Dam safety monitoring method and system

Abstract

The present application relates to the field of water conservancy technology, and in particular to a dam safety monitoring method and system. The method comprises: obtaining historical rainfall data, topographic data, and the installation location of a monitoring device for a dam; inputting the historical rainfall data and topographic data into a fluid dynamics model to simulate the flow path of rainwater; predicting the monitoring accuracy of the monitoring device based on the simulated flow path, the drainage design parameters of the dam drainage structure, and the installation location of the monitoring device; updating the installation location of the monitoring device and / or updating the drainage design parameters of the dam drainage structure if the monitoring accuracy is determined to be less than an accuracy threshold; and performing safety monitoring of the dam based on the updated installation location of the monitoring device and / or the updated drainage design parameters of the dam drainage structure. The present application can improve the monitoring reliability of the monitoring device.

Description

Technical Field

[0001] The present application relates to the field of water conservancy technology, and in particular to a dam safety monitoring method and system. Background Art

[0002] Dam monitoring environments are extremely complex, with water flow and precipitation being two key sources of interference. Heavy rainfall can rapidly raise water levels, significantly altering the speed and direction of water flow. These extreme conditions pose significant challenges to the stability and accuracy of monitoring equipment.

[0003] On the one hand, 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 thus causing the data obtained by the monitoring equipment to be unable to accurately reflect the actual safety status of the dam, that is, the monitoring results are unreliable, and therefore urgently need to be improved. Summary of the Invention

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

[0005] In a first aspect, the present application provides a dam safety monitoring method, the method comprising:

[0006] Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment;

[0007] Historical rainfall data and topographic data were input into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0008] Predict the accuracy of monitoring equipment based on simulated flow paths, drainage design parameters of the dam drainage structure, and the installation location of monitoring equipment;

[0009] If it is determined that the monitoring accuracy is less than the accuracy threshold, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure;

[0010] The dam safety is monitored based on the updated monitoring equipment installation location and / or the updated drainage design parameters of the dam drainage structure.

[0011] In one embodiment, the fluid dynamics model includes a continuity equation and a momentum equation for describing water flow. The fluid dynamics model is used to take historical rainfall data and terrain data as input to simulate the flow path of rainwater, including:

[0012] Initialize the parameters of the fluid dynamics model according to the actual conditions of the dam; the model parameters include water density, viscosity, surface roughness, and boundary conditions;

[0013] The historical rainfall data were converted into lateral inflow parameters in the fluid dynamics model, and the gridded terrain data were determined as channel bottom slope parameters in the fluid dynamics model;

[0014] The finite difference method is used to numerically solve the fluid dynamics model and update the water flow parameters of each grid cell in each time step; the water flow parameters include flow direction and velocity;

[0015] The simulated flow path of rainwater is determined based on the flow direction and speed of rainwater between each grid unit.

[0016] In one embodiment, predicting the monitoring accuracy of the monitoring device based on the simulated flow path, drainage design parameters of the dam drainage structure, and the installation location of the monitoring device includes:

[0017] Based on 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 equipment are calculated using the principles of water flow continuity and energy conservation. The water flow state parameters include flow velocity, water depth, and water pressure.

[0018] Obtain accuracy assessment models based on the type of monitoring equipment;

[0019] The water flow state parameters at the installation location are input into the accuracy evaluation model, and combined with the performance parameters of the equipment itself, the monitoring accuracy of the monitoring equipment is obtained.

[0020] In one embodiment, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure includes:

[0021] Based on the dam's topography, water flow distribution, and the monitoring range of the monitoring equipment, a spatial analysis algorithm is used to generate multiple optional installation locations for the monitoring equipment;

[0022] and / or generate multiple optional drainage design parameters for the dam by using hydraulic principles and engineering experience, as well as drainage pipe diameters and slopes in drainage design parameters;

[0023] According to multiple optional installation positions of the monitoring equipment and multiple optional drainage design parameters of the dam, the installation position of the monitoring equipment is updated, and / or the drainage design parameters of the dam drainage structure are updated.

[0024] In one embodiment, updating the installation location of the monitoring device and / or updating the drainage design parameters of the dam drainage structure according to the optional installation location of the monitoring device and the optional drainage design parameters of the dam includes:

[0025] generating multiple adjustment plans according to multiple optional installation positions of the monitoring equipment and multiple optional drainage design parameters of the dam;

[0026] Substitute each adjustment scheme into the fluid dynamics model again to determine the accuracy improvement effect of multiple adjustment schemes on the monitoring equipment;

[0027] Based on the adjustment plan that best improves accuracy, the installation location of the monitoring equipment is updated, and / or the drainage design parameters of the dam drainage structure are updated.

[0028] In one embodiment, the method further comprises:

[0029] Based on historical meteorological data, the predicted dam flow conditions are predicted for the dam; the current predicted dam flow conditions include the predicted dam flow conditions;

[0030] Identify structural weaknesses of the monitoring equipment under predicted dam flow conditions from each equipment structural layer of the monitoring equipment; each equipment structural layer includes a surface protection layer, and / or an interface diversion layer, and / or a cavity protection layer of the monitoring equipment;

[0031] Generate an environmental adaptation strategy for the structural weakness layer based on the predicted dam flow conditions; the environmental adaptation strategy includes the surface energy distribution corresponding to the surface protection layer, and / or the channel cross-section curvature radius corresponding to the interface diversion layer, and / or the cavity internal pressure corresponding to the cavity protection layer;

[0032] Control monitoring equipment and adopt environmental adaptation strategies to monitor the safety of the dam.

[0033] In one embodiment, the surface protection layer is a bionic fractal hydrophobic structure provided on the housing of the monitoring device;

[0034] The interface diversion layer is a spiral involute drainage channel arranged along the circumference of the monitoring equipment;

[0035] The cavity shield is a dynamic pressure compensation cavity built around the electronic compartment of the monitoring equipment.

