Engineering surveying system based on cooperation of unmanned aerial laser radar and inertial navigation

Abstract

The application discloses an engineering surveying system based on cooperation of unmanned aerial laser radar and inertial navigation, and relates to the field of engineering surveying. The target region is initially scanned by controlling the unmanned aerial vehicle flight platform to obtain a reference point cloud; after a controllable excitation is applied to the target object, the unmanned aerial vehicle flight platform is controlled to perform dynamic response scanning on the target region to obtain a response point cloud; based on position and attitude information provided by the inertial navigation module, the reference point cloud and the response point cloud are accurately registered; through point cloud difference technology, a change amount of the target object caused by the controllable excitation is calculated and extracted; the change amount is input into a preset physical inversion model to calculate and output the mass or weight of the target object. The scheme fully utilizes the high-precision geometric perception capability of the unmanned aerial laser radar, and combines a physical model to realize the technical effect of directly inverting the mass of the object by observing the mechanical response of the object.

Description

Technical Field

[0001] This invention relates to the field of engineering surveying, and in particular to an engineering surveying system based on the coordination of UAV-borne lidar and inertial navigation. Background Technology

[0002] In the fields of engineering construction, industrial production, and infrastructure operation and maintenance, rapid and accurate weight (or mass) measurement of specific objects or structures is a fundamental and critical requirement. This type of "engineering weighing" is widely used in various scenarios such as earthwork quantity calculation, hoisting load safety monitoring, material yard inventory management, and structural health assessment (such as icing monitoring).

[0003] Currently, traditional engineering surveying methods mainly rely on the following technologies:

[0004] 1. Direct contact measurement: such as using weighbridges, platform scales, etc. While this method is direct, it requires the object to be measured to be placed on the scale body. It is ineffective for large structures (such as bridges), high-altitude equipment (such as power transmission lines), or bulk materials that cannot be weighed as a whole. In addition, contact measurement is often inefficient and difficult to deploy in certain hazardous environments (such as slopes, deep pits).

[0005] 2. Volume-Density Estimation Method: This method calculates the volume by measuring the geometric dimensions of an object and then multiplies it by an empirical density value to estimate the mass. For example, it can be used to measure the volume of a mound using a total station or early UAV photogrammetry techniques. However, the accuracy of this method heavily depends on the accuracy of the density value. For materials with complex compositions and uneven density (such as garbage dumps or mixed minerals), the density is difficult to accurately determine, leading to significant errors in the final mass estimation. Furthermore, photogrammetry techniques struggle to penetrate vegetation, making it difficult to effectively capture the three-dimensional morphology of complex structures.

[0006] 3. Indirect measurement based on sensors: such as installing force sensors on the wire rope or hook of lifting machinery. Although this method can achieve dynamic monitoring, it requires modification of existing equipment, has high installation and maintenance costs, and the sensors themselves have problems such as aging and temperature drift, requiring regular calibration, and has poor universality.

[0007] In recent years, UAV-borne LiDAR technology has been widely used in engineering surveying due to its advantages of high mobility, high data acquisition efficiency, and ability to actively acquire high-precision 3D point clouds of targets. Especially when working in conjunction with a high-precision inertial navigation system, it can quickly generate centimeter-level accurate 3D models of real-world scenes without ground control points, greatly promoting the development of topographic surveying, engineering measurement, and other fields. Existing technologies have cases of using this technology to calculate earthwork volume, which essentially involves calculating volume change through two-phase point cloud computing and then multiplying by density to obtain mass change. However, this method still falls within the scope of "volume-density" estimation, and its accuracy bottleneck remains due to the uncertainty of density. Therefore, existing technologies lack a universal weight measurement method and system that can perform non-contact, high-precision measurement of objects in different engineering scenarios, without requiring preset density or relying on pre-installed sensors. To overcome the limitations of traditional methods, this paper proposes an engineering measurement system based on the collaboration of UAV-borne LiDAR and inertial navigation. Summary of the Invention

