Self-adaptive coordinated regulation gate control method and system and storage medium

Abstract

The invention relates to the technical field of water conservancy project automation control, and discloses a self-adaptive coordinated regulation gate control method and system and a storage medium. The method comprises the following steps: acquiring gate node real-time instruction data and performing time synchronization calibration to generate an initial instruction sequence; instruction features are extracted and classified based on the sequence, and an instruction sorting list is obtained; when the emergency instruction proportion exceeds a threshold value, the emergency instruction is separated, an exclusive channel is distributed, an accelerated propagation path is generated, and an optimized transmission path is determined through path delay evaluation; selecting a path with the lowest delay from the optimized paths to perform emergency instruction distribution, and acquiring a feedback signal; verifying the feedback signal and recording a response speed index, and determining the adjusted transmission configuration based on the index; the configuration is utilized to synchronize and integrate the conventional instructions to the main propagation sequence to generate a complete regulation and control instruction set. According to the method, the multi-node instruction time sequence consistency and the emergency response capability are improved, the transmission conflict is reduced, and the cooperative regulation and control efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of automated control technology for water conservancy projects, and in particular to an adaptive and coordinated gate control method, system, and storage medium. Background Technology

[0002] As a crucial execution unit in water conservancy projects, sluice gates undertake scheduling tasks such as flood control and drainage, irrigation water supply, ecological water replenishment, and navigation. With the advancement of integrated basin scheduling and digital twin water conservancy construction, sluice gate control systems have gradually evolved from single-station local control to a collaborative control mode of "multiple sluice gate nodes - communication network - central scheduling platform": early systems mostly used manual inspection and local electrical control to achieve single gate opening adjustment; subsequently, PLC / RTU and SCADA were introduced to achieve remote centralized monitoring and timed / rule-based control; further, sensor networks, industrial Ethernet / wireless private networks, and edge computing were combined to achieve multi-node information aggregation and linkage control; in recent years, model prediction, intelligent optimization, and emergency plans have been combined to achieve rapid collaborative scheduling for scenarios such as floods and sudden water inflows.

[0003] The existing multi-gate coordinated control technology still has the following prominent problems in engineering applications: (1) The asynchronous clocks of multiple nodes lead to inconsistent instruction time bases. The controllers, sensors and communication equipment of the gate nodes are widely distributed and the operating environment is complex, which can easily cause clock drift or network delay fluctuations. As a result, instruction data in the same scheduling cycle will have different timestamps on different nodes, causing uncertainty in instruction order, difficulty in state alignment, and even malfunctions or linkage failures.

[0004] (2) In emergency situations, the transmission delay of instructions is difficult to guarantee. In cases such as rapid rise of flood peak and sudden change of water level in front of the gate, emergency instructions need to be issued and confirmed for execution quickly among multiple nodes. However, the existing system usually shares communication resources with regular instructions, which is susceptible to network congestion and link jitter, resulting in increased delay in the arrival of key instructions and affecting the effectiveness of emergency response.

[0005] (3) Conflicts may easily occur when emergency instructions and regular instructions are mixed. In actual operation, regular scheduling instructions are continuously generated. When emergency instructions exist at the same time, if there is no effective priority layering, diversion and transmission resource coordination mechanism, problems such as queue blocking, preemption failure, repeated issuance or missing confirmation feedback may occur, which will reduce the overall control efficiency and reliability.

[0006] (4) Lack of a closed-loop adaptive optimization mechanism oriented to the operating state. Some solutions only implement fixed priority or static routing policies, which makes it difficult to dynamically adjust the transmission configuration and distribution rhythm according to operating indicators such as real-time feedback, alarm information, and response speed. As a result, it is difficult to maintain stable performance when the load changes or the network condition deteriorates.

[0007] Therefore, the technical problem that this invention aims to solve is: in the scenario of multi-gate node collaborative control, how to effectively layer and divert emergency commands and regular commands while ensuring the consistency of command time base, achieve low-latency reliable transmission and dynamic path optimization for emergency commands, and form a closed-loop adaptive adjustment mechanism by combining feedback verification and response speed indicators, so as to ultimately achieve efficient coordination of emergency and regular scheduling commands, reduce transmission conflicts, and generate a complete and reliable set of control commands. Summary of the Invention

[0008] To overcome the problems of inconsistent time bases, slow emergency command response, conflict between emergency and regular commands, and lack of closed-loop adaptive optimization in existing multi-gate collaborative control, this application provides an adaptive collaborative control gate control method, system, and storage medium to achieve consistent command timing, low-latency transmission of emergency commands, and complete and reliable generation of control command sets in multi-node distributed scenarios.

[0009] In a first aspect, this application provides an adaptive and coordinated gate control method, the method comprising: S1. Obtain real-time command data from each gate node, use a time synchronization mechanism to handle time deviations, and generate an initial command sequence under a unified time reference. S2. Extract instruction features based on the initial instruction sequence and classify them to obtain a sorted list of classified instructions; S3. Determine whether the proportion of emergency instructions in the instruction sorting list exceeds the preset proportion threshold. If so, separate the emergency instruction subset from the instruction sorting list, allocate a dedicated transmission channel to the emergency instruction subset, and generate an emergency instruction path to accelerate propagation. S4. Emergency command path based on accelerated propagation: calculate the transmission delay between multiple nodes using path delay assessment technology, and determine the optimized emergency command transmission path based on the transmission delay. S5. Extract the path with the lowest latency from the optimized emergency command transmission path, distribute the emergency command, and obtain feedback signal data. S6. Verify the feedback signal data and record the response speed index, and determine the adjusted transmission configuration based on the response speed index. S7. Based on the adjusted transmission configuration, perform time synchronization processing on the remaining regular instructions, and integrate the synchronized regular instructions into the main propagation sequence to obtain a complete set of control instructions.

[0010] Secondly, this application provides an adaptive and coordinated gate control system, the system comprising: The instruction generation module is used to acquire real-time instruction data from each gate node, use a time synchronization mechanism to handle time deviations, and generate an initial instruction sequence under a unified time base. The feature classification module is used to extract instruction features from the initial instruction sequence and classify them to obtain a sorted list of classified instructions. The path generation module is used to determine whether the proportion of emergency instructions in the instruction sorting list exceeds a preset proportion threshold. If so, it separates the emergency instruction subset from the instruction sorting list, allocates a dedicated transmission channel to the emergency instruction subset, and generates an emergency instruction path to accelerate propagation. The delay assessment module is used to calculate the transmission delay between multiple nodes based on the path delay assessment technology for the accelerated propagation of emergency instructions, and to determine the optimized emergency instruction transmission path based on the transmission delay. The instruction distribution module is used to extract the path with the lowest latency from the optimized emergency instruction transmission path, distribute emergency instructions, and obtain feedback signal data. The feedback verification module is used to verify the feedback signal data and record the response speed index, and determine the adjusted transmission configuration based on the response speed index. The integration and synchronization module is used to perform time synchronization processing on the remaining regular instructions according to the adjusted transmission configuration, and integrate the synchronized regular instructions into the main propagation sequence to obtain a complete set of control instructions.

[0011] Thirdly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the aforementioned adaptive and coordinated gate control method.

[0012] Compared with the prior art, the beneficial effects of the technical solution of this application are at least as follows: 1. By calibrating the time synchronization of instruction data at each gate node, an initial instruction sequence under a unified time base is formed, which effectively overcomes the problem of instruction timing disorder caused by node clock drift and network asynchrony, improves the consistency and execution reliability of instructions for multi-node collaborative control, and fundamentally ensures the accurate execution of complex control logic.

[0013] 2. By intelligently identifying and separating emergency commands, and dynamically allocating dedicated transmission channels and optimizing low-latency paths for them, it ensures that critical control commands can penetrate the network quickly and efficiently, avoiding congestion with regular traffic, and guaranteeing the low-latency propagation capability of emergency commands under complex network conditions, thereby improving the response speed and handling efficiency in the event of a sudden flood.

