Method and device for processing multi-channel flutter test signals

Abstract

The embodiment of the present invention discloses a method and device for signal processing. The signal processing method includes: calculating a power spectrum density function matrix based on the acquired multi-channel turbulence response signal; obtaining a maximum singular value curve based on the power spectrum density function matrix; obtaining the self-power spectrum density function of the single-degree-of-freedom system based on the maximum singular value curve; and obtaining the modal parameters of the single-mode system based on the self-power spectrum density function. Through the present invention, the problem of turbulence response signal analysis in flutter flight test due to the existing technology in the related technology is solved, and the accuracy of modal parameter estimation is improved, while avoiding the technical effect of insufficient calculation real-time performance due to the random subspace method.

Description

Technical Field

[0001] The present invention relates to the field of aviation technology applications, and in particular to a signal processing method and device. Background Art

[0002] As a verification of flutter design, flutter test is an important and unavoidable link in the development process of aircraft. Accurate and effective characteristic analysis of flutter response signal is an important task in data processing of such test. Generally speaking, the implementation of artificial excitation source (such as frequency sweep of rudder surface, eccentric wheel excitation, rudder pedal, small rocket excitation, etc.) in the test can effectively improve the quality of flutter response signal, so as to improve the credibility of the conclusion of subsequent data processing. However, the active excitation method is often seriously restricted by the conditions of the flutter test itself. For example, the wind tunnel test is not convenient for implementing active excitation due to the limitation of model size and structure. The test flight needs to install excitation equipment to modify the aircraft, which increases the risk of test flight subjects such as dive, low altitude and high speed. At the same time, due to the common narrow-band characteristics of active excitation signal, the high-frequency modal information in the structure is not easy to be fully excited, which in turn affects the analysis effect of higher frequency modes.

[0003] Turbulence excitation is an unavoidable form of excitation in flutter flight tests / wind tunnel tests. At the same time, there is no need to make additional modifications to the aircraft / aeroelastic model. Turbulence excitation itself is a broadband noise, so it has become a necessary and effective excitation method in high-risk flight test subjects, wind tunnel tests, and high-frequency modal analysis. Since the atmospheric turbulence energy is dispersed and unmeasurable, although the turbulence response signal contains rich and valuable flutter test information, the randomness and low quality of its data often make modal analysis difficult, thus affecting the accurate acquisition of test conclusions. Summary of the invention

[0004] The embodiments of the present invention provide a signal processing method and device to at least solve the problem of turbulence response signal analysis in flutter flight test in the prior art.

[0005] According to one aspect of an embodiment of the present invention, a signal processing method is provided, comprising: calculating a power spectral density function matrix based on an acquired multi-channel turbulence response signal; obtaining a maximum singular value curve based on the power spectral density function matrix; obtaining an auto-power spectral density function of a single degree of freedom system based on the maximum singular value curve; and obtaining modal parameters of a single mode system based on the auto-power spectral density function.

[0006] Optionally, obtaining a power spectral density function matrix based on the acquired multi-channel turbulence response signal includes: performing power spectrum analysis on the multi-channel turbulence response signal to obtain a power spectral density function matrix corresponding to each signal in the multi-channel turbulence response signal, wherein the power spectral density function matrix is ​​an autocorrelation power spectral density function matrix or a cross-correlation power spectral density function matrix corresponding to each signal.

[0007] Further, optionally, obtaining the maximum singular value curve according to the power spectrum density function matrix includes: based on frequency domain orthogonality, performing singular value decomposition on the power spectrum density function matrix at each frequency point to obtain the maximum singular value curve of each frequency band.

[0008] Optionally, the method also includes: based on frequency domain orthogonality, performing singular value decomposition on the power spectrum density function matrix at each frequency point to obtain a left singular value vector corresponding to each frequency point; wherein the left singular value vector represents the modal vibration shape of the system.

