Method for compiling measured severe maneuver spectrum of aircraft based on representative overload overshoot curve

Abstract

The method for compiling the measured severe maneuver spectrum of an aircraft based on a severe representative overload exceedance curve comprises the following steps: obtaining measured maneuver load data of each task section in each task profile; analyzing the load data to obtain a first overload peak-valley value sequence; calculating the damage of the first overload peak-valley value sequence and confirming severe damage, and screening the first overload peak-valley value sequence according to the severe damage to obtain a second overload peak-valley value sequence; fitting the second overload peak-valley value sequence to obtain a severe representative overload exceedance curve; and compiling a severe maneuver measured spectrum according to the severe representative overload exceedance curve. The severe representative overload exceedance curve determined based on the severe damage can be used to compile a more accurate and more representative severe spectrum, and the dispersion of the maneuver load is fully considered, the severe spectrum reflects the severe condition of the expected experienced load, the fatigue dispersion coefficient can be reduced, the fatigue test time can be reduced, and the test failure characteristics are more consistent with the field failure characteristics.

Description

Technical Field

[0001] This invention relates to the field of flight load spectrum compilation technology, and more specifically to a method for compiling a measured severe maneuver spectrum of an aircraft based on a curve representing the overload exceedance number. Background Technology

[0002] Flight load spectrum refers to the spectrum compiled from the load time history experienced by an aircraft's airframe structure during flight. It is compiled through specialized testing modifications and flight tests to determine and verify the aircraft's design service life, and is a prerequisite for determining the fatigue life extension of aircraft structures. Maneuvering loads account for a significant proportion of damage in flight loads, making the compilation of measured maneuvering spectra crucial for determining the life extension of military and civilian aircraft. While the concept, compilation methods, and life analysis methods under average spectra are relatively mature, several key technologies remain to be solved in the research of severe spectra. For example, failure to fully consider the dispersion of maneuvers, the characteristics of maneuvering overloads, and the characteristics of measured maneuvering loads on the aircraft leads to prolonged fatigue testing times.

[0003] Therefore, how to provide a method for compiling the measured severe maneuver spectrum of an aircraft based on the representative overload exceedance number curve, which can fully consider the maneuver dispersion and reduce the fatigue test time, is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention provides a method for compiling the measured severe maneuver spectrum of an aircraft based on the overload exceedance number curve, which can fully consider the maneuver dispersion and reduce the fatigue test time.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for compiling the spectrum of a severely maneuvered aircraft based on a curve representing the overload exceedance number includes the following steps:

[0007] Obtain measured maneuver load data for each mission segment within each mission profile;

[0008] The load data is analyzed to obtain the first overload peak-valley value sequence;

[0009] Severe damage is confirmed based on the first overload peak-valley value sequence, and the damage in the first overload peak-valley value sequence is filtered based on the severe damage to obtain the second overload peak-valley value sequence.

[0010] The severe overload exceedance number curve is obtained by fitting the second overload peak-valley value sequence.

[0011] The severe maneuver test spectrum is compiled based on the severe representative overload exceedance number curve.

[0012] Furthermore, the measured maneuver load data for each mission segment within each mission profile are obtained. The steps include:

[0013] Obtain complete load data;

[0014] Set mission profile parameters, which include mission segment, mission segment altitude, speed, weight, flight distance, and flight time;

[0015] The complete load data is divided into multiple measured maneuver load data corresponding to multiple task segments based on the task profile parameters.

[0016] Furthermore, the steps also include: preprocessing the actual load data;

[0017] The preprocessing includes overload standardization and gust maneuver overload separation.

[0018] Furthermore, the overload standardization is as follows:

[0019] The Y-axis overload data of the aircraft's center of gravity and wings are used to calculate the corresponding actual mass G. i The ratio of the standard aircraft mass G0 for this mission segment to the flight profile diagram is corrected:

[0020] △ny0=△ny i *G i / G0

[0021] Wherein, △ny0 is the overload value corrected according to the standard task section specifications; △ny i This is the measured overload value.

