A method and device for detecting the correlation between dam area deformation and water level

Abstract

An embodiment of the present invention provides a method and device for detecting the correlation between dam area deformation and water level. The method includes: performing interferometric measurement on a synthetic aperture radar image data set to obtain time-series deformation information of multiple permanent scatterer target points; performing water level decomposition on the acquired water level data set to obtain a cosine signal, which includes an initial phase and angular velocity of the water level; performing correlation calculation on the time-series deformation information, the initial phase and angular velocity of the water level to obtain correlation parameters, and analyzing the spatial and temporal correlation between the deformation of the dam body and the surrounding environment and the reservoir water level, thereby improving detection accuracy and ensuring the safety of people's lives and property.

Description

Technical Field

[0001] The present invention relates to the field of radar technology, in particular to the field of artificial intelligence technology, and more particularly to a method and device for detecting the correlation between dam area deformation and water level. Background Art

[0002] Dam reservoirs and their slopes are often affected by fluctuations in water levels, often leading to basin subsidence and valley deformation. To mitigate the loss of life and property caused by natural disasters, monitoring these deformations is crucial. With the recent advancement of satellite remote sensing technology, synthetic aperture radar interferometry (InSAR) has emerged as a promising new method for surface deformation monitoring, offering advantages such as long-term, large-scale, high-precision, and dynamic continuity. Related technologies typically use InSAR to examine the effect of water level on slope surface deformation, typically treating the slope deformation as linear or plotting the displacement rate of permanent scatterers (PS) points on the same graph as the water level, performing a simple qualitative analysis of the PS target rate and water level. However, these techniques suffer from significant limitations in their temporal analysis, resulting in poor detection accuracy. Summary of the Invention

[0003] One object of the present invention is to provide a method for detecting the correlation between dam deformation and water level. By analyzing the spatial and temporal correlation between the deformation of the dam body and surrounding environment and the reservoir water level, the method improves detection accuracy and ensures the safety of people's lives and property. Another object of the present invention is to provide an apparatus for detecting the correlation between dam deformation and water level. Another object of the present invention is to provide a computer-readable medium. Yet another object of the present invention is to provide a computer device.

[0004] In order to achieve the above objectives, the present invention discloses a method for detecting the correlation between dam area deformation and water level, comprising:

[0005] Interferometry is performed on synthetic aperture radar image data sets to obtain the temporal deformation information of multiple permanent scatterer target points;

[0006] Perform water level decomposition on the acquired water level data set to obtain a cosine signal, which includes the initial phase and angular velocity of the water level;

[0007] The correlation parameters are obtained by performing correlation calculation on the time series deformation information, the initial phase of the water level and the angular velocity.

[0008] Preferably, interferometry is performed on a synthetic aperture radar image data set to obtain temporal deformation information of multiple permanent scatterer target points, including:

[0009] By using the permanent scatterer synthetic aperture radar interferometry technology, interferometry is performed on the synthetic aperture radar image dataset to obtain the temporal deformation information of multiple permanent scatterer target points.

[0010] Preferably, before performing water level decomposition on the acquired water level data set to obtain the cosine signal, the method further includes:

[0011] Measure the water level in the dam area at specified time intervals using water level measuring equipment;

[0012] Record the water level in the dam area and the corresponding measurement time;

[0013] A water level dataset is generated based on multiple sets of dam area water levels and corresponding measurement times.

[0014] Preferably, performing water level decomposition on the acquired water level data set to obtain a cosine signal includes:

[0015] The water level data set is calculated based on the constructed cosine model using the least squares method to obtain the cosine signal.

[0016] Preferably, correlation calculation is performed on the time series deformation information, the initial phase of the water level and the angular velocity to obtain correlation parameters, including:

[0017] Through the least squares method, according to the constructed correlation model, the correlation of the time series deformation information, the initial phase of the water level and the angular velocity is calculated to obtain the correlation parameters.

[0018] Preferably, the correlation parameter includes the phase of the deformation hysteresis water level;

[0019] After calculating the correlation between the time series deformation information, the initial phase of the water level and the angular velocity and obtaining the correlation parameters, the following steps are also included:

[0020] The phase of the deformation lag water level is calculated using the lag time formula to obtain the deformation lag time.

[0021] Preferably, after calculating the phase of the deformation hysteresis water level by the hysteresis time formula to obtain the deformation hysteresis time, the method further includes:

[0022] According to the different colors set, the permanent scatterer target points corresponding to different ranges of deformation lag time are visualized.

[0023] Preferably, after visually displaying the permanent scatterer target points corresponding to the deformation lag times in different ranges according to the set different colors, the method further includes:

[0024] Filter out the target lag time within the set lag range from the deformation lag time;

[0025] Visualize the target points of permanent scatterers corresponding to the target lag time.

[0026] Preferably, the correlation parameter includes a deformation amplitude value;

[0027] After calculating the correlation between the time series deformation information, the initial phase of the water level and the angular velocity and obtaining the correlation parameters, the following steps are also included:

[0028] According to the different colors set, the permanent scatterer target points corresponding to the deformation amplitude values ​​in different ranges are visualized.

[0029] Preferably, after visually displaying the permanent scatterer target points corresponding to the deformation amplitude values ​​in different ranges according to the set different colors, the method further includes:

[0030] Filter out target amplitude values ​​that are within a set amplitude threshold from the deformation amplitude values;

[0031] Visualize the permanent scatterer target points corresponding to the target amplitude values.