[0014] 3. Based on feedback signal verification and response speed indicators, a closed-loop adaptive adjustment mechanism is formed, which can dynamically determine the transmission configuration according to the operating status, and perform synchronous processing and sequence integration of regular instructions under this configuration. This reduces the risk of congestion and conflict caused by the mixing of emergency and regular instructions, and ensures that the final control instruction set is complete, verifiable and applicable to the collaborative scheduling needs of multiple scenarios.

[0015] 4. By organically integrating command synchronization, intelligent classification, resource scheduling, path optimization, and feedback tuning, a closed-loop management system is achieved, encompassing the entire process from data perception to decision execution and system self-optimization. This transforms the gate control system from a static execution tool into an intelligent collaborative entity capable of adapting to complex and ever-changing environments and continuously improving performance, thereby comprehensively enhancing the level of intelligent water resource scheduling. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 The flowchart is of the adaptive coordinated control gate control method of this application; Figure 2 This is a schematic diagram comparing the cumulative success rate of the method and the traditional method as a function of the number of processed instructions in the embodiments of this application. Figure 3 This is a schematic diagram comparing the response time distribution of the method in this application with that of the traditional method in the embodiments of this application; Figure 4 This is a schematic diagram comparing the success rate of emergency command processing between the method described in this application and the traditional method in the embodiments of this application; Figure 5 This is a schematic diagram of the adaptive coordinated control gate control system of this application. Detailed Implementation

[0018] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms “comprising” or “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] For ease of understanding, the specific process of the embodiments of this application is described below. Figure 1 The diagram shows a flowchart of the adaptive coordinated control gate control method provided by the present invention. The flowchart specifically includes the following steps: S1. Obtain real-time command data from each gate node, use a time synchronization mechanism to handle time deviations, and generate an initial command sequence under a unified time reference.

[0020] In one specific embodiment, the process of performing step S1 may specifically include the following steps: Real-time command data is collected from each gate node, and a timestamp is added to each command data. A timestamp synchronization mechanism is used to align the clocks of each node to calibrate the time deviation and generate a preliminary command sequence after preliminary clock alignment. For inter-node communication, multi-node transmission optimization technology is used to adjust the data transmission rhythm of the initial instruction sequence. Based on the adjusted transmission rhythm, the initial instruction sequence is synchronously transmitted to the central processing unit to form an optimized communication flow. By combining gate status synchronization data, the instructions in the optimized communication stream are precisely calibrated to generate an initial instruction sequence under a unified time base; The initial instruction sequence is validated for consistency, and the validation results are obtained. If the verification results show that the time deviation exceeds the preset deviation threshold, the timestamp synchronization mechanism is iteratively adjusted and subsequent steps are re-executed until an initial instruction sequence that meets the time consistency requirements is generated.

[0021] Specifically, in the scenario of sluice gate group control, the dispatch center needs to issue control commands such as opening adjustment and water level control to multiple gate nodes based on the basin water level, water inflow process, and gate operating conditions. However, since the nodes are distributed at different sites and transmit data through the network, clock drift and link latency can cause inconsistencies in command timestamps and differences in command order across different nodes within the same dispatch cycle. This leads to confusion in the sequence of coordinated actions and difficulty in aligning confirmation feedback. To ensure a unified temporal basis for subsequent command classification, emergency command diversion, and path optimization, it is necessary to establish data correspondence and form an iterative time-consistent closed loop.

[0022] During the command acquisition phase, command data generated by the controller is written to the acquisition buffer at each gate node. The command data includes at least the gate identifier, target opening degree or control mode, and generation time, and is appended with a timestamp field from the node's local clock. Each node's local clock is periodically synchronized with the central time source using the Network Time Protocol (NTP) to keep clock deviations between nodes within a preset threshold. After this clock alignment process, each node forms a preliminary command sequence, where each record maintains the correspondence between the command field and the timestamp field.

[0023] After the initial instruction sequence enters the multi-node transmission optimization module, data packets are sorted by priority queue and the transmission rhythm is adjusted according to network load. The transmission frequency of non-critical data is suppressed during congestion periods, while instruction data carrying control action fields is guaranteed transmission time slots. Simultaneously, bandwidth allocation is dynamically updated based on link occupancy, ensuring that instruction data receives available bandwidth under multi-link conditions. The output of this module does not change the instruction content, but rather alters the "time distribution of instruction records arriving at the central processing unit," making the arrival intervals of instructions in the central receiving queue smoother and reducing burst delays caused by congestion. This provides a continuous observation window for subsequent time calibration based on state data. Through the adjusted transmission rhythm, the initial instruction sequence is synchronously transmitted to the central processing unit and converged into a "communication stream." The communication stream retains the original timestamp and arrival time of each instruction record, forming a mapping relationship between "initial instruction sequence record - communication stream record."

[0024] The time calibration phase introduces gate status synchronization data to match the "instruction records in the communication stream" with the "status records." The status synchronization data is obtained through periodic broadcasting by nodes and includes at least fields such as gate opening, water level before and after the gate, flow velocity, or water pressure, along with a status timestamp. The central processing unit extracts the timestamp value of each instruction record, denoted as time α, and extracts the timestamp value of the status record of the corresponding node, denoted as time β. It calculates the deviation γ = β - α and corrects the instruction timestamp using a unified time reference time ρ as the target. A linear interpolation approach can be used to proportionally allocate the correction amount to the time positioning of the instruction record. For example, the corrected instruction time can be set to ρ = α - γ / 2, aligning the instruction record with the state evolution process under a unified reference. If there are two sampling points in the state record near α, the state value at the intermediate time is estimated using the linear change assumption between the two sampling points, and the allocation ratio of γ is adjusted accordingly to ensure that the instruction time correction matches the state change rate. After this processing, the instruction records in the communication stream are converted into an "initial instruction sequence", and each record in the initial instruction sequence can be aligned with the corresponding state record on a unified timeline.

[0025] The consistency verification phase verifies the initial instruction sequence to form an iterative closed loop. The central processing unit cross-compares the timestamps of each node in the sequence within the same scheduling window, calculates time deviation statistics (such as overall deviation variance), and compares them with a preset deviation threshold. Simultaneously, it checks for time jumps or reverse order phenomena in the sequence. If verification passes, the initial instruction sequence is written to the storage medium to form a basic dataset. This dataset serves as input for subsequent feature extraction and emergency instruction proportion determination, maintaining a consistent index of "basic dataset record ↔ initial instruction sequence record". If verification fails, it triggers synchronization mechanism parameter iteration, adjusting the synchronization period, offset compensation, or network latency estimation parameters, and re-executing communication scheduling and state matching calibration. This allows new communication flows and state data to regenerate a new initial instruction sequence, which is then verified again. This iterative process links "synchronization parameter changes → initial instruction sequence changes → consistency index changes," ensuring that the time base quality is controlled within the threshold and preventing mismatches or misjudgments in the emergency instruction confirmation link due to accumulated time deviations.

[0026] S2. Extract instruction features based on the initial instruction sequence and classify them to obtain a sorted list of classified instructions.

[0027] In one specific embodiment, the process of performing step S2 may specifically include the following steps: Traverse the initial instruction sequence, extract the instruction feature value of each instruction, and divide the instructions into high-priority layer and low-priority layer according to the instruction feature value based on the preset instruction priority layering method, and obtain the layered instruction set. Acquire water flow parameter data, apply emergency command separation technology to match and analyze the commands in the stratified command set with the water flow parameter data, identify emergency commands and regular commands, and obtain the distribution ratio of emergency commands; Based on the distribution ratio and preset arrangement rules, an initial sorted list of classified instructions is generated; Priority verification is performed on the initial instruction sorting list to confirm that emergency instructions have a higher sorting priority than regular instructions. If the verification fails, the parameters of the instruction priority hierarchical method and / or emergency instruction separation technology are iteratively adjusted, and the hierarchical classification and sorting are re-executed until an initial instruction sorting list that passes priority verification is generated. The initial instruction sorting list that has passed priority verification is subjected to stability evaluation, and an instruction sorting list is generated based on the evaluation results.