[0008] The main objective of this invention is to provide an engineering measurement system based on the collaboration of UAV-borne lidar and inertial navigation. This system can fully utilize the high-precision geometric perception capability of UAV lidar and, combined with reliable physical principles, directly invert the mass of an object by observing its mechanical response, thus effectively solving the problems in the background technology.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0010] An engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation includes:

[0011] Unmanned aerial vehicle (UAV) flight platform;

[0012] The lidar scanning module integrated into the UAV flight platform is used to acquire three-dimensional point cloud data of the target area;

[0013] An inertial navigation module integrated into the UAV flight platform is used to acquire the position and attitude information of the UAV flight platform;

[0014] 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:

[0015] The drone flight platform is controlled to perform an initial scan of the target area and acquire a reference point cloud. ;

[0016] 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. ;

[0017] 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;

[0018] The change in the target object caused by the controllable excitation is calculated and extracted using point cloud difference technology. ;

[0019] The change Input a preset physical inversion model, calculate and output the mass or weight of the target object.

[0020] A non-transitory computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps performed by the control and data processing unit.

[0021] An engineering measurement method based on the coordinated use of UAV-borne lidar and inertial navigation, the method comprising:

[0022] By using an UAV-borne lidar and inertial navigation system, a reference point cloud of the target object before it is stimulated is obtained. ;

[0023] 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. ;

[0024] The reference point cloud is based on inertial navigation data. and the response point cloud Perform precise registration;

[0025] The change in the target object caused by the controllable excitation is extracted using point cloud difference technology. ;

[0026] The change Substituting the values ​​into a preset physical inversion model, the mass or weight of the target object is calculated through inversion.

[0027] Furthermore, the controllable stimulus includes any one or more of the following:

[0028] Active excitation: a known force or mass applied to the target object by the UAV flight platform or its auxiliary equipment;

[0029] Passive excitation: using the load change of the target object itself as the excitation;

[0030] Environmental stimulus: using wind, vibration or temperature changes in the natural environment acting on the target object as a stimulus.

[0031] Furthermore, the amount of change For any one or more of the following geometric physical quantities:

[0032] The displacement or settlement of the surface of the target object;

[0033] The deformation of the target object;

[0034] The change in volume of the target object;

[0035] The vibration frequency or amplitude of the target object.

[0036] Furthermore, the physical inversion model includes a cantilever beam model for load measurement, specifically in the following form:

[0037] = ;

[0038] 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. 为截面惯性矩，用于描述梁截面形状和尺寸对抗弯能力影响的几何量，单位：m4，根据点云拟合出的截面尺寸计算； 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. 为重力加速度，单位：m / s2。

[0039] Furthermore, the physical inversion model includes an elastic foundation model for estimating bulk materials, specifically in the following form:

[0040] = ;

[0041] 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. 为物料堆底面积，用于反映物料堆与地面接触的总投影面积，单位：m2，从基准点云中通过边界识别和面积计算得到， 为冲击影响面积，为质量块冲击引起沉降的区域面积，单位：m2，从差分点云中沉降区域的分布计算得到， 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.

[0042] Furthermore, the physical inversion model includes a vibration frequency model for environmental excitation, specifically in the following form:

[0043] = ;

[0044] 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.

[0045] Furthermore, when performing point cloud registration and differencing, the control and data processing unit is specifically used for:

[0046] 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;

[0047] The iterative nearest point algorithm is used to precisely register the two point clouds and solve for the optimal rigid body transformation matrix;

[0048] 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. .

[0049] Furthermore, 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.

[0050] The present invention has the following beneficial effects:

[0051] Compared with existing technologies, the measurement system proposed in this solution does not require contact with the object being measured and can complete all data acquisition work directly in the air. This makes it possible to weigh hazardous environments (such as slopes, deep pits, and polluted areas), high-risk structures (such as high-voltage transmission lines and damaged bridges), and hard-to-reach areas (such as the top of large material piles and suspended structures), fundamentally ensuring the safety of personnel and equipment.

