A bank-dam linkage safety risk dynamic assessment method, device and medium

Abstract

The application discloses a kind of reservoir bank-dam linkage security risk dynamic evaluation methods, comprising: obtaining dam GNSS deformation monitoring data and reservoir bank slope InSAR monitoring data, utilize GNSS data to InSAR data is carried out atmospheric delay error correction and coordinate system projection;Based on GNSS monitoring data constructs dam deformation statistical model and according to model deformation residual inversion is used to reflect the real-time health resistance factor of dam current structure intensity;Utilize InSAR monitoring data to identify reservoir bank potential landslide hidden danger area, calculate potential maximum surge impact load conducted to dam front under instability working condition of hidden danger area.Potential maximum surge impact load and the static water pressure load that dam is currently bearing are superposed, form extreme condition total load, and combined with real-time health resistance factor calculate reservoir bank-dam linkage risk index, finally carry out safety early warning.The application can realize the precise dynamic evaluation of watershed level reservoir bank-dam system security risk.

Description

Technical Field

[0001] This invention relates to the field of water conservancy project safety monitoring technology, specifically to a method, equipment, and storage medium for dynamic assessment of reservoir bank-dam linkage safety risks based on the spatiotemporal fusion of InSAR (Synthetic Aperture Radar Interferometry) and GNSS (Global Navigation Satellite System). Background Technology

[0002] As a large hydraulic structure that relies on its own weight to maintain stability, the safety of concrete gravity dams is directly related to the safety of people's lives and property downstream. As the operating years of large reservoirs increase, the structural performance of the dam will gradually degrade.

[0003] Currently, monitoring of dam safety mainly relies on point sensors such as GNSS and plumb line coordinate instruments, which assess the health status of the dam by analyzing changes in physical quantities such as dam deformation and seepage.

[0004] However, the safety of a dam depends not only on its own structural condition, but also on the significant influence of the reservoir area environment, especially the stability of the reservoir bank slopes, which is an important external risk source threatening dam safety.

[0005] Under conditions such as extreme rainstorms or sudden drops in reservoir water levels, reservoir bank slopes are highly susceptible to landslides. If the massive impact wave generated by the landslide enters the water and propagates to the front of the dam, it will exert a huge additional hydrodynamic pressure on the dam. If the dam itself is operating at a high water level or has minor structural damage, this superimposed load can easily induce a dam failure disaster.

[0006] Existing monitoring methods suffer from a significant "island effect": dam monitoring systems only focus on the deformation of the dam itself and cannot detect the risks of reservoir bank slopes; while slope monitoring systems (such as InSAR or GPS) only focus on the displacement of landslide bodies and cannot quantify the specific threats they pose to the dam.

[0007] Furthermore, most existing safety assessment methods are based on static indicators of a single object, lacking a dynamic assessment mechanism that can physically couple "potential landslide risk on reservoir banks" with "real-time structural status of the dam," making it difficult to cope with systemic risks caused by complex disaster chains.

[0008] Therefore, this application proposes a dynamic assessment method for the safety risks of reservoir bank-dam linkage to solve the above-mentioned technical problems. Summary of the Invention

[0009] The main objective of this invention is to provide a dynamic risk assessment method for the linkage between reservoir bank and dam. By integrating the area monitoring advantages of InSAR with the point-based high-precision advantages of GNSS, a physical transmission model is established from "reservoir bank instability" to "dam loading". This enables dynamic risk assessment of the dam under potential extreme disaster chain conditions, thereby solving the technical problems mentioned in the background art.

[0010] The present invention solves the above-mentioned technical problems by adopting the following technical solutions: A dynamic assessment method for the safety risks of reservoir bank-dam linkage is implemented using computer equipment, comprising the following steps: Step S1. Acquire GNSS deformation monitoring data of the dam and InSAR monitoring data of the reservoir bank slope. Use GNSS data to perform atmospheric delay error correction and coordinate system projection on InSAR data to achieve spatiotemporal reference unification of multi-source data. Step S2. Construct a statistical model of dam deformation based on GNSS monitoring data. First, fit the regression coefficients and then substitute them into the model to remove the elastic influence of water level and temperature components. Calculate the difference between the displacement and the measured displacement as the model deformation residual. Then, based on the model deformation residual, obtain the real-time health resistance factor that reflects the current structural strength of the dam. Step S3. Identify potential landslide hazard areas on the reservoir bank using InSAR monitoring data. Based on the geometric characteristics of the hazard areas and the existing landslide-surge physical transmission model, calculate the potential maximum surge impact load transmitted to the front of the dam under the unstable working condition of the hazard areas. Step S4. The potential maximum surge impact load is superimposed with the hydrostatic pressure load currently borne by the dam to form the total load under extreme conditions. The reservoir bank-dam linkage risk index is calculated in combination with the real-time health resistance factor. Finally, a safety warning is issued based on the reservoir bank-dam linkage risk index.