[0028] Specifically, within the same time window, the dispatch center may have both routine control commands such as planned opening adjustments and ecological water replenishment, and emergency control commands such as flood peaks and sudden rises in water levels in front of the sluice gates. However, communication resources and execution windows are limited, which can lead to emergency commands and routine commands being mixed and crowding each other in the queue, causing delays in key actions and inconsistent feedback confirmations. Therefore, an instruction sorting list can be generated to transform the mixing problem into a controllable priority structure and quantifiable emergency proportion data.

[0029] The initial instruction sequence is constrained by a unified time base. Each instruction record in the sequence includes a gate identifier, instruction type, target opening degree or control quantity, generation timestamp, and time positioning information aligned with the node status. During traversal processing, each instruction is mapped to a feature vector. The feature vector consists of at least a timestamp field, a gate identifier field, and an operation type field, and can be supplemented with fields such as target opening degree change, scheduling mode flag, and instruction source flag to reflect the control intent and scope of influence. After the feature vector enters the instruction priority layering module, layering labels are generated according to preset rules. The rules can map action types such as "flood discharge increase" and "emergency gate closure" to high-priority layers, and "routine water regulation" and "timed inspection and adjustment" to low-priority layers. At the same time, the layering boundaries can be refined using the target opening degree change and the controlled water level range, so that instructions that are also opening degree adjustments are promoted to high-priority layers when the change is large or the upper limit of the water level is triggered. The layering result is output in the form of a set, forming a "layered instruction set".

[0030] Emergency command separation relies on matching analysis of flow parameter data and command sets. Flow parameter data originates from upstream and downstream water level gauges, velocity meters, rain gauges, or water pressure sensors. Data records include measuring point identifiers, sampling timestamps, and fields such as water level, flow velocity, and fluctuation amplitude, and are aligned with a unified time reference. Matching analysis associates the layered command sets with flow parameter records according to gate identifiers and timestamp windows. Association methods can use nearest neighbor or interpolation alignment within time windows, ensuring that each command obtains corresponding water level change rate and flow velocity fluctuation information near its timestamp. Emergency separation technology uses threshold judgment or pattern recognition for marking. For example, when the water level rise rate exceeds a threshold, the flow velocity fluctuation amplitude exceeds a threshold, or the upstream water level approaches a warning value, the associated command is marked as an emergency command; otherwise, it is marked as a regular command. When a command is already in a high-priority layer and simultaneously meets the abnormal water level or flow velocity conditions, the emergency marking takes precedence, thus avoiding missed judgments due to relying solely on action type judgment. The ratio of the number of emergency markers to the total number of instructions is statistically analyzed at the set level to form the emergency distribution ratio. This ratio serves as the basis for subsequent diversion, enabling a calculable mapping between the level of urgency and the on-site water conditions.

[0031] The sorting generation phase combines the emergency distribution ratio with the sorting rules. These rules can be defined as placing emergency instructions at the beginning of the list and regular instructions at the end. Within each segment, instructions are sorted in ascending order based on timestamps, grouped by gate identifiers, or further sorted by hierarchical labels. The emergency distribution ratio can also be used as a weighting factor to influence batch size and the length of the initial segment, ensuring that when the emergency proportion increases, the initial segment covers more instructions and shortens the distribution interval. The generated initial instruction sorting list retains the emergency marker and hierarchical label for each instruction.

[0032] Priority verification is used to check whether the sorting list meets the constraint that "emergency instructions have higher priority than regular instructions". Verification methods include scanning the list to locate the first regular instruction and confirming that there are no emergency-marked instructions after it, or calculating the proportion of emergency markers in the list that precede regular markers and comparing it with the target threshold. When the verification fails, it indicates that the stratification threshold or emergency separation threshold is set unreasonably. This may result in abnormal water conditions not triggering emergency markers or the action type stratification being too wide, causing emergency segments to be mixed with regular instructions. In this case, parameter iteration is initiated. Parameter iteration can adjust the water level change rate threshold, fluctuation amplitude threshold, time window width, or stratification boundary to make the emergency markers more consistent with the water conditions after rematching and to push the sorting to meet the constraints. This closed loop uses constraint checks to ensure that the priority rule is implemented under verifiable conditions.

[0033] Stability assessment is used to suppress the sensitivity of sorting results to noisy data. During assessment, the sorting list can be repeatedly generated within adjacent time windows, and the relative position changes of the same command in the list can be compared. Alternatively, small disturbances can be added to the sampling of water flow parameters, and the drastic flipping of the emergency marker and sorting can be observed. The order change rate is calculated and compared with a threshold. When the change rate is too high, it indicates that the threshold setting is too sensitive or the time window is too narrow, requiring a rollback adjustment of the separation or stratification parameters to improve consistency. After stability is passed, the command sorting list is output along with the emergency distribution ratio as input for subsequent steps. This ensures that subsequent emergency command proportion threshold judgments and emergency subset separation are based on stable sorting, thereby reducing the risk of frequent channel switching or false triggering of diversion due to short-term fluctuations.

[0034] S3. Determine whether the proportion of emergency instructions in the instruction sorting list exceeds the preset proportion threshold. If so, separate the emergency instruction subset from the instruction sorting list, allocate a dedicated transmission channel to the emergency instruction subset, and generate an emergency instruction path to accelerate propagation.

[0035] In one specific embodiment, the process of performing step S3 may specifically include the following steps: Count the number of emergency instructions in the sorted instruction list and calculate the percentage of emergency instructions. If the proportion of emergency instructions exceeds a preset threshold, all emergency instructions will be extracted from the instruction sorting list through a dedicated channel allocation technology to form a subset of emergency instructions. Monitor current network bandwidth usage, combine dynamic bandwidth adjustment technology to allocate dedicated transmission channels to a subset of emergency commands, and confirm the channel parameters after allocation; Based on the allocation results of dedicated transmission channels, combined with the current network topology and node status, an emergency command path for accelerated propagation is generated. The transmission efficiency of the emergency command path is pre-evaluated, and the evaluation results are compared with the preset rapid propagation requirements. If the requirements are not met, the dynamic bandwidth adjustment strategy is iteratively adjusted, channels are reallocated and paths are generated, until an emergency command path that meets the preset rapid propagation requirements is obtained.

[0036] Specifically, the dispatch center needs to process instruction queues from different gate stations within the same communication cycle. Sudden rises in water level, abnormal water pressure in front of the gate, or increased flow velocity fluctuations can cause a concentrated surge in emergency instructions within a short period. If emergency instructions and regular instructions share a channel and are transmitted in a single queue, network congestion will increase the arrival delay of critical instructions and cause execution confirmation delays. To address the congestion and delay problems caused by the mixing of emergency and regular instructions, this embodiment achieves the separation and accelerated transmission of emergency instructions through the following steps.

[0037] The instruction sorting list contains multiple instruction records, each carrying an emergency marker, hierarchical label, gate identifier, timestamp, and sorting position. The emergency marker is derived from flow parameter matching analysis, thus providing interpretable hydrological information within the same time window. Emergency instruction counts are based on the emergency marker; the list is traversed to obtain an emergency count, which is then matched with the total number of instructions to obtain an emergency percentage. This percentage is compared with a preset percentage threshold to determine whether to enter the separation process. The percentage threshold can be set to 0.2 or 0.3, depending on the scheduling strategy, to distinguish between "sporadic emergencies" and "concentrated emergencies," thereby avoiding frequent switching of network resource allocation strategies when there are very few emergency instructions, which could cause fluctuations in regular scheduling. The percentage data serves as an input parameter for channel allocation, establishing a quantitative mapping between resource scheduling and the urgency of the hydrological situation, forming a quantifiable gating system to address the problem of "lack of triggering conditions leading to untimely or excessive resource allocation."

