A method for analyzing the stability of flood control dams

Abstract

The present invention belongs to the technical field of dam flood discharge stability monitoring, and discloses a flood control dam stability analysis method. The present invention performs adaptive segmentation based on the deviation of dam height, cross-sectional area and curvature radius, so that the structural characteristics of each segment have homogeneity. Compared with the equidistant division of the prior art, this method can independently divide high-risk curve sections into monitoring units, thereby improving the accuracy of risk positioning. The present invention obtains the appropriate flood discharge rate by matching historical safe flood discharge cases, and performs dynamic correction based on upstream flood discharge data and the proportion of silt accumulation cross-sectional area, automatically adjusts the flood discharge rate and performs upper limit control in combination with the gate flood discharge capacity. This strategy can adapt to different water inflow conditions and dam body conditions, avoid dam body overload due to improper rate control, and improve the safety and flexibility of flood discharge scheduling.

Description

Technical Field

[0001] The invention belongs to the technical field of dam flood discharge stability monitoring and relates to a flood control dam stability analysis method. Background Art

[0002] Flood control dams, as key hydraulic engineering structures for resisting flooding, are designed to intercept and channel floodwaters, protecting cities, farmland, infrastructure, and the safety of life and property within the basin. The structural stability of dams directly determines the reliability of flood control systems. Especially during flood season, dams must withstand the lateral and seepage pressures of floodwaters, as well as the impact of water flow during discharge. Any structural defects or degradation in stability could lead to catastrophic consequences such as dam failure.

[0003] Flood discharge is a critical step in flood control and scheduling. When the upstream water level exceeds the warning value, the flood discharge rate must be controlled through gates. However, the hydrodynamic loads on the dam will fluctuate dramatically during the flood discharge process. Factors such as instantaneous fluctuations in seepage pressure, the scouring effect of water on the dam body, and silt accumulation can exacerbate potential stability risks of the dam body. If the flood discharge rate is not properly controlled, it may not only cause overload on the dam structure but also trigger downstream flooding risks. Therefore, real-time monitoring of dam stability during flood discharge and dynamic adjustment of flood discharge strategies are important prerequisites for ensuring safe and efficient flood control and scheduling.

[0004] There are also technical solutions for analyzing the stability of flood control dams in the existing technology. For example, a Chinese invention patent with announcement number CN111382526B is a method for analyzing dam seepage by identifying anti-seepage section types and coupling monitoring data. The method includes: first, classifying and coding the seepage section types of earth-rock dams; second, programming calculation formulas for various sections based on the seepage calculation analytical method; then analyzing the seepage pressure monitoring point data, collecting graphic files to generate generalized sections; then assigning input parameters, calculating the seepage results and correcting them with big data adjustment coefficients; finally, coupling the analytical calculation data and monitoring data to generate analysis results and judge the seepage stability of the dam.

[0005] Another Chinese invention patent application, publication number CN119476063A, relates to a method for predicting the stability of dam projects during flood season using a multi-model joint decision-making approach. This method involves: establishing a numerical model by acquiring dam parameters and solving for safety factors; optimizing three single machine learning models using an improved gray wolf algorithm, combining judgment indicators and safety factor training to obtain the optimal model; utilizing DS evidence theory to perform decision-level fusion of the optimal models to construct a high-precision prediction model; and finally, calculating the safety factor using the prediction model and comparing it with the allowable value to assess dam stability. This method integrates the advantages of multiple models, significantly improving prediction accuracy and reliability.

[0006] Although the above two schemes have proposed some solutions for the stability analysis of flood control dams, they still have certain limitations. For example: 1. Traditional methods mostly divide the dam into sections based on experience or fixed spacing, and do not fully consider the spatial differences in geometric parameters such as dam height, cross-sectional area and waterway curvature. As a result, the risk monitoring units do not match the actual structural characteristics, making it difficult to accurately locate high-risk areas.

[0007] 2. Existing technologies often focus solely on single indicators such as damage area or depth, lacking comprehensive analysis of multi-dimensional parameters such as damage extent and spatial concentration, and thus fail to fully reflect the foundation stability risk status of the dam. Traditional seepage monitoring relies on single-point sensors, which cannot capture the distribution and changes of pore water pressure within the dam in real time, making it difficult to provide timely warnings of instantaneous stability risks under dynamic conditions such as flood discharge.

[0008] 3. The existing flood discharge rate settings are mostly based on historical experience values, and are not dynamically corrected based on real-time monitoring of the dam's risk status and upstream water conditions, which may lead to a mismatch between the flood discharge plan and actual working conditions. Summary of the Invention

[0009] In view of this, in order to solve the problems raised in the above background technology, a flood control dam stability analysis method is proposed.

