Structure safety risk early warning method based on space-air-ground integrated remote sensing network

Abstract

The invention discloses a structure safety risk early warning method based on a space-air-ground integrated remote sensing network, relates to the technical field of remote sensing monitoring, and effectively improves the accuracy of multi-source remote sensing data fusion. According to the invention, real-time horizontal construction videos and real-time laser signal frequency spectrums of all structures are collected through an unmanned aerial vehicle along a flight route of the unmanned aerial vehicle, and laser signal frequency spectrums of all structures in horizontal and vertical directions are collected through a ground detection device; establishing a real-time construction progress model of each structure according to the real-time horizontal construction video and the real-time laser signal spectrum, dividing a plurality of unit structure areas in the real-time construction progress model, and rendering each unit structure area through the laser signal spectrum of the structure in the horizontal and vertical directions, and mapping each unit structure region into the target scene image model according to a rendering result, and further judging whether the current construction progress of each structure has a construction risk or not.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing monitoring technology, and in particular to a structure safety risk early warning method based on an air-space-ground integrated remote sensing network. Background Art

[0002] With the acceleration of urbanization and the continuous expansion of infrastructure construction, the safety of structures (such as buildings, bridges, tunnels, etc.) has received increasing attention. Traditional methods of monitoring the safety of structures mainly rely on manual inspections and regular testing, which is not only inefficient but also difficult to cover all potential risk points. In recent years, with the development of remote sensing technology, the integrated space-air-ground remote sensing network has gradually become an emerging means of monitoring the safety of structures. The integrated space-air-ground remote sensing network uses a variety of remote sensing platforms such as satellites, drones, and ground sensors to achieve all-round, multi-angle real-time monitoring of structures, provide data support with high temporal and spatial resolution, and effectively improve the safety early warning capabilities of structures.

[0003] The existing monitoring of construction of structures through remote sensing technology has the following defects:

[0004] Accuracy of remote sensing data: High-precision remote sensing data is the key to ensuring the accuracy of early warning. However, due to factors such as sensor performance and environmental conditions, existing technologies may have certain errors in some cases.

[0005] Data fusion: The integrated air-space-ground network involves multiple data sources (such as satellites, drones, and ground sensors). How to efficiently and accurately integrate these data to form a unified risk assessment model still needs further optimization.

[0006] Therefore, how to efficiently and accurately integrate multi-source remote sensing data while improving the credibility of remote sensing data is a difficulty in the existing technology. For this purpose, a structure safety risk early warning method based on an integrated air-space-ground remote sensing network is provided. Summary of the invention

[0007] In order to solve the above technical problems, the purpose of the present invention is to provide a structure safety risk early warning method based on an integrated air-space-ground remote sensing network.

[0008] In order to achieve the above object, the present invention provides the following technical solutions:

[0009] The structure safety risk early warning method based on the integrated air-space-ground remote sensing network includes the following steps:

[0010] Step S1, collecting vertical image data of the target construction site in an initial state through satellite remote sensing technology, and establishing a target scene image model based on the vertical image data in the initial state, planning a UAV flight route on the target scene image model according to a preset structure construction plan, and marking a number of ground detection positions;

[0011] Step S2: installing several ground detection devices on the target construction site according to the target scene image model, and then collecting the real-time horizontal construction video and real-time laser signal spectrum of each structure along the flight route of the drone, and collecting the laser signal spectrum of each structure in the horizontal and vertical directions through the ground detection device;

[0012] Step S3, a real-time construction progress model of each structure is established according to the real-time horizontal construction video and the real-time laser signal spectrum, a number of unit structure areas are divided in the real-time construction progress model, and each unit structure area is rendered by the laser signal spectrum of the structure in the horizontal and vertical directions, and each unit structure area is mapped in the target scene image model according to the rendering result, so as to judge whether there is a construction risk in the current construction progress of each structure until the construction of all structures is completed.

