Slope deformation monitoring system and method for geological engineering

Abstract

The invention discloses a slope deformation monitoring system and method for geological engineering. The system comprises an unmanned aerial vehicle base station module, a base, a hinge seat, a handle, a protective sleeve, a battery bin, a guide rail, a lifting plate, a data processing and storage module, a point cloud and image fusion module, a deformation monitoring and analysis module and an early warning and decision module. The method comprises the steps of 1, unmanned aerial vehicle data acquisition; 2, receiving and preprocessing data; 3, carrying out coordinate registration and data storage; 4, fusing the point cloud and the image; step 5, deformation monitoring and analysis; step 6, constructing and optimizing a digital elevation model; step 7, early warning and decision making; the portable unmanned aerial vehicle base station is designed, take-off and landing of the unmanned aerial vehicle can be automatically achieved, the requirement for human resources is reduced, a battery is arranged in the unmanned aerial vehicle base station, the unmanned aerial vehicle parked in the battery can be charged, the continuous operation capacity of the unmanned aerial vehicle is improved, and the continuity and efficiency of monitoring work are guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geological engineering, in particular to a slope deformation monitoring system and method for geological engineering. BACKGROUND

[0002] Slope deformation monitoring is crucial for geological engineering, as the stability of the slope is directly related to the safety of the project. By monitoring the deformation of the slope, potential safety hazards can be detected in a timely manner, and necessary engineering measures can be taken to reinforce or repair, thereby avoiding or reducing disasters caused by slope instability.

[0003] The existing slope deformation monitoring has the following defects: first, when using unmanned aerial vehicle technology to perform slope deformation prediction and monitoring tasks for geological engineering projects, although the high-altitude perspective provides a unique observation advantage, the frequent take-off and landing requirements of the unmanned aerial vehicle not only increase the operation complexity, but also put high demands on human resources. In addition, during the execution of the task, there is a lack of efficient and convenient mobile charging and maintenance sites, which limits the continuous operation capability of the unmanned aerial vehicle and affects the continuity and efficiency of the monitoring work; secondly, traditional slope deformation information extraction methods mainly rely on point cloud data or image analysis. These methods are often limited to a single data source, so there is a problem of insufficient information dimension, making it difficult to provide accurate three-dimensional spatial positioning information and intuitive detailed image feature information simultaneously, reducing the comprehensiveness and accuracy of deformation monitoring, and making the monitoring results may not fully reflect the true deformation state of the slope; thirdly, in the face of complex and variable terrain, especially in high and steep slope areas, the ranging accuracy of the laser radar carried by the unmanned aerial vehicle is limited by environmental conditions and scanning angles, resulting in incomplete point cloud data collection in some severely occluded areas, and even data missing phenomenon, which directly affects the construction quality of the subsequent digital elevation model, making the generated digital elevation model may appear distorted, unable to truly reflect the topographic features of the slope, greatly hindering the ability to accurately assess the slope deformation. SUMMARY

[0004] The purpose of the present application is to provide a slope deformation monitoring system and method for geological engineering to solve the problems raised in the background.

[0005] To achieve the above purpose, the present application provides the following technical solution: a slope deformation monitoring system for geological engineering, comprising an unmanned aerial vehicle base station module, the unmanned aerial vehicle base station module is data connected with a data processing and storage module, the data processing and storage module is data connected with a point cloud and image fusion module, the point cloud and image fusion module is data connected with a deformation monitoring and analysis module, and the deformation monitoring and analysis module is data connected with a warning and decision-making module.

[0006] As a further technical scheme of the present application, the unmanned aerial vehicle base station module comprises a base, a gear is rotatably connected to the base, a motor is fixedly connected to the outer wall of one side of the base, the output end of the motor is fixedly connected to the gear, a first connecting rod and a third connecting rod are fixedly connected to the gear, a second connecting rod is hingedly connected to the other end of the first connecting rod, a lifting plate is hingedly connected to the other end of the second connecting rod, sliding grooves are formed in the outer walls of the lifting plate, guide rails are arranged on the inner wall of the base at positions corresponding to the sliding grooves, the guide rails are slidingly connected in the sliding grooves, a movable cover plate is hingedly connected to the other end of the third connecting rod, an unmanned aerial vehicle module is arranged on the lifting plate, and a laser radar module and an optical camera module are arranged on the unmanned aerial vehicle module.

