A multi-point water intake metering system for a hydroelectric power station

Abstract

The application discloses a kind of hydropower station multi-point water taking measurement systems, it is related to hydropower station water taking measurement and hydraulic transient signal processing technical field, to each water taking branch according to round to exert codebook micro water hammer excitation carrying water taking branch identification and round identification and output reference template, obtains transient observation signal in pre-set observation position and obtains candidate event based on reference template and outputs verification pass event and verification fail event;Impulse response is updated in calibration window and generates water taking branch uncertainty index;Verification pass event generates physical consistency token quantity and generates write budget;Calculate congestion risk index and generate event priority and only allow to write minimum event frame in conservative mode;Virtual continuous page type real extraction buffer pool unit executes page type real extraction mapping to form writable window;Event frame settlement unit generates event frame;Measurement calculation and output unit outputs water taking branch instantaneous flow, water taking branch water taking and measurement confidence index.

Description

Technical Field

[0001] This invention relates to the field of water intake metering and hydraulic transient signal processing technology for hydropower stations, specifically a multi-point water intake metering system for hydropower stations. Background Technology

[0002] Hydropower stations typically have a main intake pipe, branch pipe sections, and multiple intake branches to meet water demands for unit operation, ecological discharge, sand flushing and removal, plant water intake, and maintenance. The statistical analysis of water consumption from multiple intake points is crucial not only for operation scheduling, energy management, and water resource accounting, but also directly impacts operational safety and dispute resolution. Current technologies usually involve installing flow meters, differential pressure gauges, level gauges, or valve position acquisition devices on intake branches or key pipe sections, and then aggregating and processing the collected data through the station control system to obtain the instantaneous flow rate and cumulative water intake of each branch.

[0003] Existing technologies can achieve a certain degree of multi-point water intake metering by installing flow meters on each water intake branch or deploying pressure and velocity sensors at pipeline nodes and combining them with empirical models for conversion. However, there are still some limitations: First, when multiple branches take water concurrently, valves operate frequently, or hydraulic conditions change abruptly, transient disturbances and reflections can easily cause measurement signals to become aliased, leading to unstable attribution of water intake branches and making it difficult to reliably distinguish events from different water intake branches within the same pipeline network. Second, some metering links rely on fixed sampling and fixed write queues. When a sudden surge of large flow occurs, the data link is prone to sudden congestion, and the writing of key data is uncertain, resulting in missing or unverifiable metering results. Third, model parameters are usually calibrated offline or updated at low frequency, making it difficult to reflect the drift of the impact response caused by changes in head, temperature, roughness, and pipeline conditions in a timely manner, thus causing fluctuations in metering errors and reliability. Fourth, existing data records often lack a strong chain of evidence that is strongly linked to the metering results, making it difficult to quickly trace back and determine responsibility for abnormal periods.

[0004] Therefore, there is an urgent need for a multi-point water intake metering system for hydropower stations that can stably output the instantaneous flow rate and water intake volume of water intake branches under conditions of concurrent operation of multiple branches and sudden changes in operating conditions. This system can be achieved through the coordination of a codebook micro-water hammer excitation unit, a continuous observation and verification unit along the route, an impulse response and uncertainty estimation unit, a physical consistency token casting unit, a structured execution graph scheduling unit, a virtual continuous page-type real-time buffer pool unit, an event frame settlement unit, and a metering calculation and output unit. It can also provide metering reliability indicators to support metering verification and operation management. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and propose a multi-point water intake metering system for hydropower stations to solve the above-mentioned problems.

[0006] The objective of this invention is achieved through the following technical solution: a multi-point water intake metering system for hydropower stations, comprising a codebook micro water hammer excitation unit, a continuous observation and verification unit along the route, an impulse response and uncertainty estimation unit, a physical consistency token casting unit, a structured execution graph scheduling unit, a virtual continuous page-type real-time buffer pool unit, an event frame settlement unit, and a metering calculation and output unit. The codebook micro water hammer excitation unit is used to apply codebook micro water hammer excitation carrying water intake branch identifier and cycle identifier to each water intake branch according to the cycle and output a reference template. The continuous observation and verification unit along the route is used to acquire transient observation signals at preset observation locations, and perform matching positioning based on reference templates to obtain candidate events, generate matching positioning confidence and propagation delay sets, and perform relevant peak significance judgment, propagation delay consistency judgment and attenuation reflection consistency judgment on candidate events to output verification passed events and verification failed events; The impulse response and uncertainty estimation unit is used to update the impulse response of the intake branch to the preset observation position based on the codebook micro water hammer excitation and transient observation signal within the calibration window, and to generate the uncertainty index of the intake branch based on the fitting residual. The physical consistency token minting unit is used to calculate the number of physical consistency tokens based on event energy, consistency residual and water intake branch uncertainty index within the event window only for events that pass verification, and generate the write budget accordingly. For events that fail verification, zero tokens and zero budget are generated. The virtual contiguous page-based physical page retrieval buffer pool unit includes a reserved contiguous virtual buffer space, a set of virtual pages divided by pages, and a set of physical pages that have already been retrieved. The structured execution graph scheduling unit is used to determine the target virtual page interval based on the write budget and drive the virtual continuous page-based real-time buffer pool unit to perform page-based real-time mapping on the target virtual page interval to form a writable window, and control the write execution to consume the write budget within the writable window to complete the event data writing; The event frame settlement unit is used to generate event frames and record the water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, water intake branch uncertainty index, physical consistency token quantity, write budget, write virtual page interval index and settlement mark; The metering calculation and output unit is used to output the instantaneous flow rate of the water intake branch, the water intake volume of the water intake branch, and the metering reliability index based solely on the verification pass event of the generated event frame and in combination with the impulse response.

[0007] The codebook micro water hammer excitation unit includes a fast-acting actuator and a codebook sequence generator. The codebook sequence generator is used to generate a codebook sequence containing water intake branch identifiers and cycle identifiers for different water intake branches. The fast-acting actuator is used to perform a limited action on the valve stroke of the water intake branch according to the codebook sequence within the cycle time window to form codebook micro water hammer excitation and limit the amplitude of codebook micro water hammer excitation within a preset safety boundary.

[0008] The continuous observation and verification unit along the route includes a distributed optical fiber sensing link and a consistency determination component. The consistency determination component is used to complete the propagation delay consistency determination based on the arrival time difference of multiple preset observation locations, and to complete the attenuation and reflection consistency determination based on the amplitude attenuation ratio and reflection characteristics of multiple preset observation locations.

[0009] The impulse response and uncertainty estimation unit is used to establish a convolutional fitting relationship between the codebook micro-water hammer excitation and transient observation signal within the calibration window, and to estimate the impulse response under regular constraints, so that the impulse response satisfies the smoothness constraint and the causality constraint.

[0010] The physical consistency token minting unit is used to calculate the event energy based on the transient observation signals from multiple preset observation locations with preset weights, calculate the consistency residual based on the difference between the impulse response prediction signal and the transient observation signal, and map the number of physical consistency tokens to the write budget.

[0011] The structured execution graph scheduling unit is used to calculate congestion risk indicators based on the actual physical page occupancy and the write budget to be written. It generates event priorities based on the number of physical consistency tokens, consistency residuals, water intake branch uncertainty indicators, and congestion risk indicators, and divides candidate events into high-priority events and low-priority events accordingly. When the congestion risk indicators reach the entry threshold, it enters conservative mode to freeze the write budget allocation for low-priority events and only allows the writing of the minimum event frame. When the congestion risk indicators decrease to the exit threshold, it exits conservative mode and resumes write budget allocation. The minimum event frame includes water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, number of physical consistency tokens, and settlement flag.

