Load measurement method, device and equipment for undercarriage of unmanned aerial vehicle, and medium

Abstract

The invention discloses an unmanned aerial vehicle undercarriage load measurement method, device and equipment and a medium, and relates to the field of unmanned aerial vehicle undercarriage load measurement, and the method comprises the steps: carrying out the ground load calibration of a target part of an unmanned aerial vehicle undercarriage; establishing a strain-load model for the target component based on the target load applied in the calibration process and the corresponding strain data; performing a flight test on the unmanned aerial vehicle to obtain flight parameter data and structural response data; aligning the two kinds of data in time; inputting strain data in the aligned structural response data into a corresponding strain-load model to obtain landing gear ground load time domain data, and determining a target maneuvering action and corresponding occurrence time of the unmanned aerial vehicle according to the aligned flight parameter data; and associating the landing gear ground load time domain data with the target maneuvering action and the corresponding occurrence time to obtain landing gear maneuvering load data, and verifying and optimizing the design of the corresponding body structure of the unmanned aerial vehicle by using the landing gear maneuvering load data.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) landing gear load measurement, and in particular to a method, apparatus, equipment and medium for measuring the load of UAV landing gear. Background Technology

[0002] As a core load-bearing component of UAVs, the landing gear's load data during actual use directly determines flight safety, maintenance efficiency, structural design optimization, aircraft performance optimization, and structural damage assessment. It is a necessary prerequisite for achieving landing gear health monitoring, predicting performance degradation, and optimizing maintenance strategies. With the rapid development of the UAV industry towards lightweight, long-endurance, and low-cost designs, some UAV landing gears adopt composite material mid-section designs without buffers. At the same time, the compact cabin space and strict modification constraints place higher demands on the accuracy, adaptability, and non-intrusiveness of load measurement.

[0003] Existing technologies for measuring UAV landing gear loads have significant limitations: some solutions employ digital twins or health monitoring systems, primarily using simulation models to analyze vibration signals and qualitatively assess landing gear health, failing to provide quantitative, continuous load spectrum data. Other solutions rely on fiber optic strain sensing and other technologies for load identification, but these are often limited to laboratory environments or specific ground tests, lacking integration with the UAV flight system and unable to capture real-world loads used in actual flight missions. Furthermore, the compact space and limited power supply of UAV cabins impose strict constraints on the size, weight, and power consumption of measurement equipment, making traditional large and complex measurement systems unsuitable for direct application. Simultaneously, UAV landing gear structures may exhibit asymmetric characteristics, and loads possess multi-axis coupling features. Existing calibration methods often struggle to establish high-precision strain-load mapping models applicable to complex real-world conditions, resulting in significant deviations between the strain-load mapping model and the actual stress scenario, leading to insufficient prediction accuracy. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method, device, equipment, and medium for measuring the load of a UAV landing gear, which can efficiently, accurately, and non-invasively achieve real-time measurement of the landing gear load of a UAV throughout its entire flight state. The specific solution is as follows:

[0005] In a first aspect, this application provides a method for measuring the load on the landing gear of an unmanned aerial vehicle (UAV), including:

[0006] Ground load calibration is performed on the target components of the UAV landing gear; wherein, during the calibration process, a target load is applied to the target components and strain data generated under the action of the target load is acquired; the target load includes unidirectional base loads along different directions, and multidimensional coupled combined loads formed by the simultaneous application of loads in at least two directions;

[0007] Based on the target load and the corresponding strain data, establish a corresponding strain-load model for each of the target components;

[0008] The UAV is tested by a pre-installed data measurement system. The data measurement system includes a flight parameter acquisition unit for acquiring flight parameters and a structural response measurement unit for collecting landing gear structural strain data and fuselage acceleration data. During the flight test, the flight parameter acquisition unit and the structural response measurement unit work independently and synchronously, respectively recording flight parameter data and structural response data containing time information.

[0009] After the UAV finishes its flight, the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data are aligned in time.

[0010] The strain data from the aligned structural response data is input into the corresponding strain-load model to obtain the landing gear ground load time domain data. Based on the aligned flight parameter data, the target maneuver of the UAV in the target phase and the corresponding occurrence time are determined; the target phase includes the take-off and landing phase and the taxiing phase.

[0011] The landing gear ground load time domain data is correlated with the target maneuver and the corresponding occurrence time to obtain landing gear maneuver load data, which is then used to verify and optimize the design of the UAV landing gear and corresponding airframe structure.

[0012] Optionally, the target component includes the main strut assembly of the first main landing gear of the UAV, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear.

[0013] During the calibration process, the main strut assembly of the first main landing gear, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear are calibrated independently, and a pre-set dummy wheel device is used to replace the real wheels to bear the calibration load.

[0014] Accordingly, applying the target load to the target component includes:

[0015] A multidimensional coupled combined load is applied to the main support component of the UAV, and a unidirectional basic load is applied to the retraction and extension actuator of the UAV.

[0016] Optionally, based on the target load and the corresponding strain data, a corresponding strain-load model is established for the main support component, including:

[0017] The multidimensional coupled combined load on the main support component is decomposed into yaw load component, spanwise load component and vertical load component.

