Shooting vibration environment simulation method based on impact response spectrum

Abstract

The invention belongs to the technical field of ground tests in the aviation system technology, and particularly relates to a bomb vibration environment simulation method based on an impact response spectrum. The blasting vibration environment simulation method aims at improving the accuracy of blasting impact environment simulation of aviation components in a ground test. The method comprises the following steps: firstly, calculating amplification coefficients of a low-frequency part and a high-frequency part by analyzing a resonance effect of a blasting frequency, and formulating an intermediate transition SRS according to the amplification coefficients; thirdly, constructing a shock waveform parameterized dictionary matrix, and synthesizing a single shot shock signal through an optimization algorithm; and then, copying, translating and combining the single shot vibration impact signals to form repeated impact signals, generating full-band random noise signals through a filter bank, compensating the full-band random noise signals to a repeated shot vibration impact curve, and finally forming multi-shot vibration impact environment time domain waveform signals meeting a target SRS curve. According to the invention, the simulation effect of the ground test of the shot vibration impact environment can be effectively improved, and the impact environment adaptability of the airborne equipment can be more accurately tested.

Description

Technical Field

[0001] The present invention belongs to the field of ground test technology in aviation system technology, and relates to a method for simulating a bombardment vibration environment based on an impact response spectrum, and specifically to a method for effectively simulating a bombardment vibration environment based on an impact response spectrum in a ground laboratory. Background Art

[0002] Gun shock refers to the transient, high-frequency, repetitive excitations experienced by materials and structures during gunfire, such as the vibrations produced by the firing of a gun on an aircraft. This shock is characterized by a relatively short duration, but can be repeated if multiple shots are fired.

[0003] The main problem with the cannon shock environment is that it may damage the structural and functional integrity of airborne equipment. Common structural failures include changes in the friction characteristics of the connection parts, permanent mechanical deformation, accelerated material fatigue, and cracks in brittle materials (such as optical materials). In terms of functionality, cannon shock may cause temporary changes in the performance of equipment components at the moment of impact, or permanent changes after the impact, affecting insulation resistance, magnetic and electrostatic field strength, and piezoelectric properties. Therefore, it is necessary to perform cannon shock testing on the equipment under a laboratory shaker, which helps to evaluate the equipment's ability to withstand actual cannon shock environments.

[0004] When conducting a cannon vibration shock test in the laboratory, an exciter (such as an electric vibration table) is required to provide time history signal data. According to the most widely used military standard MIL-STD-810H, the generation of cannon vibration shock signals mainly adopts the following three methods: (1) measurement data reproduction, (2) SRS (Shock Response Spectrum) generation, and (3) random sine generation. At present, the cannon vibration signal synthesis technology mainly adopts method (1) and method (3), that is, it is achieved by simulating the statistical characteristics of the measurement data and combining the random sine technology.

[0005] In many cases, it is not possible to obtain gun shock measurement data for in-service aircraft, making it impossible to synthesize experimental signals based on statistical characteristics. This may occur when designing a new aircraft model or installing equipment in a new location. In these cases, random generation methods can be used to generate gun shock signals, the most representative of which is the random plus sine method. However, this method is not suitable for simulating gun shock environments. The sine-plus-random vibration method provides a consistent rise time by superimposing harmonically related sinusoidal components to the stationary random vibration, but this is much lower than the rise time in the real gun shock environment, and its duration is much longer than the real gun shock environment. Therefore, random generation methods are not reliable and are usually used as a last resort to generate gun shock signals.

[0006] When measured cannon shock signals are not available, the use of shock response spectrum (SRS) generation methods should be given priority. Based on the predicted cannon shock SRS, a cannon shock signal that conforms to the SRS curve can be generated. Since SRS is the most widely used method for comparing shock severity, the generated shock signal is considered to have the same destructive force as the actual cannon shock. The standard MIL-STD-810 provides the basic requirements for generating signals from SRS. However, to date, no effective methods for synthesizing cannon shock signals from SRS have been found in public academic databases. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a bombardment vibration environment simulation method based on the shock response spectrum, so as to accurately simulate the vibration environment of aviation equipment during the bombardment process under laboratory conditions, so as to facilitate the evaluation and ensure the reliability of its structure and function.

[0008] S1. Develop an intermediate transition SRS based on the resonance effect and the target SRS spectrum.

