A method for converting a buffet frequency spectrum of an aircraft structure into a fatigue load spectrum

Abstract

The present application belongs to the technical field of aircraft structure fatigue strength, and particularly relates to a method for converting a buffeting frequency spectrum of an aircraft structure into a fatigue load spectrum, comprising the following steps: Step 1: processing buffeting response load data of the aircraft structure to obtain a first-order bending modal characteristic frequency f1; Step 2: performing narrowband filtering on the buffeting response load data, and calculating a root mean square value σ of the filtered narrowband buffeting response load data; Step 3: performing rainflow counting on the filtered narrowband buffeting response load data to count the amplitude distribution of the narrowband buffeting response load data; fitting the amplitude distribution of the narrowband buffeting response load data with a Rayleigh distribution; and equivalently distributing the amplitude distribution fitted with the Rayleigh distribution to three typical load amplitudes; and Step 4: establishing a periodic step load spectrum according to the frequency of the three equivalent typical load amplitudes.

Description

Technical Field

[0001] This invention belongs to the field of aircraft structural fatigue strength technology, specifically relating to a method for converting the flutter spectrum of an aircraft structure into a fatigue load spectrum. Background Technology

[0002] Modern advanced fighter jets experience severe airflow separation in the high angle-of-attack / post-stall region. The high-intensity detached vortices can cause fluttering on multiple wing surfaces, including the horizontal and vertical stabilizers. This harsh fluttering environment significantly reduces the fatigue life of the structure, leading to premature fatigue cracks and even compromising flight safety.

[0003] Flutter loads on aircraft wing structures are typically dynamic responses (spectral data) and are also influenced by maneuvering loads, placing the wing under simultaneous static and flutter load conditions. In this context, it is difficult to calculate the structural life using traditional fatigue analysis methods, and simultaneously applying both conventional fatigue and flutter spectra in experiments presents significant challenges; there are currently no successful examples in the industry. If the flutter spectrum could be converted to a conventional fatigue spectrum, and the fatigue damage caused by both could be ensured to be equivalent, then the aforementioned problems could be effectively solved. Summary of the Invention

[0004] The purpose of this invention is to propose a method for converting the flutter spectrum of an aircraft structure into a fatigue load spectrum, which can be used for fatigue life analysis and testing of aircraft wing structures under flutter.

[0005] The technical solution of the present invention:

[0006] A method for converting the flutter spectrum of an aircraft structure into a fatigue load spectrum includes the following steps:

[0007] Step 1: Process the buffeting response load data of the aircraft structure to obtain the first-order bending mode characteristic frequency f1;

[0008] Step 2: Perform narrowband filtering on the chattering response load data and calculate the root mean square value σ of the filtered narrowband chattering response load data;

[0009] Step 3: Perform rainflow counting on the filtered narrowband chatter response load data and statistically analyze the amplitude distribution of the narrowband chatter response load data;

[0010] The amplitude distribution of narrowband flutter response load data was fitted using the Ruili distribution.

[0011] The amplitude distribution after fitting the Ruili distribution is equivalent to three typical load amplitudes;

[0012] Step 4: Establish a periodic stepped load spectrum based on the frequency of the amplitudes of the three equivalent typical loads.

[0013] Furthermore, in step one, the vibration response load data is one of bending moment, strain, or stress;

[0014] Perform a Fourier transform on the buffeting response load data, and identify the first-order bending mode characteristic frequency f1 based on the Fourier transform result.

[0015] Furthermore, in step two, the filtering frequency range for narrowband filtering is 0.9f1 to 1.1f1.

[0016] Furthermore, in step two, the root mean square value σ of the filtered narrowband chattering response load data is fitted by a Gaussian fitting formula or calculated by the following formula:

[0017]

[0018] Where, x i represents the filtered narrowband chatter response load data value, i = 1:n; n is the total number of filtered narrowband chatter response load data points.

[0019] Furthermore, in step three, the three typical load amplitudes are 2σ, 3σ, and 4σ, where σ is the root mean square value of the filtered narrowband chattering response load data.

[0020] Furthermore, in step three, the load amplitude damage between 1.5σ and 2.5σ according to the Rayleigh distribution is equivalent to the typical load amplitude of 2σ occurring P 2σ The damage caused by this load amplitude between 2.5σ and 3.5σ is equivalent to the damage caused by a typical load amplitude of 3σ. 3σ The damage caused by this event, with load amplitude damage in the 0 to 1.5σ range and the 3.5σ to 4.5σ range, is equivalent to the damage caused by a typical load amplitude of 4σ. 4σ Damage caused by this load amplitude greater than 4.5σ is negligible.

