Method for preparing measured severe ground spectrum based on overload extrapolation

Abstract

The application discloses a kind of based on overload extrapolation's measured severe ground spectrum compilation method, it is related to flight load spectrum compilation technical field. Including: according to aircraft use requirement, determine flight mission profile, and according to flight mission profile will aircraft flight process be divided into multiple ground mission sections, including taxiing mission section and impact mission section;Corresponding measured load data of different ground mission section is obtained, and it is preprocessed, and corresponding ground overload peak and valley value data are obtained;The ground overload peak and valley value data obtained is filtered and selected based on incremental overload, and the cumulative number of exceedances corresponding to each level ground overload is obtained;Overload cumulative number of exceedances is fitted to obtain corresponding ground overload cumulative number of exceedances curve family, and corresponding severe ground overload cumulative number of exceedances curve is obtained according to ground overload cumulative number of exceedances curve;Complete severe ground spectrum compilation.The application can reflect the ground load situation that aircraft really meets, reduce the time of aircraft fatigue test.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of flight load spectrum compilation, and more particularly to a measured severe ground spectrum compilation method based on overload extrapolation. BACKGROUND

[0002] Flight load spectrum refers to a spectrum of load time history experienced by an aircraft in flight. A measured flight load spectrum of an aircraft is compiled through special test modification and flight test, and is used to determine and verify the design service life of the aircraft, which is a prerequisite for aircraft structure fatigue life extension. Ground load damage accounts for a high proportion during the ground-air-ground operation of an aircraft, and the compilation of a measured ground spectrum of an aircraft is of great significance to the life extension of military / civil aircraft.

[0003] Even if the same aircraft is used under the same usage requirements, the load-time history of different aircrafts in the fleet has obvious differences, corresponding to the dispersion of the load spectrum, and durability analysis and testing must be carried out under a certain (unique) load spectrum. Therefore, how to select and compile a reasonable load spectrum has become the key to structural durability analysis and evaluation. For this reason, a "severe spectrum" is proposed, which has the advantages of being able to expose the failure characteristics of the aircraft itself and reducing the test time, so the application of severe spectrum in the compilation of measured spectrum is also increasing.

[0004] The concept, compilation method and life analysis method under the average spectrum are relatively mature, but there are still several key technologies to be solved in the research on severe spectrum.

[0005] As for the specific spectrum compilation method, the US military standard MIL-A-8866 mentions that for ground mission segments, it is appropriate to use equivalent one-level spectrum for load spectrum compilation, but the severity is unknown. Currently, there is no relevant information on the severe ground spectrum compilation method for aircraft in China.

[0006] Therefore, how to provide a severe ground measured spectrum compilation method for an aircraft that fully considers the dispersion of ground loads and the characteristics of ground loads (the load of the taxi mission segment can be considered as a symmetric load, and the load of the impact mission segment is generally not considered as a symmetric load) while ensuring safety and economy is a problem that those skilled in the art need to solve. SUMMARY

[0007] Therefore, the present application provides a measured severe ground spectrum compilation method based on overload extrapolation, which reduces the time of aircraft fatigue test and exposes the failure characteristics of the aircraft as soon as possible.

[0008] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0009] A measured severe ground spectrum compilation method based on overload extrapolation, comprising:

[0010] S1, determining a flight mission profile according to a use requirement of the aircraft, and dividing a flight process of the aircraft into a plurality of ground mission segments according to the flight mission profile, the plurality of ground mission segments including a taxiing mission segment and a crash mission segment;

[0011] S2, obtaining measured load data corresponding to different ground mission segments of the aircraft, and preprocessing the measured load data to obtain corresponding ground overload peak-valley value data;

[0012] S3, filtering and screening the obtained measured take-off and landing ground overload peak-valley value data based on incremental overload to obtain cumulative overrun numbers corresponding to ground overloads of different levels;

[0013] S4, fitting the overload cumulative overrun numbers to obtain a family of ground overload cumulative overrun number curves corresponding to different ground mission segments;

[0014] S5, obtaining corresponding severe ground overload cumulative overrun number curves according to the ground overload cumulative overrun number curves corresponding to different ground mission segments;

[0015] S6, completing severe ground spectrum compilation according to the severe ground overload cumulative overrun number curves corresponding to different ground mission segments.

[0016] Preferably, in step S1, the flight process of the aircraft is divided into a plurality of ground mission segments according to the flight mission profile, and the division criteria specifically include:

[0017] 1) the take-off taxiing start point is determined by the criterion that the speed is greater than 0 after the engine test is completed;

[0018] 2) the take-off taxiing end point is determined by the criterion that the three landing gears completely leave the ground;

[0019] 3) the landing crash start point is determined by the change of Y-direction load;

[0020] 4) the landing crash end point is determined by the criterion that the main landing Y-direction load returns to the ground stable state;

[0021] 5) the landing taxiing start point is determined by the criterion that the main landing gear contacts the ground;

[0022] 6) the landing taxiing end point is determined by the criterion that the yaw angle is greater than 10°.