[0010] The purpose of the present invention can be achieved through the following technical solutions: a flood control dam stability analysis method, including: autonomous division of dam sections, using a three-dimensional laser scanning device to construct a three-dimensional contour model of the dam containing a collective structure, obtaining the dam height, dam cross-sectional area and waterway axis curvature radius to adaptively divide the dam sections, and generate corresponding risk monitoring levels.

[0011] Foundation stability risk assessment: Based on the three-dimensional contour model of the dam, a dam damage evaluation collection including effective damage area, effective damage degree and damage concentration is constructed. The foundation stability risk index is output by the pre-constructed damage risk model input based on the actual service life of the dam.

[0012] Instantaneous stability risk assessment uses a distributed fiber optic seepage pressure sensor network to monitor the pore water pressure data in the dam body in real time. Based on the real-time pore water pressure data, the seepage water level and effective pore pressure are identified to generate an instantaneous stability risk index.

[0013] Dynamic flood discharge risk setting, calculation of the comprehensive risk index of the dam, analysis of the appropriate flood discharge rate based on historical flood discharge cases, real-time acquisition of upstream flood discharge data and silt accumulation data, and dynamic correction of the appropriate flood discharge rate based on the gate flood discharge capacity.

[0014] Compared with the existing technology, the present invention has the following beneficial effects: (1) The present invention performs adaptive segmentation based on the deviation of dam height, cross-sectional area and curvature radius, making the structural characteristics of each segment homogeneous. Compared with the equidistant segmentation of the existing technology, this method can independently divide high-risk curve sections into monitoring units, thereby improving the accuracy of risk location.

[0015] (2) The damage assessment dataset constructed by the present invention comprehensively considers the effective damage area, damage degree, and damage aggregation, and comprehensively reflects the deterioration status of the dam body through multi-dimensional calculations. This avoids ignoring the synergistic destructive effect of clustered damage due to a single indicator, making the risk assessment results closer to actual working conditions.

[0016] (3) This method uses real-time distributed monitoring of pore water pressure within the dam body, calculates the seepage water level and effective pore pressure using a pressure-water level correlation formula, and uses the maximum value of each monitoring profile as the basis for risk assessment. This method can capture transient changes in water pressure during flood discharge in real time, effectively resolving monitoring lags.

[0017] (4) The present invention obtains the appropriate flood discharge rate by matching historical safe flood discharge cases, and dynamically corrects it based on upstream flood discharge data and the proportion of silt accumulation cross-sectional area. It automatically adjusts the flood discharge rate and implements upper limit control based on the gate flood discharge capacity. This strategy can adapt to different water conditions and dam conditions, avoid dam overload caused by improper rate control, and improve the safety and flexibility of flood discharge scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 Schematic diagram of the implementation of the method steps of the present invention.

[0020] Figure 2 A schematic diagram of the process of constructing a dam damage assessment collection corresponding to an embodiment provided by the present invention.

[0021] Figure 3 A schematic diagram of the mileage for constructing a damage risk model corresponding to an embodiment provided by the present invention. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] See also Figure 1 As shown, the present invention provides a flood control dam stability analysis method, including: autonomous division of dam sections, construction of a three-dimensional contour model of the dam containing a collective structure using a three-dimensional laser scanning device, acquisition of dam height, dam body cross-sectional area and waterway axis curvature radius to adaptively divide the dam sections, and generation of corresponding risk monitoring levels.

[0024] It's important to note that dam height, dam cross-sectional area, and the radius of curvature of the waterway axis are used as the basis for adaptive dam segmentation: these three parameters are key structural characteristics of dams. Dam height affects flood loads, cross-sectional area reflects the structural bearing capacity, and the radius of curvature reflects the risk of scour. The spatial differences in these three parameters directly determine the stress state and damage pattern of each dam segment. Using these deviations as the basis for zoning can homogenize the structural characteristics of the segmented segments, accurately identifying high-risk areas, such as curved sections with large curvatures, and thus improving the targeted and effective risk monitoring.

[0025] In a preferred embodiment of the present invention, the adaptive division of the dam sections is performed as follows: the dam height, the dam cross-sectional area and the curvature radius of the waterway axis corresponding to each position point in the waterway axis are extracted.

[0026] The dam height deviation, dam cross-sectional area deviation and waterway axis curvature radius deviation corresponding to each position point and the adjacent position points are obtained, and then compared with the pre-set thresholds respectively.

