A system and method for monitoring tower landslide disasters based on drone modeling simulation

Abstract

The present invention relates to the field of pole tower landslide disasters, and in particular to a system and method for monitoring pole tower landslide disasters based on drone modeling and simulation. The present invention monitors the complex terrain around pole towers through means such as drone operation modeling, geological disaster hazard identification, three-dimensional monitoring and early warning, and dynamic hazard prevention and control. Extensive testing of pole towers under different terrain conditions verified the reliability and effectiveness of this method, reducing the reliance on hardware during embedded software testing, enabling comprehensive real-time monitoring of terrain changes, and accurately identifying signs of landslides. The present invention significantly improves the monitoring and early warning capabilities of pole tower landslide disasters, providing a strong guarantee for the safe and stable operation of power systems.

Description

Technical Field

[0001] The present invention relates to the field of geological disaster background and disaster prevention around power system towers, and in particular to a system and method for monitoring tower landslide disasters based on unmanned aerial vehicle modeling simulation. Background Art

[0002] With the rapid development of society and the economy, the stable operation of power systems is crucial to maintaining the normal order of production and life. As a crucial support infrastructure for power transmission, the safety of power towers is directly related to the reliability of power supply. However, in areas with complex geological conditions and frequent natural disasters, power towers face the threat of geological hazards such as landslides. Landslides are a common geological hazard characterized by suddenness and destructiveness. Once a landslide occurs in the area where a power tower is located, it can cause the tower to tilt or collapse, leading to power outages and significant economic losses and adverse social impacts. Traditional methods for monitoring power tower landslides rely primarily on manual inspections and ground-based monitoring equipment. These methods suffer from limited monitoring coverage, low efficiency, and difficulty in obtaining accurate, real-time data. In recent years, the rapid development of drone technology has provided new ideas and methods for monitoring power tower landslides. Drones offer advantages such as high maneuverability, flexible operation, and the ability to quickly acquire high-precision data over large areas, effectively addressing the shortcomings of traditional monitoring methods. By utilizing drones equipped with high-precision sensors and cameras, coupled with automated analysis and recognition software, they rapidly scan and collect data from the area surrounding the towers. Advanced modeling and simulation techniques are then used to construct precise three-dimensional terrain models, analyzing and predicting potential landslide risks. This not only enables real-time, dynamic monitoring of tower landslide hazards, but also provides timely and accurate early warning information to power companies, enabling them to implement effective preventative measures and ensure the safe and stable operation of power facilities.

[0003] Because power lines cover a wide range and have long transmission distances, and pass through many areas with harsh environmental conditions, complex geological terrain, and changeable climates, the safe and stable operation of the power grid places higher demands on disaster prevention and mitigation work and prediction and early warning technologies for transmission channels, and the situation of geological disaster prevention and control is severe. Summary of the Invention

[0004] In order to realize the problem of monitoring tower landslide disasters and dynamically simulating landslide disasters, the present invention provides a system and method for monitoring tower landslide disasters based on drone modeling simulation. The system mainly includes: a drone operation modeling module, a geological disaster hazard identification module, a three-dimensional monitoring and early warning module, and a hazard dynamic prevention and control module connected in sequence;

[0005] The UAV operation modeling module is used to establish a three-dimensional field model through photography of UAV field operations based on UAV orthophotometry / oblique photogrammetry and UAV close-up photogrammetry data;

[0006] The geological disaster hazard identification module is used to collect geological environment information and remote sensing satellite image data along key transmission lines, study the main geological disaster categories and development conditions, and determine potential hazards and risk areas by analyzing and summarizing the development characteristics and temporal and spatial distribution patterns of geological disasters;

[0007] The three-dimensional monitoring and early warning module is used to three-dimensionally monitor high-risk geological disaster hazards in important power transmission channels, including remote sensing surface monitoring and ground point monitoring;

[0008] The dynamic prevention and control module for hidden dangers is used to simulate the movement process and predict the impact range, so as to achieve dynamic and coordinated prevention and control of geological disasters in important transmission channels.