[0023] Preferably, in step S2, it specifically includes:

[0024] S21, standardizing the measured load data corresponding to different ground mission segments of the aircraft;

[0025] S22, detecting the peak-valley value of the standardized measured load data to obtain overload peak-valley value data corresponding to different ground mission segments.

[0026] Preferably, the measured load data corresponding to different ground task segments of the aircraft in step S21 is normalized, specifically including:

[0027] According to the provisions of the aircraft mission profile, the load data of different ground task segments of the aircraft is corrected by the ratio of the real mass corresponding to the load data to the standard aircraft mass of the different ground task segments of the mission profile.

[0028] Preferably, in step S22, the peak and valley values of the normalized measured load data are detected, specifically including:

[0029] The time series data of the normalized measured load data is obtained, if the sequence data at a certain time point is greater than the sequence data at adjacent time points, the sequence data at the time point is taken as the peak value; if the sequence data at a certain time point is less than the sequence data at adjacent time points, the sequence data at the time point is taken as the valley value; and the sequence data other than the peak and valley values is filtered out.

[0030] Preferably, in step S4, the overload cumulative overrun number of the ground overload cumulative overrun number is calculated, and the overload cumulative overrun number is fitted to obtain a family of ground overload cumulative overrun number curves corresponding to different ground task segments, specifically including:

[0031] S41, the ground overload cumulative overrun number is divided into positive ground overload cumulative overrun number and negative ground overload cumulative overrun number;

[0032] S42, for the taxi task segment, the geometric mean of the positive ground overload cumulative overrun number and the negative ground overload cumulative overrun number is calculated to obtain the merged overload cumulative overrun number of the taxi task segment;

[0033] For the impact task segment, the positive overload cumulative overrun number and the negative overload cumulative overrun number of the impact task segment are obtained respectively;

[0034] S43, for the taxi task segment, the merged overload cumulative overrun number is fitted to obtain the overload cumulative overrun number curve of the taxi task segment, and the fitting equation is: Wherein, N1 represents the merged overload cumulative overrun number of the taxi task segment, Δn y1 represents the incremental overload of the taxi task segment, and a1 and b1 represent fitting parameters of the taxi task segment;

[0035] For the impact task segment, the positive overload cumulative overrun number and the negative overload cumulative overrun number are fitted respectively to obtain the positive overload cumulative overrun curve and the negative overload cumulative overrun curve of the impact task segment, and the fitting equation of the positive overload cumulative overrun curve of the impact task segment is: Δn y2 =a2*lgN2(Δn y2The fitting equation for the cumulative overload curve of the impact mission segment is: -Δn + b2; y2 =a2*lgN2(-Δn y2 )+b2, where N2(Δn) y2 ) represents the cumulative positive overload exceedance number of the impact mission segment, Δn y2 This indicates the positive incremental overload of the impact mission segment, N2(-Δn) y2 ) represents the cumulative negative overload exceedance number of the impact mission segment, -Δn y2 a2 represents the negative incremental overload of the impact mission segment, and b2 both represent the fitting parameters of the impact mission segment.

[0036] Preferably, in step S5, the corresponding severe ground overload cumulative exceedance number curve is obtained from the ground overload cumulative exceedance number curve for different ground mission segments, specifically including:

[0037] S51. Discretize the cumulative overload exceedance curves of different ground mission segments to obtain overload exceedance data pairs for different ground mission segments.

[0038] S52. Perform distribution characteristic detection on the overload exceedance number data pairs, assuming that the overload corresponding to the specified cumulative exceedance number follows a normal distribution;

[0039] S53. Estimate the distribution parameters using the maximum likelihood function estimation method, where the likelihood function is:

[0040] In the formula x i =lgΔN i μ represents the logarithmic median of the overload increment, and σ represents the standard deviation of the overload.

[0041] S54. Based on the likelihood function and distribution parameters, extrapolate the overload increment with a coverage rate of 90%, i.e.

[0042] Δn y90,i =μ i +μ 90 σ i

[0043] Where, μ i σ i These are the log-median and standard deviation of the overload corresponding to the i-th level overload N; obtain the severe overload exceedance data pairs corresponding to different ground mission segments;

[0044] S55. Fit the severe overload exceedance number data pair to obtain the severe ground overload cumulative exceedance number curve corresponding to different ground mission segments.

[0045] Preferably, in step S6, the severe ground spectrum is compiled according to the severe ground overload cumulative overrun curve corresponding to different ground mission segments, specifically comprising:

[0046] S61, determining the load order based on the mission profile;

[0047] S62, calculating the load parameters of each load based on the severe ground overload cumulative overrun curve corresponding to different ground mission segments, the load parameters including equivalent load and equivalent load cycle number;

[0048] S63, assuming that the highest load in the flight glide mission segment in each taxi mission segment is the normal logarithmic extreme value distribution, determining the number of occurrences of each type of flight; assuming that the ground spectrum shape of various flight types is similar, compiling the 5x5 ground incremental overload spectrum of different ground mission segments under the mission profile;

[0049] S64, sequentially compiling the mission segment spectrum and the mission profile spectrum according to the 5x5 ground incremental overload spectrum;

[0050] S65, compiling the final flight-to-flight final load spectrum according to the mission profile spectrum.