[0009] The gun shock signal can be synthesized according to the target SRS, simplifying the SRS into a piecewise function: the low-frequency range is a linear rising part (expressed in logarithmic scale), while the high-frequency range is a flat platform part. The target SRS can be expressed as:

[0010]

[0011] in

[0012] k: slope;

[0013] f: frequency variable;

[0014] F I : starting frequency;

[0015] F K : inflection point frequency;

[0016] F C : cut-off frequency;

[0017] A I : Starting frequency F I The acceleration amplitude at ;

[0018] A K : Inflection point frequency F K The acceleration amplitude at .

[0019] The slope k is defined as:

[0020]

[0021] likeFigure 1 As shown in the figure, the synthesis process of the gun shock includes the following three steps: (a) synthesizing the signal of a single shock event, (b) copying and splicing the single shock signal to form multiple shock signals, and (c) adding stable random vibration for SRS compensation. When splicing shock signals multiple times, especially in the low frequency band, due to the time interval between repeated single shock signals, these repeated signals will form a resonance phenomenon at a certain frequency. The frequency of resonance is closely related to the firing rate of the weapon, so an intermediate SRS can be constructed for a single gun shock, and its acceleration amplitude is low. Based on the single-shot gun shock signal generated by this intermediate transition SRS, the synthesized SRS can be at the same level as the target SRS.

[0022] The intermediate transition SRS is calculated as follows:

[0023]

[0024] Where L I and L k are the amplification factors (dB) of the low-frequency and high-frequency parts, respectively, which are obtained by analyzing the resonance effect caused by the bombardment frequency.

[0025] The slope k' in the low frequency range is usually between 6-12dB / oct. According to the low frequency slope calculation formula, the inflection point frequency of the middle SRS can be calculated by the following formula:

[0026]

[0027] Therefore, the intermediate transition SRS can be expressed as:

[0028]

[0029] S2, analyzing the time domain characteristics of the single-shot shock signal and constructing a parameterized dictionary matrix of the shock waveform;

[0030] The intermediate transition SRS obtained from S1 synthesizes the signal of a single cannon shock. Figure 2 As shown in the figure, the single shot shock signal is discretely modeled in the form of matrix multiplication:

[0031] u=Ga(7)

[0032] where u∈R M is a single shot shock signal containing M samples, a∈R N is the amplitude vector, the matrix G∈R M×N Contains N column vectors g, that is, the matrix G

[0033] [g1 g2 g3 ... g N ] (8)

[0034] In order to better control the temporal characteristics of the cannon shock (especially the initial rise time and effective duration), each column vector g is generated from the shock waveform function,

[0035] g(t)=(e ωζ(τ-t) +ζ τω(ln t-ln τ )·sin(ωt))*δ φ (t) (9)

[0036] Where t is the time variable, δ is the Dirac delta function with a time delay φ, ω = 2πf is the center frequency in radians, ζ is the damping ratio, τ is the rise time (the time when the envelope peak appears), and '*' is the convolution operation. Using the convolution property, the delayed Dirac delta function is used to move the impulse waveform to any time position. Formula (9) is given in amplitude normalized form, and its absolute maximum amplitude is always 1.

[0037] The matrix G has N columns, each of which is controlled by four unknown parameters, so there are a total of 4N parameters that need to be defined. Applying the parameter dictionary design technique of the sparse representation method, let γ be the parameter space of G, which can be discretized into a parameter matrix Γ∈γ, where:

[0038]

[0039] is a 4×N matrix, the discrete impulse waveform g i is obtained by using the parameter vector γ i The input of formula (9) is given in Table 1 to better define the parameter space. The limit of frequency f depends on the frequency resolution and sampling rate of the signal, and the damping ratio is constrained by the normal physical range. The parameters τ and φ have an important influence on the rise time of the synthetic impulse, so they are set to the target rise time τ spec , the parameters in the matrix Γ can be obtained by solving the objective function:

[0040]

[0041] Table 1 Boundary constraints of shock waveform parameters

[0042]

[0043] Note: f s is the sampling rate of the signal.