[0018] During the calibration process, the strain signal channel corresponding to the strain data obtained from the sensors arranged on the main support assembly is defined as a candidate strain signal channel.

[0019] For any load component in any direction, enumerate the corresponding candidate strain signal channel combinations. Based on the strain data corresponding to the load component and the candidate strain signal channel combinations, establish candidate models corresponding to each candidate strain signal channel combination. Use cross-validation to evaluate the model error of the candidate models, and take the candidate model with the smallest model error as the strain-load model of the main support component in any direction, so as to obtain the strain-load model of the main support component in different directions.

[0020] Optionally, based on the target load and the corresponding strain data, a corresponding strain-load model is established for the retraction and extension actuator, including:

[0021] Based on the uniaxial foundation load and corresponding strain data of the retractable actuator, a strain-load model is established for the retractable actuator using a univariate linear regression method.

[0022] Optionally, aligning the flight parameter data and the structural response data in time using the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data includes:

[0023] Extract the first fuselage acceleration data with timestamps acquired by the flight parameter acquisition unit from the flight parameter data, and extract the second fuselage acceleration data with timestamps recorded by the acceleration sensor in the structural response measurement unit from the structural response data;

[0024] Determine the time offset between the first fuselage acceleration data and the second fuselage acceleration data;

[0025] The time axis of the flight parameter data or the structural response data is corrected based on the time offset so that the data points representing the same physical event in the flight parameter data and the structural response data coincide on the time axis.

[0026] Optionally, determining the target maneuver of the UAV during the target phase based on the aligned flight parameter data includes:

[0027] Based on preset maneuver judgment rules, the temporal change characteristics of the aligned flight parameter data are judged, and the maneuver category of the UAV in the target phase is determined according to the judgment result.

[0028] The maneuvering categories include takeoff roll, landing deceleration, symmetrical landing, asymmetrical landing, trailer towing, taxiing turn, constant speed taxiing, acceleration roll, deceleration roll, and aircraft turnaround.

[0029] Optionally, the step of verifying and optimizing the design of the UAV landing gear and corresponding airframe structure using the landing gear maneuver load data includes:

[0030] Based on the UAV's airframe structural parameters and landing gear structural parameters, and using the landing gear dynamic load data, the intersection load data of the UAV landing gear and fuselage connection node is obtained.

[0031] The design margins of the UAV landing gear and corresponding airframe structure are checked based on the intersection load data, and the structural design is optimized using the check results.

[0032] Secondly, this application provides a load measuring device for a drone landing gear, comprising:

[0033] The calibration module is used to perform ground load calibration on target components of the UAV landing gear. During the calibration process, a target load is applied to the target component, and strain data generated under the target load is acquired. The target load includes unidirectional base loads in different directions and multidimensional coupled combined loads formed by the simultaneous application of loads in at least two directions.

[0034] The model building module is used to build corresponding strain-load models for each of the target components based on the target load and the corresponding strain data.

[0035] The testing module is used to conduct flight tests on the UAV using a data measurement system pre-installed on the UAV. The data measurement system includes a flight parameter acquisition unit for acquiring flight parameters and a structural response measurement unit for collecting landing gear structural strain data and fuselage acceleration data. During the flight test, the flight parameter acquisition unit and the structural response measurement unit work independently and synchronously, respectively recording flight parameter data and structural response data containing time information.

[0036] The time alignment module is used to align the flight parameter data and the structural response data in time after the UAV has finished flying, using the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data.

[0037] The data determination module is used to input the strain data from the aligned structural response data into the corresponding strain-load model to obtain the landing gear ground load time domain data. Based on the aligned flight parameter data, it determines the target maneuver of the UAV in the target phase and the corresponding occurrence time. The target phase includes the take-off and landing phase and the taxiing phase.

[0038] The optimization module is used to correlate the landing gear ground load time domain data with the target maneuver and the corresponding occurrence time to obtain landing gear maneuver load data, so as to use the landing gear maneuver load data to verify and optimize the design of the UAV landing gear and corresponding airframe structure.

[0039] Thirdly, this application provides an electronic device, comprising:

[0040] Memory, used to store computer programs;

[0041] A processor is used to execute the computer program to implement the aforementioned method for measuring the load of the UAV landing gear.

[0042] Fourthly, this application provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned method for measuring the load of a UAV landing gear.