[0027] It should be noted that the pre-set thresholds are determined based on the allowable parameter deviations in the water conservancy project design specifications, the correlation between parameter deviations and damage in historical damage cases of similar dams, the critical stress state of the dam body simulated by finite element analysis, and the empirical judgment of water conservancy experts on weak links, to ensure that the zoning meets safety requirements and fits the actual project.

[0028] Merge adjacent position points until the following partitioning conditions are met: Condition 1: Any one of the dam height deviation, dam cross-sectional area deviation, and waterway axis curvature radius deviation is greater than the corresponding threshold.

[0029] Condition 2: The axis length of the merged location points is greater than the preset maximum length of the embankment section.

[0030] It should be noted that condition 1 uses parameter deviation as the trigger point. When the deviation of dam height, cross-sectional area or curvature radius exceeds the threshold, it indicates that the stress state or damage mode of adjacent sections may be different, and independent zoning is required for accurate monitoring. Condition 2 controls the upper limit of the section axis length to avoid the ambiguity of risk characteristics due to excessively long zoning, ensuring that each section has both structural homogeneity and monitoring operability. The combination of the two realizes the unity of scientific and practical section division.

[0031] Output several continuous pre-divided dam sections, obtain the axial length of each pre-divided dam section, and then compare it with the preset minimum length of the dam section. If any preset dam section has a length less than the preset minimum length of the dam section, merge it into the adjacent dam section with a smaller length, and finally generate several dam sections.

[0032] It should be explained that if the length of a pre-divided section is less than the minimum value, it means that its spatial scale is too small. Monitoring it alone will increase costs and lack practical significance. Therefore, it will be merged into adjacent sections with smaller lengths to avoid segment fragmentation and ensure that the final divided sections have both structural homogeneity and meet the practical scale requirements of engineering monitoring.

[0033] In a preferred embodiment of the present invention, the specific method of generating the corresponding risk monitoring level is as follows: the dam height, dam body cross-sectional area and water channel axis curvature radius of each position point in each dam section are compared respectively, and the minimum dam height, minimum dam body cross-sectional area and minimum water channel axis curvature radius are selected as the effective dam height, effective dam body cross-sectional area and effective water channel axis curvature radius of the corresponding dam section.

[0034] It's important to explain that the minimum dam height, minimum cross-sectional area, and minimum radius of curvature were chosen because they represent the weakest height for flood control, the minimum structural load-bearing capacity, and the point of greatest scour risk within the section, respectively. Using these extreme values ​​as valid parameters ensures that the section's risk assessment is based on the most unfavorable conditions, accurately pinpointing weak links and providing a reliable basis for risk classification.

[0035] The effective dam height, effective dam body cross-sectional area and effective waterway axis curvature radius of each dam section are compared with pre-set thresholds respectively.

[0036] It should be noted that the thresholds are pre-set critical parameter values ​​used to determine the risk level of dam sections. Specifically, they include thresholds for effective dam height, effective dam cross-sectional area, and effective waterway axis curvature radius. These thresholds are based on the safe allowable ranges of parameters in hydraulic engineering design specifications, the correlation between parameter deviations and risks in historical damage data for similar dams, the critical stress states of the dam body derived from finite element analysis, and the empirical judgment of hydraulic experts on weak links in dams, to ensure a scientific and rational risk assessment for each dam section.

[0037] When any parameter exceeds the corresponding threshold, one point is accumulated and the basic risk quantitative score of each embankment section is calculated. The quantitative score is any one of 0-3 points, and the parameter is any one of the effective dam height, effective dam cross-sectional area and effective waterway axis curvature radius.

[0038] Specifically, if the effective dam height is less than the effective dam height threshold, one point will be accumulated; if the effective dam body cross-sectional area is less than the effective dam body cross-sectional area threshold, one point will be accumulated; if the effective waterway axis curvature radius is less than the effective waterway axis curvature radius threshold, one point will be accumulated.

[0039] The corresponding risk monitoring levels based on the basic risk quantification scores of each dam section are divided into level one, level two, level three and no risk.

[0040] Specifically, if the basic risk quantification score is 0, the risk monitoring level is determined to be no risk; if the basic risk quantification score is 1, the risk monitoring level is determined to be level three; if the basic risk quantification score is 2, the risk monitoring level is determined to be level two; if the basic risk quantification score is 3, the risk monitoring level is determined to be level one.

[0041] It should be noted that the risk monitoring level of the dam section can be identified and divided into different levels according to the basic risk quantitative score, so as to facilitate the targeted strengthening of the monitoring frequency and intensity of the first, second and third level high-risk sections, and moderately reduce the monitoring resource input for the risk-free sections, so as to achieve scientific allocation of monitoring resources, accurately control the safety status of the dam, and improve risk warning and management efficiency.

