Transmission line safety prediction method and device, processor and storage medium

Abstract

The invention discloses a transmission line safety prediction method and device, a processor and a storage medium. The method comprises the steps that a plurality of radar images of a target ground are acquired, and a transmission line is deployed on the target ground; based on the multiple radar images, land subsidence data of the target ground are determined, and the land subsidence data are used for indicating the subsidence amplitude of the target ground; the land subsidence data are input into a target prediction model for prediction, a safety result of the transmission line is obtained, the target prediction model is obtained through training of historical land subsidence data of the target ground and geographic information of the transmission line, and the safety result is used for indicating the safety degree of the transmission line on the target ground. The technical problem that the transmission line safety cannot be predicted is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of security prediction, and in particular to a security prediction method, device, processor and storage medium for a transmission line. Background Art

[0002] At present, ground subsidence has many adverse effects on transmission lines, including equipment damage, signal attenuation, network instability, high maintenance costs and reduced service quality, which in turn causes power outages or other safety issues. Predicting the risks of transmission lines in advance can help relevant departments take timely measures, such as reinforcing transmission lines or relocating lines, to avoid possible losses and accidents. Therefore, it is very important to detect ground subsidence early and predict transmission line risks, which can effectively ensure the safe and stable operation of transmission lines.

[0003] Under normal circumstances, since traditional methods can only consider limited factors and situations, their prediction results may have certain uncertainties and errors and cannot accurately capture all potential risks. Therefore, there is a technical problem that the safety of transmission lines cannot be predicted.

[0004] With respect to the above-mentioned technical problem of being unable to predict the safety of transmission lines, no effective solution has been proposed so far. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, processor and storage medium for predicting the security of a transmission line, so as to at least solve the technical problem that the security of a transmission line cannot be predicted.

[0006] According to one aspect of an embodiment of the present invention, a method for predicting the safety of a transmission line is provided. The method may include: acquiring multiple radar images of a target ground, wherein a transmission line is deployed on the target ground; determining ground subsidence data of the target ground based on the multiple radar images, wherein the ground subsidence data is used to indicate the subsidence amplitude of the target ground; inputting the ground subsidence data into a target prediction model for prediction, and obtaining a safety result of the transmission line, wherein the target prediction model is obtained by training with historical ground subsidence data of the target ground and geographic information of the transmission line, and the safety result is used to indicate the safety degree of the transmission line on the target ground.

[0007] Optionally, determining ground subsidence data of the target ground based on multiple radar images includes: establishing an interference image based on the multiple radar images; extracting phase information of the target ground from the interference image; and determining ground subsidence data of the target ground based on the phase information.

[0008] Optionally, the safety prediction method for a transmission line further includes: obtaining historical ground subsidence data of the target ground; establishing a training set based on the historical ground subsidence data; and training an initial prediction model based on the training set to obtain a target prediction model.

[0009] Optionally, a training set is established based on historical ground subsidence data, including: obtaining geographic information of the transmission line corresponding to the target ground; matching the historical ground subsidence data with the geographic information of the transmission line to obtain a matching result; in response to a successful matching of the historical ground subsidence data with the geographic information of the transmission line, establishing the historical ground subsidence data and the geographic information of the transmission line as a training set.

[0010] Optionally, before matching the historical ground subsidence data with the geographic information of the transmission line to obtain a matching result, the method further includes: preprocessing the historical ground subsidence data to obtain preprocessed historical ground subsidence data.

[0011] Optionally, the safety prediction method for a transmission line further includes: visualizing historical ground subsidence data and geographic information of the transmission line.

[0012] According to another aspect of an embodiment of the present invention, a safety prediction device for a transmission line is also provided. The device may include: an acquisition unit, used to acquire multiple radar images of a target ground, wherein a transmission line is deployed on the target ground; a determination unit, used to determine ground subsidence data of the target ground based on multiple radar images, wherein the ground subsidence data is used to indicate the subsidence amplitude of the target ground; a prediction unit, used to input the ground subsidence data into a target prediction model for prediction, and obtain a safety result of the transmission line, wherein the target prediction model is obtained by training with historical ground subsidence data of the target ground and geographic information of the transmission line, and the safety result is used to indicate the safety degree of the transmission line on the target ground.

[0013] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the security prediction method for the transmission line in an embodiment of the present invention.

