Power transmission line landslide geological disaster monitoring and early warning method, device, equipment and medium

Abstract

The present disclosure relates to a power transmission line landslide geological disaster monitoring and early warning method, device, equipment and medium, the method comprising: acquiring at least two radar remote sensing satellite images, respectively using SBAS-InSAR technology and D-InSAR technology to extract the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images; according to the deformation area, the deformation rate and the historical landslide point, the deformation risk level of the deformation area is determined, and the target deformation area meeting the target deformation risk level is selected; using LiDAR and optical camera to obtain two groups of aircraft monitoring data of the target deformation area before and after the occurrence of key weather, and to determine the landslide hidden danger point; collecting the vibration signals of the landslide hidden danger point and the tower on the power transmission line, and determining the landslide risk level of the power transmission line in the target deformation area according to the vibration signals; according to the landslide risk level of the power transmission line, the preset monitoring and early warning platform is used to issue early warning information. The present disclosure can improve the prediction accuracy of landslide geological disasters and improve the early warning capability.

Description

Technical Field

[0001] This disclosure relates to the field of power transmission line safety protection technology, and in particular to a method, device, equipment and medium for monitoring and early warning of landslide geological disasters along power transmission lines. Background Technology

[0002] Landslides near power transmission towers can easily expose and damage the tower foundation, and in severe cases, cause the tower to tilt and collapse. Rainstorm-induced landslides have become one of the major hazards threatening the safe operation of power lines. These landslide hazards are numerous and widespread, and important power transmission lines are often located in high-altitude and densely vegetated areas. Currently, manual investigation and inspection of these hazard points are necessary, but manual investigation and inspection are difficult to detect and have significant limitations. Summary of the Invention

[0003] To address the aforementioned technical problems, this disclosure provides a method, device, equipment, and medium for monitoring and early warning of landslide geological disasters along power transmission lines.

[0004] According to one aspect of this disclosure, a method for monitoring and early warning of geological hazards such as landslides along power transmission lines is provided, comprising:

[0005] Acquire at least two types of radar remote sensing satellite images, and use SBAS-InSAR and D-InSAR technologies respectively to extract the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images;

[0006] The deformation risk level of the deformation area is determined based on the deformation area, the deformation rate, and the previously acquired historical landslide points, and a target deformation area that meets the target deformation risk level is selected based on the deformation risk level.

[0007] Two sets of aircraft monitoring data were acquired using LiDAR and optical cameras before and after the occurrence of critical weather in the target deformation area. Each set of aircraft monitoring data included: a ground digital elevation model (DEM) and visible light imagery.

[0008] Based on the two sets of aircraft monitoring data before and after the occurrence of critical weather, landslide hazard points along the power transmission line were identified;

[0009] Vibration signals were collected from the landslide hazard points and the towers on the transmission lines, and the landslide risk level of the transmission lines within the target deformation area was determined based on the vibration signals.

[0010] Based on the landslide risk level of the transmission line, early warning information is issued through a pre-set monitoring and early warning platform.

[0011] According to another aspect of this disclosure, a monitoring and early warning device for landslide geological disasters along power transmission lines is provided, comprising:

[0012] The image acquisition module is used to acquire at least two types of radar remote sensing satellite images, and to extract the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images using SBAS-InSAR and D-InSAR technologies respectively.

[0013] The deformation level determination module is used to determine the deformation risk level of the deformation area based on the deformation area, the deformation rate and the pre-acquired historical landslide points, and to select a target deformation area that meets the target deformation risk level based on the deformation risk level.

[0014] The aerial monitoring module is used to acquire two sets of aircraft monitoring data of the target deformation area before and after the occurrence of critical weather using LiDAR and optical cameras. Each set of aircraft monitoring data includes: ground digital elevation model (DEM) and visible light imagery.

[0015] The landslide point determination module is used to determine potential landslide points along the power transmission line based on two sets of aircraft monitoring data before and after the occurrence of critical weather.

[0016] The landslide level determination module is used to collect vibration signals from the landslide hazard points and the towers on the transmission line, and to determine the landslide risk level of the transmission line within the target deformation area based on the vibration signals.

[0017] The early warning module is used to issue early warning information through a preset monitoring and early warning platform based on the landslide risk level of the transmission line.

[0018] According to another aspect of this disclosure, an electronic device is provided, the electronic device comprising:

[0019] processor;

[0020] Memory used to store the processor's executable instructions;

[0021] The processor is configured to read the executable instructions from the memory and execute the instructions to implement the above method.

[0022] According to another aspect of this disclosure, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the above-described method.