[0043] In this application, ground load calibration is performed on target components of a UAV landing gear. During the calibration process, target loads are applied to the target components, and strain data generated under these loads is acquired. The target loads include unidirectional base loads along different directions and multidimensional coupled loads formed by the simultaneous application of loads from at least two directions. Based on the target loads and corresponding strain data, corresponding strain-load models are established for each target component. Flight tests are conducted on the UAV using a pre-installed data measurement system. The data measurement system includes a flight parameter acquisition unit for acquiring flight parameters and a structural response measurement unit for collecting landing gear structural strain data and fuselage acceleration data. During the flight test, the flight parameter acquisition unit and the structural response measurement unit operate independently and synchronously, recording data respectively. The system includes flight parameter data and structural response data containing time information. After the UAV flight ends, the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data are aligned in time. The strain data in the aligned structural response data is input into the corresponding strain-load model to obtain the landing gear ground load time-domain data. Based on the aligned flight parameter data, the target maneuver of the UAV in the target phase and the corresponding occurrence time are determined. The target phase includes the takeoff and landing phase and the taxiing phase. The landing gear ground load time-domain data is correlated with the target maneuver and the corresponding occurrence time to obtain landing gear maneuver load data, which is used to verify and optimize the design of the UAV landing gear and corresponding airframe structure. As can be seen from the above, this application establishes strain-load models for each target component through ground load calibration, combines the structural strain data collected during flight testing, outputs quantitative landing gear ground load time-domain data, and correlates it with maneuver actions to obtain complete maneuver load data, realizing continuous and quantitative load spectrum acquisition. On the other hand, by pre-installing the data measurement system on the UAV, flight parameter data and structural response data are simultaneously collected during flight testing. Combined with the strain-load model, actual loads are calculated, avoiding the limitations of laboratory or ground tests and obtaining the loads used in real flight missions. Furthermore, the data measurement system adopts a highly integrated design where the flight parameter acquisition unit and structural response measurement unit operate independently. This allows it to adapt to the compact space and limited power supply conditions of the cabin without complex modifications, meeting the UAV's onboard measurement requirements. Simultaneously, during calibration, unidirectional base loads and multi-dimensional coupled combined loads are applied simultaneously. A separate strain-load model is established for each target component, adapting to the asymmetric characteristics of the landing gear and the multi-axis coupled load features, improving the model's fit with actual stress scenarios and prediction accuracy. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0045] Figure 1 This is a flowchart of a method for measuring the load of a UAV landing gear disclosed in this application;

[0046] Figure 2 This is a schematic diagram of the overall bridge structure and arrangement angles of a tension-compression bridge and a shear bridge disclosed in this application;

[0047] Figure 3 This is a basic connection diagram of a Wheatstone full-bridge circuit;

[0048] Figure 4 This is a schematic diagram of a main support component calibration scheme disclosed in this application;

[0049] Figure 5 This is a schematic diagram of a calibration scheme for a retractable actuator cylinder disclosed in this application;

[0050] Figure 6 This is a schematic diagram of a high-efficiency integrated system for landing gear load measurement disclosed in this application;

[0051] Figure 7 This application discloses a flowchart for identifying a type of motorized motion.

[0052] Figure 8 This is a schematic diagram of the output results after the operation of a motion recognition process disclosed in this application.

[0053] Figure 9 This is a schematic diagram of the load measuring device for a UAV landing gear disclosed in this application;

[0054] Figure 10 This is a schematic diagram of the structure of an electronic device disclosed in this application. Detailed Implementation

[0055] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0056] Existing technologies for measuring UAV landing gear loads have significant limitations: some methods primarily rely on simulation models to analyze vibration signals for qualitative assessment of landing gear health, failing to provide quantitative and continuous load spectrum data. Other methods are largely confined to laboratory environments or specific ground tests, lacking integration with the UAV flight system and thus unable to capture real-world loads used in actual flight missions. Furthermore, the compact space and limited power supply of UAV cabins impose strict constraints on the size, weight, and power consumption of measurement equipment, making traditional large and complex measurement systems difficult to apply directly. Therefore, this application provides a method for measuring UAV landing gear loads, enabling efficient, accurate, and non-invasive real-time measurement of landing gear loads across all UAV flight states, and accurately correlating load data with specific flight maneuvers.

[0057] See Figure 1 As shown in the figure, this application discloses a method for measuring the load of a UAV landing gear, including:

[0058] Step S11: Perform ground load calibration on the target component of the UAV landing gear; wherein, during the calibration process, a target load is applied to the target component and strain data generated under the action of the target load is obtained; the target load includes unidirectional base loads along different directions and multidimensional coupled combined loads formed by the simultaneous application of loads in at least two directions.

[0059] In this embodiment, the target components include the main strut assembly of the first main landing gear of the UAV, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear. During the calibration process, the main strut assembly of the first main landing gear, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear are calibrated independently, and a preset dummy wheel device is used to replace the real wheels to bear the calibration load.

[0060] Applying target loads to target components may include: applying multi-dimensional coupled combined loads to the main support assembly of the UAV, and applying unidirectional basic loads to the UAV's retraction and deployment actuators.

[0061] The following example illustrates the process of ground load calibration for target components of a drone landing gear:

[0062] The first step is to determine the strain gauge placement and bridge configuration. First, based on the landing gear load distribution characteristics and simulation analysis results, structural areas sensitive to ground load responses are selected, such as key sections of the main struts and the retraction / extension actuators, to ensure data calculation accuracy. Then, a Wheatstone full-bridge circuit is constructed using resistance strain gauges. Tension / compression bridges (sensitive to tension / compression loads) and shear bridges (sensitive to shear loads) are configured according to the force measurement requirements. Redundant spare bridge circuits are added at a 1:1 ratio, ensuring that the working and spare bridges have identical functions and participate in the test simultaneously, guaranteeing the reliability of the measurement system. Finally, the modified strain gauge bridge is connected to the airborne strain acquisition system via a standard interface to complete data acquisition preparation. For example... Figure 2 The diagram shows a tension-compression bridge sensitive to tension and compression loads, and a shear bridge sensitive to shear loads. Figure 3 The connection relationships of the resistors (R1, R2, R3, R4) and the signal output (Ug) methods for these two bridge circuits are marked.

