Method and system for compiling a center of gravity overload spectrum of a compound wing transport unmanned aerial vehicle, and readable storage medium

Abstract

This invention provides a method, system, and storage medium for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV, solving the problem that existing load spectra are not suitable for compound-wing configurations. The method divides typical mission profiles into four load units based on measured flight data: vertical takeoff, transition flight, cruise, and landing. It compiles the center-of-gravity overload time history sequence for each segment, statistically analyzes the overload frequency, and determines the standard spectrum length, ultimately using it for structural fatigue life analysis and experimental loading. This invention closely matches the actual load characteristics of compound-wing UAVs, fills a gap in industry standard spectra, supports structural fatigue assessment and airworthiness verification, and has strong versatility and engineering applicability.

Description

Technical Field

[0001] This invention relates to the field of aircraft structural load spectrum compilation and fatigue life assessment technology, and in particular to a method, system and readable storage medium for compiling the center of gravity overload spectrum of a compound wing transport unmanned aerial vehicle. Background Technology

[0002] Damage tolerance and fatigue life design of aircraft structures are highly dependent on load spectrum data, with the flight load spectrum considered an abstract expression of the aircraft's main operating conditions. Currently, commonly used load spectrum compilation methods are typically based on mission profile analysis: by identifying typical flight missions and their flight phases, the duration and state parameters of each phase are statistically analyzed to compile the corresponding load sequences. For example, mature standard load spectra are available for fixed-wing aircraft and helicopters. However, in the field of compound-wing vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs), there is currently a lack of standard center-of-gravity overload spectra for this novel configuration. Directly using traditional fixed-wing and rotary-wing aircraft load spectra due to significant differences in flight characteristics leads to incompatibility issues: fixed-wing aircraft experience relatively stable loads during the cruise phase, while rotary-wing aircraft's rotor components endure high-cycle, low-amplitude alternating load environments. Compound-wing UAVs combine fixed-wing and rotary-wing flight modes, with a large span between takeoff and landing and cruise conditions; existing spectra cannot fully cover their load characteristics. Furthermore, as compound-wing UAVs are gradually put into practical use, it has become very urgent to construct a load spectrum that accurately reflects the actual usage conditions using flight test data, in order to support structural fatigue life assessment and airworthiness requirements.

[0003] Therefore, it is necessary to study a method, system, and readable storage medium for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV to address the shortcomings of existing technologies and solve or mitigate one or more of the aforementioned problems. Summary of the Invention

[0004] In view of this, the present invention provides a method, system, and readable storage medium for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV, solving the problem that existing load spectra are not suitable for compound-wing configurations. The method divides typical mission profiles into four load units based on measured flight data: vertical takeoff, transition flight, cruise, and landing. It compiles the center-of-gravity overload time history sequence for each segment, statistically analyzes the overload frequency, and determines the standard spectrum length, ultimately using it for structural fatigue life analysis and experimental loading. This invention closely matches the actual load characteristics of compound-wing UAVs, fills a gap in industry standard spectra, supports structural fatigue assessment and airworthiness verification, and has strong versatility and engineering applicability.

[0005] On one hand, the present invention provides a method for compiling the center-of-gravity overload spectrum of a compound-wing transport unmanned aerial vehicle, comprising: S1. Acquire measured flight data and analyze typical mission profiles; S2. Divide the mission profile into four payload units: vertical takeoff segment, transition flight segment, cruise segment, and landing segment. S3. Compile a corresponding center of gravity overload time history sequence for each load unit; S4. Statistically analyze the frequency of occurrence of each overload level and determine the standard spectrum length of the corresponding scheduled mission to complete the compilation of the UAV center of gravity overload spectrum; S5. Conduct structural fatigue life analysis and test loading based on the standard spectrum.

[0006] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the acquisition of measured flight data and analysis of typical mission profiles in S1 includes: S11. Collect flight parameters of the UAV in vertical take-off and landing and fixed-wing switching modes; S12. Calculate the duration and status changes of each flight phase based on flight parameters; S13. Organize all flight data to form a standardized mission profile description file; S14. Verify the effectiveness of the mission profile to ensure that the profile covers all major flight conditions of the UAV.

[0007] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the mission profile in S2 is divided into four payload units: a vertical takeoff segment, a transition flight segment, a cruise segment, and a landing segment, including: S21. Define the characteristics of the sharp increase in overload during the vertical takeoff phase; S22. Define the attitude adjustment transition characteristics of the flight transition segment; S23. Define the smooth fluctuation characteristics of the cruise segment; S24. Define the ground impact characteristics of the landing phase and complete the precise division of the four load units.

[0008] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the S3 process compiles a corresponding center-of-gravity overload time history sequence for each load element, including: S31. Generate the overload surge sequence corresponding to the vertical takeoff segment; S32. Generate the attitude transition sequence corresponding to the flight transition segment; S33. Generate a stationary fluctuation sequence corresponding to the cruise segment; S34. Generate the load recovery sequence corresponding to the landing phase; S35. According to the flight time sequence, splice together the overload sequences of each segment to form the initial center of gravity overload time history sequence.

[0009] As described above and in any possible implementation, a further implementation is provided in which the compilation of a corresponding center-of-gravity overload time history sequence for each load element in S3 further includes: S36. Extract the overload value range of each flight load unit; S37. Simulate the random variation characteristics of loads caused by atmospheric turbulence; S38. Adjust the overload sequence parameters based on measured statistical data to ensure data matching; S39. Output the complete center of gravity overload time history sequence file after calibration.

[0010] As described above and in any possible implementation, a further implementation is provided in which the S4 step of counting the frequency of each overload level and determining the standard spectrum length corresponding to a predetermined sortie mission includes: S41. The frequency of occurrence of low-frequency statistical loads close to the reference value and preset loads, wherein the preset loads are conventional loads; S42. Statistically analyze the distribution pattern of moderate amplitude overload during flight; S43. Centralize and control the distribution of high-amplitude overload events at the tail of the standard spectrum; S44. Accumulate the number of overload cycles at each level to form the standard spectrum length corresponding to the predetermined mission.