[0011] Preferably, the specific operation procedure for performing atmospheric delay error correction and coordinate system projection on InSAR data in step S1 includes: Using stable GNSS reference stations deployed on the bedrock on both sides of the dam as ground control points, the atmospheric phase delay error of InSAR imagery is calculated to obtain the line-of-sight deformation of the corrected InSAR imagery data. ; By correcting line-of-sight deformation in InSAR image data When projecting onto a horizontal or sloping surface, the projection formula is as follows:

[0012] in, This represents the actual deformation value of the ground surface after projection (such as displacement along the slope direction). The angle of incidence of the InSAR satellite radar wave. This is the angle between the InSAR satellite's flight azimuth and the slope aspect. Finally, after projection, the InSAR deformation data of the reservoir bank are unified to a local engineering coordinate system centered on the dam. Preferably, the statistical model for dam deformation in step S2 is constructed using a water pressure-season-time (HST) model, expressed as:

[0013] in, for The radial displacement value of the dam monitored by GNSS at all times. for The reservoir water level at any given time for The ambient temperature at any given time For monitoring time, To specify the regression coefficients, This represents the model deformation residual.

[0014] Preferably, the specific calculation formula for obtaining the real-time health resistance factor in step S2 is as follows:

[0015]

[0016] in, for The normalized health resistance factor obtained from the dam inversion has a value range of [value range missing]. , for Time-deformation residuals of the model The absolute value, This is a preset allowable residual threshold, used to characterize the maximum deviation within the structural elastic limit. This is the upper cutoff value for the health decay factor. To measure the radial displacement of the dam, Construct a predicted radial displacement of the dam for the water pressure-season-time (HST) model.

[0017] Preferably, the specific identification process of identifying potential landslide hazard areas on the reservoir bank using InSAR monitoring data and the calculation process of the geometric features of the hazard areas in step S3 include: Spatial clustering analysis was performed on the spatiotemporally corrected InSAR deformation field data using the DBSCAN algorithm to identify connected regions with deformation rates exceeding the safety threshold (5 mm / year) and mark them as "potential landslide hazard areas". By combining the digital elevation model (DEM) of the reservoir bank, the total volume of the potential landslide mass is estimated using an empirical formula for landslide thickness. The volume estimation formula is expressed as:

[0018] in, The potential landslide volume is estimated based on the InSAR deformation area. Area of ​​the deformed region identified by InSAR. This represents the average thickness of the landslide mass. and This is a specified geological experience coefficient for the region.

[0019] Preferably, the inference formula for the potential maximum surge impact load in step S3 is as follows:

[0020]

[0021] in, To determine the potential surge height transmitted to the front of the dam, This represents the straight-line distance from the center of the potential landslide hazard zone to the dam. This represents the initial maximum surge height at the landslide entry point, which is related to the landslide's entry velocity into the water and the Froude number. The average width of the reservoir area. The angle between the direction of the landslide entering the water and the normal direction of the dam axis. The surge attenuation index, The potential maximum surge impact load is calculated using the hydrodynamic pressure load formula. For the density of water, It is the acceleration due to gravity. This is the hydrodynamic pressure conversion coefficient.

[0022] Preferably, the specific calculation formula for the reservoir-dam linkage risk index in step S4 is as follows:

[0023] in, for The reservoir-dam linkage risk index at any given time is a dimensionless risk index. Current reservoir water level The corresponding hydrostatic pressure load, The potential maximum surge height The corresponding hydrodynamic pressure load, The ultimate load-bearing capacity of the dam. for Normalized health resistance factors obtained from the dam inversion.