[0044] Using the solution Γ′ obtained from formula (11), the matrix G′ can be calculated according to formula (9). Then, the impulse waveform sequence g′ is i The valid duration is checked and the waveforms that meet the conditions are combined into a new matrix G:

[0045] G = {g′ i |T(g′i )<T spec} (12)

[0046] Where T spec is the target duration. The function T(·) calculates the effective duration of the signal, for example, by the moving root mean square (RMS) method provided by MIL-STD-810H. By following the selection process in formula (12), the effective duration of each impulse waveform in the matrix G meets the specification requirements. Therefore, the synthesized impulse signal not only meets the requirements for effective duration, but also meets the expectations for the initial rise time.

[0047] S3. Construct the objective function of single-shot shock and synthesize the time domain curve of the single-shot shock environment.

[0048] For the synthesis problem of artillery shock, the main goal is to meet the required SRS specifications. But in addition, since the shock is essentially an elastic vibration of the structure, its amplitude in the positive and negative directions must be symmetrical, so "net zero displacement" is also an inherent requirement of the synthetic shock. Therefore, given the signal model, the synthesis problem of a single artillery shock can be transformed into a dual-objective optimization problem:

[0049]

[0050] Among them, l(·) is the objective function used to measure the error, and SRS(·) is the conventional SRS calculation function. In this dual-objective optimization, l1 is used to measure the error between the SRS of the synthesized single impact signal and the intermediate transition SRS, and l2 is used to measure whether the synthesized single impact signal meets the requirements of net displacement change. These objective functions can be minimized at the same time, similar to the single-objective optimization problem. By combining the objective functions and substituting formula (7), the dual-objective optimization problem can be converted into the following form:

[0051]

[0052] Where α controls the weight of the 'net zero displacement change' objective function. Given the matrix G, the amplitude vector α can be accurately and efficiently calculated by a heuristic algorithm (such as a genetic algorithm, simulated annealing algorithm, or particle swarm optimization). Subsequently, the single shot shock signal u is calculated by formula (7).

[0053] S4. Copy, translate and combine the single shot shock signal to form a repeated shock signal.

[0054] The single shot shock signal u is obtained through S3, and then it is copied, translated, and combined. The expression is:

[0055]

[0056] Among them, n is the number of shot vibrations, and λ is the time interval between adjacent shot vibrations. Although the displacement change of the synthesized single shot vibration waveform is the smallest, its displacement change will increase by n times after synthesis, which cannot be ignored. (-1) n The components control the net displacement change of multiple shot vibrations by offsetting the displacement of paired shot vibrations. The time domain image after splicing is as follows: Figure 3 shown.

[0057] S5. Generate a full-band random noise signal through a filter group, synthesize a low-frequency noise curve of repeated cannon shock impact, compensate the low-frequency noise curve to the repeated cannon shock impact curve, and finally form a multi-shot cannon shock environment time domain waveform signal that meets the target SRS curve.

[0058] The repeated impact signal obtained in S4 needs to add stable random vibration to compensate the low-frequency noise of the spliced ​​impact signal. The generated white noise signal r(t) follows the normal distribution:

[0059]

[0060] F' I to F' K A 1 / 12 octave filter bank is applied to the white noise r(t), producing a series of bandpass filtered signals:

[0061] r i (t)=(r*h i )(t) (17)

[0062] f i+1 =f i ×2 1 / 12 F I <f i <F′ K (18)

[0063] Among them, h i (t) is the impulse response of the ith bandpass filter, with center frequency f i .

[0064] Model the low-frequency noise w(t) as a linear combination of bandpass signals:

[0065] w(t)=∑b i ·r i (t) (19)

[0066] where b i is the amplitude parameter of each bandpass filtered noise. represents the low-frequency stationary noise of multiple impact signals.

[0067] The amplitude parameter b of the bandpass filtered signal can be controlled by another optimization problem: i:

[0068]

[0069] In formula (20), the noise signal is added to the spliced ​​impulse signal v(t) to compensate for its SRS and ensure that the SRS specification is met. Similar to the single impulse generation problem in formula (14), this optimization problem can also be solved by a common heuristic algorithm. The final generated multiple impulse signal s(t) is obtained by adding low-frequency noise w(t) to the spliced ​​impulse signal v(t):

[0070] s(t)=v(t)+w(t) (21)

[0071] The synthesized signal meets the target shock response spectrum specification.