[0038] When the proportion exceeds a threshold, the dedicated channel allocation technology extracts emergency-marked instructions from the instruction sorting list and forms an emergency instruction subset. This subset maintains the index mapping relationship with the original list, containing both the instruction content and the relative order information of the instructions in the original sorting, facilitating the maintenance of order within the emergency segment during subsequent distribution. The extraction process can employ filtering operators to include instructions marked as emergency and in the high-priority layer into the subset, while keeping instructions marked as emergency but in the low-priority layer as optional, with their inclusion determined based on the degree of abnormality in the water flow parameters, thus avoiding frequent changes in the subset boundary due to single threshold fluctuations. The size of the emergency instruction subset, as the object of channel resource allocation, and the distribution and time density of the instruction target nodes determine the bandwidth and time slot allocation required by the dedicated channel.

[0039] The channel allocation phase introduces network bandwidth monitoring data and dynamic bandwidth adjustment technology. Network bandwidth monitoring data is obtained through switch port statistics or link probing, including indicators such as available link bandwidth, current occupancy rate, packet loss rate, and queuing latency, and corresponds to the connection relationships between node pairs. Dynamic bandwidth adjustment technology calculates the bandwidth share required for the dedicated channel based on the size of the emergency instruction subset and the target node set, and allocates resources from the shared channel. Allocation methods may include setting a higher scheduling weight for the emergency queue or reserving time slots for emergency data packets, while reducing the transmission frequency of the regular queue to release bandwidth. Channel parameters are explicitly defined in this phase, including bandwidth limits, queue weights, maximum queuing latency, and retransmission windows, and are bound to the emergency instruction subset to form a "subset-channel parameter" correspondence. After the channel parameters are confirmed, they are written into the communication control module, ensuring that subsequent emergency instruction data packets carry the channel identifier when transmitted and are processed by network devices according to a dedicated queue, mitigating the impact of congestion propagation on critical instructions from the transmission layer.

[0040] The emergency command path generation phase combines the allocation results of dedicated channels with network topology data and node status data. Network topology data describes the connectivity of links between nodes and the set of candidate routes, while node status data describes the online status, processing load, and recent response latency of gate nodes. The path generation process maps the target node set onto the topology graph and selects the combination of paths with lower latency and lighter load from the candidate paths that satisfy dedicated channel reachability as the emergency command path. Paths are represented as node sequences or link sequences, and a correspondence is established with the target node of each command in the emergency command subset, allowing different commands in the same subset to share the path front and branch at the fork point. This process couples "channel parameter constraints" with "topology reachability," avoiding the situation where dedicated channels are unavailable on some links due to relying solely on the shortest path selection and avoiding forwarding failures caused by selecting offline nodes.

[0041] Transmission efficiency assessment focuses on emergency command paths, collecting real-time traffic monitoring data and feedback signals along these paths. The assessment inputs consist of channel parameters, historical link latency statistics, current occupancy rate, and node processing latency. The assessment outputs path transmission latency, congestion risk indicators, or arrival rate predictions, which are compared with preset rapid propagation requirements. These preset rapid propagation requirements can be represented by the maximum allowable latency or minimum arrival rate. If the requirements are not met, the dynamic bandwidth adjustment strategy is iteratively updated. Update methods may include increasing the emergency queue weight, expanding bandwidth share, adjusting the retransmission window, or selecting a backup link segment. Simultaneously, the path is regenerated and reassessed. Let the path latency estimate be δ, and the rapid propagation requirement threshold be ε. When δ > ε, strategy iteration is triggered, and δ is recalculated until a path with δ ≤ ε is determined as the emergency command path that meets the requirements.

[0042] S4. Based on the accelerated propagation of emergency instructions, the transmission delay between multiple nodes is calculated using path delay assessment technology, and an optimized emergency instruction transmission path is determined based on the transmission delay.

[0043] In one specific embodiment, the process of performing step S4 may specifically include the following steps: Extract the node sequence contained in the emergency command path that accelerates propagation, collect the response delay data of each node in the node sequence, and apply path delay assessment technology to calculate the total transmission delay of the emergency command path among multiple nodes. If the total transmission delay is lower than the preset delay threshold, the emergency command path will be selected as the candidate emergency command transmission path. Stability testing was conducted on candidate emergency command transmission paths. After the stability test was passed, a real-time path monitoring mechanism was deployed. The load and link status of each node on the path are continuously monitored by the real-time path selection method. When the load of the main path exceeds the preset load threshold or the link status deteriorates, indicating that the latency will exceed the latency threshold, dynamic adjustment is triggered to switch the transmission command to the backup path or to make detour adjustments to the current node. If the total transmission latency of the adjusted path does not meet the preset latency threshold, then based on the latest network status data, the path dynamic adjustment and latency recalculation are iteratively performed until path data that meets the latency threshold and passes the stability test is obtained, and an optimized emergency command transmission path is generated.

[0044] Specifically, the emergency command propagation path, which is accelerated, may still experience latency jitter under conditions of continuous changes in network topology, link occupancy, and node processing load. In order to solve the problem of difficulty in guaranteeing the latency of command propagation under emergency conditions, a computable and iterative processing chain is established to transform the emergency command path from an "available path" into a set of transmission paths that "meet latency constraints and are monitorable and switchable".

[0045] The path for accelerating the propagation of emergency instructions is described in the form of a link graph, depicting the forwarding relationships between nodes. The path includes communication nodes such as gate nodes, edge gateways, switching equipment, and the central processing unit. The path can be represented as a set Π, where each element corresponds to a forwarding node identifier. After extracting the node sequence, node response delay data collection establishes a data alignment relationship around each node in Π. Response delay data can be reported by the node or measured from probe messages. Data fields include node processing queuing delay, forwarding processing delay, the average value and fluctuation amplitude over a recent period, and are mapped one-to-one with node identifiers to form a mapping table. Since different nodes in the same path contribute differently to the total delay, the path delay assessment technique merges node response delay data with link delay data. Link delay data can be obtained from link probes and stored as a mapping relationship according to adjacent node pairs, thus forming a "node pair - link delay" correspondence table for adjacent nodes in Π. The total path transmission delay is calculated by summing the response delay of each node in Π with the link delay of each adjacent node pair.

[0046] The threshold determination phase compares the total path transmission delay with a preset delay threshold. This preset threshold is set according to the emergency scheduling requirements of the sluice gate and can correspond to the gate's response window; for example, it could be set to 500 milliseconds or correspond to a certain proportion of the control cycle. When the total path transmission delay is lower than the threshold, the current emergency command path is registered as a candidate emergency command transmission path, and the candidate path identifier and the total path transmission delay are written into the candidate path table.

[0047] Stability testing verifies the reliability of candidate paths under high load conditions. Inputs include the parameters Π and channel parameters from the candidate path table. Virtual traffic or simulated service traffic is introduced to create a stress load, which is injected along Π and superimposed on existing service traffic, bringing the link queue and node queuing status close to emergency peak conditions. During the test, packet loss rate, latency fluctuation, and retransmission count are continuously collected to form a set of stability indicators. These indicators are compared with stability criteria, which specify that the packet loss rate must be below a certain threshold and the latency fluctuation must be within an allowable range. Upon successful stability testing, a real-time path monitoring mechanism is deployed. This mechanism monitors the candidate paths, using node load, link occupancy, queue length, and link status as monitoring parameters, and associates these with node identifiers and node-to-node identifiers.

[0048] The real-time path selection method continuously reads monitoring sequence data during operation and determines the load and link status of the main path. The load threshold can be set to 80% bandwidth utilization or node queuing length exceeding the upper limit. Link status deterioration can be characterized by increased packet loss rate, increased latency jitter, or increased link retransmission rate. When the triggering conditions are met, dynamic adjustment is activated, and the path is switched or rerouted. The switching action maps the forwarding of emergency instructions from the main path to the backup path, and the rerouting action replaces a node or link segment in the main path to avoid the fault point or congestion point. Preferably, the main path is selected from candidate emergency instruction transmission paths. In specific implementation, among the candidate paths that meet the latency threshold and pass the stability test, the total transmission latency is compared, and the path with the lowest latency and normal node online status is selected as the actual carrying path and recorded as the main path. The corresponding backup path is an alternative path pre-calculated based on the network topology or selected from the candidate set when the triggering conditions occur.