[0032] The present invention also discloses a device for detecting the correlation between dam area deformation and water level, comprising:

[0033] Interferometry unit, used to perform interferometry on synthetic aperture radar image data sets to obtain temporal deformation information of multiple permanent scatterer target points;

[0034] A water level decomposition unit is used to decompose the acquired water level data set to obtain a cosine signal, which includes an initial phase and angular velocity of the water level;

[0035] The first calculation unit is used to perform correlation calculation on the time series deformation information, the initial phase of the water level and the angular velocity to obtain a correlation parameter.

[0036] The present invention also discloses a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the method described above is implemented.

[0037] The present invention also discloses a computer device, including a memory and a processor, wherein the memory is used to store information including program instructions, the processor is used to control the execution of program instructions, and the processor implements the above method when executing the program.

[0038] The present invention performs interferometric measurement on a synthetic aperture radar image data set to obtain time-series deformation information of multiple permanent scatterer target points; performs water level decomposition on the acquired water level data set to obtain a cosine signal, which includes an initial phase and angular velocity of the water level; and performs correlation calculation on the time-series deformation information, the initial phase of the water level, and the angular velocity to obtain correlation parameters. By analyzing the spatial and temporal correlation between the deformation of the dam body and the surrounding environment and the reservoir water level, the detection accuracy is improved to ensure the safety of people's lives and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 A flow chart of a method for detecting the correlation between dam area deformation and water level provided by an embodiment of the present invention;

[0041] Figure 2 A flow chart of another method for detecting the correlation between dam area deformation and water level provided by an embodiment of the present invention;

[0042] Figure 3 A flowchart of performing interferometric measurement on a SAR image dataset by using PS-InSAR technology is provided in an embodiment of the present invention;

[0043] Figure 4 A schematic diagram of the location of a dam in a certain place provided by an embodiment of the present invention;

[0044] Figure 5 A water level time sequence diagram of the reservoir provided in an embodiment of the present invention;

[0045] Figure 6 A schematic diagram showing a comparison between a water level cosine fitting and the actual water level provided in an embodiment of the present invention;

[0046] Figure 7 A schematic diagram of the InSAR down-orbit monitoring results of the area provided by an embodiment of the present invention;

[0047] Figure 8 A schematic diagram comparing the original deformation time sequence and the restored deformation time sequence of a point P provided in an embodiment of the present application;

[0048] Figure 9 A schematic diagram of the deformation amplitude of a PS target point in the dam area provided by an embodiment of the present invention;

[0049] Figure 10 A schematic diagram of deformation amplitude of a PS target point in the dam area provided by another embodiment of the present invention;

[0050] Figure 11 A schematic diagram of deformation amplitude of a PS target point in the dam area provided by another embodiment of the present invention;

[0051] Figure 12 A schematic diagram of deformation lag time of a PS target point in the dam area provided by an embodiment of the present invention;

[0052] Figure 13 A schematic structural diagram of a device for detecting the correlation between dam area deformation and water level provided by an embodiment of the present invention;

[0053] Figure 14 A schematic structural diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0055] In order to facilitate understanding of the technical solution provided by this application, the relevant contents of the technical solution of this application are first described below. Synthetic Aperture Radar Interferometry (InSAR) technology is a synthetic aperture radar technology that uses interferometry technology. Specifically, microwaves are emitted to the target area by radar, and the echoes reflected by the target area are received to obtain a pair of synthetic aperture radar (SAR) complex images of the same target area. The SAR complex image pair includes radiation intensity information and phase angle information. If there is a coherence condition between the SAR complex image pairs, an interference pattern can be obtained by conjugate multiplication of the SAR complex image pairs. According to the phase value of the interference pattern, the path difference of the microwaves in the two imaging is obtained, thereby calculating the topography, landform and slight changes on the surface of the target area. InSAR technology can be used in application fields such as digital elevation model establishment and crustal deformation detection. Specifically, InSAR technology has applications in the fields of surface deformation, subsidence, reservoir slope landslides, dam structure deformation, etc. in cities, buildings, and mining areas. In the field of hydraulic engineering, InSAR technology has also been used to monitor landslides in multiple reservoirs and dams such as the Three Gorges Reservoir.

[0056] Natural disasters such as landslides on the reservoir slopes will experience a long period of deformation accumulation in the early stages. If the abnormal slope deformation areas can be discovered in time in the early stages and monitoring and safety precautions are strengthened accordingly, the loss of life and property can be effectively reduced. In traditional methods, in order to monitor the deformation of the dam reservoir area and the slopes on both sides, observation points are usually set up on the slopes and monitored by distance measuring instruments such as total stations to obtain the deformation of some areas. However, this traditional monitoring method has high monitoring costs and can only obtain the deformation of the measuring point area, and cannot obtain the deformation of a large range. With the development of satellite remote sensing technology in recent years, the existing technology generally regards the slope deformation caused by water level as linear, that is: Dsp _water =k△h _water , among which, DSP _water is the slope deformation, △h _water is the water level difference, and k is a linear parameter. Alternatively, plotting the displacement rate of permanent scatterers (PS) points based on InSAR technology alongside the water level on the same graph and performing a rough, simple qualitative analysis of the displacement rate and water level at the PS target points can effectively address some of the shortcomings of traditional methods. However, due to differences in geological conditions and seepage flow after water level changes, both sides of the slope will experience varying degrees of deformation, resulting in varying lag times. Therefore, relying solely on a rough correspondence between PS target points and water levels cannot accurately detect dam area deformation, and thus cannot guarantee the safety of people's lives and property.