[0023] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0024] The method, apparatus, equipment, and medium for monitoring and early warning of landslide geological disasters along power transmission lines provided in this disclosure include: acquiring at least two types of radar remote sensing satellite images; extracting the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images using SBAS-InSAR and D-InSAR technologies, respectively; determining the deformation risk level of the deformation area based on the deformation area, deformation rate, and pre-acquired historical landslide points; selecting a target deformation area that meets the target deformation risk level based on the deformation risk level; acquiring two sets of aircraft monitoring data of the target deformation area before and after critical weather events using LiDAR and an optical camera, each set of aircraft monitoring data including: a ground digital elevation model (DEM) and visible light images; identifying landslide hazard points along the power transmission line based on the two sets of aircraft monitoring data before and after critical weather events; collecting vibration signals from landslide hazard points and towers on the power transmission line; determining the landslide risk level of the power transmission line within the target deformation area based on the vibration signals; and issuing early warning information through a preset monitoring and early warning platform based on the landslide risk level of the power transmission line.

[0025] This technical solution enables three-dimensional monitoring of landslide geological hazards along power transmission lines using data from multiple distances, including satellite, air, and ground. "Satellite" refers to radar remote sensing satellite imagery monitored by remote sensing satellites, which can be used to identify high-risk deformation areas. "Air" refers to DEM and visible light imagery monitored by aerial drones, which can be used to identify potential landslide sites along the power transmission line. "Ground" refers to vibration signals monitored by ground monitoring devices, which can be used to determine the landslide risk level of the deformation area. Under this integrated satellite-air-ground monitoring, a comprehensive survey, detailed investigation, and verification of landslide hazards near power transmission lines can be achieved, assessing the impact of landslides on power transmission lines before and after heavy rain, enabling continuous monitoring of landslides, facilitating early detection of potential landslide signs, providing early warnings, and reducing disaster risks. Therefore, this disclosure can improve the accuracy of predicting landslide hazards along power transmission lines during heavy rain and ensure the safe operation of the power grid. Attached Figure Description

[0026] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0027] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a flowchart of the method for monitoring and early warning of landslide geological disasters along power transmission lines, as described in this embodiment.

[0029] Figure 2 This is a schematic diagram of a multi-source stereoscopic observation system according to an embodiment of the present disclosure;

[0030] Figure 3 This is a deformation rate diagram of an embodiment of the present disclosure;

[0031] Figure 4 This is a schematic diagram of the target deformation region in an embodiment of this disclosure;

[0032] Figure 5 This is a schematic diagram of the landslide area according to an embodiment of the present disclosure;

[0033] Figure 6 This is a schematic diagram of the structure of the monitoring and early warning platform according to an embodiment of this disclosure;

[0034] Figure 7 This is a structural block diagram of a power transmission line landslide geological disaster monitoring and early warning device according to an embodiment of this disclosure;

[0035] Figure 8 This is a schematic diagram of the electronic device structure according to an embodiment of the present disclosure. Detailed Implementation

[0036] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0037] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0038] Traditional manual surveys and investigations are insufficient to detect potential landslide hazards caused by rainstorms along power transmission lines. To overcome the limitations of traditional manual surveys and investigations, this disclosure provides a method, device, equipment, and medium for monitoring and early warning of landslide hazards along power transmission lines. This technical solution constructs a multi-source, three-dimensional observation system integrating synthetic aperture radar interferometry, airborne LiDAR measurement technology, and ground vibration measurement technology to identify major geological hazard risks at an early stage. Furthermore, based on understanding the deformation patterns and stages of landslide collapses, as well as their temporal and spatial deformation characteristics, a hierarchical comprehensive risk early warning system is established. A real-time geological hazard monitoring and early warning system is then utilized to gradually realize the practical application and operationalization of geological hazard monitoring and early warning. For ease of understanding, the embodiments of this disclosure are described below.

[0039] Figure 1The flowchart of a monitoring and early warning method for landslide geological disasters of transmission lines provided by an embodiment of the present disclosure. This method can be executed by a monitoring and early warning device for landslide geological disasters of transmission lines configured on a terminal, and this device can be implemented by software and / or hardware. The monitoring and early warning method for landslide geological disasters of transmission lines is applied to a multi-source three-dimensional observation system integrating space, air, and ground, such as Figure 2 As shown, this multi-source three-dimensional observation system can include: satellite monitoring using synthetic aperture radar interferometry technology, UAV identification using airborne LiDAR and optical cameras, and ground monitoring with vibration frequency monitoring devices arranged.

[0040] Such as Figure 1 As shown, the monitoring and early warning method for landslide geological disasters of transmission lines can include the following steps.

[0041] S102. Obtain at least two radar remote sensing satellite images, and respectively use SBAS-InSAR technology and D-InSAR technology to extract the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images. Among them, the radar remote sensing satellite images can include: C-band remote sensing satellite images and L-band remote sensing satellite images.

