Side slope detection method and device, electronic equipment and storage medium

Abstract

The invention discloses a slope detection method and device, electronic equipment and a storage medium, and relates to the technical field of remote sensing deformation detection data processing, and the main technical scheme comprises the steps: obtaining global positioning system data and three-dimensional point cloud data sent by a sensing system; performing fusion analysis according to the global positioning system data and the three-dimensional point cloud data, and determining a deformation type and deformation parameters of the slope; and when the deformation parameter of the side slope exceeds a preset deformation threshold value, early warning information is triggered to give an alarm. Compared with the prior art, the embodiment of the invention reduces the dependence on manual operation through an automatic measurement and data processing algorithm, and reduces the manpower and resource cost. Besides, in combination with intelligent analysis of multi-temporal data, the system can autonomously identify a slope change area, subjective errors in manual operation are effectively avoided, slope deformation information can be captured in time under any weather condition, and timely discovery and early warning of potential safety hazards are ensured.

Description

Technical Field

[0001] The present disclosure relates to the technical field of remote sensing deformation detection data processing, and in particular to a slope detection method and device, electronic equipment and storage medium. Background Art

[0002] In a mining environment, slope stability is an important aspect of ensuring mine safety. Disasters such as slope collapse can pose a serious threat to the safety of mining workers and equipment, especially in high-risk areas such as spoil dumps.

[0003] In order to timely monitor and prevent potential disasters on the slope, manual measurement is currently the main method used for detection.

[0004] Although manual detection can detect potential hazards of slopes to a certain extent, manual measurement is time-consuming and labor-intensive, with limited coverage and difficult to guarantee accuracy. Therefore, how to achieve automatic real-time detection of slope stability is an urgent problem to be solved. Summary of the invention

[0005] The present disclosure provides a slope detection method, device, electronic device and storage medium, the main purpose of which is to achieve real-time detection of slope stability in a convenient deployment situation.

[0006] According to a first aspect of the present disclosure, a slope detection method is provided, comprising:

[0007] Obtaining global positioning system data and three-dimensional point cloud data sent by the sensor system;

[0008] Performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope;

[0009] When the deformation parameter of the slope exceeds a preset deformation threshold, the early warning information is triggered to execute an alarm.

[0010] Optionally, after acquiring the global positioning system data and the three-dimensional point cloud data sent by the sensor system, the method further includes:

[0011] Filtering the three-dimensional point cloud data based on progressively encrypted triangulated point cloud filtering to remove noise;

[0012] unifying the global positioning system coordinates of the global positioning system data with the coordinates of the three-dimensional point cloud data;

[0013] Synchronize the GPS data and the 3D point cloud data according to the timestamps of the GPS data and the 3D point cloud data, and align the GPS data and the 3D point cloud data at the same time;

[0014] The global positioning system data and the three-dimensional point cloud data after the coordinates are unified are spatially corrected.

[0015] Optionally, the performing fusion analysis based on the global positioning system data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope includes:

[0016] Based on the global positioning system data and the three-dimensional point cloud data after time synchronization and spatial alignment, a joint analysis of slope changes is performed to determine whether the slope has displacement or deformation.

[0017] Optionally, the performing fusion analysis based on the global positioning system data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope further includes:

[0018] Generate a three-dimensional model based on three-dimensional point cloud data at different times; wherein the three-dimensional point cloud model contains time information of the three-dimensional point cloud data;

[0019] According to the nearest neighbor search algorithm, the three-dimensional point cloud data at adjacent moments in the three-dimensional model are detected to determine whether there is a slope change area;

[0020] The point cloud change distance of the slope change area in the point model is calculated, and the slope change area is marked.

[0021] Optionally, the performing fusion analysis based on the global positioning system data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope further includes:

[0022] The changes in vertical settlement and horizontal displacement are determined based on the GPS data, and the deformation type and deformation parameters of the slope are determined.

[0023] According to a second aspect of the present disclosure, there is provided a slope detection device, comprising:

[0024] An acquisition unit, used for acquiring global positioning system data and three-dimensional point cloud data sent by the sensor system;

[0025] An analysis unit, used for performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope;

[0026] The alarm unit is used to trigger early warning information to execute an alarm when the deformation parameter of the slope exceeds a preset deformation threshold.