[0024] Preferably, the security warning in step S4 adopts the following hierarchical warning mechanism: for The risk index of reservoir bank-dam linkage at any time : when When the dam area is deemed a safe operating zone (green), it means that even if a landslide occurs, the dam has sufficient capacity to withstand it. when At that time, the dam area was identified as an early warning concern area (orange), indicating an increase in reservoir bank risk or a decline in dam health, and monitoring frequency should be increased; when When the area is designated as an extremely high-risk zone (red), it indicates that if a landslide occurs on the reservoir bank, the dam faces an extremely high risk of collapse, and the emergency response plan must be activated immediately.

[0025] In another aspect, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0026] In another aspect, the present invention also discloses a computer device, including a data acquisition module, a memory, and a processor. The data acquisition module is used to acquire GNSS and InSAR monitoring data. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the method described above.

[0027] As can be seen from the above technical solution, the present invention provides a dynamic assessment method for the safety risks of reservoir bank-dam linkage. Compared with the prior art, the present invention has the following advantages: 1. This invention establishes a linkage assessment system for the reservoir bank-surge-dam disaster chain, breaking the limitations of traditional isolated monitoring of dams and reservoir bank slopes. It can quantify reservoir bank landslide hazards into surge loads and couple them with the dam structural status for analysis, thereby achieving accurate and dynamic assessment of the safety risks of the basin-level reservoir bank-dam system.

[0028] 2. This invention solves the core problem of the lag in traditional solutions that rely solely on measured values ​​for alarms by constructing a dynamic early warning mechanism that combines measured structural health with potential surge loads. It can predict risks in advance and dynamically adjust safety thresholds before landslide impacts occur, thereby significantly improving the foresight and timeliness of safety early warning.

[0029] 3. This invention utilizes the high-precision GNSS of the dam as control points to correct InSAR data, which can solve the problems of InSAR data being greatly affected by atmospheric errors and the small spatial coverage of GNSS. This further facilitates the accurate identification of minor deformations of the reservoir bank and eliminates monitoring blind spots, ultimately greatly improving the accuracy and coverage efficiency of reservoir bank and dam deformation monitoring.

[0030] It should be understood that the descriptions in this section are not intended to identify key or essential features of embodiments of the invention, nor are they intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Of course, implementing any product of the invention does not necessarily require achieving all of the advantages described above simultaneously. Attached Figure Description

[0031] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a schematic diagram of the spatial distribution of multi-source monitoring of the dam-reservoir bank based on InSAR and GNSS in an embodiment of the present invention; Figure 3 This is a diagram showing the inversion results of dam structure response feature extraction and real-time health status in an embodiment of the present invention; Figure 4 This is a schematic diagram of the coupled evolution model of reservoir bank landslide-wave-dam load in an embodiment of the present invention; Figure 5 This is a dynamic assessment result diagram of the dam linkage safety risk based on multi-source data fusion in an embodiment of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] For details in the embodiments, please refer to Figures 1 to 5 .

[0034] like Figure 1 As shown, considering the characteristics of InSAR data being greatly affected by atmospheric errors and the small spatial coverage of GNSS, the dynamic assessment method for reservoir bank-dam linkage safety risks proposed in this embodiment of the invention takes a large concrete gravity dam and its upstream reservoir bank area as the research object. Since there are significant differences between dam deformation monitoring data (GNSS) and reservoir bank slope monitoring data (InSAR) in terms of acquisition principles, spatial references, and temporal resolution, multi-source data fusion processing must be performed first. Therefore, this embodiment specifically includes the following steps: Step S1. Multi-source data acquisition and spatiotemporal benchmark unification: Acquire GNSS deformation monitoring data of the dam and InSAR monitoring data of the reservoir bank slope. Use GNSS data to perform atmospheric delay error correction and coordinate system projection on InSAR data to achieve spatiotemporal reference unification of multi-source data.

[0035] The specific operations include: Step S11. Data Acquisition: (1) GNSS data acquisition for the dam: High-precision GNSS monitoring stations are deployed on the dam crest, dam foundation and both banks to obtain the three-dimensional coordinate sequence of key parts of the dam; The sampling frequency is once a day, and the acquired monitoring data includes the geodetic coordinates of the monitoring points. and the corresponding monitoring time .

[0036] (2) InSAR data acquisition of reservoir bank: Acquire SAR satellite image data covering the reservoir bank area upstream of the dam and extract the phase information of the surface.

[0037] Step S12. Spatial reference unification: Since InSAR acquires deformation along the line of sight (LOS), while GNSS acquires deformation in three-dimensional geographic coordinates, it is necessary to unify the two into the same spatial reference system (a local coordinate system related to the dam axis).