[0042] Foundation stability risk assessment: Based on the three-dimensional contour model of the dam, a dam damage evaluation collection including effective damage area, effective damage degree and damage concentration is constructed. The foundation stability risk index is output by the pre-constructed damage risk model input based on the actual service life of the dam.

[0043] It should be noted that the effective damage area, effective damage degree, and damage concentration were selected as construction factors because the effective damage area quantifies the damage range, the effective damage degree reflects the impact of structural volume loss on bearing capacity, and the damage concentration characterizes the synergistic destructive effect of the spatial distribution of damage. These three factors comprehensively cover the key characteristics of dam damage from the dimensions of planar extent, depth impact, and spatial correlation, accurately depicting the comprehensive impact of damage on embankment stability and providing multi-dimensional data support for basic risk assessment.

[0044] In a preferred embodiment of the present invention, please refer to Figure 2 As shown, the specific construction method of the dam damage evaluation collection is as follows: A1. Surface contour data of each dam section is obtained from the dam three-dimensional contour model, and the planning contour data of the corresponding dam body is simultaneously obtained.

[0045] A2. Calculate the displacement distance of each dam surface point compared to the time when the dam was put into use, compare the displacement distance with a preset displacement distance threshold, and record the dam surface point with a displacement distance greater than the preset displacement distance threshold as a damage point.

[0046] It should be noted that the preset displacement distance threshold is determined based on the mechanical properties of the dam material, the safety limit of structural displacement in the design specifications, the correlation between displacement and damage in the historical monitoring data of similar dams, and the critical point of finite element simulation displacement, to ensure that displacement anomalies affecting the stability of the dam can be identified in a timely manner.

[0047] A3. Classify adjacent damage points to obtain several damage point sets, which constitute several damage areas.

[0048] A31. Obtain the area of ​​each damaged area and perform cumulative calculation to obtain the effective damaged area of ​​each embankment section.

[0049] A32. Based on the three-dimensional contour model of the dam, the volume reduction of the existing contour corresponding to each damaged area compared with the corresponding contour in the planned contour data is obtained. The volume reduction of each damaged area is accumulated to obtain the total damaged volume of each dam section, and the effective damage degree of each dam section is calculated by proportion calculation with the planned volume of the corresponding section in the planned contour data.

[0050] A33. Obtain the regional center point of each damaged area, obtain the distance between the regional center point of each damaged area and the regional center points of other damaged areas, use it as the monitoring interval of the corresponding damaged area group, calculate the ratio with the dam height of the corresponding embankment section to obtain the aggregation degree of each damaged area group, and calculate the average of the aggregation degree of each damaged area group to obtain the damage aggregation degree of each embankment section.

[0051] In a preferred embodiment of the present invention, please refer to Figure 3 As shown, the specific construction method of the damage risk model is as follows: B1. Clearly take the effective damage area, effective damage degree, damage concentration, and actual service life of the dam as input variables, and the basic stability risk index as output variable.

[0052] B2. Through historical monitoring data, inspection reports, and operation and maintenance records, collect the damage area, damage degree, damage spatial distribution density, and corresponding foundation stability risk index of different dams at different service years. The foundation stability risk index is calibrated by combining historical accidents or expert evaluation.

[0053] B3. Normalize or dimensionlessly process each input variable to eliminate the impact of dimensional differences.

[0054] B4. Use multiple regression analysis to fit the mapping relationship between input variables and risk index, and give priority to model structures whose fit has been verified by historical data and whose generalization error meets the standard.

[0055] B5. Use cross-validation to adjust model parameters and verify prediction accuracy through independent test data sets to ensure that the error in risk index output is within a controllable range.

[0056] B6. Encapsulate the model algorithm under the optimal parameters to form a damage risk model that can input four variables and directly output the basic stability risk index.

[0057] Instantaneous stability risk assessment uses a distributed fiber optic seepage pressure sensor network to monitor the pore water pressure data in the dam body in real time. Based on the real-time pore water pressure data, the seepage water level and effective pore pressure are identified to generate an instantaneous stability risk index.

[0058] It's important to explain that after analyzing foundation stability risk, transient stability risk still needs to be analyzed, as the two focus on different dimensions: foundation stability risk focuses on static degradation conditions such as material aging and damage accumulation during the long-term operation of the dam, assessing structural risk based on historical damage data and service life; whereas transient stability risk emphasizes the impact of transient loads such as sudden changes in seepage pressure within the dam under dynamic conditions, capturing the risk of sudden seepage damage through real-time pore water pressure data. Combining these two approaches comprehensively covers dam stability risk scenarios from both the long-term cumulative damage and transient dynamic load dimensions, avoiding the omission of sudden risks due to single-dimensional assessments and providing a more accurate risk basis for emergency decisions such as flood discharge scheduling.

