A hydraulic engineering data monitoring method and system

Abstract

The application relates to the technical field of water conservancy engineering optimization, in particular to a water conservancy engineering data monitoring method, which comprises the following steps: constructing a three-dimensional water flow potential energy model of a water conservancy engineering region based on basic data, determining the potential energy distribution and variation trend of different spatial positions according to the three-dimensional water flow potential energy model, and determining the potential energy decreasing direction on the basis of the potential energy distribution and variation trend; searching for a potential seepage channel formed in the water conservancy engineering region in the three-dimensional space according to the potential energy decreasing direction, performing iterative tracking on the potential seepage channel, generating a channel extension track obtained through the tracking, and generating a potential seepage path for reflecting the groundwater flow direction. The application can construct a three-dimensional water flow potential energy model, determine the potential energy distribution and variation trend of different spatial positions, determine the potential energy decreasing direction, search for a potential seepage channel according to the potential energy decreasing direction, and perform iterative tracking to generate a potential seepage path.

Description

Technical Field

[0001] This application relates to the field of water conservancy engineering optimization technology, specifically to a water conservancy engineering data monitoring method and system. Background Technology

[0002] Water conservancy projects are affected by multiple factors during long-term operation, including changes in water pressure, pore water seepage, dam structure aging, and changes in the external environment. Seepage is one of the most common and insidious safety risks. Existing monitoring systems generally rely on point data obtained from multiple monitoring points, combined with manual inspections and periodic analysis methods, to record and compare indicators such as seepage pressure changes, seepage flow fluctuations, and structural deformation, thereby conducting a basic safety assessment of the operational status of water conservancy projects.

[0003] However, due to the strong spatial heterogeneity and concealment of seepage, the point data collected by fixed-location sensors is difficult to reflect the true water flow distribution within the entire water conservancy project area, especially in underground spaces where no monitoring points are set up, where potential seepage channels are easily formed and difficult to detect.

[0004] Furthermore, existing technologies often rely primarily on anomalous deviations in single-point values ​​as the main criterion, lacking in-depth analysis of spatial correlations, temporal evolution trends, and coupling relationships between different data types. This makes it difficult to identify the development trajectory of seepage in three-dimensional space from an overall structural perspective. Consequently, when groundwater flow shows signs of gradually extending, penetrating, or breaking through key structural areas, traditional monitoring methods often fail to identify potential leakage paths in advance. This makes it difficult to accurately assess leakage risks in the early stages, reducing the efficiency of safety management in water conservancy projects.

[0005] Therefore, this application proposes a data monitoring method and system for water conservancy projects in order to solve the above problems. Summary of the Invention

[0006] To achieve the above objectives, this application provides a method for monitoring water conservancy project data, comprising the following: Acquire monitoring data in the water conservancy project area, define and extract seepage data from the monitoring data, perform time synchronization and calibration processing on the seepage data, and obtain basic data for subsequent modeling based on the calibration processing.

[0007] Based on the basic data, a three-dimensional water flow potential energy model of the water conservancy project area is constructed. The potential energy distribution and change trend at different spatial locations are determined according to the three-dimensional water flow potential energy model, and the direction of potential energy decrease is determined based on the potential energy distribution and change trend.

[0008] Based on the direction of potential energy decrease, search for potential seepage channels that may form in the water conservancy project area in three-dimensional space, perform iterative tracking of potential seepage channels, and generate potential seepage paths that reflect the possible direction of groundwater flow based on the tracked channel extension trajectory.

[0009] The spatial extension characteristics and changing trends of potential seepage paths are analyzed, and the corresponding channel risk level is assessed in conjunction with whether the potential seepage path crosses the preset key structural area.

[0010] Based on the comprehensive relationship between channel risk level and seepage data, a seepage risk index is generated to reflect the seepage status of the water conservancy project area, and the current seepage risk trend of the water conservancy project area is determined based on the seepage risk index.

[0011] Preferably, monitoring data is acquired in the water conservancy project area, seepage data is defined and extracted from the monitoring data, time synchronization and calibration processing is performed on the seepage data, and basic data for subsequent modeling is obtained based on the calibration processing, specifically including: The monitoring data includes seepage pressure monitoring data, seepage flow monitoring data, pore water pressure monitoring data, water temperature monitoring data, and deformation monitoring data in the water conservancy project area.

[0012] The definition of seepage data is a combined dataset based on seepage pressure, seepage flow rate, and pore water pressure, used to reflect the characteristics of groundwater flow activity. The seepage data includes seepage pressure data to represent the degree of water flow pressure, seepage flow rate data to represent the water flow capacity, and pore water pressure data to reflect the pressure changes inside the pores. Seepage data is extracted by filtering and classifying the monitoring data according to data type and spatial location.

[0013] The time synchronization involves aligning the acquisition cycle of the seepage data, correcting the timestamps, and correcting time deviations across devices; the calibration process involves performing noise removal, outlier identification, and sensor drift correction on the seepage data.

[0014] Preferably, a three-dimensional water flow potential energy model of the water conservancy project area is constructed based on basic data, specifically including: A three-dimensional water flow potential energy model is constructed using basic data. The calibrated seepage pressure data, seepage flow data, and pore water pressure data are mapped to the three-dimensional coordinate grid of the water conservancy project area according to their corresponding spatial locations. Based on the monitoring data of each grid node, a node potential energy value is formed to represent the water flow potential energy of the node. Based on the spatial difference relationship between the potential energy values ​​of each node, a three-dimensional potential energy distribution covering the dam body, dam foundation, and surrounding areas is generated.

[0015] Based on the three-dimensional potential energy distribution, and combined with the water flow activity trend reflected by the changes in seepage flow and pore water pressure, the change of potential energy over time is analyzed to obtain the potential energy change trend information reflecting the trend of water flow direction, thus forming a three-dimensional water flow potential energy model for identifying the spatial distribution and evolution characteristics of groundwater flow.

[0016] Preferably, the potential energy distribution and variation trend at different spatial locations are determined based on a three-dimensional water flow potential energy model, and the direction of potential energy decrease is determined based on the potential energy distribution and variation trend, specifically including: The potential energy values ​​of each grid node are collected and organized using a three-dimensional water flow potential energy model. Based on the spatial relationship between adjacent nodes in the three-dimensional coordinate grid, the known node potential energy values ​​are extrapolated to locations without monitoring points, thus obtaining potential energy distribution information for each spatial location covering the water conservancy project area. At the same time, the sequence of node potential energy values ​​at the same spatial location within a continuous time period is used as the analysis object to determine the direction and magnitude of potential energy change over time, forming potential energy change trend information to represent the current spatial location's water flow potential energy change trend.

[0017] Based on the potential energy distribution information and potential energy change trend information at different spatial locations, and taking the potential energy difference between adjacent spatial locations and the direction of potential energy change over time as the basis, when the potential energy value of the first spatial location is greater than the potential energy value of the adjacent second spatial location, the direction from the first spatial location to the second spatial location is determined as the corresponding water flow transmission direction. The water flow transmission directions corresponding to each pair of adjacent spatial locations are combined to obtain a direction field that represents the gradual decrease in potential energy direction within the water conservancy project area. The direction corresponding to each spatial location in the direction field is taken as the potential energy decreasing direction of the current spatial location.