[0022] Furthermore, the aforementioned gust maneuver overload separation specifically includes:

[0023] Overload changes that are slow and last for more than 2 seconds are considered motor overloads; otherwise, they are considered sudden wind overloads.

[0024] An overload with an absolute value of 4° or greater on the control surface deflection is a maneuver overload; otherwise, it is a gust overload.

[0025] Furthermore, the peak-valley value filtering specifically involves: detecting all peak values ​​and valley values, and filtering out the data between the peak values ​​and valley values.

[0026] Furthermore, the load data is analyzed to obtain the first overload peak-valley value sequence, the steps of which include:

[0027] The preprocessed load data is counted using the rainflow counting method to obtain the full cycle range and the full cycle mean in the load time history of each task segment, thus obtaining the first overload peak-valley value sequence.

[0028] Furthermore, severe damage is confirmed, and the damage sequence of the first overload peak-valley value is filtered according to the severity of the damage to obtain the second overload peak-valley value sequence. The steps include:

[0029] Obtain the full cycles generated by rainflow counts in the first overload peak-valley value sequence, calculate the damage of each full cycle, and accumulate to obtain the load spectrum damage:

[0030] The distribution of load spectrum damage in each task segment is analyzed to obtain the expected damage distribution;

[0031] The load spectrum damage with a reliability of 90% is extracted from the expected damage distribution as severe damage, and the severe damage is selected from the first overload peak-valley value sequence to obtain the overload peak-valley value sequence under severe damage, i.e., the second overload peak-valley value sequence.

[0032] Furthermore, by fitting the second overload peak-valley value sequence, a severe representative overload exceedance number curve is obtained. The steps include:

[0033] Based on the overload peak-valley value sequence under severe damage, determine the cumulative exceedance number at each level;

[0034] The cumulative overload exceedance numbers at each level are standardized to obtain the processed cumulative overload exceedance number data pairs.

[0035] Selected overload cumulative exceedance data pairs (Δn) for each task segment y ,N) i By fitting the curve, we obtain the severe overload exceedance number curve.

[0036] Furthermore, the formula for calculating the damage is:

[0037]

[0038] Where m is the damage index, i.e., the material / structure fatigue SN curve at R=0, and R is the stress ratio, representing the slope of the life-stress curve. k is the dimensionless coefficient of the standard weight of the aircraft mission segment, k = standard weight of the aircraft mission segment / aircraft takeoff weight.

[0039] Furthermore, the process of compiling the severe overload exceedance number curve into a severe maneuver test spectrum includes the following steps:

[0040] Load discretization is performed based on the cumulative exceedance number curve of severe maneuver overload in the mission segment;

[0041] Based on the discrete results, the load levels and their corresponding occurrence counts are confirmed, and the overload degree of each load level is obtained. Based on the overload degree, five flight types are divided, and based on the five load levels and the corresponding flight counts under the five flight types, a 5×5 spectrum is compiled.

[0042] Based on the 5×5 spectrum, the mission segment spectrum, mission profile spectrum, and flight-continue-flight spectrum are compiled.

[0043] The beneficial effects of this invention are:

[0044] As can be seen from the above technical solutions, compared with the prior art, this invention discloses a method for compiling a measured severe maneuver spectrum of an aircraft based on a representative overload exceedance number curve. This method can reduce fatigue testing time, and the dispersion factor used in life determination only needs to consider the dispersion factor of the structure, without considering the dispersion of the load. Furthermore, this invention provides a method for calculating severe damage to aircraft groups and generating severe maneuver overload exceedance number curves. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0046] Figure 1 The attached figure is a flowchart of a method for compiling a measured severe maneuver spectrum of an aircraft based on a representative overload exceedance number curve, provided by the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] This invention discloses a method for compiling a measured severe maneuver spectrum of an aircraft based on a representative overload exceedance number curve, comprising the following steps:

[0049] S1: Define the aircraft mission profile and obtain measured maneuver load data for each mission segment within each mission profile. Based on the aircraft's operational requirements, specify the composition and proportions of the mission profiles; for each mission profile, define the composition, order, proportions, and parameters of the mission segments constituting the mission profile.

