A method and equipment for testing the bearing capacity of newly filled sites

Abstract

The present invention discloses a method and equipment for testing the bearing capacity of recently reclaimed land. The method comprises: using an unmanned aerial vehicle (UAV) to map the land and obtain a digital elevation model (DEM) of the land; setting a number of detection points on the land based on the DEM, and using a UAV to measure soil layer data at each detection point using a detector; calculating the bearing capacity of each detection point based on the soil layer data, and generating a bearing capacity distribution map based on the bearing capacity of each detection point. The present invention uses a UAV to map the land and, based on the mapping results, uses the UAV-mounted detection equipment to measure the bearing capacity of the land. This method addresses the low efficiency and high safety risks of existing methods for measuring the bearing capacity of recently reclaimed land.

Description

Technical Field

[0001] The present invention relates to the technical field of geotechnical engineering investigation, and in particular to a method and equipment for testing the bearing capacity of a newly filled site. Background Art

[0002] Land reclamation and artificial island dredging and filling projects often result in a "mud soup" of fill interlaced with the original soft soil. While the original soft soil has a high moisture content, its bearing capacity is still sufficient to support mechanical construction. However, the ultra-soft soil formed by recent fill, after hydraulic reshaping and particle re-sorting, has not yet completed its self-weight consolidation. It contains high levels of clay and strongly hydrophilic minerals, a loose structure, and extremely high moisture content, resulting in extremely poor engineering properties and near-zero foundation bearing capacity. Therefore, the fill site requires rapid shallow surface reinforcement to form a hard crust layer, allowing for the entry of construction equipment.

[0003] In the early stages, the ultra-soft soil areas need to be separated from the soft soil areas based on their bearing capacity, and only the ultra-soft soil areas will be reinforced with shallow vacuum preloading. Traditional bearing capacity testing relies heavily on manual surveys, which is not only inefficient but also poses high safety risks. Summary of the Invention

[0004] To solve the above problems, the present invention provides a method and equipment for testing the bearing capacity of recently filled sites. The filled sites are surveyed by drones, and the bearing capacity of the site is measured using detection equipment mounted on the drones based on the surveying results. This solves the problems of low efficiency and high safety risks of existing methods for surveying the bearing capacity of recently filled sites.

[0005] To achieve the above objectives, the present invention provides the following technical solutions:

[0006] A method for testing the bearing capacity of a newly filled site comprises the following steps:

[0007] S1. Use a drone to survey the site and obtain a digital elevation model of the site;

[0008] S2. Set up several inspection points on the site based on the site digital elevation model, and use the drone to measure the soil layer data at each inspection point on the site;

[0009] S3. Calculate the bearing capacity of each detection point based on the soil layer data of each detection point, and generate a bearing capacity distribution map based on the bearing capacity of each detection point.

[0010] Furthermore, in step S1, the drone surveys and maps the site, which is specifically implemented as follows:

[0011] Several control points are evenly distributed in the field. For each control point, the UAV flies to the control point and collects the vertical distance between the control point and the UAV and the vertical coordinate of the UAV. The absolute elevation of the control point is calculated based on the vertical distance and the vertical coordinate of the UAV. The absolute elevation of the i-th control point is The calculation formula is:

[0012] ,in, is the error correction value, i represents the i-th control point, It represents the vertical distance between the UAV and the i-th control point when the UAV navigates to the i-th control point. It is the ordinate coordinate of the UAV when it navigates to the i-th control point. The absolute elevation of all control points is obtained, and the digital elevation model of the site is generated using the spatial interpolation method based on the absolute elevation of each control point.

[0013] Furthermore, the number of control points is arranged according to the site area, with 2 Place at least one control point.

[0014] Furthermore, in step S2, the drone measures the soil layer data of each detection point on the site through the detector. The specific implementation method is: for each detection point, the drone navigates to the detection point, controls the detector to penetrate the soil layer, and the detector collects the penetration depth, cone tip resistance and side wall friction resistance in real time, and records the plane coordinates of the drone at this time.