[0012] The virtual contiguous page-based physical page eviction buffer pool unit also includes a delayed reclamation queue. The structured execution graph scheduling unit is used to add the evicted physical pages to the delayed reclamation queue after writing is completed, and to perform batch reclamation on the delayed reclamation queue when the evicted physical page occupancy reaches the high watermark threshold, and to pause reclamation when the evicted physical page occupancy decreases to the low watermark threshold.

[0013] The event frame settlement unit is used to generate enhanced event frames. The enhanced event frames further include the impulse response summary fingerprint, water intake branch uncertainty index and write budget consumption record on the basis of the minimum event frames. The structured execution graph scheduling unit is used to allow the generation of only minimum event frames in conservative mode and to allow the generation of enhanced event frames in non-conservative mode.

[0014] The metering calculation and output unit is used to reconstruct the flow change of the transient observation signal of the water intake branch based on the propagation delay set and impulse response recorded in the event frame, and to integrate the flow change within the preset metering period to obtain the water intake of the water intake branch. Based on the uncertainty index and consistency residual of the water intake branch, the unit outputs the metering reliability index.

[0015] A multi-point water intake metering method for a hydropower station includes: S1, apply codebook micro water hammer excitation carrying water intake branch identifier and cycle identifier to each water intake branch according to the cycle and output reference template; S2, acquire transient observation signals at preset observation locations in the main pipe, branch pipe sections and water intake branches; S3, perform matching localization on transient observation signals based on reference templates to obtain candidate events, and generate a set of matching localization confidence and propagation delay; S4 performs relevant peak significance determination, propagation delay consistency determination, and attenuation reflection consistency determination on candidate events to output verification passed events and verification failed events; S5 updates the impulse response of the intake branch to the preset observation position based on the codebook micro water hammer excitation and transient observation signal within the calibration window, and generates the uncertainty index of the intake branch based on the fitting residual. S6 calculates the event energy and consistency residual only for events that pass verification within the event window, and calculates the number of physical consistency tokens based on the event energy, consistency residual and water intake branch uncertainty index, and generates the write budget accordingly. For events that fail verification, zero tokens and zero budget are generated. S7 calculates congestion risk indicators based on the actual physical page occupancy and the write budget to be written. It also generates event priorities based on the number of physical consistency tokens, consistency residuals, water intake branch uncertainty indicators, and congestion risk indicators, classifying candidate events into high-priority and low-priority events accordingly. When the congestion risk indicators reach the entry threshold, it enters a conservative mode to freeze the write budget allocation for low-priority events and only allows writing of the minimum event frame. The minimum event frame includes the water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, and physical page count. The system calculates the consistency token quantity and settlement flag, and exits conservative mode and resumes write budget issuance when the congestion risk index decreases to the exit threshold. Based on the write budget, it determines the target virtual page interval and performs page-based real-time mapping on the target virtual page interval to form a writable window. Within the writable window, it consumes the write budget to complete the event data writing and generates event frames and settlement flags. The event frame records the water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, water intake branch uncertainty index, physical consistency token quantity, write budget, and write virtual page interval index. S8 outputs the instantaneous flow rate of the water intake branch, the water intake volume of the water intake branch, and the metering reliability index based only on the verification pass event of the generated event frame and combined with the impulse response.

[0016] The beneficial effects of this invention are: The codebook micro-water hammer excitation unit uses codebook micro-water hammer excitation carrying water intake branch identifiers and cycle identifiers as a controllable input and outputs a reference template, enabling multiple water intake branches to generate transient responses with separable characteristics in the same pipeline network. The continuous observation and verification unit along the pipeline acquires transient observation signals at preset observation locations in the main pipe, branch pipe sections, and water intake branches, and completes matching and positioning based on the reference template. At the same time, it performs relevant peak significance determination, propagation delay consistency determination, and attenuation reflection consistency determination, further constraining the matching to physical consistency. This suppresses false identification events caused by noise, local disturbances, or reflection superposition from entering the metering link from the source, avoiding contamination of multi-point water intake metering by false events. This combination ensures that each verification pass event entering subsequent processing has clear evidence of water intake branch attribution, cycle attribution, and consistency along the pipeline, thereby improving the authenticity and auditability of metering input data.

[0017] The impulse response and uncertainty estimation unit establishes a convolutional fitting relationship based on the codebook micro-water hammer excitation and transient observation signals within the calibration window, and estimates the impulse response under regularization constraints, ensuring that the impulse response satisfies smoothness and causality constraints. At the same time, it generates the intake branch uncertainty index based on the fitting residual. The physical consistency token casting unit calculates the event energy according to the preset weights of the transient observation signals from multiple preset observation locations within the event window, and calculates the consistency residual based on the difference between the impulse response prediction signal and the transient observation signal. Then, it calculates the number of physical consistency tokens by combining the intake branch uncertainty index and maps them to generate the write budget. This combination forms a closed-loop mapping of model-observation-credibility-resource, so that the write budget is no longer determined by a fixed queue depth or static parameters, but is constrained by the physical consistency of the event itself and the model credibility. Thus, it automatically converges to the matching write intensity under different water heads, different flow regimes, and different disturbance backgrounds, reducing manual tuning costs and improving cross-scenario adaptability.

[0018] The structured execution graph scheduling unit organizes event location, event verification, token minting, budget allocation, page-based withdrawal, write execution, and settlement writeback into a defined processing sequence based on execution graph dependencies. It calculates congestion risk indicators based on the physical page occupancy and the write budget to be written. Then, it uses the physical consistency token quantity, consistency residual, water intake branch uncertainty, and congestion risk indicators together to generate event priorities and classify events into high-priority and low-priority categories. When the congestion risk indicator reaches the entry threshold, it enters conservative mode, freezes the write budget allocation for low-priority events, and only allows the writing of the smallest event frame. When the congestion risk indicator decreases to the exit threshold, it exits conservative mode and resumes write budget allocation. This combination allows the system to prioritize the allocation of limited write bandwidth to events with stronger physical consistency and higher metering value during sudden surges in traffic, and compresses the write content into the smallest event frame. This ensures that the metering link remains unbroken even under sudden link congestion conditions, avoiding system-level failures caused by complete write failures or total overload. Simultaneously, the hysteresis control of the entry and exit thresholds suppresses policy jitter caused by frequent switching, improving stability under sudden changes in operating conditions.

[0019] The virtual contiguous page-based real-time extraction buffer pool unit uses reserved contiguous virtual buffer space and a set of virtual pages divided by pages to carry the write window, and provides page-based real-time extraction mapping capability through the set of physically extracted pages. The structured execution graph scheduling unit determines the target virtual page interval based on the write budget and drives the page-based real-time extraction mapping to form a writable window and controls the write execution to consume the write budget within the writable window to complete the event data writing. This combination transforms the write capacity from a fixed-length queue to a budget-driven writable window. The window size changes synchronously with the event credibility and the system congestion state, which can amplify throughput under stable operating conditions and quickly converge write occupancy under congested operating conditions. It avoids the problem of a fixed queue depth being too large, causing congestion, or too small, causing the loss of critical events in different scenarios.

