Deep foundation pit structure crack AI intelligent monitoring control method and system

Abstract

The invention discloses a deep foundation pit structure crack AI intelligent monitoring control method and system, and relates to the technical field of civil engineering structure health monitoring, and the method comprises the following steps: S1, measurement positioning: obtaining project control points of a field working face and feature data of foundation pit structure side lines, and carrying out positioning recheck based on positioning data of a positioning system; s2, unmanned aerial vehicle scanning: guiding the unmanned aerial vehicle to move in the deep foundation pit site based on the measurement positioning data, and scanning the site by a pre-loaded scanning radar to obtain point cloud data of the deep foundation pit structural surface; s3, modeling: modeling based on the point cloud data, identifying structure change features based on a model, and marking feature attributes; and S4, structural analysis and early warning: outputting a structural abnormity prompt based on the annotation information, and recording change information of the structure based on a time sequence for structural evolution analysis and prediction. The method has the effect of improving the monitoring effect of the deep foundation pit crack.

Description

Technical Field

[0001] This application relates to the field of civil engineering structural health monitoring technology, and in particular to an AI-based intelligent monitoring and control method and system for cracks in deep foundation pit structures. Background Technology

[0002] The safety of deep foundation pit support structures is of paramount importance, and cracks that appear in these structures are a key early warning signal of structural instability.

[0003] Currently, the detection of cracks in deep foundation pits mainly relies on traditional manual inspections and sensor-based local monitoring. Manual inspections suffer from problems such as poor timeliness, strong subjectivity, limited coverage, and high safety risks. Sensor monitoring, on the other hand, faces limitations such as reliance on manual prediction for placement and isolated information.

[0004] Therefore, this application proposes a new technical solution. Summary of the Invention

[0005] To improve the monitoring effect of cracks in deep foundation pits, this application provides an AI-based intelligent monitoring and control method and system for cracks in deep foundation pit structures.

[0006] Firstly, this application provides an AI-based intelligent monitoring and control method for cracks in deep foundation pit structures, employing the following technical solution:

[0007] A method for AI-powered intelligent monitoring and control of cracks in deep foundation pit structures includes the following steps:

[0008] S1. Measurement and positioning, which includes: acquiring the characteristic data of the project control points and the edge lines of the foundation pit structure on the working face, and performing positioning verification based on the positioning data of the positioning system;

[0009] S2. UAV scanning, which includes: based on measurement and positioning data, guiding the UAV to move on the deep foundation pit site, and scanning the site with a pre-loaded scanning radar to obtain point cloud data of the deep foundation pit structure surface;

[0010] S3. Modeling, which includes: modeling based on point cloud data, and identifying structural change features based on the model and annotating feature attributes;

[0011] S4. Structural analysis and early warning, which includes: outputting structural anomaly alerts based on labeled information, and recording structural change information based on time series for structural evolution analysis and prediction.

[0012] Optionally, the positioning verification includes:

[0013] A laser calibrator with an integrated positioning unit is established; wherein the laser calibrator is capable of emitting laser light vertically upwards at least;

[0014] The laser calibrator is used to perform laser pointing and obtain positioning data at multiple project control points and multiple structural sides in the foundation pit;

[0015] At a pre-selected point on the deep foundation pit site, obtain the calibration indication image of the laser calibrator during calibration from an overhead or upward perspective;

[0016] Multiple calibration indicator images are subjected to layer unification and overlay processing to obtain a global calibration indicator image;

[0017] The positioning data from each laser calibrator during its previous calibrations are marked on the global calibration indicator diagram.

[0018] Based on the global calibration indicator diagram, the parameters are verified in conjunction with the construction project drawings.

[0019] Secondly, this application provides a monitoring and control system for the AI ​​intelligent monitoring and control method for cracks in deep foundation pit structures as described above, employing the following technical solution:

[0020] A monitoring and control system, comprising:

[0021] A laser calibrator is used to perform laser pointing and acquire at least one positioning data at multiple project control points and multiple structural sides in the foundation pit.