[0072] Beneficial Effects

[0073] The present invention controls the synthesis of SRS time domain, realizes the synthesis of multiple shot shock environment time domain waveforms for a given SRS, and based on the shock waveform dictionary technology, the time characteristics such as the initial rise time and duration of a single shock and the repetition interval of multiple shocks are all controllable. This technology effectively improves the overall simulation effect of the ground test of the shot shock environment, and more accurately tests the shock environment adaptability of airborne equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 Schematic diagram of the synthesis steps of the cannon shock signal.

[0075] Figure 2 This is the algorithm flow chart for single impact signal synthesis.

[0076] Figure 3 This is the waveform diagram after the single-shot shock signal is copied, translated, and combined.

[0077] Figure 4 It is the target shock response spectrum (SRS) and the intermediate transition SRS spectrum diagram.

[0078] Figure 5 It is a tiled diagram of the shock waveform synthesized from a single shock signal, where g1 to g10 are the first ten shock waveform diagrams in the parameter dictionary G respectively.

[0079] Figure 6 (a) is the acceleration time history diagram of the synthesis result of the single-shot shock signal; Figure 6 (b) is the shock response spectrum (SRS) diagram of the synthesis result of the single-shot shock signal.

[0080] Figure 7 (a) is the acceleration time history diagram after the synthesis of multiple blast shock signals; Figure 7 (b) is the shock response spectrum (SRS) diagram after the synthesis of multiple blast shock signals.

[0081] Figure 8 (a) is the acceleration time history diagram of the synthesized low-frequency noise; Figure 8 (b) is the temporal shock response spectrum (SRS) of the synthesized low-frequency noise.

[0082] Fig. 9 (a) is the acceleration time history diagram of multiple synthetic blast shocks; Fig. 9 (b) is the shock response spectrum (SRS) diagram of the synthesized multiple blast shocks. DETAILED DESCRIPTION

[0083] The present invention is further illustrated by specific examples below. These examples are exemplary and are intended to illustrate the problem and explain the present invention, but are not intended to be limiting.

[0084] 1. Target SRS for the gun shock test

[0085] The target SRS in the present invention is derived from MIL-STD-810H. Based on this target SRS, an intermediate transition SRS is generated to synthesize a single impact signal. I and L K They are set to -9dB and -1dB respectively. This is chosen based on the estimation of the SRS resonance effect after impact splicing. The slope of the intermediate transition SRS is set to 6.4dB / oct. After determining these parameters, the inflection point frequency of the intermediate SRS is calculated using formula (5). Table 2 lists the parameters of the target SRS and its corresponding intermediate transition SRS. Figure 4 Two SRS curves are shown.

[0086] Table 2 Target SRS and intermediate transition SRS parameters of MIL-STD-810H standard

[0087]

[0088] 2. Synthesis of single shot shock signal

[0089] Construct the parameter matrix of the impulse waveform dictionary. Duration T spec , initial rise time τ spec , weight α and the total number of basis functions N are set to 15ms, 4ms, 0.1 and 40 respectively. Based on these parameters, the dictionary matrix G is calculated by equations (7)-(11). Figure 5 The graphs of the first ten impulse waveforms in the parameter dictionary G are shown. These waveforms are mainly concentrated in the duration of 15ms, and the time delay and initial rise time are both less than 4ms, thus ensuring that they basically coincide at 4ms.

[0090] The particle swarm optimization algorithm is used to solve the amplitude vector α from equation (13), and then the impact waveform is weighted superimposed according to its amplitude to generate a single impact signal, as shown in Figure 6 (a) and 6(b). The peak acceleration of the time history signal is 202.3 m / s 2 , the effective duration and initial time are about 15ms and 4ms respectively, which is in line with the requirements in the dictionary design process. The synthesized single impact signal oscillates around the zero axis, meeting the requirement of net zero displacement change. The SRS of the synthesized impact signal is highly consistent with the intermediate SRS, with almost no difference, and strictly meets the tolerance range of ±3dB in the entire frequency range.

