Dam safety monitoring method and system

Abstract

The invention relates to the technical field of water conservancy, in particular to a dam safety monitoring method and system, and the method comprises the steps: obtaining the historical rainfall data and topographic data of a dam, and the installation position of monitoring equipment; inputting the historical rainfall data and the topographic data into a hydrodynamic model, and simulating a simulated flow path of rainwater; predicting the monitoring accuracy of the monitoring equipment according to the simulated flow path, the drainage design parameters of the dam drainage structure and the installation position of the monitoring equipment; when it is determined that the monitoring accuracy is smaller than an accuracy threshold value, the installation position of the monitoring equipment is updated, and / or drainage design parameters of the dam drainage structure are updated; and performing safety monitoring on the dam based on the monitoring equipment with the updated installation position and / or the dam drainage structure with the updated drainage design parameters. The monitoring reliability of the monitoring equipment can be improved.

Description

Technical Field

[0001] This application relates to the field of water conservancy technologies, and particularly to a dam safety monitoring method and system. Background Art

[0002] The dam monitoring environment is extremely complex, and water flow and precipitation are two key interference sources. Heavy rainfall can cause the water level to rise rapidly, and the water flow speed and direction will change significantly accordingly. Under such extreme conditions, the stability and accuracy of monitoring equipment will be severely challenged.

[0003] On the one hand, the turbulent water flow may impact the monitoring equipment, causing its position to shift and the collected data to deviate. On the other hand, the runoff formed by continuous precipitation will form complex hydrodynamic conditions on the dam surface, changing the original monitoring environment of the equipment, and further causing the data obtained by the monitoring equipment to not accurately reflect the actual safety status of the dam, that is, the monitoring results are unreliable, so there is an urgent need for improvement. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a dam safety monitoring method and system that can optimize the reliability of dam safety monitoring.

[0005] In a first aspect, this application provides a dam safety monitoring method, which includes: Obtain the historical rainfall data, topographic data of the dam, and the installation location of the monitoring equipment; Input the historical rainfall data and topographic data into a hydrodynamic model to simulate the simulated flow path of rainwater; Predict the monitoring accuracy of the monitoring equipment based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring equipment; In the case where it is determined that the monitoring accuracy is less than the accuracy threshold, update the installation location of the monitoring equipment and / or update the drainage design parameters of the dam drainage structure; Perform dam safety monitoring based on the monitoring equipment with the updated installation location and / or the dam drainage structure with the updated drainage design parameters.

[0006] In one embodiment, the hydrodynamic model includes a continuity equation and a momentum equation for describing the movement of water flow; using the hydrodynamic model, taking the historical rainfall data and topographic data as inputs to simulate the simulated flow path of rainwater includes: According to the actual situation of the dam, initialize the model parameters of the hydrodynamic model; the model parameters include the density, viscosity, surface roughness of the water flow, and boundary conditions; Convert the historical rainfall data into lateral inflow parameters in the hydrodynamic model, and determine the gridded topographic data as the channel bottom slope parameters in the hydrodynamic model; The finite difference method is used to numerically solve the hydrodynamic model, and the water flow parameters of each grid cell are updated within each time step; the water flow parameters include the flow direction and velocity. According to the flow direction and velocity of rainwater between each grid cell, the simulated flow path of rainwater is determined.

[0007] In one embodiment, according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring device, the monitoring accuracy of the monitoring device is predicted, including: According to the simulated flow path and the drainage design parameters of the dam drainage structure, the water flow state parameters at the installation location of the monitoring device are calculated through the principles of water flow continuity and energy conservation; the water flow state parameters include flow velocity, water depth, and water pressure. According to the type of the monitoring device, an accuracy evaluation model is obtained. The water flow state parameters at the installation location are input into the accuracy evaluation model, and combined with the performance parameters of the device itself, the monitoring accuracy of the monitoring device is obtained.

[0008] In one embodiment, updating the installation location of the monitoring device and / or updating the drainage design parameters of the dam drainage structure includes: According to the topography of the dam, the water flow distribution, and the monitoring range of the monitoring device, a spatial analysis algorithm is used to generate multiple optional installation locations of the monitoring device. And / or using the principles of hydraulics and engineering experience, as well as the pipe diameter and slope in the drainage design parameters, to generate multiple optional drainage design parameters of the dam. According to the multiple optional installation locations of the monitoring device and the multiple optional drainage design parameters of the dam, the installation location of the monitoring device is updated, and / or the drainage design parameters of the dam drainage structure are updated.

[0009] In one embodiment, according to the optional installation location of the monitoring device and the optional drainage design parameters of the dam, updating the installation location of the monitoring device and / or updating the drainage design parameters of the dam drainage structure includes: According to the multiple optional installation locations of the monitoring device and the multiple optional drainage design parameters of the dam, multiple adjustment schemes are generated. Each adjustment scheme is re-substituted into the hydrodynamic model to determine the improvement effect of the multiple adjustment schemes on the accuracy of the monitoring device. According to the adjustment scheme with the optimal improvement effect, the installation location of the monitoring device is updated, and / or the drainage design parameters of the dam drainage structure are updated.

[0010] In one embodiment, the method further includes: Predict the water flow conditions of the dam based on historical meteorological data; the current predicted water flow conditions of the dam include the predicted water flow conditions of the dam; Identify the structural weak layer of the monitoring device under the predicted water flow conditions of the dam from each device structure layer of the monitoring device; each device structure layer includes the surface protection layer of the monitoring device, and / or the interface diversion layer, and / or the cavity protection layer; Generate an environmental adaptation strategy corresponding to the structural weak layer according to the predicted water flow conditions of the dam; the environmental adaptation strategy includes the surface energy distribution corresponding to the surface protection layer, and / or the channel cross-sectional curvature radius corresponding to the interface diversion layer, and / or the internal cavity pressure corresponding to the cavity protection layer; Control the monitoring device and use the environmental adaptation strategy to conduct safety monitoring of the dam.

