Super Gaussian accelerated vibration fatigue test method, medium and system

Abstract

The invention discloses a super Gaussian accelerated vibration fatigue test method, medium and system, and the method comprises the steps: S1, obtaining the relation between Gaussian and super Gaussian random vibration fatigue damage of each stable state under the same power spectrum density; s2, obtaining actually measured vibration data, calculating the damage cumulant of the vehicle-mounted equipment according to the actually measured vibration data, and constructing a super Gaussian accelerated vibration model based on the relationship between Gaussian and super Gaussian random vibration fatigue damage; and S3, carrying out a super Gaussian accelerated vibration test based on the super Gaussian accelerated vibration model. The device has the advantages of high test precision, high test efficiency and the like.

Description

Technical Field

[0001] The present invention mainly relates to the field of rail transit technology, and in particular to a super-Gaussian accelerated vibration fatigue test method, medium and system. Background Art

[0002] High-speed railway is an inevitable trend in the development of world railway transportation and a major symbol of railway technology modernization. High-speed railway has been widely valued and developed vigorously in countries around the world. As the core equipment of high-speed railway, high-speed EMUs are subject to increasingly harsh vibration environments under multiple stress excitations such as aerodynamic loads, pressure and micro-pressure waves, and wheel-rail forces, which leads to a sudden increase in equipment failure rate, which has a serious impact on the safe operation of high-speed EMUs.

[0003] In order to ensure the quality and reliability of on-board equipment during actual operation, rail transit equipment manufacturers in various countries generally complete Gaussian vibration tests according to IEC 61373. However, equipment that has passed the vibration test still has batch vibration failure problems when running on certain special lines. For this reason, after testing the vibration environment of certain special lines, it is known that its on-site vibration data shows obvious super-Gaussian characteristics, which is significantly different from the standard Gaussian vibration. Due to Gaussian vibration, the instantaneous peak value of acceleration greater than 3 times the root mean square value (RMS) only accounts for 0.27% of the total vibration time, but according to the analysis of the field measured data, the time when the instantaneous peak value of acceleration exceeds 3 times the RMS is as high as 1.5% of the total vibration time. That is to say, compared with the field measured super-Gaussian vibration, the standard Gaussian vibration has a time of 10s and 54s of instantaneous peak value of acceleration exceeding 3 times the RMS in a vibration test lasting 1 hour. Since most vibration fatigue damage is caused by peak acceleration of 2 to 4 times RMS, the use of Gaussian vibration testing will significantly reduce the duration of these instantaneous peak accelerations, thereby greatly reducing the damage that onboard equipment should bear in actual use. Therefore, performing ultra-Gaussian vibration tests that meet the actual conditions on site is crucial to ensuring the safety and reliability of high-speed EMU equipment running on special lines.

[0004] Since the design life of high-speed EMUs is generally 25 years, accelerated vibration tests must be carried out to shorten the test time, and the accelerated vibration model is the core of the accelerated test. At present, the methods for establishing accelerated vibration models mainly include time domain method and frequency domain method. Since most methods for calculating vibration fatigue assume that the vibration data obeys Gaussian distribution, the frequency domain method has high computational efficiency to estimate the fatigue life of the structure through frequency domain statistics. Therefore, the frequency domain method has been widely used in Gaussian vibration fatigue life estimation. However, for super-Gaussian vibration, due to the large errors in the calculation of its frequency domain statistics, these errors will be brought into the calculation of structural fatigue damage, thereby affecting the calculation accuracy of fatigue life. In addition, there is also a method to construct a super-Gaussian accelerated vibration model by multiplying a non-Gaussian factor in the Gaussian accelerated vibration model. This method uses the PSD value at the first-order natural frequency that has the greatest impact on the fatigue life of the specimen to estimate its life, and ignores the influence of other frequencies on fatigue damage, which will affect the estimation accuracy of the model.

[0005] In general, the current research at home and abroad is mainly on Gaussian acceleration vibration tests, and there are few theoretical studies on super-Gaussian acceleration vibration tests, especially super-Gaussian vibration tests on rail transit equipment. Therefore, it is necessary to further explore the super-Gaussian acceleration vibration test model suitable for high-speed EMU equipment. Summary of the invention

[0006] In view of the technical problems existing in the prior art, the present invention provides a super-Gaussian accelerated vibration fatigue test method, medium and system with high test accuracy.