[0018] Preferably, the search for potential seepage channels that may form in the hydraulic engineering area in three-dimensional space based on the direction of potential energy decrease includes: Using the spatial location in the water conservancy project area that is close to the upstream water source side, the reservoir water side, or where the seepage pressure has been above the preset seepage pressure threshold for a long time as the candidate starting position, starting from each candidate starting position, adjacent spatial locations are selected in the three-dimensional coordinate grid according to the corresponding potential energy decrease direction, and the spatial locations that are continuously connected along the potential energy decrease direction are formed into a spatial node sequence.

[0019] The geometric extension characteristics and potential energy change characteristics of the spatial node sequence are evaluated. When the extension distance of the spatial node sequence is not less than the preset path length threshold, the potential energy difference between adjacent spatial positions is not less than the preset potential energy difference threshold, and the angle between the potential energy decrease directions corresponding to each spatial position does not exceed the preset direction deviation threshold, the spatial node sequence is identified as a potential seepage channel.

[0020] The potential seepage channels obtained from different candidate starting positions are summarized to obtain a set of potential seepage channels for subsequent iterative tracking analysis.

[0021] Preferably, iterative tracing is performed on potential seepage channels, and a potential seepage path is generated based on the traced channel extension trajectory to reflect the possible direction of groundwater flow. Specifically, this includes: Each potential seepage channel in the potential seepage channel set is taken as the starting channel for tracking, and its end node is taken as the current tracking node. Based on the potential energy decrease direction corresponding to the current tracking node, adjacent candidate nodes are determined in the three-dimensional coordinate grid. From the candidate nodes, nodes that satisfy the potential energy difference value is not less than the preset tracking potential energy difference value threshold and the angle between the potential energy decrease direction of the current tracking node and the current tracking node does not exceed the preset tracking direction deviation threshold are selected, and the selected nodes are added to the node sequence of the current potential seepage channel. After a node is updated, the end of the updated node sequence is taken as the new current tracking node. The process of candidate node determination and node sequence update is repeated until the node sequence extension distance reaches the preset maximum tracking distance, or the potential energy difference between adjacent nodes is lower than the preset termination potential energy difference threshold, or the current tracking node falls into the preset boundary area. At this point, the iterative tracking of the corresponding potential seepage channel is terminated, and the channel extension trajectory corresponding to the potential seepage channel is obtained. The channel extension trajectories of different potential seepage channels are sorted and merged. Spatially continuous trajectory segments that are consistent in the direction of decreasing potential energy are connected into a complete trajectory. Geometric smoothing and back-turn segment removal are performed on the connected node sequence to generate potential seepage paths that represent the continuous direction of groundwater flow.

[0022] Preferably, the spatial extension characteristics and changing trends of potential seepage paths are analyzed, and the corresponding channel risk level is assessed based on whether the potential seepage path crosses a pre-defined key structural area. Specifically, this includes: Based on the starting and ending spatial locations of potential seepage paths and the sequence of spatial nodes traversed by the path, the path length, burial depth range, dominant extension direction, and length changes of newly added path segments within continuous monitoring periods are calculated to form path feature data that describes the spatial distribution morphology and temporal evolution characteristics of potential seepage paths.

[0023] In the three-dimensional coordinate grid of the water conservancy project, the water-facing side of the dam body, the area near the seepage prevention structure inside the dam body, the contact zone between the dam foundation and the bedrock, the area near the downstream slope toe of the dam, and the surrounding area recorded as weak points are marked as critical structural areas, and a set of critical structural areas is constructed.

[0024] The path feature data is overlaid with the spatial boundary of the set of key structural regions. When at least one spatial node in the spatial node sequence of a potential seepage path is located inside any key structural region, and the corresponding path length, burial depth range, or path length increment within a preset time window exceeds a preset risk threshold, the potential seepage path is marked as a risk channel. The risk channel is then classified according to the number of key structural regions traversed by the potential seepage path, the length of the corresponding path segment inside the key structural region, and the value of the path length increment, generating a channel risk level corresponding to the potential seepage path.

[0025] Preferably, based on the comprehensive relationship between the channel risk level and seepage data, a seepage risk index is generated to reflect the seepage status of the water conservancy project area, and the current seepage risk trend of the water conservancy project area is determined based on the seepage risk index, specifically including: Based on the risk level of the channel, a channel risk weight is assigned to each potential seepage path, and the weights are superimposed within the water conservancy project area according to the spatial range covered by the potential seepage path to obtain a channel risk distribution value that reflects the development degree of the seepage channel. Combined with the deviation and rate of change of seepage pressure, seepage flow and pore water pressure relative to the preset safety threshold during the continuous monitoring period, seepage anomaly indicators that characterize the degree of abnormality of seepage conditions are calculated. The channel risk distribution value and the seepage anomaly index are normalized and synthesized according to the preset weighting rules to obtain the leakage risk index with a value range of 0 to 1. The index is then divided into the first, second and third preset risk ranges, which correspond to the safe state, the attention state and the warning state, respectively. Based on the leakage risk index obtained from multiple monitoring periods, a risk index time series is constructed. Within a preset time window, the change range of the risk index is calculated and compared with a first change threshold and a second change threshold. Changes not greater than the first change threshold are judged as a stable trend, changes between the first and second change thresholds are judged as a slow deterioration trend, and changes greater than the second change threshold are judged as a rapid deterioration trend. The leakage risk index and the corresponding trend are output as the leakage status assessment results.

[0026] This application also provides a water conservancy project data monitoring system, including the following: The seepage data acquisition unit is used to acquire monitoring data in the water conservancy project area, define and extract seepage data from the monitoring data, perform time synchronization and calibration processing on the seepage data, and obtain basic data for subsequent modeling based on the calibration processing.

[0027] The water flow potential energy modeling unit is used to construct a three-dimensional water flow potential energy model of the water conservancy project area based on basic data. It determines the potential energy distribution and change trend at different spatial locations based on the three-dimensional water flow potential energy model, and determines the direction of potential energy decrease based on the potential energy distribution and change trend.

[0028] The potential seepage query unit is used to search for potential seepage channels that may form in the water conservancy project area in three-dimensional space according to the direction of potential energy decrease, perform iterative tracking of potential seepage channels, and generate potential seepage paths that reflect the possible direction of groundwater flow based on the tracked channel extension trajectory.

[0029] The trend analysis and prediction unit is used to analyze the spatial extension characteristics and changing trends of potential seepage paths, and to assess the corresponding channel risk level in combination with whether the potential seepage path crosses a preset key structural area.

[0030] The risk index calculation unit is used to generate a leakage risk index that reflects the leakage status of the water conservancy project area based on the comprehensive relationship between the channel risk level and seepage data, and to determine the current leakage risk trend of the water conservancy project area based on the leakage risk index.

