Engineering measurement system based on cooperation of unmanned aerial vehicle-mounted laser radar and inertial navigation

Abstract

The invention discloses an engineering measurement system based on cooperation of an unmanned aerial vehicle laser radar and inertial navigation, and relates to the field of engineering measurement. Performing initial scanning on a target area by controlling the unmanned aerial vehicle flying platform to obtain a reference point cloud; after controllable excitation is applied to the target object, the unmanned aerial vehicle flight platform is controlled to carry out dynamic response scanning on the target area, and response point cloud is obtained; based on the position and attitude information provided by the inertial navigation module, performing accurate registration on the reference point cloud and the response point cloud; calculating and extracting the variable quantity of the target object caused by the controllable excitation through a point cloud difference technology; the variable quantity is input into a preset physical inversion model, and the mass or weight of the target object is calculated and output. According to the scheme, the high-precision geometric perception capability of the unmanned aerial vehicle laser radar is fully utilized, the physical model is combined, and the technical effect that the mass of the object is inversed directly by observing the mechanical response of the object is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of engineering surveying, and in particular to an engineering surveying system based on cooperation of unmanned aerial laser radar and inertial navigation. BACKGROUND

[0002] In the fields of engineering construction, industrial production and infrastructure operation, it is a basic and key requirement to quickly and accurately measure the weight (or mass) of a specific object or structure. Such "engineering weight measurement" is widely used in earthwork quantity accounting, hoisting load safety monitoring, stockpile inventory management, structure health assessment (such as icing monitoring), and other scenarios.

[0003] Currently, traditional engineering surveying methods mainly rely on the following technologies: 1. Contact type direct measurement: such as using a weighbridge, platform scale, etc. This method is direct, but requires the measured object to be placed on the scale body. It is not applicable to large structures (such as bridges), high-altitude equipment (such as power transmission lines), or scattered materials that cannot be weighed as a whole. In addition, contact measurement is often inefficient and difficult to deploy in some dangerous environments (such as slopes, deep pits).

[0004] 2. Volume-density estimation method: this method calculates the volume by measuring the geometric size of the object, and then multiplies the empirical density value to estimate the mass. For example, using a total station or early unmanned aerial photography surveying technology to measure the earthwork volume. However, the accuracy of this method depends heavily on the accuracy of the density value. For complex, unevenly distributed materials (such as garbage piles, mixed mineral materials), it is difficult to accurately determine the density, resulting in large errors in the final mass estimation. At the same time, photography surveying technology cannot penetrate vegetation and effectively obtain the three-dimensional shape of complex structures.

[0005] 3. Indirect measurement based on sensors: such as installing force sensors on the steel wire rope or hooks of hoisting machinery. This method can achieve dynamic monitoring, but requires modification of existing equipment, with high installation and maintenance costs. The sensors themselves have problems such as aging, temperature drift, and need to be calibrated regularly, with poor universality.

[0006] In recent years, the unmanned aerial laser radar technology has been widely applied in engineering surveying and mapping field due to its strong maneuverability, high data acquisition efficiency and the advantage of actively obtaining high-precision three-dimensional point cloud of the detection target. Especially when it works with high-precision inertial navigation system, it can quickly generate a real three-dimensional model with centimeter-level precision without ground control points, which greatly promotes the development of terrain mapping, engineering measurement and other fields. In the prior art, there are cases of using this technology to calculate earthwork volume, the essence of which is to calculate the volume change through two periods of point cloud and then multiply the density to obtain the mass change. However, this method still does not break out of the category of "volume-density" estimation, and the precision bottleneck is still the uncertainty of density. Therefore, there is a lack of a universal weight measurement method and system for non-contact, high-precision, no need to preset density and no dependence on pre-installed sensors for objects in different engineering scenes. In order to break through the limitations of traditional methods, an engineering measurement system based on cooperation of unmanned aerial laser radar and inertial navigation is proposed. SUMMARY

[0007] The main purpose of the present application is to provide an engineering measurement system based on cooperation of unmanned aerial laser radar and inertial navigation, which can fully utilize the high-precision geometric perception ability of unmanned aerial laser radar, combine reliable physical principles, and directly invert the mass of the object by observing its mechanical response, thereby effectively solving the problems in the background technology.