[0063] The second step involves designing calibration conditions and specialized devices. Addressing the asymmetric load characteristics of the UAV's main landing gear, such as batch variations in structural materials and manufacturing / assembly tolerances, independent calibration of the main strut assemblies and retraction / extension actuators for both left and right main landing gears is required. Furthermore, based on the actual geometric dimensions and wheel center coordinates of the wheels, a specialized dummy wheel device can be designed to replace the original wheels in bearing the calibration load, thereby realistically replicating the mechanical response characteristics of the landing gear under typical operating conditions. A schematic diagram of the main strut assembly calibration scheme is shown below. Figure 4 As shown in the diagram, the calibration scheme for the retractable actuator is as follows: Figure 5 As shown. The load spectrum covers the entire working condition combined load domain, including unidirectional basic loads along the vertical, heading, reverse heading, and left and right sides, as well as multidimensional coupled combined loads with loads applied simultaneously in at least two directions. The test load amplitude is controlled within the range of 40% to 60% of the material yield strength, and the calibration load of the right main support is mirrored through the fuselage symmetry plane to ensure data comparability.

[0064] The third step is to conduct calibration tests and collect data. According to the preset calibration conditions, as shown in Tables 1 and 2, the target load is gradually applied to the main support and the retraction / extension actuator via the loading actuator, and the load magnitude is monitored in real time using force sensors. Strain data output from the strain gauge bridge is collected simultaneously, and the load parameters and corresponding strain response data under different load conditions are recorded to form a complete calibration dataset, providing raw data support for subsequent strain-load model construction.

[0065] Table 1 Calibration conditions for the retraction and extension actuator

[0066]

[0067] Table 2 Main Support Calibration Conditions

[0068]

[0069] Step S12: Based on the target load and the corresponding strain data, establish a corresponding strain-load model for each target component.

[0070] In this embodiment, for the strain-load model corresponding to the main support component, the multidimensional coupled combined load on the main support component can be decomposed into lateral load components, spanwise load components, and vertical load components. During calibration, the strain signal channels corresponding to the strain data obtained from sensors deployed on the main support component are defined as candidate strain signal channels. For any load component in any direction, the corresponding combinations of candidate strain signal channels are enumerated. Based on the strain data corresponding to the load components and the combinations of candidate strain signal channels, candidate models are established for each combination of candidate strain signal channels. The model error of the candidate models is evaluated using cross-validation, and the candidate model with the smallest model error is taken as the strain-load model of the main support component in any direction, thus obtaining the strain-load models of the main support component in different directions.

[0071] For the strain-load model corresponding to the retracting actuator, a strain-load model can be established based on the uniaxial foundation load and corresponding strain data of the retracting actuator, and using the univariate linear regression method.

[0072] Understandably, for the force characteristics of the main landing gear retraction and extension actuator, since its mechanical behavior is close to that of an ideal two-force member, its intersection load fitting can be directly solved using a univariate linear regression model. However, for the main strut structure, due to the significant multi-directional coupled load characteristics, in order to improve the prediction accuracy of the regression equation, a split-axis modeling strategy can be adopted, that is, establishing three independent regression models for the strain-load relationship of the main strut in the heading, spanwise, and vertical directions.

[0073] Among these methods, a high-precision linear regression model can be constructed based on the optimal subset method to solve the problem of parameter identification and accuracy optimization of the strain-load model under multi-axis coupled load scenarios of main supports. Specifically, this can include:

[0074] After decoupling the coupling effects along each axis, the parameters of the regression equation are identified and the model is validated sequentially according to the axis order. Therefore, in the entire dataset D, assume there are p predictor variables X1, X2, ..., X... p Given a response variable Y, the linear regression model is as follows:

[0075] ;

[0076] in For error terms, is the regression coefficient.

[0077] In the process of finding the optimal subset, a specific subset such as The model can be written as:

[0078] ;

[0079] The optimal subset method requires traversing all possible combinations of variables. For p predictor variables, it contains a total of There are k possible subsets. Here, K-fold cross-validation is used to randomly and uniformly divide the entire dataset D into k disjoint subsets, denoted as D1, D2, ..., Dk. k .

[0080] Use the fitted model on the validation set D i The mean squared error for prediction is:

[0081] ;

[0082] in, Let be the number of samples in the i-th fold. For the true value, These are predicted values.

[0083] Then, the average of the validation errors calculated in the k iterations is used to obtain the k-fold cross-validation error of the variable subset S:

[0084] ;

[0085] Compare the CV values ​​of all subsets and select the subset with the smallest CV value. As the optimal subset:

[0086] ;

[0087] Therefore, the desired linear regression model is:

[0088] .

