Non-stationary non-gaussian random signal generation method based on amplitude and phase joint modulation

Abstract

The application relates to a non-stationary non-Gaussian random signal generation method based on amplitude and phase joint modulation. A Gaussian signal is obtained by performing inverse Fourier transform on the power spectrum of a non-stationary non-Gaussian vibration signal, a modulation signal is generated based on a frequency range, a non-stationary non-Gaussian signal is obtained according to the Gaussian signal and the modulation signal, corresponding frequency domain amplitude spectrum and frequency domain phase spectrum are obtained according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, the non-stationary non-Gaussian signal is reconstructed according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transform, and whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis is judged. If not, the phase of the frequency domain phase spectrum is modulated until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is the final output signal. The method can accurately generate a non-stationary non-Gaussian signal with a specified power spectral density.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vibration signal generation, in particular to a non-stationary non-Gaussian random signal generation method based on joint amplitude and phase modulation. BACKGROUND

[0002] In actual engineering structures (such as bridges, buildings, aircraft, etc.), the vibration excitation received is often non-stationary and non-Gaussian. For example, ground motion, strong wind, sea wave impact, etc. The intensity and frequency components of these excitations change over time, and their amplitude distribution usually deviates from the Gaussian distribution. In order to more realistically simulate these actual working conditions and more accurately monitor the health, detect the damage and predict the life of the structure, it is necessary to generate corresponding non-stationary non-Gaussian random vibration signals for analysis and testing.

[0003] The existing non-stationary non-Gaussian random vibration signal generation is shown in FIG. 1. As can be seen from the figure, the existing method changes the frequency domain amplitude of the original signal, so that the non-stationary non-Gaussian signal with the specified power spectral density cannot be accurately generated. Figure 1 However, in structural dynamics, the power spectral density is used to describe the distribution of the energy of the random vibration excitation at different frequencies. If the power spectral density of the generated signal is not accurate, the response analysis (such as displacement, stress, etc.) based on the signal to the structure will be biased. This may lead to inaccurate safety and reliability evaluation of the structure, and may result in overdesign or underdesign when designing the structure. SUMMARY

[0004] Therefore, it is necessary to provide a non-stationary non-Gaussian random signal generation method based on joint amplitude and phase modulation, which can accurately generate a non-stationary non-Gaussian signal with a specified power spectral density, in order to solve the above technical problems.

[0005] A non-stationary non-Gaussian random signal generation method based on joint amplitude and phase modulation, the method comprising:

[0006] obtaining the power spectrum and the frequency range of a non-stationary non-Gaussian vibration signal;

[0007] performing inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal;

[0008] obtaining the frequency domain amplitude spectrum corresponding to the Gaussian signal and the frequency domain phase spectrum of the non-stationary non-Gaussian signal according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and reconstructing the non-stationary non-Gaussian signal according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0009] determining whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, modulating the phase of the frequency domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0010] In one embodiment, the frequency range is in the range of 0 to 100 Hz.

[0011] In one embodiment, the generating a modulation signal based on the frequency range comprises:

[0012] generating a low-frequency standard normal distribution signal equal to the length of the Gaussian signal according to the frequency range;

[0013] generating the modulation signal according to the absolute value of the low-frequency standard normal distribution signal.

[0014] In one embodiment, the Gaussian signal is represented as:

[0015]

[0016] In the above formula, c0 is a constant, representing the mean of the signal, A n represents the amplitude of the frequency domain, φ n represents the phase, and Δf represents the frequency resolution, and N represents the number of sampling points of the signal.

[0017] In one embodiment, the reconstructed non-stationary non-Gaussian signal is represented as:

[0018]

[0019] In the above formula, A n_g represents the amplitude of the Gaussian signal, φ n_x represents the phase of the non-stationary non-Gaussian signal.

[0020] In one embodiment, the kurtosis of the reconstructed non-stationary non-Gaussian signal is calculated using the following formula:

[0021]

[0022] In the above formula, A represents the amplitude of the Gaussian signal in the frequency domain, which reflects the strength of different frequency component signals, φ represents the phase of the non-stationary non-Gaussian signal, which describes the relative position information of the signal at different times, and subscripts j, k, n, m are used to distinguish the amplitudes and corresponding phases that meet different conditions.