[0007] As a further technical scheme of the present application, the base is provided with a hinged seat, a handle is hingedly connected to the hinged seat, a protective sleeve is sleeved on the handle, a battery compartment is formed in the base, a battery module is arranged in the battery compartment, the battery module is electrically connected to the unmanned aerial vehicle module, and an automatic take-off and landing module and a base communication module are arranged on the unmanned aerial vehicle base station module.

[0008] As a further technical scheme of the present application, the data processing and storage module comprises a data receiving module, a data preprocessing module, a coordinate registration module and a data storage module, and the data receiving module is in data connection with the unmanned aerial vehicle module.

[0009] As a further technical scheme of the present application, the point cloud and image fusion module comprises a point cloud processing module, an orthophoto processing module, a point cloud registration module, an image dense point cloud generation module and a point cloud fusion module, the deformation monitoring and analysis module comprises a deformation information extraction module, a three-dimensional space positioning module, an image feature analysis module, a deformation trend prediction module and a digital elevation model module, and the early warning and decision-making module comprises a deformation threshold setting module, an early warning signal issuing module, a decision-making suggestion generation module and a report generation module.

[0010] As a further technical scheme of the present application, the digital elevation model module comprises a DEM construction module, a model optimization module and a model verification module.

[0011] A slope deformation monitoring method for geological engineering, comprising the following steps: step one, unmanned aerial vehicle data acquisition; step two, data receiving and preprocessing; step three, coordinate registration and data storage; step four, point cloud and image fusion; step five, deformation monitoring and analysis; step six, digital elevation model construction and optimization; and step seven, early warning and decision-making. In the above step one, the unmanned aerial vehicle module is automatically taken off by the unmanned aerial vehicle base station module, and relevant data of the slope area is collected. In the above step two, the point cloud and image data collected by the unmanned aerial vehicle are received by the data processing and storage module, and the original data are preprocessed to improve the data quality. In the above step three, the point cloud data and the image data are converted to a unified coordinate system by using a coordinate registration module, and the accurate alignment of the point cloud and the image is ensured through feature point matching and spatial transformation; In the above step four, the laser point cloud and the image dense point cloud are fused by using a point cloud fusion module to complete the missing point cloud data and generate a more complete and higher precision point cloud data set. In the above step five, a deformation monitoring and analysis module extracts the slope deformation information from the fused point cloud data and analyzes the ground feature texture in the orthographic image to confirm the deformation condition. In the above step six, a digital elevation model module constructs a digital elevation model by using the fused point cloud data. In the above step seven, an early warning and decision module generates a warning signal according to the deformation condition and generates corresponding engineering measure suggestions and reports.

[0012] As a further technical solution of the present application, in the step one, the unmanned aerial vehicle base station module is moved to the designated location by the handle, and then the monitoring flight route of the unmanned aerial vehicle module is set. The motor on the base drives the first connecting rod and the third connecting rod to rotate, the first connecting rod drives the second connecting rod on the lifting plate to rotate, the second connecting rod drives the lifting plate to rise, the lifting plate rises along the guide rail through the sliding groove and drives the unmanned aerial vehicle module on it to rise, and at the same time, the third connecting rod drives the movable cover plate to unfold to one side. The two side mechanisms realize synchronous movement through gears. After the movable cover plate is opened, the automatic take-off and landing module controls the unmanned aerial vehicle module to take off smoothly to perform the monitoring task. The laser radar module and the optical camera module are mounted on the unmanned aerial vehicle module. The laser radar module is used to collect three-dimensional point cloud data of the slope area, and the optical camera module is used to collect high-resolution orthographic image data of the slope area. When the unmanned aerial vehicle module completes the monitoring task, it lands on the lifting plate. The motor drives the lifting plate to descend in reverse, and at the same time, the movable cover plate is closed. Then, the battery module arranged in the battery compartment is used to charge the unmanned aerial vehicle module.