[0038] The specific operations include: Using stable GNSS reference stations deployed on the bedrock on both sides of the dam as ground control points, the atmospheric phase delay error of InSAR imagery is calculated to obtain the line-of-sight deformation of the corrected InSAR imagery data. ; By correcting line-of-sight deformation in InSAR image data When projecting onto a horizontal or sloping surface, the projection formula is as follows:

[0039] in, This represents the actual deformation value of the ground surface after projection (such as displacement along the slope direction). The angle of incidence of the InSAR satellite radar wave. This is the angle between the InSAR satellite's flight azimuth and the slope aspect. Finally, after projection, the InSAR deformation data of the reservoir bank are unified to a local engineering coordinate system centered on the dam.

[0040] Through the above projection, the reservoir bank InSAR deformation data are unified to a local engineering coordinate system centered on the dam, with reference to... Figure 2 This achieved spatial correlation between the monitoring points on the dam itself and the potential landslide sites on the reservoir bank.

[0041] Step S13. Time base alignment: Since the revisit period for InSAR data is 15 days, while GNSS data has a high frequency characteristic (8 hours / data), the two need to be aligned on the time axis to achieve linked analysis.

[0042] The specific operations include: Based on the acquisition time of InSAR images Based on this, the GNSS data sequence is resampled or interpolated; For non-overlapping time points, cubic spline interpolation is used to estimate the dam's GNSS displacement at that time, thereby constructing a time-synchronized monitoring dataset. , For dam displacement, This represents slope displacement.

[0043] Step S2. Extract dam deformation features and perform health status inversion based on GNSS monitoring data: A statistical model of dam deformation was constructed based on GNSS monitoring data. After removing the elastic influence of water level and temperature components, the deformation residuals were extracted, and the real-time health resistance factor reflecting the current structural strength of the dam was obtained by inversion based on the deformation residuals.

[0044] The specific operations include: Step S21. Construct a statistical model for dam deformation by fitting the radial displacement of the dam monitored by GNSS using a water pressure-season-time (HST) model. In this embodiment, the dam deformation is a linear superposition of environmental factors, and its mathematical expression is constructed as follows:

[0045] In the formula, for Fitted values ​​of radial displacement of the dam monitored by GNSS at various times; for The reservoir water level at any given time Indicates the water pressure component; The ambient temperature is represented by sine and cosine terms to indicate the temperature components. As a time-sensitive factor, Indicates time-sensitive components; All of these are regression coefficients to be determined, obtained by training historical monitoring data using the least squares method.

[0046] Step S22. Calculate the predicted displacement at the current time using the trained HST model. and compared with the measured displacement By comparison, the deformation residuals are obtained. The residual is used to reflect the nonlinear deformation portion that could not be explained by water pressure and temperature; At this point, based on the residual sequence, the real-time health resistance factor of the dam is defined. The calculation formula is as follows:

[0047] In the formula, The normalized health resistance factor has a value range of [value range missing]. The closer the value is to 1, the more the dam structure conforms to the elastic law and the healthier its condition. The preset allowable residual threshold (3 times the error); This is the upper limit cutoff value for the health degradation factor (taken as 0.2, indicating that even if the residual is large, the structural resistance will not drop to 0 instantaneously).

[0048] refer to Figure 3 Steps S21-S22 realize the transformation from simple "displacement monitoring" to "structural health measurement", providing basic parameters for the dam side for subsequent risk coupling.

[0049] Step S3. Identify potential landslides on the reservoir bank and simulate surge hazard chains based on InSAR monitoring data: Identifying such as using InSAR monitoring data Figure 2 The potential landslide hazard area shown is used to estimate the maximum potential surge impact height transmitted to the front of the dam under unstable conditions based on the geometric characteristics of the hazard area and the landslide-surge physical transmission model. This is used to further obtain the maximum potential surge impact load.

[0050] The specific operations include: Step S31. Identification and volume estimation of potential landslide hazard areas: The DBSCAN algorithm is used to perform spatial clustering analysis on the spatiotemporally corrected InSAR deformation field data to identify connected regions with deformation rates exceeding the safety threshold (5 mm / year), which are marked as "potential landslide hazard areas". Then, combined with the reservoir bank digital elevation model (DEM), the total volume of the potential landslide body is estimated using an empirical formula for landslide thickness. The volume estimation formula is as follows:

[0051] in, Potential landslide volume ( ); Area of ​​the deformed region identified by InSAR ( ); This represents the average thickness of the landslide mass. and The geological experience coefficient for this area (taken in this embodiment) ).