[0051] Preferably, in step S64, the mission segment spectrum and the mission profile spectrum are sequentially compiled according to the 5x5 ground incremental overload spectrum, specifically comprising:

[0052] S641, according to the data in the 5x5 ground incremental overload spectrum, associating the kth flight type single take-off and landing of the ith ground mission segment of the jth profile with the occurrence frequency of each load and its corresponding load, randomly selecting peak and valley values for random pairing arrangement, forming the load spectrum of a specific flight type in different ground mission segments, representing the ground mission segment in the form of load pair sequence, and compiling the spectrum of various flight types under the ground mission segment;

[0053] The form of the load pair sequence is: f i,j,k =(Δn ydn ,-Δn ydm ) h

[0054] Where Δn ydn is the nth load of the ground mission segment, representing the peak load; -Δn ydm is the mth load of the ground mission segment, representing the valley load; n and m are natural numbers;

[0055] S642, arranging the spectrum of each ground mission segment of each mission profile, and compiling all mission profiles to obtain the mission profile spectrum.

[0056] Preferably, in step S65, the final flight-continuation-flight final load spectrum is compiled according to the mission profile, and specifically comprises:

[0057] According to the mission profile and a preset mission profile flight type vector, a mission profile sequence is constructed; all mission profiles in the mission profile sequence are sequentially numbered in a natural number sequence, and the numbers are correspondingly matched with a preset random integer sequence, and the final flight-continuation-flight load spectrum is obtained by sorting the values in the sequence.

[0058] According to the above technical solution, compared with the prior art, the application discloses a measured severe ground spectrum compilation method based on overload extrapolation, and has the following beneficial effects:

[0059] The application fully considers the ground load dispersion and ground load characteristics, can reflect the real ground load condition encountered by the aircraft, expose the failure characteristics of the aircraft as early as possible, and reduce the time of the aircraft fatigue test. BRIEF DESCRIPTION OF DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute a part of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of the provided drawings.

[0061] Figure 1 The method flowchart provided for the embodiments of the present application is shown in the following;

[0062] Figure 2 The peak-valley value detection schematic diagram provided for the embodiments of the present application is shown in the following;

[0063] Figure 3 The overload time history count screening data schematic diagram provided for the embodiments of the present application is shown in the following. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0065] As shown in the following, Figure 1 The application discloses a measured severe ground spectrum compilation method based on overload extrapolation, which comprises:

[0066] S1, determining a flight mission profile according to the use requirement of the aircraft, and dividing the flight process of the aircraft into a plurality of ground mission segments according to the flight mission profile, the plurality of ground mission segments including a taxiing mission segment and a crash mission segment;

[0067] S2, obtaining measured load data corresponding to different ground mission segments of the aircraft, and preprocessing the measured load data to obtain corresponding ground overload peak-valley value data;

[0068] S3, filtering and screening the obtained ground overload peak-valley value data of each measured take-off and landing based on incremental overload to obtain cumulative overrun numbers corresponding to each level of ground overload;

[0069] S4, fitting the overload cumulative overrun numbers to obtain a family of ground overload cumulative overrun number curves corresponding to different ground mission segments;

[0070] S5, obtaining corresponding severe ground overload cumulative overrun number curves according to the ground overload cumulative overrun number curves corresponding to different ground mission segments;

[0071] S6, completing severe ground spectrum compilation according to the severe ground overload cumulative overrun number curves corresponding to different ground mission segments.

[0072] The above steps will be described in detail below.

[0073] In step S1, the flight mission profile is determined according to the use requirement of the aircraft, mainly referring to determining the mission profile, mission profile ratio and mission profile composition of the aircraft according to the use requirement of the aircraft, and giving mission profile parameters such as mission segment, height, speed, weight, flight distance, flight time, etc.

[0074] In this embodiment, the flight process of the aircraft is divided into a plurality of ground mission segments according to the flight mission profile, and the division criteria specifically include:

[0075] 1) The take-off taxiing start point is determined by the criterion that the speed is greater than 0 after the engine test is completed;

[0076] 2) The take-off taxiing end point is determined by the criterion that the three landing gears completely leave the ground;

[0077] 3) The landing crash start point is determined by the change of Y-direction load;

[0078] 4) The landing crash end point is determined by the criterion that the main landing Y-direction load returns to the ground stable state;

[0079] 5) The landing taxiing start point is determined by the criterion that the main landing gear contacts the ground;

[0080] 6) The landing taxiing end point is determined by the criterion that the yaw angle is greater than 10°.