[0008] To achieve the above purpose, the technical scheme adopted by the present application is, The engineering measurement system based on cooperation of unmanned aerial laser radar and inertial navigation comprises: An unmanned aerial vehicle flight platform; A laser radar scanning module integrated in the unmanned aerial vehicle flight platform, used for acquiring three-dimensional point cloud data of a target region; An inertial navigation module integrated in the unmanned aerial vehicle flight platform, used for acquiring position and attitude information of the unmanned aerial vehicle flight platform; A control and data processing unit configured to control the laser radar scanning module and the inertial navigation module to work cooperatively and perform the following steps: Controlling the unmanned aerial vehicle flight platform to perform initial scanning on the target region to acquire reference point cloud ; After applying a controllable excitation to the target object, controlling the unmanned aerial vehicle flight platform to perform dynamic response scanning on the target region to acquire response point cloud ; Based on the position and attitude information provided by the inertial navigation module, accurately registering the reference point cloud and the response point cloud ; The change amount of the target object caused by the controllable excitation is calculated and extracted by point cloud difference technology ; The change amount is input into a preset physical inversion model, and the mass or weight of the target object is calculated and output.

[0009] A non-transitory computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps performed by the control and data processing unit.

[0010] An engineering surveying method based on the cooperation of unmanned aerial laser radar and inertial navigation, the method comprising: acquiring the reference point cloud of the target object before excitation by the unmanned aerial laser radar and inertial navigation system ; After applying a controllable excitation to the target object, the response point cloud of the target object after excitation is acquired by the unmanned aerial laser radar and inertial navigation system ; The reference point cloud and the response point cloud are accurately registered based on inertial navigation data; The change amount of the target object caused by the controllable excitation is extracted by point cloud difference technology ; The change amount is substituted into a preset physical inversion model to obtain the mass or weight of the target object by inversion calculation.

[0011] Further, the controllable excitation includes any one or more of the following: Active excitation: a known force or mass block applied to the target object by the unmanned aerial vehicle flight platform or auxiliary equipment; Passive excitation: using the load change of the target object itself as excitation; Environmental excitation: using wind, vibration or temperature change acting on the target object in the natural environment as excitation.

[0012] Further, the change amount is any one or more of the following geometric and physical quantities: The displacement or settlement of the surface of the target object; The deformation of the target object; The volume change of the target object; The vibration frequency or amplitude of the target object.

[0013] Further, the physical inversion model includes a cantilever beam model for the load measurement, specifically: = ; wherein, is the mass or weight of the target object, is the elastic modulus, which is a measure of the ability of a material to resist elastic deformation, unit: pascal Pa, which can be obtained by consulting the material manual or through the pre-calibration experiment, is the cross-sectional moment of inertia, which is a geometric quantity used to describe the influence of the cross-sectional shape and size of the beam on the bending resistance, unit: m 4 , calculated according to the cross-sectional size fitted from the point cloud; is the maximum deflection, which is used to describe the maximum vertical displacement of the cantilever beam end relative to the unloaded position, unit: m, which is extracted by comparing the point clouds before and after loading, and then calculating the difference, is the cantilever length, which is used to describe the length of the beam from the fixed end to the free end, unit: m, which is fitted and measured from the point cloud, is the gravitational acceleration, unit: m / s 2 .