[0013] Furthermore, the process of establishing the target scene image model includes:

[0014] The satellite collects optical image data and pulse signal spectrum of the target construction site in the non-construction state, performs grayscale processing on the optical image data, and obtains the pixel value of each pixel in the optical image data according to the grayscale processing result. Each pixel is taken as the center, and then each pixel and its surrounding pixels are blurred, and a pixel difference threshold is set;

[0015] Determine whether the pixel difference between adjacent pixels after pixel blurring is greater than or equal to a pixel difference threshold, set the same label for two adjacent pixels according to the determination result, integrate the pixels with the same label, and then mark several pixel-related areas in the optical image data according to the integration result;

[0016] A three-dimensional image model of the target construction site is established according to the pulse signal spectrum, and the optical image data is mapped to the three-dimensional image model of the site, thereby obtaining a target scene image model corresponding to the target construction site.

[0017] Furthermore, the process of establishing the UAV flight route includes:

[0018] The construction plan of the structure records N three-dimensional models of the structures to be constructed, and the three-dimensional models of the structures are annotated with the construction location, height, floor area and structural appearance pattern of the corresponding structures, where N is a natural number greater than 0;

[0019] Then, according to the construction positions of each structure recorded in the construction plan of the structure, it is judged whether the construction positions of each structure have a concave-convex state at the corresponding position of the target scene image model, and according to the judgment result, the three-dimensional model of the structure is inlaid in the target scene image model in proportion, and then according to the distribution of the three-dimensional model of the structure in the target scene image model, a number of UAV flight routes are set, and ground detection positions are respectively set for the locations of the target scene image model;

[0020] The unit flight speed and periodic inspection time are set, and then several UAV models are set to perform flight simulation in the target scene image model along the UAV flight route according to the unit flight speed. The flight route of each UAV is adjusted according to the flight simulation results, so that within the periodic inspection time, there are UAV models passing around the three-dimensional model of each structure, and there is no collision between the UAV models.

[0021] Furthermore, the acquisition process of the real-time horizontal construction video and the real-time laser signal spectrum of the structure includes:

[0022] According to the ground detection positions marked by the target scene image model, ground detection devices are installed at corresponding positions of the target construction site, and each ground detection device is numbered;

[0023] Each ground detection device is composed of four groups of data acquisition units, each of which is composed of a laser inclinometer and a laser sensor. When construction workers carry out construction at the target construction site according to the construction plan of the structure, several drones are set to fly in the target construction site according to the number of drone flight routes. The drones are equipped with high-resolution cameras and laser radars, and the high-resolution cameras and laser radars are set with the same data acquisition range;

[0024] When the UAV flies along its flight route, it uses high-resolution cameras and lidar to collect real-time horizontal construction videos and real-time laser signal spectra of the structures within its data collection range, and marks the two with the numbers of the ground detection devices associated with the corresponding structures.

[0025] Furthermore, each data acquisition unit transmits laser signals vertically upward and horizontally along the structure through a laser inclinometer and a laser sensor to obtain laser signal spectra of the corresponding structure in the horizontal and vertical directions.

[0026] Furthermore, the process of establishing the real-time construction progress model includes:

[0027] A real-time appearance image model of each structure is established according to the real-time horizontal construction video, and a real-time internal structure image model is established according to the real-time laser signal spectrum, and a plurality of two-dimensional model areas of the same size are respectively set on the surface of the real-time appearance image model and the real-time internal structure image model, and the total pixel value of each two-dimensional model area is obtained;

[0028] The real-time horizontal construction video and the real-time laser signal spectrum with the same number are used to generate overlapping mappings of the real-time appearance image model and the real-time internal structure image model, and a total value difference threshold is set;

[0029] Then, the relationship between the total pixel value difference of the two-dimensional model area at the same position of the real-time appearance image model and the real-time internal structure image model and the total value difference threshold is determined;

[0030] Based on the judgment results, the two-dimensional model areas of the corresponding positions from different image models are overlapped and fused to obtain the real-time construction progress model of each structure, and each real-time construction progress model is labeled with a corresponding number according to the number of the corresponding ground detection device of each structure.

[0031] Furthermore, the process of rendering the unit structure area includes:

[0032] A process of dividing a number of unit structure areas in a real-time construction progress model and dividing pixel-related areas according to optical image data, rendering each unit structure area according to the laser signal spectrum in the horizontal and vertical directions, and marking a number of cracks or patterns on the surface of each unit structure area according to the rendering results;

[0033] At the same time, according to the division process of the unit structure area, a number of detection unit structure areas are divided in the three-dimensional model of each structure. When all the unit structure areas are rendered, each unit structure area is overlapped and mapped with the detection unit structure area of ​​the corresponding structure.