[0050] Specifically, the mission profile, its scale, and its composition are determined, and mission profile parameters are provided, such as mission segments, their altitude, speed, weight, flight distance, and flight time. The division of mission segments based on measured data follows these principles:

[0051] a) The criterion is that the flap angle changes to 35° when the flaps are lowered and the entry is started.

[0052] b) The criterion for determining the end point of the flap deployment is when the flap deflection angle becomes 0°.

[0053] c) The turning point where the altitude curve begins to level out during level flight is used as the criterion;

[0054] d) The end point of level flight is determined by the inflection point of the altitude descent curve;

[0055] e) The criterion is to press the flap deflection angle to 35° when the flaps are lowered and the entry begins.

[0056] f) The criterion is that the flap deflection angle becomes 0° at the end of the entry point after the flaps are lowered.

[0057] S2: Load Data Preparation. Preprocessing of the measured maneuver load data includes overload standardization, gust maneuver overload separation, and peak-to-valley value filtering.

[0058] Overload standardization: This involves standardizing the measured center of gravity overload n. y Subtracting 1 gives the incremental overload Δn at that moment. y ;

[0059] Overload data n y Standardization processing: Load data is the Y-axis overload at the center of gravity. The Y-axis overload data of the aircraft's center of gravity and wings are converted into the actual mass "G" at each moment. i The ratio of the standard aircraft mass "G0" for this mission segment to the flight profile diagram is corrected. That is:

[0060] △ny0=△ny i *G i / G0

[0061] In the formula, △ny0 is the overload value corrected according to the standard task section specifications; △ny i The overload value is the measured value, where i represents the time i. The actual load mass data is given by subtracting fuel consumption from the aircraft weight. The fuel consumption is obtained by calculating the total average (the average fuel consumption is calculated from the start of takeoff taxiing to the end of landing impact).

[0062] Separation of Gust Load and Maneuver Load: The measured maneuver load data includes both maneuver load and gust load. It is necessary to separate the maneuver and maneuver load and filter out the gust load. The interpretation of the maneuver and maneuver load spectrum in flight is determined by comprehensively considering the following two conditions:

[0063] a) Overload changes that are slow and last for more than 2 seconds are considered motor overloads; otherwise, they are considered sudden wind overloads.

[0064] b) An overload with an absolute value of 4° or greater on the control surface deflection is a maneuver overload; otherwise, it is a gust overload.

[0065] Peak and valley values ​​were filtered to obtain preprocessed load data:

[0066] All peaks and troughs are detected, and the data between the peaks and troughs is filtered out, while the corresponding sampling point numbers are retained. As shown in the figure, Δn is retained. z1 , Δn z3 , Δn z5 , Δn z6 , Δn z7 , Δn z8 , Δn z10 Peak and valley points, remove Δn z2 , Δn z4 , Δn z9 Sampling point.

[0067] S3: Analyze the preprocessed load data, calculate severe damage, and confirm the overload peak-valley sequence under severe damage;

[0068] The specific steps are as follows:

[0069] S31: The rainflow counting method is used to count the preprocessed load data to obtain the full cycle range and the full cycle mean in the load time history of each task segment, and to obtain the sequence of maneuver overload peak and valley values.

[0070] Counting process:

[0071] (1) The length of a measured task segment is used as the counting unit.

[0072] (2) Find the maximum peak value in the center of gravity overload time history of the task segment, and disconnect from the maximum peak value to reconstruct a new master parameter history from the start of the maximum peak value to the end of the maximum peak value.

[0073] Among them, the principal parameter is the time history of peak and valley values. The new principal parameter history includes the first principal parameter history from the initial peak value to the maximum peak value and the second principal parameter history from the maximum peak value to the final peak value.

[0074] (3) The new master parameter history is counted using a two-parameter cyclic counting method. After processing a full cycle, its range and mean are given. The range refers to the difference between the peak and the valley, and the mean is the average of the peak and the valley.