[0014] Further, the physical inversion model includes an elastic foundation model for the bulk material estimation, specifically: = ; wherein, is the mass or weight of the target object, is the system calibration constant, which is a dimensionless empirical coefficient used to reflect the mechanical properties of the material, which needs to be calibrated through experiments, is the material pile bottom area, which is used to reflect the total projection area of the material pile in contact with the ground, unit: m 2 , obtained from the reference point cloud through boundary identification and area calculation, is the impact area, which is the area of the region caused by the impact of the mass block, unit: m 2 , calculated from the distribution of the settlement area in the differential point cloud, is the initial average height, which is the average height of the material pile before the excitation is applied, unit: m, calculated by comparing the reference point cloud with the ground model, is the average settlement, which represents the average sinking depth of the material surface in the affected area after the known mass block is applied, unit: meter, obtained by point cloud difference technology, is the excitation mass, i.e. the mass block from the unmanned aerial vehicle flight platform to the material, unit: kg.

[0015] Further, the physical inversion model comprises a vibration frequency model for environmental excitation, specifically: = ; wherein, is the mass or weight of the target object, is the equivalent stiffness, used to reflect the ability of the structure to resist deformation, i.e. the force required to produce a unit displacement, unit: N / m, is the vibration frequency, unit: Hz, obtained by analyzing the acquired continuous time series point cloud, is the constant of pi.

[0016] Further, the control and data processing unit is specifically used for: aligning the reference point cloud and the response point cloud initially using the high-precision position and attitude sequence obtained by the inertial navigation module; precisely registering the two point clouds using the iterative closest point algorithm to solve the optimal rigid body transformation matrix ; calculating the spatial coordinate difference of corresponding points in the two registered point clouds to generate a change vector field, and statistically obtaining the change .

[0017] Further, the laser radar scanning module and the inertial navigation module are synchronized through a hardware time synchronization device, so that the emission time of each laser corresponds to an inertial navigation attitude data; the control and data processing unit fuses global satellite navigation system observation data and observation data of the inertial navigation module through a tightly coupled Kalman filtering algorithm to obtain a high-frequency and high-precision flight trajectory of the unmanned aerial vehicle.

[0018] The present application has the following advantages, Compared with the prior art, the measurement system proposed in the present application can directly complete all data acquisition work in the air without contacting the measured object, making it possible to measure the weight of dangerous environments (such as slopes, pits, and contaminated areas), high-risk structures (such as high-voltage transmission lines and damaged bridges), and difficult-to-reach areas (such as the top of large material piles and suspended structures), thereby fundamentally ensuring the safety of personnel and equipment.

[0019] Compared with the prior art, the measurement system proposed in the present application does not rely on the empirical density measurement method of traditional methods, but measures the accurate mechanical response of the object under known excitation, and inverses based on a rigorous physical model, bypassing the density parameter, directly calculating the mass from the physical nature, eliminating the main error source caused by density estimation, and making the measurement result more reliable and accurate.

[0020] Compared with the prior art, the measurement system provided in the scheme can be applied to different weight measurement scenes such as discrete load (such as hoisting weight), bulk material (such as earthwork), and attached mass (such as ice coating) by calling different algorithms of the same set of hardware system through the construction of a configurable physical model library (such as a cantilever beam model, an elastic foundation model, and a vibration model), thereby realizing 'one machine for multiple uses', and greatly improving the utilization value of the equipment and the flexibility of the solution.

[0021] Compared with the prior art, the measurement system provided in the scheme has high measurement efficiency, is mobile and flexible by using a UAV platform, can complete a large range of scanning operations in a short time, and has a data acquisition efficiency far exceeding manual measurement methods, and in combination with a rapid automatic data processing process, can realize a rapid closed loop from data acquisition to result output.

[0022] Compared with the prior art, the measurement system provided in the scheme has high automation and intelligence, effectively reduces the dependence on traditional measurement experience of an operator, reduces human error, enables non-professional personnel to also perform complex weight measurement tasks after training, and is conducive to the rapid promotion and standardized application of the technology. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 FIG. 1 is a structural schematic diagram of an engineering measurement system based on a UAV-borne laser radar and inertial navigation cooperation according to the present application; Figure 2 FIG. 2 is a flowchart of an engineering measurement method based on a UAV-borne laser radar and inertial navigation cooperation according to the present application; Figure 3 FIG. 3 is a schematic diagram of an entity of an engineering measurement system based on a UAV-borne laser radar and inertial navigation cooperation according to the present application.