[0007] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0008] A super-Gaussian accelerated vibration fatigue test method, comprising the steps of:

[0009] S1. Obtain the relationship between Gaussian and super-Gaussian random vibration fatigue damage under the same power spectrum density;

[0010] S2. Obtain measured vibration data, calculate the damage accumulation of the vehicle-mounted equipment according to the measured vibration data, and then construct a super-Gaussian accelerated vibration model based on the relationship between Gaussian and super-Gaussian random vibration fatigue damage;

[0011] S3. Perform super-Gaussian acceleration vibration test based on super-Gaussian acceleration vibration model.

[0012] Preferably, in step S2, the measured vibration data is acceleration time domain data.

[0013] Preferably, in step S2, the specific process of calculating the damage accumulation amount of the vehicle-mounted equipment is:

[0014] To calculate the fatigue life of the structure, the relationship between stress and life is established through the SN curve;

[0015] A complete SN curve can be divided into three intervals: low cycle fatigue zone, high cycle fatigue zone and sub-fatigue zone; the high cycle fatigue zone is the main area of ​​vibration fatigue failure, and the power function form of the SN curve equation describing the high cycle fatigue zone is:

[0016] NS b =c (2)

[0017] In formula (2):

[0018] S—stress amplitude, assuming that the acceleration acting on the equipment is proportional to the stress amplitude generated;

[0019] N—stress amplitude S i The number of cycles leading to failure under the action of

[0020] b—Constant related to material;

[0021] c—constant;

[0022] From formula (2), we can get that at the stress amplitude S i Under this condition, the number of cycles leading to material failure is:

[0023] N i =cS i -b (3)

[0024] According to Miner's linear fatigue cumulative damage theory, under different stress amplitudes, the fatigue damage of the material is linearly accumulated. Each stress is independent of each other, and the total damage is obtained by the linear superposition principle. The total damage of the material under each fatigue stress is expressed as:

[0025]

[0026] In formula (4):

[0027] n i —Stress amplitude S i The number of cycles;

[0028] N i —At stress amplitude S i The number of cycles leading to failure under action;

[0029] D—total damage value under each stress amplitude;

[0030] At stress level S i The damage value is expressed as:

[0031]

[0032] Substituting equation (3) and equation (5) into equation (4), the total damage value is obtained as follows:

[0033]

[0034] Formula (6) has nothing to do with the frequency domain and directly uses time domain vibration data to calculate the damage of the structure.

[0035] Preferably, the duration of the vibration data sample used for fatigue damage calculation is T t , from formula (6), we can see that at T t The structural damage in time is expressed as:

[0036]

[0037] Assume that the total duration of vibration data within the design life of the vehicle equipment is T s Since random vibration is a steady state process, at time T s Internal stress amplitude S i The number of cycles is expressed as

[0038] The design life of the vehicle equipment is T s The damage to the internal equipment is:

[0039]

[0040] Therefore, formula (8) satisfies the calculation of structural damage under random vibration excitation in stable states.

[0041] Preferably, assuming that the vehicle-mounted equipment is in Gaussian and super-Gaussian vibration environments with the same PSD, when the vibration data sample length is T t When the vehicle equipment design life T s The fatigue damage under Gaussian and super-Gaussian vibrations and for:

[0042]

[0043] Combining equations (9) and (10), the damage ratio ε of the structure is defined as:

[0044]

[0045] It can be seen from formula (11) that for the random vibration signal of steady states, the damage ratio of Gaussian and super Gaussian vibrations corresponding to the same PSD to the structure in the same time period is a constant. The equivalent relationship between the fatigue life of the structure under Gaussian and super Gaussian vibrations is established by formula (11).