[0013] As a further technical solution of the present application, in the step four, the point cloud processing module in the point cloud and image fusion module further processes the point cloud data collected by the laser radar to generate reference LiDAR point cloud data, and then the orthographic image processing module processes the orthographic image data collected by the optical camera to generate clear and accurate orthographic images. The point cloud registration module uses the GPU parallel operation capability to speed up the point cloud registration process and improve the registration efficiency. The image dense point cloud generation module generates dense image point cloud through multi-view oblique image generation technology. The point cloud fusion module fuses the laser point cloud and the image dense point cloud to complete the missing point cloud data and generate a more complete and higher precision point cloud data set.

[0014] As a further technical solution of the present invention, in step five, the deformation information extraction module in the deformation monitoring and analysis module extracts the deformation information of the slope from the fused point cloud data, the three-dimensional spatial positioning module provides accurate three-dimensional spatial positioning information to assist in deformation judgment, the image feature analysis module analyzes the texture features of the ground objects in the orthophoto to further confirm the deformation situation, and the deformation trend prediction module predicts future deformation trends based on historical deformation data.

[0015] Compared with the prior art, the present invention has the following beneficial effects: the present invention is designed with a portable drone base station that can automatically realize the takeoff and landing of the drone, reducing the demand for human resources, and has a built-in battery that can charge the drone parked therein, thereby improving the drone's ability to operate continuously and ensuring the consistency and efficiency of the monitoring work. The drone is equipped with a laser radar and an optical camera to regularly collect three-dimensional point clouds and high-resolution orthophoto data of the slope area, and the collected point cloud and image data are coordinate-aligned to establish point cloud data and orthophotos in a unified coordinate system, which together constitute the basic elements of the point cloud sequence. By analyzing the characteristics of the laser point cloud and image, a point cloud sequence containing high-precision three-dimensional spatial position information and rich color and texture features is constructed. The parallel computing capability of the GPU is utilized to accelerate the point cloud alignment process and improve the alignment efficiency. By fusing the dense point cloud generated by multi-view oblique images with the laser point cloud, the missing point cloud data is completed, thereby generating a more complete and higher-precision digital elevation model, which can more realistically reflect the terrain characteristics of the slope and improve the ability to accurately assess slope deformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a system structure diagram of the present invention; Figure 2 This is a module architecture diagram of the drone module of the present invention; Figure 3 A module architecture diagram of the data processing and storage module of the present invention; Figure 4 This is a module architecture diagram of the deformation monitoring and analysis module of the present invention; Figure 5 This is a module architecture diagram of the digital elevation model module of the present invention; Figure 6 Schematic diagram of the three-dimensional structure of the drone module of the present invention; Figure 7 Schematic diagram of the top view of the UAV module of the present invention; Figure 8 This is an exploded view of the structure of the drone module of the present invention; Figure 9 for Figure 8 Schematic diagram of the enlarged structure of area A in the middle; Figure 10 System flowchart of the present application; Figure 11 Method flowchart of the present application.