[0024] In the figure: 1, UAV flight platform; 2, inertial navigation module; 3, laser radar scanning module; 4, control and data processing unit. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0026] Example 1: Referring to Figure 1 FIG. 1 is a structural schematic diagram of an engineering measurement system based on a UAV-borne laser radar and inertial navigation cooperation according to the present application, and Figure 3 FIG. 3 is a schematic diagram of an entity of an engineering measurement system based on a UAV-borne laser radar and inertial navigation cooperation according to the present application. The UAV flight platform 1; The laser radar scanning module 3 integrated in the UAV flight platform 1 is used to obtain the three-dimensional point cloud data of the target area; The inertial navigation module 2 integrated in the UAV flight platform is used to obtain the position and attitude information of the UAV flight platform 1; The control and data processing unit 4 is configured to control the laser radar scanning module 3 and the inertial navigation module 2 to work cooperatively and perform the following steps: The UAV flight platform 1 is controlled to perform initial scanning on the target area to obtain the reference point cloud ; After applying a controllable excitation to the target object, the UAV flight platform 1 is controlled to perform dynamic response scanning on the target area to obtain the response point cloud ; Based on the position and attitude information provided by the inertial navigation module 2, the reference point cloud and the response point cloud are accurately registered; Through point cloud difference technology, the change amount of the target object caused by the controllable excitation is calculated and extracted , wherein the change amount includes: displacement or settlement of the target object surface; deformation of the target object; volume change of the target object; vibration frequency or amplitude of the target object; The change amount is input into a preset physical inversion model to calculate and output the mass or weight of the target object.

[0027] According to the above system structure, an implementable measurement process of the measurement system of the present application is given, including the following specific implementation steps: First stage: preparation Step 1: survey and scheme design Step 1.1, site survey: confirm the type of target object (such as cantilever beam, bulk material, suspension structure), surrounding environment (such as GNSS signal condition, obstacle) and safety.

[0028] Step 1.2, model selection: select the most suitable physical inversion model according to the target object (such as cantilever beam model, elastic foundation model, suspension model or vibration frequency model).

[0029] Step 1.3, excitation design: Determine the way to apply controllable excitation, including: Active excitation: known force or mass block applied to the target object by the UAV flight platform or auxiliary equipment; Passive excitation: Use the target object's own load change as the excitation, while planning the scanning opportunity of the unloaded and loaded states; Environmental excitation: Use the wind, vibration or temperature change in the natural environment acting on the target object as the excitation, while confirming whether the environmental force (such as wind) is sufficient and planning the continuous scanning time.

[0030] Step 2: System configuration and calibration Step 2.1, Equipment assembly Integrate the laser radar, IMU, GNSS receiver into the unmanned aerial vehicle platform, and connect the control and data processing unit.

[0031] Step 2.2, Time synchronization Ensure that the hardware time synchronization accuracy between the laser radar, IMU and GNSS receiver reaches the microsecond level.

[0032] Step 2.3, System calibration Sensor calibration: Accurately calibrate the spatial conversion relationship between the laser radar and the IMU (such as the lever arm value, installation angle).

[0033] Model parameter calibration: For the elastic foundation model, calibrate the system constant through the previous experiment; for the vibration frequency model, measure the initial frequency of the structure in the unloaded state to calculate the equivalent stiffness.

[0034] Step 3: Flight mission planning Step 3.1, Route design In the flight control software, plan the automatic flight route covering the target area and the surrounding reference area. Ensure that the route overlap rate, flight height and speed can meet the point cloud density and accuracy requirements.

[0035] Step 3.2, Reference station erection Erect a GNSS ground reference station on a known coordinate point near the survey area or a point with accurate coordinates obtained through long-term static observation.

[0036] Second stage: Field data collection Step 4: Initial state scanning (reference scanning) Step 4.1, Control the unmanned aerial vehicle to take off and fly according to the predetermined route.