[0057] In response to the above-mentioned technical problems that need to be solved, the present invention proposes an analysis method for spatiotemporal correlation. Based on InSAR technology, the water level changes in the dam area are correlated with time changes, and an indicator of deformation lag time is proposed. The existing qualitative time analysis is quantified, making it operational in practical applications. Ultimately, the goal of identifying abnormal deformation areas in the dam area based on the latest satellite images is achieved, providing protection for the safety of the reservoir dam itself and the property safety of people downstream.

[0058] The following uses a dam deformation and water level correlation detection device as an example to illustrate the implementation process of the dam deformation and water level correlation detection method provided by an embodiment of the present invention. It is understood that the dam deformation and water level correlation detection method provided by an embodiment of the present invention includes, but is not limited to, a dam deformation and water level correlation detection device.

[0059] Figure 1 A flow chart of a method for detecting the correlation between dam area deformation and water level provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method includes:

[0060] Step 101: Perform interferometry on a synthetic aperture radar image dataset to obtain temporal deformation information of multiple permanent scatterer target points.

[0061] Step 102: Decompose the acquired water level data set to obtain a cosine signal, which includes an initial phase and angular velocity of the water level.

[0062] Step 103: perform correlation calculation on the time series deformation information, the initial phase of the water level and the angular velocity to obtain correlation parameters.

[0063] In the technical solution provided by the embodiment of the present invention, interferometry is performed on a synthetic aperture radar image dataset to obtain time-series deformation information of multiple permanent scatterer target points; water level decomposition is performed on the acquired water level dataset to obtain a cosine signal, which includes an initial phase and angular velocity of the water level; correlation calculation is performed on the time-series deformation information, the initial phase and angular velocity of the water level to obtain correlation parameters. By analyzing the spatial and temporal correlation between the deformation of the dam body and the surrounding environment and the reservoir water level, detection accuracy is improved to ensure the safety of people's lives and property.

[0064] Figure 2 A flow chart of another method for detecting the correlation between dam area deformation and water level provided by an embodiment of the present invention is shown in FIG. Figure 2 As shown, the method includes:

[0065] Step 201: perform interferometry on the SAR image dataset to obtain temporal deformation information of multiple PS target points.

[0066] In the embodiment of the present invention, each step is performed by a dam area deformation and water level correlation detection device.

[0067] Specifically, the persistent scatterer synthetic aperture radar interferometry (PS-InSAR) technology is used to perform interferometry on the SAR image dataset to obtain the temporal deformation information of multiple permanent scatterer target points.

[0068] In this embodiment of the present invention, the SAR image dataset includes multiple scenes of image data covering the target area. A scene is the area covered by a single imaging session. The image data for each scene is continuously captured at a specified interval. The specified interval depends on the orbital period of the satellite carrying the synthetic aperture radar (SAR) and generally ranges from several days to several dozen days. As an optional solution, using Sentinel satellites, the specified interval is 12 days; using CSK (COSMO-SkyMed) satellites, the specified interval is 16 days.

[0069] In the embodiment of the present invention, the PS-InSAR technology belongs to the interference superposition technology, which obtains information on surface deformation from multi-phase SAR image data. By extending the InSAR technology to use multi-phase image data, the measurement accuracy can be improved from the centimeter (cm) level to the millimeter (mm) level, greatly reducing the application limitations of the InSAR technology (such as atmospheric influence). The PS technology is used to analyze point targets, and its results are related to linear deformation. It requires more than 20 scenes of image data to participate in the calculation, and the reception must be continuous. The PS technology is suitable for urban areas, or areas with relatively stable interference conditions and radiation. PS can detect displacements with mm accuracy and infer the deformation rate over a time period. Figure 3 The present invention provides a flowchart of performing interferometric measurement on a SAR image dataset by using PS-InSAR technology. Figure 3 As shown, through the digital elevation model (DEM), the SAR image data in the SLC format of the multi-view data is matched to the preset main image and converted to the main image coordinate system to complete the differential interferometry; PS candidate points that meet the basic requirements of the settings are selected, and the average displacement rate and DEM correction coefficient of the PS candidate points of the SAR image data are estimated, and the phase of the atmosphere is estimated; the PS target points are geocoded to estimate the average displacement rate and DEM correction coefficient, and the average displacement rate and three-dimensional position information of the PS target points are obtained. To ensure the accuracy of the results, external control points (GCPs) can be input for estimation; the PS target points are time-series analyzed to obtain time-series deformation information and generate an average SAR backscatter image. It is worth noting that PS-InSAR technology is a relatively mature existing technology. For the present invention, it is only a calculation tool for obtaining time-series deformation information of multiple PS target points. It is only briefly introduced here and will not be described in detail.

[0070] In the embodiment of the present invention, the image data in the SAR image data set is image data taken by a satellite with an ascending or descending orbit having a short orbital period and a large downward viewing angle.

