Method, device and equipment for confirming far-field noise signal of aircraft for closing penetrable surface and medium

Abstract

The invention relates to a method, a device and equipment for confirming an aircraft far-field noise signal for a closed penetrable surface and a medium. The method comprises the following steps of: dividing the closed penetrable surface into a plurality of integral surfaces which are not overlapped; respectively calculating a time domain sound pressure signal of each integral surface to the same observation point; whether turbulence passes through each integration surface is judged, if no turbulence passes through the integration surface, a far-field noise signal is obtained, and if turbulence passes through the integration surface, a sound pressure signal is obtained; purifying the sound pressure signal to obtain a purified far-field noise signal about the integral surface; and carrying out summation calculation on the obtained far-field noise signal of each integration surface and the far-field noise signal obtained by purification to obtain an aircraft far-field noise signal of the closed penetrable surface. According to the method, only one closed penetrable integral surface is needed, the complexity that multiple layers of downstream closed surfaces are needed to confirm noise in an existing method is overcome, and the method is easy and convenient to operate and has practicability.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft noise prediction and calculation, and particularly relates to a method, device, equipment and medium for confirming aircraft far-field noise signals for a closed penetrable surface. Background Art

[0002] With the acceleration of the social rhythm, air travel, a fast and convenient way of traveling, is increasingly favored by people, and the air transportation industry has developed rapidly. However, with the growth of the number of aircraft and the takeoff and landing frequency, the problem of aircraft noise pollution, together with aircraft emissions pollution and adverse effects on the climate, has been recognized as the three major environmental hazards caused by the development of the air transportation industry. For this reason, the International Civil Aviation Organization has promulgated a series of increasingly stringent aircraft noise airworthiness regulations to restrict this, and the noise level has become a mandatory airworthiness indicator for civil aircraft. With the progress of noise reduction technology and increasingly strict environmental protection requirements, the continuously improving noise airworthiness standards have become the consensus of Western aviation powers. The currently implemented fourth-stage civil aircraft noise airworthiness regulations have an index that is approximately 10 dB lower than the original standard in the third stage. In 2017, the more stringent fifth-stage noise airworthiness regulations have been implemented. The implementation of the increasingly stringent civil aircraft noise airworthiness regulations has become a way to improve the access conditions for the civil aviation industry and eliminate competitors. The increasingly demanding noise airworthiness regulations, while bringing impacts to the aviation industry, have also become a driving force for promoting the research of low-noise technologies. For this reason, it is necessary to reduce noise to achieve a low noise level.

[0003] To predict aircraft noise, the currently widely used noise prediction method is a hybrid noise prediction method based on the unsteady flow field + FW-H integral method. The hybrid calculation first obtains the flow field and sound field information in the near field through unsteady numerical simulation, and then expands the sound field solution from the near field to the far field through the FW-H integral method. The FW-H equation uses a non-physical closed penetrable surface as the integration surface, and the complete solution consists of an area integral and a volume integral. If the penetrable integration surface is large enough so that the generation, reflection, and refraction of sound waves are all enclosed therein, the contribution of the volume integral to the sound field can be ignored, and thus the sound field outside the integration surface can be calculated only using the thickness noise source and the load noise source on the penetrable integration surface, such as the analytical formula Formulation 1A.

