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

Abstract

The invention relates to a non-stationary and non-Gaussian random signal generation method based on amplitude and phase joint modulation, and the method comprises the steps: carrying out the inverse Fourier transform of a power spectrum of a non-stationary and non-Gaussian vibration signal, obtaining a Gaussian signal, generating a modulation signal based on a frequency range, obtaining a non-stationary and non-Gaussian signal according to the Gaussian signal and the modulation signal, and generating a non-stationary and non-Gaussian random signal according to the non-stationary and non-Gaussian random signal. Respectively obtaining a corresponding frequency domain amplitude spectrum and a frequency domain phase spectrum according to the Gaussian signal and the non-stationary and non-Gaussian signal, reconstructing the non-stationary and non-Gaussian signal according to the frequency domain amplitude spectrum and the frequency domain phase spectrum through inverse Fourier transform, judging whether the kurtosis of the reconstructed non-stationary and non-Gaussian signal meets a preset target kurtosis or not, and if the kurtosis of the reconstructed non-stationary and non-Gaussian signal does not meet the preset target kurtosis, determining that the non-stationary and non-Gaussian signal does not meet the preset target kurtosis. And if so, modulating the phase of the frequency domain phase spectrum until the kurtosis of the reconstructed non-stationary and non-Gaussian signal meets the preset target kurtosis, and reconstructing the non-stationary and non-Gaussian signal as a final output signal. By adopting the method, the non-stationary and non-Gaussian signal with the specified power spectral density can be accurately generated.

Description

Technical Field

[0001] The present application relates to the technical field of vibration signal generation, and particularly to a method for generating non-stationary non-Gaussian random signals based on joint modulation of amplitude and phase. Background Art

[0002] In actual engineering structures (such as bridges, buildings, airplanes, etc.), the vibration excitations received are often non-stationary and non-Gaussian. For example, ground motions, strong winds, wave impacts, etc. The intensity, frequency components, etc. of these excitations vary with time, and their amplitude distributions usually deviate from the Gaussian distribution. In order to more realistically simulate these actual working conditions and conduct more accurate health monitoring, damage detection, and life prediction of the structure, it is necessary to generate corresponding non-stationary non-Gaussian random vibration signals for analysis and testing.

[0003] Existing generation of non-stationary non-Gaussian random vibration signals is as Figure 1 shown. It can be clearly seen from the figure that the existing method will change the frequency-domain amplitude of the original signal, thus unable to accurately generate non-stationary non-Gaussian signals with a specified power spectral density. However, in structural dynamics, the power spectral density is used to describe the distribution of the energy of random vibration excitations at different frequencies. If the power spectral density of the generated signal is inaccurate, then the response analysis (such as displacement, stress, etc.) of the structure based on this signal will have deviations. This may lead to inaccurate assessment of the safety and reliability of the structure, and there may be over-design or under-design situations when designing the structure. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method for generating non-stationary non-Gaussian random signals based on joint modulation of amplitude and phase that can accurately generate non-stationary non-Gaussian signals with a specified power spectral density.

[0005] A method for generating non-stationary non-Gaussian random signals based on joint modulation of amplitude and phase, the method comprising:

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

[0007] Perform an 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;

[0008] Respectively obtain 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, and reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0009] Determine whether the kurtosis of the reconstructed non-stationary non-Gaussian signal satisfies a preset target kurtosis. If not, modulate the phase of the frequency-domain phase spectrum until the kurtosis of the reconstructed non-stationary non-Gaussian signal satisfies the preset target kurtosis, and then the reconstructed non-stationary non-Gaussian signal is the final output signal.

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

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

[0012] Generate a low-frequency standard normal distribution signal with the same length as the Gaussian signal according to the frequency range;

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

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

[0015]

[0016] In the above formula, c 0 is a constant representing the mean 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 signal sampling points.

[0017] In one embodiment, the reconstructed non-stationary non-Gaussian signal is expressed 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 in the frequency domain of the Gaussian signal, which reflects the intensity of signals with different frequency components, φ represents the phase of the non-stationary non-Gaussian signal, describing the relative position information of the signal at different times, and the subscripts j, k, n, m are used to distinguish the amplitudes that meet different conditions and their corresponding phases.