[0049] After the path is adjusted, the node sequence Π is updated to Π′, and node response delay data and link delay data are recollected based on Π′. The new total transmission delay κ′ is recalculated, and κ′ is compared with the preset delay threshold again. If κ′ still does not meet the threshold, it indicates that the adjustment has failed to eliminate the bottleneck. Therefore, the latest network status data is used as input to continue iteratively performing dynamic path adjustment and delay recalculation. The network status data includes the current topology reachability, link occupancy rate, and node processing load, and forms an incremental update relationship with the candidate path table, so that each iteration generates new Π′ and κ′ under the latest state constraints. When the path obtained in a certain iteration simultaneously meets the delay threshold and the stability criterion, the path data is written into the optimized path table and replaces the original candidate path entry, generating an optimized emergency command transmission path.

[0050] S5. Extract the path with the lowest latency from the optimized emergency command transmission path, distribute the emergency command, and obtain feedback signal data.

[0051] In one specific embodiment, the process of performing step S5 may specifically include the following steps: Extract the path with the least delay from the optimized emergency command transmission path and use it as the distribution path for this emergency command distribution; A cross-node collaboration mechanism is introduced on the distribution path to synchronize the distribution status and priority between nodes. At the same time, emergency instructions are distributed in batches based on real-time collected traffic monitoring data. Feedback signal data after batch distribution is obtained through feedback signal parsing technology, the feedback signal data is preliminarily processed, and the data integrity is verified. During the integrity verification process, if the feedback signal data is found to be missing or incorrect, the distribution mechanism is retried to redistribute the instructions that were not successfully confirmed. A statistical report on the distribution results is generated based on all feedback signal data. The statistical report includes at least the distribution success rate and the average response time.

[0052] Specifically, the emergency command transmission path is optimized and stored as a set of path records. Each path record includes a path identifier, node sequence, link segment information, total transmission latency metric, and channel parameters bound to a dedicated channel. Path records can share some link segments. The path with the lowest latency is extracted based on the total transmission latency metric and selected as the distribution path. At the same time, the node sequence and channel parameters of this path are written into the distribution configuration table, forming a fixed mapping between "distribution path - channel parameters - target node set" to avoid confirmation misalignment caused by path drift during emergency distribution.

[0053] Once the cross-node cooperation mechanism is enabled on the distribution path, a state synchronization channel needs to be established between the path nodes to enable the sharing of queue status, retransmission flags, and priority information during the distribution process. The data structure of the cooperation mechanism can include an instruction batch identifier, an instruction number within the batch, a target gate node identifier, a priority flag, and an acknowledgment status bit. The acknowledgment status bit consists of "not sent, sent, arrived, executed, and acknowledged," and each status bit is bound to a corresponding instruction number. Each forwarding node on the distribution path updates its local status bit and broadcasts a status summary to the cooperation channel upon receiving a batch of data packets. This allows upstream nodes to perceive downstream queuing pressure and acknowledgment progress, preventing packet loss caused by continuing to push data packets at a fixed rate under congestion conditions. Simultaneously, traffic monitoring data serves as the adjustment input for batch distribution. This traffic monitoring data originates from link counters and queue probes, including bandwidth utilization, queue length, packet loss count, and instantaneous throughput, and corresponds to the link segment identifier of the distribution path. The batch distribution strategy dynamically adjusts batch size and sending interval based on traffic monitoring data. For example, when bandwidth utilization increases and queue length approaches its limit, the number of instructions per batch is reduced and the batch interval is extended. When throughput decreases and packet loss count increases, batch splitting is triggered, and high-priority instructions that have not yet been acknowledged are sent first. This creates a closed-loop relationship between "traffic monitoring data - batch parameters - sending rhythm," which helps solve the problem of congestion caused by the mixing of emergency and regular traffic, leading to the blocking of critical instructions. Within the dedicated emergency channel, it further controls sudden traffic surges and reduces the impact of instantaneous congestion on arrival rates.

[0054] In the feedback signal acquisition phase, fields usable for verification and timing are extracted from the data returned by the target node using feedback signal parsing technology. After receiving and executing an emergency command, the target node returns feedback signal data, which includes the command number, node identifier, reception timestamp, execution status code, and verification fields. This data is then returned to the central processing unit via the distribution path or return channel. The parsing process unpacks the returned message, matching the command number in the message with the batch identifier on the distribution side, thus binding each feedback signal to a unique command record. Simultaneously, the reception timestamp is aligned with the distribution time. The preliminary processing phase deduplicates and sorts the feedback records. Deduplication handles duplicate receipts caused by network retransmissions, while sorting arranges receipts from the same batch in arrival order based on timestamps to identify gaps in receipts. Integrity verification uses the command number set as the comparison object. The set of numbers that should be received within a batch is compared with the set of already received numbers. If a missing number or a verification field fails, it is determined that there is a missing or incorrect number, and it is marked as "pending retransmission" in the status bit of the collaboration mechanism. Simultaneously, the missing number and its corresponding target node form a redistribution list. Targeted redistribution repackages and sends only instructions that have not been successfully confirmed according to the redistribution list. During redistribution, the priority of these instructions can be increased or the batch size can be reduced to decrease the probability of them being lost again. The feedback after redistribution continues to enter the parsing and integrity verification loop until the set of missing numbers is empty or the resend limit is reached.

[0055] During the statistical report generation phase, all feedback signal data is aggregated by batch and node. The distribution success rate is calculated as "number of confirmed instructions / number of instructions to be issued," and the average response time is obtained by averaging the difference between the distribution time and the confirmation receipt timestamp for each instruction. Both the success rate and the average response time are stored corresponding to batch identifiers. The statistical report may also include the receipt loss rate and redistribution count by node to locate weak links or node processing bottlenecks. It maintains a consistent index relationship with the status bit records of the collaboration mechanism, ensuring that the statistical results are traceable to specific instructions and specific nodes.

[0056] S6. Verify the feedback signal data and record the response speed index. Determine the adjusted transmission configuration based on the response speed index.

[0057] In one specific embodiment, the process of performing step S6 may specifically include the following steps: The feedback signal data is verified by receiving status verification technology. After the verification is successful, the abnormal status alarm information between nodes is collected, and the alarm information is integrated and analyzed. Based on the analysis results, the response speed index from instruction distribution to confirmation of receipt is calculated; Determine whether the response speed indicator meets the preset response threshold. If yes, determine the current transmission configuration as a transmission configuration adjustment scheme. If not, trigger the configuration adjustment decision. Based on the degree and pattern of indicator deviation, determine the transmission configuration parameters that need to be optimized and generate a transmission configuration adjustment scheme. The performance of the transmission configuration adjustment scheme is evaluated to verify its applicability. If the evaluation is successful, the transmission configuration adjustment scheme is determined as the adjusted transmission configuration. If the evaluation fails, the transmission configuration parameters are iteratively adjusted based on the evaluation results and the applicability evaluation is repeated until an adjusted transmission configuration that passes the evaluation is generated.

[0058] Specifically, after the emergency instruction is distributed, the scheduling link needs to confirm with verifiable data loop whether the instruction has been received and executed by the target node. At the same time, it also needs to promptly correct the transmission side parameters when network jitter, node load changes or link anomalies occur.