[0015] Furthermore, the detector is a miniature static penetration instrument.

[0016] Furthermore, in step S3, the bearing capacity of each detection point is calculated based on the soil layer data of each detection point, and the specific implementation method is as follows:

[0017] When the detector is a micro static penetration tester, the calculation formula for the bearing capacity of the detection point is:

[0018]

[0019] in, is the bearing capacity at the jth detection point, k is the empirical coefficient, is the cone tip resistance at the jth detection point.

[0020] Furthermore, the detector is a test element, and when measuring soil layer data at each test point, the vertical distance between the drone and the test point is kept fixed. , the drone releases the test element, and the test element collects soil layer data.

[0021] Furthermore, when the detector is a test element, the bearing capacity of the test point is calculated as follows:

[0022] The calculation formula for shear strength is:

[0023]

[0024] in, is the shear strength at the detection point j, is the penetration depth of the test element at the detection point j, K is the empirical coefficient of shear strength, m is the mass of the test element, g is the acceleration of gravity, and A is the bottom area of ​​the test element;

[0025] The bearing capacity of the detection point j is calculated according to the following formula:

[0026]

[0027] in, is the shear strength at the detection point j, c is the cohesion of the soil, is the vertical compressive stress, is the internal friction angle, 、 is the bearing capacity parameter, is the bearing capacity at detection point j.

[0028] Furthermore, in step S3, the bearing capacity distribution map is generated according to the bearing capacity of each detection point, and its specific implementation method is: according to the bearing capacity of each detection point in the site digital elevation model, the foundation bearing capacity contour map is generated using the Kriging interpolation method.

[0029] Through the above technical solution, the present invention has the following beneficial effects: the present invention adopts a drone as a carrying platform, which can achieve rapid maneuvering and precise positioning, greatly shortening the transfer time between test points, thereby significantly improving the overall test efficiency, and utilizing a miniature static penetration instrument, the device can collect and transmit key parameters such as the cone tip resistance and side wall friction resistance of the soil in real time, ensuring the accuracy and reliability of the test data, and providing a more accurate basis for bearing capacity assessment. In addition, through remote operation of the drone, the test personnel are effectively avoided from entering a complex or dangerous geological environment, reducing potential safety risks and ensuring the personal safety of the test personnel. The overall design of the present invention is simple, the operating process is easy to master, and no complicated on-site layout is required, which is convenient for rapid promotion and application in actual projects. In summary, the present invention has shown significant technical advantages in terms of efficiency, accuracy, safety and convenience, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The figure is a schematic diagram of the overall process of a method for testing the bearing capacity of a newly filled site according to the present invention.

[0031] Figure 2 This is a schematic diagram of a new bearing capacity testing method for a newly filled site to generate a digital elevation model of the site.

[0032] Figure 3 It is a schematic diagram of dividing the shallow vacuum preloading reinforcement area.

[0033] Figure 4 This is a schematic diagram of the structure of a bearing capacity test device for a newly filled site in an embodiment of the present invention, in which: 101, UAV carrying system, 102, micro static penetration instrument; 1, shock-absorbing suspension system; 2, UAV fuselage; 3, connecting line; 4, GNSS positioning module; 5, micro double-bridge probe. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] See also Figure 1 A method for testing the bearing capacity of a newly filled site comprises the following steps:

[0037] S1. Use a drone to survey the site and obtain a digital elevation model of the site;

[0038] S2. Set up several inspection points on the site based on the site's digital elevation model, and use a drone to measure the soil layer data at each inspection point.

[0039] S3. Calculate the bearing capacity of each detection point based on the soil layer data of each detection point, and generate a bearing capacity distribution map based on the bearing capacity of each detection point.

[0040] Specifically, the GNSS positioning system is used to determine the site boundary coordinates and plan the flight route to control the drone to perform aerial survey operations along the preset route.