[0075] (4) Continue using the above method until the range and mean of all full cycles of the take-off and landing are given, and calculate the sequence of peak and valley values ​​of the maneuver overload based on the range and mean.

[0076] S32: Based on the full cycles generated by rainflow counting, calculate the damage of each full cycle and accumulate it to obtain the load spectrum damage:

[0077] The Odin transform method was used to analyze the damage caused by aircraft maneuvering loads. The time series of measured peak and valley values ​​of maneuvering overloads for each mission segment under all profiles were obtained from rainflow counting (n ymax n ymin ) i Perform damage calculation, calculate the damage d in a single cycle. eq The damage from multiple single cycles in the load spectrum of the mission segment is summed to obtain the damage D of the load spectrum of the mission segment. eq .

[0078]

[0079] In the formula, m is the damage index, i.e., the material / structure fatigue SN curve when R=0, and R is the stress ratio. k is a dimensionless coefficient of the standard weight of the aircraft mission section, k = standard weight of the aircraft mission section / aircraft takeoff weight.

[0080] S33: Analyze the distribution of load spectrum damage in each task segment to obtain the expected damage distribution; extract the load spectrum damage with 90% reliability from the expected damage distribution to obtain severe damage.

[0081] S34: Analyze the damage distribution based on the load spectrum damage of each task segment;

[0082] Damage was calculated for each mission segment under all measured takeoffs and landings. For each mission segment, the distribution of damage under different takeoffs and landings was analyzed. It was assumed that the damage followed a log-normal distribution, and the distribution parameters were estimated using the maximum likelihood estimation method. The likelihood function is shown in the following equation.

[0083]

[0084] In the formula, x i =lgDeq i The objective parameters (μ, σ) are solved by finding that the derivatives of the likelihood functions with respect to μ and σ are zero.

[0085]

[0086]

[0087] S35: Confirm Severe Damage. The severity spectrum should reflect severe operational conditions for 90% of the aircraft in the fleet, with the corresponding severe damage being the damage in the mission segment load spectrum corresponding to 90% reliability. Severe damage is the expected damage D at 90% reliability. eq90

[0088] D eq90 =10^(μ+u) 90 σ)

[0089] In the formula, μ is the logarithmic mean of the damage, σ is the logarithmic standard deviation of the damage, and u 90 This represents the quantile corresponding to the 90th percentile of the standard normal distribution.

[0090] Perform the above operation on all task segments to obtain the severe damage D of each task segment. eq90,i (i is the sequence number of the task segment).

[0091] S36: Select from the overload peak-valley value sequence based on each takeoff and landing of the mission segment according to the severe damage to obtain the overload peak-valley value sequence under severe damage.

[0092] The severity spectrum should reflect the severe usage status of 90% of the aircraft in the fleet, and the damage for each mission segment should be equal to D. eq90i For this task segment, in D eqi Select with D eq90,i Find the closest incremental overload peak-to-trough sequence of takeoff and landing, and correct this incremental overload peak-to-trough sequence so that the damage equals D. eq90,i The correction method is (Δn) y,max ,Δn y,min ) i Multiply by a dimensionless coefficient f. eqi To measure the damage of this task segment in practice, D eq90,i The value is a constant indicating severe damage to this task segment.

[0093] S4: The overload and corresponding exceedance number are calculated based on the overload peak-valley value sequence under severe damage, resulting in a severe representative overload exceedance number curve.

[0094] The specific steps include:

[0095] S41 ： Based on the peak-valley sequence, determine the cumulative exceedance number for each level. Select several load levels and record the cumulative exceedance number for positive and negative maneuvering overloads for both positive and negative peak values, denoted as N(+Δn). y ) and N(-Δn y Generally, we start taking values ​​from 0.05g, with intervals of 0.05g, up to 2g. For example, given the sequences (0.5g, -0.1g, 0.1g-0.6g, 0.2g-0.3g) above, for a positive overload, we select these overload levels and observe how many times the peak value exceeds each level. If the peak values ​​are 0.5g, 0.1g, and 0.2g, and we choose 0.3g, the cumulative exceedance count is 1. If we choose 0.05g, the cumulative exceedance count is 3.