[0011] In one embodiment, the surface protection layer is a bionic fractal hydrophobic structure provided on the outer shell of the monitoring device; The interface diversion layer is a spiral involute drainage channel arranged along the circumference of the monitoring device; The cavity protection layer is a dynamic pressure compensation cavity constructed around the electronic compartment of the monitoring device.

[0012] In one embodiment, the surface energy distribution has a negative correlation gradient relationship with the local water flow velocity in the predicted water flow conditions of the dam; The channel cross-sectional curvature radius satisfies an adaptation relationship with the water flow kinetic energy parameter in the predicted water flow conditions of the dam; The internal cavity pressure forms a non-linear feedback regulation mechanism with the external water pressure in the predicted water flow conditions of the dam.

[0013] In one embodiment, identifying the structural weak layer of the monitoring device under the predicted water flow conditions of the dam from each device structure layer of the monitoring device includes: Obtain a sample data set, which contains the water flow conditions of each sample dam and the state information of each device structure layer of the monitoring device under the water flow conditions of each sample dam; the state information includes the attribute state information of each attribute; Use the association rule mining algorithm to analyze the water flow conditions of each sample dam and the state information of each device structure layer of the monitoring device under the water flow conditions of each sample dam, and obtain the possible probability of weaknesses appearing in each device structure layer of the monitoring device under the predicted water flow conditions; Identify the structural weak layer of the monitoring device under the predicted water flow conditions of the dam from each device structure layer of the monitoring device according to the possible probability of weaknesses appearing in each device structure layer of the monitoring device under the predicted water flow conditions.

[0014] In a second aspect, the present application also provides a dam safety monitoring system, including: An acquisition module for acquiring historical rainfall data, terrain data of the dam, and the installation locations of monitoring devices; A simulation module for inputting the historical rainfall data and terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; A performance evaluation module for predicting the monitoring accuracy of the monitoring devices based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation locations of the monitoring devices; A monitoring adjustment module for updating the installation locations of the monitoring devices and / or updating the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than the accuracy threshold; A monitoring module for performing safety monitoring on the dam based on the monitoring devices with updated installation locations and / or the dam drainage structure with updated drainage design parameters.

[0015] In a third aspect, the present application also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Acquire historical rainfall data, terrain data of the dam, and the installation locations of monitoring devices; Input the historical rainfall data and terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; Predict the monitoring accuracy of the monitoring devices based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation locations of the monitoring devices; Update the installation locations of the monitoring devices and / or update the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than the accuracy threshold; Perform safety monitoring on the dam based on the monitoring devices with updated installation locations and / or the dam drainage structure with updated drainage design parameters.

[0016] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: Acquire historical rainfall data, terrain data of the dam, and the installation locations of monitoring devices; Input the historical rainfall data and terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; Predict the monitoring accuracy of the monitoring devices based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation locations of the monitoring devices; Update the installation locations of the monitoring devices and / or update the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than the accuracy threshold; Perform safety monitoring on the dam based on the monitoring device with updated installation location and / or the dam drainage structure with updated drainage design parameters.

[0017] In a fifth aspect, the present application also provides a computer program product, including a computer program, which when executed by a processor implements the following steps: Obtain the historical rainfall data, terrain data of the dam, and the installation location of the monitoring device; Input the historical rainfall data and terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; Predict the monitoring accuracy of the monitoring device according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring device; When it is determined that the monitoring accuracy is less than the accuracy threshold, update the installation location of the monitoring device and / or update the drainage design parameters of the dam drainage structure; Perform safety monitoring on the dam based on the monitoring device with updated installation location and / or the dam drainage structure with updated drainage design parameters.

[0018] For the above-mentioned dam safety monitoring method and system, the present application simulates the rainwater flow path through a hydrodynamic model, comprehensively considers the terrain and rainfall conditions of the dam, combines the drainage design parameters and the installation location of the monitoring device, and predicts the monitoring accuracy. When the accuracy does not reach the threshold, update the installation location of the monitoring device or the drainage design parameters to ensure that the monitoring device can accurately reflect the safety status of the dam, overcoming the problem of monitoring data deviation caused by water flow and precipitation interference.

[0019] The present application changes the situation where the monitoring device is fixedly installed and the drainage design parameters remain unchanged in the past. Facing the complex and changeable water flow and precipitation environment, the installation location of the monitoring device and the drainage design parameters can be dynamically adjusted to make the monitoring system adapt to different rainfall conditions and terrain features, and can operate stably in various extreme situations. Accurately predict the monitoring accuracy of the monitoring device, providing a basis for reasonably adjusting the installation location of the monitoring device. Avoid the deviation of the device position caused by the impact of turbulent water flow, ensure that the device can continuously and stably collect data, and improve the reliability and effectiveness of the data. During the monitoring process, update the dam drainage design parameters according to the simulation analysis to make the drainage system more in line with the actual rainwater flow path. Not only ensure smooth drainage of the dam, but also reduce the impact of the change of the monitoring environment caused by poor drainage on the device, improving the reliability of the overall safety monitoring of the dam. Through the present application, realize the all-round and dynamic safety monitoring of the dam, timely discover potential safety hazards, provide scientific and accurate data support for the maintenance and management of the dam, and effectively ensure the safe operation of the dam. Description of the Drawings

[0020] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0021] Figure 1 It is a schematic flowchart of the dam safety monitoring method in an embodiment; Figure 2 It is a system block diagram of the dam safety monitoring system in an embodiment. Detailed implementation manners

[0022] In order to make the purpose, technical solutions and advantages of the present application more clear, the following further details the present application in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0023] In an exemplary embodiment, a dam safety monitoring method is provided, and the method includes: S101, obtaining the historical rainfall data, terrain data of the dam, and the installation locations of the monitoring devices.

[0024] Optionally, for the historical rainfall data: obtain the historical rainfall data of the area where the dam is located from the local meteorological department, meteorological station or relevant database, including information such as rainfall, rainfall intensity, and rainfall duration in different time periods (such as years, months, days). Clean the data to remove outliers and missing values, and then perform statistical analysis, such as calculating the average rainfall, maximum rainfall, etc., to understand the rainfall pattern in this area.