[0011] As described above and in any possible implementation, a further implementation is provided, wherein S4, which involves counting the frequency of occurrence of each overload level and determining the standard spectrum length corresponding to a predetermined sortie mission, further includes: S45. Divide the overload level range into multiple levels according to the load amplitude; S46. Accurately calculate the number of load cycles corresponding to each overload level; S47. Verify the frequency of each level of load to ensure it matches the actual operating conditions of the drone. S48. Summarize all cyclic data and generate the total cyclic data for the standard spectrum.

[0012] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the structural fatigue life analysis and experimental loading based on the standard spectrum in S5 includes: S51. The number of times the standard spectrum is applied is proportionally increased according to the preset test frame ratio. S52. Apply the amplified overload time series to the UAV test specimen to complete the loading test; S53. Real-time monitoring of test status and recording of cumulative damage data of the UAV structure; S54. Compare the cumulative damage data with the design life requirements of the UAV to complete the life verification and verify whether the structure meets the design life requirements.

[0013] As described above and in any possible implementation, a system for compiling the center-of-gravity overload spectrum of a compound-wing transport unmanned aerial vehicle is further provided, the system comprising: The mission profile analysis module is used to acquire UAV measured flight data, statistically analyze flight status and duration, and generate and verify typical mission profiles covering all operating conditions. The load unit division module is used to divide the mission profile into four independent load units based on the overload characteristics, attitude characteristics, and impact characteristics of each flight segment. The overload sequence compilation module is used to generate the basic overload sequence for each load unit, simulate turbulent random loads and calibrate and match measured data, and output a complete history sequence. The standard spectrum construction module is used to divide overload level intervals, count load frequency and cycle number, reasonably distribute high amplitude loads, and generate standard overload spectra for the corresponding predetermined flights. The fatigue test analysis module is used to scale up the standard spectrum, load the test piece, collect cumulative structural damage data, and verify the fatigue life of the UAV structure.

[0014] In addition to the aspects described above and any possible implementation, a computer-readable storage medium is further provided, wherein a computer-executable program is stored therein, which, when invoked by a processor, implements all the steps of the method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV.

[0015] Compared with the prior art, the present invention can achieve the following technical effects: 1. Filling the gap in the standard for payload spectrum of compound-wing UAVs: For the first time, a complete system for compiling the center of gravity overload spectrum is established for compound-wing transport UAVs that can switch from vertical take-off and landing to fixed wing configuration. This solves the problem that the traditional load spectrum of fixed wing and rotor is not applicable and provides a unified basis for structural fatigue design and life assessment.

[0016] 2. Load characteristics closely match real flight conditions: Based on measured flight data, four typical load units are divided to accurately reproduce the full-process overload characteristics of vertical takeoff steep increase, transition phase, cruise phase smooth fluctuation, and landing phase ground impact. At the same time, atmospheric turbulence random loads are incorporated to greatly improve the authenticity and accuracy of the load spectrum.

[0017] 3. Standard spectrum is quantifiable, scalable, and highly engineering-oriented: A predetermined standard spectrum is formed through overload classification, frequency statistics, and cycle counting. It can be scaled up proportionally according to test requirements, supports direct loading in fatigue tests, and significantly improves the efficiency and reliability of structural fatigue life analysis.

[0018] 4. Support structure optimization and airworthiness certification: It can provide precise load input for the whole aircraft and key load-bearing components, effectively reduce structural design redundancy, improve the level of structural lightweighting, and meet the requirements of aircraft damage tolerance, fatigue strength and airworthiness certification.

[0019] 5. High versatility and adaptability: The sequence parameters and cycle ratio can be flexibly adjusted according to different mission profiles, environmental conditions, and load states, making it suitable for multiple models and scenarios of compound wing transport drones and possessing broad engineering application value.

[0020] Of course, any product implementing this invention does not necessarily need to achieve all of the technical effects described above at the same time. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a graph of the center of gravity overload exceedance number in the vertical takeoff segment of the method for compiling the center of gravity overload spectrum of a compound wing transport UAV provided in an embodiment of the present invention. Figure 2 This is a graph of the overload number of the center of gravity in the transition segment of the method for compiling the overload spectrum of the center of gravity of a compound-wing transport UAV provided in an embodiment of the present invention. Figure 3 This is a cruise phase center of gravity overload exceedance number curve in the method for compiling the center of gravity overload spectrum of a compound wing transport UAV provided in an embodiment of the present invention; Figure 4 This is a curve of the center of gravity overload exceedance number during the landing phase in the method for compiling the center of gravity overload spectrum of a compound wing transport UAV provided in an embodiment of the present invention; Figure 5 This is a typical load spectrum diagram of the vertical takeoff segment in the method for compiling the center of gravity overload spectrum of a compound wing transport UAV provided in an embodiment of the present invention; Figure 6 This is a typical load spectrum diagram of the transition segment in the method for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV provided in an embodiment of the present invention; Figure 7 This is a typical load spectrum diagram of the cruise segment in the method for compiling the center of gravity overload spectrum of a compound wing transport UAV provided in an embodiment of the present invention; Figure 8 This is a typical load spectrum diagram of the landing phase in the method for compiling the center of gravity overload spectrum of a compound wing transport UAV provided in an embodiment of the present invention; Figure 9This is a general spectrum diagram in the method for compiling the center of gravity overload spectrum of a compound wing transport UAV provided in an embodiment of the present invention; (100 takeoff and landing). Detailed Implementation