[0059] In a preferred embodiment of the present invention, the specific calculation method of the seepage water level and the effective pore pressure is as follows: the dam body of each dam section is divided into several vertical monitoring sections along the axial direction of the waterway, and each vertical monitoring section has several fiber optic seepage pressure sensors, and each fiber optic seepage pressure sensor exists in a different depth layer.

[0060] The pore water pressure data in the dam body are monitored in real time based on the distributed optical fiber seepage pressure sensor network to obtain the pore water pressure of each depth layer in each vertical monitoring section. The monitored seepage water level height corresponding to each depth layer in each vertical monitoring section is calculated based on the pressure-water level correlation formula.

[0061] In a preferred embodiment, the specific formula for calculating the monitored seepage water level height corresponding to each depth layer of each vertical monitoring section is: ,in Indicates the monitoring seepage water level height corresponding to each depth layer, Indicates the datum elevation, represents the pore water pressure corresponding to each depth layer, is the water density, is the acceleration of gravity, and the pore water pressure corresponding to each depth layer is obtained by averaging the pore water pressure data monitored by the optical fiber seepage pressure sensor network at each depth layer.

[0062] It should be explained that the datum elevation This is the elevation of a fixed, artificially selected reference level. It is used to convert pore water pressure measured by pressure sensors into a uniform seepage water level in an absolute or relative elevation system. Its core function is to establish a correlation benchmark between pressure, water level, and dam structure. It can be obtained from authoritative elevation data such as hydrological stations, surveying and mapping control points, and existing dams and sluice gates around the dam.

[0063] The maximum value of the monitored seepage water level corresponding to each depth layer of each vertical monitoring section is taken as the seepage water level height of the dam section.

[0064] It's important to explain that using the maximum monitored seepage water level at each depth level across each vertical monitoring profile as the section's seepage water level is a risk assessment based on the principle of the most unfavorable operating condition. Since dam failure due to seepage is often triggered by the highest local water level, taking the maximum value at each depth level across each profile accurately captures the most dangerous seepage water level within the section, avoiding the masking of local high-risk points due to averaging. This provides key parameters that reflect the actual damage threshold for instantaneous stability risk assessment, ensuring the reliability of risk warnings.

[0065] The static water level pressure is calculated based on the static water level elevation outside the dam using the pressure-water level correlation formula. The effective pore water pressure at each depth layer of each vertical monitoring section is obtained by calculating the difference between the pore water pressure at each depth layer of each vertical monitoring section and the static water level pressure.

[0066] In a preferred embodiment, the specific calculation formula for the effective pore water pressure of each depth layer in each vertical monitoring section is: ,in represents the effective pore water pressure at each depth layer, represents the pore water pressure corresponding to each depth layer, represents the hydrostatic pressure corresponding to each depth layer, , Indicates the static water level elevation outside the dam corresponding to each depth layer.

[0067] The maximum value of the effective pore water pressure of each depth layer in each vertical monitoring section is taken as the effective pore water pressure of the dam section.

[0068] It should be explained that using the maximum effective pore water pressure at each depth level in each vertical monitoring profile as the effective pore pressure for the section is based on the localized characteristics of seepage damage. Effective pore pressure is the direct driving force behind seepage damage such as piping and soil flow, and the formation of seepage channels within the dam body often begins in areas of localized high pressure. Taking the maximum value at each depth level in each profile can accurately locate the areas with the most significant seepage damage risk within the section, avoiding underestimation of localized high risks due to average pressure values. This provides the most threatening dynamic parameters for transient stability assessments, ensuring that risk warnings target actual critical failure points and improving the accuracy and reliability of assessments.

[0069] It should be noted that the calculation of seepage water levels and effective pore pressure is intended to assess transient stability risks through real-time monitoring of the dam's internal seepage conditions. The maximum seepage water level across each monitoring profile represents the dam's most dangerous seepage level. The maximum effective pore pressure, after deducting the baseline value from the hydrostatic pressure, reflects the dominant driving force of seepage damage. Together, these two factors generate a transient stability risk index and provide accurate data support for emergency decisions such as flood discharge scheduling.

[0070] In a preferred embodiment of the present invention, the specific analysis method of the instantaneous stability risk index is as follows: the seepage water level and the effective pore pressure are compared with the preset maximum water level and effective pore pressure threshold allowed by the anti-seepage design.