[0089] Step S13: Conduct flight tests on the UAV using a pre-installed data measurement system. The data measurement system includes a flight parameter acquisition unit for acquiring flight parameters and a structural response measurement unit for collecting landing gear structural strain data and fuselage acceleration data. During the flight test, the flight parameter acquisition unit and the structural response measurement unit work independently and synchronously, respectively recording flight parameter data and structural response data containing time information.

[0090] This embodiment provides a highly efficient integrated system for landing gear load measurement, for example... Figure 6 As shown, it includes a flight parameter acquisition unit and a structural response measurement unit; the structural response measurement unit includes a structural response sensing unit and a structural response storage unit. Figure 6 The tension / compression / shear full-bridge strain gauge and acceleration sensor are the core components of the structural response sensing unit.

[0091] The structural response storage unit employs an independent power supply module and physical isolation design to safely store the response data of the full-bridge strain gauges on the landing gear structure and the acceleration response data within the fuselage section. Addressing the engineering constraints of limited space in the UAV cabin, this unit features a highly integrated design, characterized by its small size, robustness, abundant channels, large storage capacity, and long endurance.

[0092] The structural response sensing unit comprises a Wheatstone full-bridge strain gauge array, a high-precision accelerometer, and its associated signal conditioning circuitry. The Wheatstone full-bridge strain gauges are installed at key sections of the main landing gear struts and the retraction / extension actuator cylinder to synchronously acquire the combined load response of axial tension / compression and lateral shear forces. Each section of the main strut, such as the working section and the backup section, contains at least two sets of shear bridges and at least two sets of tension / compression bridges. Each section of the retraction / extension actuator cylinder contains at least one set of shear bridges and at least one set of tension / compression bridges. The accelerometer is placed near the fuselage inertial navigation system; its measurement data is used for manual verification of flight parameter overload data, and a timestamp alignment algorithm is used to synchronize the flight parameter system with the structural response storage unit in the time domain.

[0093] It should be noted that, considering the compact layout and limited capacity within the UAV cabin, a highly integrated structural response storage unit is adopted. Through optimized design, each full-bridge circuit occupies only one channel, significantly reducing the size and weight of the equipment. To avoid interference from load testing on flight functions, a timing alignment method based on the inertial navigation system's acceleration signal is used: cross-validation is performed using the inertial navigation system's built-in timestamp and the sampling trigger signal of the structural response storage unit. This eliminates the need for physical connections or logical modifications to the aircraft's functional systems, thereby removing a series of complex compatibility verification processes such as modification, debugging, and safety analysis verification of temporary installation equipment and the original system, minimizing the impact of landing gear load testing on the aircraft's preset functions. This design, through a non-intrusive integration scheme, minimizes the impact of load testing on the aircraft's preset functions while meeting data validity requirements.

[0094] Once installed, the data measurement system can be used for flight load testing. During flight load testing, data such as flight parameters, structural response, and time are acquired.

[0095] Step S14: After the UAV finishes its flight, the flight parameter data and the structural response data are aligned in time using the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data.

[0096] Since the flight parameter acquisition unit and the structural response storage unit do not achieve real-time data communication, it is necessary to align the acceleration response data stored in their respective systems to achieve time correspondence between the two systems.

[0097] This process involves aligning the flight parameter data and structural response data in time using fuselage acceleration data from both the flight parameter data and structural response data. This can include: extracting first fuselage acceleration data (including timestamps) acquired by the flight parameter acquisition unit from the flight parameter data, and extracting second fuselage acceleration data (including timestamps) recorded by the acceleration sensor in the structural response measurement unit from the structural response data. Then, the time offset between the first and second fuselage acceleration data is determined. Finally, the time axis of the flight parameter data or structural response data is corrected based on the time offset to ensure that data points representing the same physical event in both data coincide on the time axis.

[0098] Step S15: Input the strain data in the aligned structural response data into the corresponding strain-load model to obtain the landing gear ground load time domain data. Based on the aligned flight parameter data, determine the target maneuver of the UAV in the target phase and the corresponding occurrence time; the target phase includes the take-off and landing phase and the taxiing phase.

[0099] In this embodiment, the strain data in the aligned structural response data is input into the corresponding strain-load model to obtain the time-domain data of the landing gear ground load during flight (considering the characteristics of landing gear use, this mainly refers to the load during takeoff and landing).

[0100] Based on the aligned flight parameter data, the target maneuver of the UAV in the target phase can be determined, which may include: judging the temporal change characteristics of the aligned flight parameter data based on the preset maneuver judgment rules, and determining the type of maneuver of the UAV in the target phase based on the judgment result; wherein, the maneuver type includes, but is not limited to, take-off roll, landing deceleration, symmetrical landing, asymmetrical landing, trailer towing, taxiing turn, constant speed taxiing, acceleration roll, deceleration roll, and aircraft turn.