[0023] The application also provides a non-stationary non-Gaussian random signal generating device based on amplitude and phase joint modulation, the device comprising:

[0024] a data acquisition module configured to acquire a power spectrum and a frequency range of a non-stationary non-Gaussian vibration signal;

[0025] a non-stationary non-Gaussian signal generation module configured to perform inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generate a modulation signal based on the frequency range, and obtain a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal;

[0026] a reconstructed non-stationary non-Gaussian signal generation module configured to obtain a frequency-domain amplitude spectrum corresponding to the Gaussian signal and a frequency-domain phase spectrum of the non-stationary non-Gaussian signal according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0027] a reconstructed non-stationary non-Gaussian signal adjustment module configured to determine whether a kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, modulate a phase of the frequency-domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is an ultimate output signal.

[0028] A computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0029] A non-stationary non-Gaussian random signal generation method based on joint amplitude and phase modulation, the method comprising:

[0030] acquiring a power spectrum and a frequency range of a non-stationary non-Gaussian vibration signal;

[0031] performing inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal;

[0032] obtaining a frequency-domain amplitude spectrum corresponding to the Gaussian signal and a frequency-domain phase spectrum of the non-stationary non-Gaussian signal according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and reconstructing the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0033] determining whether a kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, modulating a phase of the frequency-domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is an ultimate output signal.

[0034] A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the following steps:

[0035] A non-stationary non-Gaussian random signal generation method based on amplitude and phase joint modulation, the method comprising:

[0036] Obtaining the power spectrum and frequency range of a non-stationary non-Gaussian vibration signal;

[0037] Inverse Fourier transforming the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal;

[0038] According to the Gaussian signal and the non-stationary non-Gaussian signal respectively, a frequency domain amplitude spectrum corresponding to the Gaussian signal and a frequency domain phase spectrum of the non-stationary non-Gaussian signal are obtained, and the non-stationary non-Gaussian signal is reconstructed according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transformation to obtain a reconstructed non-stationary non-Gaussian signal;

[0039] It is judged whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, the phase of the frequency domain phase spectrum is modulated until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0040] The above-mentioned non-stationary non-Gaussian random signal generation method based on amplitude and phase joint modulation, by inverse Fourier transforming the power spectrum of a non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal, according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, a frequency domain amplitude spectrum corresponding to the Gaussian signal and a frequency domain phase spectrum of the non-stationary non-Gaussian signal are obtained, and the non-stationary non-Gaussian signal is reconstructed according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transformation to obtain a reconstructed non-stationary non-Gaussian signal, it is judged whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, the phase of the frequency domain phase spectrum is modulated until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is the final output signal. Using this method, a non-stationary non-Gaussian signal with a specified power spectral density can be accurately generated. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 It is a schematic diagram of the prior art non-stationary non-Gaussian random signal generation method in one embodiment;

[0042] Figure 2 It is a flowchart of the non-stationary non-Gaussian random signal generation method based on amplitude and phase joint modulation in one embodiment;

[0043] Figure 3 Fig. 1 is a flowchart of generating a non-stationary non-Gaussian random signal by using the method in one embodiment;

[0044] Figure 4 Fig. 2 is a structural block diagram of a device for generating a non-stationary non-Gaussian random signal based on joint modulation of amplitude and phase in one embodiment;

[0045] Figure 5 Fig. 3 is an internal structure diagram of a computer device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0047] In order to truly simulate the actual working conditions of an actual engineering structure when it is subjected to vibration excitation, to achieve more accurate health monitoring, damage detection and life prediction of the structure, a corresponding non-stationary non-Gaussian random vibration signal needs to be generated for analysis and testing. However, using existing technologies, such as Figure 1 As shown in the figure, the generated signal power spectral density is not accurate. As can be seen from the figure, the method changes the frequency domain amplitude of the original signal, indicating that the method cannot accurately generate a non-stationary non-Gaussian signal with a specified power spectral density.