[0091] 3. Synthesis of multiple blast shock signals

[0092] The synthesized single shock is replicated multiple times, and the specific number of shocks can be set arbitrarily. In this study, a gun shock signal containing 20 shocks is used as an example. These shocks are spliced ​​into a repeated signal with an interval of 15ms between each shock. This time interval is equal to the duration of a single gun shock shock, so there is no overlap between adjacent shock signals. These parameter settings correspond to a machine gun with a firing rate of 4000 rounds / minute, such as the M61A1 machine gun installed on the F-16 fighter. Its time history and corresponding SRS are shown in Figure 7 (a) and 7(b). Due to the resonance effect, the spliced ​​impact SRS is amplified in the low-frequency range. This amplification effect is particularly obvious compared with the intermediate transition SRS. The maximum resonance occurs at about 33 Hz, corresponding to an amplification ratio of more than 6. Subsequently, more resonances are observed at odd multiples of 33 Hz, but the amplification ratio gradually decreases. The maximum resonance frequency is half of the shooting rate, that is, 66 Hz. This difference is due to the opposite amplitudes of the two adjacent single impacts in equation (15). So a low-frequency resonance is formed between each pair of adjacent impacts. However, due to the design of the correct intermediate transition SRS, the SRS envelope of the spliced ​​impact just meets the target SRS.

[0093] The low-frequency noise signal is generated to compensate for the splicing shock. The white noise signal is randomly generated and filtered by a twelve-octave filter bank. The filtered signals with different center frequencies are superimposed by weighted sum, and the weights are calculated by the particle swarm optimization algorithm. The time history of the synthetic low-frequency noise and its SRS are shown in Figure 8 (a) and 8(b). The amplitude of the low-frequency noise is about 100m / s 2, which is about half of the maximum amplitude of the synthetic cannon shock, ensuring that the noise signal does not cover the cannon shock, thereby preserving the temporal characteristics. The SRS of the low-frequency noise meets the target SRS in the low-frequency range, but there is a large gap at some frequencies (such as 31Hz). After 150Hz, the acceleration amplitude decreases and tends to be stable in the high-frequency range.

[0094] The final synthesized multiple blast shocks are as follows Fig. 9 As shown in (a), it is the sum of low-frequency noise and spliced ​​shocks. The temporal characteristics of each individual shot shock are well preserved and clearly displayed in the time history. Fig. 9 In (b), the SRS of the synthesized multiple shot shocks is compared with the target SRS. The SRS of the synthesized shocks falls within the ±3dB bandwidth over the entire frequency range. There is some fluctuation in the low-frequency to high-frequency transition, around the inflection frequency of the intermediate SRS. Specifically, the maximum SRS error is 2.2dB at 32Hz, and the overall average error is only 0.45dB. Therefore, the synthesized multiple shot shock signal meets the requirements of the shot shock test very well.

[0095] The above embodiments are exemplary, and their purpose is to illustrate the technical concept and features of the present invention so that people familiar with the technology in this field can understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for simulating shelling vibration environment based on shock response spectrum, characterized in that: The following steps are involved: Step S1, formulating an intermediate transition SRS according to the resonance effect and the target SRS spectrum; Step S2, constructing a parameterized dictionary matrix of shock waveform based on the time domain characteristics of the single-shot shock signal; Step S3, constructing the objective function of the single-shot vibration impact, and synthesizing the time domain curve of the single-shot vibration impact environment; Step S4, copying, translating, and combining the single shot shock signal to form a repeated shock signal; Step S5, generate a full-band random noise signal, synthesize a low-frequency noise curve of repeated cannon shock impact, compensate the low-frequency noise curve to the repeated cannon shock impact curve, and finally form a multiple cannon shock impact environment time domain waveform signal that meets the target SRS curve.

2. The method for simulating shelling vibration environment based on shock response spectrum according to claim 1, characterized in that: In step S1, The target SRS is expressed as: in, k: slope; f: current frequency point; F I : starting frequency; F K : inflection point frequency; F C : End frequency; A I : Starting frequency F I The response amplitude at ; A K : Transition frequency F K The response amplitude at ; The slope k is defined as: The intermediate transition SRS is calculated as follows: Where L I and L k are the amplification factors (dB) of the low-frequency and high-frequency parts, respectively, obtained by analyzing the resonance effect caused by the bombardment frequency; The inflection point frequency of the middle SRS is calculated by the following formula: Therefore, the intermediate transition SRS is expressed as:

3. The method for simulating shelling vibration environment based on shock response spectrum according to claim 1, characterized in that: In step S2, The single shot shock signal is discretely modeled in the form of matrix multiplication: u=Ga where u∈R M is a single shot shock signal containing M samples, a∈R N is the amplitude vector, the matrix G∈R M×N Contains N column vectors g, that is, the matrix G [g1 g2 g3 … g N ] Each column vector g is generated from the impulse waveform function: g(t)=(e ωζ(τ-t)+ζτω(lnt-lnτ) ·sin(ωt))*δ φ (t) Where t is the time variable, δ is the Dirac delta function with a time lag φ, ω=2πf is the center frequency in radians, ζ is the damping ratio, τ is the rise time, and ‘*’ is the convolution operation; using the convolution property, the delayed Dirac delta function is used to move the impulse waveform to any time position.