[0017] Figure: 1, unmanned aerial base station module; 11, automatic take-off and landing module; 12, battery module; 13, base station communication module; 14, unmanned aerial vehicle module; 141, laser radar module; 142, optical camera module; 15, base; 16, hinged seat; 17, handle; 18, protective sleeve; 19, battery compartment; 110, guide rail; 111, lifting plate; 112, sliding groove; 113, motor; 114, gear; 115, first connecting rod; 116, second connecting rod; 117, third connecting rod; 118, movable cover plate; 2, data processing and storage module; 21, data receiving module; 22, data preprocessing module; 23, coordinate registration module; 24, data storage module; 3, point cloud and image fusion module; 31, point cloud processing module; 32, orthophoto processing module; 33, point cloud registration module; 34, image dense point cloud generation module; 35, point cloud fusion module; 4, deformation monitoring and analysis module; 41, deformation information extraction module; 42, three-dimensional space positioning module; 43, image feature analysis module; 44, deformation trend prediction module; 45, digital elevation model module; 451, DEM construction module; 452, model optimization module; 453, model verification module; 5, early warning and decision-making module; 51, deformation threshold setting module; 52, early warning signal issuing module; 53, decision-making suggestion generation module; 54, report generation module. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0019] Please refer to the drawings in the embodiments of the present application Figure 1 -Appendix Figure 10The application provides a kind of embodiment: a kind of slope deformation monitoring system for geological engineering, including unmanned aerial vehicle base station module 1, data connection has data processing and storage module 2 on unmanned aerial vehicle base station module 1, data connection has point cloud and image fusion module 3 on data processing and storage module 2, data connection has deformation monitoring and analysis module 4 on point cloud and image fusion module 3, data connection has early warning and decision module 5 on deformation monitoring and analysis module 4;Unmanned aerial vehicle base station module 1 includes base 15, gear 114 is rotatably connected on base 15, motor 113 is fixedly connected on the outer wall of one side of base 15, and the output end of motor 113 is fixedly connected on gear 114, gear 114 is fixedly connected with first connecting rod 115 and third connecting rod 117, the other end of first connecting rod 115 is hinged with second connecting rod 116, the other end of second connecting rod 116 is hinged with lifting plate 111, sliding groove 112 is formed on the outer wall of both sides of lifting plate 111, guide rail 110 is arranged on the inner wall of base 15 at the position corresponding to sliding groove 112, and guide rail 110 is slidingly connected in sliding groove 112, the other end of third connecting rod 117 is hinged with movable cover plate 118, unmanned aerial vehicle module 14 is arranged on lifting plate 111, laser radar module 141 and optical camera module 142 are arranged on unmanned aerial vehicle module 14, laser radar module 141 is used to collect three-dimensional point cloud data of slope area, and optical camera module 142 is used to collect high-resolution orthographic image data of slope area;Base 15 is provided with hinged seat 16, handle 17 is hinged on hinged seat 16, protective sleeve 18 is sleeved on handle 17, battery compartment 19 is formed in base 15, battery module 12 is arranged in battery compartment 19, and battery module 12 is electrically connected to unmanned aerial vehicle module 14, automatic take-off and landing module 11 and base station communication module 13 are arranged on unmanned aerial vehicle base station module 1, automatic take-off and landing module 11 is used to realize automatic take-off and landing of unmanned aerial vehicle, reduces the demand for human resources, and base station communication module 13 is responsible for data communication with unmanned aerial vehicle, monitoring center and the like;Data processing and storage module 2 includes data receiving module 21, data preprocessing module 22, coordinate registration module 23 and data storage module 24, and data receiving module 21 is connected with unmanned aerial vehicle module 14, data receiving module 21 is used to receive point cloud and image data collected by unmanned aerial vehicle, data preprocessing module 22 is used to clean, denoise and other preprocessing operations on original data, coordinate registration module 23 is used to coordinate registration for point cloud and image data, to establish unified coordinate system, data storage module 24 is used to store the point cloud and image data after processing, for subsequent analysis.The point cloud and image fusion module 3 includes a point cloud processing module 31, an orthographic image processing module 32, a point cloud registration module 33, an image dense point cloud generation module 34, and a point cloud fusion module 35. The deformation monitoring and analysis module 4 includes a deformation information extraction module 41, a three-dimensional spatial positioning module 42, an image feature analysis module 43, a deformation trend prediction module 44, and a digital elevation model module 45. The early warning and decision-making module 5 includes a deformation threshold setting module 51, a warning signal issuing module 52, a decision-making suggestion generation module 53, and a report generation module 54. The point cloud processing module 31 further processes the point cloud data collected by the laser radar to generate reference LiDAR point cloud data. Then the orthographic image processing module 32 processes the orthographic image data collected by the optical camera to generate clear and accurate orthographic images. The point cloud registration module 33 uses GPU parallel operation capability to speed up the point cloud registration process and improve registration efficiency. The image dense point cloud generation module 34 generates dense image point clouds through multi-view oblique image generation technology. The point cloud fusion module 35 fuses laser point clouds and image dense point clouds to complete missing point cloud data and generate more complete and high-precision point cloud data sets. The deformation information extraction module 41 in the deformation monitoring and analysis module 4 extracts deformation information of the slope from the fused point cloud data. The three-dimensional spatial positioning module 42 provides accurate three-dimensional spatial positioning information to assist deformation judgment. The image feature analysis module 43 analyzes the texture features of ground objects in the orthographic image to further confirm the deformation situation. The deformation trend prediction module 44 predicts future deformation trends based on historical deformation data. The digital elevation model module 45 constructs a digital elevation model using the fused point cloud data. The early warning and decision-making module 5 generates warning signals according to the deformation situation and generates corresponding engineering measure suggestions and reports. The deformation threshold setting module 51 is used to set the deformation threshold for judging whether the slope is stable. The warning signal issuing module 52 is used to issue a warning signal when the deformation exceeds the threshold. The decision-making suggestion generation module 53 is used to generate corresponding engineering measure suggestions according to the deformation situation and the warning signal. The report generation module 54 is used to generate a slope deformation report. The digital elevation model module 45 includes a DEM construction module 451, a model optimization module 452, and a model verification module 453. The DEM construction module 451 is used to construct a digital elevation model using the fused point cloud data. The model optimization module 452 is used to optimize the DEM to improve model precision and authenticity. The model verification module 453 is used to verify the accuracy of the DEM through actual measurement data.