[0036] In one embodiment, the surface energy distribution has a negative gradient relationship with the local water velocity in the predicted dam flow conditions;

[0037] The curvature radius of the channel section satisfies the adaptation relationship with the water kinetic energy parameter in the predicted dam water flow conditions;

[0038] The internal pressure of the cavity forms a nonlinear feedback regulation mechanism with the external water pressure in the predicted dam flow conditions.

[0039] In one embodiment, identifying, from each device structure layer of the monitoring device, a structural weakness layer of the monitoring device under the predicted dam flow condition includes:

[0040] Acquire a sample data set, the sample data set including water flow conditions of each sample dam and status information of each structural layer of the monitoring equipment under the water flow conditions of each sample dam; the status information includes attribute status information of each attribute;

[0041] Using an association rule mining algorithm, we analyze the water flow conditions of each sample dam and the status information of each structural layer of the monitoring equipment under each sample dam water flow condition, and determine the possible probability of weaknesses in each structural layer of the monitoring equipment under the predicted dam water flow conditions.

[0042] According to the possible probability of occurrence of weaknesses in each structural layer of the monitoring equipment under the predicted dam water flow condition, the structural weakness layer of the monitoring equipment under the predicted dam water flow condition is identified from each device structural layer of the monitoring equipment.

[0043] In a second aspect, the present application also provides a dam safety monitoring system, comprising:

[0044] An acquisition module is used to obtain the historical rainfall data of the dam, terrain data and the installation location of monitoring equipment;

[0045] a simulation module for inputting historical rainfall data and topographic data into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0046] A performance evaluation module is used to 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;

[0047] a monitoring adjustment module, configured to update an installation location of a monitoring device and / or update drainage design parameters of a dam drainage structure when it is determined that the monitoring accuracy is less than an accuracy threshold;

[0048] The monitoring module is used to monitor the safety of the dam based on the monitoring equipment after the installation location is updated and / or the dam drainage structure after the drainage design parameters are updated.

[0049] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0050] Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment;

[0051] Historical rainfall data and topographic data were input into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0052] Predict the accuracy of monitoring equipment based on simulated flow paths, drainage design parameters of the dam drainage structure, and the installation location of monitoring equipment;

[0053] If it is determined that the monitoring accuracy is less than the accuracy threshold, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure;

[0054] The dam safety is monitored based on the updated monitoring equipment installation location and / or the updated drainage design parameters of the dam drainage structure.

[0055] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0056] Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment;

[0057] Historical rainfall data and topographic data were input into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0058] Predict the accuracy of monitoring equipment based on simulated flow paths, drainage design parameters of the dam drainage structure, and the installation location of monitoring equipment;

[0059] If it is determined that the monitoring accuracy is less than the accuracy threshold, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure;

[0060] The dam safety is monitored based on the updated monitoring equipment installation location and / or the updated drainage design parameters of the dam drainage structure.

[0061] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0062] Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment;

[0063] Historical rainfall data and topographic data were input into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0064] Predict the accuracy of monitoring equipment based on simulated flow paths, drainage design parameters of the dam drainage structure, and the installation location of monitoring equipment;

[0065] If it is determined that the monitoring accuracy is less than the accuracy threshold, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure;

[0066] The dam safety is monitored based on the updated monitoring equipment installation location and / or the updated drainage design parameters of the dam drainage structure.

[0067] The dam safety monitoring method and system described above uses a fluid dynamics model to simulate rainwater flow paths, comprehensively considering the dam's terrain and rainfall conditions. This system then combines drainage design parameters and monitoring equipment installation locations to predict monitoring accuracy. If accuracy falls below a threshold, the monitoring equipment installation location or drainage design parameters are updated to ensure the monitoring equipment accurately reflects the dam's safety status, overcoming the problem of monitoring data deviation caused by interference from water flow and precipitation.

[0068] This application changes the previous situation where monitoring equipment was fixedly installed and drainage design parameters remained unchanged. In the face of complex and changing water flow and precipitation environments, the installation position of the monitoring equipment and the drainage design parameters can be dynamically adjusted, allowing the monitoring system to adapt to different rainfall conditions and topography, and to operate stably under various extreme conditions. Accurately predict the monitoring accuracy of the monitoring equipment and provide a basis for the reasonable adjustment of the installation position of the monitoring equipment. Avoid the displacement of the equipment position due to the impact of turbulent water flow, ensure that the equipment can continuously and stably collect data, and improve the reliability and effectiveness of the data. During the monitoring process, the dam drainage design parameters are updated based on simulation analysis to make the drainage system more consistent with the actual rainwater flow path. It not only ensures smooth drainage of the dam, but also reduces the impact of changes in the monitoring environment caused by poor drainage on the equipment, thereby improving the reliability of the overall safety monitoring of the dam. Through this application, all-round and dynamic safety monitoring of the dam can be achieved, potential safety hazards can be discovered in a timely manner, and scientific and accurate data support can be provided for dam maintenance and management, effectively ensuring the safe operation of the dam. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0070] Figure 1 A schematic flow chart of a dam safety monitoring method according to an embodiment;

[0071] Figure 2 FIG. 4 is a system block diagram of a dam safety monitoring system in one embodiment. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0073] In an exemplary embodiment, a dam safety monitoring method is provided, the method comprising:

[0074] S101, obtaining historical rainfall data, topographic data and installation locations of monitoring equipment of the dam.

[0075] Optional: Historical rainfall data for the dam area should be obtained from local meteorological authorities, weather stations, or relevant databases. This data should include information such as rainfall amount, rainfall intensity, and rainfall duration for different time periods (e.g., year, month, and day). Clean the data to remove outliers and missing values, and then perform statistical analysis, such as calculating average and maximum rainfall, to understand rainfall patterns in the area.