[0034] Furthermore, it is determined whether the current construction results of each structure have deviations in vertical and directional directions, whether there are cracks, or whether the pattern is the same as that recorded in the three-dimensional model of the structure. According to the judgment results and the position of the corresponding real-time construction progress model of the unit structure area, the structure repair decision is generated and executed.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention uses a drone to collect real-time horizontal construction videos and real-time laser signal spectra of various structures along the flight route of the drone, and uses a ground detection device to collect laser signal spectra of various structures in horizontal and vertical directions. A real-time construction progress model of each structure is established according to the real-time horizontal construction video and the real-time laser signal spectrum, a plurality of unit structure areas are divided in the real-time construction progress model, and each unit structure area is rendered by the laser signal spectrum of the structure in the horizontal and vertical directions. Each unit structure area is mapped into a target scene image model according to the rendering result, and then it is judged whether there is a construction risk in the current construction progress of each structure, thereby realizing efficient and accurate fusion of multi-source remote sensing data while improving the credibility of remote sensing data. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention.

[0038] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0039] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0040] Example 1

[0041] like Figure 1 As shown, the structure safety risk early warning method based on the integrated air-space-ground remote sensing network includes the following steps:

[0042] Step S1, collecting vertical image data of the target construction site in an initial state through satellite remote sensing technology, and establishing a target scene image model based on the vertical image data in the initial state, planning a UAV flight route on the target scene image model according to a preset structure construction plan, and marking a number of ground detection positions;

[0043] Step S2: installing several ground detection devices on the target construction site according to the target scene image model, and then collecting the real-time horizontal construction video and real-time laser signal spectrum of each structure along the flight route of the drone, and collecting the laser signal spectrum of each structure in the horizontal and vertical directions through the ground detection device;

[0044] Step S3, a real-time construction progress model of each structure is established according to the real-time horizontal construction video and the real-time laser signal spectrum, a number of unit structure areas are divided in the real-time construction progress model, and each unit structure area is rendered by the laser signal spectrum of the structure in the horizontal and vertical directions, and each unit structure area is mapped in the target scene image model according to the rendering result, so as to judge whether there is a construction risk in the current construction progress of each structure until the construction of all structures is completed.

[0045] Example 2

[0046] This embodiment is a further limitation of Embodiment 1, and Step S1 is implemented by the following process:

[0047] Several signal interaction devices are set up at the edge of the target construction site, and then the satellite locates the geographical location of the target construction site through the communication results with each signal interaction device;

[0048] The satellite is provided with an optical camera and a synthetic aperture radar, and the satellite collects optical image data and pulse signal spectrum of the target construction site in a non-construction state through the optical camera and the synthetic aperture radar;

[0049] Grayscale processing is performed on the optical image data, and a pixel value of each pixel in the optical image data is obtained according to the grayscale processing result, and each pixel is taken as the center in turn, and then each pixel and its surrounding pixels are pixel-blurred, and a pixel difference threshold is set;

[0050] Determine whether the pixel difference between each adjacent pixel after pixel blurring is greater than or equal to the pixel difference threshold. If the pixel difference is less than the pixel difference threshold, set the same label for the corresponding two adjacent pixels.

[0051] If the pixel difference is greater than or equal to the pixel difference threshold, no operation is performed;

[0052] Integrate pixels with the same label, and then mark several pixel-related regions in the optical image data according to the integration result;

[0053] Since there are potholes and other terrain on the surface of the target construction site, the surface of the target construction site is irregular from the perspective of the satellite. Therefore, after the satellite sends a pulse signal to the target construction site through the synthetic aperture radar, the pulse signal spectrum generated by the reflection of the target construction site can reflect the concave and convex state of the surface of the construction site.

[0054] Then, a three-dimensional image model of the target construction site is established according to the pulse signal spectrum. Since the optical image data and the pulse signal spectrum are generated corresponding to the same target construction site, the three-dimensional image model of the site generated according to the pulse signal spectrum is in a one-to-one correspondence with the pixel-related area in the optical image data.

[0055] The optical image data is then mapped to the three-dimensional image model of the site, so that the pixel-related areas in the optical image data correspond one-to-one to the concave and convex areas in the three-dimensional image model of the scene, thereby obtaining a target scene image model corresponding to the target construction site.