[0020] The event frame settlement unit generates an event frame after each write execution and records the water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, water intake branch uncertainty index, physical consistency token quantity, write budget, write virtual page interval index, and settlement mark. The minimum event frame is used as the disk carrier in the conservative mode. The metering calculation and output unit outputs the instantaneous flow rate of the water intake branch, the water intake volume of the water intake branch, and the metering confidence index based only on the verification pass event of the generated event frame and combined with the impulse response. This combination ensures that the data source of the metering calculation is strictly aligned with the write behavior, and guarantees that each metering output can be traced back to the corresponding event frame and its verification evidence, model state, and write budget constraints at the time of generation, forming a closed loop of measurable, provable, and verifiable results. This reduces the disputes and verification costs caused by unstable data links, unclear event sources, or model drift in traditional multi-point water intake metering. Attached Figure Description

[0021] Figure 1 The process of this invention Figure 1 ; Figure 2 The process of this invention Figure 2 ; Figure 3 The process of this invention Figure 3 . Detailed Implementation

[0022] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1 like Figure 1As shown in Example 1, the multi-point water intake metering system for the hydropower station is deployed at preset observation locations corresponding to the main water intake pipe, branch pipe sections, and each water intake branch. The system includes a codebook micro-water hammer excitation unit, a continuous observation and verification unit along the pipeline, an impulse response and uncertainty estimation unit, a physical consistency token casting unit, a structured execution graph scheduling unit, a virtual continuous page-type real-time buffer pool unit, an event frame settlement unit, and a metering calculation and output unit. The units interact with each other via a communication interface, with observation data and excitation records serving as processing inputs and metering results as processing outputs.

[0024] The codebook-based micro-water hammer excitation unit includes a codebook sequence generator and a fast-acting actuator. The codebook sequence generator generates a codebook sequence containing the water intake branch identifier and cycle identifier for each water intake branch, and establishes a mapping table between the codebook sequence and the reference template for each water intake branch during the system initialization phase. The reference template is used for matching and positioning calculations. The fast-acting actuator is connected to the valve stroke actuator of the corresponding water intake branch. Within the cycle time window, the fast-acting actuator drives the valve stroke to perform restricted actions according to the codebook sequence to form codebook-based micro-water hammer excitation. The amplitude and duration of the restricted actions are constrained by preset safety boundaries and are scheduled in cycles under the control of the structured execution graph scheduling unit, so that the codebook-based micro-water hammer excitation forms identifiable transient characteristics without affecting water intake safety and unit stability. At each cycle of excitation, the codebook-based micro-water hammer excitation unit records the water intake branch identifier, cycle identifier, excitation start and end time, codebook sequence index, and reference template index, and publishes an excitation completion event to the structured execution graph scheduling unit. The excitation completion event serves as the time anchor for subsequent matching, positioning, and calibration window determination.

[0025] The continuous observation and verification unit along the pipeline collects transient observation signals at preset observation locations in the main pipe, branch pipe sections, and intake branches. These transient observation signals include pressure transient signals and their timestamps. The sampling frequency is determined by the system configuration table and remains consistent throughout operation. The continuous observation and verification unit organizes the transient observation signals into a data sequence that can be extracted by event windows in chronological order. Within each round's time window, the structured execution graph scheduling unit performs matching and positioning on the transient observation signals based on a reference template to obtain candidate events. Matching and positioning employs correlation operations and outputs the intake branch identifier, round identifier, arrival time, and matching and positioning confidence of the candidate events. The matching and positioning satisfies the following correlation model expression: in Indicates the first Transient observation signals at preset observation locations, The water intake branch road sign is And the round number is identified as The codebook micro water hammer excitation signal (i.e., in the round) Within the time window, and (equivalent) This represents the impulse response from the water intake branch to the preset observation position. To observe the noise, This represents the convolution operation. This represents the summation over all water intake branches. The continuous observation and verification unit along the route performs correlation peak significance determination, propagation delay consistency determination, and attenuation reflection consistency determination at the candidate event level. Correlation peak significance determination confirms that the matching location confidence reaches a threshold; propagation delay consistency determination confirms that the arrival time difference of the same candidate event between different preset observation locations falls within an allowable range; and attenuation reflection consistency determination confirms that the amplitude attenuation ratio and reflection characteristics of the candidate event at different preset observation locations fall within an allowable range. A verification pass event is output when all three determinations are satisfied; a verification fail event is output when any one determination is not satisfied. The continuous observation and verification unit along the route writes the verification pass and verification fail events into the event queue and publishes the results to the physical consistency token minting unit and the structured execution graph scheduling unit. Verification fail events do not proceed to subsequent token minting and writing execution.

[0026] The impulse response and uncertainty estimation unit updates the impulse response of the water intake branch to the preset observation position within the calibration window and generates the water intake branch uncertainty index. The calibration window is determined by the structured execution graph scheduling unit and satisfies the codebook round coverage condition and the data availability condition. The codebook round coverage condition is used to ensure that the codebook micro-water hammer excitation coverage of each water intake branch reaches a preset quantity threshold and meets the observation position coverage requirement within the calibration window. The data availability condition is used to ensure that the proportion of verification pass events reaches a preset proportion threshold and the congestion risk index is lower than the calibration threshold within the calibration window. Within the calibration window, the impulse response and uncertainty estimation unit establishes a convolution fitting relationship between each water intake branch and each preset observation position and estimates the impulse response under regularization constraints, so that the impulse response satisfies the smoothness constraint and the causality constraint. The impulse response estimation adopts the following core optimization expression: in For the calibration window Observation vectors at preset observation locations, For water intake branch road The codebook is composed of a convolution matrix of micro-water hammer excitation. The discrete impulse response vector. For difference operators with smoothness constraints, For regularization weights, This represents the squared L2 norm. The impulse response and uncertainty estimation unit generates an uncertainty index for the water intake branch based on the fitted residuals. The uncertainty index is obtained by normalizing the residual energy and residual variance within the calibration window and aggregated to the water intake branch level according to the preset observation location weights. The aggregated water intake branch uncertainty index is used for subsequent token quantity calculation and metrological reliability assessment. The updated impulse response and water intake branch uncertainty index are available for use by the physical consistency token casting unit and the metrological calculation and output unit.

[0027] The physical consistency token minting unit generates the number of physical consistency tokens and write budgets only for verification pass events. For verification fail events, it generates zero tokens and zero budgets, and marks the zero-budget event as write-prohibited. For each verification pass event, the physical consistency token minting unit first checks the event window... The event window is extracted from multiple preset observation location data segments, and the event energy is calculated according to preset weights. The event energy is used to describe the transient intensity and information content within the event window. The physical consistency token forging unit then generates an impulse response prediction signal based on the impulse response and calculates the consistency residual. The consistency residual is used to describe the degree of deviation between the observation and the model and reflects physical consistency. The impulse response prediction signal is obtained by convolving the updated impulse response with the codebook micro water hammer excitation of the corresponding water intake branch.

[0028] In this embodiment, let the preset set of observation locations participating in the aggregation be . For the preset observation position The propagation delay set elements are The aligned transient observation signal is defined as follows: and make the weight satisfy Event energy With consistency residuals They are defined as follows: in The water intake branch road is marked as And the round number is identified as Event window, For the preset set of observation locations participating in the aggregation, Preset observation positions in the propagation delay set The propagation delay For the aligned transient observation signal, To preset the weights of the observation locations, For event energy, For consistent residuals, This indicates the integration of time within the event window.

[0029] The physical consistency token minting unit uses event energy, consistency residual, and water intake branch uncertainty index together to calculate the number of physical consistency tokens and generate a write budget. The calculation of the number of physical consistency tokens uses the following core expression: in The water intake branch road is marked as And the round number is identified as The verification is based on the number of tokens used for physical consistency of the event. For event energy, For consistent residuals, To correspond to the uncertainty index of the water intake branch, , , , Configure system parameters, It is the natural logarithm function. The operation is rounded down. The write budget is mapped from the number of physical consistency tokens. The mapping relationship is determined by the budget granularity parameter and fixed in the system configuration table. When the number of physical consistency tokens is zero, the write budget is zero. Events with a write budget of zero do not enter the page-based real-time request queue of the virtual continuous page-based real-time request buffer pool unit. The physical consistency token minting unit outputs the event window identifier, water intake branch identifier, round identifier, number of physical consistency tokens, write budget, and summary values ​​of event energy, consistency residual, and water intake branch uncertainty index to the structured execution graph scheduling unit as inputs for event priority generation and congestion control.