[0023] To better understand the technical solution of the present invention, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0024] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0025] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0026] This invention provides a method for analyzing the structural fatigue life of an unmanned aerial vehicle (UAV) based on measured flight data, and a method for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV. The method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV includes: Step S1: Acquire measured flight data and analyze typical mission profiles. Step S11: Collect flight parameters of the UAV in vertical takeoff and landing (VTOL) and fixed-wing transition modes. In one embodiment, flight parameters include lift acceleration, attitude angular velocity, and altitude change rate during VTOL, and forward velocity, roll angle, and pitch angle data during fixed-wing transition. These parameters are recorded in real time by onboard sensors positioned near the UAV's center of gravity to ensure data accuracy. Step S12: Statistically analyze the duration and state changes of each stage based on the parameters. Specifically, the duration of the VTOL stage is typically between 30 seconds and 2 minutes, the attitude adjustment time during the transition phase is between 10 and 40 seconds, the stable flight time during the cruise phase can reach tens of minutes depending on mission requirements, and the touchdown process during the descent phase is controlled between 5 and 15 seconds. Step S13: Organize the data to form a mission profile description file. The mission profile description file records the flight state parameters of each stage in a time-series format. For example, the peak lift during VTOL and the attitude transition curve during the transition phase are integrated into a unified format file for easy use in subsequent load analysis. Step S14: Verify that the profile covers all major operating conditions. In one possible implementation, the profile is checked by comparing multiple flight test data to ensure that it includes flight conditions under environmental conditions such as high temperature, high humidity, and strong winds, thus ensuring that the profile can represent typical mission scenarios and avoiding analysis bias caused by the omission of extreme operating conditions.

[0027] Step S2 divides the mission profile into four payload units: vertical takeoff, transition flight, cruise, and landing. Step S21 defines the steep increase in overload during the vertical takeoff phase. This is characterized by a sudden increase in lift, causing the center of gravity overload to rise rapidly from zero to more than 1.5 times the acceleration due to gravity. This characteristic is most pronounced at the moment the UAV takes off from the ground, and the rate of change of overload needs to be carefully captured to reflect the takeoff impact. Step S22 defines the attitude adjustment transition characteristics during the transition flight phase. This is reflected in the continuous changes in roll and pitch angles, with the overload gradually transitioning from a steep increase to a smooth fluctuation. The transition time is typically controlled to around twenty seconds to match the establishment of the fixed-wing flight mode. Step S23 defines the smooth fluctuation characteristics during the cruise phase. The cruise phase is characterized by smooth fluctuations with the center of gravity overload oscillating slightly between 0.8 and 1.2 times the acceleration due to gravity, primarily caused by atmospheric turbulence. The fluctuation period ranges from five to thirty seconds. The average overload level needs to be recorded to support subsequent fatigue accumulation calculations. Step S24 defines the ground impact characteristics of the descent phase. The ground impact characteristics of the descent phase are characterized by a sharp increase in overload to more than twice the acceleration due to gravity at the moment of impact, followed by a rapid decline. This characteristic directly affects the stress concentration at the fuselage structural connections, requiring precise marking of the ground impact moment to extract the peak impact value.

[0028] Step S3: Compile a corresponding center-of-gravity overload time history sequence for each load unit. Step S31: Generate a steep increase sequence for the vertical takeoff phase. This sequence is formed by interpolating measured lift data. Starting from the initial takeoff moment, the overload value increases at a rate of 0.5 times the acceleration due to gravity per second until it reaches a peak and then remains briefly stable. The sequence length corresponds to the actual takeoff duration. Step S32: Generate a transition sequence for the transition flight phase. This sequence smoothly connects the overload changes during attitude adjustment. Starting from the overload value at the end of the vertical takeoff phase, it gradually decreases to the cruise level, with additional overload components caused by attitude angle changes inserted in between to ensure the sequence is continuous without abrupt changes. Step S33: Generate a fluctuation sequence for the cruise phase. This sequence is generated based on a turbulence statistical model. The overload fluctuates randomly around a baseline value, with fluctuation amplitude not exceeding 0.3 times the acceleration due to gravity. The sequence contains multiple periodic oscillations to simulate the cumulative effect during long-term cruise. Step S34: Generate a recovery sequence for the landing phase. The recovery sequence begins with the stable value of the cruise phase, gradually introducing an increase in G-force due to descent speed within the five seconds before touchdown. It peaks at touchdown and then rapidly decays to zero. A low-amplitude G-force during ground taxiing is added at the end of the sequence to fully cover the descent process. Step S35 involves stitching the sequences together chronologically. During stitching, the end of the steep increase sequence in the vertical takeoff phase is aligned with the starting point of the transition sequence in the flight transition phase. The cruise phase fluctuation sequence and the descent recovery sequence are then connected sequentially to form a complete mission profile of the center-of-gravity G-force time history sequence file. This file directly serves as input data for subsequent frequency statistics.

[0029] In this invention, S21-S24 are the "feature definition" steps, which belong to the load unit division stage. They aim to clarify the load characteristics and boundaries of the four load units: vertical takeoff, transition flight, cruise, and landing. They only provide a qualitative description of the overload change characteristics of each stage and do not generate any overload time series.

[0030] S31-S34 are the "sequence generation" steps, which belong to the overload sequence compilation stage. Based on the feature definition in S2, they quantitatively generate the center of gravity overload time history sequence corresponding to each load unit, providing a data basis for subsequent statistical analysis.

[0031] Step S4: Count the frequency of each overload level and determine the standard spectrum length corresponding to the predetermined flight mission.

[0032] Step S41: Count the frequency of loads close to the baseline value. The baseline value is set to the range of 0.9 to 1.1 times the gravitational acceleration. During the statistics, the overload points falling into this range in the history sequence are counted one by one. For example, in a typical cruise mission, the frequency of overloads in this range can reach more than 70% of the total data points. These low-amplitude loads mainly come from the cumulative effect of atmospheric disturbances.

[0033] Step S42: Statistically analyze the distribution of moderate amplitude overloads. Moderate amplitude is defined as the range of 1.1 to 1.5 times the gravitational acceleration. Each peak in the sequence is categorized into intervals, and its frequency and duration are recorded. For example, overload peaks generated during attitude adjustments in transition flight segments are mostly concentrated in this interval, and the distribution density increases linearly with the number of mission sorties. Step S43: Control the distribution of high amplitude overload events to the end of the spectrum. High amplitude is defined as events exceeding 1.5 times the gravitational acceleration. It is necessary to ensure that these events account for less than 5% of the entire standard spectrum and are placed at the end of the sequence to simulate the rarity of extreme conditions in real missions and avoid spectrum distortion affecting the accuracy of fatigue assessment. Step S44: Accumulate the number of cycles to form a standard length. The standard length corresponds to a predetermined number of missions, for example, set to a total of 500 missions. The complete spectrum length is obtained by multiplying the frequency of each interval by the proportion of missions and then summing the results. This length is directly used as input for subsequent lifetime prediction.