[0096] S42: Standardization processing. Since the actual measurement of the load spectrum is the flight time of the mission segment, which is different from the standard time of the mission segment in the mission profile, it is necessary to convert the measured overload cumulative exceedance number data of the mission segment into cumulative exceedance number data of the standard time.

[0097] Let the flight time corresponding to the measured data be t M , and the standard time of the mission segment be t S . The cumulative exceedance number of the i-th level load obtained at the measured time is N ib , then the cumulative exceedance number of the i-th level load at the standard time should be:

[0098]

[0099] By replacing the cumulative exceedance number of each level of load according to the above formula, the overload cumulative exceedance number data of the mission segment at the standard time can be obtained. The obtained overload cumulative exceedance number data pair (Δn y ,N) i .

[0100] S43: Fit the selected overload cumulative exceedance number data pair (Δn y ,N) i of each mission segment, and the fitting equation is:

[0101] Δn y =a*lgN+b

[0102] Calculate to obtain the severe maneuver positive / negative overload cumulative exceedance number curve of each mission segment.

[0103] S5: Compile the severe maneuver measured spectrum according to the severe representative overload exceedance number curve:

[0104] The specific steps include:

[0105] S51: Perform load discretization based on the severe maneuver overload cumulative exceedance number curve of the mission segment;

[0106] The discretized loads are divided into 5 intervals (LB2,LB1), (LB3,LB2), (LB4,LB3),

[0107] (LB5,LB4). Where LBi+1<LBi, LB1 is the high load value for high load truncation, and LB6 is the low load value for low load deletion;

[0108] S52: Confirm each level of load and the corresponding occurrence times according to the discretization result;

[0109] The 5 levels of loads selected for the 5×5 spectrum are LD1, LD2, LD3, LD4, and LD5 respectively, and the calculation method for each level of load is:

[0110] LD1=LB1

[0111] LDi = (LBi - 1 + LBi) / 2, 2 ≤ i ≤ 6

[0112] The frequency of occurrence of each discrete load level is as follows:

[0113] Fi = Ei i = 1

[0114] Fi = Ei - Ei-1 2 ≤ i ≤ 6

[0115] A total of 5 equivalent loads Δn were obtained. ydi (i = 1, 2, 3, 4, 5) and the corresponding number of cycles Neqi (i = 1, 2, 3, 4, 5).

[0116] S53: Based on the degree of overload, five flight types are divided. Based on the five load levels and the number of flights corresponding to the five flight types, a 5×5 spectrum is compiled.

[0117] S54: Compile the task segment spectrum based on the 5×5 spectrum;

[0118] Based on the data in the compiled 5×5 spectrum, the load levels and their corresponding frequencies of the k-th flight type in the i-th mission segment of the j-th profile are linked together. Peak and trough values ​​are randomly selected and paired to form a load spectrum for a specific flight type in the mission segment, denoted as (Δn). ydn ,-Δn ydm ) h The task segment spectrum (j×i×k segments in total) is represented as a sequence of load pairs in the following form:

[0119] f i,j,k =(Δn) ydn ,-Δn ydm ) h

[0120] In the formula, Δn ydn This represents the nth (n = 1, 2, 3, 4, 5) level of positive overload in this task segment, signifying the peak overload; -Δn ydm This represents the m-th (m = 1, 2, 3, 4, 5) level load of the mission segment, indicating the valley overload. The total number of load pairs for each flight type mission segment should be equal to the total number of cycles for each flight in the table above. Following this method, compile the spectra (load pair sequences) for all flight types under all mission segments.

[0121] S55: Compiling the Task Profile

[0122] Let F be the load spectrum of the k-th flight type on the j-th profile. j,k F j,k This can be represented as a load pair sequence f i,j,kSort the tasks according to the order i (i = 1, 2, 3... m) under this profile, i.e., f 1,j,k ,f 2,j,k ,f 3,j,k ,f 4,j,k ...f m,j,k This yields the mission profile spectrum for a complete flight. The same method is used to compile mission profile spectra for all flight types under all mission profiles. All mission profile spectra are then represented in vector form.