[0027] Optionally, the device further comprises:

[0028] A filtering unit, configured to filter the three-dimensional point cloud data based on a progressively encrypted triangulated point cloud filter to remove noise after the acquisition unit acquires the global positioning system data and the three-dimensional point cloud data sent by the sensor system;

[0029] a processing unit for unifying the GPS coordinates of the GPS data with the coordinates of the three-dimensional point cloud data;

[0030] a synchronization processing unit, configured to perform synchronization processing on the GPS data and the three-dimensional point cloud data according to timestamps of the GPS data and the three-dimensional point cloud data, and align the GPS data and the three-dimensional point cloud data at the same time;

[0031] The correction unit is used to perform spatial position correction on the global positioning system data and the three-dimensional point cloud data after coordinate unification.

[0032] Optionally, the analysis unit is further used for:

[0033] Based on the global positioning system data and the three-dimensional point cloud data after time synchronization and spatial alignment, a joint analysis of slope changes is performed to determine whether the slope has displacement or deformation.

[0034] Optionally, the analysis unit further includes:

[0035] A generating module, used to generate a three-dimensional model according to the three-dimensional point cloud data at different times; wherein the three-dimensional point cloud model contains the time information of the three-dimensional point cloud data;

[0036] A detection module, used to detect the three-dimensional point cloud data at adjacent moments in the three-dimensional model according to a nearest neighbor search algorithm to determine whether there is a slope change area;

[0037] The calculation module is used to calculate the point cloud change distance of the slope change area in the point model and mark the slope change area.

[0038] Optionally, the analysis unit is further used for:

[0039] The changes in vertical settlement and horizontal displacement are determined based on the GPS data, and the deformation type and deformation parameters of the slope are determined.

[0040] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0041] at least one processor; and

[0042] a memory communicatively connected to the at least one processor; wherein,

[0043] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0044] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0045] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0046] The present disclosure provides a slope detection method, device, electronic device and storage medium, the main technical solutions of which include: obtaining global positioning system data and three-dimensional point cloud data sent by a sensing system; performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope; when the deformation parameters of the slope exceed the preset deformation threshold, triggering the early warning information to execute the alarm. Compared with the related art, the embodiment of the present application reduces the dependence on manual operation and reduces the manpower and resource costs through automated measurement and data processing algorithms. In addition, combined with the intelligent analysis of multi-phase data, the system can autonomously identify the slope change area, effectively avoid subjective errors in human operation, and can timely capture slope deformation information under any weather conditions, ensuring the timely discovery and early warning of potential safety hazards.

[0047] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0049] Figure 1 A schematic diagram of a flow chart of a slope detection method provided by an embodiment of the present disclosure;

[0050] Figure 2 A schematic diagram of a flow chart of a slope detection method provided by an embodiment of the present disclosure;

[0051] Figure 3 A schematic diagram of the overall process of slope detection provided by an embodiment of the present disclosure;

[0052] Figure 4 A schematic diagram of the structure of a slope detection device provided in an embodiment of the present disclosure;

[0053] Figure 5 A schematic diagram of the structure of a slope detection device provided in an embodiment of the present disclosure;

[0054] Figure 6 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0055] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0056] A slope detection method, device, electronic device, and storage medium according to an embodiment of the present disclosure are described below with reference to the accompanying drawings.

[0057] Figure 1 A schematic flow chart of a slope detection method provided in an embodiment of the present disclosure.

[0058] like Figure 1 As shown, the method comprises the following steps:

[0059] Step 101, obtaining global positioning system data and three-dimensional point cloud data sent by the sensor system.

[0060] GPS (Global Positioning System) data can provide high-precision geographic location information, including longitude, latitude, altitude, etc., while three-dimensional point cloud data captures the detailed three-dimensional structure of the surface and objects on it through technologies such as laser scanning.

[0061] In some embodiments, a GPS sensor installed in the monitoring area can continuously receive signals from multiple satellites to calculate the precise location of the sensor itself. After processing, these data can reflect the displacement of the slope in the time dimension.