[0030] The virtual contiguous page-based real-pickup buffer pool unit reserves contiguous virtual buffer space during system initialization and divides it into virtual page sets. Each virtual page set records the virtual page start address, virtual page length, virtual page index, and occupancy status. The set of real-pickup physical pages records the identifiers and mapping relationships of mapped physical pages. The structured execution graph scheduling unit determines the target virtual page interval based on the write budget and drives the virtual contiguous page-based real-pickup buffer pool unit to perform page-based real-pickup mapping on the target virtual page interval to form a writable window. The writable window includes the write start virtual address, write upper limit virtual address, write virtual page interval index, and write budget upper limit. Write execution sequentially writes event data within the writable window and consumes the write budget. After write execution is complete, the write end offset and actual consumed budget are sent back to the event frame settlement unit. To ensure the controllability of the write budget and buffer occupancy, the structured execution graph scheduling unit maintains the real-pickup physical page occupancy and calculates congestion risk indicators based on the real-pickup physical page occupancy and the write budget to be written. The congestion risk indicators are used to characterize resource pressure and determine system mode switching. The structured execution graph scheduling unit further calculates congestion risk indicators based on the number of physical consistency tokens, consistency residuals, and water withdrawals. The uncertainty index and congestion risk index generate event priorities, which are then used to classify high-priority and low-priority events. High-priority events ensure that critical metering data can still be written during periods of sudden surges. Low-priority events are frozen when the congestion risk index reaches the entry threshold, and only the minimum event frame is allowed to be written. When the congestion risk index decreases to the exit threshold, the conservative mode is exited and the write budget is restored. This provides hard constraints on the write path during sudden surges in traffic and avoids sudden link congestion. At the same time, mode hysteresis avoids instability in the buffer strategy caused by sudden changes in traffic characteristics. The structured execution graph scheduling unit processes candidate events according to the execution graph dependencies. Event verification can only proceed after event location is completed. Only after the event verification outputs a verified event can token minting proceed. Only after the token minting output is written to the budget can budget distribution and page-based withdrawal proceed. Only after page-based withdrawal is completed and a writable window is formed can write execution proceed. Only after write execution is completed can event frame settlement and settlement write-back proceed. Settlement write-back is used to update the statistics of the congestion risk index, the running status of the entry threshold and exit threshold, and to calibrate the data availability statistics required for window determination.

[0031] The event frame settlement unit generates an event frame after each write operation. Each event frame corresponds one-to-one with a verification event and carries the key fields required for metering verification. An event frame records at least the water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, water intake branch uncertainty index, number of physical consistency tokens, write budget, write virtual page interval index, and settlement flag. The minimum event frame contains at least the following: water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, number of physical consistency tokens, and settlement flag; propagation delay set... The event frame is output by the continuous observation and verification unit during the propagation delay consistency determination stage and written into the event frame by the event frame settlement unit. The virtual page interval index is returned by the virtual continuous page real extraction buffer pool unit and written into the event frame by the event frame settlement unit. The settlement mark is used to identify whether the event frame has been written into the settlement and serves as a filtering condition for the metering calculation and output unit. Event frames with incomplete settlement marks are not included in the metering calculation. The event frame settlement unit organizes the event frames sequentially and enables the metering calculation and output unit to retrieve the event frames by water intake branch identifier and cycle identifier to ensure that the data source of the metering calculation is traceable and consistent with the written budget consumption.

[0032] The metering calculation and output unit performs metering calculations based solely on the verification events of the generated event frames and outputs the instantaneous flow rate of the intake branch, the water intake volume of the intake branch, and the metering reliability index. The unit first reads the intake branch identifier, round identifier, propagation delay set, settlement flag, intake branch uncertainty index, and consistency residual from the event frame, and then reads the impulse response corresponding to the version number of the event frame. Subsequently, it performs flow change restoration on the transient observation signal of the intake branch. Flow change restoration uses the impulse response as the system response core and combines it with the propagation delay set to align and fuse data from multiple preset observation locations. The fused observation signal is defined as: in To fuse observation signals, For the aligned transient observation signal, Preset observation location weights and satisfy The measurement calculation and output unit will... Discretization yields the fused observation vector The flow change vector of the water intake branch is solved under regularization constraints, so that the fused observation vector can be reconstructed in the sense of convolution: in The water intake branch road is marked as The discrete vector of flow change. To align the fused observation vectors, For water intake branch road The convolution matrix constructed from the impulse response, Regularization weights for restoring traffic changes For difference operators, This represents the square of the second norm. The measurement and output unit will... The data is mapped to an instantaneous flow sequence within an event window, and the instantaneous flow sequence within a preset metering period is integrated to obtain the water intake of the water intake branch. The integration boundary is determined by the metering period identifier and the event frame timestamp. The instantaneous flow of the water intake branch and the water intake of the water intake branch are output as the metering result. The metering reliability index is obtained by jointly mapping the water intake branch uncertainty index and the consistency residual and is output in association with the metering result. It is used to identify the reliability of the current metering result and the review priority.

[0033] In this embodiment, the system operates in the following sequential steps: S1 The codebook micro-water hammer excitation unit applies codebook micro-water hammer excitation to each water intake branch in rounds, outputs a reference template, and records the excitation information; S2 The continuous observation and verification unit along the route acquires transient observation signals at preset observation locations, performs matching positioning based on the reference template to obtain candidate events, and outputs the matching positioning reliability; S3 The continuous observation and verification unit along the route performs correlation peak significance determination, propagation delay consistency determination, and attenuation reflection consistency determination on candidate events, and outputs verification passed events and verification failed events; S4 The physical consistency token casting unit calculates the event energy and consistency residual for verification passed events, calculates the number of physical consistency tokens in conjunction with the water intake branch uncertainty index, generates a write budget, and generates zero tokens and zero budgets for verification failed events, and marks zero budget events as prohibited from writing; S5 The structured execution graph scheduling unit calculates the congestion risk index and generates event priorities, and enters conservative mode when the congestion risk index reaches the entry threshold. The conservative mode is frozen when low-priority events are allocated a write budget, allowing only the smallest event frame to be written. When the congestion risk index drops to the exit threshold, the conservative mode is exited and write budget allocation is restored. Simultaneously, the target virtual page interval is determined based on the write budget, and the virtual continuous page-type real-time extraction buffer pool unit is driven to perform page-type real-time extraction mapping to form a writable window. In S6, the write execution consumes the write budget within the writable window to complete the event data writing, and the event frame settlement unit generates an event frame and outputs a settlement mark. In S7, the metering calculation and output unit performs flow change restoration based on the event frame, propagation delay set, and impulse response, and outputs the instantaneous flow of the intake branch, the water intake of the intake branch, and the metering reliability index. In S8, the impulse response and uncertainty estimation unit updates the impulse response and the uncertainty index of the intake branch within the calibration window, and the structured execution graph scheduling unit performs settlement writeback to update the required statistics determined by the calibration window and maintain the consistency of the system's operating state, thereby ensuring that the data source, processing process, and output results are continuously closed in time sequence.