[0025] For the terrain data: use technologies such as geographic information system (GIS), lidar or unmanned aerial vehicle mapping to obtain the terrain data of the dam and its surrounding areas, including terrain elevation, slope, aspect, etc. Perform grid processing on the terrain data and convert it into a format suitable for input into the hydrodynamic model.

[0026] For the installation locations of the monitoring devices: determine the specific installation locations of each monitoring device (such as displacement sensors, piezometers, strain gauges, etc.) on the dam through on-site measurement, GPS positioning, etc., and record their coordinate information.

[0027] S102, adopting a hydrodynamic model, using the historical rainfall data and terrain data as inputs, to simulate the simulated flow path of rainwater.

[0028] Optionally, select a hydrodynamic model: According to the actual situation of the dam and the characteristics of the data, select an appropriate hydrodynamic model, such as the Saint-Venant equation model, the shallow water wave equation model, etc. These models can describe the flow process of rainwater on the ground surface and in the river channel, taking into account the effects of factors such as gravity, friction, and terrain.

[0029] Model parameter setting: Set the parameters of the model according to the actual situation, such as the density, viscosity, and surface roughness of the water flow. At the same time, use historical rainfall data and terrain data as inputs to set the boundary conditions of the model, such as the water flow inlet and outlet conditions around the dam and the rainfall boundary conditions.

[0030] Simulation calculation: Use numerical calculation methods (such as the finite difference method, the finite element method, etc.) to solve the hydrodynamic model to obtain information such as the flow path, water flow velocity, and water depth of rainwater at different time periods.

[0031] S103. Predict the monitoring accuracy of the monitoring equipment based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring equipment.

[0032] Optionally, establish a prediction model: Based on the simulated flow path, the drainage design parameters of the dam drainage structure (such as the pipe diameter, slope, and drainage capacity of the drainage pipe), and the installation location of the monitoring equipment, establish a prediction model for monitoring accuracy. Machine learning algorithms (such as neural networks, decision trees, etc.) or statistical methods (such as regression analysis) can be used to construct the prediction model. By learning and training the historical data, find the relationship between the monitoring accuracy and these factors.

[0033] Accuracy prediction: Input the simulated rainwater flow path, drainage design parameters, and monitoring equipment installation location into the prediction model to calculate the predicted monitoring accuracy value of each monitoring equipment.

[0034] S104. In the case where it is determined that the monitoring accuracy is less than the accuracy threshold, update the installation location of the monitoring equipment and / or update the drainage design parameters of the dam drainage structure.

[0035] Optionally, set the accuracy threshold: Set the threshold of the monitoring accuracy according to the safety requirements of the dam and the performance indicators of the monitoring equipment. For example, for a displacement sensor, set the monitoring accuracy threshold to 90%.

[0036] Comparison and judgment: Compare the predicted monitoring accuracy with the set threshold. If the monitoring accuracy of a certain monitoring equipment is less than the threshold, it is considered that the installation location of the equipment needs to be updated and / or the drainage design parameters of the dam drainage structure need to be updated.

[0037] S105. Based on the monitoring device after the installation position is updated, and / or the dam drainage structure after the drainage design parameters are updated, conduct safety monitoring on the dam.

[0038] Optionally, adjust the installation position of the monitoring device: According to the simulated flow path and water flow velocity distribution, select a more suitable position to install the monitoring device to avoid the interference of water flow on the device and improve the monitoring accuracy. For example, install the displacement sensor in an area where the water flow is relatively stable and not easily scoured.

[0039] Adjust the drainage design parameters: According to the simulation results, optimize the dam drainage system, such as increasing the diameter of the drainage pipe, adjusting the drainage slope, increasing the number of drainage outlets, etc., to improve the drainage efficiency, reduce the accumulation of rainwater around the dam, and improve the working environment of the monitoring device.

[0040] In an exemplary embodiment, the hydrodynamic model includes the continuity equation and the momentum equation for describing the water flow motion.

[0041] It can be understood that the continuity equation: Based on the principle of mass conservation, it describes the relationship between the inflow and outflow of fluid mass and the accumulation of mass within a given control volume. For an incompressible fluid, the continuity equation indicates that the flow rate of the fluid in space is constant, that is, the amount of fluid flowing into a certain area is equal to the amount of fluid flowing out of that area. In rainwater simulation, it ensures the conservation of the mass of rainwater throughout the simulation area.

[0042] The momentum equation: Based on Newton's second law, it describes the relationship between the change in fluid momentum and the forces acting on the fluid. In rainwater flow simulation, these forces include gravity, friction, and pressure difference, etc. The momentum equation helps us determine how the velocity and direction of the water flow change with time and space.

[0043] Adopt the hydrodynamic model, take historical rainfall data and terrain data as inputs, and simulate the simulated flow path of rainwater, including: The first step is to initialize the model parameters of the hydrodynamic model according to the actual situation of the dam.

[0044] Among them, the model parameters include the density, viscosity, surface roughness of the water flow, and boundary conditions.

[0045] Optionally, the density of the water flow: The density of water is a basic physical parameter, which affects the inertia and gravitational action of the water flow. Under different temperature and pressure conditions, the density of water will have slight changes, but in most rainwater simulations, it can be regarded as a constant.

[0046] Viscosity: Viscosity reflects the internal friction of the fluid, which affects the resistance and energy loss of the water flow. A higher viscosity will make the water flow more viscous and the flow velocity slower.

[0047] Surface roughness: Surface roughness describes the roughness of the ground surface, which has a great influence on the resistance of water flow. A rough ground surface will increase the friction of water flow and slow down the water flow velocity.

[0048] Boundary conditions: Boundary conditions define the behavior of water flow on the boundaries of the simulation area, such as the inflow, outflow, and fixed boundaries of water flow. Reasonable setting of boundary conditions is crucial for accurately simulating rainwater flow.