[0021] Furthermore, in step three, P 2σ P 3σ P 4σ Calculate using the following formulas respectively:

[0022]

[0023]

[0024]

[0025] Where T is the chattering period, C is the metal material constant; m is the fatigue index, which ranges from 4 to 12 for different materials, and x... a This represents the load amplitude.

[0026] Furthermore, in step four, the period of the periodic stepped load spectrum is equal to the chattering period T; the chattering amplitudes within each period are 2σ, 3σ, 4σ, 3σ, and 2σ, respectively, and are symmetrically distributed.

[0027] The total number of times 2σ, 3σ, and 4σ occur in each cycle is P. 2σ P 3σ P 4σ .

[0028] The beneficial effects of this invention are:

[0029] This invention converts high-frequency buffeting response load data into a quasi-static fatigue load spectrum, significantly reducing the number of load data points while ensuring that the fatigue damage caused to the structure by both is equivalent. It simplifies the fatigue analysis and experimental verification of buffeting airfoil structures, saves time and costs, and has significant economic benefits. Attached Figure Description

[0030] Figure 1 A schematic diagram of a method for converting the flutter spectrum of an aircraft structure into a fatigue load spectrum;

[0031] Figure 2 A schematic diagram of chattering response and fast Fourier transform;

[0032] Figure 3 This is a schematic diagram of the chatter response distribution after narrowband filtering;

[0033] Figure 4 This is a schematic diagram of the amplitude distribution of the chattering cycle;

[0034] Figure 5 This is a schematic diagram of the amplitude distribution under a typical load cycle;

[0035] Figure 6 This is a schematic diagram of a low-high-low stepped load spectrum. Detailed Implementation

[0036] 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0037] Step 1: Preprocess the buffeting response load data of the structure to obtain the first-order bending mode characteristic frequency f1;

[0038] Obtain load data (bending moment, strain, or stress) of the flutter response of the aircraft wing structure, perform a Fourier transform on the data, and identify the characteristic frequency f1 of the first-order bending mode, such as... Figure 2 As shown.

[0039] Step 2: Perform bandpass filtering on the Fourier transform spectrum to retain narrowband data near the first bending frequency (f1±0.1f1), and then perform inverse Fourier transform to obtain the filtered chattering response load data and calculate the root mean square value.

[0040] The remaining narrowband chattering response load data after filtering is a Gaussian random process; distribution verification is shown below. Figure 3 The root mean square σ of the chattering response load can be given by Gaussian fitting or calculated directly by the following formula:

[0041]

[0042] x represents the load response value at a certain point in time, and n is the total number of data points.

[0043] Step 3: Set up three typical load cycles (amplitudes of 2σ, 3σ, and 4σ, with a mean of 0), and determine the frequency (P) of each typical load cycle occurring within one chattering cycle (time T). 2σ P 3σ and P 4σ );

[0044] Rainflow counting is performed on the narrowband chatter response load data after the previous filtering step to obtain the chatter load cycle and the amplitude x of the narrowband chatter load. a It follows a Rayleigh distribution; distribution verification can be found in [link to documentation]. Figure 4 The Rayleigh probability density function is

[0045]

[0046] Based on the characteristics of Rayleigh distribution, the probability of large loads above 4.5σ occurring is less than 0.01%, which can be ignored for fatigue. The cutoff level for high loads is 4.5σ. There are many small cyclic loads below 1.5σ, which can be compressed and converted into the high-level load range.

[0047] Based on the above two reasons, three levels of typical load states are defined: Level 1 (2σ), Level 2 (3σ), and Level 3 (4σ). Loads with a Rayleigh distribution between 1.5σ and 2.5σ are converted to a typical load of 2σ; loads between 2.5σ and 3.5σ are converted to a typical load of 3σ; loads between 3.5σ and 4.5σ are converted to a typical load of 4σ; and small loads below 1.5σ are also converted to a typical load of 4σ to minimize the total number of cycles. Figure 5 As shown.

[0048] The conversion method is based on the stress-fatigue SN curve of metallic materials.

[0049] S m N = C (3)

[0050] S is the load amplitude, C is the metal material constant; m is the fatigue index, which ranges from 4 to 12 for different materials, and N is the fatigue life.

[0051] When the load amplitude is continuously distributed and the distribution function is f(S), the expected fatigue damage to the structure from one load cycle is...