[0071] Radar satellites operate in near-polar orbits, circling the Earth from north to south. Due to the Earth's rotation, satellites can pass over the same surface in two ways: ascending (from south to north) and descending (from north to south). In addition to using the same satellite, some InSAR technologies utilize a dual-satellite system, with one satellite orbiting from south to north and the other from north to south. This means the two satellites orbit in opposite directions, also known as ascending and descending orbits. The CSK and Sentinel satellites in the embodiments of the present invention are dual-satellite systems. Longer orbital periods are less conducive to deformation monitoring, while shorter orbital periods are more conducive to deformation monitoring. A smaller satellite's central angle of view (CAV) results in a wider field of view, more severe deformation at the edges of the field of view, and weaker electromagnetic signal reflection, making it less conducive to deformation monitoring. A larger CAV also results in a narrower field of view, less deformation at the edges of the field of view, and stronger electromagnetic signal reflection, making it more conducive to deformation monitoring. As an alternative, the CAV can range from 30° to 90°.

[0072] Furthermore, for densely vegetated areas such as mountains, corner reflectors can be deployed to enhance the relevance of SAR image data. While there are no strict standards for corner reflector placement, the principle is to maintain uniformity throughout the installation and to increase density in key locations. Trees, houses, and other obstructions should be avoided within three meters of the installation point. The installation site should be away from roads, soft landslides, and other easily deformed areas. Corner reflectors should be fixed to a solid foundation, such as a concrete pier or rock mass.

[0073] Step 202: Measure the water level in the dam area at specified time intervals using water level measuring equipment.

[0074] In the embodiment of the present invention, the designated time interval may be set according to actual conditions. As an optional solution, the designated time interval may be set to 6 hours.

[0075] In the embodiment of the present invention, the water level measuring device can be any device that can collect the water level in the dam area, and the present invention does not limit this. As an optional solution, the water level measuring device is a water level meter.

[0076] Step 203: Record the water level in the dam area and the corresponding measurement time.

[0077] In the embodiment of the present invention, the water level in the dam area and the measurement time of the water level in the dam area are recorded and stored for subsequent data analysis according to the cosine model.

[0078] Step 204: Generate a water level dataset based on multiple sets of dam area water levels and corresponding measurement times.

[0079] In the embodiment of the present invention, the water level data set includes multiple groups of dam area water levels and corresponding measurement times for subsequent data analysis.

[0080] Step 205: perform water level decomposition on the acquired water level data set to obtain a cosine signal, which includes an initial phase and angular velocity of the water level.

[0081] In the embodiment of the present invention, the water level dataset is calculated using the least squares method according to the constructed cosine model to obtain a cosine signal. Specifically, the water level dataset is calculated using the following formula to generate a cosine signal, which includes a constant sequence, an angular velocity, a cosine amplitude value, and an initial phase.

[0082] In an ideal situation, the formula is:

[0083]

[0084] Among them, C is a constant sequence, A is the cosine amplitude value, ω is the angular velocity, and T is the water level monitoring time series. is the initial phase.

[0085] However, in the actual process, there will be an error residual E, which can be obtained by the least squares method. The actual formula is:

[0086] WL=BX+E

[0087]

[0088]

[0089]

[0090]

[0091] Among them, C is a constant sequence, A is the cosine amplitude value, ω is the angular velocity, is the initial phase, l n is the measured water level corresponding to a certain measurement time, t n is a certain measurement time, ε n is the error residual, WL is the measured water level sequence, and X and B are intermediate parameters.

[0092] Step 206: perform correlation calculation on the time series deformation information, the initial phase of the water level, and the angular velocity to obtain correlation parameters.

[0093] In this embodiment of the present invention, dam impoundment affects the stability of the slopes surrounding the reservoir. To explore the relationship between the two, the deformation of the slopes surrounding the reservoir is modeled. Using the least squares method and the constructed correlation model, the correlation between the time-series deformation information, the initial phase of the water level, and the angular velocity is calculated to obtain correlation parameters. These correlation parameters include a constant sequence, a monitoring time sequence, a cosine amplitude, and the phase of the deformation lagging the water level.

[0094] In an ideal situation, the formula is:

[0095]

[0096] Among them, C is a constant sequence, A' is the cosine amplitude value, ω is the angular velocity, and T' is the monitoring time sequence. is the initial phase, is the phase of deformation lagging behind water level, and V is linear deformation.

[0097] However, in the actual process, there will be an error residual E, which can be obtained by the least squares method. The actual formula is:

[0098] Def=B'X'+E

[0099]

[0100]

[0101]

[0102]

[0103] Where C is a constant sequence, A' is the cosine amplitude value, ω is the angular velocity, is the initial phase, is the phase of the deformation lag water level, V is the linear deformation, ε n is the error residual, X' and B' are intermediate parameters, d n is the deformation variable at time t n is the monitoring moment, and Def is the time series deformation information. The constant sequence indicates that there is a deformation component that is independent of water level change and time.

[0104] In the embodiment of the present invention, the larger the cosine amplitude value A' is, the more the deformation of the PS target point is affected by the water level, and the stronger the correlation between the deformation and the water level is; the phase of the deformation lags behind the water level. The larger the value is, the longer the lag time of the PS target point being affected by the water level is.

[0105] Step 207: Visually display the permanent scatterer target points according to the set visualization standard and the correlation parameters.