[0022] The drone is used to acquire calibration indication images of the laser calibrator at a pre-selected location on the deep foundation pit site from an overhead or under-the-head view; and it is also used to carry a scanning radar to scan the site and obtain point cloud data of the deep foundation pit structure surface.

[0023] The data processing platform is used to acquire data from laser calibrators, drones, and scanning radars, and to perform positioning verification, modeling, structural analysis, and early warning.

[0024] Optionally, the laser calibrator includes a housing and a gyroscope frame, a laser generating module, and a positioning unit installed in the housing. The housing has a light-transmitting hole that communicates with the inner cavity. The light-transmitting hole is enclosed by a transparent plate. The laser generating module has at least one light-emitting part, which is located on the gyroscope frame and is counterweighted so that it emits light vertically upward from the light-transmitting hole.

[0025] Optionally, the gyroscope frame includes an outer notched ring, a middle ring body, and a rotating shaft. The rotating shaft is rotatably connected to the surface of the outer notched ring that faces the light-transmitting hole and is located away from the opening. The rotating shaft is fixedly connected to the housing.

[0026] The inner ring is placed inside the notched ring and is rotatably connected to both ends of the outer notched ring on both radially symmetrical sides. The rotating shaft is radially arranged in the inner ring, rotatably connected and perpendicular to the rotation center line of the inner ring.

[0027] The laser generating module includes a focusing cone as the light emitting part and a light source unit. The focusing cone is fixed to the rotation axis with the bottom of the cone facing downward. A vertically penetrating focusing channel is opened inside the focusing cone. The light source unit is fixed to the housing, located below the focusing cone and emitting light towards the focusing cone.

[0028] Optionally, the laser generating module further includes a convex lens, which is fixed below the focusing cone and located between the focusing cone and the light source unit, and the lower end of the focusing channel is concave and flared outward.

[0029] Optionally, the housing sidewall is fixed with an adhesive groove for filling the adhesive structure, and / or the bottom is provided with a socket for connecting the support column.

[0030] Optionally, the laser calibrator further includes a wireless communication module, which is at least electrically connected to the positioning unit.

[0031] Optionally, the laser calibrator further includes a microcontroller electrically connected to the light source unit and the wireless communication module, the microcontroller being configured as follows:

[0032] Obtain the identification code of the current laser calibrator;

[0033] The optical signal characteristics of the current laser calibrator are obtained based on the preset identification code parsing rules;

[0034] Controlling the operation of the light source unit based on optical signal characteristics;

[0035] The optical signal characteristics include at least the light frequency and period.

[0036] In summary, this application includes the following beneficial technical effects: by combining UAVs and scanning radar, high-precision point cloud data can be collected from the deep foundation pit site, so as to use the point cloud data set for modeling. Based on the model, various structural features of the deep foundation pit can be automatically identified and analyzed. This not only accurately quantifies the current structural safety indicators (such as the rate of crack width evolution and the lateral displacement trend of the retaining structure), but also predicts the response and risk evolution of the structure under different working conditions (such as continued excavation, rainfall, and disturbance from nearby construction). This provides a data-driven decision-making basis for dynamically adjusting construction plans and proactive reinforcement measures, thereby improving the monitoring effect of deep foundation pit cracks. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the main process flow of the method in this application;

[0038] Figure 2 This is a schematic diagram of the overall structure of the laser calibrator of this application;

[0039] Figure 3 yes Figure 2A schematic diagram of a partial cross-section structure;

[0040] Figure 4 This is a schematic diagram of the control structure of the laser calibrator.

[0041] Explanation of reference numerals in the attached drawings: 1. Housing; 11. Adhesive groove; 2. Gyroscope frame; 21. Outer notch ring; 22. Middle ring body; 23. Rotation axis; 3. Laser generating module; 31. Focusing cone; 32. Light source unit; 33. Convex lens; 4. Positioning unit; 5. Wireless communication module; 6. Microcontroller. Detailed Implementation

[0042] The following is in conjunction with the appendix Figures 1-4 This application will be described in further detail.