[0123] B = [F] 1,1 … F 1,K F 2,1 … F 2,K F 3,1 … F 3,K ... F L,1 … F L,K ]

[0124] Example: Profile 1 contains three mission segments, each with five flight types. Therefore, five mission profile spectra need to be compiled for Profile 1, representing the five flight types respectively. These are denoted as A1, B1, C1, D1, and E1. When compiling the A1 spectra, the spectra of flight type A under each mission segment are arranged together, i.e., f 1,j,k ,f 2,j,k ,f 3,j,k The A1 spectrum can then be obtained, and the same applies to other types of task profile spectra.

[0125] S56: Compiling Flight-Continuation-Flight Spectrum

[0126] Let y represent the occurrence of the j-th profile (j=1,2…L) and the k-th flight type (k=1,2…K) in 1000 flights. j,k Next. All the y j,k Expressed in vector form as

[0127] A = [y 1,1 … y 1,K y 2,1 … y 2,K y 3,1 … y 3,K ... y L,1 … y L,K ]

[0128] In the formula, A is a vector representing the frequency of occurrence of various task profile spectra.

[0129] Vector B and vector A have a one-to-one correspondence, indicating how many times the task profile spectrum appears in this 1000-times block spectrum. The total spectrum can then be represented as the task profile spectrum sequence G:

[0130] G = A * B

[0131] By reordering the mission profile spectrum for each complete flight in G, the final flight-continued-flight spectrum can be obtained. The specific method is as follows: First, number all mission profiles in G sequentially using a natural number sequence. Then, combine each number with a random integer sequence "x". is "Corresponding to this, press x" is Sort by numerical value (e.g., the corresponding x) is If it is 5, then the corresponding task profile spectrum is placed in the 5th position. This gives us the final load spectrum.

[0132] 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 they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0133] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for compiling the spectrum of a severely maneuvered aircraft based on a representative overload exceedance number curve, characterized in that, Includes the following steps: Obtain measured maneuver load data for each mission segment within each mission profile; The load data is analyzed to obtain the first overload peak-valley value sequence; Severe damage is identified based on the first overload peak-valley value sequence, and the damage in the first overload peak-valley value sequence is filtered according to the severity of the damage to obtain the second overload peak-valley value sequence; specifically including: Obtain the full cycle generated by rainflow counting in the first overload peak-valley value sequence, calculate the damage of each full cycle, and accumulate to obtain the load spectrum damage; The distribution of load spectrum damage for each mission segment is analyzed to obtain the expected damage distribution. Specifically, this includes: calculating the damage for each mission segment under all measured takeoffs and landings, and analyzing the damage distribution for each mission segment under different takeoffs and landings. It is assumed that the damage follows a log-normal distribution, and the maximum likelihood estimation method is used to estimate the distribution parameters. Damage with a reliability of 90% is extracted from the expected damage distribution as severe damage; D eq90 =10^(μ+u 90 p) In the formula, μ is the logarithmic mean of the damage, σ is the logarithmic standard deviation of the damage, and u 90 This represents the quantile corresponding to the 90th percentile of the standard normal distribution; Perform the above operation on all task segments to obtain the severe damage D of each task segment. eq90,i , where i is the sequence number of the task segment; Based on the severe damage, the overload peak-valley value sequence in the first overload peak-valley value sequence is selected where the damage is equal to the severe damage, thus calculating the overload peak-valley value sequence under severe damage, which is the second overload peak-valley value sequence; specifically including: In the first overload peak-valley value sequence, select the incremental overload peak-valley value sequence that is closest to the severe damage, and correct the closest incremental overload peak-valley value sequence by multiplying it by a dimensionless coefficient so that its damage is equal to the severe damage. The severe overload exceedance number curve is obtained by fitting the second overload peak-valley value sequence; specifically including: Based on the overload peak-valley value sequence under severe damage, the cumulative exceedance number for each level is determined; several load levels are selected, and the positive and negative maneuver overload cumulative exceedance numbers are recorded for the positive peak and negative valley values, respectively denoted as N(+Δn). y ) and N(-Δn y ); The cumulative overload exceedance numbers at each level are standardized to obtain processed cumulative overload exceedance number data pairs; specifically including: Let the flight time corresponding to the measured data be t. M The standard time for the task segment is t. S The cumulative exceedance number N of the i-th level load obtained from the measured time. ib Then the cumulative exceedance number of the i-th level load in standard time should be: N i = N ib × By substituting the cumulative overload exceedance counts for each load level using the above formula, the cumulative overload exceedance count data for the standard time period can be obtained; the cumulative overload exceedance count data pairs (Δn) are then obtained. y , N) i ; Selected overload cumulative exceedance data pairs (Δn) for each task segment y , N) i By fitting the curve, a severe overload exceedance number curve is obtained; The severe maneuver test spectrum is compiled based on the severe representative overload exceedance number curve.