[0009] A method for monitoring tower landslide disasters based on drone modeling simulation, the method comprising the following steps:

[0010] Step 1: Prepare relevant materials according to relevant requirements and perform relevant operations according to the test process; the UAV operation modeling module uses hardware and software methods to survey and identify the geological environment around the tower, identify geological disaster risks, perform three-dimensional monitoring and early warning, and dynamically prevent and control hidden dangers.

[0011] Step 2: Collect information on the background and current status of geological hazards in the study area, and use integrated remote sensing technology of "sky-air-ground" to identify potential geological hazards and conduct monitoring and early warning.

[0012] Step 3: Use drones for field flight sampling. Through drone multi-mode photogrammetry intelligent planning and autonomous operation technology, select the drone flight mode for shooting and sampling operations according to the different geological conditions around the tower. UAV photogrammetry technology includes vertical photogrammetry, oblique photogrammetry, intelligent posing technology and close-up photogrammetry. Vertical photogrammetry, oblique photogrammetry and intelligent posing technology are used to obtain the target's fine texture. Close-up photogrammetry can highly restore the structure of the surface and objects, and is used to compensate for the distortion of data near the ground.

[0013] Step 4: Data collected by drones and the "sky-air-ground" system is collected and processed using computer multi-scale fusion modeling technology through Pix4D or ContextCapture software to obtain a variety of model results, including real-world 3D models, 3D point clouds, digital surface models, digital elevation models, and digital orthophotos, thereby completing the construction of a 3D field model.

[0014] Stet5: Identifies geological hazards based on geological environmental information and remote sensing satellite imagery collected along key transmission lines. Hazard points and risk sections are determined by analyzing and summarizing the development characteristics and temporal and spatial distribution patterns of geological hazards. The activity of hazard points is analyzed based on detailed simulation results of their movement, and their hazard is considered based on the area and objects affected. The hazard surface is simulated through detailed dynamic simulation and then the corresponding hazard points are found by referring to the actual geological environment.

[0015] Stet6: After the drone operation modeling, the data and photos collected by the drone are used, and then based on computer multi-scale fusion modeling technology, a series of numerical simulation methods are adopted to conduct a detailed simulation of the development and movement process of landslide and collapse hazards, realizing the deduction of pre-disaster disaster scenarios and the review of post-disaster disaster processes. Then, based on the detailed simulation results of the movement process of risk geological hazards above the first risk threshold, risk assessment and classification are carried out from the two dimensions of activity and hazard. For important transmission channels with high incidence of geological hazards above the second risk threshold, risk assessment and classification are carried out from the two dimensions of danger and vulnerability. Then, three-dimensional monitoring and early warning are carried out.

[0016] Stet7: After the drone operation model is established, numerical simulation methods such as finite element, discrete element, and finite difference are used to conduct detailed simulation of the development and movement of landslide and collapse hazards based on natural working conditions or rainfall conditions. This allows for dynamic and coordinated prevention and control of geological hazards in important transmission channels from both the hazard point and risk section levels, providing strong guarantees for the safe and stable operation of the power system.

[0017] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above method steps.

[0018] A computer program product includes a computer program or instructions, which implement the above method steps when the program or instructions are executed by a processor.