[0014] According to another aspect of an embodiment of the present invention, a processor is provided, which is used to run a program, wherein the security prediction method for a transmission line in an embodiment of the present invention is executed when the program is run.

[0015] According to another aspect of the embodiment of the present invention, a computer program product is provided, which includes computer instructions, and when the computer instructions are executed by a processor, the security prediction method of the transmission line in the embodiment of the present invention is implemented.

[0016] In an embodiment of the present invention, multiple radar images of the target ground are obtained, wherein a transmission line is deployed on the target ground; based on the multiple radar images, the ground subsidence data of the target ground is determined, wherein the ground subsidence data is used to indicate the subsidence amplitude of the target ground; the ground subsidence data is input into a target prediction model for prediction, and a safety result of the transmission line is obtained, wherein the target prediction model is obtained by training with the historical ground subsidence data of the target ground and the geographic information of the transmission line, and the safety result is used to indicate the safety degree of the transmission line on the target ground. That is to say, the present invention establishes a training set through the historical ground subsidence data of the target ground and the geographic information of the transmission line, and obtains a target prediction model by training with the training set, thereby obtaining the safety result of the transmission line according to the target prediction model, thereby solving the technical problem of being unable to predict the safety of the transmission line, and achieving the technical effect of predicting the technical problem of the safety of the transmission line. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 is a flow chart of a security prediction method for a transmission line according to an embodiment of the present invention;

[0019] Figure 2 is a flow chart of a method for analyzing the impact of ground subsidence on transmission trunk lines based on remote sensing maps according to an embodiment of the present invention;

[0020] Figure 3 is a schematic diagram of a security prediction device for a transmission line according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. 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 creative work should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, functional component or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, functional components or devices.

[0023] According to an embodiment of the present invention, an embodiment of a security prediction method for a transmission line is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] Figure 1 is a flow chart of a security prediction method for a transmission line according to an embodiment of the present invention. Figure 1 As shown, the method may include the following steps:

[0025] Step S101, acquiring multiple radar images of the target ground.

[0026] In the technical solution provided in the above step S101 of the present invention, a transmission line is deployed on the target ground.

[0027] In this embodiment, multiple radar images of the target ground are obtained, for example, radar image data from a satellite (such as Sentinel-1, TerraSAR-X, etc.), which is only an illustrative example and does not limit the specific method of obtaining multiple radar images.

[0028] Optionally, the radar image may also be referred to as radar image data or synthetic aperture radar interferometric data (Interferometric Synthetic Aperture Radar, referred to as InSAR for short).

[0029] For example, radar image data from satellites (such as Sentinel-1, TerraSAR-X, etc.) are obtained. These satellites usually obtain radar images of the target ground at certain time intervals.

[0030] Step S102, determining ground subsidence data of the target ground based on multiple radar images.

[0031] In the technical solution provided in the above step S102 of the present invention, the ground subsidence data is used to indicate the subsidence amplitude of the target ground. The ground subsidence data may also be referred to as ground displacement data.

[0032] In this embodiment, after a plurality of radar images of the target ground are acquired in step S101, ground subsidence data of the target ground is determined based on the plurality of radar images.

[0033] Optionally, an interference image is created based on multiple radar images, wherein the interference image contains amplitude and phase information of the target ground.

[0034] For example, an interferogram is created between the first and second acquired radar images. This typically involves multiplying the complex magnitudes and phases of the two images. Let the first image be I1, the second image be I2, and the interferogram be I int , as shown in the following formula (1):

[0035]

[0036] Here, * represents the conjugate of a complex number.

[0037] Optionally, after the interference image is established, phase information of the target ground is extracted from the interference image.

[0038] For example, extracting phase information from an interference image. Usually, the phase information is contained in the argument of the complex image. The argument represents the phase of the wave and can be calculated using the following formula (2):

[0039] φ(x,y)=arg(I int (x,y)) (2)where φ(x,y) represents the phase at the position (x,y).

[0040] Optionally, ground subsidence data of the target ground is determined based on the phase information.