[0034] In one embodiment, the statistical process can adjust the frequency threshold for different altitudes. For example, in high-altitude environments, the baseline value range needs to be expanded by 0.05 times the gravitational acceleration to compensate for the increased load fluctuation caused by the decrease in air density. It should be noted that when performing statistics on medium amplitude distributions, sensor noise interference should be eliminated, and transient peaks less than 0.5 seconds should be filtered out by setting a minimum duration threshold. For example, high amplitude event control can be verified by combining historical flight records. When a flight experiences more than two 1.8 times overload events, the tail position needs to be reallocated to maintain spectrum consistency. Step S71: Divide the overload level range. The range is divided using an equal-interval method, from 0 to 0.5 times, 0.5 to 0.8 times, 0.8 to 1.2 times, 1.2 to 1.5 times, and above 1.5 times, each level corresponding to a specific structural response characteristic. Step S72: Calculate the number of cycles for each level. The number of cycles is extracted from the process sequence using the rainflow counting method. Cycle counts at the 0.8 to 1.2 times level typically account for 60% of the total. The calculated results must be compared with the actual flight data with a deviation controlled within 3%. Step S73 ensures the frequency conforms to actual use. Conformity checks are performed by comparing the average values ​​of multiple flights. For example, in coastal missions, high-amplitude frequencies are slightly higher than inland, requiring proportional adjustments to match the actual operating environment. Step S74 generates the total cycle count. The total cycle count is set as the cumulative value for the corresponding predetermined missions. For example, one thousand missions correspond to a total cycle count exceeding one hundred thousand. This total is output as a core parameter of the standard spectrum to the fatigue analysis stage.

[0035] Step S5: Perform structural fatigue life analysis and test loading based on the standard spectrum. Step S51: Scale up the application frequency of the spectrum according to the number of sorties. The scale-up ratio is set according to the design life requirement. For example, if the design life is 5,000 sorties, the 500-sorcery cycle in the standard spectrum is scaled up tenfold to form a complete loading sequence. Step S52: Apply the scaled-up sequence to the test specimen. The test specimen is a scaled-down model with the same material and connection method as the actual fuselage. The loading device applies center-of-gravity overload according to the sequence time step using hydraulic actuators. The actuators are placed at the simulated center-of-gravity point to reproduce the real load path. Step S53: Record cumulative damage data. Damage data is collected in real time using strain gauges, focusing on monitoring strain changes at the wing root and fuselage connection. The cumulative damage value is recorded every 100 scaled-up cycles, and the data is stored in timestamp format for subsequent comparison. Step S514: Compare with the design life requirement. During comparison, the measured cumulative damage is superimposed with the theoretical life curve. Loading is stopped when the damage value reaches 80% of the design threshold to verify whether the structure meets the expected number of sorties requirement.

[0036] In one possible implementation, a safety factor can be introduced into the amplification process, for example, by amplifying high-amplitude events by an additional 1.2 times to cover extreme weather scenarios. It should be noted that pre-load calibration is required before loading the test specimen to ensure that the actuator output deviates from the standard spectrum by less than 2%. For example, in coastal high-humidity environments, the number of salt spray cycles can be increased to simulate the accelerated effect of corrosion on fatigue life. Step S61: Extract the overload range for each segment. During extraction, the vertical takeoff segment is extracted from the spliced ​​history sequence according to time markers, ranging from 0 to 1.8 times the gravitational acceleration; the transition flight segment from 0.7 to 1.6 times; the cruise segment from 0.6 to 1.4 times; and the landing segment from 0 to 2.2 times. Step S62: Simulate random variations caused by turbulence. Random variations are achieved by superimposing band-limited white noise, with the noise frequency range set to 0.1 to 5 Hz. The amplitude standard deviation is adjusted to 0.2 times the gravitational acceleration based on the measured turbulence intensity, making the sequence closer to actual atmospheric disturbances.

[0037] Step S63: Adjust the sequence to match the measured statistics. The adjustment uses a combination of scaling and offsetting. Correction is performed when the sequence mean deviates from the measured mean by more than 4%, ensuring consistency in the peak distribution probability density function. Step S64: Output the complete history sequence file. The output file uses a fixed time step of 0.01 seconds, with each line containing the time, overload value, and the identifier of the associated load cell, facilitating direct import into analysis software.

[0038] In one embodiment, the overload range extraction can be extended to account for additional fluctuations under low-light conditions for nighttime flight missions, such as adding a random component of 0.03 times the gravitational acceleration to reflect attitude disturbances caused by instrument corrections. It should be noted that the turbulence simulation noise needs to be verified through power spectral density to ensure that its overlap with the measured wind speed spectrum in the 0.5 to 2 Hz frequency band is over 90%. For example, a temperature compensation factor can be introduced when adjusting the sequence; the mean overload value decreases slightly under high-temperature conditions, requiring a corresponding upward adjustment of the sequence baseline to maintain statistical matching. Step S71: Divide the overload level intervals. Interval division is combined with structural sensitivity; for example, the interval above 1.5 times can be further subdivided into two sub-intervals: 1.5 to 1.8 times and above 1.8 times, to better capture the damage contribution of high-stress-concentration areas. Step S72: Calculate the number of cycles for each level. The calculation uses the two-parameter rainflow method, simultaneously recording the amplitude and mean. The number of cycles for the 0.8 to 1.2 times level can reach over 80,000 in 500 missions. The calculation results need to generate a frequency histogram for visualization verification. Step S73: Ensure the frequency matches actual usage. Compliance is achieved through cross-validation across multiple mission scenarios. For example, in low-altitude patrol missions around schools, medium-amplitude frequencies are relatively high and need to be adjusted according to weights to reflect the actual usage distribution. Step S74: Generate the total spectrum cycle count. The final output of the total spectrum cycle count is a core indicator of the standard spectrum. For example, the total cycle count for a predetermined mission is set to 200,000 times, and this total directly supports the input of the lifetime analysis model.