[0049] Convert historical rainfall data into lateral inflow parameters in the hydrodynamic model, and determine the channel bottom slope parameters in the hydrodynamic model from the gridded terrain data.

[0050] Optionally, lateral inflow parameters: Historical rainfall data can be converted into lateral inflow parameters, which represent the amount of water flow caused by rainfall within the simulation area. By combining historical rainfall data with time and space information, the lateral inflow situation of each grid cell can be determined.

[0051] Channel bottom slope parameters: The gridded terrain data can be used to determine the channel bottom slope parameters, which describe the slope and direction of the terrain. The channel bottom slope parameters affect the gravitational action and flow direction of water flow, and are important parameters in water flow simulation.

[0052] Second step: Numerically solve the hydrodynamic model using the finite difference method, and update the water flow parameters of each grid cell within each time step.

[0053] Among them, the water flow parameters include the flow direction and velocity.

[0054] Optionally, the finite difference method is a commonly used numerical calculation method for solving partial differential equations (such as the continuity equation and momentum equation). It discretizes the continuous space and time into a finite number of grid points and time steps, then uses differences to approximate derivatives, and transforms the partial differential equations into algebraic equation systems. By iteratively solving these algebraic equation systems, the water flow parameters of each grid cell within each time step, such as the flow direction and velocity, can be obtained.

[0055] Third step: Determine the simulated flow path of rainwater according to the flow direction and velocity of rainwater between each grid cell.

[0056] Optionally, according to the water flow parameters of each grid cell, the flow direction and velocity of rainwater between each grid cell can be determined, so as to determine the simulated flow path of rainwater. This usually involves tracking the movement process of water flow from one grid cell to another until the water flow reaches the boundary or stops flowing.

[0057] Exemplarily, a one-dimensional model: suitable for simulating the flow of simple rivers or ditches, simplifies the water flow into one-dimensional flow, only considering the changes in water flow in one direction. This model is simple to calculate and has high computational efficiency, but the simulation accuracy for complex terrains and water flow conditions is relatively low. A two-dimensional model: considers the two-dimensional flow of water on a plane and can more accurately simulate the diffusion and flow of rainwater on the ground. The two-dimensional model can handle complex terrains and boundary conditions, but the computational amount is relatively large. A three-dimensional model: considers the flow of water in three-dimensional space and can more comprehensively simulate the flow process of rainwater, including the vertical direction changes of the water flow. The three-dimensional model has the highest simulation accuracy, but the computational complexity is also the greatest, requiring a large amount of computational resources and time.

[0058] In an exemplary embodiment, according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation position of the monitoring device, predict the monitoring accuracy of the monitoring device, including: The first step: According to the simulated flow path and the drainage design parameters of the dam drainage structure, through the principles of water flow continuity and energy conservation, calculate the water flow state parameters at the installation position of the monitoring device.

[0059] Among them, the water flow state parameters include flow velocity, water depth, and water pressure.

[0060] Optionally, the principle of water flow continuity: This principle is based on mass conservation, that is, in a stable water flow system, the mass of the fluid flowing into a certain control volume per unit time is equal to the mass of the fluid flowing out of this control volume. For incompressible fluids (such as water), it can be simplified to flow rate conservation. Combining the simulated flow path and the dam drainage design parameters (such as the size and slope of the drainage channel), the relationship between the cross-sectional area and the flow rate of the water flow at the installation position of the monitoring device can be calculated, and then the flow velocity can be obtained. For example, when the water flow passes through a narrow area, the flow velocity will increase to ensure flow rate conservation.

[0061] The principle of energy conservation: In the water flow system, the total energy (including potential energy, kinetic energy, and pressure energy) remains unchanged without energy loss. Considering the energy loss in actual situations (such as frictional loss), it can be calculated through a modified form of the Bernoulli equation. Using the simulated flow path and the drainage design parameters to determine the height change and flow velocity change of the water flow, etc., and combining the principle of energy conservation, the water depth and water pressure at the installation position of the monitoring device can be calculated.

[0062] The second step: According to the type of the monitoring device, obtain the accuracy evaluation model.

[0063] Optionally, for different types of monitoring devices, the way their monitoring accuracy is affected by water flow state parameters is different. For example, ultrasonic flow meters and electromagnetic flow meters have different working principles, and their monitoring accuracies are also different under different flow velocities, water depths, and water pressures. Therefore, it is necessary to obtain an accuracy evaluation model specifically for the type of device according to the type of monitoring device. These models are usually established based on a large amount of experimental data and theoretical analysis, and can describe the relationship between the monitoring accuracy of the device and the water flow state parameters.

[0064] In the third step, input the water flow state parameters at the installation location into the accuracy evaluation model, and combine with the performance parameters of the device itself to obtain the monitoring accuracy of the monitoring device.

[0065] Optionally, input the water flow state parameters at the installation location into the accuracy evaluation model, and at the same time consider the performance parameters of the device itself (such as accuracy grade, measurement range, etc.). The evaluation model will comprehensively calculate the monitoring accuracy of the monitoring device under the current water flow conditions according to the input water flow state parameters and device performance parameters. For example, when the water flow velocity exceeds the measurement range of the device, the monitoring accuracy will decrease significantly.

[0066] In an exemplary embodiment, updating the installation location of the monitoring device and / or updating the drainage design parameters of the dam drainage structure includes: In the first step, according to the topography of the dam, water flow distribution, and the monitoring range of the monitoring device, use a spatial analysis algorithm to generate multiple optional installation locations for the monitoring device, and / or use hydraulic principles, engineering experience, and the pipe diameter and slope in the drainage design parameters to generate multiple optional drainage design parameters for the dam.

[0067] Optionally, Geographic Information System (GIS) analysis: Use GIS software to import the topographic data and water flow simulation data of the dam, and through the spatial analysis function, identify the areas with large water flow changes and key to the dam safety. Then, according to the monitoring range of the monitoring device, select suitable locations in these areas and their peripheries as optional installation locations. Mathematical modeling and optimization: Establish a mathematical model of the dam topography and water flow, convert the monitoring range into mathematical constraint conditions, and solve for the optimal installation location that meets the monitoring requirements through optimization algorithms (such as genetic algorithms, simulated annealing algorithms, etc.).