[0062] Three-dimensional point cloud data is acquired through equipment such as laser scanners, which can create a three-dimensional model of the monitoring area. It contains a large number of spatial point coordinates and can describe the morphology and structure of the surface very accurately.

[0063] Combining these two types of data can achieve comprehensive monitoring of slope deformation: GPS data provides macroscopic displacement trends, while 3D point cloud data provides microscopic surface change details.

[0064] Step 102: Perform fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope.

[0065] Fusion analysis based on the GPS data and the 3D point cloud data is an advanced technical method to reveal the slope deformation characteristics by comprehensive processing of the two data sources. The following is an extended description of the process:

[0066] In some embodiments, by analyzing the displacement vector, velocity field and acceleration field, combined with the surface morphological changes in the point cloud data, the deformation type of the slope can be identified, such as stretching, compression, shearing, rotation, etc.; based on the fused data, the key parameters of the slope deformation are calculated, including deformation amount, deformation rate, deformation direction, etc. The deformation parameters help to understand the stable state of the slope. In some embodiments, the calculated deformation parameters can be used to construct a mathematical model or physical model of slope deformation to simulate the deformation behavior of the slope and predict future deformation trends.

[0067] Step 103: When the deformation parameter of the slope exceeds a preset deformation threshold, triggering early warning information to execute an alarm.

[0068] In some embodiments, the normal range of slope deformation can be determined and a reasonable preset deformation threshold can be set by analyzing historical deformation data. The preset deformation threshold can also be dynamically adjusted according to real-time monitoring data and changes in slope stability. The embodiment of the present application does not limit the setting method of the preset deformation threshold.

[0069] In some embodiments, the warning level can be set for the warning information to deal with different deformation behaviors and deformation parameters. For example, when the deformation parameter approaches but does not exceed the threshold, a primary warning is issued to prompt the monitoring personnel to pay more attention; when the deformation parameter slightly exceeds the threshold, it may indicate that the stability of the slope has decreased and certain preventive measures need to be taken. When the deformation parameter significantly exceeds the threshold, it indicates that the slope may be about to undergo large-scale deformation or landslide, and the emergency plan needs to be activated immediately.

[0070] The present disclosure provides a slope detection, and the main technical solutions include: obtaining global positioning system data and three-dimensional point cloud data sent by the sensing system; performing fusion analysis based on the global positioning system data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope; when the deformation parameters of the slope exceed the preset deformation threshold, triggering the early warning information to execute the alarm. Compared with the related art, the embodiment of the present application reduces the dependence on manual operation and reduces the manpower and resource costs through automated measurement and data processing algorithms. In addition, combined with the intelligent analysis of multi-phase data, the system can autonomously identify the slope change area, effectively avoid subjective errors in human operation, and can timely capture slope deformation information under any weather conditions, ensuring the timely discovery and early warning of potential safety hazards.

[0071] In some embodiments, after executing step 101, the acquired GPS data and three-dimensional point cloud data need to be processed so as to perform joint detection based on the GPS data and the three-dimensional point cloud data. Figure 2 , Figure 2 A schematic diagram of a flow chart of a slope detection method provided by an embodiment of the present disclosure is optional. After acquiring the GPS data and the three-dimensional point cloud data sent by the sensor system, the method further includes:

[0072] Step 201: Filter the three-dimensional point cloud data based on progressively encrypted triangulated point cloud filtering to remove noise.

[0073] See also Figure 3 , Figure 3 A schematic diagram of the overall process of slope detection provided by the embodiment of the present disclosure is shown in FIG. Figure 3 As shown, the point cloud data and GPS total station data are preprocessed to ensure the data quality and consistency of the two; including noise reduction and coordinate alignment for the point cloud data, and coordinate conversion and filtering for the GPS data;

[0074] Point cloud preprocessing, based on the progressively encrypted triangulated network point cloud filtering to remove noise and ensure the accuracy of point cloud data, where the principle of progressively encrypted triangulated network point cloud filtering is shown in formula (1);

[0075]

[0076] Among them, P filtered is the filtered point, P i is a point in the neighborhood, and N is the number of points in the neighborhood.

[0077] Step 202: unify the GPS coordinates of the GPS data and the coordinates of the three-dimensional point cloud data.