[0039] Step S51: Perform structural fatigue life analysis and test loading based on the standard spectrum. Step S52: Scale up the application frequency of the spectrum according to the number of sorties. During scaling up, the mission profile weight is considered; for example, the scaling up ratio of the vertical takeoff cycle is higher than that of the cruise cycle to highlight the dominant role of takeoff impact on overall lifespan. Step S53: Apply the scaled-up sequence to the test specimen. The test specimen is mounted on a special fixture that simulates fuselage constraint boundary conditions. Actuator force feedback is monitored in real time during loading to ensure accurate reproduction of the overload sequence. Step S54: Record cumulative damage data. The damage data acquisition frequency is set to 100 times per second, focusing on recording strain peaks and troughs. The cumulative damage curve is updated in real time using rainflow counting. The data file includes the damage increment at the end of each sortie. Step S55: Compare with design life requirements. The comparison results are presented in the form of life margin. When the measured life exceeds four times the design requirement, it indicates that the structural design has sufficient safety margin.

[0040] In one embodiment, the number of times the amplified spectrum is applied can be adjusted according to different UAV models. For example, heavy transport UAVs need to amplify the proportion of high-amplitude events to cover greater load changes. It should be noted that modal testing should be performed on the test specimen before applying the sequence to eliminate resonance frequency interference with loading accuracy. For example, when recording cumulative damage, finite element simulation results can be used for cross-validation to ensure that the deviation between the experimental data and theoretical predictions is controlled within 5%. Step S61: Extract the overload range of each segment. The extraction process needs to retain the original timestamp information. For example, the overload range of the vertical takeoff segment is extracted from the zero moment of takeoff to the moment of attitude stabilization, and the range of the transition flight segment follows immediately until the forward flight speed reaches the cruise value. Step S62: Simulate random changes caused by turbulence. The random change simulation is generated using an autoregressive model. The model parameters are obtained by fitting measured turbulence data, and the output sequence contains continuous multi-period fluctuations to simulate long-term cruise accumulation. Step S63: Adjust the sequence to match the measured statistics. The adjustment adopts an iterative optimization method. After each iteration, the statistical moments are recalculated until the mean and variance match the measured values ​​by more than 97%. Step S64: Output the complete process sequence file. The output file supports multiple format conversions, such as exporting as a general text or binary file, for easy use by different analysis platforms.

[0041] In one possible implementation, the overload range extraction can be extended to include a lateral component with crosswind correction, for example, by adding a lateral overload range of 0.3 to 0.6 times gravitational acceleration during transition flights. It should be noted that turbulent stochastic variation simulations need to verify the power spectrum attenuation characteristics in the high-frequency band to avoid introducing spurious high-frequency damage. For example, during sequence adjustment, inter-flight variability can be introduced by randomly sampling historical mission parameters to fine-tune the mean, ensuring the generated spectrum is more representative. Step S71: Divide the overload level intervals. The interval division considers material fatigue characteristics; for example, aluminum alloy structures are highly sensitive to the 1.2 to 1.5 times range, so this interval needs to be weighted during division. Step S72: Calculate the number of cycles for each level. The calculation results generate a detailed frequency table. Although the 0 to 0.5 times level has a high number of cycles, its damage contribution is small, so it needs to be listed separately to support graded life assessment. Step S73: Ensure the frequencies conform to actual use. Conformity checks include seasonal adjustments; for example, turbulence in summer missions causes a 10% increase in the frequency of medium amplitude frequencies, requiring corresponding updates to the standard spectrum parameters. Step S74: Generate the total spectrum cycle count. Once the total spectrum cycle count is finalized, it is used for parallel analysis of multiple sorties, such as simultaneously evaluating the cumulative damage distribution across five sorties.

[0042] Step S4: Statistically analyze the frequency of each overload level and determine the standard spectrum length corresponding to the predetermined sortie mission. Step S41: Statistically analyze the frequency of loads close to the baseline value. Frequency analysis uses a sliding window method with a window length of ten seconds. The results show that the load point density within the baseline interval is highest during the cruise phase, reaching over fifteen times per second. Step S42: Statistically analyze the distribution of medium-amplitude overloads. Distribution analysis generates a probability density curve. The peak of the medium-amplitude interval appears at the end of the transition flight phase, and the curve width reflects the severity of attitude adjustments. Step S43: Control the distribution of high-amplitude overload events to the tail of the spectrum. Tail position allocation must ensure a minimum interval between events greater than thirty seconds to avoid continuous high loads causing spectrum anomalies. Step S44: Accumulate the number of cycles to form the standard length. After the standard length calculation is completed, the output is a fixed value; for example, the standard spectrum length for the predetermined sortie mission is set to 30,000 cycles.

[0043] In one embodiment, the baseline frequency statistics can be extended for different load configurations, such as adding baseline drift compensation caused by fuel consumption. It should be noted that medium amplitude distribution statistics need to exclude ground taxiing phase data to focus on in-flight load characteristics. For example, high amplitude event control can be verified for distribution rationality through Monte Carlo simulation to ensure that tail event probabilities match actual flight records. Step S51: Amplify the application frequency of the spectrum according to the sortie rate. The amplification ratio calculation needs to consider the mission repetition rate; for example, a UAV performing two missions daily needs to amplify the standard spectrum to the daily usage multiple. Step S52: Apply the amplified sequence to the test specimen. Multiple sets of strain gauges are attached to the surface of the test specimen, with the gauge spacing set to 50 mm according to the structural dimensions to ensure comprehensive capture of stress gradient changes. Step S53: Record cumulative damage data. Damage data recording uses a segmented storage method, with each segment corresponding to the end of a load unit, and the data file automatically generates a damage growth rate curve. Step S54: Compare with design life requirements. The comparison process outputs the ratio of the predicted life value to the design value; a ratio greater than one indicates that the structure meets the requirements.