[0019] The technical solution provided by the present invention has the following beneficial effects: the present invention monitors the complex terrain around power towers through methods such as drone operation modeling, geological disaster hazard identification, three-dimensional monitoring and early warning, and dynamic hazard prevention and control. The drone operation modeling module is used to establish a three-dimensional field model through drone field operations based on UAV orthophotometry / oblique photogrammetry and UAV close-up photogrammetry data; the geological disaster hazard identification module is used to collect geological environmental information and remote sensing satellite image data along key transmission lines, study the main geological disaster categories and development conditions, and determine hazard points and risk sections by analyzing and summarizing the geological disaster development characteristics and temporal and spatial distribution patterns; the three-dimensional monitoring and early warning module is used to three-dimensionally monitor high-risk geological disaster hazards in important transmission channels, including remote sensing surface monitoring and ground point monitoring; the dynamic hazard prevention and control module is used to simulate the movement process and simulate and predict the impact range, thereby realizing dynamic and coordinated prevention and control of geological hazards in important transmission channels. Through extensive testing of power towers under different terrain conditions, the reliability and effectiveness of this method have been verified, reducing the dependence on hardware during embedded software testing, achieving comprehensive real-time monitoring of terrain changes, and accurately identifying signs of landslides. The present invention significantly improves the monitoring and early warning capabilities of tower landslide disasters, providing a strong guarantee for the safe and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0021] Figure 1 This is a flow chart of a method for monitoring tower landslide disasters based on drone modeling simulation in an embodiment of the present invention;

[0022] Figure 2 This is a flowchart of the UAV operation modeling in an embodiment of the present invention;

[0023] Figure 3 This is a flow chart of geological disaster hazard identification in an embodiment of the present invention;

[0024] Figure 4 It is an automatic analysis software method for analyzing a program control diagram in an embodiment of the present invention;

[0025] Figure 5 This is a software digital architecture diagram in an embodiment of the present invention;

[0026] In the picture:

[0027] UAV operation modeling module (1), geological disaster hazard identification module (2), three-dimensional monitoring and early warning module (3), dynamic hazard prevention and control module (4), UAV multi-mode photogrammetry intelligent planning and autonomous operation technology (5), UAV multi-scale fusion quantitative and precise three-dimensional modeling method for geological hazards on transmission lines (6), hazard points (7) and risk sections (8). DETAILED DESCRIPTION

[0028] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described in detail with reference to the accompanying drawings.

[0029] Example 1

[0030] Please refer to Figure 1 , Figure 1 This is a flow chart of a method for monitoring tower landslide disasters based on drone modeling simulation in an embodiment of the present invention, which specifically includes:

[0031] A system for monitoring tower landslide hazards based on drone modeling simulation includes: a drone operation modeling module 1, a geological hazard hazard identification module 2, a three-dimensional monitoring and early warning module 3, and a dynamic hazard prevention and control module 4. First, a drone equipped with a data transmission camera is used to conduct field flights. Simultaneously, integrated "sky-air-ground" remote sensing technology is used to collect information on the background and current status of geological hazards. This data is then refined and modeled using a computer. Geological environmental information collected along key transmission lines is combined with remote sensing satellite imagery data to study the main geological hazard types and development conditions. The development characteristics and temporal and spatial distribution patterns of geological hazards are analyzed and summarized. Based on the development characteristics of typical geological hazards threatening towers and lines, a comprehensive approach to drone field operations is established, integrating intelligent route planning and autonomous operations, using a combination of oblique photogrammetry, terrain simulation flight, and intelligent posing.

[0032] Airborne remote sensing refers to aerial surveying techniques primarily based on drone technology. Represented by low-altitude drone photogrammetry, these technologies offer advantages such as simple structure, low cost, safety, reliability, flexibility, real-time performance, rich results, and high resolution, making them ideal for application in transmission line scenarios. Using drone remote sensing technology as its core, this approach reveals typical hazard-prone environments and patterns for major geological hazards along transmission lines. This approach establishes a comprehensive technical framework encompassing the identification, monitoring, and early warning of geological hazards, simulation, and dynamic prevention and control of geological hazards along transmission lines, encompassing drone field operations and detailed results production, refined identification of geological hazard hazards, integrated air-ground three-dimensional monitoring and early warning, and simulation and dynamic prevention and control. Pilot applications and device development are underway. Ground-based remote sensing applications, represented by 3D laser scanning and GNSS, offer limited coverage and are suitable for detailed medium- and small-scale remote sensing surveys, supporting the collection of basic geographic data. These three methods each have their own advantages and disadvantages. Therefore, it is necessary to give full play to the strengths of various technologies, comprehensively apply different technical methods according to different geographical environment characteristics, and establish a sky-ground integrated remote sensing coordinated monitoring and patrol and information collection technical method system for ground-based refined verification.