[0068] Optionally, hydraulic calculation and trial-and-error method: Based on basic hydraulic formulas such as the Manning formula, perform hydraulic calculations for different combinations of pipe diameters and slopes to simulate the flow of water in the drainage system. By continuously adjusting parameters and conducting trial-and-error, find an optional combination of drainage design parameters that can maximize the drainage flow rate, ensure a reasonable water flow velocity, and avoid excessive erosion or sedimentation of the water flow. Numerical simulation and optimization: Use professional hydraulic numerical simulation software such as MIKE, SWMM, etc. to establish a numerical model of the dam drainage system. Input the current design parameters and water flow conditions, and simulate the water flow conditions after adjusting different parameters through the software. Combine optimization algorithms, with drainage efficiency, water flow stability, etc. as the optimization objectives, and automatically search for the optimal optional drainage design parameters.

[0069] Step 2: According to multiple optional installation positions of the monitoring device and multiple optional drainage design parameters of the dam, update the installation position of the monitoring device and / or update the drainage design parameters of the dam drainage structure.

[0070] In one implementation, multi-scheme evaluation and decision-making: Conduct a detailed evaluation of the generated multiple optional installation positions and optional drainage design parameter schemes. Consider factors including monitoring effect, construction difficulty, cost, impact on the dam structure, etc. Multi-attribute decision-making methods such as the analytic hierarchy process and fuzzy comprehensive evaluation method can be used to score and rank each scheme, and select the scheme with the optimal comprehensive performance for update. Step-by-step iterative optimization: First, select some representative optional installation positions and optional drainage design parameters for small-scale experimental updates, then monitor the actual effects, and adjust and optimize the scheme according to the feedback data. Through multiple iterations, gradually determine the final update scheme to reduce risks and ensure that the updated system can achieve the expected performance.

[0071] In another implementable way, according to the optional installation position of the monitoring device and the optional drainage design parameters of the dam, update the installation position of the monitoring device and / or update the drainage design parameters of the dam drainage structure, including: Step 1: Generate multiple adjustment schemes according to multiple optional installation positions of the monitoring device and multiple optional drainage design parameters of the dam.

[0072] Optionally, full permutation and combination: All possible installation positions of all monitoring devices and optional drainage design parameters of the dam are permuted and combined to obtain all possible adjustment schemes. This method can ensure that all potential combination situations are considered, but when the number of optional installation positions and optional drainage design parameters is large, the number of schemes will increase sharply and the computational amount will be large. Rule-based screening and combination: According to some prior knowledge or empirical rules, the optional installation positions and optional drainage design parameters are screened and combined. For example, give priority to installation positions with high correlation with key water flow areas, or select design parameter combinations that can ensure drainage efficiency within a certain range, reduce the number of unnecessary schemes, and improve the efficiency of subsequent evaluation.

[0073] Step 2: Substitute each adjustment scheme back into the hydrodynamic model to determine the improvement effect of multiple adjustment schemes on the accuracy of the monitoring device.

[0074] Optionally, numerical simulation software: Use professional hydrodynamic numerical simulation software (such as Fluent, Flow-3D, etc.) to input the parameters of each adjustment scheme into the software for simulation calculation. These software have powerful computing capabilities and rich physical models, and can accurately simulate the complex movement of water flow. Simplified model evaluation: For some scenarios with high requirements for computational efficiency or relatively simple water flow conditions, a simplified hydrodynamic model can be used for evaluation. For example, use one-dimensional or two-dimensional shallow water equation models, and write simple calculation programs to quickly obtain the water flow state parameters under each adjustment scheme, and then evaluate the improvement effect on the accuracy of the monitoring device.

[0075] Step 3: According to the adjustment scheme with the best improvement effect on accuracy, update the installation position of the monitoring device and / or update the drainage design parameters of the dam drainage structure.

[0076] Optionally, quantitative evaluation indicators: Establish clear quantitative evaluation indicators to measure the improvement effect of the accuracy of the monitoring device, such as the reduction ratio of monitoring error, the improvement degree of the stability of monitoring data, etc. Score each adjustment scheme according to these indicators, and select the scheme with the highest score as the optimal scheme. Multi-objective optimization: In addition to the improvement effect of the accuracy of the monitoring device, other objectives can also be considered, such as the implementation cost of the adjustment scheme, the impact on the existing structure of the dam, etc. Use multi-objective optimization algorithms (such as NSGA-II, MOPSO, etc.) to balance and optimize among multiple objectives, and select the scheme with the best comprehensive performance for updating.

[0077] In an exemplary embodiment, based on the monitoring device with the updated installation position and / or the dam drainage structure with the updated drainage design parameters, safety monitoring of the dam is performed, including: Step 1: Based on historical meteorological data, predict the water flow conditions of the dam.

[0078] Among them, the current predicted water flow conditions of the dam include the predicted water flow conditions of the dam.

[0079] Optionally, establish a meteorological - water conservancy condition relationship model: Collect a large amount of historical meteorological data and corresponding dam water conservancy survey data, and use data mining techniques (such as regression analysis, neural networks, etc.) to establish a relationship model between the two. By inputting the current meteorological data, use the model to predict the rainfall conditions and water flow conditions of the dam. Combine numerical simulation: For the prediction of the water flow conditions of the dam, a hydraulic numerical model can be combined. According to the predicted rainfall conditions and information such as the topography and landform of the dam, simulate the water flow movement of the dam during the rainfall process to obtain a more accurate prediction result of the water flow conditions.

[0080] Step 2: Identify the structural weak layer of the monitoring equipment under the predicted water flow conditions of the dam from each equipment structure layer of the monitoring equipment.

[0081] Among them, each equipment structure layer includes the surface protection layer of the monitoring equipment, and / or the interface diversion layer, and / or the cavity protection layer.