[0071] Based on the comparison results, the seepage water level and effective pore pressure are divided into low risk, medium risk and high risk respectively.

[0072] Specifically, if the above parameter is less than or equal to 0.3 times the corresponding threshold, it is identified as low risk; if it is greater than 0.3 times the corresponding threshold and less than or equal to 0.6 times, it is identified as medium-low risk; if it is greater than 0.6 times the corresponding threshold, it is identified as high risk.

[0073] The low risk, medium risk and high risk are respectively assigned different risk values, and the instantaneous stability risk index of each dam section is obtained by matching and summing.

[0074] Preferably, the low risk, medium risk and high risk are assigned values ​​of 0.1, 0.3 and 0.5 respectively.

[0075] Dynamic flood discharge risk setting, calculation of the comprehensive risk index of the dam, analysis of the appropriate flood discharge rate based on historical flood discharge cases, real-time acquisition of upstream flood discharge data and silt accumulation data, and dynamic correction of the appropriate flood discharge rate based on the gate flood discharge capacity.

[0076] In a preferred embodiment of the present invention, the specific method of calculating the comprehensive risk index of the dam is as follows: the basic stability risk index and the instantaneous stability risk index of each dam section are weighted and fused to obtain the comprehensive risk index of each dam section.

[0077] It should be noted that when setting these weights based on historical data experiments, data on the foundation stability and transient stability risks of similar dams under different operating conditions, as well as corresponding accident records, were first collected to determine the proportion of the foundation risk index and transient risk index to dam instability. Simulations were performed using multiple weight combinations, and the calculated comprehensive risk index was compared with the actual accident risk level. The weight parameters were optimized using cross-validation, and the final weights were determined with the goal of minimizing error, ensuring that the weight settings conform to historical patterns and accurately reflect the actual impact of the risks.

[0078] The comprehensive risk index of each dam section is compared, and the maximum value is selected as the comprehensive risk index of the current dam.

[0079] In a preferred embodiment of the present invention, the specific method for identifying the appropriate flood discharge rate is: through a large number of pre-saved historical safe flood discharge cases, the flood discharge rate and comprehensive risk index corresponding to each case are extracted.

[0080] The comprehensive risk index of the current dam is matched with the comprehensive risk index of each case to obtain several successful matching cases.

[0081] The flood discharge rates corresponding to the successfully matched cases are averaged to obtain the appropriate flood discharge rate for the current flood discharge.

[0082] In a preferred embodiment of the present invention, the specific method of dynamically correcting the appropriate flood discharge rate is as follows: extract upstream flood discharge data and silt accumulation data, and calculate the mean of the flood discharge rate and the silt accumulation cross-sectional area ratio in a continuous time window to obtain the monitored flood discharge rate and the monitored silt accumulation cross-sectional area ratio.

[0083] The monitored flood discharge rate and the monitored silt accumulation cross-sectional area ratio are compared with the preset flood discharge rate reference value and the silt accumulation cross-sectional area reference value respectively.

[0084] If any parameter of the monitored flood discharge rate and the monitored silt accumulation cross-sectional area ratio is greater than the corresponding reference value, and the appropriate flood discharge rate is less than the corresponding value of the gate flood discharge capacity, the appropriate flood discharge rate will be increased by a preset unit.

[0085] It should be noted that when the monitored flood discharge rate or the proportion of silt accumulation cross-sectional area exceeds the corresponding reference value, and the current appropriate flood discharge rate is less than the gate's flood discharge capacity, it indicates that the existing flood discharge rate is not fully utilizing the gate's effectiveness and may lead to increased silt accumulation or low flood discharge efficiency due to insufficient rate. In this case, increasing the appropriate flood discharge rate by a preset unit can improve flood discharge efficiency within the gate's carrying capacity and alleviate silt accumulation pressure. At the same time, through dynamic adjustment, the flood discharge rate is matched to the current operating conditions of the dam, achieving a balance between safe flood discharge and optimized efficiency.

[0086] It should be noted that the preset units are set based on the adjustment accuracy of the gate equipment, the quantitative relationship between rate adjustment and seepage risk in flood discharge experiments of similar dams, and the impact amplitude of the unit rate increment on the impact load of the dam body in fluid mechanics simulation, to ensure that the unit adjustment can effectively improve the flood discharge efficiency without causing additional safety risks.

[0087] When the appropriate flood discharge rate is equal to the corresponding value of the gate's flood discharge capacity, the flood discharge rate is maintained at the corresponding value of the gate's flood discharge capacity, a danger alarm is issued and reported to the administrator.