[0041] In an optional embodiment, in step S1, the drone maps the site, which is specifically implemented as follows:

[0042] Several control points are evenly distributed in the field. For each control point, the UAV flies to the control point and collects the vertical distance between the control point and the UAV and the vertical coordinate of the UAV. The absolute elevation of the control point is calculated based on the vertical distance and the vertical coordinate of the UAV. The absolute elevation of the i-th control point is The calculation formula is:

[0043] ,in, is the error correction value, i represents the i-th control point, It represents the vertical distance between the UAV and the i-th control point when the UAV navigates to the i-th control point. It is the ordinate coordinate of the UAV when it navigates to the i-th control point. The absolute elevation of all control points is obtained, and the digital elevation model of the site is generated using the spatial interpolation method based on the absolute elevation of each control point.

[0044] Specifically, the vertical distance between each point and the UAV is obtained by using the onboard LiDAR sensor, and the real-time dynamic positioning (RTK) coordinates of the UAV are obtained. , , ) and vertical distance, calculate the absolute elevation of each control point on the site through spatial geometric relationships Absolute elevation refers to the absolute height of the ground (relative to sea level or datum). RTK high-precision positioning is a GNSS-based technology designed to provide high-precision positioning information at the centimeter or even millimeter level. RTK technology improves positioning accuracy and real-time performance through differential correction between the base station and the mobile station.

[0045] In addition, the absolute elevation Hi difference calculated for each control point should be less than 2%. The elevation difference refers to the change in elevation between two control points. If the absolute elevation difference is greater than 2%, it indicates that the terrain slope is steep or uneven, which may lead to amplified measurement errors and deviations in maps, terrain models, or engineering designs. Therefore, 1 to 2 additional control points are required between the control points to ensure the accuracy of the absolute elevation data.

[0046] A site digital elevation model (DEM) is a model that digitally represents topography. It uses a grid or triangulated network to store the elevation data of a location. It is used for slope analysis, flood simulation, earthwork calculations, and urban planning. In practical applications, the height of unknown locations is estimated from the absolute elevation of each control point through spatial interpolation. Continuous terrain surfaces are created through methods including inverse distance weighting, kriging, or triangulated irregular networks to achieve accurate measurement of site elevation.

[0047] like Figure 2, which is a schematic diagram of a specific site digital elevation model in an embodiment of the present invention. The horizontal axis in the figure represents the east-west direction, and the vertical axis represents the north-south direction. Different colors of the site in the figure correspond to different elevations, and the elevation is the absolute elevation in meters.

[0048] In an optional embodiment, the number of control points is arranged according to the area of ​​the site, with a control point per 1000 m 2 Place at least one control point.

[0049] In an optional embodiment, in step S2, the drone measures the soil layer data of each detection point on the site through a detector, and its specific implementation method is: for each detection point, the drone navigates to the detection point, controls the detector to penetrate the soil layer, and the detector collects the penetration depth, cone tip resistance and side wall friction resistance in real time, and records the plane coordinates of the drone at this time.

[0050] Specifically, the drone flies to the coordinates of the test points along a preset route and uses an onboard LiDAR sensor for real-time monitoring. Simultaneously, the drone's attitude control system ensures the platform's horizontality error is less than 0.1° to reduce measurement errors. Once the test conditions are met, the detector is automatically released. Furthermore, the density and requirements for the bearing capacity test points are based on the "Technical Specifications for Testing and Inspection of Water Transport Engineering Foundations."

[0051] In an optional embodiment, the detector is a microstatic cone penetrometer (MSCP). A microstatic cone penetrometer (MSCP) is a portable engineering instrument used for on-site soil testing. It slowly pushes a conical probe into the soil to measure the cone resistance and sidewall friction, thereby assessing soil strength, density, layer position, and bearing capacity. This instrument is compact and easy to operate, making it commonly used in shallow soil surveys, roadbed testing, and small engineering projects.

[0052] In the specific implementation, the micro static penetration instrument falls freely in the vertical direction under the action of gravity and penetrates the soil layer to be tested. The system records the penetration depth in real time δ , cone tip resistance of soil q c and sidewall friction f s The plane coordinates (Xi, Yi) of the test points are obtained through the GNSS positioning module, and the coordinate data and penetration parameters are synchronously transmitted to the computer data processing center to provide basic data for subsequent foundation bearing capacity analysis.