[0031] The beneficial effects of this application are as follows: 1. By constructing a three-dimensional water flow potential energy model based on basic data, the potential energy distribution and change trend at different spatial locations are determined, and the direction of potential energy decrease is determined. Then, potential seepage channels are searched according to the direction of potential energy decrease, and iterative tracking is performed to generate potential seepage paths. This application infers the possible direction and extension trajectory of groundwater flow in underground areas where no monitoring points are set up by spatial analysis of the three-dimensional potential field and path evolution, thereby identifying the formation and penetration process of hidden seepage channels and providing a predictive basis for judging potential leakage directions in advance.

[0032] 2. By analyzing the spatial extension characteristics and changing trends of potential seepage paths, and combining whether the potential seepage paths cross the preset key structural areas, the risk level of the channels is assessed. Then, based on the comprehensive relationship between the channel risk level and seepage data, a leakage risk index is generated and the leakage risk trend is determined, thereby improving the ability to identify hidden seepage channels and their evolution process.

[0033] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1This is a flowchart of a water conservancy project data monitoring method provided in an embodiment of this application.

[0036] Figure 2 This application also provides an overall framework diagram of a water conservancy project data monitoring system.

[0037] Figure 3 This is a schematic diagram of the three-dimensional spatial structure of the water conservancy dam provided in this application. Detailed Implementation

[0038] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0039] Please see Figure 1 , Figure 1 This application provides a flowchart of a water conservancy project data monitoring method.

[0040] In this embodiment, a method for monitoring water conservancy project data includes steps S10, S20, S30, S40, and S50, as follows: Step S10: Obtain monitoring data in the water conservancy project area, define and extract seepage data from the monitoring data, perform time synchronization and calibration processing on the seepage data, and obtain basic data for subsequent modeling based on the calibration processing, specifically including: The monitoring data includes seepage pressure monitoring data, seepage flow monitoring data, pore water pressure monitoring data, water temperature monitoring data, and deformation monitoring data in the water conservancy project area.

[0041] The definition of seepage data is a combined dataset based on seepage pressure, seepage flow rate, and pore water pressure, used to reflect the characteristics of groundwater flow activity. The seepage data includes seepage pressure data to represent the degree of water flow pressure, seepage flow rate data to represent the water flow capacity, and pore water pressure data to reflect the pressure changes inside the pores. Seepage data is extracted by filtering and classifying the monitoring data according to data type and spatial location.

[0042] The time synchronization involves aligning the acquisition cycle of the seepage data, correcting the timestamps, and correcting time deviations across devices; the calibration process involves performing noise removal, outlier identification, and sensor drift correction on the seepage data.

[0043] It should be noted that in this embodiment, 40 to 80 seepage pressure monitoring points, 10 to 20 seepage flow meters, and 20 to 40 pore water pressure gauges are deployed within the dam body and foundation area. Each monitoring point records its three-dimensional spatial coordinates using a unified engineering coordinate system. The data acquisition cycle is set between 10 and 30 minutes. The data acquisition device organizes the seepage pressure, seepage flow, and pore water pressure monitoring data into a structured record format containing timestamps, spatial coordinates, data types, and monitoring values. To make the monitoring data structure clearer, this embodiment provides a typical data recording format to illustrate how seepage pressure, seepage flow, and pore water pressure monitoring data are recorded after unified structured organization. The data acquisition device organizes each monitoring record into a four-field structure based on timestamps, spatial coordinates, data types, and monitoring values. An example record format is as follows: [ { "timestamp": "2024-05-12 10:20:00", "position": {"x": 125.3, "y": -42.7, "z": -18.0}, "type": "piezometric_pressure", "value": 142.6 }, { "timestamp": "2024-05-12 10:20:00", "position": {"x": 126.1, "y": -40.9, "z": -15.2}, "type": "seepage_flow", "value": 3.12 }, { "timestamp": "2024-05-12 10:20:00", "position": {"x": 130.4, "y": -39.5, "z": -20.1}, "type": "pore_water_pressure", "value": 98.4 } ] Wherein, timestamp is the monitoring time after unified time synchronization; position is the three-dimensional spatial coordinate of the monitoring point in the engineering coordinate system; type is the monitoring data type identifier; value is the corresponding monitoring value; the above example is only used to illustrate the data record structure, and those skilled in the art can understand the organization format of the monitoring data before entering the synchronization calibration stage.

[0044] It should be noted that seepage data is logically defined as a combined recording unit consisting of three types of monitoring values: seepage pressure, seepage flow rate, and pore water pressure, under the same timestamp and spatial coordinates. When a single monitoring value is missing in the combined recording unit, it is completed by linear interpolation using the monitoring values ​​from two adjacent sampling times.

[0045] It should be noted that the time synchronization process uses a unified time series as a reference to correct the timestamps reported by different acquisition terminals, so that the error between the corrected timestamp and the reference time series does not exceed 1 second, and the sequences with deviations in the acquisition period are resampled according to the unified acquisition period.

[0046] It should be noted that the calibration process first employs a smoothing filter based on a sliding window of 5 sampling points to reduce high-frequency random noise. Then, using the data from the past 7 days as a reference statistical interval, the standard deviation of the monitoring value distribution is calculated. Monitoring values ​​with an absolute deviation exceeding 3 times the standard deviation within this interval are marked as outliers and removed. The average value of the monitoring values ​​of each sensor is calculated as the reference baseline during periods when the water level change rate does not exceed 0.05 m / h. If, during subsequent operation, the absolute deviation between the monitoring value of a certain sensor and the reference baseline continuously exceeds 5% of the reference baseline, the deviation is used as the sensor drift to correct the subsequent monitoring sequence of that sensor.

[0047] It should be noted that the above-mentioned principles for the layout of monitoring points, the data structure organization method, and the filtering, interpolation, outlier identification and drift correction processing are common knowledge in this field. Those skilled in the art can reproduce the results by engineering adjustments to the number of monitoring points, the collection cycle and threshold parameters according to the scale of the water conservancy project, geological conditions and the configuration of the monitoring system, and will not be elaborated further here.

[0048] Step S20: Construct a three-dimensional water flow potential energy model of the water conservancy project area based on the basic data. Determine the potential energy distribution and variation trend at different spatial locations based on the three-dimensional water flow potential energy model, and determine the direction of potential energy decrease based on the potential energy distribution and variation trend. Specifically, this includes: A three-dimensional water flow potential energy model is constructed using basic data. The calibrated seepage pressure data, seepage flow data, and pore water pressure data are mapped to the three-dimensional coordinate grid of the water conservancy project area according to their corresponding spatial locations. Based on the monitoring data of each grid node, a node potential energy value is formed to represent the water flow potential energy of the node. Based on the spatial difference relationship between the potential energy values ​​of each node, a three-dimensional potential energy distribution covering the dam body, dam foundation, and surrounding areas is generated.