[0020] Please refer to the attached Figure 11The application provides a slope deformation monitoring method for geological engineering, which comprises the following steps: step 1, unmanned aerial vehicle data acquisition; step 2, data receiving and preprocessing; step 3, coordinate registration and data storage; step 4, point cloud and image fusion; step 5, deformation monitoring and analysis; step 6, digital elevation model construction and optimization; and step 7, early warning and decision making. In the above step one, the unmanned aerial vehicle module 14 is automatically taken off by the unmanned aerial vehicle base station module 1, the unmanned aerial vehicle base station module 1 is moved to a designated position through the handle 17, then the monitoring flight route of the unmanned aerial vehicle module 14 is set, the motor 113 on the base 15 drives the first connecting rod 115 and the third connecting rod 117 to rotate, the first connecting rod 115 drives the second connecting rod 116 on the lifting plate 111 to rotate, the second connecting rod 116 drives the lifting plate 111 to ascend, the lifting plate 111 ascends along the guide rail 110 through the sliding groove 112 and drives the unmanned aerial vehicle module 14 on it to ascend, and meanwhile the third connecting rod 117 drives the movable cover plate 118 to unfold to one side, the two sides are synchronously moved through the gear 114, after the movable cover plate 118 is unfolded, the automatic taking-off and landing module 11 controls the unmanned aerial vehicle module 14 to smoothly take off to perform a monitoring task, the unmanned aerial vehicle module 14 is provided with a laser radar module 141 and an optical camera module 142, the laser radar module 141 is used for collecting three-dimensional point cloud data of a slope region, and the optical camera module 142 is used for collecting high-resolution orthographic image data of the slope region, when the unmanned aerial vehicle module 14 completes the monitoring task, lands on the lifting plate 111, the motor 113 drives the lifting plate 111 to descend in the reverse direction, and meanwhile the movable cover plate 118 is closed, then the unmanned aerial vehicle module 14 is charged through the battery module 12 arranged in the battery compartment 19; In the above step two, the data processing and storage module 2 receives the point cloud and image data collected by the unmanned aerial vehicle and pre-processes the original data to improve the data quality. In the above step three, the coordinate registration module 23 is used for converting the point cloud data and the image data to a unified coordinate system, and the accurate alignment of the point cloud and the image is ensured through feature point matching and space transformation. In the above step four, the point cloud processing module 31 in the point cloud and image fusion module 3 further processes the point cloud data collected by the laser radar to generate reference LiDAR point cloud data, then the orthographic image processing module 32 processes the orthographic image data collected by the optical camera to generate clear and accurate orthographic images, the point cloud registration module 33 uses the GPU parallel operation capability to speed up the point cloud registration process and improve the registration efficiency, the image dense point cloud generation module 34 generates dense image point clouds through multi-view oblique image generation technology, and the point cloud fusion module 35 fuses the laser point cloud and the image dense point cloud to complete the missing point cloud data and generate a more complete and higher-precision point cloud data set. In the above step five, the deformation information extraction module 41 in the deformation monitoring and analysis module 4 extracts the deformation information of the slope from the fused point cloud data, the three-dimensional space positioning module 42 provides accurate three-dimensional space positioning information to assist deformation judgment, the image feature analysis module 43 analyzes the texture features of the ground objects in the orthographic image to further confirm the deformation condition, and the deformation trend prediction module 44 predicts the future deformation trend according to the historical deformation data; In the above step six, the digital elevation model module 45 constructs a digital elevation model by using the fused point cloud data. In the above step seven, the early warning and decision module 5 generates a warning signal according to the deformation condition, and generates corresponding engineering measure suggestions and reports.