[0056] Furthermore, the construction plan of the structure records N three-dimensional models of the structures to be constructed, and the three-dimensional models of the structures are annotated with the construction location, height, floor area and structural appearance pattern of the corresponding structures, where N is a natural number greater than 0;

[0057] For example, the main structure may be load-bearing walls and beams, and the external decoration may be, for example, the roof and exterior walls;

[0058] Then, according to the construction positions of each structure recorded in the construction plan, it is determined whether the construction positions of each structure are concave or convex at the corresponding positions of the target scene image model. If so, a corresponding scene correction plan is generated and executed by the construction personnel. After the scene correction plan is executed, the target scene image model is updated synchronously.

[0059] If it does not exist, the three-dimensional model of the structure is inlaid in the target scene image model in proportion, and then according to the distribution of the three-dimensional model of the structure in the target scene image model, a number of UAV flight routes are set, and ground detection positions are set for the locations of the target scene image model;

[0060] The unit flight speed and periodic inspection time are set, and then several UAV models are set to perform flight simulation in the target scene image model along the UAV flight route at the unit flight speed. The flight route of each UAV is adjusted according to the flight simulation results, so that within the periodic inspection time, there are UAV models passing around the three-dimensional model of each structure, and there is no collision between the UAV models.

[0061] Example 3

[0062] This embodiment is a further limitation of Embodiment 1, and Step S2 is implemented by the following process:

[0063] According to the ground detection positions marked by the target scene image model, ground detection devices are installed at the corresponding positions of the target construction site, and each ground detection device is numbered a1, a2, a3, ..., a N ;

[0064] It should be noted that each ground detection device is composed of four groups of data acquisition units, and each data acquisition unit is distributed around the target construction site corresponding to each three-dimensional model of the structure, and the data acquisition unit is composed of a laser inclinometer and a laser sensor;

[0065] When construction workers are carrying out construction at the target construction site according to the construction plan of the structure, a number of drones are set to fly in the target construction site according to the number of drone flight routes, and the drones are provided with high-resolution cameras and laser radars, and the high-resolution cameras and laser radars are set with the same data collection range;

[0066] When the UAV flies along the flight route, it collects real-time horizontal construction video and real-time laser signal spectrum of the structures within its data collection range through high-resolution cameras and laser radars, and marks the numbers of the ground detection devices associated with the corresponding structures on both.

[0067] At the same time, each data acquisition unit transmits laser signals vertically upward and horizontally along the structure through a laser inclinometer and a laser sensor to obtain the laser signal spectrum of the corresponding structure in the horizontal and vertical directions.

[0068] Example 4

[0069] This embodiment is a further limitation of Embodiment 1, and step S3 is implemented by the following process:

[0070] A real-time appearance image model of each structure is established according to the real-time horizontal construction video, and a real-time internal structure image model is established according to the real-time laser signal spectrum, and a plurality of two-dimensional model areas of the same size are respectively set on the surface of the real-time appearance image model and the real-time internal structure image model, and the total pixel value of each two-dimensional model area is obtained;

[0071] Since the real-time horizontal construction video and real-time laser signal spectrum corresponding to each real-time appearance image model and real-time internal structure image model are generated simultaneously, and the two correspond to the same structure, there must be a correlation between the real-time appearance image model and the real-time internal structure image model;

[0072] The real-time horizontal construction video and the real-time laser signal spectrum with the same number are used to generate overlapping mappings of the real-time appearance image model and the real-time internal structure image model, and a total value difference threshold is set;

[0073] Then, the relationship between the total pixel value difference of the two-dimensional model area at the same position of the real-time appearance image model and the real-time internal structure image model and the total value difference threshold is determined;

[0074] If the total pixel value difference is greater than the total value difference, there is a difference between the real-time appearance image model and the real-time internal structure image model at the corresponding position, and no operation is performed;

[0075] If the total pixel value difference is less than or equal to the total value difference, the two-dimensional model regions from different image models at the corresponding positions are overlapped and fused;

[0076] Repeat the above-mentioned process of overlapping and fusing the two-dimensional model regions to obtain the real-time construction progress model of each structure, and mark each real-time construction progress model with a corresponding number according to the number of the ground detection device corresponding to each structure.