[0009] Further, optionally, obtaining the autopower spectral density function of the single degree of freedom system according to the maximum singular value curve includes: analyzing the left singular value vector based on the modal vibration shape coherence criterion to obtain the autopower spectral density function of the single degree of freedom system at the corresponding frequency.

[0010] Optionally, obtaining the modal parameters of the single-mode system based on the auto-power spectral density function includes: performing frequency domain fitting on the auto-power spectral density function through orthogonal polynomials, and estimating the modal parameters of the single-degree-of-freedom system through the polynomial fitting to obtain the modal parameters of the single-mode system, wherein the modal parameters of the single-mode system include: frequency and damping of the single-degree-of-freedom system.

[0011] According to another aspect of an embodiment of the present invention, a signal processing device is provided, comprising: a signal processing module, used to calculate a power spectral density function matrix based on an acquired multi-channel turbulence response signal; a first acquisition module, used to obtain a maximum singular value curve based on the power spectral density function matrix; a second acquisition module, used to obtain an auto-power spectral density function of a single degree of freedom system based on the maximum singular value curve; and a third acquisition module, used to obtain modal parameters of a single-mode system based on the auto-power spectral density function.

[0012] Optionally, the signal processing module includes: a signal processing unit, used to perform power spectrum analysis on the multi-channel turbulence response signal to obtain a power spectrum density function matrix corresponding to each signal in the multi-channel turbulence response signal, wherein the power spectrum density function matrix is ​​an autocorrelation power spectrum density function matrix or a cross-correlation power spectrum density function matrix corresponding to each signal.

[0013] Further, optionally, the first acquisition module includes: a first acquisition unit, configured to perform singular value decomposition on the power spectrum density function matrix at each frequency point based on frequency domain orthogonality to obtain a maximum singular value curve of each frequency band.

[0014] Optionally, the first acquisition module also includes: a decomposition unit, used to perform singular value decomposition on the power spectrum density function matrix at each frequency point based on frequency domain orthogonality, to obtain a left singular value vector corresponding to each frequency point; wherein the left singular value vector represents the modal vibration shape of the system.

[0015] In the embodiment of the present invention, the power spectrum density function matrix is ​​calculated based on the acquired multi-channel turbulence response signal; the maximum singular value curve is obtained based on the power spectrum density function matrix; the self-power spectrum density function of the single degree of freedom system is obtained based on the maximum singular value curve; and the modal parameters of the single mode system are obtained based on the self-power spectrum density function. In other words, the embodiment of the present invention can solve the problem of turbulence response signal analysis in flutter flight test in the related technology due to the existing technology, and achieve the technical effect of improving the accuracy of modal parameter estimation, while avoiding the lack of real-time calculation due to the random subspace method. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 A schematic flow chart of a signal processing method provided by an embodiment of the present invention;

[0018] Figure 2 A schematic flow chart of another signal processing method provided by an embodiment of the present invention;

[0019] Figure 3 A schematic diagram of a signal processing device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "first", "second" and the like in the specification, claims and drawings of the present invention are used to distinguish different objects rather than to limit a specific order.

[0022] In the related art, there are mainly the following signal processing methods for frequency domain decomposition method and processing of turbulence response signals of flutter test:

[0023] The traditional frequency domain decomposition method calculates the auto-power spectral density function of the single-degree-of-freedom system by frequency domain decomposition based on the modal coherence criterion, calculates the time domain impulse response of the single-degree-of-freedom system by interpolation and zero padding, and then performs inverse Fourier transform, and then estimates the modal parameters;

[0024] For the analysis of turbulence response signals in flutter tests, usually in wind tunnel tests, since the test speed is close to the flutter boundary, the turbulence response signals can be processed by random reduction technology to obtain free decay response, and then the time domain modal parameters can be estimated;

[0025] In view of the fact that the test data in flutter test flight is far lower than the flutter speed and the atmospheric turbulence interference is relatively large, the modal parameters of the turbulence response signal are estimated by using the random subspace method.