[0046] Preferably, in step S2, the specific process of constructing the super-Gaussian acceleration vibration model is:

[0047] The same PSD is used to perform Gaussian and super-Gaussian vibration tests. The test time of the corresponding Gaussian vibration is T ku＝3 , the test time of super Gaussian vibration under the same total cumulative damage condition is T ku＝k , then from equation (9) and equation (10) we get:

[0048]

[0049] Let D T_ku＝k =D T_ku＝3 The solution is:

[0050]

[0051] Formula (15) is the super-Gaussian accelerated vibration model, which establishes the equivalent relationship between the fatigue life of the structure after Gaussian and super-Gaussian vibrations in the steady states corresponding to the same PSD.

[0052] Preferably, the kurtosis k u As a parameter that characterizes the sharpness of the probability density function curve of a random process, the kurtosis k u Less than 3 is sub-Gaussian, kurtosis k u Those greater than 3 are super-Gaussian.

[0053] The present invention also discloses a computer program product, comprising a computer program, wherein the computer program executes the steps of the method described above when executed by a processor.

[0054] The present invention further discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described above are executed.

[0055] The present invention also discloses an ultra-Gaussian accelerated vibration fatigue test system, comprising a memory and a processor connected to each other, wherein a computer program is stored in the memory, and when the computer program is run by the processor, the steps of the method described above are executed.

[0056] Compared with the prior art, the advantages of the present invention are:

[0057] By constructing a super-Gaussian accelerated vibration model, the present invention can simulate the long-term accumulated vibration fatigue damage in the actual operating environment in a shorter test time, thereby greatly shortening the test cycle and improving the test efficiency. The present invention combines the measured vibration data with the relationship between Gaussian and super-Gaussian random vibration fatigue damage, making the accelerated vibration test closer to the actual working environment and improving the accuracy of the test results. By performing super-Gaussian accelerated vibration tests on vehicle-mounted equipment, the present invention can discover potential fatigue problems in advance, provide guidance for the operation and maintenance of the equipment, and thus improve the reliability of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a probability density function diagram of the measured vibration data of the present invention.

[0059] Figure 2 The present invention is a flowchart of the super-Gaussian accelerated vibration fatigue test method in an embodiment. DETAILED DESCRIPTION

[0060] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0061] like Figure 2 As shown, the super-Gaussian accelerated vibration fatigue test method of the embodiment of the present invention is applied to the test of vehicle-mounted equipment, wherein the vibration environment of the vehicle-mounted equipment has the characteristics of stable ergodicity, and the above test method comprises the steps of:

[0062] S1. Through Miner's linear fatigue cumulative damage theory, the relationship between Gaussian and super-Gaussian random vibration fatigue damage under the same power spectrum density PSD is obtained;

[0063] S2. Obtain measured vibration data, calculate the damage accumulation of vehicle-mounted equipment using the rain flow cycle counting method, and then construct a super Gaussian accelerated vibration model based on the relationship between Gaussian and super Gaussian random vibration fatigue damage;

[0064] S3. Perform super-Gaussian acceleration vibration test based on super-Gaussian acceleration vibration model.

[0065] Two super-Gaussian vibration tests with kurtosis of 5 and 7 were carried out on 6005A-T5 aluminum specimens. The results showed that the relative errors between the expected life and the test life of the accelerated vibration model were 1.6% and 2.9%, respectively, which verified the accuracy of the super-Gaussian accelerated vibration test model.

[0066] The above-mentioned super-Gaussian accelerated vibration model can more accurately establish the fatigue damage equivalence relationship between the laboratory accelerated super-Gaussian vibration test and the on-site operation vibration of the high-speed EMU, thus laying a theoretical foundation for the subsequent super-Gaussian vibration fatigue simulation and super-Gaussian accelerated vibration test.

[0067] Specifically, the construction process of the above super-Gaussian acceleration vibration model is as follows:

[0068] 1. Super Gaussian random process

[0069] In engineering, the normalized third-order moment and fourth-order moment are generally used, that is, the skewness S and the kurtosis k u To describe the hypergaussian characteristics of the random process x(t), as shown in formula (1):

[0070]

[0071] In formula (1), the skewness S represents the degree to which PDF (Probability density Function) deviates from the symmetrical distribution. A skewness of 0 means that PDF follows a symmetrical distribution, and vice versa, it is an asymmetrical distribution. In engineering, the skewness is generally agreed to be 0; while the kurtosis k u As a parameter that characterizes the sharpness of the probability density function (PDF) curve of a random process, non-Gaussian random vibrations are further divided into sub-Gaussian and super-Gaussian random vibrations, where the kurtosis k u Less than 3 is sub-Gaussian, kurtosis k u Those greater than 3 are super-Gaussian; X(t) is a random variable; E[X(t)] is the expected value of X(t)]; σ x is the standard deviation of the random variable X(t); is the third-order moment of the random variable X(t); is the fourth-order moment of the random variable X(t).