[0034] Example 2 like Figure 1 and Figure 2 As shown, in Example 2, based on Example 1, the continuous observation and verification unit along the path is specifically implemented as a combination of a distributed optical fiber sensing link and a consistency determination component. Continuous observation along the path replaces the discrete point acquisition method and strengthens the data foundation for propagation delay consistency determination and attenuation reflection consistency determination. This makes the verification of candidate events more stable through event determination, thereby making the generation of physical consistency tokens and write budget more controllable and reducing the time-series fluctuation of the metrological credibility index. Except for the hardware link deployment, data structure, alignment fusion and consistency determination process of the continuous observation and verification unit along the path, the composition, interface and processing flow of the other units are consistent with those of Example 1.

[0035] In this embodiment, the distributed optical fiber sensing link is laid along the main pipe, branch pipe sections, and water intake branches. The spatial sampling interval and temporal sampling frequency of the distributed optical fiber sensing link are fixed by the station configuration table and matched with the time window of the codebook micro water hammer excitation cycle. The distributed optical fiber sensing link outputs the along-path position index and the corresponding transient observation signal. The along-path position index is used to identify the preset observation position along the pipeline direction, and the transient observation signal is used to characterize the transient response caused by the propagation of the codebook micro water hammer excitation in the pipeline. To ensure that the along-path position index is consistent with the preset observation position of the system, the structured execution graph scheduling unit reads the pipeline during the system initialization phase. A mapping table between line mileage coordinates and fiber optic location indexes is provided. The mapping table records the start and end ranges of the mileage of the main pipe, branch pipe sections, and water intake branches, as well as the corresponding location index intervals. A preset set of observation locations that meets the preset number of observation locations and covers the main pipe, branch pipe sections, and water intake branches is selected from the mapping table. The preset set of observation locations remains unchanged during operation, and each preset observation location has a unique observation location identifier and location index. The distributed fiber optic sensing link continuously outputs the corresponding transient observation signal according to the location index, and the continuous observation and verification unit along the path performs streaming access on the local computing node side.

[0036] After connecting to the distributed optical fiber sensing link, the continuous observation and verification unit along the path uses a preset set of observation locations as an index to perform segmented extraction and time alignment of the transient observation signals along the path, forming a transient observation signal sequence for each preset observation location. Within each round's time window, it performs matching and positioning based on a reference template to obtain candidate events. To ensure that the arrival time difference between different preset observation locations can be used for propagation delay consistency determination, this embodiment sets up a time reference correction process within the continuous observation and verification unit along the path. The time reference correction process uses the round identifier and excitation start time issued by the codebook micro-water hammer excitation unit as a reference, and adjusts each preset... The transient observation signal sequence at each observation location is resampled onto a unified time axis. Then, a correlation operation based on a reference template is performed on the transient observation signal sequence at each preset observation location. The correlation operation outputs the arrival time and matching location confidence of the candidate event for that preset observation location. The candidate events are aggregated by the structured execution graph scheduling unit according to the water intake branch identifier and the round identifier. After aggregation, a candidate event record is formed. The candidate event record includes at least the water intake branch identifier, the round identifier, the candidate arrival time set, and the candidate matching location confidence set. The candidate arrival time set and the candidate matching location confidence set are indexed according to the preset observation location identifier.

[0037] The consistency determination component performs propagation delay consistency determination and attenuation reflection consistency determination on candidate event records. The propagation delay consistency determination takes the arrival time differences of multiple preset observation locations as input and outputs the propagation delay consistency determination result as a constraint using the residual form of the arrival time differences. The candidate event is placed at the preset observation location... The arrival time at the location is Preset observation location Compared with the reference preset observation position The predicted equivalent propagation delay between them is 1. The residual set for determining the consistency of propagation delay is defined as follows: in Preset observation location The time delay residual at the location, and These are the observation values ​​at the arrival time. The consistency determination component calculates the values ​​for all preset observation locations involved in the determination. And the consistency of propagation delay is measured using residual energy: in As a scalar measure of propagation delay consistency, This is the set of pre-defined observation locations for participating in the propagation delay consistency determination. This represents the summation of all positions within the set. The consistency determination component... Propagation delay consistency is determined when the value is less than the propagation delay consistency threshold. If the propagation delay consistency threshold is not less than the propagation delay consistency threshold, then the propagation delay consistency is deemed invalid, and... The index of the preset observation location set participating in the judgment is written into the candidate event record as the basis for calculating the propagation delay set.

[0038] The attenuation and reflection consistency determination takes the amplitude attenuation ratio and reflection characteristics at multiple preset observation locations as input and outputs the attenuation and reflection consistency determination result. In this embodiment, the amplitude attenuation ratio is calculated from the peak amplitude within the candidate event window, and the reflection characteristics are composed of the relevant peak sequence after the main peak within the candidate event window and a preset reflection time window. Let the preset observation locations... The peak amplitude of the event window is Reference to the preset observation position The peak amplitude of the event window is The amplitude attenuation ratio is then defined as: in Preset observation location The amplitude attenuation ratio at the preset observation position. The reflection feature vector is Reference to the preset observation position The reflection feature vector is Then the measure of reflectance feature difference is defined as: in As a measure of the difference in reflectance characteristics, This represents the squared L2 norm. The consistency determination component further imposes joint constraints on the difference between the amplitude attenuation ratio residual energy and the reflection characteristic measure, setting the predicted amplitude attenuation ratio to be... Then the attenuation reflection consistency metric is defined as: in As a measure of attenuation and reflection consistency, These are the reflection feature weight parameters. The consistency determination component... Attenuation reflection consistency is determined to be valid when the value is less than the attenuation reflection consistency threshold. If the value is not less than the attenuation reflection consistency threshold, the attenuation reflection consistency is deemed invalid. The significance determination of the relevant peak value of the candidate event still takes the matching location confidence set as input and outputs the significance determination result with the preset confidence threshold as constraint. The consistency determination component outputs the verification passed event and generates the corresponding propagation delay set only when the significance determination of the relevant peak value, the consistency determination of propagation delay and the consistency determination of attenuation reflection are all valid. The propagation delay set is composed of the preset observation positions that meet the consistency determination in the candidate arrival time set and is output after being sorted according to the preset observation position identifier. The verification failed event does not generate a propagation delay set and is marked as a zero token candidate.

[0039] When the continuous observation and verification unit outputs the verification pass event to the physical consistency token casting unit, it simultaneously outputs the propagation delay set bound to the verification pass event, the preset observation position index set, and the event window data segment identifier used to calculate the event energy and consistency residual. The event window data segment identifier is used to extract transient observation signal segments from multiple preset observation positions within the event window. Based on this, the physical consistency token casting unit calculates the event energy and consistency residual for the verification pass event and generates the number of physical consistency tokens and writes the budget. In this embodiment, the event energy is weighted and aggregated according to the preset observation position weights of the transient observation signal energy within the event window. In this embodiment, the consistency residual is obtained by aggregating the difference energy between the impulse response prediction signal and the transient observation signal. The calculation of the event energy and consistency residual is consistent with that in Embodiment 1 and maintains linkage with the uncertainty index of the water intake branch. The propagation delay set is used to align the impulse response prediction signal to the observation time axis of multiple preset observation positions and reduce the systematic offset of the consistency residual between different preset observation positions. The structured execution graph scheduling unit receives the verification pass event and its consistency metric. and Then, the consistency metric is written into the candidate event metadata and participates in the event priority generation, so that the candidate event with stronger consistency along the process has a higher event priority, thus ensuring that the candidate event with strong consistency along the process enters the write execution first when the congestion risk index increases.