[0052] Compared with existing technologies, the measurement system proposed in this scheme does not rely on the empirical density measurement method of traditional methods. By measuring the precise mechanical response of an object under known excitation and performing inversion based on a rigorous physical model, it bypasses the density parameter and directly calculates the mass from the physical essence, eliminating the main source of error caused by density estimation, making the measurement results more reliable and accurate.

[0053] Compared with existing technologies, the measurement system proposed in this solution, by constructing a configurable physical model library (such as cantilever beam model, elastic foundation model, vibration model), allows the same hardware system to be applied to drastically different weighing scenarios, ranging from discrete loads (such as lifting weights) and bulk materials (such as earthwork) to attached mass (such as icing), by simply calling different algorithms. This achieves "one machine for multiple uses" and greatly enhances the utilization value of the equipment and the flexibility of the solution.

[0054] Compared with existing technologies, the measurement system proposed in this solution has extremely high measurement efficiency. It adopts a UAV platform that is mobile and flexible, and can complete large-scale scanning operations in a short time. Its data acquisition efficiency far exceeds that of manual measurement methods. Combined with a rapid automated data processing flow, it can achieve a fast closed loop from data acquisition to result output.

[0055] Compared with existing technologies, the measurement system proposed in this solution has a high degree of automation and intelligence, effectively reducing reliance on operators' traditional measurement experience, reducing human error, and enabling non-professionals to perform complex weighing tasks after training, which is conducive to the rapid promotion and standardized application of the technology. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the engineering measurement system based on the collaboration between UAV-borne lidar and inertial navigation according to the present invention.

[0057] Figure 2 This is a flowchart illustrating the engineering measurement method based on the collaboration between UAV-borne lidar and inertial navigation according to the present invention.

[0058] Figure 3 This is a schematic diagram of an engineering measurement system based on the collaboration between UAV-borne lidar and inertial navigation, according to the present invention.

[0059] In the diagram: 1. Unmanned aerial vehicle (UAV) flight platform; 2. Inertial navigation module; 3. LiDAR scanning module; 4. Control and data processing unit. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0061] Example 1:

[0062] See Figure 1 The diagram shown is a structural schematic of an engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation according to the present invention. Figure 3 The schematic diagram shown illustrates an engineering measurement system based on the coordinated use of UAV-borne lidar and inertial navigation, including:

[0063] Unmanned aerial vehicle (UAV) flight platform 1;

[0064] The lidar scanning module 3, integrated into the UAV flight platform 1, is used to acquire three-dimensional point cloud data of the target area;

[0065] The inertial navigation module 2, integrated into the UAV flight platform, is used to acquire the position and attitude information of the UAV flight platform 1.

[0066] The control and data processing unit 4 is configured to control the coordinated operation of the lidar scanning module 3 and the inertial navigation module 2, and to perform the following steps:

[0067] The control drone flight platform 1 performs an initial scan of the target area to acquire a reference point cloud. ;

[0068] After applying a controllable excitation to the target object, the UAV flight platform 1 is controlled to perform a dynamic response scan of the target area and acquire the response point cloud. ;

[0069] Based on the position and attitude information provided by inertial navigation module 2, the reference point cloud is... and response point cloud Perform precise registration;

[0070] Point cloud difference technology is used to calculate and extract the changes in the target object caused by controllable excitation. Among them, the change This includes: the displacement or settlement of the target object's surface; the deformation of the target object; the volume change of the target object; and the vibration frequency or amplitude of the target object.

[0071] Change Input a preset physical inversion model, calculate and output the mass or weight of the target object.