[0033] like Figure 2 As shown, the UAV operation modeling module 1 establishes a field model from three dimensions: studying the typical geological environment of transmission lines and the development characteristics of major geological hazards, UAV multi-mode photogrammetry intelligent planning and autonomous operation technology 5, and UAV multi-scale fusion quantitative and fine three-dimensional modeling method of geological hazards along transmission lines 6. Among them, the typical geological environment of transmission lines and the development characteristics of major geological hazards are studied using the "sky-air-ground" integrated comprehensive remote sensing technology. UAV multi-modal photogrammetry intelligent planning and autonomous operation technology 5 includes oblique photogrammetry and close-up photogrammetry, terrain-simulating flight, and intelligent posing; oblique photogrammetry refers to carrying multiple sensors on the same flight platform to simultaneously collect images from five different angles: vertical, four oblique, and so on, to obtain rich textures of the building top surface and side view; close-up photogrammetry refers to target-oriented photogrammetry, which takes the surface of the object as the photography object and photographs the surface of any slope and slope direction in three-dimensional space. It is a method between two-dimensional and three-dimensional photography; terrain-simulating flight refers to the drone adjusting the flight altitude according to the acquired terrain data to maintain a constant height difference with the ground; intelligent posing means that the aircraft will fly along two mutually perpendicular bow-shaped routes, performing intelligent swinging photography of the survey area from different angles. The UAV-based multi-scale fusion quantitative and detailed 3D modeling method for geological hazards along power transmission lines[6] utilizes computer-aided multi-scale fusion modeling technology to process drone-collected data and photos using software such as Pix4D or ContextCapture. This method generates a variety of outputs, including realistic 3D models of potentially threatening towers and transmission lines, 3D point clouds, digital surface models (DSMs), digital elevation models (DEMs), digital orthophotos, and other high-precision data. These provide crucial basic information and data for quantitative monitoring and assessment, and serve as a foundation for subsequent work. The embedded software runs on a virtual target machine, implementing all software design functions. The fully digital simulation environment displays and modifies the status of all CPU registers, on-chip devices, and memory, supporting ARM, DSP, PowerPC, Loongson, and Phytium processors. It offers common debugging features such as single-stepping, breakpoints, and variable monitoring. System states can be saved and restored, and a peripheral device controller simulation library is provided. The system is extensible, supporting the development and integration of various simulation models and providing multiple APIs. This fully digital simulation environment enables rapid prototyping of embedded systems, system fault injection, unit-level testing of processor executed code, and other simulation, software verification, and testing capabilities. This allows for better integration of drones and software, enabling enhanced identification and judgment of tower geology. Space-based remote sensing technologies, including optical satellite remote sensing and InSAR, offer advantages such as all-weather, all-day coverage, wide coverage, high spatial resolution, non-contact operation, and low overall cost, making them suitable for large-scale geological hazard surveys and long-term continuous observation.

[0034] like Figure 3 As shown, the geological disaster hazard identification module 2 is used to collect geological environmental information and remote sensing satellite imagery along key transmission lines, study the main geological hazard types and development patterns, and analyze and summarize the geological hazard development characteristics and temporal and spatial distribution patterns to determine hazard points 7 and risk segments 8. The activity of hazard points 7 is analyzed based on the results of a detailed simulation of their movement, and their hazard is considered based on the area and targets at risk. The hazard surface created through detailed dynamic simulation is then referenced to the actual geological environment to identify the corresponding hazard points, simultaneously identifying geological disaster hazards. Risk segment 8 comprises: hazard and vulnerability. Hazard refers to the probability of a geological disaster of a certain scale and type occurring in a certain area within a certain period of time under the influence of certain triggering factors. Vulnerability refers to the probability of geological disaster damage to the hazard-bearing objects within the risk area and the ease with which damage will occur, taking into account the vulnerability of population, buildings, and roads.