[0023] This application also provides a non-stationary non-Gaussian random signal generation device based on joint modulation of amplitude and phase. The device includes:

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

[0025] A non-stationary non-Gaussian signal generation module, configured to perform an 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 respectively obtain 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, and reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an 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 the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis. 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 then the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0028] A computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0029] A method for generating a non-stationary non-Gaussian random signal based on joint modulation of amplitude and phase, the method including:

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

[0031] Perform an 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;

[0032] Respectively obtain 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, and reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0033] Determine whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis. 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 then the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0034] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

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

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

[0037] Perform an 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;

[0038] Respectively obtain 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, and reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0039] Judge whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis. 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 then the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0040] The above method for generating a non-stationary non-Gaussian random signal based on joint amplitude and phase modulation performs an inverse Fourier transform on the power spectrum of the non-stationary non-Gaussian vibration signal to obtain a Gaussian signal, generates a modulation signal based on the frequency range, obtains a non-stationary non-Gaussian signal according to the Gaussian signal and the modulation signal, respectively obtains the corresponding frequency-domain amplitude spectrum and frequency-domain phase spectrum according to the Gaussian signal and the non-stationary non-Gaussian signal, reconstructs the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal, judges whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis. 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 then the reconstructed non-stationary non-Gaussian signal is the final output signal. Using this method can accurately generate non-stationary non-Gaussian signals with a specified power spectral density. Description of the Drawings

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

[0042] Figure 2 It is a schematic flowchart of a method for generating a non-stationary non-Gaussian random signal based on joint amplitude and phase modulation in an embodiment;

[0043] Figure 3 It is a schematic flow chart of generating non-stationary non-Gaussian random signals using this method in an embodiment;

[0044] Figure 4 It is a structural block diagram of a non-stationary non-Gaussian random signal generation device based on amplitude and phase joint modulation in an embodiment;

[0045] Figure 5 It is an internal structure diagram of a computer device in an embodiment. Specific implementation manners

[0046] In order to make the objectives, technical solutions and advantages of this application clearer, the following further details this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0047] In order to truly simulate the actual working conditions of an actual engineering structure when it is subjected to vibration excitation and achieve more accurate health monitoring, damage detection and life prediction of the structure, it is necessary to generate corresponding non-stationary non-Gaussian random vibration signals for analysis and testing. However, using existing technologies, such as Figure 1 As shown, the power spectral density of the generated signal is not accurate. It can be clearly seen from the figure that this method will change the frequency-domain amplitude of the original signal, indicating that this method cannot accurately generate non-stationary non-Gaussian signals 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 power spectral density of the generated signal is inaccurate, then the response analysis (such as displacement, stress, etc.) of the structure based on this signal will have deviations. This may lead to inaccurate evaluations of the safety and reliability of the structure, and there may be over-design or under-design situations 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 during actual operation; conversely, over-design will result in waste of materials and costs. For mechanical equipment, its vibration characteristics at different frequencies are closely related to its performance and life. An inaccurate power spectral density signal will cause errors in the evaluation of the equipment's vibration characteristics, thereby affecting the judgment of the equipment's failure mode, fatigue life, etc. It may miss the early fault signs of the equipment, resulting in sudden equipment failures, affecting the production process, and even causing safety accidents. Therefore, generating non-stationary non-Gaussian signals with a specified power spectral density has important practical significance.

[0049] To address the above problems, in this application, as Figure 2As shown, a method for generating a non-stationary non-Gaussian random signal based on joint amplitude and phase modulation is provided, which specifically includes the following steps:

[0050] Step S100, obtain the power spectrum and frequency range of the non-stationary non-Gaussian vibration signal.

[0051] Step S110, perform an 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.

[0052] Step S120, respectively obtain 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, and reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal.

[0053] Step S130, determine whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis. If not, adjust the phase of the modulation 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.

[0054] In step S100, first obtain the power spectrum of a defined non-stationary non-Gaussian vibration signal, and here an appropriate power spectrum can be selected according to the subsequent specific application background.

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

[0056] In step S110, after a given power spectrum, generate a Gaussian signal g(t) through an inverse Fourier transform, expressed as:

[0057]

[0058] In formula (1), c 0 is a constant representing the mean 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 signal sampling points.