[0059] The feedback signal data has been parsed and preliminarily processed in step S5. The data record includes at least the instruction number, node identifier, receiving timestamp, execution status code, verification field, and distribution time associated with the batch identifier. The receiving status verification technology verifies each feedback record, covering both integrity and consistency. Integrity verification confirms that the feedback record has not been truncated or tampered with by comparing the verification field or verification code. Consistency verification checks whether the receipt corresponds to the issued instruction set by mapping the instruction number to the batch identifier, and eliminates obvious receipt mismatches by checking the timestamp order. Feedback records that pass verification are written to the "valid feedback set," while those that fail are entered into the "abnormal feedback set" with a failure reason code. This allows subsequent statistics and alarm fusion to distinguish between "missing data due to link packet loss" and "unavailability due to data format errors," isolating unusable receipts and preserving location clues.

[0060] After the effective feedback set is determined, abnormal state alarm information is collected and time-aligned with the feedback records. Alarm information originates from node controllers, communication devices, or security modules. Record fields include alarm type, node identifier, occurrence timestamp, duration, and severity flag. Alarm types can cover link congestion, high node CPU load, queue overflow, sensor anomalies, or actuator jamming. Alarm information integration and analysis aligns alarm timestamps with feedback reception timestamps using a unified time base, and aggregates alarms within batch windows to form an analysis result of "batch—alarm type distribution—severity summary." This analysis result has two correspondences with the effective feedback set: record-level and batch-level. At the record level, a specific feedback record is associated with the alarms appearing on that node within its reception window using the same node identifier. At the batch level, the overall performance of a group of feedback records is associated with the alarm distribution using the batch identifier.

[0061] The response speed metric is calculated based on the time difference between instruction distribution and acknowledgment reception, and is statistically analyzed at both the batch and node dimensions. Let the distribution time of an instruction be λ1 and the acknowledgment reception time be μ1, then the response latency is defined as ν1 = μ1 - λ1. ν1, along with the corresponding node identifier and instruction number, is written into the metric table. At the batch dimension, the mean and quantile of ν1 for the same batch are calculated to form the batch response level. Simultaneously, the success rate is calculated by combining the execution status code and the alarm analysis results to form a joint record of "batch-response metric-alarm characteristics." This joint record supports the identification of deviation patterns. For example, an increase in the mean and a lengthening of the quantile, accompanied by a link congestion alarm, indicates insufficient bandwidth or unreasonable queue weights. Conversely, a normal mean but a decreased success rate accompanied by a queue overflow alarm indicates insufficient packet loss and retransmission. An increase in the mean accompanied by a node overload alarm indicates a node processing bottleneck. After comparing the response speed index with the preset response threshold, the system enters the configuration decision branch. The response threshold can be given by the emergency scheduling window or control cycle constraints, and compared with the mean or quantile of the batch response level to avoid accidental triggering by a small number of extreme values.

[0062] The configuration adjustment decision takes the degree and pattern of deviation from the indicators as input, and outputs a set of transmission configuration parameters to be optimized and their corresponding adjustment ranges. The transmission configuration parameter set may include verification and retransmission policy parameters, queue scheduling weight parameters, batch distribution rhythm parameters, and channel bandwidth share parameters. Parameter selection is based on the deviation pattern mapping. For example, congestion-related deviations trigger increasing the emergency queue weight, reducing batch size, or increasing the dedicated channel bandwidth share; packet loss-related deviations trigger adjusting the retransmission window and acknowledgment timeout threshold and strengthening the verification strategy to improve the arrival rate; node load-related deviations trigger detours or reducing the concurrency of transmissions to specific nodes and coordinating with node-side buffering strategies. The generated transmission configuration adjustment scheme is represented in the form of a parameter list and saved along with the batch identifier, alarm characteristics, and response indicators that triggered the scheme, forming a correspondence of "scheme—triggering evidence—target parameter," preventing configuration adjustments from becoming unfounded static settings.

[0063] Performance evaluation verifies whether the transmission configuration adjustment scheme meets the applicability requirements under target load conditions. Evaluation can be conducted through online short-window trials or controlled load testing in isolated channels. Evaluation inputs include adjustment scheme parameters and network status data; evaluation outputs include success rate, response latency, and packet loss statistics. Response speed metrics are calculated using the same method for comparison with thresholds. If the evaluation passes, the adjustment scheme is solidified as the adjusted transmission configuration and distributed to the transmission control module. If the evaluation fails, parameters are updated based on the evaluation results, and the evaluation is repeated. Updates can adjust parameter step sizes according to the deviation direction while maintaining alarm characteristic constraints; for example, continuing to increase bandwidth share or further reducing batch concurrency if congestion is not alleviated. Through this iteration, the transmission configuration gradually converges from a "candidate adjustment scheme" to a "deployable configuration."

[0064] S7. Based on the adjusted transmission configuration, perform time synchronization processing on the remaining regular instructions, and integrate the synchronized regular instructions into the main propagation sequence to obtain a complete set of control instructions.

[0065] In one specific embodiment, the process of performing step S7 may specifically include the following steps: The remaining regular instructions are time-synchronized using the adjusted transmission configuration to obtain the synchronized regular instruction sequence. By combining the instruction execution confirmation information and the node status comparison results, the synchronized regular instruction sequence is integrated into the main propagation sequence; The integrated propagation sequence is subjected to transmission collision detection, and the instruction distribution rhythm is dynamically adjusted based on the collision detection results; Perform integrity verification on the propagation sequence after rhythm adjustment to ensure that no instructions are omitted or conflicting, and obtain the verification results; If the verification results show that there are conflicts or missing instructions, the distribution rhythm is adjusted iteratively and integrity verification is performed until the propagation sequence verification is passed. A complete set of control instructions is generated based on the finally verified propagation sequence.

[0066] Specifically, after emergency instructions are prioritized and distributed in the dedicated channel and the configuration is adjusted by feedback verification and response indicators, regular scheduling still needs to be restored to the continuous operation state of multi-gate linkage. With the adjusted transmission configuration as a constraint, the remaining regular instructions are reintegrated into the unified time base and merged with the main propagation sequence. At the same time, a cyclic correction is constructed with conflict detection and integrity verification to ensure that the control instruction set can cover all effective actions in the emergency phase and the regular phase and maintain the executable order.

[0067] The remaining regular instructions are derived from records in the instruction sorting list of step S2 that were not included in the emergency instruction subset. These records contain gate identifiers, control types, target opening degree or control quantity, generation timestamps, and time positioning information aligned with a unified time base. The adjusted transmission configuration's configuration parameters at least cover timestamp synchronization mechanism parameters, verification strategy parameters, retransmission and acknowledgment threshold parameters, and distribution rhythm control-related parameters. Therefore, the time synchronization process uses the timestamp synchronization mechanism in this configuration as a basis to re-align the timestamps of the regular instruction records and generate a synchronized regular instruction sequence. The re-alignment process maps the local time positioning of each regular instruction to a unified time axis, and triggers resynchronization when a time deviation exceeds a threshold. The threshold is given by the configuration parameters. After triggering, the node clock offset can be recalibrated or the interpolation coefficients updated to ensure that the regular instruction sequence is consistent with the time base used in the emergency phase.

[0068] The main propagation sequence carries out the propagation and confirmation process of emergency instructions during the emergency phase. Its sequence structure records the instruction identifier, target node, distribution path identifier, confirmation status, and timestamp aligned with the node status. When the synchronized regular instruction sequence is integrated into the main propagation sequence, the instruction execution confirmation information and the node status comparison result need to be introduced as an admission condition. The instruction execution confirmation information comes from node feedback or execution logs and includes the instruction number, execution result code, and confirmation timestamp, which corresponds to the regular instruction record through numbering or hash identification. The node status comparison result comes from status synchronization data and includes status fields such as gate opening, water level, and flow velocity, along with their timestamps. The comparison process matches the target status of the regular instruction with the actual status after execution within the same time window to determine whether the instruction has been executed or whether there is any deviation. The integration operation performs "acknowledgment mapping and status matching" on each regular instruction. When acknowledgment information exists and status matching is successful, the regular instruction is appended or inserted into the main propagation sequence. Appending is used when the instruction timestamp is later than the end of the existing sequence, and insertion is used when the instruction timestamp falls in the middle of the sequence. During insertion, the main propagation sequence is maintained by sorting according to the timestamp. When acknowledgment information is missing or status matching fails, the regular instruction is marked as pending and enters the retransmission or delayed delivery queue to prevent unacknowledged instructions from directly entering the main propagation sequence and causing subsequent conflict judgment distortion. This integration mechanism establishes a three-way correspondence between "instruction record - acknowledgment record - status record," enabling sequence fusion to be based on verifiable execution and solving the problems of missing feedback leading to inability to confirm execution status and difficulty in traceability after sequence integration.