[0044] In one possible implementation, environmental factors can be introduced during spectrum amplification, such as increasing the amplification ratio by 0.1 times in low-temperature environments to simulate material embrittlement effects. It should be noted that temperature changes must be monitored during test specimen loading to maintain the test environment consistent with the measured flight temperature. For example, cumulative damage records can be combined with acoustic emission monitoring to capture the initiation moment of microcracks for early warning. Step S61: Extract the overload range for each segment. The extracted range must be strictly aligned with the time stamp in the mission profile description file to ensure that the starting point of the vertical takeoff segment precisely corresponds to the moment of lift abrupt change. Step S62: Simulate random changes caused by turbulence. The random change simulation parameters are obtained by least-squares fitting of measured data, and the turbulence period in the output sequence matches the actual wind speed spectrum characteristics. Step S613: Adjust the sequence to match measured statistics. The number of adjustment iterations is usually controlled within five, and the sequence is updated after each iteration until the statistical parameters converge. Step S64: Output a complete history sequence file. The output file includes a metadata header recording the generation date, mission number, and spectrum version number for easy version tracking.

[0045] In one embodiment, the overload range extraction can be extended to include additional landing segments for emergency return scenarios, such as adding a sub-interval of 1.5 to 2.5 times gravitational acceleration. It should be noted that turbulence simulation must avoid introducing periodic artifacts, and random phase modulation should be used to ensure natural changes. For example, during sequence adjustment, normalization can be performed by referring to the average spectrum of multiple sorties to ensure the statistical representativeness of the generated history sequence. Step S71: Divide the overload level intervals. Interval division supports custom expansion; for example, users can add refined sub-intervals based on specific structural weak points. Step S72: Calculate the number of cycles for each level. The calculation uses parallel processing, simultaneously outputting the number of cycles and equivalent damage values ​​for each interval for rapid evaluation. Step S73: Ensure the frequency conforms to actual use. Conformity verification includes correlation with historical fault data; for example, if the frequency of high amplitude values ​​is too high, the maintenance records of the corresponding structural components need to be checked. Step S74: Generate the total cycle count of the total spectrum. After the total cycle count of the total spectrum is generated, it can be directly used for multi-scheme comparative analysis, such as evaluating the lifespan differences under different mission profiles.

[0046] Step S5: Perform structural fatigue life analysis and test loading based on the standard spectrum. Step S51: Scale up the application frequency of the spectrum according to the number of runs. The scale-up process must retain the original sequence shape, only expanding the number of repetitions proportionally. Step S52: Apply the scaled-up sequence to the test specimen. A full-size component is used for verification loading on the test specimen, with actuators working collaboratively to reproduce the multi-point load distribution. Step S53: Record cumulative damage data. Damage data is uploaded to the monitoring terminal in real time via a wireless transmission module, and a report is automatically generated after each scale-up run. Step S54: Compare with design life requirements. The comparison results are displayed in graphical form, with changes in the slope of the life curve reflecting the accelerated damage stage.

[0047] In one embodiment, the number of times the amplification spectrum is applied can be adjusted according to the season; for example, the amplification ratio is reduced in winter missions to reflect the low-turbulence environment. It should be noted that the test specimen application sequence needs to be dynamically calibrated to eliminate the influence of actuator hysteresis. For example, vibration acceleration monitoring can be added when recording cumulative damage data to capture the superimposed effect of resonance on fatigue. Step S61: Extract the overload range for each segment. The extracted range supports dynamic adjustment, for example, fine-tuning the upper limit of the cruise segment based on real-time flight parameters. Step S62: Simulate random changes caused by turbulence. Random changes are generated through multi-scale decomposition, and each scale component is independently modulated and then synthesized. Step S63: Adjust the sequence to match measured statistics. The adjustment adopts a feedback control method; recalculation is automatically triggered when the deviation exceeds a threshold. Step S64: Output a complete history sequence file. The output file supports encrypted storage to protect sensitive flight data.

[0048] Example 1:

[0049] like Figures 1-9 As shown, where, Figure 1 This is a curve showing the number of overloads at the center of gravity during the vertical takeoff phase of this invention. It is used to represent the distribution of the number of overloads corresponding to different overload amplitudes during the vertical takeoff phase, and to intuitively reflect the load characteristics of the rapid increase in overload during the takeoff phase. The overload is mainly concentrated in the range of 1.2g to 1.5g. Figure 2 The curve of the center of gravity overload exceedance number during the transition flight phase of this invention reflects the change law of overload with attitude adjustment during the transition flight phase. The overload is distributed in the range of 0.7g to 1.6g, reflecting the dynamic transition characteristics of the mode transition process. Figure 3 The graph shows the overload exceedance number curve of the center of gravity during the cruise phase of this invention, demonstrating that the overload fluctuates smoothly in the range of 0.9g to 1.3g during the cruise phase, which is consistent with the statistical distribution characteristics of the load under atmospheric turbulence. Figure 4 This is the overload exceedance curve of the center of gravity during the landing phase of this invention, which reflects the overload changes caused by the impact of landing. The peak value can reach 2.2g, and it fully covers the load distribution throughout the entire landing process. Figure 5 This is a typical load spectrum diagram of the vertical takeoff phase of the present invention, which presents the process of the overload during the vertical takeoff phase rapidly increasing from 0 to the peak value and then stabilizing briefly in the form of a time history. Figure 6 This is a typical load spectrum of the transition phase of the present invention, which shows the smooth transition of the overload during the transition phase from the takeoff peak to the cruise level in the form of a time series, without abrupt changes and continuous and complete. Figure 7 This is a typical load spectrum of the cruise phase of the present invention, showing the time history of the overload during the cruise phase fluctuating slightly around 1g, simulating the stable load characteristics under real atmospheric disturbances. Figure 8 This is a typical load spectrum diagram of the landing phase of the present invention, which fully shows the overload change process from smooth descent to ground impact and then rapid return, accurately reproducing the landing impact load characteristics. Figure 9This invention presents a complete center-of-gravity overload (CG) spectrum for 100 typical missions, integrating the four load sequences of vertical takeoff, transition flight, cruise, and landing according to the mission sequence. This spectrum can be directly used for structural fatigue life analysis and experimental loading. The invention provides a CG spectrum for compound-wing unmanned transport aircraft based on measured flight data and typical mission profiles. The core is to establish a standardized CG spectrum to address the gaps in existing spectrums and meet the structural fatigue analysis requirements of UAVs with vertical takeoff and landing (VTOL) + fixed-wing transition modes. This CG spectrum consists of load sequences from multiple typical flight phases, covering all operating conditions of a complete mission for a compound-wing UAV. Specifically, the spectrum is divided into four typical load units: vertical takeoff, transition flight, cruise, and landing. Each load segment corresponds to the time-varying characteristics and load range of the CG spectrum for that flight phase. Vertical takeoff phase: This phase is relatively short in duration, with the overload value changing rapidly from a stationary state, typically slightly above 1g, to overcome gravity and achieve vertical takeoff. The overload spectrum in this phase exhibits a sharp increase in lift at startup, and the load range covers from 1g in level flight to the peak overload at the moment of takeoff (e.g., fluctuating within the range of 1.2-1.5g, depending on the thrust-to-weight ratio and takeoff control strategy).