[0037] Step 4.2, Synchronously collect laser radar point cloud data, IMU raw data, airborne GNSS observation data and ground reference station GNSS data.

[0038] Step 4.3, Reference point cloud obtained in this stage As the reference for subsequent changes.

[0039] For the cantilever beam model: Obtain the shape of the beam when unloaded.

[0040] For elastic foundation model: Obtain the surface morphology of the material pile before applying excitation.

[0041] For vibration frequency model: Short-time scanning, mainly for obtaining geometric size.

[0042] Step 5: Apply controllable excitation Step 5.1, apply excitation according to preset scheme Active excitation: UAV precisely drops standard weights, or applies known force at target point through other means.

[0043] Passive excitation: Place or hang the weight to be measured at the target position (such as crane hook).

[0044] Environmental excitation: Wait and confirm that the natural wind reaches the magnitude that can excite the structure vibration.

[0045] Step 6: Dynamic response scanning (monitoring scanning) Step 6.1, immediately after applying excitation, control UAV to perform second flight scanning (flight path should be as consistent as possible with the first time).

[0046] Step 6.2, synchronously collect all sensor data, obtain response point cloud .

[0047] For vibration frequency model: This step is replaced by continuous scanning, taking point cloud sequence in a period of time as data source, capturing vibration time history curve of the structure.

[0048] Third stage: Data processing and quality inversion in office Step 7: GNSS / IMU integrated navigation solution Step 7.1, perform differential processing on airborne GNSS data and ground reference station data.

[0049] Step 7.2, use tight coupling Kalman filtering algorithm to fuse differential GNSS observation value and high-frequency angular velocity and acceleration data of IMU, to solve high-precision position, velocity and attitude sequence of UAV at each time.

[0050] Step 8: Point cloud generation and accurate registration Step 8.1, use the solved accurate trajectory and laser radar raw data to generate high-precision three-dimensional reference point cloud and response point cloud .

[0051] Step 8.2, use accurate registration algorithms such as Iterative Closest Point (ICP) to register reference point cloud and response point cloud Registration to the same coordinate system, eliminating any minor residual alignment errors.

[0052] Step 9: Change detection and feature extraction Step 9.1, Perform point cloud difference calculation on the two registered point clouds, generate a three-dimensional change vector field.

[0053] Step 9.2, Extract the feature change corresponding to the model from the change vector field : For cantilever beam model: extract the maximum deflection at the end of the beam.

[0054] For elastic foundation model: calculate the average settlement of the weight impact area.

[0055] For vibration frequency model: perform spectral analysis on the point cloud time series, extract the first-order natural frequency of the structure.

[0056] Step 10: Physical inversion and quality calculation Step 10.1, Substitute the geometric parameters (such as L, A_total, etc.) extracted from the point cloud and the change Δ obtained in step 9 into the preset physical inversion model.

[0057] Step 10.2, Perform calculation Use the physical inversion model to invert the mass of the target object, including: Cantilever beam model for hoisting weight measurement, specific form: = ; Where, M is the mass or weight of the target object, E is the elastic modulus, which reflects the measure of the material's resistance to elastic deformation, unit: Pascal Pa, obtained by consulting the material manual or through the pre-calibration experiment, I is the cross-sectional moment of inertia, which describes the geometric quantity of the beam cross-sectional shape and size affecting the bending resistance, unit: m 4 , calculated according to the cross-sectional size fitted from the point cloud; δ is the maximum deflection, which describes the maximum vertical displacement of the cantilever beam end relative to the unloaded position, unit: m, extracted by comparing the point clouds before and after loading, and then difference calculation, L is the cantilever length, which describes the length of the beam from the fixed end to the free end, unit: m, fitted and measured from the point cloud, g is the acceleration of gravity, unit: m / s 2 .