[0082] Optionally, the surface protection layer is a bionic fractal hydrophobic structure set on the outer shell of the monitoring equipment. The interface diversion layer is a spiral involute drainage channel arranged along the circumference of the monitoring equipment. The cavity protection layer is a dynamic pressure compensation cavity constructed around the electronic cabin of the monitoring equipment.

[0083] It can be understood that the surface protection layer (bionic fractal hydrophobic structure) has the following functions: Reducing water adhesion: The bionic fractal hydrophobic structure mimics the surface structures of natural objects such as lotus leaves with superhydrophobic properties. This structure has extremely high surface energy anisotropy, which can cause water to form water droplets on the surface of the equipment, greatly reducing the contact area between water and the surface of the equipment, thereby reducing the adhesion of water to the surface of the equipment, preventing the surface of the equipment from being wetted by water, and avoiding problems such as corrosion and rust caused by long-term contact with water.

[0084] The interface diversion layer (spiral involute drainage channel) has the following functions: Efficient drainage: The spiral involute drainage channel arranged along the circumference of the monitoring equipment can utilize the characteristics of the spiral structure to guide the water flow along a specific path, enabling the water to drain more smoothly from the surface of the equipment. This design can prevent water from accumulating on the surface of the equipment, reduce the soaking time of the equipment by water, and reduce the possibility of damage to the equipment caused by water.

[0085] The cavity protection layer (dynamic pressure compensation cavity) has the following functions for pressure balance: A dynamic pressure compensation cavity is constructed around the electronic compartment of the monitoring device. Its main function is to balance the pressure inside and outside the electronic compartment. When the external water pressure where the device is located changes, the dynamic pressure compensation cavity can automatically adjust the internal pressure to adapt to the external water pressure, thereby protecting the electronic components and circuit systems inside the electronic compartment from the influence of pressure differences and preventing device deformation, seal failure, or damage to electronic components caused by pressure imbalance.

[0086] Optionally, finite element analysis: Finite element modeling is performed on each structural layer of the monitoring device to simulate the stress and strain distribution of each structural layer under different predicted dam water flow conditions, and the structural weak layer is determined by analyzing these results.

[0087] Step 3: Generate an environmental adaptation strategy corresponding to the structural weak layer according to the predicted dam water flow conditions. The environmental adaptation strategy includes the surface energy distribution corresponding to the surface protection layer, and / or the channel cross-sectional curvature radius corresponding to the interface diversion layer, and / or the internal pressure of the cavity corresponding to the cavity protection layer.

[0088] Optionally, the surface energy distribution has a negative correlation gradient relationship with the local water flow velocity in the predicted dam water flow conditions. The channel cross-sectional curvature radius satisfies an adaptation relationship with the water flow kinetic energy parameter in the predicted dam water flow conditions. The internal pressure of the cavity forms a non-linear feedback adjustment mechanism with the external water pressure in the predicted dam water flow conditions.

[0089] It can be understood that the negative correlation gradient relationship between the surface energy distribution and the local water flow velocity: According to the principles of fluid mechanics, the faster the water flow velocity, the stronger the impact force and erosion effect on the object surface. By making the surface energy distribution of the surface protection layer have a negative correlation gradient relationship with the local water flow velocity, the surface energy can be lower in areas with high water flow velocity, increasing the contact angle between water and the surface, reducing the adhesion and erosion of water on the surface, and using the hydrophobic principle to reduce the damage of water flow to the device surface and protect the monitoring device.

[0090] The adaptation relationship between the channel cross-sectional curvature radius and the water flow kinetic energy parameter: The greater the water flow kinetic energy, the stronger the impact force and the ability to carry impurities of the water flow. The channel cross-sectional curvature radius of the interface diversion layer is adapted to the water flow kinetic energy parameter to enable the drainage channel to reasonably guide the water flow according to the energy state of the water flow, avoiding excessive pressure fluctuations, eddies, or blockages in the channel due to inappropriate curvature radius, ensuring smooth drainage, and reducing the scouring and erosion of the water flow on the device.

[0091] Nonlinear feedback regulation mechanism for the internal pressure of the cavity and the external water pressure: The external water pressure where the monitoring device is located changes with the predicted water flow conditions of the dam. When the external water pressure increases, it may damage the internal structures such as the electronic compartment of the device. By establishing a nonlinear feedback regulation mechanism for the internal pressure of the cavity and the external water pressure, the internal pressure of the cavity can be adjusted adaptively according to the change of the external water pressure to balance the external pressure, protect the devices such as electronic components in the electronic compartment, and prevent device damage caused by the pressure difference.

[0092] Surface energy distribution design: First, measure and analyze the water flow velocities at different positions of the dam in detail and establish a water flow velocity distribution model. Then, according to the negative correlation gradient relationship, design the material composition and microstructure of the surface protective layer. For example, in areas with higher water flow velocities, use low surface energy materials such as fluoropolymers, and form areas with lower surface energy by adjusting the coating thickness, surface roughness, etc. of the materials; in areas with lower water flow velocities, appropriately increase the surface energy of the materials to ensure the overall stability and functionality of the device surface.

[0093] Design of the channel cross-section curvature radius: First, measure and calculate the water flow kinetic energy parameters in the predicted water flow conditions of the dam, including water flow velocity, flow rate, water body density, etc. According to these parameters, combined with the hydrodynamic equation in fluid mechanics, design the channel cross-section curvature radius of the interface diversion layer. For example, for areas with larger water flow kinetic energy, design a larger curvature radius so that the water flow can pass through the drainage channel smoothly; for areas with smaller water flow kinetic energy, appropriately reduce the curvature radius, but ensure that the channel will not be blocked or generate too large a water flow resistance due to too small a curvature radius.