[0050] The transition phase: This is the phase connecting vertical climb and horizontal cruise, and the load changes are complex throughout its time history. As the propulsion system transitions from lift mode to forward flight mode, the center of gravity overload may initially decrease and then increase. The overload range in this phase fluctuates around 1g, and there may be short-term slight negative overloads (below 1g) and positive overload peaks (slightly above 1g) to reflect load changes during airframe attitude adjustments and aerodynamic lift takeover.

[0051] Cruise phase: The longest phase, corresponding to the stable cruise of fixed-wing horizontal flight. During this phase, the center of gravity overload fluctuates slightly around 1g, with a relatively stable time history but superimposed with load variations caused by random turbulence and maneuvers. The load range is generally between 0.9-1.3g, with occasional moderate overload events (such as short-term overloads above 1.3g caused by gusts or small maneuvers). The overall spectrum curve exhibits low-frequency, slowly varying characteristics.

[0052] The descent phase encompasses the entire process from cruise to vertical descent and landing. In terms of time history, the overload initially varies slightly with speed reduction and attitude transition, approaching or slightly below 1g during vertical descent (simulating the slight weightlessness experienced during hovering descent), while an overload rebound occurs upon landing or during hovering braking. The peak of the load spectrum in this phase typically occurs at the moment of landing (potentially reaching 1.2-1.4g, reflecting the vertical deceleration impact), then rapidly drops to 0g (unloading) and stabilizes. The entire descent phase spectrum reflects the load characteristics of the vertical recovery process of the compound-wing UAV.

[0053] The aforementioned center-of-gravity overload spectrum has clear statistical characteristics and application purposes. The spectrum covers various overload levels that a compound-wing UAV may experience during operation, ranging from small oscillating loads to extreme overload events. The total length of the spectrum is measured by the number of cycles. The standard spectrum length, obtained through statistical analysis of typical flight data, represents the total cumulative load cycles of a predetermined number of flights. In this invention, the standard length of the center-of-gravity overload spectrum corresponds to the cumulative load sequence of 100 takeoff and landing missions, comprehensively encompassing all center-of-gravity overload events in approximately 100 missions. In other words, this standard spectrum is equivalent to simulating the full load profile experienced by the UAV in 100 typical missions, with a total number of cycles reaching tens of thousands, capable of covering the main fatigue damage contributions within the design life. The frequency of each overload level in the spectrum conforms to actual usage statistics: for example, cruise loads close to 1g occur most frequently, higher overloads (e.g., >1.3g) occur less frequently and mostly occur during takeoff and landing, while rare extreme overloads are controlled within a few cycles at the end of the spectrum. Through such frequency distribution control, the typical flight missions and sortie counts represented by the spectrum have statistical equivalence, which can be used to accelerate the simulation of long-term service conditions during fatigue testing. This center-of-gravity overload spectrum, as a standard load spectrum for fatigue life analysis and testing, can be directly used for strength and durability verification of the entire aircraft and key components. Designers can use this spectrum to calculate structural fatigue life and predict whether the cumulative structural damage meets requirements under design life conditions (e.g., N flight hours or M sorties). Furthermore, in practical applications, the load sequence and distribution provided by this spectrum can serve as a benchmark spectrum for full-scale structural fatigue testing in the laboratory, applying loads that the UAV might encounter in service to the test specimen in the same order and frequency to evaluate its durability performance.

[0054] The center-of-gravity overload spectrum of this invention also possesses excellent scalability and application flexibility. On one hand, it is compiled based on typical mission profiles, and the load spectrum under different mission sorties or different mission combinations can be reconstructed based on this spectrum: users can adjust and splice the repetition frequency or sequence of each flight segment in the spectrum according to specific usage scenarios to generate a fatigue load input spectrum corresponding to that scenario. For example, if a UAV performs frequent vertical take-off and landing missions, the frequency of the take-off / landing segment spectrum in the overall spectrum can be increased; if performing long-endurance cruise missions, the cyclic ratio of the cruise segment load spectrum can be extended. Through this modular reconstruction method of spectrum segments, the standard spectrum of this invention can adapt to the fatigue loading requirements of different sortie counts and mission profiles. On the other hand, this center-of-gravity overload spectrum can serve as a unified reference within the design life. When it is necessary to verify the structural integrity of the UAV within its design life (such as several years or several flight hours), the application frequency of the spectrum can be proportionally increased according to the total number of sorties in the life, and it can be used as the loading sequence for fatigue tests to ensure that the cumulative damage reaches the design life level. This makes this spectrum a fundamental tool for structural fatigue assessment of compound-wing unmanned transport aircraft in engineering, filling a gap in existing technology and possessing significant practical value.