[0048] However, in structural dynamics, the power spectral density is used to describe the distribution of the energy of random vibration excitation at different frequencies. If the generated signal power spectral density is not accurate, the response analysis (such as displacement, stress, etc.) of the structure based on the signal will be biased. This may lead to inaccurate safety and reliability evaluation of the structure, and may result in overdesign or underdesign when designing the structure. For example, for bridge design, if the vibration energy at certain frequencies is underestimated, the bridge may be damaged due to excessive stress in actual operation; on the contrary, overdesign will cause waste of materials and cost. For mechanical equipment, its vibration characteristics at different frequencies are closely related to its performance and life. Inaccurate power spectral density signals will cause errors in the evaluation of the vibration characteristics of the equipment, and thus affect the judgment of the failure mode, fatigue life, etc. of the equipment. Early signs of equipment failure may be missed, leading to sudden equipment failure, affecting the production process, and even causing safety accidents. Therefore, it is of great practical significance to generate a non-stationary non-Gaussian signal with a specified power spectral density.

[0049] In view of the above problems, in the present application, as Figure 2As shown, a non-stationary non-Gaussian random signal generation method based on amplitude and phase joint modulation is provided, which specifically comprises the following steps:

[0050] In step S100, the power spectrum and the frequency range of the non-stationary non-Gaussian vibration signal are obtained.

[0051] In step S110, the power spectrum of the non-stationary non-Gaussian vibration signal is inversely Fourier transformed to obtain a Gaussian signal, a modulation signal is generated based on the frequency range, and a non-stationary non-Gaussian signal is obtained according to the Gaussian signal and the modulation signal.

[0052] In step S120, the frequency domain amplitude spectrum corresponding to the Gaussian signal and the frequency domain phase spectrum of the non-stationary non-Gaussian signal are obtained according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and the non-stationary non-Gaussian signal is reconstructed according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transformation to obtain a reconstructed non-stationary non-Gaussian signal.

[0053] In step S130, it is judged whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, if not, the phase of the frequency domain phase spectrum is modulated until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, then the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0054] In step S100, the power spectrum of a defined non-stationary non-Gaussian vibration signal is first obtained, which can be selected according to the specific application background.

[0055] In one embodiment, the frequency range can be [0.1-0.5Hz] or [0.5-1Hz].

[0056] In step S110, after the power spectrum is given, the Gaussian signal g(t) is generated by inverse Fourier transform, which is expressed as:

[0057]

[0058] In formula (1), c0 is a constant, representing the mean value of the signal, A n represents the amplitude in the frequency domain, and φ n represents the phase, and Δf represents the frequency resolution, and N represents the number of sampling points of the signal.

[0059] In this embodiment, generating a modulation signal based on the frequency range includes: generating a low-frequency standard normal distribution signal Z(t) with a length equal to that of the Gaussian signal according to the frequency range, and then generating a modulation signal m(t) according to the absolute value of the low-frequency standard normal distribution signal. The frequency range is in the low frequency range of 0.1 to 100 Hz, which is to simulate the complex service vibration environment of aerospace structures, ship structures and automobile parts.

[0060] In one embodiment, the frequency range can be [0.1-0.5Hz] or [0.5-1Hz].

[0061] In step S120, the Gaussian random vibration signal g(t) is multiplied with the amplitude modulation signal m(t) in time domain to obtain the non-stationary non-Gaussian signal x(t). Meanwhile, the frequency domain amplitude spectrum of the Gaussian signal g(t) is obtained by Fourier transform, and the amplitude spectrum and phase spectrum of the non-stationary non-Gaussian signal x(t) in frequency domain are obtained.

[0062] In step S130, the amplitude spectrum of the Gaussian signal g(t) and the phase spectrum of the non-stationary non-Gaussian signal x(t) are used to obtain the reconstructed non-stationary non-Gaussian signal by inverse Fourier transform, and the reconstructed non-stationary non-Gaussian signal is expressed as:

[0063]

[0064] In formula (2), A n_g represents the amplitude of the Gaussian signal, and φ n_x represents the phase of the non-stationary non-Gaussian signal.