[0078] GPS data preprocessing, converting GPS coordinates into a coordinate system consistent with point cloud data, from geographic coordinate system to plane rectangular coordinate system, and reducing noise interference through Kalman filter;

[0079] Step 203: Synchronize the GPS data and the 3D point cloud data according to the timestamps of the GPS data and the 3D point cloud data, and align the GPS data and the 3D point cloud data at the same time.

[0080] The point cloud data and GPS monitoring data collected at different time phases are aligned and synchronized in time and space to ensure that the data of the two can be analyzed and integrated in the same space-time framework; ① Time synchronization, the point cloud and GPS data are synchronized through timestamps to ensure that the data at the same time corresponds.

[0081] Step 204 , performing spatial position correction on the GPS data and the three-dimensional point cloud data after coordinate unification.

[0082] Spatial alignment uses coordinate transformation to correct the spatial positions of the two so that the coordinates of the monitoring points collected by GPS can match the coordinate system of the point cloud data.

[0083] In some embodiments, the performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope includes:

[0084] Based on the GPS data and the three-dimensional point cloud data after time synchronization and spatial alignment, a joint analysis of slope changes is performed to determine whether the slope has displacement or deformation.

[0085] Change monitoring and fusion analysis, based on the point cloud differential data and real-time monitoring data after time synchronization and spatial alignment, jointly analyzes slope changes and determines the displacement or deformation of the slope; aligns the displacement of the monitoring points accurately measured by the robot with the details in the global point cloud to improve the accuracy of the differential point cloud. This fusion can optimize the accuracy of the slope change area, especially in the detection of changes in vertical settlement and displacement of local areas of the slope; at the same time, based on the point cloud difference, combined with real-time monitoring data, identify areas where the slope has changed significantly. For areas with significant changes, especially those with height changes, based on the high-precision Z value provided by the robot, a more reliable slope change model can be generated, and these changes can be further classified to mark different change modes such as settlement and slip.

[0086] Result analysis and early warning: The fused results are used in the real-time monitoring and early warning system of the slope. If the monitored slope change exceeds the preset threshold, an early warning is triggered and a real-time alarm is output.

[0087] In some embodiments, the step of performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope further includes:

[0088] Generate a three-dimensional model based on three-dimensional point cloud data at different times; wherein the three-dimensional point cloud model contains time information of the three-dimensional point cloud data;

[0089] According to the nearest neighbor search algorithm, the three-dimensional point cloud data at adjacent moments in the three-dimensional model are detected to determine whether there is a slope change area;

[0090] The point cloud change distance of the slope change area in the point model is calculated, and the slope change area is marked.

[0091] Multi-temporal point cloud registration, the point cloud data at different times are fused to generate a 3D model containing time information. The ICP (Iterative Closest Point) algorithm is used to match and stitch multi-temporal point clouds to ensure that point clouds at different times can be registered with high precision. The ICP algorithm is shown in formula (2);

[0092]

[0093] Among them, R is the rotation matrix, t is the translation vector, P point is the current point cloud, P ref is the reference point cloud.

[0094] Slope change area extraction: The change area in the two phases of data is detected by the nearest neighbor search algorithm, the point cloud change distance is calculated, and the area with significant slope displacement or deformation is marked. The change distance is shown in formula (3);

[0095]

[0096] Among them, D ij It is the minimum distance between point cloud points. If it exceeds a certain threshold, it is considered that there is a slope change.

[0097] In some embodiments, the step of performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope further includes:

[0098] The changes in vertical settlement and horizontal displacement are determined based on the GPS data, and the deformation type and deformation parameters of the slope are determined.

[0099] Before executing this step, first arrange the reference points and detection points of the measuring robot and the total station, and the robot sets up the station. The measuring robot is placed on the roof of the building opposite the spoil dump as the station. The forced centering disc and bricks are poured with cement. After they are completely solidified, the measuring robot is placed on the station. In some embodiments, the reference points and detection points can be arranged according to the following methods. It should be noted that this description method is only an exemplary description and is not a specific limitation on the specific arrangement method. The embodiments of the present application do not limit this.