[0081] In step S2, the measured load data corresponding to different ground mission segments of the aircraft is acquired, and the measured load data is processed, specifically including:

[0082] S21, the measured load data corresponding to different ground mission segments of the aircraft is standardized processed;

[0083] The standardized processing refers to correcting the load data of different ground mission segments of the aircraft according to the true mass corresponding to the aircraft and the ratio of the true mass to the standard aircraft mass of different ground mission segments of the mission profile.

[0084] More specifically, according to the regulations of the aircraft profile, the Y-direction overload data of the aircraft center of gravity and the wing are corrected according to the ratio of the true mass "G i " corresponding to the aircraft to the standard aircraft mass "G0" of the mission profile, that is:

[0085] △n y0 =△n yi *G i / G0 (1)

[0086] In the formula, △n y0 is the corrected overload value according to the standard mission segment regulations; △n yi is the measured overload value. The load true mass data is calculated according to the aircraft weight minus fuel consumption, and the fuel consumption is calculated according to the total average (the time for calculating the average fuel consumption is from the start of take-off taxiing to the end of landing impact)

[0087] S22, peak and valley value detection is performed on the standardized processed measured load data to obtain overload peak and valley value data corresponding to different ground mission segments.

[0088] The peak and valley value detection is performed on the standardized processed measured load data, specifically including:

[0089] The time series data of the standardized processed measured load data is obtained, if the sequence data at a certain time point is greater than the sequence data at adjacent time points, the sequence data at the time point is taken as a peak value; if the sequence data at a certain time point is less than the sequence data at adjacent time points, the sequence data at the time point is taken as a valley value; and the sequence data other than the peak and valley values is filtered out.

[0090] Specifically, the peak and valley value detection is to detect all peak and valley values in the counting process, filter out the data between the peak and valley values, and retain the corresponding sampling point serial numbers. As shown in Figure 2 , Δn z1 , Δn z3 , Δn z5 , Δn z6 , Δn z7, Δn z8 , Δn z10 , Δn z2 , Δn z4 , Δn z9 , Δn

[0091] If the condition is met , the peak value is taken, and if the condition is met , the valley value is taken once.

[0092] In step S3, the obtained ground overload peak and valley value data is filtered and screened based on the incremental overload to obtain the cumulative overrun number corresponding to each level of ground overload, specifically including:

[0093] The overload peak and valley value data of different ground mission segments is filtered and screened again to obtain the corresponding ground overload cumulative overrun number;

[0094] Specifically, as shown in Figure 3 , the ground overload time history is counted, and the incremental overload with a small amplitude near the mean value needs to be filtered out, and the specific processing requirements are as follows:

[0095] 1) The peak value must meet the maximum value between two valley values, and must meet the condition that the difference between the peak value (p) and the previous and subsequent valley values (v i ) is not less than 50% of the peak value, that is, the condition The peak value must be greater than 0.1g, unless the next valley value is less than -0.1g.

[0096] 2) The valley value must meet the lowest value of two peak values, and at least 0.1g lower than the previous and subsequent peak values.

[0097] In step S4, the merged overload cumulative overrun number is fitted to obtain a family of ground overload cumulative overrun number curves corresponding to different ground mission segments, specifically including:

[0098] S41, divide the ground overload cumulative overrun number into positive ground overload cumulative overrun number and negative ground overload cumulative overrun number;

[0099] S42, for the sliding mission segment, calculate the geometric mean of the positive ground overload cumulative overrun and the negative ground overload cumulative overrun number to obtain the merged overload cumulative overrun number of the sliding mission segment;

[0100] For the impact mission segment, the positive overload cumulative overrun number and the negative overload cumulative overrun number of the impact mission segment are obtained respectively;

[0101] The peak value selected by the above method is greater than 0, and the valley value is less than 0. Select a number of levels of load, and record the positive ground overload cumulative overrun number and the negative ground overload cumulative overrun number as N(+Δn y) and N(-Δn y ).

[0102] For the taxiing task segment, the geometric mean is used to obtain a merged ground overload corresponding cumulative number of exceedances, so that the cumulative number of exceedances curve of ±Δn y is obtained, as shown in equation (2).

[0103]

[0104] For the ground task segment other than taxiing (landing impact task segment), in general, the positive and negative overloads are processed separately and are not considered symmetric.

[0105] S43, for the taxiing task segment, the merged overload cumulative number of exceedances is used for fitting to obtain the overload cumulative number of exceedances curve of the taxiing task segment, and the fitting equation is:

[0106]

[0107] Wherein, N1 represents the merged overload cumulative number of exceedances of the taxiing task segment, Δn y1 represents the incremental overload of the taxiing task segment, and a1, b1 represent fitting parameters of the taxiing task segment.