[0076] Topographic data: Use geographic information systems (GIS), lidar, or drone mapping to obtain topographic data of the dam and its surrounding area, including terrain elevation, slope, and aspect. Grid the topographic data and convert it into a format suitable for input into the fluid dynamics model.

[0077] Monitoring equipment installation location: Determine the specific installation location of each monitoring device on the dam (such as displacement sensor, piezometer, strain gauge, etc.) through on-site measurement, GPS positioning, etc., and record its coordinate information.

[0078] S102 uses a fluid dynamics model to simulate the simulated flow path of rainwater by taking historical rainfall data and topographic data as input.

[0079] Optionally, select a fluid dynamics model: Based on the actual dam conditions and data characteristics, choose an appropriate fluid dynamics model, such as the Saint-Venant equation model or the shallow water wave equation model. These models can describe the flow of rainwater on the surface and in the river channel, taking into account the effects of gravity, friction, topography, and other factors.

[0080] Model parameter setting: Set the model parameters according to the actual situation, such as water density, viscosity, surface roughness, etc. At the same time, use historical rainfall data and terrain data as input to set the model boundary conditions, such as water inlet and outlet conditions around the dam and rainfall boundary conditions.

[0081] Simulation calculation: Use numerical calculation methods (such as finite difference method, finite element method, etc.) to solve the fluid dynamics model to obtain information such as the flow path, water velocity and water depth of rainwater in different time periods.

[0082] S103, predicting 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.

[0083] Optionally, develop a predictive model: This model is based on the simulated flow path, drainage design parameters of the dam drainage structure (such as pipe diameter, slope, and drainage capacity), and the location of the monitoring equipment. This model can be constructed using machine learning algorithms (such as neural networks and decision trees) or statistical methods (such as regression analysis). By learning and training from historical data, the model can be used to identify the relationship between monitoring accuracy and these factors.

[0084] Accuracy prediction: The simulated rainwater flow path, drainage design parameters and monitoring equipment installation locations are input into the prediction model to calculate the monitoring accuracy prediction value of each monitoring device.

[0085] S104: When it is determined that the monitoring accuracy is less than the accuracy threshold, the installation position of the monitoring equipment is updated, and / or the drainage design parameters of the dam drainage structure are updated.

[0086] Optionally, set an accuracy threshold: Based on the dam's safety requirements and the performance indicators of the monitoring equipment, set a threshold for monitoring accuracy. For example, for displacement sensors, set the monitoring accuracy threshold to 90%.

[0087] Comparative judgment: The predicted monitoring accuracy is compared with the set threshold. If the monitoring accuracy of a monitoring device is less than the threshold, it is considered necessary to update the installation location of the device and / or update the drainage design parameters of the dam drainage structure.

[0088] S105 , performing safety monitoring on the dam based on the monitoring equipment with updated installation locations and / or the dam drainage structure with updated drainage design parameters.

[0089] Optionally, adjust the monitoring device installation location: Based on the simulated flow path and water velocity distribution, select a more appropriate location to install the monitoring device to avoid water flow interference and improve monitoring accuracy. For example, install the displacement sensor in an area with relatively stable water flow and less susceptible to scouring.

[0090] Adjust drainage design parameters: Based on the simulation results, optimize the dam's drainage system, such as increasing the diameter of the drainage pipe, adjusting the drainage slope, and increasing the number of drainage outlets, to improve drainage efficiency, reduce the accumulation of rainwater around the dam, and improve the working environment of the monitoring equipment.

[0091] In an exemplary embodiment, the fluid dynamics model includes continuity equations and momentum equations for describing the motion of water flow.

[0092] The continuity equation, based on the principle of conservation of mass, describes the flow and accumulation of fluid mass within a given control volume. For incompressible fluids, the continuity equation states that the flow rate of the fluid is constant in space—that is, the amount of fluid flowing into a region is equal to the amount of fluid flowing out of that region. In rainwater simulations, this ensures the conservation of mass throughout the entire simulation area.

[0093] The momentum equation, based on Newton's second law, describes the relationship between changes in a fluid's momentum and the forces acting on it. In rainwater flow simulations, these forces include gravity, friction, and pressure differences. The momentum equation helps us determine how the speed and direction of water flow vary over time and space.

[0094] A fluid dynamics model is used to simulate the flow path of rainwater, taking historical rainfall data and topographic data as input, including:

[0095] The first step is to initialize the model parameters of the fluid dynamics model according to the actual situation of the dam.

[0096] The model parameters include water density, viscosity, surface roughness and boundary conditions.

[0097] Optional, water density: Water density is a fundamental physical parameter that affects the inertia and gravity effects of water flow. Water density will vary slightly under different temperature and pressure conditions, but in most rain simulations it can be treated as a constant.

[0098] Viscosity: Viscosity reflects the friction within the fluid, which affects the resistance and energy loss of water flow. Higher viscosity makes the water flow more viscous and slows down the flow rate.

[0099] Surface roughness: Surface roughness describes the roughness of the surface, which has a significant impact on the resistance to water flow. A rough surface increases the friction of water flow, slowing down the flow.

[0100] Boundary conditions: Boundary conditions define the behavior of water flow at the boundaries of the simulation area, such as inflow, outflow, and fixed boundaries. Proper boundary condition settings are crucial for accurately simulating rainwater flow.

[0101] The historical rainfall data were converted into lateral inflow parameters in the fluid dynamics model, and the gridded terrain data were determined as channel bottom slope parameters in the fluid dynamics model.

[0102] Optional, lateral inflow parameter: Historical rainfall data can be converted into a lateral inflow parameter, which represents the amount of water flowing into the simulation area due to rainfall. By combining historical rainfall data with temporal and spatial information, the lateral inflow for each grid cell can be determined.

[0103] Channel bottom slope parameters: Gridded terrain data can be used to determine channel bottom slope parameters, which describe the slope and direction of the terrain. Channel bottom slope parameters affect the gravity effect and flow direction of water flow and are important parameters in water flow simulation.