[0100] Benchmark point layout: The benchmark points are laid out on the stable surface or slope outside the sliding body; the three benchmark points are located with the robot as the center, 120° apart, and the vertical angle with the measurement robot's line of sight does not exceed 45°. At the same time, they have line of sight with each other and are located in a stable area outside the measurement area. The height is 10 cm;

[0101] Monitoring points are set up on the sliding body and boundary line, and the spacing between monitoring points is generally 5 to 15m. The monitoring points must be closely integrated with the slope rock mass. When buried, holes can be drilled in the rock mass with a depth of not less than 0.5m, and then a metal rod with a diameter of 20cm and a length of 0.8 to 1.0m is inserted; prisms are evenly arranged on each layer of the slope of the southwest spoil dump, with a total of 60 prisms. First, the specific location and height of the prism installation are determined by the measuring robot; a small red flag is inserted at the specific installation location and the height that can be seen by the measuring robot is written; then at the monitoring point location Wire steel was hammered in and raised by about 60 centimeters. The prism was reinforced by burying three anchors and tightening the wire. The problems of the prism being too low to be scanned by the total station and the prism shaking leading to inaccurate positioning were solved. After field tests, the prism basically remained motionless and could be scanned by the total station under wind speeds of 5-6. Finally, a total of 60 monitoring points were installed on the slope of the southwest spoil dump, with the specific distribution of 1 on the first layer, 2 on the second layer, 3 on the third layer, 8 on the fourth layer, 8 on the fifth layer, 11 on the sixth layer, 10 on the seventh layer, 9 on the eighth layer, and 8 on the ninth layer.

[0102] Slope point monitoring data collection, the measuring robot conducts real-time and uninterrupted measurement of the slope, and the collection time spans the frozen soil period, spring thaw period, and rainy season. The TM50 measuring robot is used to monitor the slope points, mainly monitoring the vertical settlement Z and the horizontal displacement X, Y changes.

[0103] Corresponding to the above-mentioned slope detection method, the present invention also provides a slope detection device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be repeated in the present invention.

[0104] Figure 4A schematic diagram of the structure of a slope detection device provided in an embodiment of the present disclosure is shown in FIG. Figure 4 As shown, including:

[0105] An acquisition unit 31 is used to acquire global positioning system data and three-dimensional point cloud data sent by the sensor system;

[0106] An analysis unit 32, configured to perform fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope;

[0107] The alarm unit 33 is used to trigger early warning information to execute an alarm when the deformation parameter of the slope exceeds a preset deformation threshold.

[0108] The present disclosure provides a slope detection device, the main technical scheme of which includes: obtaining global positioning system data and three-dimensional point cloud data sent by a sensing system; performing fusion analysis based on the global positioning system data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope; when the deformation parameters of the slope exceed the preset deformation threshold, triggering the early warning information to execute the alarm. Compared with the related art, the embodiment of the present application reduces the dependence on manual operation and reduces the manpower and resource costs through automated measurement and data processing algorithms. In addition, combined with the intelligent analysis of multi-phase data, the system can autonomously identify the slope change area, effectively avoid subjective errors in human operation, and can timely capture slope deformation information under any weather conditions, ensuring the timely discovery and early warning of potential safety hazards.

[0109] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the device also includes:

[0110] The filtering unit 34 is used to filter the three-dimensional point cloud data based on the progressively encrypted triangulated point cloud filtering to remove noise after the acquisition unit 31 acquires the global positioning system data and the three-dimensional point cloud data sent by the sensor system;

[0111] A processing unit 35, configured to unify the GPS coordinates of the GPS data with the coordinates of the three-dimensional point cloud data;

[0112] A synchronization processing unit 36, configured to perform synchronization processing on the GPS data and the 3D point cloud data according to timestamps of the GPS data and the 3D point cloud data, and align the GPS data and the 3D point cloud data at the same time;

[0113] The correction unit 37 is used to perform spatial position correction on the GPS data and the three-dimensional point cloud data after coordinate unification.

[0114] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the analysis unit 32 is also used for:

[0115] Based on the global positioning system data and the three-dimensional point cloud data after time synchronization and spatial alignment, a joint analysis of slope changes is performed to determine whether the slope has displacement or deformation.