[0108] For the impact task segment, the positive overload cumulative number of exceedances and the negative overload cumulative number of exceedances are used for fitting respectively to obtain the positive overload cumulative number of exceedances curve and the negative overload cumulative number of exceedances curve of the impact task segment, and the fitting equation of the positive overload cumulative number of exceedances curve of the impact task segment is: Δn y2 =a2*lgN2(Δn y2 )+b2; the fitting equation of the negative overload cumulative number of exceedances curve of the impact task segment is: -Δn y2 =a2*lgN2(-Δn y2 )+b2, wherein, N2(Δn y2 ) represents the positive overload cumulative number of exceedances of the impact task segment, Δn y2 represents the positive incremental overload of the impact task segment, N2(-Δn y2 ) represents the negative overload cumulative number of exceedances of the impact task segment, -Δn y2 represents the negative incremental overload of the impact task segment, and a2, b2 represent fitting parameters of the impact task segment.

[0109] In step S5, the ground overload cumulative number of exceedances curve corresponding to different ground task segments obtains the corresponding severe ground overload cumulative number of exceedances curve, which specifically includes:

[0110] S51, discretize the ground overload cumulative number of exceedances curve corresponding to different ground task segments to obtain the overload exceedance data pairs corresponding to different ground task segments.

[0111] Specifically, the overload-accumulative exceedance curve of the taxiing mission segment is discretized. The discretization is (Δn y1 , N1) i (i = 1, …, n) data pairs.

[0112] The overload-accumulative exceedance curve of the landing impact mission segment is discretized. The discretization is (Δn y2 , N2) i (i = 1, …, n) and (-Δn y2 , N2) i (i = 1, …, n) data pairs.

[0113] S52, distribution characteristic detection is performed on the overload exceedance data pairs, assuming that the overload corresponding to the specified accumulative exceedance is subject to a normal distribution;

[0114] Generally, the variable model is used to complete the exceedance distribution characteristic detection, and the present application assumes that the overload Δn y corresponding to the specified N is subject to a normal distribution

[0115] S53, distribution parameters are estimated by using a maximum likelihood function estimation method, and the likelihood function is:

[0116]

[0117] In the formula, x i = lgΔN i , μ represents the logarithmic median of the overload increment, and σ represents the standard deviation of the overload;

[0118]

[0119]

[0120] When specifically facing different ground mission segments of the taxiing mission segment or the impact mission segment, N i and Δn y in the formulas (4), (5), and (6) will take different values, and different subscripts can be used for specific differentiation.

[0121] S54, according to the likelihood function and the distribution parameters, the overload increment covering a 90% coverage rate is extrapolated, that is,

[0122] Δn y90,i = μ i + μ 90 σ i

[0123] Wherein, μ i , σ irespectively, are the logarithmic median and standard deviation of the overload corresponding to the i-th level overload; obtain the serious overload exceedance data pairs corresponding to different ground mission segments;

[0124] In the present application, the serious spectrum reflects the serious use condition of 90% of the aircraft in the fleet, and the corresponding overload-accumulative exceedance curve is the accumulative exceedance curve corresponding to 90% reliability.

[0125] S55, fitting the serious overload exceedance data pairs to obtain the serious ground overload accumulative exceedance curves corresponding to different ground mission segments.

[0126] After obtaining the (Δn y90,i , N) i data pairs of the ground taxi mission segment and the (Δn y90,i , N) i and (-Δn y90,i , N) i data pairs of the landing impact mission segment, the fitting method of step S34 can be used to obtain the serious ground overload accumulative exceedance curves of the ground taxi mission segment and the landing impact mission segment.

[0127] In step S6, the serious ground spectrum is compiled according to the serious ground overload accumulative exceedance curves corresponding to different ground mission segments, and specifically includes:

[0128] S61, determining the load order based on the mission profile;

[0129] S62, calculating the load parameters of each load order based on the serious ground overload accumulative exceedance curves corresponding to different ground mission segments, wherein the load parameters include equivalent load and equivalent load cycle number;

[0130] Based on the serious ground overload accumulative exceedance curves of the mission segment, the equivalent calculation of the load spectrum is performed. The calculation of the equivalent load: assuming that a discrete segment needs to be calculated, the equivalent load of the discrete segment is Δn yd , the equivalent load cycle number is N eq , a m-segment straight line is used to replace the curve of the discrete segment, and the linear equation of the i-th segment is:

[0131] Δg=a i lgN+b i (7)

[0132] wherein a i and b i are constants of the i-th load spectrum curve.

[0133] Then the equivalent load is:

[0134]

[0135] wherein:

[0136]

[0137] S is the material S-N curve slope parameter, S = 2.0 for aluminum alloy.

[0138] Equivalent load cycle times

[0139]

[0140] It should be noted that for the landing impact mission segment, the positive and negative overloads need to be equal, so that the positive and negative overloads can be paired without generating excess peaks or valleys. The Δn yd with the smallest absolute value of negative overload can be modified eq so that the corresponding N i,j,k is changed to satisfy the equality of the positive and negative overloads.

