unit is configured to allocate the classified data to the local storage nodes and the distributed storage nodes of the associated terminals according to the storage priority through a multi-node redundant storage architecture.

9. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 8, characterized in that, The distributed storage unit is also used for: Dynamic management of stored data is based on data retention period and access frequency; For non-critical data that has exceeded its retention period and is accessed infrequently, it is automatically archived or deleted; for data that is accessed frequently, its storage location is optimized. When data is lost or damaged on local or distributed storage nodes, backup data is obtained from other normal storage nodes based on the redundant storage architecture. Data is then completed through data interpolation and feature matching, and the cause of data loss and the recovery process are recorded.

10. The integrated protection and control terminal supporting peer-to-peer communication and distributed intelligent collaboration as described in claim 1, characterized in that, The status monitoring module includes a terminal self-monitoring unit, a device monitoring unit, and an anomaly early warning unit; The terminal self-monitoring unit is configured to collect data in real time on the CPU operating load, memory usage, power supply voltage stability, and communication module operating status of each terminal to assess the terminal's own operational health. The equipment monitoring unit is configured to obtain real-time operating status parameters of the monitored equipment through data interaction with the protection and control execution module, and analyze the operating trend and potential fault risks of the equipment by combining historical operating data and fault case library. The anomaly warning unit is configured to set multi-level warning thresholds based on the monitoring results of the terminal self-monitoring unit and the device monitoring unit. When the monitoring parameters exceed the warning thresholds, corresponding warning information is generated according to the severity of the anomaly. The warning information includes the warning level, anomaly type, location of occurrence, and suggested handling measures. The warning information is sent to the relevant management terminal and host computer through the communication interaction module.

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