[0035] After the drone operation modeling is completed, the three-dimensional monitoring and early warning module 3 uses the data and photos collected by the drone, and then based on the computer multi-scale fusion modeling technology, finally adopts a series of numerical simulations to conduct a detailed simulation of the development and movement process of landslide and collapse hazards, so as to realize the deduction of disaster scenes before the disaster and the review of the disaster process after the disaster; based on the detailed simulation results of the movement process of risk geological disaster hazards above the first risk threshold, risk assessment and level division are carried out from the two dimensions of their activity and harmfulness; for the important transmission channel sections prone to geological disasters above the second risk threshold, risk assessment and level division are carried out from the two dimensions of dangerousness and vulnerability; then three-dimensional monitoring and early warning are carried out to provide dynamic prevention and control for hidden dangers.

[0036] After the UAV operation model is established, the dynamic hidden danger prevention and control module 4 uses numerical simulation methods, including finite element, discrete element, and finite difference, based on the real-life three-dimensional model to study the fine simulation of the development and movement process of landslide and collapse hidden dangers based on natural working conditions or rainfall conditions. It realizes the dynamic coordinated prevention and control of geological disasters in important transmission channels from the two levels of hidden danger points and risk sections, and improves the stable operation capacity and level of the power grid.

[0037] Based on the above research results, for important power transmission channels that are susceptible to typical geological disasters such as collapse and landslides, a standard process of drone-based detailed modeling, monitoring and early warning, simulation and risk prevention and control for geological disaster hazards such as landslides and collapses has been established, and on-site pilot applications have been completed.

[0038] Figure 4To automatically analyze program control diagrams using software, the present invention uses the AETG-SA algorithm in conjunction with software to generate test data during the drone identification process. This algorithm incorporates feedback from test results, dynamically adjusts algorithm parameters, and obtains the optimal test set, thereby improving test coverage. When testing the system, it is necessary to determine whether requirements have changed. If so, the test data is introduced, automatic test cases are executed, and the test results are analyzed and stored. A use case generation algorithm is used to automatically generate test data, and it is determined whether the first round of testing is to be performed. If so, a fully digital simulation test environment is constructed. If not, the test data is introduced, the automatic test cases are executed, and the test results are analyzed and stored.

[0039] If the requirements have not changed, the functional requirements and software inputs are sorted out, test data is automatically generated, and it is determined whether the first round of testing is to be conducted. If it is the first round of testing, a fully digital simulation test environment is built. If it is not the first round of testing, the test data is introduced, automatic test cases are executed, and the test results are analyzed and stored.

[0040] Figure 5 This is a software digital architecture diagram. The system features an integrated console, a fault simulation module, and an automatic testing module using test code. These modules connect to the first virtual simulation node, the second virtual simulation node, the third virtual simulation node, and so on through a distributed data soft bus. Each virtual simulation node includes a controller, a virtual target machine, and virtual peripherals. Binary target code is input into the virtual target machine, which includes a virtual CPU and memory. Virtual peripherals include serial ports, CAN, 1553B chips, and other peripherals. The system also has a component management platform and a host machine.

[0041] Example 2

[0042] A method for monitoring tower landslide disasters based on drone modeling simulation, specifically including:

[0043] Step 1: Prepare relevant materials according to relevant requirements and perform relevant operations according to the test process; the UAV operation modeling module uses hardware and software methods to survey and identify the geological environment around the tower, identify geological disaster risks, perform three-dimensional monitoring and early warning, and dynamically prevent and control hidden dangers.