[0052] Step S32. Calculation of the potential maximum surge height: Pre-identifying potential landslide hazard zones that, under extreme conditions, experience overall instability and slide into the reservoir, the maximum surge height transmitted to the dam is calculated using a semi-empirical formula for landslide surges. The formula for calculating the potential maximum surge height is as follows:

[0053] in, The potential surge height (m) transmitted to the front of the dam. The initial maximum surge height at the point where the landslide enters the water is related to the landslide's entry velocity into the water and the Froude number. The landslide volume estimated in step S31; This represents the average width of the reservoir area; This represents the straight-line propagation distance from the center of the landslide hazard zone to the dam. The angle between the direction of wave propagation and the normal to the dam axis; This is the surge attenuation index.

[0054] Through this step, the present invention will transform the abstract deformation rate patches (such as those detected by InSAR) into... Figure 2 As shown), this can be converted into a specific, quantifiable hydraulic indicator: potential surge height. (like Figure 4 (As shown in the orange area), to achieve the physical quantification of disaster source characteristics.

[0055] in Used for further calculation of the potential maximum surge impact load .

[0056] Step S4. Dynamic assessment of reservoir bank-dam linkage safety risks, used for the final output of graded safety early warning: The maximum potential surge impact load is superimposed with the hydrostatic pressure load currently borne by the dam to form the total load under extreme conditions. The reservoir bank-dam linkage risk index is calculated by combining the real-time health resistance factor, and safety early warning is issued accordingly.

[0057] The specific operations include: Step S41. Construct a total load model for extreme conditions. Since the safety of the dam depends not only on the current hydrostatic pressure but also on the hydrodynamic pressure brought by potential disaster chains, therefore, define... Total load under extreme working conditions faced by the dam For the superposition of static and dynamic loads, we have:

[0058] In the formula, The total water thrust load after conversion (kN / m) Current measured reservoir water level The hydrostatic pressure generated; The potential surge height calculated in step S3 The generated hydrodynamic pressure; For the density of water, It is the acceleration due to gravity; This is the hydrodynamic pressure conversion coefficient. Considering the instantaneous effect of surge impact, this coefficient is usually greater than 1.0 (taken as 1.5).

[0059] At this point, the model data based on the coupled evolution of reservoir bank landslide-wave-dam load is as follows: Figure 4 As shown.

[0060] Step S42. Calculate the linkage risk index and early warning. Based on the "load-resistance" model, introduce the real-time health resistance factor obtained from step S2. The design resistance of the dam is modified to construct a reservoir bank-dam linkage risk index. The calculation formula is as follows:

[0061] In the formula, A dimensionless risk index; The ultimate design capacity of the dam. This represents the current health reduction factor for the dam.

[0062] Step S43. Risk classification and early warning, based on the calculated linkage risk index. Establish a tiered early warning mechanism (such as...) Figure 5 As shown below: when When the dam is in a safe operating zone (green), it is considered to have sufficient capacity to withstand a landslide. when When the area is designated as an orange warning zone, it indicates an increase in reservoir bank risk or a decline in dam health, requiring increased monitoring frequency. when When the area is designated as an extremely high-risk zone (red), it indicates that if a landslide occurs on the reservoir bank, the dam faces an extremely high risk of collapse, and the emergency response plan must be activated immediately.

[0063] It should be noted that since existing early warning systems are mostly based on exceeding the limits of measured values, this invention constructs a dynamic early warning mechanism that combines virtual and real data. This mechanism not only uses GNSS to assess the health status of the dam, but also uses InSAR to estimate the (potential) surge load. This forward-looking early warning mechanism can dynamically adjust the dam's safety threshold based on slope anomalies before the dam is impacted, greatly improving the timeliness of the early warning.

[0064] In addition, the invention utilizes the high-precision GNSS of the dam as control points to correct InSAR data, which significantly improves the ability to identify small deformations of the reservoir bank; at the same time, it uses the wide-area coverage of InSAR to make up for the shortcomings of GNSS in monitoring blind areas of the reservoir bank, and realizes the complementary advantages of multi-source data.