[0069] After the propagation sequence is integrated, transmission collision detection is performed. The collision detection input includes the instruction timestamp sequence from the main propagation sequence, the target node set, and channel occupancy information. Channel occupancy information comes from queue weight and bandwidth share parameters in the transmission configuration, as well as real-time link monitoring data. Collision types can include the same node receiving mutually exclusive instructions within an overlapping time window, coordinated instructions from different nodes causing queue congestion and acknowledgment timeouts, and emergency backhauls and regular transmissions simultaneously triggering queue overflows on the same link segment. The detection method involves grouping the main propagation sequence by node and checking if the minimum interval between adjacent instructions is lower than the execution safety interval. Simultaneously, the expected occupancy rate of the link segment is estimated and compared with the queue capacity. When a collision risk is detected, a collision detection result is output, including the collision node identifier, the collision instruction pair identifier, and the collision cause code. The distribution rhythm is dynamically adjusted based on the collision detection result. Adjustment variables can include batch size, transmission interval, node concurrency, and queue scheduling weight. The adjustment process is constrained by the adjusted transmission configuration. For example, when the acknowledgment threshold is strict, concurrency is reduced to decrease false timeouts; when the retransmission window is large, the interval is appropriately lengthened to avoid retransmission stacking. After the rhythm adjustment, the distribution plan of the main propagation sequence is updated, and the updated parameters are written into the rhythm control table.

[0070] Integrity verification performs coverage and consistency checks on the main propagation sequence after rhythm adjustment. Coverage checks compare the "set of regular instructions to be processed" with the "set of regular instructions already written into the main propagation sequence" to confirm any omissions. Consistency checks verify the absence of mutually exclusive instruction pairs or duplicate instruction records in the sequence through conflict detection. Simultaneously, it checks each instruction in the sequence for corresponding acknowledgments or traceable execution status based on the confirmation information. The verification results include a list of missing instructions and a list of conflicting instructions, associated with reason codes. If the verification results show conflicts or missing instructions, the distribution rhythm adjustment and integrity verification enter an iterative loop. Iterations can increase the retransmission priority and reduce the concurrency of related nodes for missing instructions, and increase the instruction interval or adjust the insertion order for conflicting instruction pairs. The distribution plan and sequence content are updated after each iteration until the verification results no longer contain missing or conflicting instructions. The verified main propagation sequence is solidified into the output of the control instruction set. The control instruction set contains a complete set of emergency instructions and regular instructions in the form of a sequence. Each instruction retains a timestamp, target node, confirmation status and channel identifier under a unified time base, so that the control instruction set can be directly used for multi-gate collaborative control execution and post-event traceability.

[0071] Figure 2 This diagram illustrates the comparison between the cumulative success rate of our method and the traditional method as a function of the number of processed instructions. The diagram plots the cumulative success rate curves of the traditional method and our method during the continuous processing of multiple instructions, with the number of processed instructions on the horizontal axis and the cumulative success rate on the vertical axis. This is used to characterize the overall success rate of the two methods during the continuous distribution and confirmation of instructions, as well as the fluctuations caused by changes in the processing scale. The phased decline of the curve reflects the impact of changes in network load, link status, or node processing capacity on the instruction confirmation success rate. Figure 3 This diagram illustrates the comparison of response time distribution between our method and the traditional method. The diagram uses response time as the vertical axis and displays box plots of response time samples from both methods under the same test scenario. The boxes represent quartile intervals, the median line represents the median response time, and the upper and lower bars represent the distribution range of the samples. This diagram characterizes the differences in the concentration and dispersion of response time between the two methods during the instruction distribution to confirmation reception process, thereby reflecting the statistical distribution characteristics of the response speed index. Figure 4 This diagram illustrates the comparison of the success rates of emergency command processing between our method and the traditional method. The diagram plots the success rates of the traditional method and our method on multiple emergency command samples, with the emergency command number on the horizontal axis and the success rate on the vertical axis. Corresponding trend lines are also provided to characterize the dispersion and overall trend of the processing results of each step in the emergency command distribution and confirmation process. The trend lines reflect the overall level of success rate changes under different emergency command number conditions.

[0072] The aforementioned traditional method refers to a method in multi-gate node control where instructions are transmitted in a shared channel / shared queue according to the default communication mechanism, without traffic diversion or dedicated channel allocation based on the proportion of urgent requests, without adaptive transmission configuration adjustment based on feedback indicators, and with fixed strategies for paths and distribution rhythms (such as static routing, fixed bandwidth / fixed queue weight, or first-come-first-served), and feedback is only used for basic reception confirmation without driving configuration iteration and optimization.

[0073] The adaptive coordinated control gate control method in the embodiments of this application has been described above. The adaptive coordinated control gate control system in the embodiments of this application is described below. Please refer to [link / reference]. Figure 5 The present application provides a schematic diagram of the adaptive coordinated control gate control system, which includes: The instruction generation module 10 is used to acquire real-time instruction data from each gate node, use a time synchronization mechanism to handle time deviations, and generate an initial instruction sequence under a unified time reference.

[0074] The feature classification module 20 is used to extract instruction features based on the initial instruction sequence and classify them to obtain a sorted list of classified instructions.

[0075] The path generation module 30 is used to determine whether the proportion of emergency instructions in the instruction sorting list exceeds a preset proportion threshold. If so, it separates the emergency instruction subset from the instruction sorting list, allocates a dedicated transmission channel to the emergency instruction subset, and generates an emergency instruction path to accelerate propagation.

[0076] The delay assessment module 40 is used to calculate the transmission delay between multiple nodes based on the path delay assessment technology according to the accelerated propagation path of emergency instructions, and to determine the optimized emergency instruction transmission path based on the transmission delay.

[0077] The instruction distribution module 50 is used to extract the path with the lowest latency from the optimized emergency instruction transmission path, distribute emergency instructions, and obtain feedback signal data.

[0078] The feedback verification module 60 is used to verify the feedback signal data, record the response speed index, and determine the adjusted transmission configuration based on the response speed index.

[0079] The integration synchronization module 70 is used to perform time synchronization processing on the remaining regular instructions according to the adjusted transmission configuration, and integrate the synchronized regular instructions into the main propagation sequence to obtain a complete set of control instructions.

[0080] This application also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the adaptive coordinated control gate control method.

[0081] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An adaptive and coordinated gate control method, characterized in that, The method includes: S1. Obtain real-time command data from each gate node, use a time synchronization mechanism to handle time deviations, and generate an initial command sequence under a unified time reference. S2. Extract instruction features based on the initial instruction sequence and classify them to obtain a sorted list of classified instructions; S3. Determine whether the proportion of emergency instructions in the instruction sorting list exceeds a preset proportion threshold. If so, separate an emergency instruction subset from the instruction sorting list, allocate a dedicated transmission channel to the emergency instruction subset, and generate an emergency instruction path to accelerate propagation. S4. Based on the accelerated propagation of the emergency command path, the transmission delay between multiple nodes is calculated using path delay evaluation technology, and an optimized emergency command transmission path is determined based on the transmission delay. S5. Extract the path with the lowest latency from the optimized emergency command transmission path, distribute the emergency command, and obtain feedback signal data. S6. Verify the feedback signal data and record the response speed index, and determine the adjusted transmission configuration based on the response speed index. S7. Based on the adjusted transmission configuration, perform time synchronization processing on the remaining regular instructions, and integrate the synchronized regular instructions into the main propagation sequence to obtain a complete set of control instructions.