[0026] However, the above signal processing solutions have good effects under certain technical conditions, but they also have certain technical defects:

[0027] In the traditional frequency domain decomposition method, the inverse Fourier transform of the auto-power spectrum of the single-degree-of-freedom system has poor effect in calculating the time domain impulse response signal due to the problem of spectral line density, which has a great impact on the fitting results.

[0028] The random reduction technique, which is commonly used in flutter wind tunnel tests, has a large error in calculating the free decay response signal due to problems such as atmospheric turbulence and principle flutter boundaries in flutter test flights, and the modal parameter estimation effect of flutter test flights is poor.

[0029] The random subspace method has good performance for modal parameter estimation of flutter test flight. However, in order to obtain better estimation results, the subspace method obtains a large number of modal parameters through modal parameter estimation of different orders, and identifies stable modes based on the steady-state diagram method. This signal processing method has high time requirements, which is a major defect in actual engineering applications.

[0030] Therefore, a signal processing method provided in an embodiment of the present application takes the turbulence response signal of a flutter test as the object, and improves the traditional frequency domain decomposition method, and directly performs modal parameter estimation of orthogonal polynomials in the frequency domain. Directly performing modal parameter estimation in the frequency domain can better avoid estimation errors caused by insufficient spectral line density, and improve the results of modal parameter estimation. According to the technical route of this frequency domain modal fitting, for the modal parameter estimation problem of the turbulence response signal of the flutter test, it is only necessary to obtain the autopower spectral density function of the system, and fitting can be performed in the frequency domain based on this scheme to obtain the modal parameter results of the system.

[0031] Specifically, according to one aspect of an embodiment of the present invention, a signal processing method is provided. Figure 1 A flow chart of a signal processing method provided by an embodiment of the present invention. Figure 1 As shown, the signal processing method provided in the embodiment of the present application includes:

[0032] Step S102, calculating a power spectrum density function matrix according to the acquired multi-channel turbulence response signal;

[0033] Optionally, calculating the power spectral density function matrix based on the acquired multi-channel turbulence response signal in step S102 includes: performing power spectrum analysis on the multi-channel turbulence response signal to obtain a power spectral density function matrix corresponding to each signal in the multi-channel turbulence response signal, wherein the power spectral density function matrix is ​​an autocorrelation power spectral density function matrix or a cross-correlation power spectral density function matrix corresponding to each signal.

[0034] Specifically, Figure 2 A flow chart of another signal processing method provided by an embodiment of the present invention is as follows: Figure 2 As shown, in the embodiment of the present application, a power spectrum analysis is performed on the multi-channel turbulence response signal to obtain the auto(cross)correlation power spectrum density function matrix of the corresponding signal, and the power spectrum density function matrix of the multi-channel turbulence response signal is obtained by the periodogram method.

[0035] Step S104, obtaining a maximum singular value curve according to a power spectrum density function matrix;

[0036] Optionally, obtaining the maximum singular value curve according to the power spectrum density function matrix in step S104 includes: performing singular value decomposition on the power spectrum density function matrix at each frequency point based on frequency domain orthogonality to obtain the maximum singular value curve of each frequency band.

[0037] Optionally, the signal processing method provided in the embodiment of the present application also includes: based on frequency domain orthogonality, performing singular value decomposition on the power spectrum density function matrix at each frequency point to obtain a left singular value vector corresponding to each frequency point; wherein the left singular value vector represents the modal vibration shape of the system.

[0038] Specifically, Figure 2 As shown, based on the orthogonality of the frequency domain, the power spectrum density function matrix is ​​subjected to singular value decomposition at each frequency point to obtain the maximum singular value curve of each frequency band and the left singular value vector corresponding to each frequency point; the maximum singular value curve is obtained by singular value decomposition (Singular Value Decomposition) based on the power spectrum density function matrix obtained in step S102.