[0101] For example Figure 7The flowchart shown illustrates the maneuver identification process. Taking flight parameters such as wheel speed increase / decrease, ground speed increase / decrease, propeller speed, braking signal, nose wheel turning signal, and heading / turning signal as input, it focuses on the critical stages of UAV takeoff and landing—the two phases where landing gear loads are prone to sudden changes. By comprehensively judging the parameter matrix formed by the coordinated changes of the above parameters, it identifies core operating conditions such as landing impact, sudden stop during takeoff, and ground taxiing / turning. It can classify and output typical maneuvers such as takeoff takeoff, landing deceleration, symmetrical / asymmetrical landing, trailer towing, taxiing / turning, constant speed taxiing, deceleration takeoff, and aircraft turning. The related identification program is developed based on Matlab.

[0102] Figure 8 for Figure 7 The actual output results after the operation of the maneuver identification process provide a detailed representation of the key basic information of a single flight mission, such as the flight parameter start time 2025-04-13 09:32:27.310000, takeoff time 10:08:37.116939, landing time 10:31:15.626909, maximum impact value 2.5198, and corresponding times. It also includes motion segments based on wheel speed, such as labeled sample size, number of non-zero values, wheel speed increase / decrease indicators, start / end ground speed, average propeller speed, braking status, start / end time, motion duration, and distance traveled. It also includes turning maneuvers identified by the front wheel turning signal, such as turn start / end sequence number, left / right indicators, duration, upper and lower limits of turn amount, start / end time, presence of taxiing, and sample size. Finally, it includes steering maneuvers identified by the heading signal, such as turn start / end sequence number, sample size, duration, start / end angle, apex angle, peak angle, start / end time, and corresponding taxiing state. This provides a crucial time dimension and action type basis for the precise correlation between subsequent landing gear ground load time-domain data and specific maneuvers.

[0103] Step S16: Correlate the landing gear ground load time domain data with the target maneuver and the corresponding occurrence time to obtain landing gear maneuver load data, so as to verify and optimize the design of the UAV landing gear and corresponding airframe structure using the landing gear maneuver load data.

[0104] In this embodiment, the landing gear ground load time domain data is correlated with the aircraft maneuvering motion to obtain more accurate landing gear maneuvering load data.

[0105] Furthermore, the design of the UAV landing gear and corresponding airframe structure can be verified and optimized using landing gear maneuver load data. This can include: obtaining the intersection load data of the connection nodes between the UAV landing gear and the fuselage based on the UAV's airframe structural parameters and landing gear structural parameters, using the landing gear maneuver load data. Then, the design margin of the UAV landing gear and corresponding airframe structure is checked based on the intersection load data, and the structural design is optimized using the check results.

[0106] As shown above, this embodiment fully considers the asymmetric working conditions and multi-axis coupled force characteristics of the UAV landing gear during the calibration phase. A high-precision strain-load model is constructed by independently calibrating the left and right main struts and the retraction / extension actuators, using dummy wheels to simulate real forces, applying combined loads, and combining the optimal subset method for variable selection and axis-specific modeling. Secondly, in terms of data fusion, time-domain alignment between systems is achieved through cross-correlation analysis of flight parameter overload spectra and strain response spectra. Furthermore, based on an automatic maneuver identification program, more than ten flight maneuvers during takeoff and landing are directly correlated with measured load spectra, solving the problem of load event tracing. Simultaneously, based on high-precision full-state ground load data and known aircraft structural parameters, the load spectrum at the intersection of the main landing gear and fuselage is derived, which can be directly used to verify structural design margins, optimize life prediction, and significantly shorten the model iteration cycle.

[0107] See Figure 9 As shown in the figure, this application also discloses a load measuring device for the landing gear of an unmanned aerial vehicle (UAV), comprising:

[0108] The calibration module 11 is used to perform ground load calibration on the target component of the UAV landing gear; wherein, during the calibration process, a target load is applied to the target component and strain data generated under the action of the target load is acquired; the target load includes unidirectional base loads along different directions and multidimensional coupled combined loads formed by the simultaneous application of loads in at least two directions;

[0109] Model building module 12 is used to build corresponding strain-load models for each of the target components based on the target load and the corresponding strain data;

[0110] Test module 13 is used to conduct flight tests on the UAV through a data measurement system pre-installed on the UAV; the data measurement system includes a flight parameter acquisition unit for acquiring flight parameters, and a structural response measurement unit for collecting landing gear structure strain data and fuselage acceleration data; during the flight test, the flight parameter acquisition unit and the structural response measurement unit work independently and synchronously, respectively recording flight parameter data and structural response data containing time information;

[0111] The time alignment module 14 is used to align the flight parameter data and the structural response data in time after the UAV has finished flying, using the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data.

[0112] The data determination module 15 is used to input the strain data in the aligned structural response data into the corresponding strain-load model to obtain the landing gear ground load time domain data, and determine the target maneuver of the UAV in the target phase and the corresponding occurrence time based on the aligned flight parameter data; the target phase includes the take-off and landing phase and the taxiing phase;

[0113] The optimization module 16 is used to correlate the landing gear ground load time domain data with the target maneuver and the corresponding occurrence time to obtain landing gear maneuver load data, so as to use the landing gear maneuver load data to verify and optimize the design of the UAV landing gear and corresponding airframe structure.