[0141] S63, according to the assumption that the highest load of the flight glide mission segment in each glide mission segment is a normal logarithmic extreme value, determine the number of occurrences of each type of flight; according to the assumption that the ground spectrum shape of various flight types is similar, compile the 5x5 ground incremental overload spectrum of different ground mission segments in the mission profile;

[0142] S64, according to the 5x5 ground incremental overload spectrum, compile the mission segment spectrum and the mission profile spectrum in turn;

[0143] Specifically, it includes:

[0144] S641, according to the data in the 5x5 ground incremental overload spectrum, associate the kth flight type single take-off and landing of the ith ground mission segment of the jth profile with the corresponding occurrence frequency of each level load and its each level load, randomly and alternately select the peak and valley values for random pairing arrangement, form the load spectrum of the specific flight type of different ground mission segments, express the ground mission segment as a form of load pair sequence, and compile the spectrum of various flight types under the ground mission segment;

[0145] The form of the load pair sequence is: f i,j,k = (Δn ydn ,-Δn ydn ) h (11)

[0146] Where Δn ydn is the nth load of the ground mission segment, representing the peak load; -Δn ydm is the mth load of the ground mission segment, representing the valley load; n and m are both natural numbers.

[0147] S642. Arrange the ground mission segment spectra of each mission profile and compile all mission profiles to obtain the mission profile spectrum.

[0148] 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,k Sort 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.

[0149] 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 ]

[0150] The hollow profile includes three ground mission segments: takeoff taxiing, landing impact, and landing taxiing. Each ground mission segment is divided into five typical flight types according to different severity levels. Therefore, for each ground mission segment of the hollow profile, a profile spectrum of five typical flight types needs to be compiled, representing the severity of each flight type. These are denoted as A1, B1, C1, D1, and E1. When compiling the A1 spectrum, the spectra of flight type A under each mission segment are arranged, 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.

[0151] The principle for determining typical flight types is as follows: using the ground spectrum of the aircraft taxiing mission segment with the highest load as a benchmark, and assuming that the highest load in each aircraft taxiing mission segment follows a normal logarithmic extreme distribution, determine the frequency of each type of flight (determine y). i Based on the assumption that the ground spectrum shapes of various flight types are similar, ground incremental overload spectra for various flight types are compiled for 1000 flights (determining B). ij As shown in Table 1, flight types A, B, C, D, and E represent five different levels of severity for takeoffs and landings. Flight type A is the most severe.

[0152] Table 1 5×5 spectrum

[0153]

[0154] The sum of y1+y2+y3+y4+y5 in the table should be equal to the number of times the profile appears in 1000 flights. The 5x5 spectrum of each mission segment under all profiles is compiled according to the above method. And the y1, y2, y3, y4, y5 of the 5x5 spectrum of each mission segment under each mission profile are the same. For the 5x5 spectrum of positive and negative overload of the landing impact mission segment, the same should also be ensured to complete the random pairing of positive and negative overload.

[0155] S65, according to the mission profile spectrum, the final flight-continuation flight final load spectrum is compiled.

[0156] In step S65, according to the mission profile spectrum, the final flight-continuation flight final load spectrum is compiled, specifically including:

[0157] According to the mission profile spectrum and the preset mission profile flight type vector, a mission profile spectrum sequence is constructed; first, all the mission profiles in the mission profile sequence are sequentially numbered in natural number sequence, and then the number is corresponded to the preset random integer sequence respectively, and sorted according to the size of each value in the sequence, to obtain the final flight-continuation flight load spectrum.

[0158] Specifically, the number of times y j,k of the jth profile (j=1, 2...L) under the kth flight type (k=1, 2...K) in 1000 flights is recorded. All y j,k are expressed in vector form as

[0159] 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 ] (12) In the formula, A is a vector of the number of times of each mission profile spectrum. Among them

[0160] The A vector and the B vector are in one-to-one correspondence, indicating how many times the mission profile spectrum appears in this 1000-time block spectrum. The total spectrum can be represented as a mission profile spectrum sequence G, G=A*B

[0161] The mission profile spectrum under each complete flight in G is reordered to obtain the final flight-continuation flight spectrum. The specific method is as follows: first, all the mission profiles in G are sequentially numbered in natural number sequence, and then the number is corresponded to the random integer sequence "x is " respectively, and sorted according to x is ​the value of the corresponding x is is 5, the corresponding task profile is placed in the 5th position) to obtain the final load spectrum.

[0162] In the embodiment of the present application, the random number sequence "x i " of the peak, valley value and total load spectrum G is randomly selected by using the pseudo-random method of multiplication congruence, and reasonable random results are obtained by adjusting the random parameters.

[0163] Multiplication congruence:

[0164] y i+1 = λy i (mod2 k ) (13)

[0165] x i =y i / 2 m (14)

[0166] First, the "y i " sequence is formed by formula (13), and then the random number sequence "x i " is obtained by formula (10). Calculate x i in the total sequence in the order from small to large xis, so that the random integer sequence "xis" is obtained.