[0059] In this embodiment, generating a modulation signal based on the frequency range includes: generating a low-frequency standard normal distribution signal Z(t) equal in length to 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 automotive components.

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

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

[0062] In step S130, using the amplitude spectrum of the Gaussian signal g(t) and the phase spectrum of the non-stationary non-Gaussian signal x(t), the reconstructed non-stationary non-Gaussian signal is obtained through inverse Fourier transform. 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 a phase group that satisfies specific conditions is modulated until the target kurtosis is reached, which can ensure that the amplitude spectrum of the reconstructed signal does not change.

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

[0067]

[0068] In formula (3), A represents the amplitude in the frequency domain of the Gaussian signal, which reflects the intensity of signals with different frequency components. 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. 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 that satisfy different conditions and their corresponding phases. For example, in , n is used as the summation index and traverses from 1 to N, and A n represents different frequency-domain amplitudes of the Gaussian signal, and different n correspond to the amplitudes of different frequency components.,

[0069] In this embodiment, when phase-modulating the phase spectrum, if the phase φ of the random signal nIf it is randomly selected, then the values 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. Since the values of the cosine function are uniformly distributed between -1 and 1, the sums of these product terms compensate each other, resulting in the result of each summation term approaching 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 some phases are changed so that the sum of the phases in the cosine function in the summation term is 0, then the values of the cosine function are not uniformly distributed between -1 and 1, but the maximum value is 1. For example, in the third term let the phase group φ j and φ k (satisfying the subscript condition j = 3k) satisfy φ j = 3φ k , then the product of the amplitude and the cosine function corresponding to this subscript group in the third term will be equal to instead of being uniformly distributed between and This will lead to an increasing trend in 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 actual engineering environment simulation tasks, so as to more accurately evaluate the reliability and safety of the structure under complex and changing actual working conditions.

[0072] As Figure 3 shown, it is a schematic diagram of the generation process of the non-stationary non-Gaussian random vibration signal.

[0073] In the above method for generating non-stationary non-Gaussian random signals based on joint modulation of amplitude and phase, 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 according to the Gaussian signal and the modulation signal, the corresponding frequency-domain amplitude spectrum and frequency-domain phase spectrum are obtained respectively according to the Gaussian signal and the non-stationary non-Gaussian signal, the non-stationary non-Gaussian signal is reconstructed according to the frequency-domain amplitude spectrum and frequency-domain phase spectrum through an inverse Fourier transform 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. 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.

[0074] In actual engineering environments, such as in the fields of earthquake engineering, ocean engineering, aerospace, etc., the vibration signals endured by structures are usually non-stationary and non-Gaussian. Using this method can generate signals with a specified power spectrum, which can accurately simulate these actual vibration environments. For example, for earthquake simulation, by setting an appropriate power spectrum, the energy distribution of seismic waves at different frequencies can be reproduced, making the seismic resistance test of building structures closer to the real earthquake scenario. Among them, the specification of the target kurtosis helps to simulate the peak characteristics of vibration signals, better simulate the spike pulse signals under extreme working conditions such as earthquakes and strong winds, and thus more accurately evaluate the reliability and safety of structures under complex and changeable actual working conditions.

[0075] Meanwhile, for equipment such as machinery and electronics, different working environments and conditions will cause the equipment to be subjected to vibrations with different characteristics. In non-stationary and non-Gaussian random vibrations, signals with specified power spectra and kurtoses correspond to different vibration environments: rich in low frequencies and with a relatively high kurtosis in the power spectrum, commonly found in environments with low-frequency excitation sources and accompanied by intermittent impacts, such as large buildings under strong winds; wide-frequency distribution in the power spectrum and medium to high kurtosis, mostly seen in vibration environments with complex multi-source excitations, like a vehicle driving on a rough road; obvious discrete peaks in the power spectrum and large kurtosis variations, mostly related to vibration systems with specific frequency excitations or potential faults, such as before and after the failure of rotating machinery; mainly high-frequency in the power spectrum and relatively low kurtosis, which may occur in environments with high-frequency excitation but relatively stable, such as high-frequency vibration table tests; time-varying power spectrum and fluctuating kurtosis, typical in complex dynamically changing environments, such as the flight process of an aircraft. Using this method to generate non-stationary and non-Gaussian random signals with specified power spectra and kurtoses can simulate the vibration environments of equipment under various complex working conditions, and be used for durability tests, fault diagnosis tests, etc. of the equipment. This helps to discover potential design defects in the product R & D stage, optimize the product structure and performance, improve the product quality, and can also shorten the product R & D cycle and reduce the R & D cost.