[0104] In the second step, the finite difference method is used to numerically solve the fluid dynamics model and update the water flow parameters of each grid cell in each time step.

[0105] Among them, water flow parameters include flow direction and speed.

[0106] Alternatively, the finite difference method is a commonly used numerical computational technique for solving partial differential equations (such as the continuity equation and the momentum equation). It discretizes continuous space and time into a finite number of grid points and time steps. It then uses difference approximations to replace derivatives, transforming the partial differential equations into a system of algebraic equations. By iteratively solving these algebraic equations, flow parameters such as flow direction and velocity can be determined for each grid cell at each time step.

[0107] The third step is to determine the simulated flow path of rainwater based on the flow direction and speed of rainwater between each grid unit.

[0108] Optionally, based on the flow parameters of each grid cell, the direction and speed of rainwater flow between grid cells can be determined, thereby determining the simulated flow path of rainwater. This usually involves tracing the movement of water from one grid cell to another until the water reaches a boundary or stops flowing.

[0109] For example, one-dimensional model: suitable for simple river or ditch water flow simulation, simplifies the water flow into one-dimensional flow, and only considers 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 terrain and water flow conditions is low. Two-dimensional model: takes into account the two-dimensional flow of water on the plane, and can more accurately simulate the diffusion and flow of rainwater on the ground. The two-dimensional model can handle complex terrain and boundary conditions, but the amount of calculation is relatively large. Three-dimensional model: takes into account the flow of water in three-dimensional space, and can more comprehensively simulate the flow process of rainwater, including the vertical direction changes of water flow. The three-dimensional model has the highest simulation accuracy, but the computational complexity is also the greatest, requiring a lot of computing resources and time.

[0110] In an exemplary embodiment, predicting the monitoring accuracy of a monitoring device based on a simulated flow path, drainage design parameters of a dam drainage structure, and an installation location of the monitoring device includes:

[0111] The first step is to calculate the water flow state parameters at the installation location of the monitoring equipment based on the simulated flow path and the drainage design parameters of the dam drainage structure and the principles of water flow continuity and energy conservation.

[0112] Among them, water flow state parameters include flow velocity, water depth and water pressure.

[0113] Optional: The Flow Continuity Principle: This principle is based on the conservation of mass, which states that in a stable flow system, the mass of fluid flowing into a control volume per unit time equals the mass of fluid flowing out of the control volume. For incompressible fluids (such as water), this principle can be simplified to the conservation of flow rate. By combining the simulated flow path with dam drainage design parameters (such as drainage channel dimensions and slope), the relationship between the cross-sectional area and flow rate at the monitoring device installation location can be calculated, thereby determining the flow velocity. For example, when the flow passes through a narrow area, the flow velocity will increase to ensure flow conservation.

[0114] The principle of conservation of energy: In a water flow system, total energy (including potential, kinetic, and pressure energy) remains constant in the absence of energy losses. Taking into account the presence of energy losses (such as frictional losses) in real-world situations, a modified form of the Bernoulli equation can be used for calculation. By simulating the flow path and drainage design parameters to determine changes in water height and velocity, and applying the principle of conservation of energy, the water depth and pressure at the monitoring device installation location can be calculated.

[0115] The second step is to obtain the accuracy assessment model based on the type of monitoring equipment.

[0116] Optionally, the accuracy of different types of monitoring equipment is affected differently by water flow parameters. For example, ultrasonic and electromagnetic flow meters operate on different principles, resulting in varying accuracy under varying flow rates, water depths, and water pressures. Therefore, it is necessary to develop an accuracy assessment model tailored to the type of monitoring equipment. These models are typically developed based on extensive experimental data and theoretical analysis, and they describe the relationship between the equipment's accuracy and water flow parameters.

[0117] The third step is to input the water flow state parameters at the installation location into the accuracy evaluation model, and combine them with the performance parameters of the equipment itself to obtain the monitoring accuracy of the monitoring equipment.

[0118] Optionally, the water flow parameters at the installation location are input into the accuracy evaluation model, taking into account the device's performance parameters (such as accuracy level and measurement range). The evaluation model comprehensively calculates the monitoring device's accuracy under the current flow conditions based on the input water flow parameters and device performance parameters. For example, when the water flow rate exceeds the device's measurement range, monitoring accuracy will drop significantly.

[0119] 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:

[0120] The first step is to use a spatial analysis algorithm to generate multiple optional installation locations for the monitoring equipment based on the dam's topography, water flow distribution, and the monitoring range of the monitoring equipment, and / or use hydraulic principles and engineering experience, as well as the drainage pipe diameter and slope in the drainage design parameters, to generate multiple optional drainage design parameters for the dam.

[0121] Optional Geographic Information System (GIS) analysis: Using GIS software, import dam topographic data and flow simulation data. Using spatial analysis capabilities, identify areas with significant flow variations and critical impacts on dam safety. Based on the monitoring range of the monitoring equipment, suitable locations within and around these areas are selected as potential installation locations. Mathematical modeling and optimization: Develop a mathematical model of the dam topography and flow, transform the monitoring range into mathematical constraints, and use optimization algorithms (such as genetic algorithms and simulated annealing) to determine the optimal installation location that meets the monitoring requirements.

[0122] Optional hydraulic calculations and trial-and-error methods: Based on basic hydraulic formulas, such as the Manning equation, hydraulic calculations are performed for different pipe diameter and slope combinations to simulate water flow within the drainage system. By adjusting parameters and conducting trial and error, the optimal combination of drainage design parameters is found that maximizes drainage flow, maintains a reasonable flow velocity, and avoids excessive scouring or siltation. Numerical simulation and optimization: A numerical model of the dam drainage system is constructed using professional hydraulic numerical simulation software, such as MIKE and SWMM. Current design parameters and flow conditions are input, and the software simulates flow with various parameter adjustments. Combined with optimization algorithms, the optimal optional drainage design parameters are automatically searched for, with optimization objectives such as drainage efficiency and flow stability.