[0044] Step 2: Based on the collection of information on the background and current status of geological hazards in the study area, we will use integrated "sky-air-ground" remote sensing technology to identify geological hazard risks and conduct monitoring and early warning. By leveraging the strengths of various technologies, we will develop a system of sky-ground integrated remote sensing coordinated monitoring and patrol, and information collection techniques for ground-based detailed verification, by leveraging the combined strengths of these technologies and applying different methods to address different geographical environments. This will allow us to conduct on-site geological sampling, record data, and transmit it to a computer.

[0045] Step 3: Conduct drone field sampling flights. By studying intelligent planning and autonomous operation technologies for multi-modal drone photogrammetry, we can select appropriate drone flight methods based on the different geological conditions surrounding the towers for more effective sampling and filming. Drone photogrammetry techniques include vertical photogrammetry, oblique photogrammetry, intelligent posing techniques, and close-up photogrammetry. The first three can be used to obtain detailed textures of targets and are suitable for terrain with large drop heights, but they lack detailed near-surface information. Close-up photogrammetry addresses the shortcomings of the first three, providing a high degree of restoration of the surface and object structure, compensating for near-surface data distortion.

[0046] Step 4: Data collected by drones and the "sky-air-ground" system is collected and processed using computer-based multi-scale fusion modeling technology, using software such as Pix4D or ContextCapture. This yields a variety of models, providing a data foundation for subsequent work. These include real-world 3D models, 3D point clouds, digital surface models (DSMs), digital elevation models (DEMs), digital orthophotos, and other related models. This completes the creation of a 3D model.

[0047] Stet5: Identify geological disaster risks. Analyze the activity of potential hazards based on detailed simulation results of their movement, and assess their severity based on the affected area and targets. By fine-tuning the hazard surface through dynamic simulation and then referencing the actual geological environment to identify corresponding potential hazards, geological disaster risks can be identified.

[0048] Stet6: Conducts three-dimensional monitoring and early warning. Using drone-based modeling, data and photos collected by drones are then used. Computer-based multi-scale fusion modeling techniques are then employed, along with a series of numerical simulations and other methods. This allows for detailed simulation of the movement of hazards such as landslides and collapses, enabling both pre-disaster scenarios and post-disaster reconstructive analysis. Based on these detailed simulations of the movement of high-risk geological hazards, risk assessments and classifications are conducted based on their activity and hazardness, enabling three-dimensional monitoring and early warning.

[0049] Stet7: Dynamic prevention and control of hidden dangers. After the model is established through drone operations and satellite photography, numerical simulation methods such as finite element, discrete element, and finite difference are used to conduct detailed simulation of the development and movement of hidden dangers such as landslides and collapses based on natural working conditions or rainfall conditions. Dynamic and coordinated prevention and control of geological disasters in important transmission channels are achieved from the two levels of hidden danger points and risk sections, providing strong guarantees for the safe and stable operation of the power system.

[0050] Example 3

[0051] A computer-readable storage medium is characterized in that it stores a computer program, and when the program is executed by a processor, the above method steps are implemented.

[0052] Example 4

[0053] A computer program product, characterized in that it includes a computer program or instructions, and when the program or instructions are executed by a processor, the above method steps are implemented.