[0040] In this embodiment, the event frame settlement unit uses the event frame field set of embodiment 1 and ensures that the propagation delay set comes from the output of the consistency determination component. When generating an event frame, the event frame settlement unit writes the propagation delay set and verification through event binding into the event frame, and also writes the propagation delay consistency measure output by the consistency determination component. Consistency measure with attenuation reflection The extended field area of ​​the event frame is written as the basis for verification. The extended field area and the minimum event frame field area are stored separately, and whether to write to the extended field area is determined by the write budget. When the write budget is insufficient, only the minimum event frame is written to ensure that writing and settlement can still be completed stably in conservative mode. When the metering calculation and output unit reads the event frame for metering calculation, it prioritizes using the propagation delay set to align and fuse the transient observation signal and combines it with the impulse response to perform flow change restoration. The multi-preset observation location data provided by continuous observation along the process makes the flow change restoration adopt a weighted fusion form, so that the aligned first... The transient observation signals at each preset observation location are The corresponding impulse response is The fused observation signal used to reconstruct the flow change of the water intake branch is defined as: in To fuse observation signals, Preset observation location The weights and satisfy (Normalization constraint) This represents the summation over the set of observed locations. The metering calculation and output unit reconstructs the data using the fused observed signals and corresponding impulse response sets, and outputs the instantaneous flow rate and water intake of the intake branch. The metering reliability indicators consist of the intake branch uncertainty index, consistency residual, and consistency measure. and The joint mapping is obtained and output together with the measurement results, making the measurement reliability index sensitive to changes in consistency along the fiber and able to reflect changes in the quality of fiber observations along the fiber.

[0041] In this embodiment, the continuous data processing process maintains a closed time sequence. The codebook micro-water hammer excitation unit outputs a reference template and round identifier. The distributed optical fiber sensing link outputs the along-path position index and transient observation signal, and the along-path continuous observation and verification unit forms a preset observation position sequence and outputs candidate event records. The consistency determination component outputs a set of verification pass events, verification fail events, and propagation delay based on the arrival time difference, amplitude attenuation ratio, and reflection characteristics of multiple preset observation positions, and provides a consistency metric. The physical consistency token minting unit outputs the number of physical consistency tokens for each verification pass event. The structured execution graph scheduling unit generates event priorities based on the written budget and outputs a zero budget flag for verification failure events. It then drives the virtual continuous page-type real-time buffer pool unit to form a writable window and complete the write execution. The event frame settlement unit generates event frames and outputs settlement flags. The metering calculation and output unit outputs the instantaneous flow rate of the water intake branch, the water intake volume of the water intake branch, and the metering reliability index based on the event frames, the propagation delay set, and the impulse response, and writes them back to the metering management platform. This enables the verification link, which is enhanced by continuous observation along the process, to form a coherent and uninterrupted data-driven support for subsequent tokens, writes, and metering outputs.

[0042] Example 3 like Figures 1 to 3 As shown, in Example 3, based on Examples 1 and 2, to address the issues of sudden link congestion caused by a sudden surge in traffic, the inability to adapt under different scenarios due to a fixed write queue depth, and the instability of the buffer strategy caused by sudden changes in traffic characteristics, the linkage mechanism of the structured execution graph scheduling unit, the virtual continuous page-based real-time withdrawal buffer pool unit, and the event frame settlement unit is enhanced. This makes event priority, conservative mode switching, write budget allocation, page-based real-time withdrawal mapping, delayed recycling queue, and event frame hierarchical generation form a closed-loop collaboration. Except for the event priority generation and freezing strategy, the batch recycling strategy of the delayed recycling queue, and the enhanced event frame generation strategy in different modes, which are the focus of this example, the composition, data source, interface, and basic processing flow of the other units are the same as those in Examples 1 and 2.

[0043] In this embodiment, the structured execution graph scheduling unit maintains a candidate event metadata record for each candidate event. The candidate event metadata record includes at least the water intake branch identifier, round identifier, matching location confidence, propagation delay set validity flag, event window identifier, physical consistency token quantity, write budget, water intake branch uncertainty index, consistency residual, and pending write status flag. The candidate event metadata record is established after the candidate events are output and verified by the continuous observation and verification unit along the route. After the physical consistency token casting unit completes the token casting, the physical consistency token quantity and write budget fields are supplemented, and the impulse response and uncertainty estimation unit supplements the water intake branch uncertainty index field. The structured execution graph scheduling unit also maintains a buffer resource status record. The buffer resource status record includes at least the occupied physical pages, the number of pending physical pages in the target virtual page interval, the length of the delayed reclamation queue, the number of events being written, and the write budget arrival rate in the most recent statistical window. The buffer resource status record is used to calculate the congestion risk index and serves as the input for event priority generation and mode switching.

[0044] To ensure that congestion risk indicators can be calculated, the most recent statistical window mentioned in this embodiment is a preset statistical window, and the statistical window can have a preset duration. Implemented using a sliding time window or a sliding event window with a preset number of events; write budget arrival rate. The write budget consumption rate is calculated by dividing the total amount of newly generated write budget within the statistics window by the length of the statistics window. The statistics are calculated by dividing the total amount of actual consumption written into the budget within the statistics window by the length of the statistics window. The statistics are updated each time the event is settled and written back.

[0045] The congestion risk indicator is presented as a scalar quantity derived from a combination of multiple resource pressure parameters to facilitate rapid determination during graph scheduling. Let the actual physical page occupancy be... The actual physical page capacity limit is 1. The physical page requirement to be actually requested corresponds to the target virtual page range obtained from the write budget conversion. The length of the delayed recycling queue is The maximum capacity of the delayed recycling queue is The recent budget write arrival rate within the statistics window is The recent budget write consumption rate within the statistics window is The core expression for calculating the congestion risk index by the structured execution graph scheduling unit is: in As an indicator of congestion risk. , , Configure system parameters, To prevent positive constants with a denominator of zero, The function aims to maximize the value. The structured execution graph scheduling unit compares the congestion risk index with the entry threshold and exit threshold to switch system modes. When the congestion risk index reaches the entry threshold, it enters conservative mode; when the congestion risk index decreases to the exit threshold, it exits conservative mode. When the entry threshold is greater than the exit threshold, a hysteresis interval is formed. The hysteresis interval is used to suppress frequent switching caused by the jitter of the congestion risk index near the threshold.

[0046] Regarding event priority generation, the structured execution graph scheduling unit calculates the event priority for each candidate event. This event priority is used to determine the write budget allocation object and event frame generation level when resources are scarce. Let the number of physical consistency tokens for each candidate event be... Consistency residual is The uncertainty index of the water intake branch is The congestion risk indicator is The event priority is then calculated using the following core expression: in For event priority scalar, , , , Configure system parameters (weighting coefficients). The function is the natural logarithm. The structured execution graph scheduling unit compares the event priority with a preset priority threshold. Candidate events with an event priority not less than the preset priority threshold are classified as high-priority events, and candidate events with an event priority less than the preset priority threshold are classified as low-priority events. The classification results of high-priority events and low-priority events are written into the candidate event metadata record and used as the control conditions for the budget disbursement node and the event frame settlement node.