[0049] It should be noted that, in this embodiment, for any grid node i, its nodal potential energy value The weighted hydraulic potential, characterized by osmotic pressure, pore water pressure, and seepage flow, can be specifically expressed as:

[0050] In the formula, The value of seepage pressure near this node is obtained by inverse distance weighted interpolation. This is the interpolation result of the pore water pressure monitoring values ​​near this node. This refers to the seepage flow monitoring value or interpolation result corresponding to this node. Let be the density of water, and g be the acceleration due to gravity. This is the reference seepage constant used for dimensionless processing. These are the weighting coefficients, and they satisfy... .

[0051] Those skilled in the art can determine the engineering focus based on the specific engineering priorities. The value of is adjusted in an engineering manner to construct a nodal potential energy value that matches the actual seepage conditions.

[0052] It should be noted that, in this embodiment, the three-dimensional coordinate grid uses the dam axis as the X-axis, the direction along the river as the Y-axis, and the vertical direction as the Z-axis. The step size of the grid cell in the X-axis and Y-axis directions is set to 5 to 10 meters, and the step size in the Z-axis direction is set to 2 to 5 meters. The boundary range of the water conservancy project area is determined by extending 200 to 500 meters on both sides of the dam axis, from the dam body to the normal water level, and from the dam body to the top surface of the bearing layer of the dam foundation. The node potential energy value is represented by the difference between the water head value of the monitoring point and its elevation. When there are multiple monitoring points near the grid node, the monitoring value is interpolated using an inverse distance weighting method. The interpolation weight index is set in the range of 1.5 to 3.0 to construct a continuous three-dimensional potential energy distribution field. The selection of the coordinate system, grid division, and interpolation method can be engineered by those skilled in the art according to the project scale and monitoring deployment density.

[0053] Based on the three-dimensional potential energy distribution, and combined with the water flow activity trend reflected by the changes in seepage flow and pore water pressure, the change of potential energy over time is analyzed to obtain the potential energy change trend information reflecting the trend of water flow direction, thus forming a three-dimensional water flow potential energy model for identifying the spatial distribution and evolution characteristics of groundwater flow.

[0054] It should be noted that in this embodiment, the potential energy change trend analysis uses monitoring data from 7 to 30 consecutive days as the time window. The node potential energy value of the same grid node at two adjacent sampling times is calculated by difference to obtain the potential energy change rate per unit time. The consistency is checked by combining the seepage flow change direction and the pore water pressure change direction at the corresponding time. For nodes whose potential energy change rate is completely opposite to the seepage flow change direction, the node is marked as an anomaly and its weight is reduced in the subsequent seepage channel search.

[0055] It should be noted that, in this embodiment, the potential energy change trend analysis uses monitoring data from 7 to 30 consecutive days as the time window, and analyzes the same grid node at two adjacent sampling times. and nodal potential value and Perform a difference calculation to determine the rate of change of potential energy. according to Perform the calculation.

[0056] For example, by substituting a set of data into the calculation, for a certain grid node, in Nodal potential energy value at time 1 It is 12.5 meters, in Nodal potential energy value at time 1 If the height is 13.1 meters, then the rate of change of potential energy over a 30-minute time interval is... for The value of the potential energy change rate can be used as a reference dimension to determine whether the water flow activity near the node is in an abnormal evolutionary state.

[0057] The potential energy values ​​of each grid node are collected and organized using a three-dimensional water flow potential energy model. Based on the spatial relationship between adjacent nodes in the three-dimensional coordinate grid, the known node potential energy values ​​are extrapolated to locations without monitoring points, thus obtaining potential energy distribution information for each spatial location covering the water conservancy project area. At the same time, the sequence of node potential energy values ​​at the same spatial location within a continuous time period is used as the analysis object to determine the direction and magnitude of potential energy change over time, forming potential energy change trend information to represent the current spatial location's water flow potential energy change trend.

[0058] It should be noted that for grid nodes without monitoring points, the estimation of node potential energy values ​​adopts a multi-point interpolation method based on 3 to 6 adjacent known nodes. During the interpolation process, if the spatial distance between any known node and the node to be estimated exceeds 50 meters, it will not participate in the interpolation calculation to avoid unreasonable influence of distant monitoring points on the local potential energy field. The change in potential energy over time is calculated by statistically analyzing the difference between the maximum and minimum values ​​of node potential energy values ​​over a continuous period and comparing it with the long-term average value of node potential energy values. When the change exceeds 10% of the long-term average value, the node is marked as a node sensitive to potential energy changes and is used as a key area of ​​focus in the subsequent seepage channel search phase.

[0059] Based on the potential energy distribution information and potential energy change trend information at different spatial locations, and taking the potential energy difference between adjacent spatial locations and the direction of potential energy change over time as the basis, when the potential energy value of the first spatial location is greater than the potential energy value of the adjacent second spatial location, the direction from the first spatial location to the second spatial location is determined as the corresponding water flow transmission direction. The water flow transmission directions corresponding to each pair of adjacent spatial locations are combined to obtain a direction field that represents the gradual decrease in potential energy direction within the water conservancy project area. The direction corresponding to each spatial location in the direction field is taken as the potential energy decreasing direction of the current spatial location.

[0060] It should be noted that when calculating the water flow transmission direction between adjacent spatial locations, if the difference between the potential energy value of the first spatial location and the potential energy value of the adjacent second spatial location is lower than the preset minimum potential energy difference threshold, a water flow transmission direction is not established in that direction to reduce the interference of numerical fluctuations on the direction field. After the direction field is constructed, the water flow transmission direction of the same spatial location in the three coordinate axes is normalized so that the potential energy decreasing direction corresponding to each spatial location is represented as a unit vector, which facilitates the subsequent search for seepage channels based on the direction field in three-dimensional space. Those skilled in the art can adjust the minimum potential energy difference threshold and the direction normalization method according to the project scale and monitoring accuracy. In this embodiment, the preset minimum potential energy difference threshold is determined comprehensively based on the range and accuracy of the seepage pressure sensor, the noise level of the monitoring data, and the statistical distribution of the potential energy difference at the nodes under typical working conditions. This ensures that the preset minimum potential energy difference threshold is higher than the normal range of measurement noise and data fluctuations, while being lower than the upper limit of head loss that can be ignored in engineering. This ensures that noise is filtered out while retaining sensitivity to potential energy gradients that are of engineering significance. In this embodiment, the preset minimum potential energy difference threshold is set to 0.05 meters of head. This value is greater than three times the standard deviation corresponding to the sensor measurement accuracy and the corresponding hydraulic gradient is insufficient to form a continuous and stable seepage driving force in the dam body and dam foundation materials, while taking into account both numerical stability and seepage identification sensitivity.

[0061] Step S30: Search for potential seepage channels that may form in the hydraulic engineering area in three-dimensional space according to the direction of potential energy decrease, perform iterative tracking of the potential seepage channels, and generate potential seepage paths to reflect the possible direction of groundwater flow based on the tracked channel extension trajectories. Specifically, this includes: Using the spatial location in the water conservancy project area that is close to the upstream water source side, the reservoir water side, or where the seepage pressure has been above the preset seepage pressure threshold for a long time as the candidate starting position, starting from each candidate starting position, adjacent spatial locations are selected in the three-dimensional coordinate grid according to the corresponding potential energy decrease direction, and the spatial locations that are continuously connected along the potential energy decrease direction are formed into a spatial node sequence.