[0076] It should be understood that although Figure 2 the steps in the flowchart of Figure 2 are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover,

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

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

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

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

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

[0082] For the specific limitations on the non-stationary and non-Gaussian random signal generation device based on combined amplitude and phase modulation, reference can be made to the limitations on the non-stationary and non-Gaussian random signal generation method based on combined amplitude and phase modulation in the above text, which will not be elaborated here. Each module in the above non-stationary and non-Gaussian random signal generation device based on combined amplitude and phase modulation can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0083] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as 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 operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes a method for generating a non-stationary non-Gaussian random signal based on joint amplitude and phase modulation. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the casing of the computer device, or an external keyboard, a touchpad, or a 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 some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0085] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

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

[0087] Perform an 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;

[0088] Respectively obtain 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. Reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0089] Judge whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis. 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. Then the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0090] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

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

[0092] Perform an 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;

[0093] Respectively obtain 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, and reconstruct the non-stationary non-Gaussian signal according to the frequency-domain amplitude spectrum and the frequency-domain phase spectrum through an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal;

[0094] Determine whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets a preset target kurtosis. 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 then the reconstructed non-stationary non-Gaussian signal is the final output signal.

[0095] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. 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 embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in this application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and 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] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0097] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to 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 a non-stationary non-Gaussian random signal based on joint amplitude and phase modulation, characterized in that: The method comprises: Obtain the power spectrum and frequency range of non-stationary non-Gaussian vibration signals; Performing an 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; According to the Gaussian signal and the non-stationary non-Gaussian signal, 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 respectively, and the non-stationary non-Gaussian signal is reconstructed according to the frequency domain amplitude spectrum and the frequency domain phase spectrum by inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal; Determine whether the kurtosis of the reconstructed non-stationary non-Gaussian signal meets the preset target kurtosis. 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. The reconstructed non-stationary non-Gaussian signal is the final output signal.

2. The method for generating a non-stationary non-Gaussian random signal according to claim 1, characterized in that: The frequency range is in the range of 0 to 100 Hz.

3. The method for generating a non-stationary non-Gaussian random signal according to claim 2, characterized in that: Generating a modulation signal based on the frequency range comprises: Generating a low-frequency standard normal distribution signal having a length equal to that of the Gaussian signal according to the frequency range; The modulation signal is generated according to the absolute value of the low-frequency standard normal distribution signal.

4. The method for generating a non-stationary non-Gaussian random signal according to any one of claims 1 to 3, characterized in that: The Gaussian signal is expressed as: In the above formula, c0 is a constant, which represents 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 for generating a non-stationary non-Gaussian random signal according to claim 4, characterized in that: The reconstructed non-stationary non-Gaussian signal is expressed as: In the above formula, A n_g represents the amplitude of the Gaussian signal, φ n_x Represents the phase of a non-stationary, non-Gaussian signal.

6. The method for generating a non-stationary non-Gaussian random signal according to claim 5, characterized in that: 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 in the frequency domain, which reflects the strength of signals with different frequency components. φ represents the phase of the non-stationary non-Gaussian signal, which describes the relative position information of the signal at different times. The 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 generation device based on amplitude and phase joint modulation, characterized in that: The device comprises: A data acquisition module, used to obtain the power spectrum and frequency range of the non-stationary non-Gaussian vibration signal; A non-stationary non-Gaussian signal generating module, used for performing an 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 is used to obtain a frequency domain amplitude spectrum and a frequency domain phase spectrum of the non-stationary non-Gaussian signal corresponding to the 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 an inverse Fourier transform to obtain a reconstructed non-stationary non-Gaussian signal; The reconstructed non-stationary non-Gaussian signal adjustment module is used to determine 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. The reconstructed non-stationary non-Gaussian signal is the final output signal.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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 steps of the method according to any one of claims 1 to 6 are implemented.

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