[0042] In this embodiment, for multiple groups of C-band remote sensing satellite images, use SBAS-InSAR technology to process the C-band remote sensing satellite images to obtain a first effective spatio-temporal baseline pair, and the first effective spatio-temporal baseline pair is a spatio-temporal baseline pair that meets the preset spatio-temporal threshold and spatial distance; determine the first deformation rate map of the monitoring area based on the first effective spatio-temporal baseline pair.

[0043] In a specific embodiment, the full name of SBAS-InSAR is Small Baseline Subset InSAR, which represents the differential interferometric short baseline set time series analysis technology. Use SBAS-InSAR technology to process the C-band remote sensing satellite images to obtain a relatively large number of spatio-temporal baseline pairs. Determine the spatio-temporal baseline pairs that meet the preset spatio-temporal threshold and spatial distance as the first effective spatio-temporal baseline pair; among them, the above spatio-temporal threshold is time t < t0 days (such as t < 36 days), and the spatial distance is d < d0 meters (such as d < 150 meters).

[0044] Next, based on the first effective spatio-temporal baseline pairs with a coherence coefficient higher than the first coefficient value (such as 0.7), obtain time series SAR interferograms. Exemplarily, select the first effective spatio-temporal baseline pairs with a coherence coefficient > 0.7 to obtain multiple groups of effective time series SAR interferograms.

[0045] Simultaneously, densely vegetated areas are determined based on the first effective spatiotemporal baseline pair within a first range of coherence coefficients; the coherence coefficient of these densely vegetated areas is then improved using DS-InSAR technology. In one example, the densely vegetated areas are determined based on the first effective spatiotemporal baseline pair with coherence coefficients within the range of [0.3, 0.7]. The coherence coefficient of these densely vegetated areas is improved using DS-InSAR technology to enhance their scattering capability. Subsequently, based on the temporal SAR interferogram and the densely vegetated areas with improved coherence coefficients, the first deformation rate map of the monitored area is determined.

[0046] In this embodiment, for multiple sets of L-band remote sensing satellite images, D-InSAR technology is used to process the L-band remote sensing satellite images to obtain a second effective spatiotemporal baseline pair; based on the second effective spatiotemporal baseline pair, a second deformation rate map of the monitoring area is determined.

[0047] In a specific embodiment, D-InSAR stands for Differential InSAR, which represents the differential interferometry technique of synthetic aperture radar. The process of processing L-band remote sensing satellite imagery using D-InSAR technology to obtain the second effective spatiotemporal baseline pair can be referred to the embodiment described above for obtaining the first effective spatiotemporal baseline pair.

[0048] Next, a D-InSAR interferogram is obtained based on a second effective spatiotemporal baseline pair with a coherence coefficient higher than the second coefficient value; the second coefficient value is, for example, 0.7. Densely vegetated areas are determined based on the second effective spatiotemporal baseline pair within a second range of coherence coefficients; the second range may be the same as or different from the aforementioned first range. The coherence coefficient of the densely vegetated areas is improved using DS-InSAR technology. Based on the D-InSAR interferogram and the densely vegetated areas with improved coherence coefficients, a second deformation rate map of the monitored area is determined.

[0049] like Figure 3 As shown, after obtaining the first deformation rate map for C-band remote sensing satellite imagery and the second deformation rate map for L-band remote sensing satellite imagery according to the above embodiments, the deformation area and deformation rate of the surface of the monitoring area can be determined by comparing the first deformation rate map and the second deformation rate map; the deformation rate refers to the annual average deformation rate.

[0050] S104. Determine the deformation risk level of the deformation area based on the deformation area, deformation rate, and pre-acquired historical landslide points, and select the target deformation area that meets the target deformation risk level based on the deformation risk level.

[0051] In this embodiment, data such as transmission lines, deformation areas, deformation rates, and historical landslide points can be combined to classify deformation risk levels of deformation areas, and areas with higher average annual deformation rates near transmission lines can be selected from multiple deformation areas to form target deformation areas that meet the target deformation risk level.

[0052] In one example, the deformation risk can be divided into three levels according to severity, from low to high.

[0053] Deformation Risk Level 1: The deformation rate is not greater than the first rate value (e.g., V≤20mm / y), and the distance between the deformation area and the tower on the transmission line is not less than the first distance value (e.g., D≥2000 meters), and there are no historical landslide points within the distance between the deformation area and the tower. Deformation Risk Level 1 indicates a low-risk deformation area that has no impact on the tower, and there is no need to verify this deformation area.