[0072] Based on the above system structure, an implementable measurement process for the measurement system of the present invention is given, including the following specific implementation steps:

[0073] Phase 1: Preparation

[0074] Step 1: Survey of the survey area and design of the plan

[0075] Step 1.1, On-site investigation: Confirm the type of the target object (such as cantilever beam, bulk material, suspension structure), the surrounding environment (such as GNSS signal conditions, obstacles) and safety.

[0076] Step 1.2, Model Selection: Select the most suitable physical inversion model (such as cantilever beam model, elastic foundation model, suspension cable model or vibration frequency model) based on the target object.

[0077] Step 1.3, Incentive Design:

[0078] Determine the methods for applying controllable stimuli, including:

[0079] Active excitation: A known force or mass applied to a target object by the drone flight platform or its auxiliary equipment;

[0080] Passive excitation: Utilize the load changes of the target object itself as excitation, and plan the scanning timing for both no-load and loaded states.

[0081] Environmental stimulus: Utilize wind, vibration, or temperature changes acting on the target object in the natural environment as a stimulus, while confirming whether the environmental forces (such as wind) are sufficient and planning the continuous scanning time.

[0082] Step 2: System Configuration and Calibration

[0083] Step 2.1, Equipment Assembly

[0084] The lidar, IMU, and GNSS receiver are integrated into the UAV platform and connected to the control and data processing unit.

[0085] Step 2.2, Time Synchronization

[0086] Ensure that the hardware time synchronization accuracy between the lidar, IMU, and GNSS receiver reaches the microsecond level.

[0087] Step 2.3, System Calibration

[0088] Sensor calibration: Accurately calibrate the spatial conversion relationship between the lidar and the IMU (such as lever arm value and installation angle).

[0089] Model parameter calibration: For the elastic foundation model, the system constants are calibrated through previous experiments; for the vibration frequency model, the initial frequency of the structure is measured under no-load conditions to calculate the equivalent stiffness.

[0090] Step 3: Flight Mission Planning

[0091] Step 3.1, Route Design

[0092] The flight control software plans an automated flight path covering the target area and surrounding reference areas. It ensures that the path overlap, flight altitude, and speed meet the point cloud density and accuracy requirements.

[0093] Step 3.2, Base Station Setup

[0094] GNSS ground reference stations are set up at known coordinate points or at points where precise coordinates have been obtained through long-term static observations near the survey area.

[0095] Phase Two: Field Data Collection

[0096] Step 4: Initial state scan (baseline scan)

[0097] Step 4.1: Control the drone to take off and fly along the predetermined route.

[0098] Step 4.2: Simultaneously acquire lidar point cloud data, IMU raw data, airborne GNSS observation data, and ground reference station GNSS data.

[0099] Step 4.3, the benchmark point cloud acquired in this stage As a benchmark for subsequent changes.

[0100] For the cantilever beam model: obtain the shape of the beam when unloaded.

[0101] For the elastic foundation model: obtain the surface morphology of the material pile before applying excitation.

[0102] For vibration frequency models: brief scans are possible, primarily used to obtain geometric dimensions.

[0103] Step 5: Apply controllable stimulus

[0104] Step 5.1: Apply excitation according to the preset scheme.

[0105] Active stimulation: The drone accurately drops standard weights, or applies a known force to the target point through other means.

[0106] Passive excitation: The object to be measured is placed or suspended at the target position (such as on a crane hook).

[0107] Environmental stimulus: Wait for and confirm that the natural wind reaches a level that can induce structural vibration.

[0108] Step 6: Dynamic Response Scan (Monitoring Scan)

[0109] Step 6.1: After applying the stimulus, immediately control the UAV to perform a second flight scan (the flight path should be as consistent as possible with the first scan).

[0110] Step 6.2: Synchronously collect data from all sensors to obtain the response point cloud. .

[0111] For vibration frequency models: this step is changed to continuous scanning, using a point cloud sequence over a period of time as the data source to capture the vibration time history curve of the structure.