[0021] Based on the above, the advantages of the present application are that when the slope deformation monitoring is carried out by using the present application, firstly, the unmanned aerial vehicle module 14 is automatically taken off by the unmanned aerial vehicle base station module 1, the unmanned aerial vehicle base station module 1 is moved to the designated place through the handle 17 and the protective sleeve 18 on the hinged seat 16, then the monitoring flight route of the unmanned aerial vehicle module 14 is set, the motor 113 on the base 15 drives the first connecting rod 115 and the third connecting rod 117 to rotate, the first connecting rod 115 drives the second connecting rod 116 on the lifting plate 111 to rotate, the second connecting rod 116 drives the lifting plate 111 to rise, the lifting plate 111 rises along the guide rail 110 through the sliding groove 112, and the unmanned aerial vehicle module 14 on the lifting plate 111 rises, at the same time, the third connecting rod 117 drives the movable cover plate 118 to unfold to one side, the two sides are synchronously moved through the gear 114, after the movable cover plate 118 is opened, the automatic take-off and landing module 11 controls the unmanned aerial vehicle module 14 to take off smoothly to perform the monitoring task, the unmanned aerial vehicle module 14 is provided with a laser radar module 141 and an optical camera module 142, the laser radar module 141 is used for collecting three-dimensional point cloud data of the slope area, and the optical camera module 142 is used for collecting high-resolution orthographic image data of the slope area, when the unmanned aerial vehicle module 14 completes the monitoring task, lands on the lifting plate 111, the motor 113 drives the lifting plate 111 to descend in reverse, and then the movable cover plate 118 is closed, then the unmanned aerial vehicle module 14 is charged through the battery module 12 arranged in the battery compartment 19, the base station communication module 13 is responsible for data communication with the unmanned aerial vehicle, the monitoring center and the like, then the data processing and storage module 2 receives the point cloud and image data collected by the unmanned aerial vehicle, and the original data is preprocessed to improve the data quality, specifically, the data receiving module 21 is used for receiving the point cloud and image data collected by the unmanned aerial vehicle, the data preprocessing module 22 is used for performing preprocessing operations such as cleaning and denoising on the original data, the coordinate registration module 23 is used for coordinate registration of the point cloud and image data, and a unified coordinate system is established, the data storage module 24 is used for storing the processed point cloud and image data, which is convenient for subsequent analysis, then the point cloud processing module 31 in the point cloud and image fusion module 3 further processes the point cloud data collected by the laser radar, generates reference LiDAR point cloud data, then the orthographic image processing module 32 processes the orthographic image data collected by the optical camera, generates clear and accurate orthographic images, the point cloud registration module 33 utilizes the GPU parallel operation capability to speed up the point cloud registration process and improve the registration efficiency, the image dense point cloud generation module 34 generates dense image point cloud through multi-view oblique image generation technology, the point cloud fusion module 35 fuses the laser point cloud and the image dense point cloud to complete the missing point cloud data, and generates a more complete and higher-precision point cloud data set, the deformation information extraction module 41 in the deformation monitoring and analysis module 4 extracts the deformation information of the slope from the fused point cloud data, the three-dimensional space positioning module 42 provides accurate three-dimensional space positioning information to assist deformation judgment,The image feature analysis module 43 analyzes the texture features of ground objects in the orthographic image, further confirms the deformation condition, the deformation trend prediction module 44 predicts the future deformation trend according to historical deformation data, the digital elevation model module 45 constructs a digital elevation model by using the fused point cloud data, the DEM construction module 451 is used for constructing a digital elevation model by using the fused point cloud data, the model optimization module 452 is used for optimizing the DEM to improve the model precision and authenticity, the model verification module 453 is used for verifying the accuracy of the DEM through actual measurement data, the early warning and decision module 5 generates a warning signal according to the deformation condition, and generates corresponding engineering measure suggestions and reports, the deformation threshold setting module 51 is used for setting a deformation threshold, which is used for judging whether the slope is stable, the early warning signal issuing module 52 is used for issuing a warning signal when the deformation exceeds the threshold, the decision suggestion generation module 53 is used for generating corresponding engineering measure suggestions according to the deformation condition and the warning signal, and the report generation module 54 is used for generating a slope deformation report.