[0123] The second step is to update the installation position of the monitoring equipment and / or update the drainage design parameters of the dam drainage structure according to the multiple optional installation positions of the monitoring equipment and the multiple optional drainage design parameters of the dam.

[0124] In one implementation, multiple-scenario evaluation and decision-making involves conducting a detailed evaluation of the multiple generated alternative installation locations and drainage design parameter options, taking into account factors such as monitoring effectiveness, construction difficulty, cost, and impact on the dam structure. Multi-attribute decision-making methods such as the Analytic Hierarchy Process (AHP) and the Fuzzy Comprehensive Evaluation Method (Fuzzy Comprehensive Evaluation Method) can be used to score and rank the options, selecting the one with the best overall performance for update. Stepwise iterative optimization involves first selecting a few representative alternative installation locations and drainage design parameters for small-scale experimental updates. The actual results are then monitored, and the options are adjusted and optimized based on the feedback data. Through multiple iterations, the final update plan is gradually determined to reduce risk and ensure that the updated system achieves the expected performance.

[0125] In another possible implementation, updating the installation location of the monitoring device and / or updating the drainage design parameters of the dam drainage structure according to the optional installation location of the monitoring device and the optional drainage design parameters of the dam includes:

[0126] The first step is to generate multiple adjustment plans based on multiple optional installation positions of the monitoring equipment and multiple optional drainage design parameters of the dam.

[0127] Optional, full permutation and combination: All the optional installation locations of all monitoring equipment and the optional drainage design parameters of the dam are fully permuted and combined to obtain all possible adjustment schemes. This method can ensure that all potential combinations are taken into account, but when the number of optional installation locations and optional drainage design parameters is large, the number of schemes will increase sharply and the amount of calculation will be large. Rule-based screening and combination: According to some prior knowledge or empirical rules, the optional installation locations and optional drainage design parameters are screened and combined. For example, priority is given to installation locations with high correlation with key water flow areas, or a combination of design parameters that can ensure drainage efficiency within a certain range is selected to reduce the number of unnecessary schemes and improve the efficiency of subsequent evaluations.

[0128] The second step is to substitute each adjustment scheme into the fluid dynamics model again to determine the accuracy improvement effect of multiple adjustment schemes on the monitoring equipment.

[0129] Optional: Numerical simulation software: Utilize professional fluid dynamics numerical simulation software (such as Fluent, Flow-3D, etc.) to input the parameters of each adjustment scheme into the software for simulation calculations. These software have powerful computing capabilities and a rich set of physical models, which 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 fluid dynamics model can be used for evaluation. For example, using a one-dimensional or two-dimensional shallow water equation model, by writing a simple calculation program, the water flow state parameters under each adjustment scheme can be quickly obtained, and then the effect of improving the accuracy of the monitoring equipment can be evaluated.

[0130] Step 3: Update the installation location of the monitoring equipment and / or update the drainage design parameters of the dam drainage structure based on the adjustment plan that best improves accuracy.

[0131] Optional, quantitative evaluation metrics: Establish clear quantitative evaluation metrics to measure the effectiveness of improving monitoring equipment accuracy, such as the reduction in monitoring error and the improvement in monitoring data stability. Score each adjustment plan based on these metrics, and select the one with the highest score as the optimal solution. Multi-objective optimization: In addition to improving monitoring equipment accuracy, other objectives can also be considered, such as the implementation cost of the adjustment plan and its impact on the existing dam structure. Use a multi-objective optimization algorithm (such as NSGA-II or MOPSO) to balance and optimize multiple objectives, and select the solution with the best overall performance for the update.

[0132] In an exemplary embodiment, the safety monitoring of a dam is performed based on monitoring equipment with updated installation locations and / or a dam drainage structure with updated drainage design parameters, including:

[0133] The first step is to predict the predicted dam flow conditions based on historical meteorological data.

[0134] Among them, the current predicted dam water flow conditions include predicted dam water flow conditions.

[0135] Optionally, a meteorological-hydraulic condition relationship model can be established: A large amount of historical meteorological data and corresponding dam hydraulic survey data can be collected and used to establish a relationship model between the two using data mining techniques (such as regression analysis and neural networks). The model can be used to predict rainfall and flow conditions at the dam by inputting current meteorological data. Combined with numerical simulations: To predict dam flow conditions, a hydraulic numerical model can be combined with predicted rainfall conditions and information about the dam's topography and landforms to simulate water flow at the dam during rainfall, resulting in more accurate flow condition predictions.

[0136] The second step is to identify the structural weakness layer of the monitoring equipment under the predicted dam water flow conditions from each equipment structure layer of the monitoring equipment.

[0137] Among them, each equipment structure layer includes a surface protection layer, and / or an interface guide layer, and / or a cavity protection layer of the monitoring equipment.

[0138] Optionally, the surface protection layer is a bionic fractal hydrophobic structure provided on the outer shell of the monitoring device. The interface guide 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.

[0139] It's understood that the surface protection layer (bionic fractal hydrophobic structure) has the following functions: Reduces water adhesion: The bionic fractal hydrophobic structure mimics the super-hydrophobic surface structure of natural lotus leaves. This structure has extremely high surface energy anisotropy, causing water to form beads on the device surface, significantly reducing the contact area between the water and the device surface. This reduces water adhesion to the device surface, prevents water from soaking the device surface, and avoids corrosion, rust, and other problems caused by long-term water contact.

[0140] The interface guide layer (spiral involute drainage channel) has the following functions: Efficient drainage: The spiral involute drainage channel arranged along the circumference of the monitoring device can use the characteristics of the spiral structure to guide water flow along a specific path, allowing water to drain more smoothly from the device surface. This design prevents water from accumulating on the device surface, shortens the time it soaks in water, and reduces the possibility of water damage to the device.