[0106] In this embodiment of the present invention, PS target points are displayed on an optical image or 3D surface model according to their location. They are color-coded based on deformation rate, correlation, or lag time, with different values ​​corresponding to different colors, and the color differences between different color bands should be relatively clear. Furthermore, a target threshold can be set according to actual needs, displaying only PS target points within the target threshold to intuitively demonstrate areas of greater impact. The target threshold includes a lag range and an amplitude range.

[0107] If the correlation parameter includes the phase of the deformation hysteresis water level, step 207 specifically includes:

[0108] Step 2071: Calculate the phase of the deformation lag water level using the lag time formula to obtain the deformation lag time.

[0109] In the embodiment of the present invention, the number of days that the deformation of the surrounding mountains lags behind the water level is an important indicator for exploring the impact of reservoir water storage on the surrounding slopes. The fluctuation period of the water level and the deformation of the PS target point is one year, and the phase of the deformation lags behind the water level. Converting it into deformation lag time LagD can be more intuitive and easier to analyze.

[0110] Specifically, the phase of the deformation hysteresis water level is calculated using the following formula to obtain the deformation hysteresis time.

[0111]

[0112] Among them, LagD is the deformation lag time, is the phase of the deformation lagging water level.

[0113] Step 2072: Visually display the PS target points corresponding to the deformation lag times in different ranges according to the set colors.

[0114] In the embodiment of the present invention, different colors may be set for PS target points corresponding to deformation lag times in different ranges according to actual conditions. The embodiment of the present invention does not limit the setting of the deformation lag time and the corresponding color.

[0115] Step 2073: Filter out the target lag time within the set lag range from the deformation lag time.

[0116] In the embodiment of the present invention, the hysteresis range can be set according to actual conditions, and the embodiment of the present invention does not limit this. By selecting the target hysteresis time within the hysteresis range, the hysteresis area of ​​the dam deformation can be observed more intuitively and conveniently.

[0117] Step 2074: Visually display the PS target point corresponding to the target lag time.

[0118] In the embodiment of the present invention, the PS target points corresponding to the target lag time may be visualized according to the different colors of each PS target point, so that the areas corresponding to different lag times can be intuitively identified.

[0119] If the correlation parameter includes a deformation amplitude value, step 207 specifically includes:

[0120] Step 3071: Visually display the permanent scatterer target points corresponding to deformation amplitude values ​​in different ranges according to the set different colors.

[0121] In the embodiment of the present invention, different colors can be set for PS target points corresponding to amplitude values ​​in different ranges according to actual conditions. The embodiment of the present invention does not limit the setting of the deformation lag time and the corresponding color.

[0122] Step 3072: Filter out target amplitude values ​​that are within a set amplitude threshold from the deformation amplitude values.

[0123] In the embodiment of the present invention, the amplitude range can be set according to actual conditions and is not limited in the embodiment of the present invention. As an optional solution, the amplitude range is -5 to 5. By selecting the target amplitude value within the amplitude range, the deformation amplitude of the dam deformation area can be observed more intuitively and conveniently.

[0124] Step 3073: Visually display the permanent scatterer target point corresponding to the target amplitude value.

[0125] In the embodiment of the present invention, the PS target points corresponding to the target amplitude values ​​may be visualized according to the different colors of each PS target point, so that the deformation areas corresponding to different target amplitude values ​​can be intuitively seen.

[0126] The following describes the process of detecting the correlation between dam area deformation and water level using a specific embodiment:

[0127] Take a hydropower station in a certain place as an example. Figure 4 A schematic diagram of a dam location in a certain place is provided in an embodiment of the present invention, such as Figure 4 As shown, the horizontal axis is latitude, the vertical axis is longitude, and the scale in the figure is 1 kilometer (km). Figure 4 The area enclosed in the box is the location of a dam. The total installed capacity of the hydropower station is 13.86 million kilowatts, with a total capacity of 12.67 billion m 3 , regulating reservoir capacity 6.46 billion m 3This monitoring used Sentinel satellite imagery from January 2016 to May 2018, totaling 53 images. The polarization mode was VV polarization, with a center-down viewing angle of 36°. Using PS-InSAR technology, a set of 60,000 PS target points near the hydropower station was obtained.

[0128] Water level monitoring at this location has been ongoing since December 20, 2012. During the early stages of water level monitoring, the area had not yet stored water and was in the construction phase. Water storage began in the fall of 2014. This example captured water level data from June 1, 2014, to April 26, 2019. Figure 5 A water level time sequence diagram of the reservoir provided by the embodiment of the present invention is as follows: Figure 5 As shown in the figure, the horizontal axis is the monitoring period, from July 2012 to January 2020, and the vertical axis is the water level in meters (m). The reservoir water level is decomposed by least squares to obtain the initial phase, which is used to solve the correlation parameters later. Figure 6 A schematic diagram of the comparison between a water level cosine fitting and the actual water level provided in the embodiment of the present invention is Figure 5 A comparison chart of cosine fitting of water levels based on the data from July 2012 to January 2020 is shown in the figure. The horizontal axis is the monitoring time, from July 2012 to January 2020, and the vertical axis is the water level height in meters (m).

[0129] The monitoring period of the water level data is inconsistent with the time series obtained by InSAR monitoring. From January 2016 to May 2018, water level and InSAR monitoring overlapped. During this period, two situations occurred: 1) Water level monitoring data was available on the same day, but InSAR data was not. 2) InSAR data was available on the same day, but water level data was not. Correlation analysis requires that the two data sets coincide in time, so interpolation is performed for each data set to ensure that both have data for the same day within the shared period.