[0022] It will be obvious to a person skilled in the art that the application is not limited to the details of the above-described exemplary embodiments, but that the application can be implemented in other concrete forms without departing from the spirit or essential characteristics of the application. The embodiments should, therefore, be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the above description, and it is intended to include all changes and modifications that fall within the meaning and scope of equivalents of the claims. Any reference signs in the claims should not be construed as limiting the claims concerned.

Claims

1. A slope deformation monitoring system for geological engineering, comprising a drone base station module (1), characterized in that: The data processing and storage module (2) is connected to the data processing and storage module (2), the data processing and storage module (2) is connected to the point cloud and image fusion module (3), the data point cloud and image fusion module (3) is connected to the deformation monitoring and analysis module (4), and the data deformation monitoring and analysis module (4) is connected to the early warning and decision-making module (5).

2. A slope deformation monitoring system for geological engineering according to claim 1, characterized in that: The UAV base station module (1) includes a base (15), a gear (114) is rotatably connected to the base (15), a motor (113) is fixedly connected to an outer wall of one side of the base (15), and an output end of the motor (113) is fixedly connected to the gear (114), a first connecting rod (115) and a third connecting rod (117) are fixedly connected to the gear (114), the other end of the first connecting rod (115) is hinged to the second connecting rod (116), and the other end of the second connecting rod (116) is hinged to the lifting plate ( 111), slide grooves (112) are provided on the outer walls of both sides of the lifting plate (111), guide rails (110) are provided on the inner wall of the base (15) at positions corresponding to the slide grooves (112), and the guide rails (110) are slidably connected in the slide grooves (112), and the other end of the third connecting rod (117) is hinged with a movable cover (118), and a drone module (14) is provided on the lifting plate (111), and a laser radar module (141) and an optical camera module (142) are provided on the drone module (14).

3. The slope deformation monitoring system for geological engineering according to claim 2, characterized in that: The base (15) is provided with an articulated seat (16), a handle (17) is hingedly connected to the articulated seat (16), a protective cover (18) is sleeved on the handle (17), a battery compartment (19) is provided in the base (15), a battery module (12) is provided in the battery compartment (19), and the battery module (12) is electrically connected to the drone module (14), and an automatic take-off and landing module (11) and a base station communication module (13) are provided on the drone base station module (1).

4. The slope deformation monitoring system for geological engineering according to claim 1, characterized in that: The data processing and storage module (2) comprises a data receiving module (21), a data pre-processing module (22), a coordinate registration module (23) and a data storage module (24), and the data receiving module (21) establishes a data connection with the drone module (14).

5. The slope deformation monitoring system for geological engineering according to claim 1, characterized in that: The point cloud and image fusion module (3) includes a point cloud processing module (31), an orthophoto processing module (32), a point cloud registration module (33), an image dense point cloud generation module (34) and a point cloud fusion module (35); the deformation monitoring and analysis module (4) includes a deformation information extraction module (41), a three-dimensional space positioning module (42), an image feature analysis module (43), a deformation trend prediction module (44) and a digital elevation model module (45); the warning and decision module (5) includes a deformation threshold setting module (51), a warning signal issuance module (52), a decision suggestion generation module (53) and a report generation module (54).