[0055] The foregoing has provided a detailed description of the method, system, and readable storage medium for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV, as provided in the embodiments of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of this application; furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

[0056] Certain terms are used in the specification and claims to refer to specific components. Those skilled in the art will understand that hardware manufacturers may use different names to refer to the same component. This specification and claims do not distinguish components based on differences in name, but rather on differences in function. The terms "comprising" and "including" used throughout the specification and claims are open-ended and should be interpreted as "comprising / including but not limited to". "Approximately" means that within an acceptable margin of error, those skilled in the art can solve the technical problem and substantially achieve the technical effect within a certain margin of error. The following descriptions in the specification are preferred embodiments for carrying out this application; however, these descriptions are for the purpose of illustrating the general principles of this application and are not intended to limit the scope of this application. The scope of protection of this application shall be determined by the appended claims.

[0057] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a product or system comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a product or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the product or system that includes said element.

[0058] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0059] The foregoing description illustrates and describes several preferred embodiments of this application. However, as previously stated, it should be understood that this application is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the application concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of this application should be within the protection scope of the appended claims.

Claims

1. A method for compiling the center-of-gravity overload spectrum of a compound-wing transport unmanned aerial vehicle, characterized in that, include: S1. Acquire measured flight data and analyze typical mission profiles; S2. Divide the mission profile into four payload units: vertical takeoff segment, transition flight segment, cruise segment, and landing segment. S3. Compile a corresponding center of gravity overload time history sequence for each load unit; S4. Statistically analyze the frequency of occurrence of each overload level and determine the standard spectrum length of the corresponding scheduled mission to complete the compilation of the UAV center of gravity overload spectrum; S5. Conduct structural fatigue life analysis and test loading based on the standard spectrum.

2. The method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV according to claim 1, characterized in that, The S1 process involves acquiring measured flight data and analyzing typical mission profiles, including: S11. Collect flight parameters of the UAV in vertical take-off and landing and fixed-wing switching modes; S12. Calculate the duration and status changes of each flight phase based on flight parameters; S13. Organize all flight data to form a standardized mission profile description file; S14. Verify the effectiveness of the mission profile to ensure that the profile covers all major flight conditions of the UAV.

3. The method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV according to claim 1, characterized in that, The S2 section divides the mission profile into four payload units: vertical takeoff, transition flight, cruise, and landing. S21. Define the characteristics of the sharp increase in overload during the vertical takeoff phase; S22. Define the attitude adjustment transition characteristics of the flight transition segment; S23. Define the smooth fluctuation characteristics of the cruise segment; S24. Define the ground impact characteristics of the landing phase and complete the precise division of the four load units.

4. The method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV according to claim 1, characterized in that, S3 involves compiling a corresponding center of gravity overload time history sequence for each load unit, including: S31. Generate the overload surge sequence corresponding to the vertical takeoff segment; S32. Generate the attitude transition sequence corresponding to the flight transition segment; S33. Generate a stationary fluctuation sequence corresponding to the cruise segment; S34. Generate the load recovery sequence corresponding to the landing phase; S35. According to the flight time sequence, splice together the overload sequences of each segment to form the initial center of gravity overload time history sequence.

5. The method for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV according to claim 4, characterized in that, The S3 step of compiling a corresponding center-of-gravity overload time history sequence for each load unit also includes: S36. Extract the overload value range of each flight load unit; S37. Simulate the random variation characteristics of loads caused by atmospheric turbulence; S38. Adjust the overload sequence parameters based on measured statistical data to ensure data matching; S39. Output the complete center of gravity overload time history sequence file after calibration.

6. The method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV according to claim 1, characterized in that, The S4 step, which involves counting the frequency of each overload level and determining the standard spectrum length corresponding to a predetermined sortie mission, includes: S41, frequency of low-frequency statistical loads approaching the baseline value, frequency of preset load occurrence; S42. Statistically analyze the distribution pattern of moderate amplitude overload during flight; S43. Centralize and control the distribution of high-amplitude overload events at the tail of the standard spectrum; S44. Accumulate the number of overload cycles at each level to form the standard spectrum length corresponding to the predetermined mission.

7. The method for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV according to claim 6, characterized in that, The S4 step of counting the frequency of each overload level and determining the standard spectrum length corresponding to the predetermined sortie mission also includes: S45. Divide the overload level range into multiple levels according to the load amplitude; S46. Accurately calculate the number of load cycles corresponding to each overload level; S47. Verify the frequency of each level of load to ensure it matches the actual operating conditions of the drone. S48. Summarize all cyclic data and generate the total cyclic data for the standard spectrum.

8. The method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV according to claim 1, characterized in that, The S5 section describes structural fatigue life analysis and experimental loading based on standard spectra, including: S51. The number of times the standard spectrum is applied is proportionally increased according to the preset test frame ratio. S52. Apply the amplified overload time series to the UAV test specimen to complete the loading test; S53. Real-time monitoring of test status and recording of cumulative damage data of the UAV structure; S54. Compare the cumulative damage data with the design life requirements of the UAV to complete the life verification and verify whether the structure meets the design life requirements.

9. A system for compiling the center-of-gravity overload spectrum of a compound-wing transport unmanned aerial vehicle, characterized in that, The method for compiling the center-of-gravity overload spectrum of a compound-wing transport UAV according to any one of claims 1-8, the system comprising: The mission profile analysis module is used to acquire UAV measured flight data, statistically analyze flight status and duration, and generate and verify typical mission profiles covering all operating conditions. The load unit division module is used to divide the mission profile into four independent load units based on the overload characteristics, attitude characteristics, and impact characteristics of each flight segment. The overload sequence compilation module is used to generate the basic overload sequence for each load unit, simulate turbulent random loads and calibrate and match measured data, and output a complete history sequence. The standard spectrum construction module is used to divide overload level intervals, count load frequency and cycle number, reasonably distribute high amplitude loads, and generate standard overload spectra for the corresponding predetermined flights. The fatigue test analysis module is used to scale up the standard spectrum, load the test piece, collect cumulative structural damage data, and verify the fatigue life of the UAV structure.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer-executable program, which, when invoked by a processor, implements all the steps of the method for compiling the center-of-gravity overload spectrum of the compound-wing transport UAV according to any one of claims 1 to 8.

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