[0114] In some specific embodiments, the target component includes the main strut assembly of the first main landing gear of the UAV, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear.

[0115] During the calibration process, the main strut assembly of the first main landing gear, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear are calibrated independently, and a pre-set dummy wheel device is used to replace the real wheels to bear the calibration load.

[0116] Accordingly, the calibration module 11 includes:

[0117] The load application unit is used to apply a multi-dimensional coupled combined load to the main support component of the UAV and to apply a unidirectional basic load to the retraction and extension actuator of the UAV.

[0118] In some specific embodiments, the model building module 12 includes:

[0119] The load decomposition unit is used to decompose the multidimensional coupled combined loads on the main strut assembly into yaw load components, spanwise load components, and vertical load components.

[0120] The channel determination unit is used to define the strain signal channel corresponding to the strain data obtained by the sensors arranged on the main support assembly during the calibration process as a candidate strain signal channel.

[0121] The first model building unit is used to enumerate the corresponding candidate strain signal channel combinations for any load component in any direction, establish candidate models corresponding to each candidate strain signal channel combination based on the strain data corresponding to the load component and the candidate strain signal channel combination, evaluate the model error of the candidate models using cross-validation, and take the candidate model with the smallest model error as the strain-load model of the main support component in any direction, so as to obtain the strain-load model of the main support component in different directions.

[0122] In some specific embodiments, the model building module 12 includes:

[0123] The second model building unit is used to build a corresponding strain-load model for the retractable actuator based on the unidirectional foundation load and corresponding strain data of the retractable actuator and using the univariate linear regression method.

[0124] In some specific embodiments, the time alignment module 14 includes:

[0125] The data extraction unit is used to extract first fuselage acceleration data with timestamps acquired by the flight parameter acquisition unit from the flight parameter data, and to extract second fuselage acceleration data with timestamps recorded by the acceleration sensor in the structural response measurement unit from the structural response data.

[0126] An offset determination unit is used to determine the time offset between the first fuselage acceleration data and the second fuselage acceleration data;

[0127] The time axis correction unit is used to correct the time axis of the flight parameter data or the structural response data based on the time offset, so that the data points representing the same physical event in the flight parameter data and the structural response data coincide on the time axis.

[0128] In some specific embodiments, the data determination module 15 includes:

[0129] The judgment unit is used to judge the temporal change characteristics of the aligned flight parameter data based on the preset maneuver judgment rules, and determine the type of maneuver of the UAV in the target phase according to the judgment result.

[0130] The maneuvering categories include takeoff roll, landing deceleration, symmetrical landing, asymmetrical landing, trailer towing, taxiing turn, constant speed taxiing, acceleration roll, deceleration roll, and aircraft turnaround.

[0131] In some specific embodiments, the optimization module 16 includes:

[0132] The data acquisition unit is used to obtain the intersection load data of the connection node between the UAV landing gear and the fuselage based on the UAV's airframe structural parameters and landing gear structural parameters, and using the landing gear motor load data.

[0133] The verification unit is used to verify the design margin of the UAV landing gear and corresponding airframe structure based on the intersection load data, and to optimize the structural design using the verification results.

[0134] Furthermore, embodiments of this application also disclose an electronic device, Figure 10 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0135] Figure 10 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the unmanned aerial vehicle landing gear load measurement method disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0136] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0137] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0138] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the unmanned aerial vehicle landing gear load measurement method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0139] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned method for measuring the load of the UAV landing gear. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0140] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0141] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0142] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0143] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0144] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for measuring the load on the landing gear of an unmanned aerial vehicle (UAV), characterized in that, include: Ground load calibration is performed on the target components of the UAV landing gear; wherein, during the calibration process, a target load is applied to the target components and strain data generated under the action of the target load is acquired; the target load includes unidirectional base loads along different directions, and multidimensional coupled combined loads formed by the simultaneous application of loads in at least two directions; Based on the target load and the corresponding strain data, establish a corresponding strain-load model for each of the target components; The UAV is subjected to flight testing using a pre-installed data measurement system. The data measurement system includes a flight parameter acquisition unit for acquiring flight parameters and a structural response measurement unit for collecting landing gear structural strain data and fuselage acceleration data. During the flight test, the flight parameter acquisition unit and the structural response measurement unit work independently and synchronously, respectively recording flight parameter data and structural response data containing time information. After the UAV finishes its flight, the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data are aligned in time. The strain data from the aligned structural response data is input into the corresponding strain-load model to obtain the landing gear ground load time domain data. Based on the aligned flight parameter data, the target maneuver of the UAV in the target phase and the corresponding occurrence time are determined; the target phase includes the take-off and landing phase and the taxiing phase. The landing gear ground load time domain data is correlated with the target maneuver and the corresponding occurrence time to obtain landing gear maneuver load data, which is then used to verify and optimize the design of the UAV landing gear and corresponding airframe structure.