[0094] Internal pressure regulation of the cavity: Install a pressure sensor and a pressure regulation device in the cavity protective layer of the monitoring device. The pressure sensor monitors the change of the external water pressure in real time and transmits the signal to the control system. The control system adjusts the internal pressure of the cavity by controlling the pressure regulation device, such as a small air pump, a hydraulic device, etc., according to the preset nonlinear feedback regulation mechanism. For example, when the external water pressure increases rapidly, the control system makes the internal pressure of the cavity increase rapidly in a nonlinear manner to adapt to the change of the external pressure faster and protect the electronic compartment; when the change of the external water pressure is small, the adjustment of the internal pressure of the cavity is also relatively gentle to avoid the impact on the device caused by frequent fluctuations of the internal pressure.

[0095] Fourth step: Based on the monitoring device with updated installation position and / or the dam drainage structure with updated drainage design parameters, control the monitoring device and adopt an environmental adaptation strategy to conduct safety monitoring of the dam.

[0096] Optionally, controlling the monitoring device to adopt the generated environment adaptation strategy can enable the monitoring device to be in an optimal working state under the predicted dam water flow conditions, improve the accuracy and reliability of its monitoring data, and thus better conduct safety monitoring of the dam and timely detect potential safety hazards.

[0097] In an exemplary embodiment, from each device structure layer of the monitoring device, identify the structural weakness layer of the monitoring device under the predicted dam water flow conditions, including: First step, obtain a sample data set, which contains various sample dam water flow conditions and the state information of each device structure layer of the monitoring device under each sample dam water flow condition.

[0098] Among them, the state information includes the attribute state information of each attribute.

[0099] Optionally, data collection and collation: establish a data collection system, and continuously collect the state information of each structure layer of the survey device under different water conservancy survey conditions, including various attribute state information such as the wear condition of the surface protection layer, the blockage condition of the interface diversion layer, and the pressure stability of the cavity protection layer, and organize this information together with the corresponding water conservancy survey condition data into a sample data set to ensure the accuracy and integrity of the data.

[0100] Second step, adopt an association rule mining algorithm to analyze each sample dam water flow condition and the state information of each device structure layer of the monitoring device under each sample dam water flow condition, and obtain the possible probability of weaknesses appearing in each structure layer of the monitoring device under the predicted dam water flow conditions.

[0101] Optionally, select a suitable association rule mining algorithm, such as the Apriori algorithm or the FP - growth algorithm, etc. Format the water conservancy survey conditions and device structure layer state information in the sample data set to meet the input requirements of the algorithm. Then, by setting appropriate support and confidence thresholds, run the algorithm to mine the association rules between the water conservancy survey conditions and the state of each structure layer, so as to obtain the probability of weaknesses appearing in each structure layer under the current water conservancy survey conditions.

[0102] Third step, according to the possible probability of weaknesses appearing in each structure layer of the monitoring device under the predicted dam water flow conditions, identify the structural weakness layer of the monitoring device from each device structure layer of the monitoring device.

[0103] Optionally, set a threshold according to the probability of weaknesses appearing in each structure layer obtained by the association rule mining algorithm. When the probability of weaknesses appearing in a certain structure layer exceeds this threshold, identify it as the structural weakness layer. It can be re - analyzed and identified regularly or in real - time according to new water conservancy survey conditions and updated sample data sets to adapt to the changing actual situation.

[0104] In an exemplary embodiment, based on the above dam safety monitoring method, this embodiment provides a dam safety monitoring system, which includes: An acquisition module 11, configured to acquire historical rainfall data, terrain data of the dam, and the installation positions of monitoring devices; A simulation module 12, configured to input the historical rainfall data and terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; A performance evaluation module 13, configured to predict the monitoring accuracy of the monitoring devices according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation positions of the monitoring devices; A monitoring adjustment module 14, configured to update the installation positions of the monitoring devices and / or update the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than the accuracy threshold; A monitoring module 15, configured to perform safety monitoring on the dam based on the monitoring devices with updated installation positions and / or the dam drainage structure with updated drainage design parameters.

[0105] In an exemplary embodiment, this embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Acquire historical rainfall data, terrain data of the dam, and the installation positions of monitoring devices; Input the historical rainfall data and terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; Predict the monitoring accuracy of the monitoring devices according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation positions of the monitoring devices; Update the installation positions of the monitoring devices and / or update the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than the accuracy threshold; Perform safety monitoring on the dam based on the monitoring devices with updated installation positions and / or the dam drainage structure with updated drainage design parameters.

[0106] In an exemplary embodiment, this embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: Acquire historical rainfall data, terrain data of the dam, and the installation positions of monitoring devices; Input the historical rainfall data and terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; Predict the monitoring accuracy of the monitoring device according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring device; When it is determined that the monitoring accuracy is less than the accuracy threshold, update the installation location of the monitoring device and / or update the drainage design parameters of the dam drainage structure; Based on the monitoring device with the updated installation location and / or the dam drainage structure with the updated drainage design parameters, conduct safety monitoring on the dam.

[0107] In an exemplary embodiment, the present embodiment further provides a computer program product, including a computer program, which when executed by a processor implements the following steps: Obtain the historical rainfall data, terrain data of the dam, and the installation location of the monitoring device; Input the historical rainfall data and terrain data into the hydrodynamic model to simulate the simulated flow path of rainwater; Predict the monitoring accuracy of the monitoring device according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring device; When it is determined that the monitoring accuracy is less than the accuracy threshold, update the installation location of the monitoring device and / or update the drainage design parameters of the dam drainage structure; Based on the monitoring device with the updated installation location and / or the dam drainage structure with the updated drainage design parameters, conduct safety monitoring on the dam.

[0108] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0109] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as within the scope recorded in the present application.

[0110] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A dam safety monitoring method, characterized in that, The method includes: Obtaining the historical rainfall data, topographic data of the dam, and the installation locations of the monitoring devices; Inputting the historical rainfall data and the topographic data into a hydrodynamic model to simulate the simulated flow path of rainwater; Predicting the monitoring accuracy of the monitoring devices based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation locations of the monitoring devices; Updating the installation locations of the monitoring devices and / or updating the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than the accuracy threshold; Performing safety monitoring on the dam based on the monitoring devices with updated installation locations and / or the dam drainage structure with updated drainage design parameters.