[0116] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the analysis unit 32 also includes:

[0117] A generating module 321, used to generate a 3D model according to the 3D point cloud data at different times; wherein the 3D point cloud model contains the time information of the 3D point cloud data;

[0118] A detection module 322 is used to detect the three-dimensional point cloud data at adjacent moments in the three-dimensional model according to a nearest neighbor search algorithm to determine whether there is a slope change area;

[0119] The calculation module 323 is used to calculate the point cloud change distance of the slope change area in the point model and mark the slope change area.

[0120] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 5 As shown, the analysis unit 32 is also used for:

[0121] The changes in vertical settlement and horizontal displacement are determined based on the GPS data, and the deformation type and deformation parameters of the slope are determined.

[0122] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present disclosure, and the principle is the same, which is no longer limited in the embodiment of the present disclosure.

[0123] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0124] Figure 6A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0125] like Figure 6 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 402 or a computer program loaded from a storage unit 408 to a RAM (Random Access Memory) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0126] A number of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0127] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as a slope detection method. For example, in some embodiments, a slope detection method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the aforementioned slope detection method in any other appropriate manner (for example, by means of firmware).

[0128] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a special purpose or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0129] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0130] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0131] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0132] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0133] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0134] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0135] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0136] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A slope detection method, characterized in that: include: Obtaining global positioning system data and three-dimensional point cloud data sent by the sensor system; Performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope; When the deformation parameter of the slope exceeds a preset deformation threshold, the early warning information is triggered to execute an alarm.

2. The method according to claim 1, characterized in that After acquiring the global positioning system data and the three-dimensional point cloud data sent by the sensor system, the method further includes: Filtering the three-dimensional point cloud data based on progressively encrypted triangulated point cloud filtering to remove noise; unifying the global positioning system coordinates of the global positioning system data with the coordinates of the three-dimensional point cloud data; Synchronize the GPS data and the 3D point cloud data according to the timestamps of the GPS data and the 3D point cloud data, and align the GPS data and the 3D point cloud data at the same time; The global positioning system data and the three-dimensional point cloud data after the coordinates are unified are spatially corrected.

3. The method according to claim 2, characterized in that The step of performing fusion analysis based on the GPS data and the 3D point cloud data to determine the deformation type and deformation parameters of the slope includes: Based on the global positioning system data and the three-dimensional point cloud data after time synchronization and spatial alignment, a joint analysis of slope changes is performed to determine whether the slope has displacement or deformation.

4. The method according to claim 3, characterized in that The step of performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope further includes: Generate a three-dimensional model based on three-dimensional point cloud data at different times; wherein the three-dimensional point cloud model contains time information of the three-dimensional point cloud data; According to the nearest neighbor search algorithm, the three-dimensional point cloud data at adjacent moments in the three-dimensional model are detected to determine whether there is a slope change area; The point cloud change distance of the slope change area in the point model is calculated, and the slope change area is marked.

5. The method according to claim 3, characterized in that: The step of performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope further includes: The changes in vertical settlement and horizontal displacement are determined based on the GPS data, and the deformation type and deformation parameters of the slope are determined.

6. A slope detection device, characterized in that: include: An acquisition unit, used for acquiring global positioning system data and three-dimensional point cloud data sent by the sensor system; An analysis unit, used for performing fusion analysis based on the GPS data and the three-dimensional point cloud data to determine the deformation type and deformation parameters of the slope; The alarm unit is used to trigger early warning information to execute an alarm when the deformation parameter of the slope exceeds a preset deformation threshold.

7. The device according to claim 6, characterized in that The device also includes: A filtering unit, configured to filter the three-dimensional point cloud data based on a progressively encrypted triangulated point cloud filter to remove noise after the acquisition unit acquires the global positioning system data and the three-dimensional point cloud data sent by the sensor system; a processing unit for unifying the GPS coordinates of the GPS data with the coordinates of the three-dimensional point cloud data; a synchronization processing unit, configured to perform synchronization processing on the GPS data and the three-dimensional point cloud data according to timestamps of the GPS data and the three-dimensional point cloud data, and align the GPS data and the three-dimensional point cloud data at the same time; The correction unit is used to perform spatial position correction on the GPS data and the three-dimensional point cloud data after coordinate unification.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 5.

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