[0062] It should be noted that the preset seepage pressure threshold is set by statistically analyzing seepage pressure monitoring data over a historical operating period of no less than one year, and using the sum of the long-term average value and twice the standard deviation as the threshold. In this embodiment, if the long-term average seepage pressure is 120 kPa and the standard deviation is 15 kPa, then the preset seepage pressure threshold is 150 kPa.

[0063] The geometric extension characteristics and potential energy change characteristics of the spatial node sequence are evaluated. When the extension distance of the spatial node sequence is not less than the preset path length threshold, the potential energy difference between adjacent spatial positions is not less than the preset potential energy difference threshold, and the angle between the potential energy decrease directions corresponding to each spatial position does not exceed the preset direction deviation threshold, the spatial node sequence is identified as a potential seepage channel.

[0064] It should be noted that the preset path length threshold is set by referring to the dam thickness and the layout range of the seepage prevention structure, so that the seepage path at least penetrates a part of the main seepage prevention structure. In this embodiment, the preset path length threshold is set to 20 meters.

[0065] It should be noted that the preset potential energy difference threshold is set by analyzing the range of head loss per unit step length under typical steady-state seepage conditions. In this embodiment, the minimum head difference between adjacent spatial locations is set to 0.10 meters.

[0066] It should be noted that the preset directional deviation threshold is set by taking into account the allowable deflection angle of groundwater flow in a heterogeneous medium. In this embodiment, the maximum included angle between the potential energy reduction directions corresponding to adjacent spatial positions is set to 30°.

[0067] The potential seepage channels obtained from different candidate starting positions are summarized to obtain a set of potential seepage channels for subsequent iterative tracking analysis.

[0068] Each potential seepage channel in the potential seepage channel set is taken as the starting channel for tracking, and its end node is taken as the current tracking node. Based on the potential energy decrease direction corresponding to the current tracking node, adjacent candidate nodes are determined in the three-dimensional coordinate grid. From the candidate nodes, nodes that satisfy the potential energy difference value is not less than the preset tracking potential energy difference value threshold and the angle between the potential energy decrease direction of the current tracking node and the current tracking node does not exceed the preset tracking direction deviation threshold are selected, and the selected nodes are added to the node sequence of the current potential seepage channel.

[0069] It should be noted that the preset tracking potential energy difference threshold is set by setting the lower limit requirement of the head gradient inside the potential seepage channel, so that the tracking process maintains a continuous and effective decrease in head. In this embodiment, the minimum head difference between adjacent nodes during the tracking process is set to 0.05 meters.

[0070] It should be noted that the preset tracking direction deviation threshold is appropriately relaxed relative to the initial channel search stage to allow the seepage channel to deflect to a certain extent in local heterogeneous areas. In this embodiment, the maximum direction deviation angle of the tracking stage is set to 45°.

[0071] After a node is updated, the end of the updated node sequence is taken as the new current tracking node. The process of candidate node determination and node sequence update is repeated until the node sequence extension distance reaches the preset maximum tracking distance, or the potential energy difference between adjacent nodes is lower than the preset termination potential energy difference threshold, or the current tracking node falls into the preset boundary area. At this point, the iterative tracking of the corresponding potential seepage channel is terminated, and the channel extension trajectory corresponding to the potential seepage channel is obtained.

[0072] It should be noted that the preset maximum tracking distance is determined by referring to the characteristic dimensions of the combined structure of the dam body and dam foundation in the valley direction and longitudinal direction. In this embodiment, the maximum tracking distance is set to 300 meters to cover the range of the medium-sized gravity dam body and dam foundation.

[0073] It should be noted that the preset termination potential energy difference threshold is used to determine whether the water head reduction process is basically dissipated. In this embodiment, the minimum water head difference between adjacent spatial locations is set to 0.02 meters. When the water head difference is lower than this threshold in multiple consecutive steps, it is determined that the seepage channel has entered the region of slow potential energy change.

[0074] It should be noted that the preset boundary area includes a buffer zone extending 10 meters outward from the rectangular boundary of the three-dimensional coordinate grid, a range of 5 meters outside the dam slope, and the space below the bearing layer of the dam foundation. If the current tracking node falls into any of the above boundary ranges, the iterative tracking of the corresponding channel will be terminated.

[0075] The channel extension trajectories of different potential seepage channels are sorted and merged. Spatially continuous trajectory segments that are consistent in the direction of decreasing potential energy are connected into a complete trajectory. Geometric smoothing and back-turn segment removal are performed on the connected node sequence to generate potential seepage paths that represent the continuous direction of groundwater flow.

[0076] It should be noted that the geometric smoothing process reduces the local jagged lines by using a moving average of the coordinates of 3 to 5 consecutive spatial nodes. The backsliding segment removal process detects the angle between two adjacent trajectory vectors. When the angle is greater than 150°, it is determined that there is a backsliding phenomenon and the intermediate nodes are deleted, thus obtaining a potential seepage path that is more continuous in shape and consistent with the actual flow direction of groundwater.

[0077] Step S40: Analyze the spatial extension characteristics and changing trends of potential seepage paths, and assess the corresponding channel risk level based on whether the potential seepage path crosses a pre-defined key structural area. Specifically, this includes: Based on the starting and ending spatial locations of potential seepage paths and the sequence of spatial nodes traversed by the path, the path length, burial depth range, dominant extension direction, and length changes of newly added path segments within continuous monitoring periods are calculated to form path feature data that describes the spatial distribution morphology and temporal evolution characteristics of potential seepage paths.

[0078] In the three-dimensional coordinate grid of the water conservancy project, the water-facing side of the dam body, the area near the seepage prevention structure inside the dam body, the contact zone between the dam foundation and the bedrock, the area near the downstream slope toe of the dam, and the surrounding area recorded as weak points are marked as critical structural areas, and a set of critical structural areas is constructed.

[0079] The path feature data is overlaid with the spatial boundary of the set of key structural regions. When at least one spatial node in the spatial node sequence of a potential seepage path is located inside any key structural region, and the corresponding path length, burial depth range, or path length increment within a preset time window exceeds a preset risk threshold, the potential seepage path is marked as a risk channel. The risk channel is then classified according to the number of key structural regions traversed by the potential seepage path, the length of the corresponding path segment inside the key structural region, and the value of the path length increment, generating a channel risk level corresponding to the potential seepage path.

[0080] It should be noted that the preset risk threshold is determined by statistical analysis of path length, burial depth range, and path length increment in historical safe operation phases and known leakage event samples. The 80th percentile of each indicator in the leakage event samples is used as the judgment boundary. In this embodiment, the path length threshold is set to 30 meters, the burial depth range threshold is set to no more than 5 meters from the inner surface of the water-facing side of the dam, and the path length increment threshold is set to 10 meters within 30 consecutive days. When any of the above indicators reaches or exceeds the corresponding threshold, it is considered that the preset risk threshold has been exceeded.