[0041] For example, the phase difference Δφ between two radar images can be calculated using the following formula (3):

[0042] Δφ(x,y)=φ2(x,y)-φ1(x,y) (3)

[0043] Among them, Δφ(x,y) represents the phase difference at the position (x,y), φ1(x,y) and φ2(x,y) represent the phase of the first and second radar images respectively. The phase difference is converted into ground displacement, that is, ground subsidence data, which can be completed by the following formula (4):

[0044]

[0045] Where D(x,y) represents the ground displacement at position (x,y), λ represents the radar wavelength, Δφ(x,y) represents the phase difference, and θ represents the incident angle.

[0046] Step S103, inputting the ground subsidence data into the target prediction model for prediction to obtain the safety result of the transmission line.

[0047] In the technical solution provided in the above step S103 of the present invention, the target prediction model is obtained by training the historical ground subsidence data of the target ground and the geographic information of the transmission line, and the safety result is used to indicate the safety level of the transmission line on the target ground.

[0048] In this embodiment, after the ground subsidence data of the target ground is determined in step S102, the ground subsidence data is input into the target prediction model for prediction to obtain the safety result of the transmission line.

[0049] Optionally, historical ground subsidence data of the target ground is obtained; and a training set is established based on the historical ground subsidence data, wherein the training set is used to train an initial prediction model.

[0050] For example, the geographic information of the transmission line corresponding to the target ground is obtained; the historical ground subsidence data is matched with the geographic information of the transmission line to obtain a matching result; when the historical ground subsidence data is successfully matched with the geographic information of the transmission line, a training set is established.

[0051] For another example, the geographic coordinate information of the communication transmission trunk line is obtained, including the longitude and latitude data of each key point, and the estimated ground subsidence data is matched with the geographic coordinates of the transmission trunk line. Once the matching is completed, the ground subsidence data can be associated with the geographic coordinates of the transmission trunk line.

[0052] Optionally, the initial prediction model is trained according to the training set to obtain a target prediction model.

[0053] It should be noted that the above embodiments can be executed by a security prediction device for a transmission line.

[0054] In the above steps S101 to S103 of the present invention, a plurality of radar images of the target ground are obtained, wherein a transmission line is deployed on the target ground; based on the plurality of radar images, the ground subsidence data of the target ground is determined, wherein the ground subsidence data is used to indicate the subsidence amplitude of the target ground; the ground subsidence data is input into the target prediction model for prediction, and the safety result of the transmission line is obtained, wherein the target prediction model is obtained by training with the historical ground subsidence data of the target ground and the geographic information of the transmission line, and the safety result is used to indicate the safety degree of the transmission line on the target ground. That is to say, the present invention establishes a training set through the historical ground subsidence data of the target ground and the geographic information of the transmission line, and obtains the target prediction model by training with the training set, thereby obtaining the safety result of the transmission line according to the target prediction model, thereby solving the technical problem of being unable to predict the safety of the transmission line, and achieving the technical effect of predicting the technical problem of the safety of the transmission line.

[0055] The above method of this embodiment is further introduced below.

[0056] As an optional implementation method, ground subsidence data of the target ground is determined based on multiple radar images, including: establishing an interference image based on multiple radar images; extracting phase information of the target ground from the interference image; and determining ground subsidence data of the target ground based on the phase information.

[0057] In this embodiment, an interference image is created based on a plurality of radar images; phase information of the target ground is extracted from the interference image; and ground subsidence data of the target ground is determined based on the phase information.

[0058] For example, radar images taken at two different time points are used to generate an interference image by calculating the phase difference. The interference image is in complex form (interference complex number), which contains amplitude and phase information. The phase of the interference image usually contains 2π jumps, and it is necessary to unwrap the phase to obtain the continuous displacement information of the surface. The following formula (5) is usually used for unwrapping:

[0059] P r =P c +2πN (5)

[0060] Among them, P c is the continuous phase, P r is the original phase, and N is an integer. The unwrapped phase information represents the displacement of the ground surface, which can be calculated using the above formula (6):

[0061]

[0062] Where D is the displacement, λ is the radar wavelength, Δ is the phase difference, and θ is the angle of incidence.

[0063] As an optional implementation method, the safety prediction method of the transmission line also includes: obtaining historical ground subsidence data of the target ground; establishing a training set based on the historical ground subsidence data; and training an initial prediction model based on the training set to obtain a target prediction model.

[0064] In this embodiment, historical ground subsidence data of the target ground is obtained; a training set is established based on the historical ground subsidence data, and an initial prediction model is trained based on the training set to obtain a target prediction model.