[0054] Deformation Risk Level 2: Situations that are neither Deformation Risk Level 1 nor Deformation Risk Level 3 can be classified as Deformation Risk Level 2. Deformation Risk Level 2 indicates a medium-risk deformation area with a moderate impact on the tower, and this deformation area needs to be checked regularly using C-band satellite and SBAS technology.

[0055] Deformation Risk Level 3: The deformation rate is greater than the second rate value (e.g., V>50mm / y), and the distance between the deformation area and the tower is less than the second distance value (e.g., D<800 meters), and there are historical landslide points within the distance between the deformation area and the tower; wherein, the second rate value is greater than the first rate value, and the second distance value is greater than the first distance value. Deformation Risk Level 3 indicates a high-risk deformation area that poses a serious threat to the tower, requiring the use of drones or other aircraft to verify the deformation area.

[0056] Based on the above deformation risk levels, the method for determining the deformation risk level of the deformation region in this embodiment may include:

[0057] Determine the target distance between the deformation zone and the towers on the power transmission line;

[0058] If the deformation rate corresponding to the deformation area is not greater than the first rate value (V≤20mm / y), the target distance is not less than the first distance value (D≥2000 meters), and there are no historical landslide points within the target distance, then the deformation area is determined to be of low risk level.

[0059] If the deformation rate corresponding to the deformation area is greater than the second rate value (V>50mm / y), the target distance is less than the second distance value (D<800 meters), and there are historical landslide points within the target distance, then the deformation area is determined to be of high risk level.

[0060] If the deformed area does not match either the low-risk or high-risk level, then the deformed area is determined to be at the medium-risk level.

[0061] After determining the deformation risk level of each deformation region, target deformation regions that meet the target deformation risk level are selected; for example, if the target deformation risk level is high risk, then the high-risk deformation regions are identified as target deformation regions to be further monitored using aerial and ground-based methods. (Refer to...) Figure 4 The diagram shows the buffer analysis of the polarization time series results of the target deformation region in a certain city.

[0062] S106. Use LiDAR and optical cameras to acquire two sets of aircraft monitoring data of the target deformation area before and after the occurrence of critical weather. Each set of aircraft monitoring data includes: DEM (Digital Elevation Model) and visible light imagery.

[0063] Critical weather conditions refer to weather events such as heavy rain and mudslides that affect the reliability of power transmission lines. For example, before and after heavy rain, a drone equipped with LiDAR and an optical camera was controlled to fly along the power transmission line. Based on this, LiDAR was used to acquire the DEM (Diagram of the Deformed Area) of the target area before and after the heavy rain; LiDAR, short for Light Detection and Ranging, uses lasers for detection and measurement to obtain point cloud data and generate a precise DEM. The optical camera was used to acquire visible light images of the target area before and after the heavy rain. Thus, a set of drone monitoring data, including DEM and visible light images, was obtained before and after the heavy rain.

[0064] S108. Based on the monitoring data of two sets of aircraft before and after the occurrence of critical weather, landslide hazard points along the power transmission line were identified.

[0065] This embodiment includes: First, differentially analyzing two DEMs before and after the critical weather event, and identifying topographic anomalies where the terrain change range exceeds a first area value based on the differential results. Specifically, differentially analyzing two DEMs before and after the rainstorm, if the terrain change range exceeds a first area value (e.g., ΔS > 500m²), the target deformation area is considered a topographic anomaly, belonging to a suspected landslide area, which can be referenced. Figure 5 The image below is shown.

[0066] Then, the displacement of the topographic anomaly point between two visible light images before and after the critical weather event is compared to determine whether the topographic anomaly point is a potential landslide site. Visible light images can be referenced. Figure 5 As shown in the image above; specifically, the displacement of the terrain anomaly point between two visible light images before and after the rainstorm can be compared. When the displacement is greater than the displacement threshold, the terrain anomaly point is identified as a key landslide hazard point near the transmission line.

[0067] S110. Collect vibration signals from landslide hazard points and transmission line towers, and determine the landslide risk level of transmission lines within the target deformation area based on the vibration signals.

[0068] In this embodiment, a vibration frequency monitoring device can be deployed on the ground near the transmission line. Specifically, the vibration frequency monitoring device can be deployed at the tower and landslide area. The vibration frequency monitoring device can collect vibration signals from the landslide hazard point and the tower on the transmission line in real time. Based on the vibration signals, the landslide risk level of the transmission line in the target deformation area can be determined. The specific implementation process can include the following.

[0069] The vibration impact acceleration and tower vibration frequency are determined based on the vibration signal; the landslide risk level of the transmission line within the target deformation area is determined based on the vibration impact acceleration, tower vibration frequency, and the target distance between the target deformation area and the tower on the transmission line.