[0065] In step S140, the kurtosis of the reconstructed non-stationary non-Gaussian signal is calculated, and then it is judged whether the reconstructed non-stationary non-Gaussian signal reaches the target kurtosis. If the target kurtosis is not reached, the phase spectrum of the reconstructed non-stationary non-Gaussian signal is phase-modulated, and the phase group satisfying a certain condition is modulated until the target kurtosis is reached, so as to ensure that the amplitude spectrum of the reconstructed signal does not change.

[0066] In this embodiment, the kurtosis of the reconstructed non-stationary non-Gaussian signal is calculated by the following formula:

[0067]

[0068] In formula (3), A represents the amplitude of the Gaussian signal in frequency domain, which reflects the intensity of different frequency component signals. φ represents the phase of the non-stationary non-Gaussian signal, which is used to describe the relative position information of the signal at different times. The subscripts j, k, n, m, etc. have clear functions and meanings. In the summation operation of the formula, they are used to distinguish the amplitudes and their corresponding phases that satisfy different conditions. For example, in , n is used as a summation index, A n represents different Gaussian signal frequency domain amplitudes, and different n corresponds to the amplitudes of different frequency components.

[0069] In this embodiment, when the phase spectrum is phase-modulated, if the phase φ nIf the phase is randomly selected, then the value of the cosine function in formula (3) will be uniformly distributed between -1 and 1. Each term in the formula contains a large number of summations of the product terms of the amplitude and the cosine function that satisfy the subscript equality. Because the value of the cosine function is uniformly distributed between -1 and 1, the sums of these product terms compensate for each other, resulting in the result of each summation term being close to 0. This shows that if the phase is randomly selected, the kurtosis of the random signal x(t) will not deviate from the first term, that is, the kurtosis is 3.

[0070] If we change certain phases so that the sum of the phases in the cosine function of the summation term is 0, then the value of the cosine function will no longer be uniformly distributed between -1 and 1, but will instead have a maximum value of 1. For example, in the third term... In the middle, let the phase group φ j φ k (Satisfies the subscript condition j = 3k) satisfies φ j =3φ k Then, the product of the magnitude of the corresponding subscript group in the third term and the cosine function will equal... Instead of being evenly distributed arrive This will lead to a trend of increasing kurtosis.

[0071] After step S140, a non-stationary non-Gaussian random vibration signal with a specified power spectral density and kurtosis can be generated to meet the subsequent simulation tasks of actual engineering environment, thereby more accurately evaluating the reliability and safety of the structure under complex and variable actual working conditions.

[0072] like Figure 3 The diagram shown illustrates the generation process of a non-stationary, non-Gaussian random vibration signal.

[0073] In the above-mentioned method for generating non-stationary non-Gaussian random signals based on amplitude and phase joint modulation, a Gaussian signal is obtained by performing an inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal. A modulation signal is generated based on the frequency range. A non-stationary non-Gaussian signal is obtained based on the Gaussian signal and the modulation signal. The corresponding frequency domain amplitude spectrum and frequency domain phase spectrum are obtained based on the Gaussian signal and the non-stationary non-Gaussian signal, respectively. The non-stationary non-Gaussian signal is reconstructed by performing an inverse Fourier transform on the frequency domain amplitude spectrum and the frequency domain phase spectrum to obtain a reconstructed non-stationary non-Gaussian signal. It is determined whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis. If it does not meet the target kurtosis, the phase of the frequency domain phase spectrum is modulated until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis. The reconstructed non-stationary non-Gaussian signal is then the final output signal.

[0074] In actual engineering environments, such as earthquake engineering, ocean engineering, aerospace, etc., the vibration signals borne by structures are usually non-stationary and non-Gaussian. The method can generate signals with specified power spectrum, which can accurately simulate these actual vibration environments. For example, for seismic simulation, by setting appropriate power spectrum, the energy distribution of seismic waves at different frequencies can be reproduced, making the seismic test of building structures more close to the real seismic scenario. The specification of the target kurtosis helps to simulate the peak characteristics of the vibration signal, better simulates the sharp pulse signal under extreme conditions such as earthquakes, strong winds, etc., and thus more accurately evaluates the reliability and safety of the structure under complex and variable actual working conditions.