[0130] A correlation model is established. The time series deformation information in the correlation model includes linear deformation, water level influence, constant sequence and error residual. The correlation parameters of each PS target point are solved one by one by the least squares method. Then, the correlation parameters are graded and colored according to their size and visualized. Taking the case where the correlation parameters include linear deformation as an example, Figure 7 A schematic diagram of the InSAR down-orbit monitoring results of the area provided by the embodiment of the present invention is shown as follows: Figure 7The horizontal axis is latitude, the vertical axis is longitude, and the scale is 2.5 kilometers (km). The legend shows linear deformation velocity (Velocity) and its corresponding color. Linear deformation velocity includes: less than -18, -18 to -14, -14 to -10, -10 to -6, -6 to -2, -2 to 2, 2 to 6, 2 to 6, 6 to 10, 10 to 14, 14 to 18, and greater than 18. The unit is millimeter per year (mm / yr). The dam has multiple PS target points, and the linear deformation range of each PS target point is displayed with its corresponding color. Figure 7 There is a PS target point P in the figure, and the fitting result of point P is compared with the deformation time series after restoration. Figure 8 A schematic diagram comparing the original deformation time sequence and the actual deformation time sequence of a point P provided in an embodiment of the present application is shown as follows: Figure 8 As shown in the figure, the horizontal axis is the monitoring time, and the vertical axis is the deformation amount, and the unit is millimeter (mm). It can be seen that the fitting result is basically consistent with the actual deformation time series.

[0131] As an option, the correlation parameter includes a deformation amplitude value, Figure 9 A schematic diagram of the deformation amplitude of the PS target point in the dam area provided by an embodiment of the present invention is shown as follows: Figure 9 As shown, the horizontal axis is latitude and the vertical axis is longitude. The scale in the figure is 2.5 kilometers (km). The legend shows the range of deformation amplitude values ​​and the corresponding colors. According to the size of the deformation amplitude value, it is divided into 10 intervals. The interval interval is 2, with 0 as the symmetry point. The color transitions from light to dark as the deformation amplitude value increases. The specific range of deformation amplitude values ​​and their corresponding colors refer to Figure 9 Legend. Figure 9 It can be clearly observed that the PS points around the dam are the darkest in color. The darkest color indicates that the deformation at this location is greatly affected by the water level. Figure 9 The medium and dark color points are denser and more spatially distinguishable from other color points.

[0132] Figure 10 A schematic diagram of the deformation amplitude of another PS target point in the dam area provided by an embodiment of the present invention is shown as follows: Figure 10 As shown, the horizontal axis is latitude and the vertical axis is longitude. The scale in the figure is 2.5 kilometers (km). The legend shows the range of deformation amplitude values ​​and the corresponding colors. The specific range of deformation amplitude values ​​and their corresponding colors refer to Figure 10 Legend. Figure 10 As shown in the figure, taking -9 as the threshold, the boundary of the area greatly affected by the water level is circled. The area extends approximately 600 meters along the bank of the site, upstream of the dam. It can be seen that the water level has a greater impact on the left bank than on the right bank.

[0133] Figure 11A schematic diagram of the deformation amplitude of another PS target point in the dam area provided by an embodiment of the present invention is shown as follows: Figure 11 As shown, the horizontal axis is latitude and the vertical axis is longitude. The scale in the figure is 2.5 kilometers (km). The legend shows the range of deformation amplitude values ​​and the corresponding colors. The specific range of deformation amplitude values ​​and their corresponding colors refer to Figure 11 To explore the impact of water level on high-level landslides, PS target points with deformation amplitude values ​​between -5 and 5 were filtered out, as it was believed that the deformation of such points was less affected by water level. The remaining points were distributed as follows: Figure 11 As shown in the figure, the area circled by the black rectangle has a relatively large relative elevation, and a large number of PS target points in this area are filtered out, indicating that this area is less affected by the water level.

[0134] As an option, the correlation parameters include the deformation lag time, Figure 12 A schematic diagram of the deformation lag time of a PS target point in the dam area provided by an embodiment of the present invention is shown as follows: Figure 12 As shown, the horizontal axis is latitude and the vertical axis is longitude. The scale is 2.5 kilometers (km). The legend shows the range of deformation lag time and the corresponding color. According to the size of the deformation amplitude value, it is divided into 10 intervals, with an interval of 8 and 0 as the symmetry point. The specific range of deformation lag time and its corresponding color refer to Figure 12 Legend. Figure 12 It can be clearly seen that except for some mountain tops, the mountain tops are relatively high in elevation and are less affected by water storage. Figure 12 The deformation at other locations lags behind the water level obviously.

[0135] In the technical solution of the method for detecting the correlation between dam area deformation and water level provided by an embodiment of the present invention, interferometric measurement is performed on a synthetic aperture radar image data set to obtain time-series deformation information of multiple permanent scatterer target points; water level decomposition is performed on the acquired water level data set to obtain a cosine signal, which includes an initial phase and angular velocity of the water level; correlation calculation is performed on the time-series deformation information, the initial phase and angular velocity of the water level to obtain correlation parameters. By analyzing the correlation between the deformation of the dam body and the surrounding environment and the reservoir water level in space and time, the detection accuracy is improved and the safety of people's lives and property is guaranteed.