[0077] Furthermore, several unit structural areas are divided in the real-time construction progress model. At the same time, according to the laser signal spectrum of each structure in the horizontal and vertical directions, as the structure progresses continuously, the laser signal spectrum generated by the laser inclinometer and laser sensor in the vertical and horizontal states will also change accordingly;

[0078] For example, when a laser signal spectrum is generated in the vertical direction, as the construction progress of the structure changes, the structure will have different degrees of concavity or convexity in the vertical direction, causing the laser signal spectrum generated by the laser signal passing through the corresponding position to change to different degrees. Similarly, the laser spectrum generated in the horizontal reverse direction also has the same situation.

[0079] The process of dividing pixel-related regions according to optical image data, and then rendering each unit structure region according to the laser signal spectrum in the horizontal and vertical directions, and marking a number of cracks or patterns on the surface of each unit structure region according to the rendering results;

[0080] If there are two-dimensional model areas on the surface of the unit structure area that are not overlapped and fused, the two two-dimensional model areas that are not overlapped and fused are rendered according to the laser signal spectrum in the horizontal direction, and then it is re-determined whether the total pixel value difference of the two-dimensional model area at the corresponding position is less than or equal to the total value difference threshold. If so, the two-dimensional model areas from different image models at the corresponding position are overlapped and fused;

[0081] If it is not true, the real-time horizontal construction video and real-time laser signal spectrum of the corresponding structure are collected again to generate a real-time construction progress model;

[0082] According to the division process of unit structure area, several detection unit structure areas are divided in the three-dimensional model of each structure;

[0083] When all unit structure areas are rendered, each unit structure area is overlapped and mapped with the detection unit structure area of ​​the corresponding structure;

[0084] Then, it is determined whether the current construction results of each structure have deviations in verticality and direction, and whether there are cracks, or whether the pattern is the same as that recorded in the three-dimensional model of the structure;

[0085] If any of the two judgment results is established, it is judged that the current construction result of the corresponding structure is at risk, and a structure repair decision is generated and executed according to the position of the unit structure area in the corresponding real-time construction progress model;

[0086] If both judgment results are not established, no operation is performed and the above judgment process is repeated until the construction of all structures is completed.

[0087] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A structure safety risk early warning method based on an integrated air-space-ground remote sensing network, characterized in that: The following steps are involved: Step S1, collecting vertical image data of the target construction site in an initial state through satellite remote sensing technology, and establishing a target scene image model based on the vertical image data in the initial state, planning a UAV flight route on the target scene image model according to a preset structure construction plan, and marking a number of ground detection positions; Step S2: installing several ground detection devices on the target construction site according to the target scene image model, and then collecting the real-time horizontal construction video and real-time laser signal spectrum of each structure along the flight route of the drone, and collecting the laser signal spectrum of each structure in the horizontal and vertical directions through the ground detection device; Step S3, a real-time construction progress model of each structure is established according to the real-time horizontal construction video and the real-time laser signal spectrum, a number of unit structure areas are divided in the real-time construction progress model, and each unit structure area is rendered by the laser signal spectrum of the structure in the horizontal and vertical directions, and each unit structure area is mapped in the target scene image model according to the rendering result, so as to judge whether there is a construction risk in the current construction progress of each structure until the construction of all structures is completed.

2. The structure safety risk early warning method based on the integrated air-space-ground remote sensing network according to claim 1 is characterized in that: The process of establishing the target scene image model includes: The satellite collects optical image data and pulse signal spectrum of the target construction site in the non-construction state, performs grayscale processing on the optical image data, and obtains the pixel value of each pixel in the optical image data according to the grayscale processing result. Each pixel is taken as the center, and then each pixel and its surrounding pixels are blurred, and a pixel difference threshold is set; Determine whether the pixel difference between adjacent pixels after pixel blurring is greater than or equal to a pixel difference threshold, set the same label for two adjacent pixels according to the determination result, integrate the pixels with the same label, and then mark several pixel-related areas in the optical image data according to the integration result; A three-dimensional image model of the target construction site is established according to the pulse signal spectrum, and the optical image data is mapped to the three-dimensional image model to obtain a target scene image model of the target construction site.