6. The slope deformation monitoring system for geological engineering according to claim 5, characterized in that: The digital elevation model module (45) includes a DEM construction module (451), a model optimization module (452) and a model verification module (453).

7. A slope deformation monitoring method for geological engineering, comprising step 1: drone data acquisition; step 2: data reception and preprocessing; step 3: coordinate registration and data storage; step 4: point cloud and image fusion; step 5: deformation monitoring and analysis; step 6: digital elevation model construction and optimization; and step 7: early warning and decision-making. The method is characterized by: In the step 1, the drone module (14) is automatically launched through the drone base station module (1), and data related to the slope area is collected; In the second step, the data processing and storage module (2) receives the point cloud and image data collected by the drone and pre-processes the original data to improve the data quality; In the step 3, the point cloud data and the image data are converted into a unified coordinate system using a coordinate registration module (23), and accurate alignment of the point cloud and the image is ensured through feature point matching and spatial transformation; In the fourth step, the laser point cloud and the image dense point cloud are fused using the point cloud fusion module (35) to complete the missing point cloud data and generate a more complete and higher precision point cloud data set; In the step 5, the deformation monitoring and analysis module (4) extracts slope deformation information from the fused point cloud data, analyzes the texture features of the ground objects in the orthophoto, and confirms the deformation situation; In step six, the digital elevation model module (45) uses the fused point cloud data to construct a digital elevation model; In step seven, the early warning and decision module (5) generates an early warning signal according to the deformation situation, and generates corresponding engineering measures suggestions and reports.

8. The slope deformation monitoring method for geological engineering according to claim 7, characterized in that: In the step 1, the UAV base station module (1) is moved to a designated location by the handle (17), and then the monitoring flight route of the UAV module (14) is set. The motor (113) on the base (15) drives the first link (115) and the third link (117) to rotate. The first link (115) drives the second link (116) on the lifting plate (111) to rotate. The second link (116) drives the lifting plate (111) to rise. The lifting plate (111) rises along the guide rail (110) through the slide groove (112) and drives the UAV module (14) thereon to rise. At the same time, the third link (117) drives the movable cover (118) to unfold to one side. The mechanisms on both sides realize synchronous movement through the gear (114). After the movable cover (118) is opened, the automatic take-off and landing module (11) controls the drone module (14) to take off smoothly to perform the monitoring task. The drone module (14) is equipped with a laser radar module (141) and an optical camera module (142). The laser radar module (141) is used to collect three-dimensional point cloud data of the slope area, and the optical camera module (142) is used to collect high-resolution orthophoto data of the slope area. When the drone module (14) completes the monitoring task, it lands on the lifting plate (111), and the motor (113) drives the lifting plate (111) to descend in the reverse direction. At the same time, the movable cover (118) is closed, and then the drone module (14) is charged through the battery module (12) provided in the battery compartment (19).

9. The slope deformation monitoring method for geological engineering according to claim 7, characterized in that: In the step 4, the point cloud processing module (31) in the point cloud and image fusion module (3) further processes the point cloud data collected by the laser radar to generate benchmark LiDAR point cloud data, and then the orthophoto processing module (32) processes the orthophoto data collected by the optical camera to generate clear and accurate orthophoto images. The point cloud registration module (33) uses the parallel computing capability of the GPU to accelerate the point cloud registration process and improve the registration efficiency. The image dense point cloud generation module (34) generates a dense image point cloud through multi-view oblique image generation technology. The point cloud fusion module (35) fuses the laser point cloud with the image dense point cloud to complete the missing point cloud data and generate a more complete and higher-precision point cloud data set.

10. The slope deformation monitoring method for geological engineering according to claim 7, characterized in that: In the step 5, the deformation information extraction module (41) in the deformation monitoring and analysis module (4) extracts the deformation information of the slope from the fused point cloud data, the three-dimensional spatial positioning module (42) provides accurate three-dimensional spatial positioning information to assist in deformation judgment, the image feature analysis module (43) analyzes the texture features of the ground objects in the orthophoto to further confirm the deformation situation, and the deformation trend prediction module (44) predicts the future deformation trend based on the historical deformation data.

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