[0136] Figure 13 This is a schematic diagram of a device for detecting the correlation between dam deformation and water level provided by an embodiment of the present invention. The device is used to perform the above-mentioned method for detecting the correlation between dam deformation and water level. Figure 13 As shown, the device includes: an interference measurement unit 11, a water level decomposition unit 12 and a first calculation unit 13.

[0137] The interferometric measurement unit 11 is used to perform interferometric measurement on the synthetic aperture radar image data set to obtain temporal deformation information of multiple permanent scatterer target points.

[0138] The water level decomposition unit 12 is used to perform water level decomposition on the acquired water level data set to obtain a cosine signal, which includes an initial phase and angular velocity of the water level.

[0139] The first calculation unit 13 is used to perform correlation calculation on the time series deformation information, the initial phase of the water level and the angular velocity to obtain a correlation parameter.

[0140] In the embodiment of the present invention, the interferometry unit 11 is specifically configured to perform interferometry on a synthetic aperture radar image dataset using a permanent scatterer synthetic aperture radar interferometry technique to obtain temporal deformation information of multiple permanent scatterer target points.

[0141] In the embodiment of the present invention, the device further includes: a measuring unit 14 , a recording unit 15 and a generating unit 16 .

[0142] The measuring unit 14 is used to measure the water level in the dam area at specified time intervals using a water level measuring device.

[0143] The recording unit 15 is used to record the water level in the dam area and the corresponding measurement time.

[0144] The generating unit 16 is configured to generate a water level data set according to multiple sets of dam area water levels and corresponding measurement times.

[0145] In the embodiment of the present invention, the water level decomposition unit 12 calculates the water level data set according to the constructed cosine model using the least squares method to obtain a cosine signal.

[0146] In the embodiment of the present invention, the first calculation unit 13 is specifically configured to perform correlation calculation on the time series deformation information, the water level initial phase and the angular velocity according to the constructed correlation model by using the least square method to obtain correlation parameters.

[0147] In the embodiment of the present invention, the device further includes a second calculation unit 17 .

[0148] The second calculation unit 17 is used to calculate the phase of the deformation lag water level by using the lag time formula to obtain the deformation lag time.

[0149] In the embodiment of the present invention, the device further includes a first display unit 18 .

[0150] The first display unit 18 is used to visually display permanent scatterer target points corresponding to deformation lag times in different ranges according to different set colors.

[0151] In the embodiment of the present invention, the device further includes: a first screening unit 19 and a second display unit 20 .

[0152] The first screening unit 19 is used to screen out a target lag time within a set lag range from the deformation lag times.

[0153] The second display unit 20 is used to visually display the permanent scatterer target point corresponding to the target lag time.

[0154] In the embodiment of the present invention, the device further includes: a third display unit 21 .

[0155] The third display unit 21 is used to visually display the permanent scatterer target points corresponding to deformation amplitude values ​​in different ranges according to different set colors.

[0156] In the embodiment of the present invention, the device further includes: a second screening unit 22 and a fourth display unit 23 .

[0157] The second screening unit 22 is used to screen out a target amplitude value having an amplitude threshold within a set amplitude range from the deformation amplitude values.

[0158] The fourth display unit 23 is used to visually display the permanent scatterer target point corresponding to the target amplitude value.

[0159] In the solution of the embodiment of the present invention, interferometry is performed on a synthetic aperture radar image dataset to obtain time-series deformation information of multiple permanent scatterer target points; water level decomposition is performed on the acquired water level dataset to obtain a cosine signal, which includes an initial phase and angular velocity of the water level; correlation calculation is performed on the time-series deformation information, the initial phase and angular velocity of the water level to obtain correlation parameters. By analyzing the spatial and temporal correlation between the deformation of the dam body and the surrounding environment and the reservoir water level, detection accuracy is improved to ensure the safety of people's lives and property.

[0160] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer device. Specifically, the computer device may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0161] An embodiment of the present invention provides a computer device, including a memory and a processor, the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the steps of the embodiment of the above-mentioned method for detecting the correlation between dam area deformation and water level are implemented. For a specific description, please refer to the embodiment of the above-mentioned method for detecting the correlation between dam area deformation and water level.

[0162] Reference below Figure 14 , which shows a structural diagram of a computer device 600 suitable for implementing an embodiment of the present application.

[0163] like Figure 14 As shown, the computer device 600 includes a central processing unit (CPU) 601, which can perform various appropriate tasks and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage portion 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the computer device 600 are also stored in the RAM 603. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0164] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, and the like; an output section 607 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 608 including devices such as a hard disk; and a communication section 609 including a network interface card such as a LAN card or a modem. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 606 as needed. Removable media 611, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 610 as needed, so that computer programs read therefrom can be installed in the storage section 608 as needed.

[0165] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program including program code for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication portion 609 and / or installed from removable media 611.