[0043] This application discloses an AI-based intelligent monitoring and control method for cracks in deep foundation pit structures.

[0044] Reference Figure 1 The AI-based intelligent monitoring and control method for cracks in deep foundation pit structures includes the following steps:

[0045] S1. Measurement and positioning, which includes: acquiring the characteristic data of the project control points and the edge lines of the foundation pit structure on the working face, and performing positioning verification based on the positioning data of the positioning system.

[0046] Specifically:

[0047] Before collecting on-site model data, surveyors obtained data such as project control points and the edge lines of the foundation pit support structure from the on-site work surface. Project control points refer to key monitoring nodes and points set to ensure construction safety and quality, such as the location and number of monitoring sampling points and displacement thresholds. The edge lines of the foundation pit structure include the location and number of sampling points along the edge of the foundation pit support structure.

[0048] In this embodiment, the positioning system can be selected from the BeiDou satellite positioning system. The actual geographical locations of the above-mentioned points are obtained through satellite positioning, and the positions obtained from the drawings and other references are accurately verified to ensure the accuracy of the measurement.

[0049] S2. UAV scanning, which includes: guiding the UAV to move on the deep foundation pit site based on measurement and positioning data, and scanning the site with a pre-loaded scanning radar to obtain point cloud data of the deep foundation pit structural surface.

[0050] Understandably, when using drones, pre-selected locations can be entered into the drone's navigation and flight control system, and its built-in navigation software can be used to automatically optimize and generate the optimal flight path (considering the shortest path, the most comprehensive coverage, and the best obstacle avoidance) to efficiently and safely collect data and obtain a high-precision point cloud dataset of the deep foundation pit site.

[0051] Scanning radar can be lidar, millimeter-wave radar, etc. The following explanation uses lidar as an example. The usage of drones and laser scanners (radar) is existing technology and will not be elaborated on here.

[0052] S3. Modeling, which includes: modeling based on point cloud data, and identifying structural change features based on the model, and annotating feature attributes.

[0053] Understandably, after generating dense point cloud data through laser scanning, it will outline the contours of the target area in a three-dimensional coordinate system. After being imported into a corresponding computer system for analysis, the data can be denoised, error-corrected, and high-precision models generated using appropriate AI software models. The computer system can also utilize multi-source datasets obtained from multiple scans by drones to iteratively optimize and repair defects in the model, significantly improving its accuracy and completeness. Modeling laser point cloud data is an existing technology and will not be elaborated upon further.

[0054] When constructing the above model, on-site monitoring data such as stress at each point can also be integrated. Then, based on the real-world model of the deep foundation pit, structural change features such as cracks, deformation, and water seepage points of the deep foundation pit are identified using image recognition technology, and the location, size, depth, and other feature information of the cracks are marked in the model.

[0055] When using it, monitoring personnel can manually remove noisy data from the analysis results and re-analyze them to achieve the highest accuracy in feature finding.

[0056] S4. Structural analysis and early warning, which includes: outputting structural anomaly alerts based on labeled information, and recording structural change information based on time series for structural evolution analysis and prediction.

[0057] Regarding prompts, for example: when a new crack appears with a width or depth exceeding a preset threshold, the computer system outputs corresponding information to a designated account, or prompts a pop-up window on the corresponding terminal.

[0058] Based on the time-series recording of structural changes, this refers to: UAVs re-equipping themselves with scanning radar to scan the deep foundation pit again at a set frequency and in a patrol manner, re-modeling it, and then recording the changes in cracks before and after according to the timeline, and even generating animations to show the characteristics of structural evolution, helping staff to conduct analysis and prediction, accurately predict future deformation trends through forward-looking inference, quantify the probability of instability risk, and provide timely warnings of critical states.

[0059] In other words, this method can not only accurately quantify current structural safety indicators (such as crack width evolution rate and lateral displacement trend of the retaining structure), but also predict the structural response and risk evolution under different working conditions (such as continued excavation, rainfall, and disturbance from nearby construction), providing data-driven decision-making basis for dynamically adjusting construction plans and proactive reinforcement measures.