2. The method according to claim 1, wherein The hydrodynamic model includes the continuity equation and the momentum equation for describing the water flow motion; the inputting the historical rainfall data and the topographic data into the hydrodynamic model to simulate the simulated flow path of rainwater includes: Initializing the model parameters of the hydrodynamic model according to the actual situation of the dam; the model parameters include the density, viscosity, surface roughness of the water flow, and boundary conditions; Converting the historical rainfall data into the lateral inflow parameters in the hydrodynamic model, and determining the gridded topographic data as the channel bottom slope parameters in the hydrodynamic model; Numerically solving the hydrodynamic model using the finite difference method, and updating the water flow parameters of each grid cell within each time step; the water flow parameters include the flow direction and velocity; Determining the simulated flow path of rainwater according to the flow direction and velocity of rainwater between each grid cell.

3. The method according to claim 1, characterized in that The predicting the monitoring accuracy of the monitoring devices based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation locations of the monitoring devices includes: Calculating the water flow state parameters at the installation locations of the monitoring devices according to the simulated flow path and the drainage design parameters of the dam drainage structure through the principles of water flow continuity and energy conservation; the water flow state parameters include the flow velocity, water depth, and water pressure; Obtaining an accuracy evaluation model according to the type of the monitoring devices; Inputting the water flow state parameters at the installation locations into the accuracy evaluation model, and combining with the performance parameters of the devices themselves to obtain the monitoring accuracy of the monitoring devices.

4. The method according to claim 1, wherein The updating the installation locations of the monitoring devices and / or updating the drainage design parameters of the dam drainage structure includes: Generating multiple optional installation locations of the monitoring devices using a spatial analysis algorithm according to the topography, water flow distribution of the dam, and the monitoring range of the monitoring devices; And / or generating multiple optional drainage design parameters of the dam using the hydraulic principles and engineering experience, and the pipe diameter and slope in the drainage design parameters; Updating the installation locations of the monitoring devices and / or updating the drainage design parameters of the dam drainage structure according to the multiple optional installation locations of the monitoring devices and the multiple optional drainage design parameters of the dam.

5. The method according to claim 4, wherein Updating the installation position of the monitoring device and / or updating the drainage design parameters of the dam drainage structure according to multiple optional installation positions of the monitoring device and multiple optional drainage design parameters of the dam includes: Generating multiple adjustment schemes according to multiple optional installation positions of the monitoring device and multiple optional drainage design parameters of the dam; Substituting each adjustment scheme back into the hydrodynamic model to determine the improvement effect of each adjustment scheme on the accuracy of the monitoring device; Updating the installation position of the monitoring device and / or updating the drainage design parameters of the dam drainage structure according to the adjustment scheme with the optimal accuracy improvement effect.

6. The method according to claim 1, characterized in that Performing safety monitoring on the dam based on the monitoring device with the updated installation position and / or the dam drainage structure with the updated drainage design parameters, including: Predicting the predicted dam water flow conditions based on the historical meteorological data of the dam; Identifying the structural weak layer of the monitoring device under the predicted dam water flow conditions from each device structure layer of the monitoring device; each device structure layer includes the surface protection layer of the monitoring device and / or the interface diversion layer, and / or the cavity protection layer; Generating an environmental adaptation strategy corresponding to the structural weak layer according to the predicted dam water flow conditions; the environmental adaptation strategy includes the surface energy distribution corresponding to the surface protection layer and / or the channel cross-sectional curvature radius corresponding to the interface diversion layer, and / or the internal cavity pressure corresponding to the cavity protection layer; Based on the monitoring device with the updated installation position and / or the dam drainage structure with the updated drainage design parameters, controlling the monitoring device to adopt the environmental adaptation strategy to perform safety monitoring on the dam.

7. The method according to claim 6, characterized in that, The surface protection layer is a bionic fractal hydrophobic structure provided on the outer shell of the monitoring device; The interface diversion layer is a spiral involute drainage channel arranged along the circumference of the monitoring device; The cavity protection layer is a dynamic pressure compensation cavity constructed around the electronic compartment of the monitoring device.

8. The method according to claim 7, characterized in that The surface energy distribution has a negative correlation gradient relationship with the local water flow velocity in the predicted dam water flow conditions; The channel cross-sectional curvature radius satisfies an adaptation relationship with the water flow energy parameter in the predicted dam water flow conditions; The internal cavity pressure and the external water pressure in the predicted dam water flow conditions form a non-linear feedback adjustment mechanism.

9. The method according to claim 8, wherein Identifying the structural weak layer of the monitoring device under the predicted dam water flow conditions from each device structure layer of the monitoring device includes: Obtaining a sample data set, the sample data set includes each sample dam water flow condition and the state information of each device structure layer of the monitoring device under each sample dam water flow condition; the state information includes the attribute state information of each attribute; Using an association rule mining algorithm to analyze each sample dam water flow condition and the state information of each device structure layer of the monitoring device under each sample dam water flow condition to obtain the possible probability of weaknesses occurring in each device structure layer of the monitoring device under the predicted dam water flow conditions; Identify the structural weak layer of the monitoring device under the predicted dam water flow conditions from each device structural layer of the monitoring device according to the possible probability of weaknesses occurring in each structural layer of the monitoring device under the predicted dam water flow conditions.

10. A dam safety monitoring system, characterized in that, The system includes: An acquisition module for acquiring historical rainfall data, terrain data of the dam, and the installation location of the monitoring device; A simulation module for inputting the historical rainfall data and the terrain data into a hydrodynamic model to simulate the simulated flow path of rainwater; A performance evaluation module for predicting the monitoring accuracy of the monitoring device according to the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring device; A monitoring adjustment module for updating the installation location of the monitoring device and / or updating the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than the accuracy threshold; A monitoring module for performing safety monitoring on the dam based on the monitoring device with the updated installation location and / or the dam drainage structure with the updated drainage design parameters.

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