[0065] For example, radar measurement data, geographic information (location and characteristics of transmission trunks), and possible other relevant data are obtained. After processing, the data set is used to train the neural network. Preprocess radar data, geographic information of transmission lines, and related data. Extract relevant features of ground subsidence and transmission trunks. Create labels to represent the impact of subsidence on transmission trunks. Use neural network training models to establish the relationship between subsidence and trunk impact. Apply the cost function to the entire training set, average all loss function values, and the optimal solution is the minimum value of the cost function. The ability to obtain the optimal solution proves that the indicator can be monitored through the Geographic Information System (GIS), thereby estimating the impact of ground subsidence on the transmission network.

[0066] Optionally, a cost function is applied to the entire training set, as shown in the following formula (7):

[0067]

[0068] Among them, y (i) represents the fitted line, h(x (i) ) represents the value of the actual data. (i) ) and the fitted line y (i) The corresponding value of is subtracted to find the gap between the fitted straight line and the actual value. The optimal solution is the minimum value of the cost function minJ(θ0,θ1). The ability to obtain the optimal solution proves that the indicator can be monitored through the GIS system, and then the impact of ground subsidence on the transmission network can be estimated.

[0069] As an optional implementation method, a training set is established based on historical ground subsidence data, including: obtaining the geographic information of the transmission line corresponding to the target ground; matching the historical ground subsidence data with the geographic information of the transmission line to obtain a matching result; in response to a successful match between the historical ground subsidence data and the geographic information of the transmission line, establishing the historical ground subsidence data and the geographic information of the transmission line as a training set.

[0070] In this embodiment, the geographic information of the transmission line corresponding to the target ground is obtained; the historical ground subsidence data is matched with the geographic information of the transmission line to obtain a matching result; when the historical ground subsidence data is successfully matched with the geographic information of the transmission line, a training set is established.

[0071] For example, GIS tools or Python are used to associate the estimated ground subsidence with the geographic coordinates of the transmission trunk line, which can be achieved through distance measurement or spatial connection. Taking GIS tools as an example, it is divided into the following three steps: Data import: Import the generated subsidence grid data and the geographic coordinate data of the transmission trunk line (usually in vector data format, such as Shapefile, GeoJSON. Spatial connection: Use the "Spatial Connection" function to associate the subsidence data with the transmission trunk line data. Select the appropriate connection type (such as "Nearest Neighbor" or "Spatial Intersection"). Result verification: Check the matching results to ensure that the subsidence data is accurately applied to each point of the transmission trunk line and verify whether there are errors or mismatches. Once the matching is completed, the ground subsidence data can be associated with the geographic coordinates of the transmission trunk line. The estimated ground subsidence value is associated with the corresponding transmission trunk line coordinates. This can be expressed using the following formula (8):

[0072] D associated =D estimated (8)

[0073] Among them, D associated is the ground subsidence value associated with the transmission trunk, D estimated It is the land subsidence value estimated from remote sensing InSAR data. By aligning the subsidence data with the geographic coordinate system of the transmission trunk, the impact of land subsidence on the transmission trunk can be quantitatively described.

[0074] As an optional implementation manner, before matching the historical ground subsidence data with the geographic information of the transmission line to obtain a matching result, the method further includes: preprocessing the historical ground subsidence data to obtain preprocessed historical ground subsidence data.

[0075] In this embodiment, the historical ground subsidence data is preprocessed to obtain the preprocessed historical ground subsidence data.

[0076] For example, preprocessing satellite data, including correction, registration, and denoising, to ensure data quality and consistency. Collect data points of historical ground subsidence data, including subsidence amount z i and the corresponding geographic coordinates (x i ,y i ), ensure the quality and accuracy of the data, and pre-process the data using inverse distance weighted (IDW) interpolation, which can be processed by the following formula (9):

[0077]

[0078] where z(x,y) is the estimated settlement value at position (x,y), i is the sedimentation value of the ith data point, d i is the distance from the position (x, y) to the i-th data point, p is the weight exponent (p = 2), and IDW interpolation is used to generate a settlement grid or surface model covering the study area.

[0079] As an optional implementation manner, the method for safety prediction of a transmission line further includes: visualizing historical ground subsidence data and geographic information of the transmission line.