4. The method for simulating shelling vibration environment based on shock response spectrum according to claim 3 is characterized in that: The matrix G has N columns, each column is controlled by four unknown parameters, and a total of 4N parameters need to be defined; the parameter dictionary design technique of the sparse representation method is applied, and γ is set as the parameter space of G, which is discretized into a parameter matrix Γ∈γ, where: The parameter matrix Γ is a 4×N matrix, and the discrete impulse waveform g i By using the parameter vector γ i As input to the equation; the frequency f is bounded by the frequency resolution and sampling rate of the signal, and the damping ratio is constrained by the normal physical range.

5. The method for simulating shelling vibration environment based on shock response spectrum according to claim 4 is characterized in that: in, The parameters τ and φ are set to the target rise time τ spec , the parameters in the matrix Γ are obtained by solving the objective function: Using the solution Γ′ of the above formula, calculate the matrix G′ according to the calculation formula of g(t) and check the impact waveform column g′ i The effective duration of the shock waveforms that meet the conditions is combined into a new matrix G: G={g′ i ∣T(g′ i ) <T spec } Among them, T spec is the target duration, and the function T(·) calculates the effective duration of the signal.

6. The method for simulating shelling vibration environment based on shock response spectrum according to claim 5, characterized in that: In step S3, The synthesis problem of single-shot shock is transformed into a dual-objective optimization problem: Among them, l(·) is the objective function used to measure the error; SRS(·) is the conventional SRS calculation function; in this dual-objective optimization, l1 is used to measure the error between the SRS of the synthesized single impact signal and the intermediate transition SRS, and l2 is used to measure whether the synthesized single impact signal meets the requirements of net displacement change; By minimizing these objective functions simultaneously, the bi-objective optimization problem is transformed into the following form: Wherein, α controls the weight of the 'net zero displacement change' objective function; given the matrix G, the amplitude vector α is calculated by a heuristic algorithm; the heuristic algorithm is selected from: genetic algorithm, simulated annealing algorithm, particle swarm optimization.

7. The method for simulating shelling vibration environment based on shock response spectrum according to claim 6, characterized in that: In step S4, The single shot shock signal is copied, translated, and combined, and the expression is: Among them, n is the number of cannon vibrations, and λ is the time interval between adjacent cannon vibrations.

8. The method for simulating shelling vibration environment based on shock response spectrum according to claim 1, characterized in that: In step S5, Generate a white noise signal that follows a normal distribution: F' I to F' K A 1 / 12 octave filter bank is applied to the white noise r(t), producing a series of bandpass filtered signals: r i (t)=(r*h i )(t) f i+1 =f i ×2 1 / 12 F I <f i <F′ K Among them, h i (t) is the impulse response of the ith bandpass filter, with center frequency f i . Model the low-frequency noise w(t) as a linear combination of bandpass signals: w(t)=∑b i ·r i (t) where b i is the amplitude parameter of each bandpass filtered noise, representing the low-frequency stationary noise of the multiple-impact signal.

9. The method for simulating shelling vibration environment based on shock response spectrum according to claim 8, characterized in that: The amplitude parameter b of the bandpass filtered signal is adjusted through an optimization problem i , thereby controlling the noise signal: Among them, the noise signal is added to the series impulse signal v(t) to compensate its SRS; The final generated multiple impact signal s(t) is the low-frequency noise w(t) added to the spliced ​​impact signal v(t) to obtain the target SRS that meets the target requirements: s(t)=v(t)+w(t).

10. The method for simulating shelling vibration environment based on shock response spectrum according to claim 9, characterized in that: Adjust the amplitude parameter b of the bandpass filter signal i The optimization problem is solved by using a heuristic algorithm.

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