[0065] Through the above steps, this invention breaks through the limitations of single-object monitoring and the isolated mode of "dam managing dam, slope managing slope" in traditional monitoring. It establishes a physical transmission mechanism of the disaster chain of "reservoir bank-surge-dam", realizes the coupled assessment of "current state" and "future potential impact" in the time dimension, and transforms the potential external threats to the reservoir bank into specific load increments and superimposes them on the current structural state of the dam. This provides a more forward-looking and systematic decision-making basis for the safe operation and management of reservoir dams, and realizes a true basin-level system safety assessment.

[0066] In another aspect, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0067] In another aspect, the present invention also discloses a computer device, including a data acquisition module, a memory, and a processor. The data acquisition module is used to acquire GNSS and InSAR monitoring data. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the method described above.

[0068] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the reservoir-bank-dam linkage safety risk dynamic assessment methods described in the above embodiments.

[0069] It is understood that the system provided in the embodiments of the present invention corresponds to the method provided in the embodiments of the present invention, and the explanation, examples and beneficial effects of the relevant content can be referred to the corresponding parts of the above method.

[0070] This application also provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other via the communication bus. Memory, used to store computer programs; When the processor executes the program stored in the memory, it implements the above-mentioned dynamic assessment method for the safety risks of the reservoir bank-dam linkage.

[0071] The communication bus mentioned in the above-mentioned electronic devices can be a standard bus for interconnecting peripheral components or an extended industrial standard structure bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc.

[0072] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0073] The memory may include random access memory or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0074] The processors mentioned above can be general-purpose processors, including central processing units, network processors, etc.; they can also be digital signal processors, application-specific integrated circuits, field-programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0075] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc.

[0076] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0077] Furthermore, it should be noted that if any directional indication (such as up, down, left, right, front, back, etc.) is involved in the embodiments of the present invention, the directional indication is only used to explain the relative positional relationship and movement of each component in a specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0078] Furthermore, those skilled in the art should understand that in the actual use of the embodiments of this application, there may be preset thresholds used as the basis for judging the corresponding technical solutions. These thresholds are conventional technical means commonly used in the field to implement functions such as state judgment, condition recognition, and control logic switching. The specific values, setting basis, value selection methods, determination methods, and adjustment rules of the thresholds involved in this technical solution are all conventional technical choices that can be reasonably determined by those skilled in the art based on conventional technical factors such as actual application scenarios, system working states, characteristics of the detection object, hardware performance parameters, and functional requirements, through conventional experiments, calibrations, and debugging. The specific setting and adjustment of the aforementioned thresholds will not cause this technical solution to be unimplementable as a whole, nor will it affect the realization of the core concept and the achievement of the technical effects of this technical solution.

[0079] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, in the embodiments of this invention, "multiple" refers to two or more. Moreover, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

Claims

1. A dynamic assessment method for the safety risks of reservoir bank-dam linkage, characterized in that, include: Step S1. Acquire GNSS deformation monitoring data of the dam and InSAR monitoring data of the reservoir bank slope, and use GNSS data to perform atmospheric delay error correction and coordinate system projection on InSAR data; Step S2. Construct a statistical model of dam deformation based on GNSS monitoring data. First, fit the regression coefficients and then substitute them into the model to remove the elastic influence of water level and temperature components. Calculate the difference between the displacement and the measured displacement as the model deformation residual. Then, based on the model deformation residual, obtain the real-time health resistance factor that reflects the current structural strength of the dam. Step S3. Identify potential landslide hazard areas on the reservoir bank using InSAR monitoring data. Based on the geometric characteristics of the hazard areas and the existing landslide-surge physical transmission model, calculate the potential maximum surge impact load transmitted to the front of the dam under the unstable working condition of the hazard areas. Step S4. The potential maximum surge impact load is superimposed with the hydrostatic pressure load currently borne by the dam to form the total load under extreme conditions. The reservoir bank-dam linkage risk index is calculated in combination with the real-time health resistance factor. Finally, a safety warning is issued based on the reservoir bank-dam linkage risk index.