[0047] In conservative mode, the structured execution graph scheduling unit freezes the write budget allocation for low-priority events and only allows the allocation of write budgets corresponding to the minimum event frame for high-priority events. In this embodiment, the write budget corresponding to the minimum event frame adopts a fixed minimum write budget granularity. And using event priority as the issuance condition, the write budget for the issuance of high-priority events by the structured execution graph scheduling unit is... And the corresponding target virtual page interval length is This ensures that the write usage of each high-priority event in conservative mode is strictly limited. Low-priority events retain candidate event metadata records in conservative mode but do not enter the paged real-time mapping queue. After exiting conservative mode, they are reordered according to event priority and write budget allocation is resumed. In non-conservative mode, the structured execution graph scheduling unit can allocate write budgets to both high-priority and low-priority events. The write budget is mapped from the number of physical consistency tokens and allows writing of enhanced event frames, so that the event frames have more complete verification information under normal operating conditions.

[0048] To address the issue of fixed write queue depth leading to a lack of adaptability across different scenarios, this embodiment replaces the write queue depth with a write budget-driven page-based real-time provisioning mapping window. At the budget allocation node, the structured execution graph scheduling unit converts the write budget into a target virtual page interval and triggers the virtual continuous page-based real-time provisioning buffer pool unit to execute page-based real-time provisioning mapping. The target virtual page interval is allocated according to the set of virtual pages in the continuous virtual buffer space, constrained by the write budget granularity. The larger the write budget, the longer the target virtual page interval and the larger the writable window, thereby improving throughput under low congestion conditions and converging the writable window to a minimum size through a conservative mode under high congestion conditions. Write execution consumes the write budget sequentially within the writable window and submits a write completion event when the budget limit is reached or the write completion condition is met. The event frame settlement unit generates an event frame and outputs a settlement flag.

[0049] In this embodiment, the virtual continuous page-based physical page withdrawal buffer pool unit further introduces a delayed reclamation queue to suppress buffer strategy instability caused by sudden changes in traffic characteristics. The delayed reclamation queue is used to store the identifiers and mapping information of physical pages that have been written but have not yet been physically reclaimed. After writing is completed, the structured execution graph scheduling unit adds the corresponding physical page to the delayed reclamation queue and marks the physical page as eligible for delayed reclamation. The delayed reclamation queue is sorted by the timestamp of entry into the queue to maintain continuity during batch reclamation. The structured execution graph scheduling unit continuously monitors the occupancy of physical pages that have been withdrawn and compares it with the high watermark threshold and the low watermark threshold. When the occupancy of physical pages that have been withdrawn reaches the high watermark threshold, the batch reclamation process is triggered, and the batch reclamation is started from the head of the delayed reclamation queue according to the batch reclamation quantity. Retrieve the already withdrawn physical pages, perform unmapping and physical page release. When the occupied physical pages decrease to the low watermark threshold, pause the batch reclamation process and retain the remaining physical pages in the delayed reclamation queue for reuse in subsequent write windows. The high watermark threshold is greater than the low watermark threshold to form a hysteresis interval, and both the high watermark threshold and the low watermark threshold are preset thresholds. Batch reclamation quantity. The size of the batch reclamation is adaptively determined by the structured execution graph scheduling unit based on congestion risk indicators. Let the maximum batch reclamation quantity be... The batch recycling quantity is determined using the following core expression: in This represents the number of physical pages reclaimed in this batch. Configure system parameters, As an indicator of congestion risk. To find the minimum value function, This is for rounding up. This batch reclamation strategy allows physical pages to be released in a concentrated manner during periods of sudden congestion to quickly reduce the occupancy of already displaced physical pages, while maintaining physical page mapping during non-congestion periods to avoid thrashing caused by frequent mapping reclamation, thereby improving the stability of the buffering strategy and reducing the system overhead of page-based actual displacement mapping.

[0050] In this embodiment, the event frame settlement unit implements a hierarchical event frame generation mechanism to coordinate with the conservative mode and priority freezing strategy. After the write execution is completed, the event frame settlement unit determines whether to generate a minimum event frame or an enhanced event frame based on the system mode flag provided by the structured execution graph scheduling unit and the event priority division results in the candidate event metadata record. In conservative mode, the event frame settlement unit only generates the minimum event frame and writes it into the event frame index area. The minimum event frame fields are water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, physical consistency token quantity, and settlement flag. The write budget consumption record is not written to reduce the amount of writing and shorten the write execution time. In non-conservative mode... In this formula, the event frame settlement unit generates an enhanced event frame. The enhanced event frame further includes an impulse response summary fingerprint, a water intake branch uncertainty index, and a written budget consumption record on the basis of the minimum event frame. The impulse response summary fingerprint is used to identify the consistent impulse response version participating in the calculation and to ensure that the same version of the impulse response can be retrieved during post-event review. In this embodiment, the impulse response summary fingerprint is generated by combining the summary value and version number of the impulse response vector at a preset sampling point and written into the enhanced event frame. The written budget consumption record is returned by the write execution and includes at least the written budget upper limit, the actual consumption budget, and the written virtual page interval index. After the enhanced event frame is written, the event frame settlement unit outputs a settlement mark and issues a measurable event notification to the metering calculation and output unit.

[0051] In this embodiment, the metering calculation and output unit maintains the metering calculation method of Embodiments 1 and 2, but adds an adaptation strategy for event frame classification in data reading. The metering calculation and output unit first filters event frames with valid settlement marks and reads the propagation delay set and impulse response summary fingerprint. If the event frame is the smallest event frame, the metering calculation is performed with the current valid impulse response version number and propagation delay set, and the metering reliability index is marked as the source of conservative mode. If the event frame is an enhanced event frame, the impulse response version is locked with the impulse response summary fingerprint, and the original event data is located and verified by the write virtual page interval index in the write budget consumption record. The metering calculation is then completed and the metering reliability index is output. The metering calculation and output unit outputs the metering results, metering reliability index and event frame type identifier to the metering management platform, so that the metering management platform can perform differentiated display and verification scheduling of the metering results during the conservative mode.

[0052] The data processing in this embodiment remains continuous and uninterrupted. The continuous observation and verification unit along the route outputs verification pass events and verification fail events, and provides a set of propagation delays. The impulse response and uncertainty estimation unit provides uncertainty indicators and impulse response version information for the water intake branch. The physical consistency token minting unit outputs the number of physical consistency tokens and the write budget, and outputs event energy and consistency residuals. The structured execution graph scheduling unit calculates congestion risk indicators, generates event priorities, and classifies high-priority events into low-priority events accordingly. It also switches between conservative modes and controls write budget distribution and page-based real-time mapping. The continuous page-based real-time withdrawal buffer pool unit forms a writable window based on the target virtual page interval. After writing, it adds the real-time withdrawn physical pages to the delayed recycling queue and triggers batch recycling and pause recycling based on high and low water level thresholds. The event frame settlement unit generates minimum event frames or enhanced event frames according to the system mode, writes the corresponding fields, and outputs the settlement mark. The metering calculation and output unit outputs the instantaneous flow rate of the water intake branch, the water intake volume of the water intake branch, and the metering reliability index based on the event frames and the impulse response, and writes them back to the metering management platform. This makes the write path convergence under sudden congestion, the buffer recycling stable, and the event frame information hierarchically controllable.