[0088] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A flood control dam stability analysis method, characterized in that: include: The dam is divided into sections autonomously. A 3D laser scanning device is used to construct a 3D contour model of the dam including a collective structure. The dam height, dam cross-sectional area, and waterway axis curvature radius are obtained to adaptively divide the dam into sections and generate corresponding risk monitoring levels. Foundation stability risk assessment: Based on the 3D contour model of the dam, a dam damage evaluation set is constructed, including the effective damage area, effective damage degree, and damage concentration. The foundation stability risk index is output by the pre-constructed damage risk model based on the actual service life of the dam. Instantaneous stability risk assessment uses a distributed fiber optic seepage pressure sensor network to monitor pore water pressure data within the dam body in real time. Based on the real-time pore water pressure data, the seepage water level and effective pore pressure are identified to generate an instantaneous stability risk index. Dynamic flood discharge risk setting, calculation of the comprehensive risk index of the dam, analysis of the appropriate flood discharge rate based on historical flood discharge cases, real-time acquisition of upstream flood discharge data and silt accumulation data, and dynamic correction of the appropriate flood discharge rate based on the gate discharge capacity; The method of adaptively dividing the dam sections is as follows: Extract the dam height, dam cross-sectional area and curvature radius of the waterway axis corresponding to each position point on the waterway axis; Obtain the dam height deviation, dam cross-sectional area deviation, and waterway axis curvature radius deviation corresponding to each location point and its adjacent location points, and then compare them with pre-set thresholds respectively; Merge adjacent points until the following partition conditions are met: Condition 1: Any of the dam height deviation, dam cross-sectional area deviation, and waterway axis curvature radius deviation is greater than the corresponding threshold; Condition 2: The axis length of the merged location point is greater than the maximum length of the preset embankment section; Output several continuous pre-divided dam sections, obtain the axial length of each pre-divided dam section, and then compare it with the preset minimum length of the dam section. If any preset dam section has a length less than the preset minimum length of the dam section, merge it into the adjacent dam section with a smaller length, and finally generate several dam sections.

2. A flood control dam stability analysis method according to claim 1, characterized in that: The specific method of generating the corresponding risk monitoring level is as follows: The dam height, dam cross-sectional area and waterway axis curvature radius of each location point in each dam section are compared respectively, and the minimum dam height, minimum dam cross-sectional area and minimum waterway axis curvature radius are selected as the effective dam height, effective dam cross-sectional area and effective waterway axis curvature radius of the corresponding dam section; Comparing the effective dam height, effective dam cross-sectional area and effective waterway axis curvature radius of each dam section with pre-set thresholds respectively; When any parameter exceeds the corresponding threshold, one point is accumulated, and the basic risk quantitative score of each dam section is calculated. The quantitative score is any one of 0-3 points. The parameter is any one of the effective dam height, effective dam cross-sectional area and effective waterway axis curvature radius; The corresponding risk monitoring levels based on the basic risk quantification scores of each dam section are divided into level one, level two, level three and no risk.

3. A flood control dam stability analysis method according to claim 1, characterized in that: The specific construction method of the dam damage assessment collection is as follows: A1. Obtain the surface contour data of each dam section from the 3D dam contour model, and simultaneously obtain the planning contour data of the corresponding dam body; A2. Calculate the displacement distance of each dam surface point compared to the time when the dam was put into use, compare the displacement distance with a preset displacement distance threshold, and record the dam surface point with a displacement distance greater than the preset displacement distance threshold as a damage point; A3. Classify adjacent damage points to obtain a plurality of damage point sets, wherein the damage point sets constitute a plurality of damage regions; A31. Obtain the area of ​​each damaged area and perform cumulative calculation to obtain the effective damaged area of ​​each embankment section; A32. Based on the 3D embankment contour model, obtain the volume reduction of the existing contour corresponding to each damaged area compared to the corresponding contour in the planned contour data. Accumulate the volume reduction of each damaged area to obtain the total damaged volume of each embankment section. Calculate the ratio of this to the planned volume of the corresponding section in the planned contour data to obtain the effective damage degree of each embankment section. A33. Obtain the regional center point of each damaged area, obtain the distance between the regional center point of each damaged area and the regional center points of other damaged areas, use it as the monitoring interval of the corresponding damaged area group, calculate the ratio with the dam height of the corresponding embankment section to obtain the aggregation degree of each damaged area group, and calculate the average of the aggregation degree of each damaged area group to obtain the damage aggregation degree of each embankment section.