[0141] The cavity protection layer (dynamic pressure compensation chamber) provides the following pressure balancing functions: A dynamic pressure compensation chamber is constructed around the monitoring device's electronics compartment to balance the pressure inside and outside the compartment. When the external water pressure changes, the chamber automatically adjusts its internal pressure to match the external pressure, protecting the electronic components and circuitry within the compartment from pressure differences. This prevents pressure imbalances that could cause device deformation, seal failure, or damage to electronic components.

[0142] Optional, Finite Element Analysis: Perform finite element modeling on each structural layer of the monitoring equipment to simulate the stress and strain distribution of each structural layer under different predicted dam water flow conditions, and identify the structural weak layer by analyzing these results.

[0143] The third step is to generate an environmental adaptation strategy for the structural weakness layer based on the predicted dam flow conditions. This strategy includes the surface energy distribution corresponding to the surface protection layer, the curvature radius of the channel cross section corresponding to the interface diversion layer, and / or the internal pressure of the cavity corresponding to the cavity protection layer.

[0144] Optionally, the surface energy distribution exhibits a negatively correlated gradient relationship with the local water velocity in the predicted dam flow conditions. The radius of curvature of the channel cross section satisfies an adaptive relationship with the kinetic energy parameter in the predicted dam flow conditions. The internal pressure of the cavity and the external water pressure in the predicted dam flow conditions form a nonlinear feedback regulation mechanism.

[0145] It is understandable that the surface energy distribution has a negative gradient correlation with the local water velocity: according to the principles of fluid mechanics, the faster the water velocity, the greater the impact and erosion on the surface of the object. By making the surface energy distribution of the surface protective layer have a negative gradient correlation with the local water velocity, the surface energy can be lowered in areas with high water velocity, increasing the contact angle between water and the surface, reducing water adhesion and erosion on the surface, and utilizing the hydrophobic principle to reduce water damage to the equipment surface, thus protecting the monitoring equipment.

[0146] The relationship between the channel cross-sectional curvature radius and the kinetic energy parameters of the water flow: The greater the kinetic energy of the water flow, the greater the impact force and ability to carry impurities. The cross-sectional curvature radius of the interface guide layer is adapted to the kinetic energy parameters of the water flow to enable the drainage channel to properly guide the water flow according to its energy state. This avoids excessive pressure fluctuations, eddies, or blockages caused by an inappropriate curvature radius, ensuring smooth drainage and reducing erosion and corrosion of equipment.

[0147] A nonlinear feedback regulation mechanism for the cavity's internal pressure and external water pressure: The external water pressure surrounding the monitoring equipment varies with the predicted dam flow conditions. Increased external water pressure can damage internal structures such as the equipment's electronics compartment. By establishing a nonlinear feedback regulation mechanism for the cavity's internal pressure and external water pressure, the cavity's internal pressure can be adaptively adjusted based on changes in external water pressure to balance the external pressure, protecting the electronic components and other equipment within the electronics compartment and preventing damage due to pressure differentials.

[0148] Surface energy distribution design: First, detailed measurements and analysis of water velocity at different locations on the dam were conducted to establish a water velocity distribution model. Then, based on the negative gradient relationship, the material composition and microstructure of the surface protective layer were designed. For example, in areas with higher water velocity, low-surface-energy materials such as fluoropolymers were used. By adjusting the coating thickness and surface roughness, regions with lower surface energy were created. In areas with lower water velocity, the surface energy of the material was appropriately increased to ensure overall stability and functionality of the device surface.

[0149] Channel cross-sectional curvature radius design: First, measure and calculate the kinetic energy parameters of the predicted dam flow conditions, including velocity, flow rate, and water density. Based on these parameters and incorporating hydrodynamic equations from fluid mechanics, design the cross-sectional curvature radius of the interface guide layer. For example, in areas with high kinetic energy, a larger curvature radius is designed to ensure smooth flow through the drainage channel. In areas with lower kinetic energy, the curvature radius is appropriately reduced, but ensure that the channel does not become clogged or create excessive flow resistance due to an excessively small curvature radius.

[0150] Internal cavity pressure regulation: A pressure sensor and pressure regulating device are installed in the cavity protective layer of the monitoring equipment. The pressure sensor monitors changes in external water pressure in real time and transmits the signal to the control system. The control system adjusts the pressure inside the cavity by controlling pressure regulating devices such as small air pumps and hydraulic devices based on a preset nonlinear feedback regulation mechanism. For example, when the external water pressure increases rapidly, the control system causes the internal cavity pressure to increase rapidly in a nonlinear manner to adapt more quickly to external pressure changes and protect the electronic compartment. When the external water pressure changes slightly, the adjustment of the internal cavity pressure is also relatively smooth, preventing frequent fluctuations in internal pressure from affecting the equipment.

[0151] Step 4: Based on the updated monitoring equipment at the installation location and / or the updated drainage design parameters of the dam drainage structure, control the monitoring equipment and adopt an environmental adaptation strategy to monitor the safety of the dam.

[0152] Optionally, the control monitoring equipment adopts the generated environmental adaptation strategy, which can make the monitoring equipment work in the best state under the predicted dam water flow conditions, improve the accuracy and reliability of its monitoring data, and thus better monitor the safety of the dam and timely discover potential safety hazards.

[0153] In an exemplary embodiment, identifying, from each device structure layer of the monitoring device, a structural weakness layer of the monitoring device under predicted dam water flow conditions includes:

[0154] The first step is to obtain a sample data set, which includes the water flow conditions of each sample dam and the status information of each structural layer of the monitoring equipment under the water flow conditions of each sample dam.

[0155] The status information includes attribute status information of each attribute.

[0156] Optional: Data collection and organization: Establish a data collection system to continuously collect status information of each structural layer of the survey equipment under different water conservancy survey conditions, including various attribute status information such as the wear of the surface protective layer, the blockage of the interface diversion layer, and the pressure stability of the cavity protective layer. This information is then organized into a sample data set together with the corresponding water conservancy survey condition data to ensure data accuracy and completeness.