[0112] Phase 3: Internal Data Processing and Quality Inversion

[0113] Step 7: GNSS / IMU Integrated Navigation Solution

[0114] Step 7.1: Perform differential processing on the airborne GNSS data and the ground reference station data.

[0115] Step 7.2: Using a tightly coupled Kalman filter algorithm, the differential GNSS observations and the high-frequency angular velocity and acceleration data of the IMU are fused to calculate the high-precision position, velocity and attitude sequence of the UAV at each moment.

[0116] Step 8: Point Cloud Generation and Precise Registration

[0117] Step 8.1: Using the calculated precise trajectory and the original LiDAR data, generate a high-precision 3D reference point cloud. and response point cloud .

[0118] Step 8.2: Use precise registration algorithms such as Iterative Closest Point (ICP) to register the reference point cloud. and response point cloud Register them to the same coordinate system to eliminate any tiny residual alignment errors.

[0119] Step 9: Change Detection and Feature Extraction

[0120] Step 9.1: Perform point cloud difference calculation on the two registered point clouds to generate a three-dimensional variation vector field.

[0121] Step 9.2: Extract the feature change quantities corresponding to the model from the changing vector field. :

[0122] For the cantilever beam model: extract the maximum deflection at the end of the beam.

[0123] For the elastic foundation model: calculate the average settlement in the impact zone of the weight.

[0124] For the vibration frequency model: perform spectral analysis on the point cloud time series to extract the first-order natural frequencies of the structure.

[0125] Step 10: Physical Inversion and Mass Calculation

[0126] Step 10.1 involves extracting geometric parameters (such as L, A) from the point cloud. total The change Δ obtained in step 9 and the other steps are substituted into the preset physical inversion model.

[0127] Step 10.2, Perform the calculation

[0128] The mass of a target object can be determined using a physics inversion model, including:

[0129] The cantilever beam model used for load measurement is in the following form:

[0130] = ;

[0131] 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. 为截面惯性矩，用于描述梁截面形状和尺寸对抗弯能力影响的几何量，单位：m4，根据点云拟合出的截面尺寸计算； 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. 为重力加速度，单位：m / s2。

[0132] The elastic foundation model used for estimating bulk materials takes the following form:

[0133] = ;

[0134] 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. 为物料堆底面积，用于反映物料堆与地面接触的总投影面积，单位：m2，从基准点云中通过边界识别和面积计算得到， 为冲击影响面积，为质量块冲击引起沉降的区域面积，单位：m2，从差分点云中沉降区域的分布计算得到， 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.

[0135] The vibration frequency model used for environmental excitation has the following specific form:

[0136] = ;

[0137] 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.

[0138] Step 11: Output and Report Generation

[0139] Step 11.1, the system outputs the final quality. The measurement results.

[0140] Step 11.2: Automatically generate a weighing report, including: input parameters, intermediate observations, calculation process, final results, and accuracy assessment.

[0141] Example 2

[0142] 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:

[0143] By using an UAV-borne lidar and inertial navigation system, a reference point cloud of the target object before it is stimulated is obtained. ;

[0144] 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. ;

[0145] Reference point cloud based on inertial navigation data and response point cloud Perform precise registration;

[0146] Point cloud difference technology is used to extract the changes in the target object caused by controllable excitation. ;

[0147] Change Substituting the data into the preset physical inversion model, the mass or weight of the target object is calculated.

[0148] Example 3

[0149] 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.

[0150] 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. 为截面惯性矩，用于描述梁截面形状和尺寸对抗弯能力影响的几何量，单位：m4，根据点云拟合出的截面尺寸计算； 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. 为重力加速度，单位：m / s2。 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. 为物料堆底面积，用于反映物料堆与地面接触的总投影面积，单位：m2，从基准点云中通过边界识别和面积计算得到， 为冲击影响面积，为质量块冲击引起沉降的区域面积，单位：m2，从差分点云中沉降区域的分布计算得到， 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 precisely register 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 response point cloud of the target object 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.

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