[0075] At the same time, for mechanical, electronic and other equipment, different working environments and conditions will cause the equipment to be subjected to different characteristics of vibration. In non-stationary and non-Gaussian random vibration, signals with specified power spectrum and kurtosis correspond to different vibration environments: the power spectrum is rich in low frequency and the kurtosis is high, which is often found in environments with low-frequency excitation sources and intermittent impacts, such as large buildings under strong winds; the power spectrum is widely distributed, and the kurtosis is moderately high, which is often found in complex multi-source excitation vibration environments, such as vehicles driving on rough roads; the power spectrum has obvious discrete peak value, and the kurtosis changes greatly, which is often related to vibration systems with specific frequency excitation or fault hidden danger, such as rotating machinery before and after failure; the power spectrum is mainly high frequency, and the kurtosis is low, which may occur in high-frequency excitation but relatively stable environments, such as high-frequency vibration table test; the power spectrum is time-varying and the kurtosis fluctuates, which is typical in complex environments that change dynamically, such as aircraft flight process. By generating non-stationary and non-Gaussian random signals with specified power spectrum and kurtosis, the method can simulate the vibration environment of equipment under various complex working conditions, which can be used for durability test, fault diagnosis test, etc. of equipment. This helps to find potential design defects in the product development stage, optimize product structure and performance, improve product quality, and shorten the product development cycle and reduce the cost of research and development.

[0076] It should be understood that, although Figure 2 The steps in the flowchart are displayed in sequence according to the direction of the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figure 2 At least part of the steps in

[0077] In one embodiment, as Figure 4As shown, a non-stationary non-Gaussian random signal generation device based on amplitude and phase joint modulation is provided, comprising: a data acquisition module 200, a non-stationary non-Gaussian signal generation module 210, a reconstructed non-stationary non-Gaussian signal generation module 220, and a reconstructed non-stationary non-Gaussian signal adjustment module 230, wherein:

[0078] The data acquisition module 200 is configured to acquire the power spectrum and the frequency range of the non-stationary non-Gaussian vibration signal.

[0079] The non-stationary non-Gaussian signal generation module 210 is configured to perform inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generate a modulation signal based on the frequency range, and obtain a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal.

[0080] The reconstructed non-stationary non-Gaussian signal generation module 220 is configured to obtain a frequency domain amplitude spectrum corresponding to the Gaussian signal and a frequency domain phase spectrum of the non-stationary non-Gaussian signal according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and reconstruct the non-stationary non-Gaussian signal according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal.

[0081] The reconstructed non-stationary non-Gaussian signal adjustment module 230 is configured to determine whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, modulate the phase of the frequency domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0082] The specific limitations of the non-stationary non-Gaussian random signal generation device based on amplitude and phase joint modulation can be referred to the limitations of the non-stationary non-Gaussian random signal generation method based on amplitude and phase joint modulation in the foregoing, which will not be repeated here. Each module in the above non-stationary non-Gaussian random signal generation device based on amplitude and phase joint modulation can be realized by software, hardware and their combination in whole or in part. The above modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each module.

[0083] In one embodiment, a computer device is provided, which can be a terminal, and its internal structure diagram can be as shown in Figure 5As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the computer device is used to communicate with the external terminal through the network connection. The computer program is executed by the processor to implement a non-stationary non-Gaussian random signal generation method based on amplitude and phase joint modulation. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0084] Those skilled in the art can understand that, Figure 5 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0085] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the following steps:

[0086] Obtaining the power spectrum and the frequency range of the non-stationary non-Gaussian vibration signal;

[0087] Performing inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal;

[0088] According to the Gaussian signal and the non-stationary non-Gaussian signal respectively, the frequency domain amplitude spectrum corresponding to the Gaussian signal and the frequency domain phase spectrum of the non-stationary non-Gaussian signal are obtained, and the non-stationary non-Gaussian signal is reconstructed through inverse Fourier transform according to the frequency domain amplitude spectrum and the frequency domain phase spectrum, to obtain a reconstructed non-stationary non-Gaussian signal;