[0039] Step S106, obtaining the autopower spectral density function of the single degree of freedom system according to the maximum singular value curve;

[0040] Optionally, obtaining the autopower spectral density function of the single degree of freedom system according to the maximum singular value curve in step S106 includes: analyzing the left singular value vector based on the modal vibration shape coherence criterion to obtain the autopower spectral density function of the single degree of freedom system at the corresponding frequency.

[0041] Specifically, Figure 2 As shown, based on the left singular value vector in step S104 representing the modal vibration shape of the system, the left singular value vector is analyzed based on the modal vibration shape coherence criterion to obtain the autopower spectral density function of the single degree of freedom system of the corresponding frequency; based on the modal frequency to be analyzed by the maximum singular value curve obtained in step S104, the autopower spectral density function of the single degree of freedom system is obtained according to the modal amplitude coherence condition.

[0042] Step S108, obtaining the modal parameters of the single-mode system according to the auto-power spectral density function.

[0043] Optionally, obtaining the modal parameters of the single-mode system based on the auto-power spectral density function in step S108 includes: performing frequency domain fitting on the auto-power spectral density function through orthogonal polynomials, and estimating the modal parameters of the single-degree-of-freedom system through the polynomial fitting to obtain the modal parameters of the single-mode system, wherein the modal parameters of the single-mode system include: frequency and damping of the single-degree-of-freedom system.

[0044] Specifically, Figure 2 As shown, the autopower spectral density function of the single degree of freedom system obtained in step S106 is frequency-domain fitted by orthogonal polynomials, and the modal parameters of the single degree of freedom system directly fitted by the polynomials are estimated, and finally the frequency and damping of the single degree of freedom system are obtained.

[0045] In summary, the signal processing method provided in the embodiment of the present application is aimed at analyzing the turbulence response signal in the flutter test flight, which can improve the accuracy of modal parameter estimation and avoid the problem of insufficient calculation real-time performance caused by the random subspace method.

[0046] In the embodiment of the present invention, the power spectrum density function matrix is ​​calculated based on the acquired multi-channel turbulence response signal; the maximum singular value curve is obtained based on the power spectrum density function matrix; the self-power spectrum density function of the single degree of freedom system is obtained based on the maximum singular value curve; and the modal parameters of the single mode system are obtained based on the self-power spectrum density function. In other words, the embodiment of the present invention can solve the problem of turbulence response signal analysis in flutter flight test in the related technology due to the existing technology, and achieve the technical effect of improving the accuracy of modal parameter estimation, while avoiding the lack of real-time calculation due to the random subspace method.

[0047] According to another aspect of an embodiment of the present invention, a signal processing device is provided. Figure 3 A schematic diagram of a signal processing device provided by an embodiment of the present invention. Figure 3 As shown, it includes: a signal processing module 32, which is used to calculate the power spectrum density function matrix based on the acquired multi-channel turbulence response signal; a first acquisition module 34, which is used to obtain the maximum singular value curve based on the power spectrum density function matrix; a second acquisition module 36, which is used to obtain the self-power spectrum density function of the single-degree-of-freedom system based on the maximum singular value curve; a third acquisition module 38, which is used to obtain the modal parameters of the single-mode system based on the self-power spectrum density function.

[0048] Optionally, the signal processing module 32 includes: a signal processing unit, used to perform power spectrum analysis on the multi-channel turbulence response signal to obtain a power spectrum density function matrix corresponding to each signal in the multi-channel turbulence response signal, wherein the power spectrum density function matrix is ​​an autocorrelation power spectrum density function matrix or a cross-correlation power spectrum density function matrix corresponding to each signal.

[0049] Further, optionally, the first acquisition module 34 includes: a first acquisition unit, configured to perform singular value decomposition on the power spectrum density function matrix at each frequency point based on frequency domain orthogonality to obtain a maximum singular value curve of each frequency band.