[0053] In an optional embodiment, in step S3, the bearing capacity of each detection point is calculated based on the soil layer data of each detection point, and the specific implementation method is:

[0054] When the detector is a micro static penetration tester, the calculation formula for the bearing capacity of the detection point is:

[0055]

[0056] in, is the bearing capacity at the jth detection point, k is the empirical coefficient, is the cone tip resistance at the jth detection point.

[0057] In an optional embodiment, the detector is a test element, and when measuring soil layer data at each test point, the vertical distance between the drone and the test point is kept at , the drone releases the test element, and the test element collects soil layer data.

[0058] In the practical application of the embodiment of this solution, the test element is a standard metal body made of high-density alloy material. ρ >2g / cm³. A high-precision displacement sensor integrated into the top monitors and records penetration depth δ in real time, with a measurement accuracy of ±0.1mm. The entire component complies with foundation testing equipment standards and exhibits excellent axial stiffness and bending resistance, ensuring no buckling deformation during testing.

[0059] In an optional embodiment, when the detector is a test element, the bearing capacity of the detection point is calculated as follows:

[0060] The calculation formula for shear strength is:

[0061]

[0062] in, is the shear strength at the detection point j, is the vertical distance between the UAV and the detection point, is the penetration depth of the test element at the detection point j, K is the empirical coefficient of shear strength, m is the mass of the test element, g is the acceleration of gravity, and A is the bottom area of ​​the test element;

[0063] The bearing capacity of the detection point j is calculated according to the following formula:

[0064]

[0065] in, is the shear strength at the detection point j, c is the cohesion of the soil, is the vertical compressive stress, is the internal friction angle, 、 is the bearing capacity parameter, The actual value measured here is the ultimate bearing capacity at the detection point j, that is, the upper limit of the bearing capacity at this location, which is used to measure the force that can be carried and determine whether it is suitable for foundation construction.

[0066] In an optional embodiment, in step S3, the bearing capacity distribution map is generated according to the bearing capacity of each detection point, and its specific implementation method is: according to the bearing capacity of each detection point in the site digital elevation model, the foundation bearing capacity contour map is generated using the Kriging interpolation method.

[0067] like Figure 3 As shown in the figure, the horizontal axis represents the east-west direction, and the vertical axis represents the north-south direction. Different colors in the site correspond to different elevations in the figure. Elevation is the absolute elevation, measured in meters. Based on the soft foundation treatment threshold specified in the specification, GIS spatial analysis technology is used to delineate the shallow vacuum preloading treatment area based on the foundation bearing capacity contour map, determine the boundary coordinates of the treatment range, and divide the shallow vacuum preloading reinforcement area. The area within the red line in the figure is the shallow vacuum preloading reinforcement area. The treatment depth is calculated and determined according to the standard formula based on the physical and mechanical indicators of the soil layer. The final foundation treatment plan diagram is formed, which includes parameters such as geographic coordinates, treatment range, and treatment depth. It provides a technical basis for the subsequent drainage board layout, sealing system setting, and loading scheme design in vacuum preloading construction.

[0068] In an optional embodiment, a multi-UAV collaborative operation system may also be used to integrate high-precision GNSS positioning technology with remote sensing sensors to achieve rapid and efficient detection of the bearing capacity of large-scale fill sites.

[0069] like Figure 4 As shown, in another optional embodiment, a device for testing the bearing capacity of a recently filled site is provided, comprising an unmanned aerial vehicle (UAV) carrying system 101, a micro-static cone penetration instrument 102, a shock-absorbing suspension system 1, a UAV body 2, a connecting cable 3, a GNSS positioning module 4, and a micro-double-bridge probe 5. The UAV carrying system 101 includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of a method for testing the bearing capacity of a recently filled site. The UAV body 2 is equipped with a LiDAR sensor, an RTK positioning chip, and an attitude control system. The connecting cable 3 is used to control the elevation and transmission of the micro-static cone penetration instrument 102 or a test element. Furthermore, since the embodiments of the present application are targeted at recently filled sites, where the soil strength is relatively low, when the UAV uses the micro-static cone penetration instrument or test element for surveying at the inspection point, the soil layer can be penetrated by the device's own weight.