[0080] In this embodiment, historical ground subsidence data is visualized together with geographic information of the transmission lines.

[0081] For example, the associated land subsidence data can be visualized and analyzed together with the geographic coordinates of the transmission trunks, thus enabling a better understanding of the impact of land subsidence on communication transmission trunks and supporting decision making.

[0082] It should be noted that the above embodiments can be executed by a security prediction device for a transmission line.

[0083] In this embodiment, multiple radar images of the target ground are obtained, wherein a transmission line is deployed on the target ground; based on the multiple radar images, the ground subsidence data of the target ground is determined, wherein the ground subsidence data is used to indicate the subsidence amplitude of the target ground; the ground subsidence data is input into the target prediction model for prediction, and the safety result of the transmission line is obtained, wherein the target prediction model is obtained by training with the historical ground subsidence data of the target ground and the geographic information of the transmission line, and the safety result is used to indicate the safety degree of the transmission line on the target ground. That is to say, the present invention establishes a training set through the historical ground subsidence data of the target ground and the geographic information of the transmission line, and obtains the target prediction model by training with the training set, thereby obtaining the safety result of the transmission line according to the target prediction model, thereby solving the technical problem of being unable to predict the safety of the transmission line, and achieving the technical effect of predicting the technical problem of the safety of the transmission line.

[0084] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0085] At present, ground subsidence has many adverse effects on transmission lines, including equipment damage, signal attenuation, network instability, high maintenance costs and reduced service quality, which in turn causes power outages or other safety issues. Predicting the risks of transmission lines in advance can help relevant departments take timely measures, such as reinforcing transmission lines or relocating lines, to avoid possible losses and accidents. Therefore, it is very important to detect ground subsidence early and predict transmission line risks, which can effectively ensure the safe and stable operation of transmission lines.

[0086] Under normal circumstances, since traditional methods can only consider limited factors and situations, their prediction results may have certain uncertainties and errors and cannot accurately capture all potential risks. Therefore, there is a technical problem that the safety of transmission lines cannot be predicted. There is currently no effective solution to the above-mentioned technical problem that the safety of transmission lines cannot be predicted.

[0087] However, an embodiment of the present invention proposes a method for analyzing the impact of ground subsidence on transmission trunk lines based on remote sensing maps. By acquiring ground radar images and geographic coordinate information of transmission lines, the ground subsidence data corresponding to the radar images are matched with the geographic coordinates of the transmission lines to establish a training set, and a prediction model is trained. The prediction model is used to predict the impact of ground subsidence on transmission lines, thereby solving the technical problem of being unable to predict the safety of transmission lines and achieving the technical effect of predicting safety risks to transmission lines.

[0088] The embodiments of the present invention are further described below.

[0089] Figure 2 : is a flow chart of a method for analyzing the impact of ground subsidence on transmission trunk lines based on remote sensing maps according to an embodiment of the present invention, the method comprising the following steps:

[0090] Step S201, acquiring radar image data and performing preprocessing.

[0091] In this embodiment, radar image data from satellites (such as Sentinel-1, TerraSAR-X, etc.) is acquired, and the satellite data is preprocessed, including correction, registration, denoising, etc., to ensure the quality and consistency of the data.

[0092] Alternatively, radar image data is acquired from satellites which typically acquire radar images of the same area at regular time intervals.

[0093] Optionally, the radar image data is preprocessed, including correction, registration, denoising, etc., to ensure the quality and consistency of the data.

[0094] Optionally, an interference image is generated by calculating the phase difference using radar images taken at two different time points. The interference image is in complex form (interference complex number), which contains amplitude and phase information.

[0095] Optionally, the phase of the interference image usually contains a 2π jump, and the phase needs to be unwrapped to obtain continuous displacement information of the surface. The continuous phase unwrapping formula of formula (5) is usually used for unwrapping, which will not be repeated here.

[0096] Optionally, the unwrapped phase information represents the displacement of the ground surface, which can be calculated using the aforementioned formula (6), which will not be described in detail here.

[0097] Alternatively, the displacement estimation results can be used to monitor the settlement of the ground. The differences in displacement at different time points need to be considered and converted into changes in ground height.

[0098] Step S202, calculating the phase difference and analyzing the ground subsidence.

[0099] In this embodiment, an interferometric image is created between the first and second acquired radar images, phase information is extracted from the interferometric image, and the phase difference is converted into a ground displacement.