[0050] Optionally, the first acquisition module 34 also includes: a decomposition unit, which is used to perform singular value decomposition on the power spectrum density function matrix at each frequency point based on frequency domain orthogonality to obtain a left singular value vector corresponding to each frequency point; wherein the left singular value vector represents the modal vibration shape of the system.

[0051] Further, optionally, obtaining the autopower spectral density function of the single degree of freedom system according to the maximum singular value curve includes: analyzing the left singular value vector based on the modal vibration shape coherence criterion to obtain the autopower spectral density function of the single degree of freedom system at the corresponding frequency.

[0052] Optionally, obtaining the modal parameters of the single-mode system based on the auto-power spectral density function includes: performing frequency domain fitting on the auto-power spectral density function through orthogonal polynomials, and estimating the modal parameters of the single-degree-of-freedom system through the polynomial fitting to obtain the modal parameters of the single-mode system, wherein the modal parameters of the single-mode system include: frequency and damping of the single-degree-of-freedom system.

[0053] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A signal processing method, characterized in that: include: Calculate the power spectrum density function matrix based on the acquired multi-channel turbulence response signal; including: Performing power spectrum analysis on the multi-channel turbulence response signal to obtain the power spectrum density function matrix corresponding to each signal in the multi-channel turbulence response signal, wherein the power spectrum density function matrix is ​​an autocorrelation power spectrum density function matrix or a cross-correlation power spectrum density function matrix corresponding to each signal; Obtaining a maximum singular value curve according to the power spectrum density function matrix; comprising: Based on frequency domain orthogonality, singular value decomposition is performed on the power spectrum density function matrix at each frequency point to obtain the maximum singular value curve of each frequency band; Based on frequency domain orthogonality, singular value decomposition is performed on the power spectrum density function matrix at each frequency point to obtain a left singular value vector corresponding to each frequency point; wherein the left singular value vector represents a mode vibration shape of the system; Obtaining the auto-power spectral density function of the single degree of freedom system according to the maximum singular value curve; comprising: Analyzing the left singular value vector based on the modal vibration shape coherence criterion to obtain the autopower spectral density function of the single degree of freedom system at the corresponding frequency; Obtaining the modal parameters of the single-mode system according to the auto-power spectral density function; including: The autopower spectral density function is fitted in the frequency domain by orthogonal polynomials, and modal parameters of the single-degree-of-freedom system fitted by the polynomials are estimated to obtain the modal parameters of the single-mode system, wherein the modal parameters of the single-mode system include: frequency and damping of the single-degree-of-freedom system.

2. A device for implementing the signal processing method according to claim 1, characterized in that: include: A signal processing module, used for calculating a power spectrum density function matrix based on the acquired multi-channel turbulence response signal; A first acquisition module, used for acquiring a maximum singular value curve according to the power spectrum density function matrix; A second acquisition module is used to acquire the autopower spectral density function of the single degree of freedom system according to the maximum singular value curve; The third acquisition module is used to obtain the modal parameters of the single-mode system according to the autopower spectral density function.

3. The device according to claim 2, characterized in that The signal processing module comprises: A signal processing unit is used to perform power spectrum analysis on the multi-channel turbulence response signal to obtain the power spectrum density function matrix corresponding to each signal in the multi-channel turbulence response signal, wherein the power spectrum density function matrix is ​​an autocorrelation power spectrum density function matrix or a cross-correlation power spectrum density function matrix corresponding to each signal.

4. The device according to claim 3, characterized in that The first acquisition module includes: The first acquisition unit is used to perform singular value decomposition on the power spectrum density function matrix at each frequency point based on frequency domain orthogonality to obtain the maximum singular value curve of each frequency band.

5. The device according to claim 4, characterized in that The first acquisition module also includes: A decomposition unit is used to perform singular value decomposition on the power spectrum density function matrix at each frequency point based on frequency domain orthogonality to obtain a left singular value vector corresponding to each frequency point; wherein the left singular value vector represents a modal vibration shape of the system.

Images