[0072] 2. Vibration data stability analysis

[0073] The vibration data is the acceleration time domain data obtained through testing.

[0074] (1) Stability test

[0075] The methods for stability inspection generally include physical inspection, visual qualitative inspection, root mean square value inspection, real-time analysis inspection, round inspection and variance inspection. The round inspection method is commonly used to determine whether the vibration data is stable data through stability inspection.

[0076] (2) Each state has undergone testing

[0077] According to mathematical statistics theory, when the process satisfies both the ergodicity of the mean and the ergodicity of the autocorrelation function, the process is an ergodic process, that is, the process has ergodicity. In actual data testing, when the time mean of the process is approximately equal to the ensemble mean, the process can be considered ergodic. Through the ergodic test, it is determined that the vibration data is an ergodic process.

[0078] (3) Normality test

[0079] Normality test methods include PDF analysis, Chi-square goodness-of-fit test, etc. The kurtosis test method is often used. Randomly extract a section of vibration data from the measured data sample, and use formula (1) to calculate its kurtosis k u =6.327 (PDF see Figure 1 ), it can be seen that the measured vibration data clearly presents a super-Gaussian distribution.

[0080] 3. Construction of super-Gaussian accelerated vibration model

[0081] (1) Damage ratio calculation

[0082] In order to calculate the fatigue life of the structure, it is necessary to establish the relationship between stress and life through the SN curve. A complete SN curve can be divided into three intervals: low-cycle fatigue zone, high-cycle fatigue zone and sub-fatigue zone. Among them, the high-cycle fatigue zone is the main area of ​​vibration fatigue failure. The power function form of the SN curve equation describing the high-cycle fatigue zone is:

[0083] NS b =c (2)

[0084] In formula (2):

[0085] S—stress amplitude, assuming that the acceleration acting on the equipment is proportional to the stress amplitude generated;

[0086] N—stress amplitude S i The number of cycles leading to failure under the action of

[0087] b—Constant related to material;

[0088] c—constant.

[0089] From formula (2), we can get that at the stress amplitude S i Under this condition, the number of cycles leading to material failure is:

[0090] N i =cS i -b (3)

[0091] According to Miner's linear fatigue cumulative damage theory, under different stress amplitudes, the fatigue damage of the material can be linearly accumulated. Each stress is independent of each other, and the total damage can be obtained through the linear superposition principle. The total damage of the material under each fatigue stress can be expressed as:

[0092]

[0093] In formula (4):

[0094] ni —Stress amplitude S i The number of cycles;

[0095] N i —At stress amplitude S i The number of cycles leading to failure under action;

[0096] D—Total damage value under each stress amplitude.

[0097] At stress level S i The damage value can be expressed as:

[0098]

[0099] Substituting equation (3) and equation (5) into equation (4), the total damage value is obtained as follows:

[0100]

[0101] Formula (6) is independent of the frequency domain and can directly use time domain vibration data to calculate the damage of the structure. Therefore, it is suitable for fatigue damage calculation of stationary and non-stationary, Gaussian and super-Gaussian random vibrations.

[0102] Since the service life of a structure is generally long, it is very difficult to obtain all the vibration environment data of the structure during its service life in practice. Often, only vibration data within a certain period of time can be collected. Therefore, formula (6) can only obtain the damage value within a part of the structure's service life.