[0060] In one embodiment of this application, the location verification performed using the positioning system includes:

[0061] 1) Establish a laser calibrator integrated with a positioning unit; wherein the laser calibrator can emit laser light vertically upwards at least.

[0062] It is understandable that the laser calibrator is an independent electronic device, and there can be one laser calibrator used sequentially in various locations, or multiple laser calibrators used in combination. In order to reduce the number of personnel required to operate multiple laser calibrators, the laser calibrator can also integrate a wireless communication module 5 so that personnel can remotely control it.

[0063] 2) Have the laser calibrator perform laser pointing and obtain positioning data at least once at multiple project control points and multiple structural edges in the foundation pit. Example:

[0064] After placing a laser calibrator at a project control point, it is activated, emitting a laser beam vertically upwards and reading the positioning data from the positioning unit (e.g., a BeiDou positioning unit).

[0065] 3) At a pre-selected point on the deep foundation pit site, obtain the calibration indication image of the laser calibrator during calibration from an overhead or upward perspective.

[0066] That is, firstly, the light emitted by the laser calibrator in this embodiment should be relatively bright visible light; secondly, in order to clearly identify the calibration laser, a horizontal background board (curtain) can be erected above the deep foundation pit.

[0067] 4) Perform layer unification and overlay processing on multiple calibration indicator images to obtain a global calibration indicator map;

[0068] That is, after selecting images that meet the clarity and pixel requirements, a unified scale is used, and then the images are superimposed as layers (refer to CAD layers) to obtain an image that shows all the calibrated lasers (points).

[0069] 5) Mark the positioning data from each laser calibrator's previous calibrations on the global calibration indicator map, for example:

[0070] A laser calibration is performed at point A. The coordinate positioning data during calibration is (X1, y1, z1). Then, the laser point corresponding to point A in the global calibration indicator diagram is labeled (X1, y1, z1).

[0071] 6) Verify parameters based on the global calibration indicator diagram and in conjunction with the construction project drawings; for example:

[0072] Select the location data of any two points in the diagram, calculate the distance between the points, and then compare it with the construction project drawings to verify the parameters;

[0073] Alternatively, the outline of a support structure for a deep foundation pit can be obtained by combining multiple positioning data points, and the parameters can be verified by comparing them with the parameters of the support structure in the construction drawings.

[0074] Based on the above setup, this method can verify the data from step S1 using positioning data to ensure the accuracy of the measurements performed. The above verification theoretically does not require a laser. The reason for using a laser instead of directly analyzing satellite positioning unit values ​​is because:

[0075] With the laser configured, the operation process is more visualized, and the global calibration indicator diagram is intuitive. The coordinate system required for analysis can be established directly from the origin of the diagram, which is more convenient.

[0076] More importantly, if only satellite positioning values ​​are taken, it is difficult to detect if the positioning unit malfunctions or is interfered with, resulting in a deviation in the positioning data of a certain point. It may be directly assumed that the foundation pit structure has changed.

[0077] However, with lasers, the combination of laser points in the calibration diagram will draw the structural direction and outline. If two points are adjacent and have a direct mathematical relationship, and the two laser points look correct but the satellite positioning data does not match, then the anomaly of the positioning unit can be detected relatively intuitively and quickly.

[0078] This application also discloses a monitoring and control system applied to the AI ​​intelligent monitoring and control method for deep foundation pit structural cracks as described above.

[0079] The monitoring and control system includes:

[0080] A laser calibrator is used to perform laser pointing and acquire at least one positioning data at multiple project control points and multiple structural sides in the foundation pit.

[0081] The drone is used to acquire calibration indication images of the laser calibrator at a pre-selected location on the deep foundation pit site from an overhead or under-the-head view; and it is also used to carry a scanning radar to scan the site and obtain point cloud data of the deep foundation pit structure surface.

[0082] The data processing platform can be a cloud platform built on a server, connecting the former two to acquire data from laser calibrators, drones, and scanning radar, and performing positioning verification, modeling, structural analysis, and early warning.