[0053] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A multi-point water intake metering system for a hydropower station, characterized in that, It includes a codebook micro water hammer excitation unit, a continuous observation and verification unit along the process, an impulse response and uncertainty estimation unit, a physical consistency token casting unit, a structured execution graph scheduling unit, a virtual continuous page-type real extraction buffer pool unit, an event frame settlement unit, and a measurement calculation and output unit. The codebook micro water hammer excitation unit is used to apply codebook micro water hammer excitation carrying water intake branch identifier and cycle identifier to each water intake branch according to the cycle and output a reference template. The continuous observation and verification unit along the route is used to acquire transient observation signals at preset observation locations, and perform matching positioning based on the reference template to obtain candidate events, generate a set of matching positioning confidence and propagation delay, and perform relevant peak significance determination, propagation delay consistency determination and attenuation reflection consistency determination on the candidate events to output verification passed events and verification failed events. The impulse response and uncertainty estimation unit is used to update the impulse response of the water intake branch to the preset observation position based on the codebook micro water hammer excitation and the transient observation signal within the calibration window, and to generate the water intake branch uncertainty index based on the fitting residual. The physical consistency token minting unit is used to calculate the number of physical consistency tokens based on event energy, consistency residual and uncertainty index of water intake branch within the event window only for the verification pass event, and generate the write budget accordingly, and generate zero tokens and zero budget for the verification fail event. The virtual continuous page-based physical page retrieval buffer pool unit includes a reserved continuous virtual buffer space, a set of virtual pages divided by pages, and a set of physical pages that have already been retrieved. The structured execution graph scheduling unit is used to determine the target virtual page interval based on the write budget and drive the virtual continuous page-based real-time buffer pool unit to perform page-based real-time mapping on the target virtual page interval to form a writable window, and control the write execution to consume the write budget within the writable window to complete the event data writing; The event frame settlement unit is used to generate event frames and record the water intake branch identifier, the round identifier, the matching location confidence, the propagation delay set, the event energy, the consistency residual, the water intake branch uncertainty index, the number of physical consistency tokens, the write budget, the write virtual page interval index, and the settlement flag. The metering calculation and output unit is used to output the instantaneous flow rate of the water intake branch, the water intake volume of the water intake branch, and the metering reliability index based solely on the verification pass event of the generated event frame and in combination with the impulse response.

2. The multi-point water intake metering system for hydropower stations according to claim 1, characterized in that, The codebook micro water hammer excitation unit includes a fast-acting actuator and a codebook sequence generator. The codebook sequence generator is used to generate a codebook sequence containing the water intake branch identifier and the cycle identifier for different water intake branches. The fast-acting actuator is used to perform a limited action on the valve stroke of the water intake branch according to the codebook sequence within the cycle time window to form the codebook micro water hammer excitation and limit the amplitude of the codebook micro water hammer excitation within a preset safety boundary.

3. The multi-point water intake metering system for hydropower stations according to claim 1, characterized in that, The continuous observation and verification unit along the route includes a distributed optical fiber sensing link and a consistency determination component. The consistency determination component is used to complete the propagation delay consistency determination based on the arrival time difference of multiple preset observation locations, and to complete the attenuation and reflection consistency determination based on the amplitude attenuation ratio and reflection characteristics of multiple preset observation locations.

4. The multi-point water intake metering system for hydropower stations according to claim 1, characterized in that, The impulse response and uncertainty estimation unit is used to establish a convolutional fitting relationship between the codebook micro-water hammer excitation and the transient observation signal within the calibration window, and to estimate the impulse response under regularization constraints, so that the impulse response satisfies smoothness constraints and causality constraints.

5. The multi-point water intake metering system for hydropower stations according to claim 1, characterized in that, The physical consistency token minting unit is used to calculate the event energy using the transient observation signals from multiple preset observation locations according to preset weights, calculate the consistency residual using the difference between the impulse response prediction signal and the transient observation signal, and map the number of physical consistency tokens to the write budget.

6. The multi-point water intake metering system for hydropower stations according to claim 1, characterized in that, The structured execution graph scheduling unit is used to calculate congestion risk indicators based on the actual physical page occupancy and the write budget to be written, and to generate event priorities based on the number of physical consistency tokens, the consistency residual, the water intake branch uncertainty index, and the congestion risk indicators. Based on this, the candidate events are divided into high-priority events and low-priority events. When the congestion risk indicator reaches the entry threshold, the unit enters a conservative mode to freeze the write budget allocation for the low-priority events and only allows the writing of the minimum event frame. When the congestion risk indicator decreases to the exit threshold, the unit exits the conservative mode and resumes the write budget allocation. The minimum event frame includes the water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, number of physical consistency tokens, and settlement flag.

7. The multi-point water intake metering system for hydropower stations according to claim 1, characterized in that, The virtual continuous page-based physical page withdrawal buffer pool unit also includes a delayed recycling queue. The structured execution graph scheduling unit is used to add the withdrawn physical pages to the delayed recycling queue after writing is completed, and to perform batch recycling of the delayed recycling queue when the occupied physical pages reach a high watermark threshold, and to pause recycling when the occupied physical pages decrease to a low watermark threshold.

8. The multi-point water intake metering system for hydropower stations according to claim 6, characterized in that, The event frame settlement unit is used to generate an enhanced event frame, which further includes the impulse response summary fingerprint, the water intake branch uncertainty index, and the written budget consumption record based on the minimum event frame. The structured execution graph scheduling unit is used to allow the generation of only the minimum event frame in the conservative mode and the generation of the enhanced event frame in the non-conservative mode.

9. The multi-point water intake metering system for hydropower stations according to claim 1, characterized in that, The metering calculation and output unit is used to restore the flow rate change of the transient observation signal of the water intake branch based on the propagation delay set recorded by the event frame and the impulse response, and to integrate the flow rate change within the preset metering period to obtain the water intake of the water intake branch, and to output the metering reliability index based on the uncertainty index of the water intake branch and the consistency residual.

10. A multi-point water intake metering system for a hydropower station according to any one of claims 1-9, characterized in that, Multi-point water intake metering methods include: S1, apply codebook micro water hammer excitation carrying water intake branch identifier and cycle identifier to each water intake branch according to the cycle and output reference template; S2, acquire transient observation signals at preset observation locations in the main pipe, branch pipe sections and water intake branches; S3, perform matching and localization on the transient observation signal based on the reference template to obtain candidate events, and generate a set of matching and localization confidence and propagation delay; S4, perform relevant peak significance determination, propagation delay consistency determination and attenuation reflection consistency determination on the candidate events to output verification passed events and verification failed events; S5, within the calibration window, update the impulse response of the water intake branch to the preset observation position based on the codebook micro water hammer excitation and the transient observation signal, and generate the water intake branch uncertainty index based on the fitting residual. S6, calculate the event energy and consistency residual only for the verification passed event within the event window, and calculate the number of physical consistency tokens based on the event energy, the consistency residual and the uncertainty index of the water intake branch, and generate the write budget accordingly, and generate zero tokens and zero budget for the verification failed event. S7. Based on the actual physical page occupancy and the write budget to be written, calculate the congestion risk index. Generate event priorities based on the number of physical consistency tokens, the consistency residual, the water intake branch uncertainty index, and the congestion risk index. Divide the candidate events into high-priority and low-priority events accordingly. When the congestion risk index reaches an entry threshold, enter a conservative mode to freeze the write budget allocation for low-priority events and only allow writing of the minimum event frame. The minimum event frame includes the water intake branch identifier, round identifier, matching location confidence, propagation delay set, event energy, consistency residual, and the number of physical consistency tokens. Settlement flag, and exit the conservative mode and resume write budget allocation when the congestion risk index decreases to the exit threshold. Determine the target virtual page interval based on the write budget and perform page-based real-time mapping on the target virtual page interval to form a writable window. Consume the write budget within the writable window to complete the event data writing and generate an event frame and settlement flag. The event frame records the water intake branch identifier, the round identifier, the matching location confidence, the propagation delay set, the event energy, the consistency residual, the water intake branch uncertainty index, the number of physical consistency tokens, the write budget, and the write virtual page interval index. S8, based solely on the verification pass event of the generated event frame and combined with the impulse response, output the instantaneous flow rate of the water intake branch, the water intake volume of the water intake branch, and the metering reliability index.

Images