2. The method for compiling a severe aircraft maneuver spectrum based on a representative overload exceedance number curve as described in claim 1, characterized in that, The steps to obtain measured maneuver load data for each mission segment within each mission profile include: Obtain complete load data; Set mission profile parameters, which include mission segment, mission segment altitude, speed, weight, flight distance, and flight time; The complete load data is divided into multiple measured maneuver load data corresponding to multiple task segments based on the task profile parameters.

3. The method for compiling a severe aircraft maneuver spectrum based on a representative overload exceedance number curve as described in claim 1, characterized in that, The steps also include: preprocessing the measured motor load data; The preprocessing includes overload normalization and gust maneuver overload separation.

4. The method for compiling a severe aircraft maneuver spectrum based on a representative overload exceedance number curve as described in claim 3, characterized in that, The overload standardization is as follows: The Y-axis overload data of the aircraft's center of gravity and wings are used to calculate the corresponding actual mass G. i The ratio of the standard aircraft mass G0 for this mission segment to the flight profile diagram is corrected: △ny0=△ny i ·G i / G0 Wherein, △ny0 is the overload value corrected according to the standard task section specifications; △ny i This is the measured overload value.

5. The method for compiling a severe aircraft maneuver spectrum based on a representative overload exceedance number curve as described in claim 3, characterized in that, The aforementioned gust maneuver overload separation specifically refers to: Overload changes that are slow and last for more than 2 seconds are considered motor overloads; otherwise, they are considered sudden wind overloads. An overload with an absolute value of 4° or greater on the control surface deflection is a maneuver overload; otherwise, it is a gust overload.

6. The method for compiling a severe aircraft maneuver spectrum based on a representative overload exceedance number curve as described in claim 1, characterized in that, The load data is analyzed to obtain the first overload peak-valley value sequence. The steps include: The preprocessed load data is counted using the rainflow counting method to obtain the full cycle range and the full cycle mean in the load time history of each task segment, thus obtaining the first overload peak-valley value sequence.

7. The method for compiling a severely maneuvering spectrum of an aircraft based on a representative overload exceedance number curve as described in claim 1, characterized in that, The formula for calculating the damage is: Where m is the damage index, i.e. the material / structure fatigue SN curve at R=0, R is the stress ratio, which refers to the slope of the life-stress curve; k is the dimensionless coefficient of the standard weight of the aircraft mission segment, k=standard weight of the aircraft mission segment / aircraft takeoff weight.

8. The method for compiling a severe aircraft maneuver spectrum based on a representative overload exceedance number curve as described in claim 1, characterized in that, The steps for compiling the severe overload exceedance number curve into a severe maneuver measured spectrum include: Load discretization is performed based on the cumulative exceedance number curve of severe maneuver overload in the mission segment; Based on the discrete results, the load levels and their corresponding occurrence counts are confirmed, and the overload degree of each load level is obtained. Based on the overload degree, five flight types are divided, and based on the five load levels and the corresponding flight counts under the five flight types, a 5×5 spectrum is compiled. Based on the 5×5 spectrum, the mission segment spectrum, mission profile spectrum, and flight-continue-flight spectrum are compiled.

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