[0083] Reference Figure 2 , Figure 3 and Figure 4 The usage of the above components has been described in the method embodiments of this application, so it will not be repeated here. The following mainly explains the laser calibrator, which includes a housing 1 and a gyroscope frame 2, a laser generating module 3 and a positioning unit 4 installed in the housing 1.

[0084] The housing 1 can be made of plastic, is hollow in the shape of a cuboid, and is used in a vertical position; the bottom of the housing 1 is open and the bottom cover is fixed by screws, and a light-transmitting hole is opened at the top of the housing 1, and a transparent plate (glass or acrylic plate) is sealed and fixed inside the light-transmitting hole.

[0085] The laser generating module 3 has at least one beam-emitting section, which is located on the gyroscope frame 2 and counterweighted to ensure that the beam is emitted vertically upwards from the light-transmitting hole. The positioning unit 4 can be a satellite positioning unit such as BeiDou.

[0086] Understandably, as an electronic device, the laser calibrator should have a battery and a power switch installed on its outer wall. Battery power supply is existing technology, so it will not be discussed further.

[0087] According to the above settings, when staff need to measure and locate a certain point, they only need to place the laser calibrator vertically in the corresponding position, start the equipment, and the laser will be emitted vertically upward, which is convenient for staff to observe. Moreover, because the gyroscope mount 2 is set up, it is not affected by slight non-standard placement. At the same time, it can also perform satellite positioning to obtain the satellite positioning data of the point, which can be used as the basis for the aforementioned positioning verification.

[0088] In one embodiment of this application, the gyroscope mount 2 includes an outer notched ring 21, a middle ring body 22, and a rotation axis 23.

[0089] The outer notched ring 21 can be a half-ring or a notched ring structure with more than half of the ring facing upwards, i.e. towards the light-transmitting hole, so as not to interfere with the laser emission; the bottom of the outer notched ring 21 is rotatably connected to a rotating shaft, which is vertical and its lower end is fixed to the housing 1.

[0090] The middle ring 22 is located within the outer notched ring 21 and is rotatably connected to both ends of the outer notched ring 21 on both radially symmetrical sides, meaning that the middle ring 22 can rotate relative to the outer notched ring 21. The rotation shaft 23 is radially arranged within the middle ring 22, rotatably connected, and perpendicular to the rotation center line of the middle ring 22.

[0091] The laser generating module 3 includes a focusing cone 31 as the light-emitting part and a light source unit 32. The focusing cone 31 is fixed to the rotation axis 23 with its bottom facing downwards. It can be understood that the center of gravity of the focusing cone 31 is downwards, and with the gyroscope frame 2 mentioned above, it can always remain vertically upwards after adjusting the balance.

[0092] A vertically connected focusing channel is provided inside the focusing cone 31. The inner wall of the focusing channel can be coated with aluminum, silver or other coatings to increase the reflective and focusing capabilities. The light source unit 32 is fixed to the housing 1, located below the focusing cone 31 and emitting light towards the focusing cone 31. The light source unit 32 is, for example, a laser emitting circuit module.

[0093] Based on the above settings, this application will not have wires or the like extending to the gyroscope frame 2 in order to generate laser light. In this way, the self-balancing focusing cone 31 of the gyroscope frame 2 is relatively undisturbed, and the self-balancing effect is more stable.

[0094] Understandably, based on the above configuration, there is an interference problem between the rotation axis of the outer notch ring 21 and the position of the light source unit 32. Therefore, the rotation axis of the outer notch ring 21 is a hollow tube structure, and the light source unit 32 is connected to the housing 1 on its inner side by means of a support platform or other structures.

[0095] In another embodiment of this application, the laser generating module 3 further includes a convex lens 33, which is fixed below the focusing cone 31 by a bracket and located between the focusing cone 31 and the light source unit 32; at the same time, the lower end of the focusing channel is concave and convex.

[0096] According to the above settings, when the housing 1, i.e. the light source unit 32, deflects slightly relative to the focusing cone 31, the laser can still be guaranteed to enter the focusing channel smoothly and be emitted upwards due to the refraction of light by the convex lens 33; the expansion of the lower end of the focusing channel can make the above-mentioned allowable deflection range larger.