[0054] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for monitoring tower landslide disasters based on drone modeling simulation, characterized by: The method comprises the following steps: Step 1: Prepare relevant materials according to relevant requirements and perform relevant operations according to the test process; the UAV operation modeling module uses hardware and software methods to survey and identify the geological environment around the tower, identify geological disaster risks, perform three-dimensional monitoring and early warning, and dynamically prevent and control hidden dangers. Step 2: Collect information on the background and current status of geological hazards in the study area, and use integrated remote sensing technology from "sky, air, and ground" to identify potential geological hazards and conduct monitoring and early warning. Step 3: Use drones for field flight sampling. Through drone multi-mode photogrammetry intelligent planning and autonomous operation technology, select the drone flight mode for shooting and sampling operations according to the different geological conditions around the tower. UAV photogrammetry technology includes vertical photogrammetry, oblique photogrammetry, intelligent posing technology and close-up photogrammetry. Vertical photogrammetry, oblique photogrammetry and intelligent posing technology are used to obtain the target's fine texture. Close-up photogrammetry can highly restore the structure of the surface and objects, and is used to compensate for the distortion of data near the ground. Step 4: Data collected by drones and the "sky-air-ground" system is collected and processed using computer multi-scale fusion modeling technology through Pix4D or ContextCapture software to obtain a variety of model results, including real-world 3D models, 3D point clouds, digital surface models, digital elevation models, and digital orthophotos, thereby completing the construction of a 3D field model. Stet5: Identifies geological hazards based on geological environmental information and remote sensing satellite imagery collected along key transmission lines. Hazard points and risk sections are determined by analyzing and summarizing the development characteristics and temporal and spatial distribution patterns of geological hazards. The activity of hazard points is analyzed based on detailed simulation results of their movement, and their hazard is considered based on the area and objects affected. The hazard surface is simulated through detailed dynamic simulation and then the corresponding hazard points are found by referring to the actual geological environment. Stet6: After the drone operation modeling, the data and photos collected by the drone are used, and then based on computer multi-scale fusion modeling technology, a series of numerical simulation methods are adopted to conduct a detailed simulation of the development and movement process of landslide and collapse hazards, realizing the deduction of pre-disaster disaster scenarios and the review of post-disaster disaster processes. Then, based on the detailed simulation results of the movement process of risk geological hazards above the first risk threshold, risk assessment and classification are carried out from the two dimensions of activity and hazard. For important transmission channels with high incidence of geological hazards above the second risk threshold, risk assessment and classification are carried out from the two dimensions of danger and vulnerability. Then, three-dimensional monitoring and early warning are carried out. Stet7: After the drone operation model is established, numerical simulation methods such as finite element, discrete element, and finite difference are used to conduct detailed simulation of the development and movement of landslide and collapse hazards based on natural working conditions or rainfall conditions. This allows for dynamic and coordinated prevention and control of geological hazards in important transmission channels from both the hazard point and risk section levels, providing strong guarantees for the safe and stable operation of the power system.

2. A system for monitoring tower landslide disasters based on drone modeling simulation, implemented based on the method of claim 1, characterized in that: The system comprises a UAV operation modeling module (1), a geological disaster hazard identification module (2), a three-dimensional monitoring and early warning module (3), and a hazard dynamic prevention and control module (4) connected in sequence; The UAV operation modeling module (1) is used to establish a three-dimensional field model by photographing the UAV field operation based on the UAV orthophotometry / oblique photogrammetry and UAV close-up photogrammetry data; The geological disaster hazard identification module (2) is used to collect geological environment information and remote sensing satellite image data along key transmission lines, study the main geological disaster categories and development conditions, and determine the hazard points and risk sections by analyzing and summarizing the geological disaster development characteristics and temporal and spatial distribution patterns; The three-dimensional monitoring and early warning module (3) is used for three-dimensional monitoring of high-risk geological disaster hazards in important power transmission channels, including remote sensing surface monitoring and ground point monitoring; The dynamic prevention and control module for hidden dangers (4) is used to simulate the movement process and predict the impact range, so as to achieve dynamic and coordinated prevention and control of geological hazards in important power transmission channels.

3. The system for monitoring tower landslide disasters based on drone modeling simulation according to claim 2, characterized in that: The UAV operation modeling module (1) establishes a field model from three dimensions: studying the typical geological environment of transmission lines and the development characteristics of major geological hazards, UAV multi-mode photogrammetry intelligent planning and autonomous operation technology, and UAV multi-scale fusion quantitative fine three-dimensional modeling method of geological hazards along transmission lines. The typical geological environment of transmission lines and the development characteristics of major geological hazards are studied using the "sky-air-ground" integrated comprehensive remote sensing technology.