[0166] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0167] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0168] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0169] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0170] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0171] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0172] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0173] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0174] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0175] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for detecting the correlation between dam area deformation and water level, characterized in that: The method comprises: Interferometry is performed on synthetic aperture radar image data sets to obtain the temporal deformation information of multiple permanent scatterer target points; Performing water level decomposition on the acquired water level data set to obtain a cosine signal, wherein the cosine signal includes an initial phase of the water level, an angular velocity, a constant sequence, and a cosine amplitude value; The step of performing water level decomposition on the acquired water level data set to obtain a cosine signal includes: The water level data set is calculated using the least squares method according to the constructed cosine model to obtain a cosine signal, which is as follows: Among them, C is a constant sequence, A is the cosine amplitude value, ω is the angular velocity, and T is the water level monitoring time series. is the initial phase; The correlation calculation is performed on the time series deformation information, the initial phase of the water level and the angular velocity to obtain the correlation parameters. The correlation parameters include the constant sequence, the monitoring time sequence, the cosine amplitude value and the phase of the deformation lagging water level. The formula is: Among them, C is a constant sequence, A' is the cosine amplitude value, ω is the angular velocity, and T' is the monitoring time sequence. is the initial phase, is the phase of deformation lagging behind water level, and V is linear deformation.

2. The method for detecting the correlation between dam area deformation and water level according to claim 1, characterized in that: The interferometric measurement of the synthetic aperture radar image data set to obtain the temporal deformation information of multiple permanent scatterer target points includes: By using the permanent scatterer synthetic aperture radar interferometry technology, interferometry is performed on the synthetic aperture radar image dataset to obtain the temporal deformation information of multiple permanent scatterer target points.

3. The method for detecting the correlation between dam area deformation and water level according to claim 1, characterized in that: Before performing water level decomposition on the acquired water level data set to obtain the cosine signal, the following steps are also included: Measure the water level in the dam area at specified time intervals using water level measuring equipment; Recording the water level in the dam area and the corresponding measurement time; A water level dataset is generated according to the multiple sets of dam area water levels and corresponding measurement times.

4. The method for detecting the correlation between dam area deformation and water level according to claim 1, characterized in that: The correlation calculation of the time series deformation information, the water level initial phase and the angular velocity to obtain the correlation parameters includes: By using the least squares method and based on the constructed correlation model, the correlation of the time series deformation information, the initial phase of the water level and the angular velocity is calculated to obtain the correlation parameters.

5. The method for detecting the correlation between dam area deformation and water level according to claim 1, characterized in that: The correlation parameters include the phase of the deformation hysteresis water level; After performing correlation calculation on the time series deformation information, the water level initial phase and the angular velocity to obtain the correlation parameter, the method further includes: The phase of the deformation lag water level is calculated using the lag time formula to obtain the deformation lag time.

6. The method for detecting the correlation between dam area deformation and water level according to claim 5, characterized in that: After calculating the phase of the deformation hysteresis water level using the hysteresis time formula to obtain the deformation hysteresis time, the method further includes: According to the different colors set, the permanent scatterer target points corresponding to different ranges of deformation lag time are visualized.

7. The method for detecting the correlation between dam area deformation and water level according to claim 6, characterized in that: After visually displaying the permanent scatterer target points corresponding to the deformation lag times in different ranges according to the set different colors, the method further includes: Filtering out a target lag time within a set lag range from the deformation lag time; The permanent scatterer target point corresponding to the target lag time is visually displayed.

8. The method for detecting the correlation between dam area deformation and water level according to claim 1, characterized in that: The correlation parameter includes a deformation amplitude value; After performing correlation calculation on the time series deformation information, the water level initial phase and the angular velocity to obtain the correlation parameter, the method further includes: According to the different colors set, the permanent scatterer target points corresponding to the deformation amplitude values ​​in different ranges are visualized.

9. The method for detecting the correlation between dam area deformation and water level according to claim 8, characterized in that: After visually displaying the permanent scatterer target points corresponding to the deformation amplitude values ​​in different ranges according to the set different colors, the method further includes: Filtering out a target amplitude value of an amplitude threshold within a set amplitude range from the deformation amplitude values; The permanent scatterer target point corresponding to the target amplitude value is visually displayed.

10. A device for detecting the correlation between dam area deformation and water level, characterized in that: The device comprises: Interferometry unit, used to perform interferometry on synthetic aperture radar image data sets to obtain temporal deformation information of multiple permanent scatterer target points; A water level decomposition unit is used to perform water level decomposition on the acquired water level data set to obtain a cosine signal, wherein the cosine signal includes an initial phase of the water level, an angular velocity, a constant sequence, and a cosine amplitude value; The water level decomposition unit is specifically used to calculate the water level data set according to the constructed cosine model using the least squares method to obtain a cosine signal, and the formula is: Among them, C is a constant sequence, A is the cosine amplitude value, ω is the angular velocity, and T is the water level monitoring time series. is the initial phase; The first calculation unit is used to perform correlation calculation on the time series deformation information, the initial phase of the water level and the angular velocity to obtain correlation parameters. The correlation parameters include a constant sequence, a monitoring time sequence, a cosine amplitude value and a phase of the deformation lagging water level. The formula is: Among them, C is a constant sequence, A' is the cosine amplitude value, ω is the angular velocity, and T' is the monitoring time sequence. is the initial phase, is the phase of deformation lagging behind water level, and V is linear deformation.

11. A computer-readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for detecting the correlation between dam area deformation and water level as described in any one of claims 1 to 9 is implemented.

12. A computer device comprising a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions, wherein: When the program instructions are loaded and executed by the processor, the method for detecting the correlation between dam area deformation and water level as described in any one of claims 1 to 9 is implemented.

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