[0097] Understandably, the diameter of the focusing channel can gradually increase from bottom to top, similar to a reflector bowl, to enhance the focusing effect.

[0098] In another embodiment of this application, the sidewall of the housing 1 is fixed with screws to an adhesive groove 11 for filling an adhesive structure, and / or the bottom is provided with a socket for connecting a support column.

[0099] Taking both as an example:

[0100] In the first method, when using the adhesive, the staff first fills the adhesive tank 11 with viscous adhesive blocks until they overflow the tank opening, similar to the effect of tape. At this time, the shell 1 can be fixed to the side wall of the deep foundation pit structure that is high off the ground, suspended, and where it is inconvenient to place support columns below by adhesive. After calibration, simply peel off a layer and replace the adhesive block.

[0101] The second method involves the worker first inserting a support column of a suitable diameter into the bottom of the shell 1, and then inserting the support column into the soil and fixing it on the ground to support the shell 1 placed on the edge of the deep foundation pit structure.

[0102] Based on the above setup, staff can conveniently and flexibly fix the laser calibrator in various locations for use, thus improving the effectiveness of the laser calibrator.

[0103] In another embodiment of this application, the laser calibrator also includes a wireless communication module 5, such as a Wi-Fi module or an NB-IoT module, which is installed in the housing 1 and is at least electrically connected to the positioning unit 4. This allows staff to remotely obtain satellite positioning data during laser calibrator calibration via mobile phones or other terminals, making the laser calibrator more flexible in use.

[0104] In another embodiment of this application, the laser calibrator further includes a microcontroller 6, which is electrically connected to the light source unit 32 and the wireless communication module 5. The microcontroller 6 is configured as follows:

[0105] Obtain the identification code of the current laser calibrator, such as a pre-stored or pre-assigned number;

[0106] The optical signal characteristics of the current laser calibrator are obtained based on preset identification code parsing rules; wherein, the optical signal characteristics include at least the light frequency and period; the identification code parsing rules are manually defined, for example:

[0107] The identification code consists of three sets of values. Looking at the deep foundation pit from above, the first set indicates the position within the same row, the second set indicates the position within the same column, and the third set indicates the position within the same vertical column. The rules could be:

[0108] If the first group is an odd number, the laser will remain lit for 3 seconds per cycle; if it is an even number, the laser will remain lit for 5 seconds per cycle.

[0109] The second set of values ​​represents the number of times the laser cycled on and off;

[0110] The third set of values ​​represents the interval between one complete cycle and the next cycle. Value 1 represents 7 seconds, 2 represents 8 seconds, and so on.

[0111] Subsequently, the operation of the light source unit 32 is controlled based on the characteristics of the optical signal, that is, the laser is controlled to work according to a certain frequency and on / off cycle.

[0112] Based on the above setup, when multiple laser calibrators are used together, staff can remotely observe the on / off state of each laser to infer its approximate location and the status of nearby laser calibrators, which facilitates overall planning and verification. Moreover, the effect is even better when drones are used to capture the video, which is then imported into a computer system and image recognition technology is introduced.

[0113] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for AI-powered intelligent monitoring and control of cracks in deep foundation pit structures, characterized in that, Includes the following steps: S1. Measurement and positioning, which includes: acquiring the characteristic data of the project control points and the edge lines of the foundation pit structure on the working face, and performing positioning verification based on the positioning data of the positioning system; S2. UAV scanning, which includes: based on measurement and positioning data, guiding the UAV to move on the deep foundation pit site, and scanning the site with a pre-loaded scanning radar to obtain point cloud data of the deep foundation pit structure surface; S3. Modeling, which includes: modeling based on point cloud data, and identifying structural change features based on the model and annotating feature attributes; S4. Structural analysis and early warning, which includes: outputting structural anomaly alerts based on labeled information, and recording structural change information based on time series for structural evolution analysis and prediction.