[0100] Optionally, an interferogram is created between the first and second acquired radar images. This typically involves multiplying the complex magnitudes and phases of the two images. Let the first image be I1, the second image be I2, and the interferogram be I int , as shown in the above formula (1), which will not be repeated here.

[0101] Optionally, phase information is extracted from the interference image. Usually, the phase information is contained in the argument of the complex image. The argument represents the phase of the wave and can be calculated by the above formula (2), which will not be repeated here.

[0102] Optionally, the phase difference Δφ between two InSAR images can be calculated by the aforementioned formula (3), which will not be described in detail here.

[0103] Optionally, finally, the phase difference is converted into ground displacement, that is, ground settlement data, which can be accomplished by the aforementioned formula (4) and will not be described in detail here.

[0104] Alternatively, InSAR is a remote sensing technology that uses radar interferometry to monitor surface deformation, and obtains information on surface deformation by comparing the phases of two or more radar images.

[0105] Step S203, obtaining geographic coordinate information of the communication transmission trunk line, and associating the ground subsidence data with the geographic coordinates of the transmission trunk line.

[0106] In this embodiment, the geographic coordinate information of the communication transmission trunk line is obtained, including the longitude and latitude data of each key point, and the estimated ground subsidence data is matched with the geographic coordinates of the transmission trunk line. Once the matching is completed, the ground subsidence data can be associated with the geographic coordinates of the transmission trunk line.

[0107] Optionally, the geographic coordinate information of the communication transmission trunk line is obtained, including the longitude and latitude data of each key point, and these coordinates are usually stored in a GIS database.

[0108] Optionally, the estimated ground subsidence data is matched to the geographic coordinates of the transmission trunk: the ground subsidence data is interpolated or gridded to obtain ground subsidence estimates at locations near the transmission trunk.

[0109] Optionally, collect raw data points of ground subsidence, including the amount of subsidence z i and the corresponding geographic coordinates (x i ,y i ), ensure the quality and accuracy of the data, and pre-process the data using inverse distance weighted (IDW) interpolation, which can be processed by the aforementioned formula (9) and will not be described in detail here.

[0110] Optionally, use GIS tools or Python to associate the estimated ground subsidence values ​​with the geographic coordinates of the transmission trunks, either by distance measurement or spatial join. Taking GIS tools as an example, it is divided into the following three steps: Data import: Import the generated subsidence grid data and the geographic coordinate data of the transmission trunks (usually in vector data formats such as Shapefile, GeoJSON. Spatial join: Use the "Spatial Join" function to associate the subsidence data with the transmission trunk data. Select an appropriate join type (such as "Nearest Neighbor" or "Spatial Intersection"). Result verification: Check the matching results to ensure that the subsidence data is accurately applied to each point of the transmission trunk, and verify whether there are errors or mismatches.

[0111] Optionally, once the matching is completed, the ground subsidence data can be associated with the geographical coordinates of the transmission trunk. The estimated ground subsidence value is associated with the corresponding transmission trunk coordinates. This can be expressed using the above formula (8), which will not be repeated here.

[0112] Optionally, the associated land subsidence data is visualized and analyzed together with the geographic coordinates of the transmission trunks, thereby enabling a better understanding of the impact of land subsidence on communication transmission trunks and supporting decision making.

[0113] Alternatively, GIS is a spatial information system that uses theories of system engineering and information science, supported by computer software and hardware, to scientifically manage and comprehensively analyze geographic data with spatial connotations to provide information required for planning, management, decision-making and research.

[0114] Step S204: creating a training set based on the acquired data.

[0115] In this embodiment, the acquired InSAR measurement data, geographic information (location and characteristics of transmission trunks), and possibly other relevant data are processed and used to train a neural network.

[0116] Optionally, preprocess InSAR data, geographic information and related data. Extract relevant features of ground subsidence and transmission trunks. Create labels representing the impact of subsidence on transmission trunks. Train the model with a neural network to establish the relationship between subsidence and trunk impact.

[0117] Step S205: training the prediction model using the training set.

[0118] In this embodiment, the cost function is applied to the entire training set, and all loss function values ​​are averaged. The optimal solution is the minimum value of the cost function. The ability to obtain the optimal solution proves that the indicator can be monitored through the GIS system, thereby predicting the impact of ground subsidence on the transmission network.