[0103] Since the ultra-Gaussian vibration environment data has the characteristics of stability and ergodicity, the duration of the vibration data sample used for fatigue damage calculation is assumed to be T t , from formula (6), we can see that at T t The damage of the structure in time can be expressed as:

[0104]

[0105] Assume that the total duration of vibration data within the design life of the vehicle equipment is T s Since random vibration is a steady state process, at time T s Internal stress amplitude S i The number of cycles can be expressed as Therefore, in the design life T of the vehicle equipment s The damage to the internal equipment is:

[0106]

[0107] Therefore, formula (8) can satisfy the calculation of structural damage under random vibration excitation in stable states.

[0108] Since the Gaussian and super-Gaussian random vibrations of vehicle-mounted equipment both satisfy the stationary ergodicity and the fatigue damage is linearly accumulated, the total damage within the design life of the vehicle-mounted equipment can be obtained by formula (8).

[0109] Assume that the on-board devices are in Gaussian with the same PSD (kurtosis k u =3) and super-Gaussian (kurtosis k u >3) In a vibration environment, when the vibration data sample length is T t When the vehicle equipment design life T s The fatigue damage under Gaussian and super-Gaussian vibrations and for:

[0110]

[0111] Combining equations (9) and (10), the damage ratio ε of the structure is defined as:

[0112]

[0113] It can be seen from formula (11) that for the random vibration signal of steady states, the damage ratio of Gaussian and super Gaussian vibrations corresponding to the same PSD to the structure in the same time period is a constant. The equivalent relationship between the fatigue life of the structure under Gaussian and super Gaussian vibrations is established by formula (11).

[0114] (2) Accelerate model building

[0115] Formula (11) gives the relationship between the damage ratios of super-Gaussian vibration and Gaussian vibration. Formula (11) can be used to reconstruct the super-Gaussian vibration environment of the laboratory.

[0116] If the same PSD is used for Gaussian and super-Gaussian vibration tests, the corresponding Gaussian vibration test time is T ku＝3 , the test time of super Gaussian vibration under the same total cumulative damage condition is T ku＝k , then from formula (9) and formula (10) we can get:

[0117]

[0118] Let D T_ku＝k =D T_ku＝3 It can be solved as follows:

[0119]

[0120] Formula (15) is the super-Gaussian vibration fatigue accelerated test model, which establishes the equivalent relationship between the fatigue life of the structure after Gaussian and super-Gaussian vibrations in the steady states corresponding to the same PSD.

[0121] By constructing a super-Gaussian accelerated vibration model, the present invention can simulate the long-term accumulated vibration fatigue damage in the actual operating environment in a shorter test time, thereby greatly shortening the test cycle and improving the test efficiency. The present invention combines the measured vibration data with the relationship between Gaussian and super-Gaussian random vibration fatigue damage, making the accelerated vibration test closer to the actual working environment and improving the accuracy of the test results. By performing super-Gaussian accelerated vibration tests on vehicle-mounted equipment, the present invention can discover potential fatigue problems in advance, provide guidance for the operation and maintenance of the equipment, and thus improve the reliability of the equipment.

[0122] The present invention also discloses a computer program product, including a computer program, which executes the steps of the above method when executed by a processor. The present invention further discloses a computer-readable storage medium, on which a computer program is stored, which executes the steps of the above method when executed by a processor. The present invention also discloses an ultra-Gaussian accelerated vibration fatigue test system, including an interconnected memory and a processor, on which a computer program is stored, which executes the steps of the above method when executed by a processor. The product, medium and system of the present invention correspond to the above method and also have the advantages described in the above method.

[0123] The present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiment when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable storage media include: any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. The memory is used to store computer programs and / or modules, and the processor implements various functions by running or executing computer programs and / or modules stored in the memory, and calling data stored in the memory. The memory may include high-speed random access memory and may also include non-volatile memory, such as a hard disk, an internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0124] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A super-Gaussian accelerated vibration fatigue test method, characterized in that: Includes steps: S1. Obtain the relationship between Gaussian and super-Gaussian random vibration fatigue damage under the same power spectrum density; S2. Obtain measured vibration data, calculate the damage accumulation of the vehicle-mounted equipment according to the measured vibration data, and then construct a super-Gaussian accelerated vibration model based on the relationship between Gaussian and super-Gaussian random vibration fatigue damage; S3. Perform super-Gaussian acceleration vibration test based on super-Gaussian acceleration vibration model.