[0070] For example, slope risk levels can be classified from low to high severity as follows.

[0071] Low risk: The combined acceleration of vibration and impact is less than the first acceleration value (e.g., a < 0.1 Hz), and the target distance between the deformation area of ​​the target and the tower on the power transmission line is greater than the first distance value (e.g., D > 2000 meters), and the landslide scale is less than the first volume value (e.g., V < 1,000 cubic meters). A blue warning can be issued when the landslide risk level is low.

[0072] In one example, medium risk: a situation that is neither low risk nor high risk can be identified as medium risk.

[0073] In another example, medium risk can also be divided into medium-low risk and medium-high risk. Medium-low risk is defined as follows: the combined acceleration of vibration and impact is in the first acceleration range (e.g., 0.1Hz ≤ a < 1Hz), the target distance between the deformation area and the tower on the transmission line is in the first distance range (e.g., 800 meters ≤ D < 2000 meters), and the tower vibration frequency is in the first frequency range (e.g., F < 10Hz). When the landslide risk level is medium-low, a yellow warning can be issued, and inspection personnel can be arranged for on-site geological investigation.

[0074] Medium to high risk: The combined acceleration of vibration and impact is in the second acceleration range (e.g., 1Hz ≤ a < 2Hz), the target distance between the deformation area and the tower on the transmission line is in the second distance range (e.g., D < 800 meters), the tower vibration frequency is in the second frequency range (e.g., 10Hz ≤ F < 20Hz), and the landslide scale is not less than the first volume value (e.g., V ≥ 1,000 cubic meters). In cases where the landslide risk level is medium to high, an orange alert can be issued, and inspection personnel can be arranged to conduct on-site geological surveys and formulate disaster prevention measures as needed.

[0075] High risk: The combined acceleration of vibration and impact is less than the second acceleration value (e.g., a>2Hz), and the target distance between the deformation area of ​​the target and the tower on the transmission line is less than the second distance value (e.g., D<800 meters), and the tower vibration frequency is greater than the frequency threshold (e.g., F>20Hz). In cases of high landslide risk, the impact on the stability of the tower foundation is significant, threatening structural safety. Therefore, a red alert can be issued, and inspection personnel can be dispatched to conduct on-site geological surveys and formulate disaster prevention measures.

[0076] S112. Based on the landslide risk level of the transmission line, issue early warning information through a pre-set monitoring and early warning platform.

[0077] like Figure 6 As shown, the monitoring and early warning platform in this embodiment is specifically a three-dimensional transmission line landslide geological disaster monitoring and early warning platform based on multi-source data from space and ground, which may include the following modules:

[0078] The ground monitoring module is used to query ground devices and visualize vibration signals. Specifically, the ground monitoring module can process, transmit, query, calculate, and visualize data from the ground; for example, it can query ground devices such as vibration frequency monitoring devices and transmit, process, and display vibration signals.

[0079] The satellite monitoring module is used to query radar remote sensing satellite imagery and visualize the deformation area and deformation rate of the monitored area. Specifically, the satellite monitoring module can process, query, calculate, and visualize data from satellites, such as C-band and L-band remote sensing satellite imagery, and the deformation area and deformation rate of the monitored area.

[0080] The drone monitoring module is used to query and visualize aircraft monitoring data. Specifically, the drone monitoring module can process, query, calculate, and visualize data from the air, such as aircraft monitoring data acquired using LiDAR and optical cameras, and landslide hazard points identified based on the aircraft monitoring data.

[0081] The hazard and risk analysis module is used for comprehensive analysis, querying, and display of hazard and risk data from multiple channels including space, air, and ground. Specifically, the hazard and risk analysis module is connected to the ground monitoring module, satellite monitoring module, and UAV monitoring module. It receives data from these three channels and performs comprehensive hazard and risk analysis, querying, and display of the aforementioned multi-channel data.

[0082] The data query module is used to query and graphically display data from multiple channels of the Starry Sky and Earth system.

[0083] The Monitoring Overview module is used to process multi-channel data from space, air, and ground based on GIS positioning, and to display power grid lines and tower layers. Specifically, the Monitoring Overview module is a GIS-based integrated space-air-ground data statistics, early warning analysis, query, and positioning display system that supports the display of power grid lines and tower layers, enabling integrated analysis and overall control.