[0167] Regarding the parameter values in (13) and (14), the initial value y1 is an odd number; the coefficient λ = 8t-3, t is any natural number, k is determined according to the random period "n" as needed, so that 2 k-2 ≥n; m is 2. By changing the size of y1, t, k, different random number sequences can be obtained.

[0168] In another embodiment, before fitting and calculating the overload cumulative exceedance data of each task segment, the overload cumulative exceedance data of each task segment is also subjected to high load cutting and low load cutting;

[0169] High load cutting: the high load that occurs once in 1000 flights of the task segment is taken as the cutting value;

[0170] Low load cutting: the spectrum usually contains a large number of small amplitude load cycles, which need to be deleted or equal damage converted to the lowest level load. Equal damage conversion refers to first cutting, and then converting to the lowest level load according to equal damage. Usually, the fatigue limit of the key position is determined according to the foregoing analysis, and the overload value corresponding to 70% to 80% of the fatigue limit is cut off.

[0171] The various embodiments described in this specification are implemented in a progressive manner, each embodiment focusing on the differences from other embodiments, and the same or similar parts between embodiments can be mutually referred to. For the apparatus disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0172] The above description of disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for compiling measured severe ground spectra based on overload extrapolation, characterized in that, The method includes the following steps: S1. Based on the aircraft usage requirements, determine the flight mission profile, and divide the aircraft flight process into multiple ground mission segments based on the flight mission profile. The multiple ground mission segments include taxiing mission segments and impact mission segments. S2. Obtain the measured load data corresponding to different ground mission segments of the aircraft, and preprocess the measured load data to obtain the corresponding ground overload peak and valley value data. S3. Filter the measured ground overload peak and valley values ​​of each takeoff and landing based on incremental overload to obtain the cumulative exceedance number corresponding to each level of ground overload. S4. Fit the cumulative overload exceedance number to obtain a family of ground overload exceedance number curves corresponding to different ground mission segments; specifically including: S41. Divide the cumulative ground overload exceedance number into positive cumulative ground overload exceedance number and negative cumulative ground overload exceedance number; S42. For the taxiing mission segment, calculate the geometric mean of the positive ground overload cumulative exceedance number and the negative ground overload cumulative exceedance number to obtain the merged overload cumulative exceedance number of the taxiing mission segment. For the impact mission segment, the positive overload cumulative exceedance number and the negative overload cumulative exceedance number for the impact mission segment are obtained respectively; S43. For the taxiing task segment, the accumulated overload exceedance number after merging is used for fitting to obtain the accumulated overload exceedance number curve for the taxiing task segment. The fitting equation is: Where N1 represents the merged cumulative overload exceedance number of the taxiing task segment, Δn y1 This represents the incremental overload of the taxiing task segment, where a1 and b1 are both fitting parameters of the taxiing task segment. For the impact mission segment, the cumulative overload exceedance numbers for both positive and negative overloads are fitted to obtain the cumulative overload exceedance curves for both the positive and negative overloads. The fitting equation for the cumulative overload exceedance curve for the impact mission segment is: Δn y2 =a2*lgN2(Δn) y2 The fitting equation for the cumulative overload curve of the impact mission segment is: -Δn + b2; y2 =a2*lgN2(-Δn y2 )+b2, where N2(Δn y2 ) represents the cumulative positive overload exceedance number of the impact mission segment, Δn y2 This indicates the positive incremental overload of the impact mission segment, N2(-Δn) y2 ) represents the cumulative negative overload exceedance number of the impact mission segment, -Δn y2 This represents the negative incremental overload of the impact mission segment, where a2 and b2 are both fitting parameters of the impact mission segment. S5. Obtain the corresponding severe ground overload cumulative exceedance number curve based on the ground overload cumulative exceedance number curves corresponding to the different ground mission segments; S6. Compile the severe ground spectrum based on the cumulative exceedance number curves of severe ground overload corresponding to different ground mission segments.

2. The method for compiling measured severe ground spectra based on overload extrapolation according to claim 1, characterized in that, In step S1, the aircraft flight process is divided into multiple ground mission segments based on the flight mission profile. The specific criteria for this division include: 1) The takeoff taxiing start point is determined by the speed being greater than 0 after the engine test is completed; 2) The takeoff taxiing end point is determined by the complete departure of all three landing gears from the ground; 3) The landing impact initiation point is determined by the change in Y-axis load; 4) The landing impact termination point is determined by the return of the main launcher's Y-axis load to a stable ground state; 5) The landing taxiing start point is determined by the main landing gear contacting the ground; 6) The landing taxiing end point is determined by a yaw angle greater than 10°.

3. The method for compiling measured severe ground spectra based on overload extrapolation according to claim 1, characterized in that, Step S2 specifically includes: S21. Standardize the measured load data corresponding to different ground mission segments of the aircraft. S22. Perform peak-valley value detection on the standardized measured load data to obtain overload peak-valley value data corresponding to different ground mission segments.