[0119] Optionally, a cost function is applied to the entire training set, as shown in the above formula (7), which will not be described again here.

[0120] Optionally, the actual data given by the value h(x (i) ) and the fitted line y (i) The corresponding value of is subtracted to find the gap between the fitted straight line and the actual value. The optimal solution is the minimum value of the cost function minJ(θ0,θ1). The ability to obtain the optimal solution proves that the indicator can be monitored through the GIS system, and then the impact of ground subsidence on the transmission network can be estimated.

[0121] Step S206: Use the prediction model to predict the impact of the current ground subsidence on the transmission network.

[0122] In this embodiment, a prediction model is used to predict the impact of current ground subsidence on the transmission network to obtain a prediction result.

[0123] Optionally, the present invention integrates remote sensing technology, GIS data, communication transmission trunk information and real-time monitoring functions to provide a comprehensive solution that can monitor settlement in real time, warn of potential problems in advance, and reduce maintenance costs, thereby improving the availability and reliability of transmission lines and reducing the risk of service interruptions.

[0124] Optionally, the present invention collects two or more InSAR satellite radar data, including phase information, calculates the phase difference between the two InSAR images, converts the phase difference into ground displacement to reflect the change of ground subsidence, and associates the estimated ground subsidence data with the geographical coordinates of the transmission trunk line. The geographical data of the transmission trunk line is usually collected for network planning and operation and maintenance purposes, and does not necessarily cover all areas that need to be analyzed. The spatial resolution and accuracy of the data may not be sufficient to accurately capture subtle ground subsidence conditions.

[0125] In this embodiment, by acquiring radar images of the ground and geographic coordinate information of the transmission line, the ground subsidence data corresponding to the radar image is matched with the geographic coordinates of the transmission line to establish a training set, and a prediction model is trained. The impact of ground subsidence on the transmission line is predicted by the prediction model, thereby solving the technical problem of being unable to predict the safety of the transmission line and achieving the technical effect of predicting the safety risks to the transmission line.

[0126] According to an embodiment of the present invention, a transmission line security prediction device is also provided. It should be noted that the transmission line security prediction device can be used to execute the transmission line security prediction method in embodiment 1.

[0127] Figure 3 Schematic diagram of a transmission line security prediction device according to an embodiment of the present invention. Figure 3 As shown, the transmission line security prediction device 300 may include: an acquisition unit 301 , a determination unit 302 and a prediction unit 303 .

[0128] The acquisition unit 301 is used to acquire multiple radar images of a target ground, wherein a transmission line is deployed on the target ground.

[0129] The determination unit 302 is used to determine ground subsidence data of the target ground based on the multiple radar images, wherein the ground subsidence data is used to indicate the subsidence amplitude of the target ground.

[0130] The prediction unit 303 is used to input the ground subsidence data into the target prediction model for prediction to obtain the safety result of the transmission line, wherein the target prediction model is obtained by training the historical ground subsidence data of the target ground and the geographic information of the transmission line, and the safety result is used to indicate the safety level of the transmission line on the target ground.

[0131] Optionally, the determination unit 302 may include: an establishment module for establishing an interference image based on multiple radar images; an extraction module for extracting phase information of the target ground from the interference image; and a first determination module for determining ground subsidence data of the target ground based on the phase information.

[0132] Optionally, the safety prediction device 300 for a transmission line may further include: a first acquisition unit, used to acquire historical ground subsidence data of a target ground; an establishment unit, used to establish a training set based on the historical ground subsidence data; and a training unit, used to train an initial prediction model based on the training set to obtain a target prediction model.

[0133] Optionally, the establishment unit may include: an acquisition module for acquiring the geographic information of the transmission line corresponding to the target ground; a matching module for matching the historical ground subsidence data with the geographic information of the transmission line to obtain a matching result; and an establishment module for establishing the historical ground subsidence data and the geographic information of the transmission line as a training set in response to a successful match between the historical ground subsidence data and the geographic information of the transmission line.

[0134] Optionally, the transmission line safety prediction device 300 may further include: a preprocessing unit, configured to preprocess the historical ground subsidence data to obtain preprocessed historical ground subsidence data.