2. The method according to claim 1, characterized in that, S1 includes: Real-time command data is collected from each gate node, and a timestamp is added to each command data. A timestamp synchronization mechanism is used to align the clocks of each node to calibrate the time deviation and generate a preliminary command sequence after preliminary clock alignment. For inter-node communication, the data transmission rhythm is adjusted by multi-node transmission optimization technology for the preliminary instruction sequence. Based on the adjusted transmission rhythm, the preliminary instruction sequence is synchronously transmitted to the central processing unit to form an optimized communication stream. By combining gate status synchronization data, the instructions in the optimized communication stream are precisely calibrated to generate an initial instruction sequence under a unified time base; The initial instruction sequence is subjected to consistency verification to obtain the verification result; If the verification result shows that the time deviation exceeds the preset deviation threshold, the timestamp synchronization mechanism is iteratively adjusted and subsequent steps are re-executed until the initial instruction sequence that meets the time consistency requirements is generated.

3. The method according to claim 1, characterized in that, S2 include: Traverse the initial instruction sequence, extract the instruction feature value of each instruction, and based on the preset instruction priority layering method, divide the instructions into a high-priority layer and a low-priority layer according to the instruction feature value to obtain the layered instruction set; Acquire water flow parameter data, apply emergency command separation technology to match and analyze the commands in the layered command set with the water flow parameter data, identify emergency commands and regular commands, and obtain the distribution ratio of emergency commands; Based on the distribution ratio and the preset arrangement rules, an initial sorted list of classified instructions is generated; The initial instruction sorting list is subjected to priority verification to confirm that emergency instructions have a higher sorting priority than regular instructions. If the verification fails, the parameters of the instruction priority hierarchical method and / or emergency instruction separation technology are iteratively adjusted, and the hierarchical classification and sorting are re-executed until an initial instruction sorting list that passes the priority verification is generated. A stability evaluation is performed on the initial instruction sorting list that has passed priority verification, and the instruction sorting list is generated based on the evaluation results.

4. The method according to claim 1, characterized in that, S3 include: Count the number of emergency instructions in the instruction sorting list and calculate the proportion of emergency instructions; If the proportion of emergency instructions exceeds a preset threshold, all emergency instructions are extracted from the instruction sorting list using dedicated channel allocation technology to form an emergency instruction subset. Monitor the current network bandwidth usage, allocate dedicated transmission channels to the subset of emergency instructions using dynamic bandwidth adjustment technology, and confirm the channel parameters after allocation; Based on the allocation results of the dedicated transmission channel, combined with the current network topology and node status, an emergency command path for accelerated propagation is generated. The transmission efficiency of the emergency command path is pre-evaluated, and the evaluation results are compared with the preset rapid propagation requirements. If the requirements are not met, the dynamic bandwidth adjustment strategy is iteratively adjusted, channels are reallocated, and paths are generated until an emergency command path that meets the preset rapid propagation requirements is obtained.

5. The method according to claim 1, characterized in that, S4 include: Extract the node sequence contained in the emergency command path that accelerates propagation, collect the response delay data of each node in the node sequence, and apply path delay evaluation technology to calculate the total transmission delay of the emergency command path among multiple nodes. If the total transmission delay is lower than a preset delay threshold, then the emergency command path is determined as a candidate emergency command transmission path. The candidate emergency command transmission paths are subjected to stability testing. After the stability test is passed, a real-time path monitoring mechanism is deployed. The load and link status of each node on the path are continuously monitored by the real-time path selection method. When the load of the main path exceeds the preset load threshold or the link status deteriorates, indicating that the latency will exceed the latency threshold, dynamic adjustment is triggered to switch the transmission command to the backup path or to make detour adjustments to the current node. If the total transmission delay of the adjusted path does not meet the preset delay threshold, then based on the latest network status data, the path dynamic adjustment and delay recalculation are iteratively performed until path data that meets the delay threshold and passes the stability test is obtained, and an optimized emergency command transmission path is generated.

6. The method according to claim 1, characterized in that, S5 include: The path with the minimum delay is extracted from the optimized emergency command transmission path and used as the distribution path for this emergency command distribution. A cross-node collaboration mechanism is introduced on the distribution path to synchronize the distribution status and priority among nodes. At the same time, emergency instructions are distributed in batches based on real-time collected traffic monitoring data. Feedback signal data after batch distribution is obtained through feedback signal parsing technology, the feedback signal data is preliminarily processed, and the data integrity is verified. During the integrity verification process, if the feedback signal data is found to be missing or erroneous, the distribution mechanism is retried to redistribute the instructions that were not successfully confirmed. A statistical report on the distribution results is generated based on all feedback signal data. The statistical report includes at least the distribution success rate and the average response time.

7. The method according to claim 1, characterized in that, S6 include: The feedback signal data is verified by receiving status verification technology. After the verification is passed, abnormal status alarm information between nodes is collected, and the alarm information is integrated and analyzed. Based on the analysis results, the response speed index from instruction distribution to confirmation of receipt is calculated; Determine whether the response speed indicator meets the preset response threshold. If yes, determine the current transmission configuration as a transmission configuration adjustment scheme. If no, trigger a configuration adjustment decision. Based on the degree and pattern of indicator deviation, determine the transmission configuration parameters that need to be optimized and generate a transmission configuration adjustment scheme. The performance of the transmission configuration adjustment scheme is evaluated to verify its applicability. If the evaluation is successful, the transmission configuration adjustment scheme is determined as the adjusted transmission configuration. If the evaluation fails, the transmission configuration parameters are iteratively adjusted based on the evaluation results and the applicability evaluation is repeated until an adjusted transmission configuration that passes the evaluation is generated.

8. The method according to claim 1, characterized in that, S7 includes: The remaining regular instructions are time-synchronized using the adjusted transmission configuration to obtain a synchronized sequence of regular instructions. Combining the instruction execution confirmation information and the node status comparison results, the synchronized regular instruction sequence is integrated into the main propagation sequence; The integrated propagation sequence is subjected to transmission collision detection, and the instruction distribution rhythm is dynamically adjusted based on the collision detection results; Perform integrity verification on the propagation sequence after rhythm adjustment to ensure that no instructions are omitted or conflicting, and obtain the verification results; If the verification results show that there is a conflict or missing instructions, the distribution rhythm is iteratively adjusted and integrity verification is performed until the propagation sequence verification is passed. A complete set of control instructions is generated based on the finally verified propagation sequence.

9. An adaptive and coordinated gate control system, used to implement the method as described in any one of claims 1 to 8, characterized in that, The system includes: The instruction generation module is used to acquire real-time instruction data from each gate node, use a time synchronization mechanism to handle time deviations, and generate an initial instruction sequence under a unified time base. The feature classification module is used to extract and classify instruction features based on the initial instruction sequence to obtain a sorted list of classified instructions. The path generation module is used to determine whether the proportion of emergency instructions in the instruction sorting list exceeds a preset proportion threshold. If so, it separates an emergency instruction subset from the instruction sorting list, allocates a dedicated transmission channel to the emergency instruction subset, and generates an emergency instruction path to accelerate propagation. The delay assessment module is used to calculate the transmission delay between multiple nodes based on the accelerated propagation path of the emergency command, using path delay assessment technology, and to determine an optimized emergency command transmission path based on the transmission delay. The instruction distribution module is used to extract the path with the lowest latency from the optimized emergency instruction transmission path, distribute the emergency instructions, and obtain feedback signal data. The feedback verification module is used to verify the feedback signal data, record the response speed index, and determine the adjusted transmission configuration based on the response speed index. An integration synchronization module is used to perform time synchronization processing on the remaining regular instructions according to the adjusted transmission configuration, and to integrate the synchronized regular instructions into the main propagation sequence to obtain a complete set of control instructions.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instruction is executed by the processor, it implements the adaptive coordinated control gate control method as described in any one of claims 1 to 8.

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