2. The dynamic assessment method for reservoir-dam linkage safety risks as described in claim 1, characterized in that, The specific operational procedures for atmospheric delay error correction and coordinate system projection of InSAR data in step S1 include: Using stable GNSS reference stations deployed on the bedrock on both sides of the dam as ground control points, the atmospheric phase delay error of InSAR imagery is calculated to obtain the line-of-sight deformation of the corrected InSAR imagery data. ; By correcting line-of-sight deformation in InSAR image data When projecting onto a horizontal or sloping surface, the projection formula is as follows: in, This represents the actual surface deformation value after projection. The angle of incidence of the InSAR satellite radar wave. This is the angle between the InSAR satellite's flight azimuth and the slope aspect. Finally, after projection, the InSAR deformation data of the reservoir bank are unified to a local engineering coordinate system centered on the dam.

3. The dynamic assessment method for reservoir-dam linkage safety risks as described in claim 1, characterized in that, The statistical model for dam deformation in step S2 is constructed using a water pressure-season-time model, expressed as follows: in, for The radial displacement value of the dam monitored by GNSS at all times. for The reservoir water level at any given time for The ambient temperature at any given time For monitoring time, To specify the regression coefficients, This represents the model deformation residual.

4. The dynamic assessment method for reservoir-dam linkage safety risks as described in claim 3, characterized in that, The specific calculation formula for the real-time health resistance factor obtained in step S2 is as follows: in, for Normalized health resistance factors obtained from dam inversion at any given time for Time-deformation residuals of the model The absolute value, This is a preset allowable residual threshold, used to characterize the maximum deviation within the structural elastic limit. This is the upper cutoff value for the health decay factor. To measure the radial displacement of the dam, Construct a predicted radial displacement of the dam for a water pressure-season-time model.

5. The dynamic assessment method for reservoir-dam linkage safety risks as described in claim 1, characterized in that, The specific identification process of potential landslide hazard areas on the reservoir bank using InSAR monitoring data and the calculation process of the geometric characteristics of the hazard areas in step S3 include: Spatial clustering analysis was performed on the spatiotemporally corrected InSAR deformation field data using the DBSCAN algorithm to identify connected regions with deformation rates exceeding the safety threshold, and these regions were marked as "potential landslide hazard areas". By combining the digital elevation model of the reservoir bank, the total volume of the potential landslide mass is estimated using an empirical formula for landslide thickness. The volume estimation formula is expressed as: in, The potential landslide volume is estimated based on the InSAR deformation area. Area of ​​the deformed region identified by InSAR. This represents the average thickness of the landslide body.

6. The dynamic assessment method for reservoir bank-dam linkage safety risks as described in claim 5, characterized in that, The inference formula for calculating the potential maximum surge impact load in step S3 is as follows: in, To determine the potential surge height transmitted to the front of the dam, This represents the straight-line distance from the center of the potential landslide hazard zone to the dam. This represents the initial maximum surge height at the landslide entry point, which is related to the landslide's entry velocity into the water and the Froude number. The average width of the reservoir area. The angle between the direction of the landslide entering the water and the normal direction of the dam axis. The surge attenuation index, The potential maximum surge impact load is calculated using the hydrodynamic pressure load formula. For the density of water, It is the acceleration due to gravity. This is the hydrodynamic pressure conversion coefficient.

7. The dynamic assessment method for reservoir-dam linkage safety risks as described in claim 6, characterized in that, The specific calculation formula for the reservoir-dam linkage risk index in step S4 is as follows: in, for The reservoir bank-dam linkage risk index at any given time. Current reservoir water level The corresponding hydrostatic pressure load, The potential maximum surge height The corresponding hydrodynamic pressure load, The ultimate load-bearing capacity of the dam. for Normalized health resistance factors obtained from the dam inversion.

8. The dynamic assessment method for reservoir-dam linkage safety risks as described in claim 7, characterized in that, The security warning in step S4 adopts the following hierarchical warning mechanism: for The risk index of reservoir bank-dam linkage at any time : when At that time, the dam area was determined to be a safe operating zone; when At that time, the dam area was determined to be an area of ​​concern for early warning, and the frequency of monitoring should be increased; when If the area is identified as an extremely high-risk area, an emergency response plan must be activated immediately.

9. A computer-readable storage medium, characterized in that, The device stores a computer program that, when executed by a processor, causes the processor to perform the steps of the method as described in any one of claims 1 to 8.

10. A computer device, characterized in that, The device includes a data acquisition module, a memory, and a processor. The data acquisition module is used to acquire GNSS and InSAR monitoring data. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the method as described in any one of claims 1 to 8.

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