[0157] In the second step, the association rule mining algorithm is used to analyze the water flow conditions of each sample dam and the status information of each structural layer of the monitoring equipment under each sample dam water flow condition, and the possible probability of weaknesses in each structural layer of the monitoring equipment under the predicted dam water flow conditions is determined.

[0158] Optionally, select an appropriate association rule mining algorithm, such as the Apriori algorithm or the FP-growth algorithm. Format the water conservancy survey conditions and equipment structure layer status information in the sample dataset to meet the algorithm's input requirements. Then, by setting appropriate support and confidence thresholds, run the algorithm to mine association rules between the water conservancy survey conditions and the status of each structure layer, thereby determining the probability of weaknesses in each structure layer under the current water conservancy survey conditions.

[0159] The third step is to identify the structural weakness layer of the monitoring equipment under the predicted dam water flow conditions from the various equipment structural layers of the monitoring equipment based on the possible probability of the occurrence of weaknesses in the various equipment structural layers of the monitoring equipment under the predicted dam water flow conditions.

[0160] Optionally, a threshold can be set based on the probability of weaknesses in each structural layer, as derived from the association rule mining algorithm. When the probability of a weakness in a structural layer exceeds the threshold, it is identified as a structural weakness layer. Re-analysis and identification can be performed periodically or in real time based on new water conservancy survey conditions and updated sample datasets to adapt to changing circumstances.

[0161] In an exemplary embodiment, based on the above-mentioned dam safety monitoring method, this embodiment provides a dam safety monitoring system, which includes:

[0162] An acquisition module 11 is used to obtain historical rainfall data, topographic data and installation locations of monitoring equipment of the dam;

[0163] a simulation module 12 for inputting historical rainfall data and terrain data into a fluid dynamics model to simulate a simulated flow path of rainwater;

[0164] a performance evaluation module 13 for predicting 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;

[0165] A monitoring adjustment module 14 is configured to update the installation location of the monitoring device 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;

[0166] The monitoring module 15 is used to perform safety monitoring on the dam based on the monitoring equipment with updated installation locations and / or the dam drainage structure with updated drainage design parameters.

[0167] In an exemplary embodiment, this embodiment further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0168] Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment;

[0169] Historical rainfall data and topographic data were input into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0170] Predict the accuracy of monitoring equipment based on simulated flow paths, drainage design parameters of the dam drainage structure, and the installation location of monitoring equipment;

[0171] If it is determined that the monitoring accuracy is less than the accuracy threshold, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure;

[0172] The dam safety is monitored based on the updated monitoring equipment installation location and / or the updated drainage design parameters of the dam drainage structure.

[0173] In an exemplary embodiment, this embodiment further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the following steps are implemented:

[0174] Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment;

[0175] Historical rainfall data and topographic data were input into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0176] Predict the accuracy of monitoring equipment based on simulated flow paths, drainage design parameters of the dam drainage structure, and the installation location of monitoring equipment;

[0177] If it is determined that the monitoring accuracy is less than the accuracy threshold, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure;

[0178] The dam safety is monitored based on the updated monitoring equipment installation location and / or the updated drainage design parameters of the dam drainage structure.

[0179] In an exemplary embodiment, this embodiment further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0180] Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment;

[0181] Historical rainfall data and topographic data were input into a fluid dynamics model to simulate the simulated flow path of rainwater;

[0182] Predict the accuracy of monitoring equipment based on simulated flow paths, drainage design parameters of the dam drainage structure, and the installation location of monitoring equipment;

[0183] If it is determined that the monitoring accuracy is less than the accuracy threshold, updating the installation location of the monitoring equipment and / or updating the drainage design parameters of the dam drainage structure;

[0184] The dam safety is monitored based on the updated monitoring equipment installation location and / or the updated drainage design parameters of the dam drainage structure.

[0185] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the 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-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this 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), magnetic 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 take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0186] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, 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, they should be considered to be within the scope of this application.

[0187] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A dam safety monitoring method, characterized in that: The method comprises: Obtain historical rainfall data for the dam, topographic data, and the locations of monitoring equipment; inputting the historical rainfall data and the terrain data into a fluid dynamics model to simulate a simulated flow path of rainwater; predicting the monitoring accuracy of the monitoring device based on the simulated flow path, drainage design parameters of the dam drainage structure, and the installation location of the monitoring device; If it is determined that the monitoring accuracy is less than an accuracy threshold, updating the installation position of the monitoring device and / or updating the drainage design parameters of the dam drainage structure; identifying, from each device structure layer of the monitoring device, a structural weakness layer of the monitoring device under the predicted dam water flow condition; generating an environmental adaptation strategy corresponding to the structural weakness layer according to the predicted dam water flow condition; Based on the monitoring equipment with updated installation locations and / or the dam drainage structure with updated drainage design parameters, controlling the monitoring equipment and adopting the environmental adaptation strategy to perform safety monitoring on the dam; Each device structure layer of the monitoring device includes: The surface protection layer is a bionic fractal hydrophobic structure provided on the housing of the monitoring device; An interface guide layer is a spiral involute drainage channel arranged along the circumference of the monitoring device; a cavity protection layer, which is a dynamic pressure compensation cavity constructed around the electronic compartment of the monitoring device; The environmental adaptation strategy includes the surface energy distribution corresponding to the surface protection layer, and / or the channel cross-section curvature radius corresponding to the interface guide layer, and / or the cavity internal pressure corresponding to the cavity protection layer; The surface energy distribution of the surface protective layer is negatively correlated with the local water flow velocity in the predicted dam water flow conditions; the channel cross-section curvature radius of the interface guide layer satisfies the adaptation relationship with the water kinetic energy parameters in the predicted dam water flow conditions; the internal pressure of the cavity protective layer and the external water pressure in the predicted dam water flow conditions form a nonlinear feedback regulation mechanism.