[0081] It should be noted that there are three risk levels for the seepage path: Level 1, Level 2, and Level 3. These levels are determined based on the number of critical structural areas traversed by the risk path, the proportion of path segments within critical structural areas to the total path length, and the number of indicators exceeding preset risk thresholds. Specifically, a potential seepage path is classified as Level 1 if it has only a short path segment within a single critical structural area and none of the indicators exceed the preset risk thresholds. A potential seepage path is classified as Level 2 if it has continuous path segments within one or two critical structural areas and at least one indicator exceeds the preset risk threshold. Finally, a potential seepage path is classified as Level 3 if it traverses two or more critical structural areas simultaneously, the proportion of path segments within critical structural areas to the total length is not less than 50%, and two or more indicators exceed the preset risk threshold.

[0082] Step S50: Based on the comprehensive relationship between the channel risk level and seepage data, generate a seepage risk index to reflect the seepage status of the water conservancy project area, and determine the current seepage risk trend of the water conservancy project area based on the seepage risk index, specifically including: Based on the risk level of the channel, a channel risk weight is assigned to each potential seepage path, and the weights are superimposed within the water conservancy project area according to the spatial range covered by the potential seepage path to obtain a channel risk distribution value that reflects the development degree of the seepage channel. Combined with the deviation and rate of change of seepage pressure, seepage flow, and pore water pressure relative to the preset safety threshold during the continuous monitoring period, seepage anomaly indicators characterizing the degree of abnormality of seepage conditions are calculated.

[0083] It should be noted that the preset safety threshold is determined by statistical analysis of monitoring data from at least one year of historical safe operation. Under the premise of meeting the allowable range of engineering design, the sum of the long-term average value of each monitoring quantity and twice the standard deviation is used as the upper limit control value. In this embodiment, the seepage pressure safety threshold corresponds to an equivalent water head of 160 kPa, the seepage flow safety threshold is set to 1.5 times the design seepage flow of the corresponding section, and the pore water pressure safety threshold is set to 0.8 times the equivalent pore water pressure of the formation self-weight stress.

[0084] It should be noted that the seepage anomaly index is set by normalizing the deviations of seepage pressure, seepage flow, and pore water pressure relative to their respective historical baseline values ​​and preset safety thresholds, and summing them according to weights. In this embodiment, the relative deviation values ​​and changes within 24 hours of the three types of monitoring quantities are calculated respectively. Monitoring quantities with relative deviation values ​​exceeding 10% and changes within 24 hours exceeding the corresponding safety threshold of 5% are recorded as significant anomalies. The number of significant anomalies and the degree of deviation are converted into dimensionless indices in the range of 0 to 1 according to preset weights, which are used as seepage anomaly indices.

[0085] The channel risk distribution value and the seepage anomaly index are normalized and synthesized according to the preset weighting rules to obtain a leakage risk index with a value range of 0 to 1. The index is then divided into the first, second and third preset risk ranges, which correspond to the safe state, the attention state and the warning state, respectively.

[0086] It should be noted that the channel risk distribution value refers to the scalar result obtained by superimposing the channel risk weights corresponding to all potential seepage paths passing through the spatial location in a three-dimensional coordinate grid. It is used to represent the degree of development of seepage channels in terms of quantity and intensity at that spatial location.

[0087] It should be noted that the first preset risk range is set by analyzing the statistical distribution of leakage risk index during historical safe operation phases. In this embodiment, the range of 0 to 0.30 is used as the first preset risk range, which corresponds to the leakage risk index being within the normal fluctuation range of the project.

[0088] It should be noted that the second preset risk range is set by statistically analyzing the distribution of leakage risk index under working conditions where there are records of minor leakage treatment but no structural damage. In this embodiment, the range of 0.30 to 0.60 is used as the second preset risk range, which corresponds to the state of concern that requires enhanced monitoring and analysis.

[0089] It should be noted that the third preset risk range is set by statistically analyzing the range of leakage risk indices in typical leakage incidents and known leakage accident cases. In this embodiment, the range of 0.60 to 1.00 is used as the third preset risk range, which corresponds to the early warning state where timely disposal measures are required.

[0090] Based on the leakage risk index obtained from multiple monitoring periods, a risk index time series is constructed. Within a preset time window, the change range of the risk index is calculated and compared with a first change threshold and a second change threshold. Changes not greater than the first change threshold are judged as a stable trend, changes between the first and second change thresholds are judged as a slow deterioration trend, and changes greater than the second change threshold are judged as a rapid deterioration trend. The leakage risk index and the corresponding trend are output as the leakage status assessment results.

[0091] It should be noted that the monitoring cycle is specifically 1 hour, that is, the leakage risk index is updated every 1 hour based on the latest monitoring data, and the leakage risk index within the past 24 hours or 72 hours is used for trend analysis.

[0092] It should be noted that the first preset change threshold is set by statistically analyzing the natural fluctuation range of the leakage risk index during the historical safe operation phase within a 24-hour time window. In this embodiment, the difference between the maximum and minimum values ​​of the leakage risk index within the same time window is 0.05, which is used as the first preset change threshold.

[0093] It should be noted that the second preset change threshold is set by statistically analyzing the range of increase of the leakage risk index within the same time window in typical leakage evolution cases. In this embodiment, the difference between the maximum and minimum values ​​of the leakage risk index within the same time window is 0.15, which is used to identify situations where leakage risk increases rapidly.

[0094] This completes a data monitoring method for water conservancy projects.

[0095] Additionally, please refer to Figure 2 , Figure 2 This application also provides a water conservancy project data monitoring system, comprising the following: The seepage data acquisition unit is used to acquire monitoring data in the water conservancy project area, define and extract seepage data from the monitoring data, perform time synchronization and calibration processing on the seepage data, and obtain basic data for subsequent modeling based on the calibration processing.

[0096] The water flow potential energy modeling unit is used to construct a three-dimensional water flow potential energy model of the water conservancy project area based on basic data. It determines the potential energy distribution and change trend at different spatial locations based on the three-dimensional water flow potential energy model, and determines the direction of potential energy decrease based on the potential energy distribution and change trend.

[0097] The potential seepage query unit is used to search for potential seepage channels that may form in the water conservancy project area in three-dimensional space according to the direction of potential energy decrease, perform iterative tracking of potential seepage channels, and generate potential seepage paths that reflect the possible direction of groundwater flow based on the tracked channel extension trajectory.

[0098] The trend analysis and prediction unit is used to analyze the spatial extension characteristics and changing trends of potential seepage paths, and to assess the corresponding channel risk level in combination with whether the potential seepage path crosses a preset key structural area.

[0099] The risk index calculation unit is used to generate a leakage risk index that reflects the leakage status of the water conservancy project area based on the comprehensive relationship between the channel risk level and seepage data, and to determine the current leakage risk trend of the water conservancy project area based on the leakage risk index.

[0100] Thus, a water conservancy project data monitoring system was completed.