[0135] Optionally, the transmission line safety prediction device 300 may further include: a visualization unit for visualizing historical ground subsidence data and geographic information of the transmission line.

[0136] In this embodiment, multiple radar images of the target ground are obtained, wherein a transmission line is deployed on the target ground; based on the multiple radar images, the ground subsidence data of the target ground is determined, wherein the ground subsidence data is used to indicate the subsidence amplitude of the target ground; the ground subsidence data is input into the target prediction model for prediction, and the safety result of the transmission line is obtained, wherein the target prediction model is obtained by training with the historical ground subsidence data of the target ground and the geographic information of the transmission line, and the safety result is used to indicate the safety degree of the transmission line on the target ground. That is to say, the present invention establishes a training set through the historical ground subsidence data of the target ground and the geographic information of the transmission line, and obtains the target prediction model by training with the training set, thereby obtaining the safety result of the transmission line according to the target prediction model, thereby solving the technical problem of being unable to predict the safety of the transmission line, and achieving the technical effect of predicting the technical problem of the safety of the transmission line.

[0137] According to an embodiment of the present invention, a computer-readable storage medium is further provided. The storage medium includes a stored program, wherein the program executes the security prediction method for the transmission line in Embodiment 1.

[0138] According to an embodiment of the present invention, a processor is further provided. The processor is used to run a program, wherein the security prediction method for the transmission line in Embodiment 1 is executed when the program is run.

[0139] According to an embodiment of the present invention, a computer program product is further provided. The computer program product includes computer instructions. When the computer instructions are executed by a processor, the security prediction method of the transmission line in Embodiment 1 is implemented.

[0140] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0141] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0143] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0144] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0145] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent functional component, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software functional component, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc., which can store program codes.

[0146] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A security prediction method for a transmission line, characterized in that: include: Acquire multiple radar images of a target ground surface, wherein a transmission line is deployed on the target ground surface; Determining ground subsidence data of the target ground based on the plurality of radar images, wherein the ground subsidence data is used to indicate a subsidence amplitude of the target ground; The ground subsidence data is input into a target prediction model for prediction to obtain a safety result of the transmission line, wherein the target prediction model is obtained through training with historical ground subsidence data of the target ground and geographic information of the transmission line, and the safety result is used to indicate the safety level of the transmission line on the target ground.

2. The method according to claim 1, characterized in that Determining ground subsidence data of the target ground based on the plurality of radar images includes: Based on the plurality of radar images, establishing an interference image; Extracting the phase information of the target ground from the interference image; Based on the phase information, the ground subsidence data of the target ground is determined.

3. The method according to claim 1, characterized in that The method further comprises: Acquiring the historical ground subsidence data of the target ground; Based on the historical land subsidence data, establishing a training set; Based on the training set, the initial prediction model is trained to obtain the target prediction model.

4. The method according to claim 3, characterized in that Based on the historical land subsidence data, a training set is established, including: Acquire the geographic information of the transmission line corresponding to the target ground; Matching the historical ground subsidence data with the geographic information of the transmission line to obtain a matching result; In response to successful matching of the historical ground subsidence data with the geographic information of the transmission line, the historical ground subsidence data and the geographic information of the transmission line are established as the training set.

5. The method according to claim 4, characterized in that Before matching the historical ground subsidence data with the geographic information of the transmission line to obtain a matching result, the method further includes: The historical land subsidence data is preprocessed to obtain the preprocessed historical land subsidence data.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: The historical ground subsidence data and the geographic information of the transmission line are visualized.

7. A safety prediction device for a transmission line, characterized in that: include: An acquisition unit, configured to acquire a plurality of radar images of a target ground surface, wherein a transmission line is deployed on the target ground surface; a determining unit, configured to determine ground subsidence data of the target ground based on the plurality of radar images, wherein the ground subsidence data is used to indicate a subsidence amplitude of the target ground; A prediction unit is used to input the ground subsidence data into a target prediction model for prediction to obtain a safety result of the transmission line, wherein the target prediction model is obtained through training with historical ground subsidence data of the target ground and geographic information of the transmission line, and the safety result is used to indicate the safety level of the transmission line on the target ground.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 6.

9. A processor, characterized in that: The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 6 when running.

10. A computer program product, characterized in that The computer program product comprises computer instructions, which implement the method according to any one of claims 1 to 6 when executed by a processor.

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