[0052]

[0053] The amplitude of the chattering load x a Substituting the distribution function into the above equation, the cumulative fatigue damage of the structure within one chattering cycle T is:

[0054]

[0055] Based on fatigue damage equivalence, the loads in the above intervals are converted to the set three typical load levels (2σ, 3σ, and 4σ), and their respective occurrence frequencies P 2σ P 3σ and P 4σ The solution can be obtained by the following formula.

[0056]

[0057] Step 4: Arrange the three typical load levels into a stepped fatigue load spectrum in a low-high-low pattern.

[0058] Combine the three typical load levels into Figure 6 The low-high-low stepped loading spectrum shown (one period) has a first order of P. 2σ Half of the load cycles have an amplitude of 2σ, and the second order has an amplitude of P. 3σ Half of the load cycles have an amplitude of 3σ, and the third cycle has an amplitude of P. 4σ The amplitude of the number of load cycles is 4σ, and the fourth order is P. 3σ Half of the load cycles have an amplitude of 3σ, and the fifth stage has an amplitude of P. 2σ Half of the cycles have an amplitude of 2σ. When the chattering duration has multiple cycles, the stepped load spectrum is repeated once per cycle.

[0059] The above description is merely a specific embodiment of the present invention, providing a detailed description of the invention. Parts not covered herein are conventional techniques. However, the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for converting the flutter spectrum of an aircraft structure into a fatigue load spectrum, characterized in that: The method includes the following steps: Step 1: Process the buffeting response load data of the aircraft structure to obtain the first-order bending mode characteristic frequency f1; Step 2: Perform narrowband filtering on the chattering response load data and calculate the root mean square value σ of the filtered narrowband chattering response load data; Step 3: Perform rainflow counting on the filtered narrowband chatter response load data and statistically analyze the amplitude distribution of the narrowband chatter response load data; The amplitude distribution of narrowband flutter response load data was fitted using the Ruili distribution. The amplitude distribution after fitting the Ruili distribution is equivalent to three typical load amplitudes; Step 4: Establish a periodic stepped load spectrum based on the frequency of the amplitudes of the three equivalent typical loads.

2. The method according to claim 1, characterized in that: In step one, the vibration response load data is one of bending moment, strain, or stress. Perform a Fourier transform on the buffeting response load data, and identify the first-order bending mode characteristic frequency f1 based on the Fourier transform result.

3. The method according to claim 2, characterized in that: In step two, the filtering frequency range for narrowband filtering is 0.9f1 to 1.1f1.

4. The method according to claim 3, characterized in that: In step two, the root mean square value σ of the filtered narrowband chattering response load data is calculated using the following formula: Where, x i represents the filtered narrowband chatter response load data value, i = 1:n; n is the total number of filtered narrowband chatter response load data points.

5. The method according to claim 4, characterized in that: In step three, the three typical load amplitudes are 2σ, 3σ, and 4σ, where σ is the root mean square value of the filtered narrowband chattering response load data.

6. The method according to claim 5, characterized in that: In step three, the load amplitude damage between 1.5σ and 2.5σ according to the Rayleigh distribution is equivalent to the typical load amplitude of 2σ occurring P 2σ The damage caused by this load amplitude between 2.5σ and 3.5σ is equivalent to the damage caused by a typical load amplitude of 3σ. 3σ The damage caused by this, with a load amplitude in the range of 3.5σ to 4.5σ, is equivalent to the damage caused by a typical load amplitude of 4σ occurring during P. 4σ The damage caused by this.

7. The method according to claim 6, characterized in that: In step three, P 2σ P 3σ P 4σ Calculate using the following formulas respectively: Where T is the chattering period, C is the metal material constant; m is the fatigue index, which ranges from 4 to 12 for different materials, and x... a This represents the load amplitude.

8. The method according to claim 7, characterized in that: In step four, the period of the periodic stepped load spectrum is equal to the chattering period T; the chattering amplitudes in each period are 2σ, 3σ, 4σ, 3σ, and 2σ, respectively, and are symmetrically distributed. The total number of times 2σ, 3σ, and 4σ occur in each cycle is P. 2σ P 3σ P 4σ .

9. The method according to claim 6, characterized in that: In step three, load amplitudes greater than 4.5σ in the Rayleigh distribution are ignored. Load amplitudes with a magnitude less than 1.5σ in the Rayleigh distribution are equivalent to the typical load amplitude of 4σ.

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