[0084] In summary, the method for monitoring and early warning of landslide geological disasters along power transmission lines provided in this disclosure includes: acquiring at least two types of radar remote sensing satellite images; extracting the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images using SBAS-InSAR and D-InSAR technologies, respectively; determining the deformation risk level of the deformation area based on the deformation area, deformation rate, and pre-acquired historical landslide points; selecting a target deformation area that meets the target deformation risk level based on the deformation risk level; acquiring two sets of aircraft monitoring data of the target deformation area before and after the occurrence of critical weather using LiDAR and an optical camera, each set of aircraft monitoring data including: a ground digital elevation model (DEM) and visible light imagery; identifying landslide hazard points along the power transmission line based on the two sets of aircraft monitoring data before and after the occurrence of critical weather; collecting vibration signals from landslide hazard points and towers on the power transmission line; determining the landslide risk level of the power transmission line within the target deformation area based on the vibration signals; and issuing early warning information through a preset monitoring and early warning platform based on the landslide risk level of the power transmission line.

[0085] This technical solution enables three-dimensional monitoring of landslide geological hazards along power transmission lines using data from multiple distances, including satellite, air, and ground. "Satellite" refers to radar remote sensing satellite imagery monitored by remote sensing satellites, which can be used to identify high-risk deformation areas. "Air" refers to DEM and visible light imagery monitored by aerial drones, which can be used to identify potential landslide sites along the power transmission line. "Ground" refers to vibration signals monitored by ground monitoring devices, which can be used to determine the landslide risk level of the deformation area. Under this integrated satellite-air-ground monitoring, a comprehensive survey, detailed investigation, and verification of landslide hazards near power transmission lines can be achieved, assessing the impact of landslides on power transmission lines before and after heavy rain, enabling continuous monitoring of landslides, facilitating early detection of potential landslide signs, providing early warnings, and reducing disaster risks. Therefore, this disclosure can improve the accuracy of predicting landslide hazards along power transmission lines during heavy rain and ensure the safe operation of the power grid.

[0086] Figure 7 This is a structural block diagram of a power transmission line landslide geological disaster monitoring and early warning device provided in an embodiment of this disclosure. This device is used to implement the aforementioned power transmission line landslide geological disaster monitoring and early warning method. (Refer to...) Figure 7 The device includes the following modules:

[0087] Image acquisition module 210 is used to acquire at least two types of radar remote sensing satellite images, and respectively use SBAS-InSAR technology and D-InSAR technology to extract the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images.

[0088] The deformation level determination module 220 is used to determine the deformation risk level of the deformation area based on the deformation area, the deformation rate and the pre-acquired historical landslide points, and to select a target deformation area that meets the target deformation risk level based on the deformation risk level.

[0089] The aerial monitoring module 230 is used to acquire two sets of aircraft monitoring data of the target deformation area before and after the occurrence of critical weather using LiDAR and optical cameras. Each set of aircraft monitoring data includes: ground digital elevation model (DEM) and visible light imagery.

[0090] The landslide point determination module 240 is used to determine potential landslide points along the power transmission line based on two sets of aircraft monitoring data before and after the occurrence of critical weather.

[0091] The landslide level determination module 250 is used to collect vibration signals from the landslide hazard points and the towers on the transmission line, and to determine the landslide risk level of the transmission line in the target deformation area based on the vibration signals.

[0092] The early warning module 260 is used to issue early warning information through a preset monitoring and early warning platform based on the landslide risk level of the transmission line.

[0093] In one embodiment, the radar remote sensing satellite imagery includes: C-band remote sensing satellite imagery and L-band remote sensing satellite imagery; the image acquisition module 210 is further configured to:

[0094] The C-band remote sensing satellite imagery is processed using SBAS-InSAR technology to obtain a first effective spatiotemporal baseline pair, which is a spatiotemporal baseline pair that meets the preset spatiotemporal threshold and spatial distance.

[0095] The L-band remote sensing satellite imagery was processed using D-InSAR technology to obtain a second effective spatiotemporal baseline pair;

[0096] Based on the first effective spatiotemporal baseline, a first deformation rate map of the determined monitoring area is obtained;

[0097] The second deformation rate map of the monitoring area is determined based on the second effective spatiotemporal baseline.

[0098] By comparing the first deformation rate map and the second deformation rate map, the deformation area and deformation rate of the monitoring area are determined.

[0099] In one embodiment, the image acquisition module 210 is further configured to:

[0100] Based on the first effective spatiotemporal baseline pair with a coherence coefficient higher than the first coefficient value, a temporal SAR interferogram is obtained;

[0101] The dense vegetation area is determined based on the first effective spatiotemporal baseline within the first range of the coherence coefficient.

[0102] The coherence coefficient of the densely vegetated area was improved by using DS-InSAR technology.

[0103] Based on the time-series SAR interferogram and the dense vegetation area after improving the coherence coefficient, the first deformation rate map of the monitoring area is determined.