3. The structure safety risk early warning method based on the integrated air-ground-space remote sensing network according to claim 2 is characterized in that: The process of establishing the UAV flight route includes: The construction plan of the structure records N three-dimensional models of the structures to be constructed, and the three-dimensional models of the structures are annotated with the construction location, height, floor area and structural appearance pattern of the corresponding structures, where N is a natural number greater than 0; Then, according to the construction positions of each structure recorded in the construction plan of the structure, it is judged whether the construction positions of each structure have a concave-convex state at the corresponding position of the target scene image model, and according to the judgment result, the three-dimensional model of the structure is inlaid in the target scene image model in proportion, and then according to the distribution of the three-dimensional model of the structure in the target scene image model, a number of UAV flight routes are set, and ground detection positions are respectively set for the locations of the target scene image model; The unit flight speed and periodic inspection time are set, and then several UAV models are set to perform flight simulation in the target scene image model along the UAV flight route according to the unit flight speed. The flight route of each UAV is adjusted according to the flight simulation results, so that within the periodic inspection time, there are UAV models passing around the three-dimensional model of each structure, and there is no collision between the UAV models.

4. The structure safety risk early warning method based on the integrated air-space-ground remote sensing network according to claim 3 is characterized in that: The acquisition process of the real-time horizontal construction video and real-time laser signal spectrum of the structure includes: According to the ground detection positions marked by the target scene image model, ground detection devices are installed at corresponding positions of the target construction site, and each ground detection device is numbered; Each ground detection device is composed of four groups of data acquisition units, each of which is composed of a laser inclinometer and a laser sensor. When construction workers carry out construction at the target construction site according to the construction plan of the structure, several drones are set to fly in the target construction site according to the number of drone flight routes. The drones are equipped with high-resolution cameras and laser radars, and the high-resolution cameras and laser radars are set with the same data acquisition range; When the UAV flies along its flight route, it uses high-resolution cameras and lidar to collect real-time horizontal construction videos and real-time laser signal spectra of the structures within its data collection range, and marks the two with the numbers of the ground detection devices associated with the corresponding structures.

5. The structure safety risk early warning method based on the integrated air-ground-space remote sensing network according to claim 4 is characterized in that: Each data acquisition unit transmits laser signals vertically upward and horizontally along the structure through a laser inclinometer and a laser sensor to obtain the laser signal spectrum of the corresponding structure in the horizontal and vertical directions.

6. The structure safety risk early warning method based on the integrated air-ground-space remote sensing network according to claim 5 is characterized in that: The process of establishing the real-time construction progress model includes: A real-time appearance image model of each structure is established according to the real-time horizontal construction video, and a real-time internal structure image model is established according to the real-time laser signal spectrum, and a plurality of two-dimensional model areas of the same size are respectively set on the surface of the real-time appearance image model and the real-time internal structure image model, and the total pixel value of each two-dimensional model area is obtained; The real-time horizontal construction video and the real-time laser signal spectrum with the same number are used to generate overlapping mappings of the real-time appearance image model and the real-time internal structure image model, and a total value difference threshold is set; Then, the relationship between the total pixel value difference of the two-dimensional model area at the same position of the real-time appearance image model and the real-time internal structure image model and the total value difference threshold is determined; Based on the judgment results, the two-dimensional model areas of the corresponding positions from different image models are overlapped and fused to obtain the real-time construction progress model of each structure, and each real-time construction progress model is labeled with a corresponding number according to the number of the corresponding ground detection device of each structure.

7. The structure safety risk early warning method based on the integrated air-ground-space remote sensing network according to claim 6 is characterized in that: The process of rendering the unit structure area includes: A process of dividing a number of unit structure areas in a real-time construction progress model and dividing pixel-related areas according to optical image data, rendering each unit structure area according to the laser signal spectrum in the horizontal and vertical directions, and marking a number of cracks or patterns on the surface of each unit structure area according to the rendering results; At the same time, according to the division process of the unit structure area, several detection unit structure areas are divided in the three-dimensional model of each structure. When all the unit structure areas are rendered, each unit structure area is overlapped and mapped with the detection unit structure area of ​​the corresponding structure.

8. The structure safety risk early warning method based on the integrated air-ground-space remote sensing network according to claim 7 is characterized in that: Determine whether the current construction results of each structure have deviations in verticality and direction, whether there are cracks, or whether the pattern is the same as that recorded in the three-dimensional model of the structure. Generate and execute structure repair decisions based on the judgment results and the position of the corresponding real-time construction progress model of the unit structure area.

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