4. The system for monitoring tower landslide disasters based on drone modeling simulation according to claim 3, characterized in that: The intelligent planning and autonomous operation technology of multi-modal photogrammetry of drones includes oblique photogrammetry, close-up photogrammetry, terrain-simulating flight, and intelligent posing. Oblique photogrammetry refers to carrying multiple sensors on the same flight platform to simultaneously collect images from five different angles, including vertical, four oblique, and side views, to obtain rich textures of the building's top surface and side view. Close-up photogrammetry refers to target-oriented photogrammetry, which takes the surface of an object as the photographic object and photographs surfaces of arbitrary slopes and directions in three-dimensional space. It is a method between two-dimensional and three-dimensional photography. Terrain-simulating flight refers to the drone adjusting its flight altitude based on the acquired terrain data to maintain a constant height difference with the ground. Intelligent posing means that the aircraft will fly along two mutually perpendicular bow-shaped routes, performing intelligent swinging photography of the survey area from different angles.

5. The system for monitoring tower landslide disasters based on drone modeling simulation according to claim 3, characterized in that: The UAV multi-scale fusion quantitative fine 3D modeling method for geological hazards along transmission lines (6) includes processing the data and photos collected by the UAV with computer multi-scale fusion modeling technology through Pix4D or ContextCapture processing software to obtain a variety of model results, including: real-life 3D model, 3D point cloud, digital surface model, digital elevation model, and digital orthophoto.

6. The system for monitoring tower landslide disasters based on drone modeling simulation according to claim 2, characterized in that: Hidden danger points refer to the analysis of their activity based on the results of detailed simulation of the movement process of the hidden danger points, and their hazards are considered according to the hazard area and the hazard object. The hazard surface that appears through detailed dynamic simulation is then found with reference to the actual geological environment to identify the corresponding hidden danger points for geological disaster hazards. The risk segment includes hazard and vulnerability, among which hazard is the probability of a certain scale and type of geological disaster occurring in a certain area within a certain period of time under the influence of certain inducing factors. Vulnerability refers to the chance of the disaster-bearing body in the risk area being damaged by geological disasters and the difficulty of damage, taking into account the vulnerability of population, buildings and roads.

7. The system for monitoring tower landslide disasters based on drone modeling simulation according to claim 2, characterized in that: After the UAV operation modeling, the three-dimensional monitoring and early warning module (3) uses the data and photos collected by the UAV, and then based on the computer multi-scale fusion modeling technology, finally adopts a series of numerical simulations to simulate the development and movement process of landslide and collapse hazards in detail, so as to achieve the deduction of disaster scenes before the disaster and the review of the disaster process after the disaster; based on the detailed simulation results of the movement process of risk geological disaster hazards above the first risk threshold, risk assessment and level classification are carried out from the two dimensions of activity and hazard; for the high-incidence sections of important transmission channels with geological disasters above the second risk threshold, risk assessment and level classification are carried out from the two dimensions of danger and vulnerability; then three-dimensional monitoring and early warning are carried out to make dynamic prevention and control preparations for hidden dangers.

8. The system for monitoring tower landslide disasters based on drone modeling simulation according to claim 2, characterized in that: After the UAV operation model is established, the dynamic prevention and control module (4) uses numerical simulation methods, including finite element, discrete element, and finite difference, to study the fine simulation of the development and movement process of landslide and collapse hazards based on natural working conditions or rainfall conditions, and realizes the dynamic coordinated prevention and control of geological disasters in important transmission channels from the two levels of hidden danger points and risk sections, thereby improving the stable operation capacity and level of the power grid.

9. A computer-readable storage medium, characterized in that A computer program is stored, and when the program is executed by a processor, the method steps of monitoring tower landslide disasters based on drone modeling simulation described in claim 1 are implemented.

10. A computer program product, characterized in that The method comprises a computer program or an instruction, which, when executed by a processor, implements the method steps of monitoring tower landslide disasters based on drone modeling simulation as described in claim 1.

Images