[0058] Elastic foundation model for bulk material estimation, specific form: = ; in, The mass or weight of the target object. The system calibration constant is a dimensionless empirical coefficient used to reflect the mechanical properties of the material and needs to be calibrated experimentally. The base area of ​​the material pile reflects the total projected area of ​​the material pile in contact with the ground. Unit: m² 2 It is obtained from the reference point cloud through boundary identification and area calculation. The impact area is the area of ​​settlement caused by the impact of the mass block, in meters (m²). 2 The results were calculated from the distribution of settlement regions in the differential point cloud. The initial average height is the average height of the material pile before the excitation is applied, in meters. It is calculated by comparing the baseline point cloud with the ground model. The average settlement, characterizing the average depth of the material surface within its influence area after the application of a known mass block, is expressed in meters and is obtained using point cloud differential techniques. To incentivize mass, which is the mass of the material from the drone flight platform, the unit is kg.

[0059] The vibration frequency model used for environmental excitation has the following specific form: = ; in, The mass or weight of the target object. Equivalent stiffness reflects a structure's ability to resist deformation, i.e., the force required to produce a unit displacement. The unit is N / m. The vibration frequency, in Hz, is obtained by analyzing the acquired continuous time series point cloud. Pi is a constant. Step 11: Output and Report Generation Step 11.1, the system outputs the final quality. The measurement results.

[0060] Step 11.2: Automatically generate a weighing report, including: input parameters, intermediate observations, calculation process, final results, and accuracy assessment.

[0061] Example 2 See Figure 2 The flowchart shown is a schematic diagram of an engineering measurement method based on the coordination of UAV-borne lidar and inertial navigation according to the present invention, which includes the following steps: By using an UAV-borne lidar and inertial navigation system, a reference point cloud of the target object before it is stimulated is obtained. ; After applying a controllable excitation to the target object, the response point cloud of the target object after being excited is obtained by using an UAV-borne lidar and inertial navigation system. ; Reference point cloud based on inertial navigation data and response point cloud Perform precise registration; Point cloud difference technology is used to extract the changes in the target object caused by controllable excitation. ; Change Substituting the data into the preset physical inversion model, the mass or weight of the target object is calculated.

[0062] Example 3 The present invention also provides a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, is capable of implementing the steps executed by the control and data processing unit in the system of Embodiment 1 and the steps of the engineering measurement method based on the coordination of UAV-borne lidar and inertial navigation in Embodiment 2.

[0063] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. An engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation, characterized in that, include: Unmanned aerial vehicle (UAV) flight platform; The lidar scanning module integrated into the UAV flight platform is used to acquire three-dimensional point cloud data of the target area; An inertial navigation module integrated into the UAV flight platform is used to acquire the position and attitude information of the UAV flight platform; The control and data processing unit is configured to control the coordinated operation of the lidar scanning module and the inertial navigation module, and to perform the following steps: The drone flight platform is controlled to perform an initial scan of the target area and acquire a reference point cloud. ; After applying a controllable excitation to the target object, the UAV flight platform is controlled to perform a dynamic response scan of the target area to acquire a response point cloud. ; Based on the position and attitude information provided by the inertial navigation module, the reference point cloud is... and the response point cloud Perform precise registration; The change in the target object caused by the controllable excitation is calculated and extracted using point cloud difference technology. ; The change Input a preset physical inversion model, calculate and output the mass or weight of the target object.

2. The engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation as described in claim 1, characterized in that, The controllable stimulus includes any one or more of the following: Active excitation: a known force or mass applied to the target object by the UAV flight platform or its auxiliary equipment; Passive excitation: using the load change of the target object itself as the excitation; Environmental stimulus: using wind, vibration or temperature changes in the natural environment acting on the target object as a stimulus.

3. The engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation as described in claim 1, characterized in that, The change For any one or more of the following geometric physical quantities: The displacement or settlement of the surface of the target object; The deformation of the target object; The change in volume of the target object; The vibration frequency or amplitude of the target object.