[0104] In one embodiment, the deformation level determination module 220 is further configured to:

[0105] Determine the target distance between the deformation area and the tower on the transmission line;

[0106] If the deformation rate corresponding to the deformation area is not greater than the first rate value, the target distance is not less than the first distance value, and there are no historical landslide points within the target distance, then the deformation area is determined to be of low risk level.

[0107] If the deformation rate corresponding to the deformation area is greater than the second rate value, the target distance is less than the second distance value, and there is a historical landslide point within the target distance, then the deformation area is determined to be of high risk level; wherein, the second rate value is greater than the first rate value, and the second distance value is greater than the first distance value;

[0108] If the deformed area does not match either the low-risk level or the high-risk level, then the deformed area is determined to be at the medium-risk level.

[0109] In one embodiment, the landslide point determination module 240 is further configured to:

[0110] The two DEMs before and after the critical weather event are differentially analyzed, and the terrain anomaly points with a terrain change range greater than the first area value are identified based on the differential results.

[0111] By comparing the displacement of real-time terrain anomalies between two visible light images before and after a critical weather event, it is determined whether the terrain anomaly is a potential landslide hazard point based on the displacement.

[0112] In one embodiment, the landslide grade determination module 250 is further configured to:

[0113] The vibration impact acceleration and the tower vibration frequency are determined based on the vibration signal.

[0114] Based on the combined vibration and impact acceleration, the tower vibration frequency, and the target distance between the target deformation area and the tower on the transmission line, the landslide risk level of the transmission line within the target deformation area is determined.

[0115] In one embodiment, the monitoring and early warning platform includes:

[0116] The ground monitoring module is used to query ground devices and visualize the vibration signals;

[0117] The satellite monitoring module is used to query radar remote sensing satellite images and visualize the deformation area and deformation rate of the monitored area.

[0118] The drone monitoring module is used to query and visualize the monitoring data of the aircraft.

[0119] The hidden danger and risk analysis module is used for comprehensive analysis, query and display of hidden dangers and risks from multiple channels of data from the space and ground.

[0120] The data query module is used to query and graphically display multi-channel data from the Starry Sky and Earth.

[0121] The monitoring overview module is used to process multi-channel data from the sky and ground based on GIS positioning, and to display power grid lines and tower layers.

[0122] The device provided in this embodiment has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0123] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Figure 8 As shown, the electronic device 300 includes one or more processors 301 and memory 302.

[0124] The processor 301 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device 300 to perform desired functions.

[0125] The memory 302 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 301 may execute the program instructions to implement the transmission line landslide geological disaster monitoring and early warning method described above in the embodiments of this disclosure, and / or other desired functions. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage medium.

[0126] In one example, the electronic device 300 may also include an input device 303 and an output device 304, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0127] In addition, the input device 303 may also include, for example, a keyboard, a mouse, etc.

[0128] The output device 304 can output various information to the outside, including determined distance information, direction information, etc. The output device 304 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0129] Of course, for the sake of simplicity, Figure 8 Only some of the components of the electronic device 300 relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device 300 may include any other suitable components depending on the specific application.

[0130] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program for executing the above-described method for monitoring and early warning of geological disasters caused by landslides along power transmission lines.

[0131] The computer program product of the method, device, electronic device and medium for monitoring and early warning of landslide geological disasters along power transmission lines provided in this disclosure includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0132] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0133] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring and early warning of landslide geological hazards along power transmission lines, characterized in that, include: Acquire at least two types of radar remote sensing satellite images, and use SBAS-InSAR and D-InSAR technologies respectively to extract the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images; The deformation risk level of the deformation area is determined based on the deformation area, the deformation rate, and the previously acquired historical landslide points, and a target deformation area that meets the target deformation risk level is selected based on the deformation risk level. Two sets of aircraft monitoring data were acquired using LiDAR and optical cameras before and after the occurrence of critical weather in the target deformation area. Each set of aircraft monitoring data included: a ground digital elevation model (DEM) and visible light imagery. Based on the two sets of aircraft monitoring data before and after the occurrence of critical weather, landslide hazard points along the power transmission line were identified; Vibration signals were collected from the landslide hazard points and the towers on the transmission lines, and the landslide risk level of the transmission lines within the target deformation area was determined based on the vibration signals. Based on the landslide risk level of the transmission line, early warning information is issued through a pre-set monitoring and early warning platform.

2. The method according to claim 1, characterized in that, The radar remote sensing satellite imagery includes C-band and L-band remote sensing satellite imagery; the extraction of surface deformation information of the monitoring area from the radar remote sensing satellite imagery using SBAS-InSAR and D-InSAR technologies respectively includes: The C-band remote sensing satellite imagery is processed using SBAS-InSAR technology to obtain a first effective spatiotemporal baseline pair, which is a spatiotemporal baseline pair that meets the preset spatiotemporal threshold and spatial distance. The L-band remote sensing satellite imagery was processed using D-InSAR technology to obtain a second effective spatiotemporal baseline pair; Based on the first effective spatiotemporal baseline, a first deformation rate map of the determined monitoring area is obtained; The second deformation rate map of the monitoring area is determined based on the second effective spatiotemporal baseline. By comparing the first deformation rate map and the second deformation rate map, the deformation area and deformation rate of the monitoring area are determined.