2. The AI-based intelligent monitoring and control method for cracks in deep foundation pit structures according to claim 1, characterized in that, The location verification includes: Establish a laser calibrator integrated with a positioning unit (4); wherein the laser calibrator can emit laser light vertically upward at least; The laser calibrator is used to perform laser pointing and obtain positioning data at multiple project control points and multiple structural sides in the foundation pit; At a pre-selected point on the deep foundation pit site, obtain the calibration indication image of the laser calibrator during calibration from an overhead or upward perspective; Multiple calibration indicator images are subjected to layer unification and overlay processing to obtain a global calibration indicator image; The positioning data from each laser calibrator during its previous calibrations are marked on the global calibration indicator diagram. Based on the global calibration indicator diagram, the parameters are verified in conjunction with the construction project drawings.

3. A monitoring and control system applied to the AI ​​intelligent monitoring and control method for deep foundation pit structural cracks as described in claim 2, characterized in that, include: A laser calibrator is used to perform laser pointing and acquire at least one positioning data at multiple project control points and multiple structural sides in the foundation pit. The drone is used to acquire calibration indication images of the laser calibrator at a pre-selected location on the deep foundation pit site from an overhead or under-the-head view; and it is also used to carry a scanning radar to scan the site and obtain point cloud data of the deep foundation pit structure surface. The data processing platform is used to acquire data from laser calibrators, drones, and scanning radars, and to perform positioning verification, modeling, structural analysis, and early warning.

4. The monitoring and control system according to claim 3, characterized in that: The laser calibrator includes a housing (1) and a gyroscope frame (2), a laser generating module (3) and a positioning unit (4) installed in the housing (1). The housing (1) has a light-transmitting hole that communicates with the inner cavity. The light-transmitting hole is closed with a transparent plate. The laser generating module (3) has at least one light-emitting part. The light-emitting part is located on the gyroscope frame (2) and is counterweighted so that it emits light vertically upward from the light-transmitting hole.

5. The monitoring and control system according to claim 4, characterized in that: The gyroscope frame (2) includes an outer notch ring (21), a middle ring body (22) and a rotating shaft (23). The outer notch ring (21) has an opening facing the light-transmitting hole and a rotating shaft rotatably connected to the surface away from the opening. The rotating shaft is fixedly connected to the housing (1). The middle ring (22) is built into the notched ring and is rotatably connected to both ends of the outer notched ring (21) on both sides of radial symmetry. The rotating shaft (23) is radially arranged in the middle ring (22), rotatably connected and perpendicular to the rotation center line of the middle ring (22). The laser generating module (3) includes a focusing cone (31) as the light-emitting part and a light source unit (32). The focusing cone (31) is fixed to the rotating shaft (23) with the bottom of the cone facing down. A focusing channel that runs vertically through the focusing cone (31) is opened inside the focusing cone (31). The light source unit (32) is fixed to the housing (1), located below the focusing cone (31) and emitting light towards the focusing cone (31).

6. The monitoring and control system according to claim 5, characterized in that: The laser generating module (3) also includes a convex lens (33), which is fixed below the focusing cone (31) and located between the focusing cone (31) and the light source unit (32). The lower end of the focusing channel is concave and convex.

7. The monitoring and control system according to claim 4, characterized in that: The housing (1) has an adhesive groove (11) fixed on its side wall for filling the adhesive structure, and / or a socket for connecting the support column is provided at the bottom.

8. The monitoring and control system according to claim 4, characterized in that: The laser calibrator also includes a wireless communication module (5), which is at least electrically connected to the positioning unit (4).

9. The monitoring and control system according to claim 8, characterized in that: The laser calibrator further includes a microcontroller (6), which is electrically connected to the light source unit (32) and the wireless communication module (5). The microcontroller (6) is configured as follows: Obtain the identification code of the current laser calibrator; The optical signal characteristics of the current laser calibrator are obtained based on the preset identification code parsing rules; The operation of the light source unit (32) is controlled based on the characteristics of the optical signal; The optical signal characteristics include at least the light frequency and period.

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