2. The method according to claim 1, characterized in that The fluid dynamics model includes a continuity equation and a momentum equation for describing water flow movement; the historical rainfall data and the terrain data are input into the fluid dynamics model to simulate the flow path of rainwater, including: Initializing and setting the model parameters of the fluid dynamics model according to the actual conditions of the dam; the model parameters include density, viscosity, surface roughness and boundary conditions of the water flow; converting the historical rainfall data into lateral inflow parameters in the fluid dynamics model, and determining the gridded terrain data as channel bottom slope parameters in the fluid dynamics model; The fluid dynamics model is numerically solved using a finite difference method, and the water flow parameters of each grid cell are updated in each time step; the water flow parameters include flow direction and velocity; The simulated flow path of rainwater is determined based on the flow direction and speed of rainwater between each grid unit.

3. The method according to claim 1, characterized in that The predicting of 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 includes: Calculating the water flow state parameters at the installation location of the monitoring device based on the simulated flow path and the drainage design parameters of the dam drainage structure by applying the principles of water flow continuity and energy conservation; the water flow state parameters include flow velocity, water depth, and water pressure; obtaining an accuracy assessment model based on the type of the monitoring device; 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.

4. The method according to claim 1, wherein The updating of the installation position of the monitoring device and / or the updating of the drainage design parameters of the dam drainage structure include: Generate multiple optional installation locations for the monitoring equipment using a spatial analysis algorithm based on the topography and water flow distribution of the dam and the monitoring range of the monitoring equipment; and / or generating a plurality of optional drainage design parameters for the dam using hydraulic principles and engineering experience, as well as the drainage pipe diameter and slope in the drainage design parameters; According to the multiple optional installation positions of the monitoring equipment and the multiple optional drainage design parameters of the dam, the installation position of the monitoring equipment is updated, and / or the drainage design parameters of the dam drainage structure are updated.

5. The method according to claim 4, characterized in that The updating of the installation position of the monitoring device and / or the drainage design parameters of the dam drainage structure according to the multiple optional installation positions of the monitoring device and the multiple optional drainage design parameters of the dam includes: generating a plurality of adjustment plans according to a plurality of optional installation positions of the monitoring equipment and a plurality of optional drainage design parameters of the dam; Substituting each adjustment scheme into the fluid dynamics model again to determine the effect of each adjustment scheme on improving the accuracy of the monitoring device; According to the adjustment plan with the best accuracy improvement effect, the installation position of the monitoring equipment is updated, and / or the drainage design parameters of the dam drainage structure are updated.

6. The method according to claim 1, characterized in that The step of identifying, from each device structure layer of the monitoring device, a structural weakness layer of the monitoring device under the predicted dam water flow condition, comprises: forecasting a predicted dam flow condition for the dam based on historical meteorological data for the dam; From each device structure layer of the monitoring device, a structural weakness layer of the monitoring device under the predicted dam water flow condition is identified.

7. The method according to claim 6, characterized in that The step of identifying, from each device structure layer of the monitoring device, a structural weakness layer of the monitoring device under the predicted dam water flow condition, comprises: Acquire a sample data set, wherein the sample data set includes water flow conditions of each sample dam and status information of each structural layer of the monitoring device under the water flow conditions of each sample dam; the status information includes attribute status information of each attribute; By using an association rule mining algorithm, the water flow conditions of each sample dam and the status information of each structural layer of the monitoring equipment under each sample dam water flow condition are analyzed to determine the possible probability of the occurrence of weaknesses in each structural layer of the monitoring equipment under the predicted dam water flow condition; According to the possible probability of occurrence of weaknesses in each structural layer of the monitoring equipment under the predicted dam water flow condition, the structural weakness layer of the monitoring equipment under the predicted dam water flow condition is identified from each device structural layer of the monitoring equipment.

8. A dam safety monitoring system, characterized in that: The system comprises: An acquisition module is used to obtain the historical rainfall data of the dam, terrain data and the installation location of monitoring equipment; a simulation module, configured to input the historical rainfall data and the terrain data into a fluid dynamics model to simulate a simulated flow path of rainwater; a performance evaluation module for predicting the monitoring accuracy of the monitoring device based on the simulated flow path, drainage design parameters of the dam drainage structure, and the installation location of the monitoring device; a monitoring adjustment module, configured to update the installation position of the monitoring device and / or update the drainage design parameters of the dam drainage structure when it is determined that the monitoring accuracy is less than an accuracy threshold; A monitoring module, configured to identify, from each device structure layer of the monitoring device, a structural weakness layer of the monitoring device under the predicted dam water flow condition; generating an environmental adaptation strategy corresponding to the structural weakness layer according to the predicted dam water flow condition; Based on the monitoring equipment with updated installation locations and / or the dam drainage structure with updated drainage design parameters, controlling the monitoring equipment and adopting the environmental adaptation strategy to perform safety monitoring on the dam; Each device structure layer of the monitoring device includes: The surface protection layer is a bionic fractal hydrophobic structure provided on the housing of the monitoring device; An interface guide layer is a spiral involute drainage channel arranged along the circumference of the monitoring device; a cavity protection layer, which is a dynamic pressure compensation cavity constructed around the electronic compartment of the monitoring device; The environmental adaptation strategy includes the surface energy distribution corresponding to the surface protection layer, and / or the channel cross-section curvature radius corresponding to the interface guide layer, and / or the cavity internal pressure corresponding to the cavity protection layer; The surface energy distribution of the surface protective layer is negatively correlated with the local water flow velocity in the predicted dam water flow conditions; the channel cross-section curvature radius of the interface guide layer satisfies the adaptation relationship with the water kinetic energy parameters in the predicted dam water flow conditions; the internal pressure of the cavity protective layer and the external water pressure in the predicted dam water flow conditions form a nonlinear feedback regulation mechanism.

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