[0089] Judging whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, if not, adjusting the phase of the frequency domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, then the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0090] In one embodiment, a computer readable storage medium is provided, having stored thereon a computer program, which when executed by a processor implements the following steps:

[0091] obtaining a power spectrum and a frequency range of the non-stationary non-Gaussian vibration signal;

[0092] performing inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal;

[0093] obtaining a frequency domain amplitude spectrum corresponding to the Gaussian signal and a frequency domain phase spectrum of the non-stationary non-Gaussian signal according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and reconstructing the non-stationary non-Gaussian signal according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0094] judging whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, adjusting the phase of the frequency domain phase spectrum through modulation until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0095] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. Any reference to memory, storage, database or other medium in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0096] Any combination of the technical features in the above embodiments can be made, and for the sake of brevity, not all possible combinations are described above, however, as long as the combination of the technical features does not exist in contradiction, it shall be considered within the scope of the present disclosure.

[0097] The above embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it shall not be understood as a limitation on the patent scope of the present application. It shall be pointed out that, for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, and these shall be within the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A method for generating non-stationary non-Gaussian random signals based on amplitude and phase joint modulation, characterized in that, The method comprises: acquiring a power spectrum and a frequency range of a non-stationary non-Gaussian vibration signal; performing inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal; obtaining a frequency domain amplitude spectrum corresponding to the Gaussian signal and a frequency domain phase spectrum of the non-stationary non-Gaussian signal according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and reconstructing the non-stationary non-Gaussian signal according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal; judging whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, modulating the phase of the frequency domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and then the reconstructed non-stationary non-Gaussian signal is the final output signal.

2. The method of claim 1, wherein, The frequency range is in the range of 0 to 100 Hz.

3. The method of claim 2, wherein, The generating of the modulation signal based on the frequency range comprises: generating a low-frequency standard normal distribution signal with a length equal to that of the Gaussian signal according to the frequency range; generating the modulation signal according to the absolute value of the low-frequency standard normal distribution signal.

4. The method of generating non-stationary non-Gaussian random signals according to any one of claims 1-3, characterized in that, The Gaussian signal is represented as: In the above equation, c0 is a constant, representing the mean value of the signal, A n represents the amplitude in the frequency domain, φ n represents the phase, Δf represents the frequency resolution, and N represents the number of sampling points of the signal.

5. The method of claim 4, wherein The reconstructed non-stationary non-Gaussian signal is represented as: In the above equation, A n_g denotes the amplitude of the Gaussian signal, φ n_x denotes the phase of the non-stationary non-Gaussian signal.

6. The method of claim 5, wherein, The kurtosis of the reconstructed non-stationary non-Gaussian signal is calculated using the following formula: In the above formula, A represents the amplitude of the Gaussian signal frequency domain, which reflects the intensity of different frequency component signals, φ represents the phase of the non-stationary non-Gaussian signal, which describes the relative position information of the signal at different times, and subscripts j, k, n, and m are used to distinguish the amplitudes and their corresponding phases that meet different conditions.

7. A non-stationary non-Gaussian random signal generating device based on amplitude and phase joint modulation, characterized in that, The device comprises: a data acquisition module for acquiring a power spectrum and a frequency range of a non-stationary non-Gaussian vibration signal; a non-stationary non-Gaussian signal generation module for performing inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generating a modulation signal based on the frequency range, and obtaining a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal; a reconstructed non-stationary non-Gaussian signal generation module for obtaining a frequency domain amplitude spectrum corresponding to the Gaussian signal and a frequency domain phase spectrum of the non-stationary non-Gaussian signal according to the Gaussian signal and the non-stationary non-Gaussian signal respectively, and reconstructing the non-stationary non-Gaussian signal according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal; a reconstructed non-stationary non-Gaussian signal adjustment module for judging whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis, and if not, modulating the phase of the frequency domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis, and then the reconstructed non-stationary non-Gaussian signal is the final output signal.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to realize the steps of the method in any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method in any one of claims 1 to 6.

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