2. The super-Gaussian accelerated vibration fatigue test method according to claim 1, characterized in that: In step S2, the measured vibration data is acceleration time domain data.

3. The super-Gaussian accelerated vibration fatigue test method according to claim 2, characterized in that: In step S2, the specific process of calculating the damage accumulation amount of the vehicle-mounted equipment is as follows: To calculate the fatigue life of the structure, the relationship between stress and life is established through the SN curve; A complete SN curve can be divided into three intervals: low cycle fatigue zone, high cycle fatigue zone and sub-fatigue zone; the high cycle fatigue zone is the main area of ​​vibration fatigue failure, and the power function form of the SN curve equation describing the high cycle fatigue zone is: NSb=c (2) In formula (2): S—stress amplitude, assuming that the acceleration acting on the equipment is proportional to the stress amplitude generated; N—stress amplitude S i The number of cycles leading to failure under the action of b—Constant related to material; c—constant; From formula (2), we can get that at the stress amplitude S i Under this condition, the number of cycles leading to material failure is: According to Miner's linear fatigue cumulative damage theory, under different stress amplitudes, the fatigue damage of the material is linearly accumulated. Each stress is independent of each other, and the total damage is obtained by the linear superposition principle. The total damage of the material under each fatigue stress is expressed as: In formula (4): n i —Stress amplitude S i The number of cycles; N i —At stress amplitude S i The number of cycles leading to failure under the action; D—total damage value under each stress amplitude; At stress level S i The damage value is expressed as: Substituting equation (3) and equation (5) into equation (4), the total damage value is obtained as follows: Formula (6) has nothing to do with the frequency domain and directly uses time domain vibration data to calculate the damage of the structure.

4. The super-Gaussian accelerated vibration fatigue test method according to claim 3 is characterized in that The duration of the vibration data sample used for fatigue damage calculation is T t , from formula (6), we can see that at T t The structural damage in time is expressed as: Assume that the total duration of vibration data within the design life of the vehicle equipment is T s Since random vibration is a steady state process, at time T s Internal stress amplitude S i The number of cycles is expressed as The design life of the vehicle equipment is T s The damage to the internal equipment is: Therefore, formula (8) satisfies the calculation of structural damage under random vibration excitation in stable states.

5. The super-Gaussian accelerated vibration fatigue test method according to claim 4, characterized in that: Assume that the vehicle-mounted equipment is in Gaussian and super-Gaussian vibration environments with the same PSD. When the vibration data sample length is T t When the vehicle equipment design life T s The fatigue damage under Gaussian and super-Gaussian vibrations and for: Combining equations (9) and (10), the damage ratio ε of the structure is defined as: It can be seen from formula (11) that for the random vibration signal of steady states, the damage ratio of Gaussian and super Gaussian vibrations corresponding to the same PSD to the structure in the same time period is a constant. The equivalent relationship between the fatigue life of the structure under Gaussian and super Gaussian vibrations is established by formula (11).

6. The super-Gaussian accelerated vibration fatigue test method according to claim 5, characterized in that: In step S2, the specific process of constructing the super-Gaussian acceleration vibration model is as follows: The same PSD is used to perform Gaussian and super-Gaussian vibration tests. The test time of the corresponding Gaussian vibration is T ku＝3 , the test time of super Gaussian vibration under the same total cumulative damage condition is T ku＝k , then from equation (9) and equation (10) we get: Let D T_ku＝k =D T_ku＝3 The solution is: Formula (15) is the super-Gaussian accelerated vibration model, which establishes the equivalent relationship between the fatigue life of the structure after Gaussian and super-Gaussian vibrations in the steady states corresponding to the same PSD.

7. The super-Gaussian accelerated vibration fatigue test method according to any one of claims 1 to 6, characterized in that: The kurtosis k u As a parameter that characterizes the sharpness of the probability density function curve of a random process, the kurtosis k u Less than 3 is sub-Gaussian, kurtosis k u Those greater than 3 are super-Gaussian.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are performed.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

10. An ultra-Gaussian accelerated vibration fatigue test system, comprising a memory and a processor connected to each other, wherein a computer program is stored in the memory, characterized in that: When the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

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