3. The method according to claim 2, characterized in that, The first deformation rate map of the determined monitoring area based on the first effective spatiotemporal baseline includes: Based on the first effective spatiotemporal baseline pair with a coherence coefficient higher than the first coefficient value, a temporal SAR interferogram is obtained; The dense vegetation area is determined based on the first effective spatiotemporal baseline within the first range of the coherence coefficient. The coherence coefficient of the densely vegetated area was improved by using DS-InSAR technology. Based on the time-series SAR interferogram and the dense vegetation area after improving the coherence coefficient, the first deformation rate map of the monitoring area is determined.

4. The method according to claim 1, characterized in that, Determining the deformation risk level of the deformation area based on the deformation area, the deformation rate, and pre-acquired historical landslide points includes: Determine the target distance between the deformation area and the tower on the transmission line; If the deformation rate corresponding to the deformation area is not greater than the first rate value, the target distance is not less than the first distance value, and there are no historical landslide points within the target distance, then the deformation area is determined to be of low risk level. If the deformation rate corresponding to the deformation area is greater than the second rate value, the target distance is less than the second distance value, and there is a historical landslide point within the target distance, then the deformation area is determined to be of high risk level; wherein, the second rate value is greater than the first rate value, and the second distance value is greater than the first distance value; If the deformed area does not match either the low-risk level or the high-risk level, then the deformed area is determined to be at the medium-risk level.

5. The method according to claim 1, characterized in that, The method of identifying potential landslide sites along the power transmission line based on two sets of aircraft monitoring data before and after the occurrence of critical weather conditions includes: The two DEMs before and after the critical weather event are differentially analyzed, and the terrain anomaly points with a terrain change range greater than the first area value are identified based on the differential results. By comparing the displacement of real-time terrain anomalies between two visible light images before and after a critical weather event, it is determined whether the terrain anomaly is a potential landslide hazard point based on the displacement.

6. The method according to claim 1, characterized in that, The step of determining the landslide risk level of the transmission line within the target deformation area based on the vibration signal includes: The vibration impact acceleration and the tower vibration frequency are determined based on the vibration signal. Based on the combined vibration and impact acceleration, the tower vibration frequency, and the target distance between the target deformation area and the tower on the transmission line, the landslide risk level of the transmission line within the target deformation area is determined.

7. The method according to any one of claims 1 to 6, characterized in that, The monitoring and early warning platform includes: The ground monitoring module is used to query ground devices and visualize the vibration signals; The satellite monitoring module is used to query radar remote sensing satellite images and visualize the deformation area and deformation rate of the monitored area. The drone monitoring module is used to query and visualize the monitoring data of the aircraft. The hidden danger and risk analysis module is used for comprehensive analysis, query and display of hidden dangers and risks from multiple channels of data from the space and ground. The data query module is used to query and graphically display multi-channel data from the Starry Sky and Earth. The monitoring overview module is used to process multi-channel data from the sky and ground based on GIS positioning, and to display power grid lines and tower layers.

8. A monitoring and early warning device for landslide geological disasters along power transmission lines, characterized in that, include: The image acquisition module is used to acquire at least two types of radar remote sensing satellite images, and to extract the deformation area and deformation rate of the monitoring area from the radar remote sensing satellite images using SBAS-InSAR and D-InSAR technologies respectively. The deformation level determination module is used to determine the deformation risk level of the deformation area based on the deformation area, the deformation rate and the pre-acquired historical landslide points, and to select a target deformation area that meets the target deformation risk level based on the deformation risk level. The aerial monitoring module is used to acquire two sets of aircraft monitoring data of the target deformation area before and after the occurrence of critical weather using LiDAR and optical cameras. Each set of aircraft monitoring data includes: ground digital elevation model (DEM) and visible light imagery. The landslide point determination module is used to determine potential landslide points along the power transmission line based on two sets of aircraft monitoring data before and after the occurrence of critical weather. The landslide level determination module is used to collect vibration signals from the landslide hazard points and the towers on the transmission line, and to determine the landslide risk level of the transmission line within the target deformation area based on the vibration signals. The early warning module is used to issue early warning information through a preset monitoring and early warning platform based on the landslide risk level of the transmission line.

9. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the method as described in any one of claims 1-7.

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