[0101] Please also refer to Figure 3 ,exist Figure 3 In the middle, the left-hand area represents the upstream reservoir water space, presented as a three-dimensional block with a regular grid, used to indicate the three-dimensional monitoring coordinate area where the water body is located. Figure 3 The central part of the image represents the concrete gravity dam structure and its underlying foundation, also represented by a regular three-dimensional grid. This grid showcases the spatial discrete units within the structure and the layout of computational nodes used for monitoring and analysis. The upper part of the dam, the upstream side, and the foundation are all represented by grayscale blocks, reflecting the structural composition and spatial boundaries. Several curved lines composed of dashed lines are drawn inside the dam near the upstream side, extending from the upstream reservoir water side into the dam body. These lines represent potential seepage channels; the dashed form indicates that these channels are still in the potential formation stage, suggesting a seepage trend but no stable path has yet formed.

[0102] Multiple seepage path lines composed of solid lines are drawn within the dam body and foundation area, extending from the upstream side towards the downstream slope toe, with arrows at the ends of the paths to indicate the seepage direction. The solid lines represent potential seepage paths inferred through calculation or monitoring, providing a clear indication of the seepage direction. The right slope area is the downstream slope toe, a region with lower potential energy. The solid seepage path extends outward in this area and terminates with an arrow. Its structural form is represented by continuous planar grayscale, emphasizing the topographic outline of the slope toe. The overall graphic uses continuous grids, grayscale levels, and line shapes to display the three-dimensional potential field variation, expressing the spatial trend of potential energy gradually decreasing from upstream to downstream through curved surface shapes and line distribution.

[0103] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0104] Those skilled in the art will recognize that the algorithms or steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0105] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for monitoring water conservancy project data, characterized in that, Including the following: Acquire monitoring data in the water conservancy project area, define and extract seepage data from the monitoring data, perform time synchronization and calibration processing on the seepage data, and obtain basic data for subsequent modeling based on the calibration processing; Based on the basic data, a three-dimensional water flow potential energy model of the water conservancy project area is constructed. Based on the three-dimensional water flow potential energy model, the potential energy distribution and change trend at different spatial locations are determined, and the direction of potential energy decrease is determined based on the potential energy distribution and change trend. For any grid node i, its nodal potential energy value The weighted hydraulic potential, characterized by osmotic pressure, pore water pressure, and seepage flow, can be specifically expressed as: In the formula, The value of seepage pressure near this node is obtained by inverse distance weighted interpolation. This is the interpolation result of the pore water pressure monitoring values ​​near this node. This refers to the seepage flow monitoring value or interpolation result corresponding to this node. Let be the density of water, and g be the acceleration due to gravity. This is the reference seepage constant used for dimensionless processing. These are the weighting coefficients, and they satisfy... ; Based on the direction of potential energy decrease, search for potential seepage channels that may be formed in the water conservancy project area in three-dimensional space, perform iterative tracking of potential seepage channels, and generate potential seepage paths that reflect the possible direction of groundwater flow based on the channel extension trajectory obtained from the tracking. The spatial extension characteristics and changing trends of potential seepage paths are analyzed, and the corresponding channel risk level is assessed in combination with whether the potential seepage path crosses the preset key structural area. Based on the comprehensive relationship between channel risk level and seepage data, a seepage risk index is generated to reflect the seepage status of the water conservancy project area, and the current seepage risk trend of the water conservancy project area is determined based on the seepage risk index.

2. The water conservancy project data monitoring method as described in claim 1, characterized in that, Acquire monitoring data from the water conservancy project area, define and extract seepage data from the monitoring data, perform time synchronization and calibration processing on the seepage data, and obtain basic data for subsequent modeling based on the calibration processing, specifically including: The monitoring data includes seepage pressure monitoring data, seepage flow monitoring data, pore water pressure monitoring data, water temperature monitoring data, and deformation monitoring data in the water conservancy project area; The seepage data is defined as a combined dataset based on seepage pressure, seepage flow rate, and pore water pressure, used to reflect the characteristics of groundwater flow activity. The seepage data includes seepage pressure data to represent the degree of water flow pressure, seepage flow rate data to represent the water flow capacity, and pore water pressure data to reflect the pressure changes inside the pores. The seepage data is extracted by filtering and classifying the monitoring data according to data type and spatial location. The time synchronization involves aligning the acquisition cycle of the seepage data, correcting the timestamps, and correcting cross-device time deviations; the calibration process involves performing noise removal, outlier identification, and sensor drift correction on the seepage data.

3. The water conservancy project data monitoring method as described in claim 1, characterized in that, A three-dimensional water flow potential energy model of the water conservancy project area is constructed based on basic data, specifically including: A three-dimensional water flow potential energy model is constructed using basic data. The calibrated seepage pressure data, seepage flow data, and pore water pressure data are mapped to the three-dimensional coordinate grid of the water conservancy project area according to their corresponding spatial locations. Based on the monitoring data of each grid node, a node potential energy value is formed to represent the water flow potential energy of the node. Based on the spatial difference relationship between the potential energy values ​​of each node, a three-dimensional potential energy distribution covering the dam body, dam foundation, and surrounding areas is generated. Based on the three-dimensional potential energy distribution, and combined with the water flow activity trend reflected by the changes in seepage flow and pore water pressure, the change of potential energy over time is analyzed to obtain the potential energy change trend information reflecting the trend of water flow direction, thus forming a three-dimensional water flow potential energy model for identifying the spatial distribution and evolution characteristics of groundwater flow.

4. The water conservancy project data monitoring method as described in claim 3, characterized in that, Based on the three-dimensional water flow potential energy model, the potential energy distribution and variation trend at different spatial locations are determined, and the direction of potential energy decrease is determined based on the potential energy distribution and variation trend. Specifically, this includes: The potential energy values ​​of each grid node are collected and organized using a three-dimensional water flow potential energy model. Based on the spatial relationship between adjacent nodes in the three-dimensional coordinate grid, the known node potential energy values ​​are extrapolated to the location where no monitoring point is set, thus obtaining the potential energy distribution information of each spatial location covering the water conservancy project area. At the same time, the sequence of node potential energy values ​​at the same spatial location within a continuous time period is used as the analysis object to determine the direction and magnitude of potential energy change over time, forming potential energy change trend information to represent the current spatial location water flow potential energy change trend. Based on the potential energy distribution information and potential energy change trend information at different spatial locations, and taking the potential energy difference between adjacent spatial locations and the direction of potential energy change over time as the basis, when the potential energy value of the first spatial location is greater than the potential energy value of the adjacent second spatial location, the direction from the first spatial location to the second spatial location is determined as the corresponding water flow transmission direction. The water flow transmission directions corresponding to each pair of adjacent spatial locations are combined to obtain a direction field that represents the gradual decrease in potential energy direction within the water conservancy project area. The direction corresponding to each spatial location in the direction field is taken as the potential energy decreasing direction of the current spatial location.