4. The method for compiling measured severe ground spectra based on overload extrapolation according to claim 3, characterized in that, Step S21 involves standardizing the measured load data corresponding to different ground mission segments of the aircraft, specifically including: According to the specifications of the aircraft mission profile, the load data of different ground mission segments of the aircraft are corrected by the ratio of their corresponding actual mass to the standard aircraft mass of different ground mission segments of the mission profile.

5. The method for compiling measured severe ground spectra based on overload extrapolation according to claim 3, characterized in that, In step S22, peak and valley values ​​are detected on the standardized measured load data, specifically including: Obtain time series data of the measured load data after standardization. If the sequence data at a certain time point is greater than the sequence data at the adjacent time points, then the sequence data at that time point is taken as the peak value; if the sequence data at a certain time point is smaller than the sequence data at the adjacent time points, then the sequence data at that time point is taken as the valley value; and filter out the sequence data other than the peak and valley values.

6. The method for compiling measured severe ground spectra based on overload extrapolation according to claim 1, characterized in that, In step S5, the corresponding severe ground overload cumulative exceedance number curve is obtained based on the ground overload cumulative exceedance number curves corresponding to different ground mission segments, specifically including: S51. Discretize the cumulative overload exceedance curves of different ground mission segments to obtain overload exceedance data pairs for different ground mission segments. S52. Perform distribution characteristic detection on the overload exceedance number data pairs, assuming that the overload corresponding to the specified cumulative exceedance number follows a normal distribution; S53. Estimate the distribution parameters using the maximum likelihood function estimation method, where the likelihood function is: In the formula x i =lgΔN i μ represents the logarithmic median of the overload increment, and σ represents the standard deviation of the overload. S54. Based on the likelihood function and distribution parameters, extrapolate the overload increment with a coverage rate of 90%, i.e. Where, μ i σ i These are the log-median and standard deviation of the overload corresponding to the i-th level overload N; obtain the severe overload exceedance data pairs corresponding to different ground mission segments; S55. Fit the severe overload exceedance number data pair to obtain the severe ground overload cumulative exceedance number curve corresponding to different ground mission segments.

7. The method for compiling measured severe ground spectra based on overload extrapolation according to claim 6, characterized in that, In step S6, the severe ground spectrum is compiled based on the cumulative exceedance number curves of severe ground overload corresponding to different ground mission segments, specifically including: S61. Determine the number of load levels based on the mission profile; S62. Based on the cumulative exceedance number curve of severe ground overload corresponding to different ground mission segments, calculate the load parameters for each load level, wherein the load parameters include the equivalent load and the equivalent load cycle number; S63. Based on the assumption that the highest load in the glide mission segment of each taxiing mission segment is a normal logarithmic extreme distribution, determine the number of occurrences of each type of flight; based on the assumption that the ground spectrum shapes of various flight types are similar, compile a 5×5 ground incremental overload spectrum for different ground mission segments under the mission profile. S64. Based on the 5×5 ground incremental overload spectrum, compile the mission segment spectrum and mission profile spectrum in sequence. S65. Compile the final flight-continued flight payload spectrum based on the mission profile spectrum.

8. The method for compiling measured severe ground spectrum based on overload extrapolation according to claim 7, characterized in that, Its features are, In step S64, the mission segment spectrum and mission profile spectrum are sequentially compiled based on the 5×5 ground incremental overload spectrum, specifically including: S641. Based on the data in the 5×5 ground incremental overload spectrum, the loads of each level and their corresponding frequencies of occurrence under the single take-off and landing of the k-th flight type in the i-th ground mission segment of the j-th profile are linked together. Peak and valley values ​​are randomly and alternately selected and arranged in pairs to form the load spectrum of specific flight types in different ground mission segments. The ground mission segment is represented as a load pair sequence, and the spectrum of various flight types under the ground mission segment is compiled. The load pair sequence is in the form of: f i,j,k =(Δn) ydn ,-Δn ydm )h Where, Δn ydn This represents the nth load level of the ground mission segment, indicating the peak load; -Δn ydm Let m be the m-th load of this ground mission segment, representing the valley load; n and m are both natural numbers. S642. Arrange the ground mission segment spectra of each mission profile and compile all mission profiles to obtain the mission profile spectrum.

9. The method for compiling measured severe ground spectra based on overload extrapolation according to claim 7, characterized in that, Its features are, In step S65, the final flight-continuation-flight payload spectrum is compiled based on the mission profile spectrum, specifically including: A mission profile spectrum sequence is constructed based on the mission profile spectrum and the preset mission profile flight type vector. First, all mission profiles in the mission profile sequence are numbered sequentially with natural numbers. Then, each number is associated with a preset random integer sequence and sorted according to the size of each value in the sequence to obtain the final flight-continuation-flight payload spectrum.

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