2. The method for measuring the load of a UAV landing gear according to claim 1, characterized in that, The target components include the main strut assembly of the first main landing gear of the UAV, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear. During the calibration process, the main strut assembly of the first main landing gear, the retraction and extension actuator of the first main landing gear, the main strut assembly of the second main landing gear, and the retraction and extension actuator of the second main landing gear are calibrated independently, and a pre-set dummy wheel device is used to replace the real wheels to bear the calibration load. Accordingly, applying the target load to the target component includes: A multidimensional coupled combined load is applied to the main support component of the UAV, and a unidirectional basic load is applied to the retraction and extension actuator of the UAV.

3. The method for measuring the load of a UAV landing gear according to claim 2, characterized in that, Based on the target load and the corresponding strain data, a corresponding strain-load model is established for the main support component, including: The multidimensional coupled combined load on the main support component is decomposed into yaw load component, spanwise load component and vertical load component. During the calibration process, the strain signal channel corresponding to the strain data obtained from the sensors arranged on the main support assembly is defined as a candidate strain signal channel. For any load component in any direction, enumerate the corresponding candidate strain signal channel combinations. Based on the strain data corresponding to the load component and the candidate strain signal channel combinations, establish candidate models corresponding to each candidate strain signal channel combination. Use cross-validation to evaluate the model error of the candidate models, and take the candidate model with the smallest model error as the strain-load model of the main support component in any direction, so as to obtain the strain-load model of the main support component in different directions.

4. The method for measuring the load of a UAV landing gear according to claim 2, characterized in that, Based on the target load and the corresponding strain data, a strain-load model is established for the extension and retraction actuator, including: Based on the uniaxial foundation load and corresponding strain data of the retractable actuator, a strain-load model is established for the retractable actuator using a univariate linear regression method.

5. The method for measuring the load of a UAV landing gear according to claim 1, characterized in that, The step of aligning the flight parameter data and the structural response data in time using the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data includes: Extract the first fuselage acceleration data with timestamps acquired by the flight parameter acquisition unit from the flight parameter data, and extract the second fuselage acceleration data with timestamps recorded by the acceleration sensor in the structural response measurement unit from the structural response data; Determine the time offset between the first fuselage acceleration data and the second fuselage acceleration data; The time axis of the flight parameter data or the structural response data is corrected based on the time offset so that the data points representing the same physical event in the flight parameter data and the structural response data coincide on the time axis.

6. The method for measuring the load of a UAV landing gear according to claim 1, characterized in that, The step of determining the target maneuver of the UAV in the target phase based on the aligned flight parameter data includes: Based on preset maneuver judgment rules, the temporal change characteristics of the aligned flight parameter data are judged, and the maneuver category of the UAV in the target phase is determined according to the judgment result. The maneuvering categories include takeoff roll, landing deceleration, symmetrical landing, asymmetrical landing, trailer towing, taxiing turn, constant speed taxiing, acceleration roll, deceleration roll, and aircraft turnaround.

7. The method for measuring the load of a UAV landing gear according to any one of claims 1 to 6, characterized in that, The process of verifying and optimizing the design of the UAV landing gear and corresponding airframe structure using the landing gear maneuver load data includes: Based on the UAV's airframe structural parameters and landing gear structural parameters, and using the landing gear dynamic load data, the intersection load data of the UAV landing gear and fuselage connection node is obtained. The design margins of the UAV landing gear and corresponding airframe structure are checked based on the intersection load data, and the structural design is optimized using the check results.

8. A load measuring device for the landing gear of an unmanned aerial vehicle (UAV), characterized in that, include: The calibration module is used to perform ground load calibration on target components of the UAV landing gear. During the calibration process, a target load is applied to the target component, and strain data generated under the target load is acquired. The target load includes unidirectional base loads in different directions and multidimensional coupled combined loads formed by the simultaneous application of loads in at least two directions. The model building module is used to build corresponding strain-load models for each of the target components based on the target load and the corresponding strain data. The testing module is used to conduct flight tests on the UAV using a data measurement system pre-installed on the UAV. The data measurement system includes a flight parameter acquisition unit for acquiring flight parameters and a structural response measurement unit for collecting landing gear structural strain data and fuselage acceleration data. During the flight test, the flight parameter acquisition unit and the structural response measurement unit work independently and synchronously, respectively recording flight parameter data and structural response data containing time information. The time alignment module is used to align the flight parameter data and the structural response data in time after the UAV has finished flying, using the fuselage acceleration data in the flight parameter data and the fuselage acceleration data in the structural response data. The data determination module is used to input the strain data from the aligned structural response data into the corresponding strain-load model to obtain the landing gear ground load time domain data. Based on the aligned flight parameter data, it determines the target maneuver of the UAV in the target phase and the corresponding occurrence time. The target phase includes the take-off and landing phase and the taxiing phase. The optimization module is used to correlate the landing gear ground load time domain data with the target maneuver and the corresponding occurrence time to obtain landing gear maneuver load data, so as to use the landing gear maneuver load data to verify and optimize the design of the UAV landing gear and corresponding airframe structure.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the method for measuring the load of the unmanned aerial vehicle landing gear as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the method for measuring the load of the UAV landing gear as described in any one of claims 1 to 7.

Images