5. The water conservancy project data monitoring method as described in claim 4, characterized in that, Based on the direction of potential energy decrease, potential seepage channels that may form in the hydraulic engineering area are searched in three-dimensional space, specifically including: Using the spatial location in the water conservancy project area that is close to the upstream water source side, the reservoir water side, or where the seepage pressure has been above the preset seepage pressure threshold for a long time as the candidate starting position, starting from each candidate starting position, adjacent spatial locations are selected in the three-dimensional coordinate grid according to the corresponding potential energy decrease direction, and the spatial locations that are continuously connected along the potential energy decrease direction are formed into a spatial node sequence. The geometric extension characteristics and potential energy change characteristics of the spatial node sequence are evaluated. When the extension distance of the spatial node sequence is not less than the preset path length threshold, the potential energy difference between adjacent spatial positions is not less than the preset potential energy difference threshold, and the angle between the potential energy decrease directions corresponding to each spatial position does not exceed the preset direction deviation threshold, the spatial node sequence is identified as a potential seepage channel. The potential seepage channels obtained from different candidate starting positions are summarized to obtain a set of potential seepage channels for subsequent iterative tracking analysis.

6. The water conservancy project data monitoring method as described in claim 5, characterized in that, Iterative tracing of potential seepage channels is performed, and a potential seepage path is generated based on the channel extension trajectory obtained from the tracing. This path reflects the possible direction of groundwater flow and includes: Each potential seepage channel in the potential seepage channel set is taken as the starting channel for tracking, and its end node is taken as the current tracking node. Based on the potential energy decrease direction corresponding to the current tracking node, adjacent candidate nodes are determined in the three-dimensional coordinate grid. From the candidate nodes, nodes that satisfy the potential energy difference value is not less than the preset tracking potential energy difference value threshold and the angle between the potential energy decrease direction of the current tracking node and the current tracking node does not exceed the preset tracking direction deviation threshold are selected, and the selected nodes are added to the node sequence of the current potential seepage channel. After a node is updated, the end of the updated node sequence is taken as the new current tracking node. The process of candidate node determination and node sequence update is repeated until the node sequence extension distance reaches the preset maximum tracking distance, or the potential energy difference between adjacent nodes is lower than the preset termination potential energy difference threshold, or the current tracking node falls into the preset boundary area. At this point, the iterative tracking of the corresponding potential seepage channel is terminated, and the channel extension trajectory corresponding to the potential seepage channel is obtained. The channel extension trajectories of different potential seepage channels are sorted and merged. Spatially continuous trajectory segments that are consistent in the direction of decreasing potential energy are connected into a complete trajectory. Geometric smoothing and back-turn segment removal are performed on the connected node sequence to generate potential seepage paths that represent the continuous direction of groundwater flow.

7. The water conservancy project data monitoring method as described in claim 6, characterized in that, The spatial extension characteristics and changing trends of potential seepage paths are analyzed, and the corresponding channel risk level is assessed based on whether the potential seepage path crosses a pre-defined key structural area. Specifically, this includes: Based on the starting and ending spatial locations of potential seepage paths and the sequence of spatial nodes traversed by the path, the path length, burial depth range, dominant extension direction, and length changes of newly added path segments within a continuous monitoring period are calculated to form path feature data that describes the spatial distribution morphology and temporal evolution characteristics of potential seepage paths. In the three-dimensional coordinate grid of the water conservancy project, the water-facing side of the dam body, the area near the seepage prevention structure inside the dam body, the contact zone between the dam foundation and the bedrock, the area near the downstream slope toe of the dam, and the surrounding area recorded as weak points are marked as critical structural areas, and a set of critical structural areas is constructed. The path feature data is overlaid with the spatial boundary of the set of key structural regions. When at least one spatial node in the spatial node sequence of a potential seepage path is located inside any key structural region, and the corresponding path length, burial depth range, or path length increment within a preset time window exceeds a preset risk threshold, the potential seepage path is marked as a risk channel. The risk channel is then classified according to the number of key structural regions traversed by the potential seepage path, the length of the corresponding path segment inside the key structural region, and the value of the path length increment, generating a channel risk level corresponding to the potential seepage path.

8. The water conservancy project data monitoring method as described in claim 1, characterized in that, Based on the comprehensive relationship between channel risk levels and seepage data, a seepage risk index is generated to reflect the seepage status of the water conservancy project area. The seepage risk trend of the current water conservancy project area is then determined based on the seepage risk index, specifically including: Based on the risk level of the channel, a channel risk weight is assigned to each potential seepage path, and the weights are superimposed within the water conservancy project area according to the spatial range covered by the potential seepage path to obtain a channel risk distribution value that reflects the development degree of the seepage channel. Combined with the deviation and rate of change of seepage pressure, seepage flow and pore water pressure relative to the preset safety threshold during the continuous monitoring period, seepage anomaly indicators that characterize the degree of abnormality of seepage conditions are calculated. The channel risk distribution value and the seepage anomaly index are normalized and synthesized according to the preset weighting rules to obtain the leakage risk index with a value range of 0 to 1. The index is then divided into the first, second and third preset risk ranges, which correspond to the safe state, the attention state and the warning state, respectively. Based on the leakage risk index obtained from multiple monitoring periods, a risk index time series is constructed. Within a preset time window, the change range of the risk index is calculated and compared with a first change threshold and a second change threshold. Changes not greater than the first change threshold are judged as a stable trend, changes between the first and second change thresholds are judged as a slow deterioration trend, and changes greater than the second change threshold are judged as a rapid deterioration trend. The leakage risk index and the corresponding trend are output as the leakage status assessment results.

9. A water conservancy project data monitoring system, characterized in that, Including the following: The seepage data acquisition unit is used to acquire monitoring data in the water conservancy project area, define and extract seepage data from the monitoring data, perform time synchronization and calibration processing on the seepage data, and obtain basic data for subsequent modeling based on the calibration processing. The water flow potential energy modeling unit is used to construct a three-dimensional water flow potential energy model of the water conservancy project area based on basic data, determine the potential energy distribution and change trend at different spatial locations based on the three-dimensional water flow potential energy model, and determine the direction of potential energy decrease based on the potential energy distribution and change trend. For any grid node i, its nodal potential energy value The weighted hydraulic potential, characterized by osmotic pressure, pore water pressure, and seepage flow, can be specifically expressed as: In the formula, The value of seepage pressure near this node is obtained by inverse distance weighted interpolation. This is the interpolation result of the pore water pressure monitoring values ​​near this node. This refers to the seepage flow monitoring value or interpolation result corresponding to this node. Let be the density of water, and g be the acceleration due to gravity. This is the reference seepage constant used for dimensionless processing. These are the weighting coefficients, and they satisfy... ; The potential seepage query unit is used to search for potential seepage channels that may be formed in the water conservancy project area in three-dimensional space according to the direction of potential energy reduction, perform iterative tracking of potential seepage channels, and generate potential seepage paths that reflect the possible direction of groundwater flow based on the tracked channel extension trajectory. The trend analysis and prediction unit is used to analyze the spatial extension characteristics and changing trends of potential seepage paths, and to assess the corresponding channel risk level in combination with whether the potential seepage path crosses a preset key structural area. The risk index calculation unit is used to generate a leakage risk index that reflects the leakage status of the water conservancy project area based on the comprehensive relationship between the channel risk level and seepage data, and to determine the current leakage risk trend of the water conservancy project area based on the leakage risk index.

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