4. The engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation as described in claim 1, characterized in that, The physical inversion model includes a cantilever beam model for load measurement, specifically in the following form: = ； in, The mass or weight of the target object. The elastic modulus is a measure of a beam material's resistance to elastic deformation, measured in Pascals (Pa). It is obtained by consulting material handbooks or through prior calibration experiments. Moment of inertia is a geometric quantity used to describe the influence of the beam's cross-sectional shape and dimensions on its bending capacity; unit: m. 4 The cross-sectional dimensions are calculated based on the point cloud fitting. Maximum deflection, used to describe the maximum vertical displacement of the cantilever beam end relative to its unloaded position, in meters (m), is extracted by comparing point clouds before and after loading and performing differential calculations. The cantilever length describes the length of the beam from the fixed end to the free end, in meters (m), and is obtained through fitting and measurement from the point cloud. Acceleration due to gravity, unit: m / s² 2 .

5. The engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation as described in claim 1, characterized in that, The physical inversion model includes an elastic foundation model for estimating bulk materials, specifically in the following form: = ； in, The mass or weight of the target object. The system calibration constant is a dimensionless empirical coefficient used to reflect the mechanical properties of the material and needs to be calibrated experimentally. The base area of ​​the material pile reflects the total projected area of ​​the material pile in contact with the ground. Unit: m² 2 It is obtained from the reference point cloud through boundary identification and area calculation. The impact area is the area of ​​settlement caused by the impact of the mass block, in meters (m²). 2 The results were calculated from the distribution of settlement regions in the differential point cloud. The initial average height is the average height of the material pile before the excitation is applied, in meters. It is calculated by comparing the baseline point cloud with the ground model. The average settlement, characterizing the average depth of the material surface within its influence area after the application of a known mass block, is expressed in meters and is obtained using point cloud differential techniques. To incentivize mass, which is the mass of the material from the drone flight platform, the unit is kg.

6. The engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation as described in claim 1, characterized in that, The physical inversion model includes a vibration frequency model for environmental excitation, specifically in the following form: = ； in, The mass or weight of the target object. Equivalent stiffness reflects a structure's ability to resist deformation, i.e., the force required to produce a unit displacement. The unit is N / m. The vibration frequency, in Hz, is obtained by analyzing the acquired continuous time series point cloud. Pi is a constant.

7. The engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation as described in claim 1, characterized in that, When performing point cloud registration and differencing, the control and data processing unit is specifically used for: The high-precision position and attitude sequence obtained by the inertial navigation module is used to analyze the reference point cloud. and the response point cloud Perform initial alignment; The iterative nearest-point algorithm is used to perform fine registration of the two point clouds and solve for the optimal rigid body transformation matrix. ; Calculate the spatial coordinate difference between corresponding points in the two registered point clouds, generate a change vector field, and statistically obtain the change amount. .

8. The engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation as described in claim 1, characterized in that, The lidar scanning module and the inertial navigation module are synchronized through a hardware time synchronization device, so that the emission time of each laser beam corresponds to an inertial navigation attitude data. The control and data processing unit uses a tightly coupled Kalman filter algorithm to fuse global satellite navigation system observation data and inertial navigation module observation data to calculate a high-frequency, high-precision UAV flight trajectory.

9. A non-transitory computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps performed by the control and data processing unit in the system as described in any one of claims 1 to 8.

10. An engineering measurement method based on the coordinated use of UAV-borne lidar and inertial navigation, characterized in that, The method includes the following steps: By using an UAV-borne lidar and inertial navigation system, a reference point cloud of the target object before it is stimulated is obtained. ; After applying a controllable excitation to the target object, the UAV-borne lidar and inertial navigation system acquire the target object's response point cloud after the excitation. ; The reference point cloud is based on inertial navigation data. and the response point cloud Perform precise registration; The change in the target object caused by the controllable excitation is extracted using point cloud difference technology. ; The change Substituting the values ​​into a preset physical inversion model, the mass or weight of the target object is calculated through inversion.

Images