4. A flood control dam stability analysis method according to claim 1, characterized in that: The specific construction method of the injury risk model is as follows: B1. Clearly define the effective damage area, effective damage degree, damage concentration, and actual service life of the dam as input variables, and the foundation stability risk index as the output variable; B2. Using historical monitoring data, inspection reports, and operation and maintenance records, collect information on the damage area, damage severity, spatial distribution density of damage, and corresponding foundation stability risk index for different dams at different service lives. The foundation stability risk index is calibrated based on historical accidents or expert assessments. B3. Normalize or dimensionlessly process each input variable to eliminate the impact of dimensional differences; B4. Use multiple regression analysis to fit the mapping relationship between input variables and risk indices, giving priority to model structures with good fit verified by historical data and with generalization error that meets the standard; B5. Use cross-validation to adjust model parameters and verify prediction accuracy using independent test data sets to ensure that the error in risk index output is within a controllable range; B6. Encapsulate the model algorithm under the optimal parameters to form a damage risk model that can input four variables and directly output the basic stability risk index.

5. The method for analyzing flood dam stability according to claim 1, wherein: The specific calculation method of the seepage water level and effective pore pressure is as follows: The dam body of each dam section is divided into several vertical monitoring sections along the waterway axis. Several optical fiber seepage pressure sensors are located in each vertical monitoring section, and each optical fiber seepage pressure sensor is located in a different depth layer. The distributed optical fiber seepage pressure sensor network is used to monitor the pore water pressure data in the dam body in real time to obtain the pore water pressure of each depth layer in each vertical monitoring section, and the monitoring seepage water level height corresponding to each depth layer in each vertical monitoring section is calculated based on the pressure-water level correlation formula; The maximum value of the monitored seepage water level corresponding to each depth layer of each vertical monitoring section is taken as the seepage water level of the dam section; Based on the static water level elevation outside the dam, the static water level pressure is calculated using the pressure-water level correlation formula. The effective pore water pressure at each depth layer of each vertical monitoring section is obtained by calculating the difference between the pore water pressure at each depth layer of each vertical monitoring section and the static water level pressure. The maximum value of the effective pore water pressure of each depth layer in each vertical monitoring section is taken as the effective pore water pressure of the dam section.

6. A flood control dam stability analysis method according to claim 5, characterized in that: The specific analysis method of the instantaneous stability risk index is as follows: Comparing the seepage water level and effective pore pressure with the preset maximum water level and effective pore pressure threshold allowed by the anti-seepage design respectively; Based on the comparison results, the seepage water level and effective pore pressure are divided into low risk, medium risk and high risk respectively; The low risk, medium risk and high risk are respectively assigned different risk values, and the instantaneous stability risk index of each dam section is obtained by matching and summing.

7. The method for analyzing flood dam stability according to claim 1, wherein: The specific method for calculating the comprehensive risk index of the dam is as follows: The basic stability risk index and instantaneous stability risk index of each embankment section are weighted and fused to obtain the comprehensive risk index of each embankment section. The comprehensive risk index of each dam section is compared, and the maximum value is selected as the comprehensive risk index of the current dam.

8. A flood control dam stability analysis method according to claim 1, characterized in that: Specific identification method of the appropriate flood discharge rate: Through a large number of pre-saved historical safe flood discharge cases, the flood discharge rate and comprehensive risk index corresponding to each case are extracted; Match the comprehensive risk index of the current dam with the comprehensive risk index of each case to obtain several successful matching cases; The flood discharge rates corresponding to the successfully matched cases are averaged to obtain the appropriate flood discharge rate for the current flood discharge.

9. A flood control dam stability analysis method according to claim 8, characterized in that: The specific method of dynamically correcting the appropriate flood discharge rate is as follows: Extract upstream flood discharge data and silt accumulation data, calculate the mean of flood discharge rate and silt accumulation cross-sectional area ratio in continuous time windows to obtain the monitored flood discharge rate and monitored silt accumulation cross-sectional area ratio; Comparing the monitored flood discharge rate and the monitored silt accumulation cross-sectional area ratio with a preset flood discharge rate reference value and a preset silt accumulation cross-sectional area reference value respectively; If any parameter of the monitored flood discharge rate and the monitored silt accumulation cross-sectional area ratio is greater than the corresponding reference value, and the appropriate flood discharge rate is less than the corresponding value of the gate flood discharge capacity, the appropriate flood discharge rate will be increased by one preset unit; When the appropriate flood discharge rate is equal to the corresponding value of the gate's flood discharge capacity, the flood discharge rate is maintained at the corresponding value of the gate's flood discharge capacity, a danger alarm is issued and reported to the administrator.

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