[0070] The embodiment disclosed in this specification is merely an illustration of one aspect of the present invention. The scope of protection of the present invention is not limited to this embodiment. Any other functionally equivalent embodiments fall within the scope of protection of the present invention. Those skilled in the art can make various other corresponding changes and modifications based on the technical solutions and concepts described above, and all such changes and modifications should fall within the scope of protection of the claims of the present invention.

Claims

1. A method for testing the bearing capacity of a newly filled site, characterized in that: The following steps are involved: S1. The drone surveys the site and evenly distributes several control points in the site. The number of control points is based on the site area. Every 1000 m 2 At least one control point is set up. For each control point, the drone navigates to the control point and collects the vertical distance between the control point and the drone and the vertical coordinate of the drone. The absolute elevation of the control point is calculated based on the vertical distance and the vertical coordinate of the drone. The absolute elevation of the i-th control point is The calculation formula is: ,in, is the error correction value, i represents the i-th control point, It represents the vertical distance between the UAV and the i-th control point when the UAV navigates to the i-th control point. is the elevation coordinate of the UAV when it navigates to the i-th control point. The absolute elevations of all control points are obtained. The digital elevation model of the site is generated using the spatial interpolation method according to the absolute elevation of each control point to obtain the digital elevation model of the site. S2. Based on the site's digital elevation model, several test points are set up on the site. A drone uses a detector to measure soil layer data at each test point. This is accomplished by: For each test point, the drone flies to the point and releases the detector. The detector freely falls vertically under gravity, penetrating the soil layer to be measured. The detector collects penetration depth, cone tip resistance, and sidewall friction resistance in real time, and records the drone's planar coordinates at that point. The detector is a micro static cone probe or a detection element. When the detector is a detection element, when measuring soil layer data at each detection point, the vertical distance between the drone and the detection point is kept fixed. ,The UAV releases the test element, which collects soil layer data; S3. Calculate the bearing capacity of each detection point based on the soil layer data of each detection point, and generate a bearing capacity distribution map based on the bearing capacity of each detection point.

2. A method for testing the bearing capacity of a newly filled site according to claim 1, characterized in that: In step S3, the bearing capacity of each detection point is calculated based on the soil layer data of each detection point, and the specific implementation method is as follows: When the detector is a micro static penetration tester, the calculation formula for the bearing capacity of the detection point is: in, is the bearing capacity at the jth detection point, k is the empirical coefficient, is the cone tip resistance at the jth detection point.

3. A method for testing the bearing capacity of a newly filled site according to claim 1, characterized in that: When the detector is a test element, the bearing capacity of the test point is calculated as follows: The calculation formula for shear strength is: in, is the shear strength at the detection point j, is the vertical distance between the UAV and the detection point, is the penetration depth of the test element at the detection point j, K is the empirical coefficient of shear strength, m is the mass of the test element, g is the acceleration of gravity, and A is the bottom area of ​​the test element; The bearing capacity of the detection point j is calculated according to the following formula: in, is the shear strength at the detection point j, c is the cohesion of the soil, is the vertical compressive stress, is the internal friction angle, 、 is the bearing capacity parameter, is the bearing capacity at detection point j.

4. A method for testing the bearing capacity of a newly filled site according to claim 1, characterized in that: In step S3, the bearing capacity distribution map is generated according to the bearing capacity of each detection point, which is specifically implemented by generating a foundation bearing capacity contour map using the Kriging interpolation method according to the bearing capacity of each detection point in the site digital elevation model.

5. A device, characterized in that The system comprises at least a processor and a memory, wherein the processor calls computer instructions in the memory to execute the bearing capacity testing method for a newly filled site according to any one of claims 1 to 4.

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