[0004] However, in practical applications, the penetrable integral surface often passes through a certain nonlinear region. The nonlinear small perturbations of the near-field flow contain both sound waves and vortex waves. The vortex waves decay slowly and propagate downstream along the mean flow. When passing through the penetrable integral surface, the vortex wave disturbance will be collected by the input of the pseudo-integral surface to produce pseudo sound. There are differences in the understanding of the pseudo-sound generation mechanism in the academic community. One view is that this is caused by the sharp truncation of the integral region by the penetrable integral surface, which introduces spectrum leakage. Another view is that the solution method of the acoustic analogy equation destroys the source term filtering function. Morfey et al. found that considering the contribution of the volume source term of the penetrable integral surface can eliminate pseudo-sound pollution. Rahier et al. clearly pointed out through theoretical analysis and numerical experiments that pseudo-sound pollution is caused by ignoring the contribution of the quadrupole volume source term. Obrist et al.'s research shows that the sharp truncation of the integral region by the penetrable integral surface will lead to spectrum leakage, thereby producing pseudo-sound that pollutes the sound field. Mao Yijun et al. analyzed the decoupling of the load source and thickness source of the convection FW-H equation and believed that the load source and thickness source can automatically filter the vortex wave pseudo-sound contained in themselves, but the mathematical deduction process is not strictly valid even for stationary penetrable surfaces. Accurate prediction of far-field noise requires an effective method to suppress pseudo-wave interference. The simplest method is to directly abandon the area in the penetrable surface that allows vortex waves to pass through, and predict the noise by integrating the non-closed penetrable integral surface. However, the derivation of the FW-H equation is based on the closed penetrable integral surface, so the method of using the non-closed penetrable integral surface is mathematically inaccurate. Spalart et al. used multiple adjacent penetrable integral surfaces to extract the sound source, and the final sound field is the average of the integral results of these penetrable integral surfaces. Mendez et al. gave an expression for estimating the number and position of penetrable integral surfaces. Obrist et al. suggested using a smoothly changing spatial window function to reduce truncation errors. Wright et al. proposed a generalized FW-H equation that uses penetrable integral surface data with different weights or finite thickness volume sources to reduce pseudo-wave intensity. The pseudo-wave suppression method using multiple penetrable surface data or finite thickness volume sources will lead to an increase in the sound source storage and acoustic calculation. Ikeda et al. converted the contribution of infinitely thin volume sources into surface integrals and proposed a pseudo-wave suppression method for additional surface sources. Starting from the linear Euler equation, Zhong et al. developed a sound far extrapolation method that considers the influence of local non-uniform flow on the penetrable surface, and used the divergence of the disturbance velocity and the material derivative to automatically filter the vortex waves, but increased the difficulty of calculating the integral surface source term. Mao Yijun et al. suggested using the Kirchhoff integral equation to predict noise propagation to suppress pseudo-wave pollution, but the Kirchhoff integral surface is only applicable to the linear region. Summary of the invention

[0005] In order to overcome the problems existing in the prior art, the present invention provides a method, device, equipment and medium for confirming the far-field noise signal of an aircraft of a closed penetrable surface, which are used to overcome the existing defects.

[0006] A method for confirming the far - field noise signal of an aircraft for closing a penetrable surface, the method comprising the following steps:

[0007] First step: Divide the penetrable surface into multiple non - overlapping integration surfaces;

[0008] Second step: Calculate the time - domain sound pressure signals at the same observation point for each integration surface respectively;

[0009] Third step: Determine whether there is turbulence passing through each integration surface. If there is no turbulence passing through the integration surface, the obtained signal is the far - field noise signal. If there is turbulence passing through the integration surface, the obtained signal is the sound pressure signal;

[0010] Fourth step: Purify the sound pressure signal to obtain the purified far - field noise signal for this integration surface;

[0011] Fifth step: Perform a summation calculation on the far - field noise signals of each integration surface obtained in the third step and the purified far - field noise signals to obtain the far - field noise signal of the aircraft for the penetrable surface.

[0012] For the above - mentioned aspects and any possible implementation manners, a further implementation manner is provided. In the second step, the calculation is performed based on the FW - H integral equation.

[0013] For the above - mentioned aspects and any possible implementation manners, a further implementation manner is provided. The integration surface includes an upstream integration surface and a downstream integration surface, and there is turbulence on the downstream integration surface.

[0014] For the above - mentioned aspects and any possible implementation manners, a further implementation manner is provided. The fourth step specifically includes: S21. Perform wavelet transform on the sound pressure signal to obtain the transformed sound pressure signal;

[0015] S22. Compare the absolute value of the transformed wavelet coefficients with a set threshold to obtain new wavelet coefficients,

[0016] S23. Perform inverse wavelet transform on the transformed sound pressure signal based on the new wavelet coefficients to obtain the noise time - domain signal;

[0017] S24. Calculate the cross - correlation coefficient between the noise time - domain signal and the far - field noise signal of the integration surface adjacent to the integration surface to which it belongs;

[0018] S25. Iteratively calculate the cross - correlation coefficient until the cross - correlation coefficient reaches the maximum value. At this time, the obtained noise time - domain signal is used as the purified far - field noise signal.

[0019] For the aspects and any possible implementation manners described above, a further implementation manner is provided. Specifically, S22 includes: if the absolute value of a wavelet coefficient is greater than a threshold, the wavelet coefficient is set to 0; if the absolute value of the wavelet coefficient is less than or equal to the set threshold, the wavelet coefficient remains unchanged, thereby obtaining new wavelet coefficients.

[0020] For the aspects and any possible implementation manners described above, a further implementation manner is provided. The multiple non-overlapping integration surfaces include at least three non-overlapping integration surfaces.

[0021] For the aspects and any possible implementation manners described above, a further implementation manner is provided. The method further includes a sixth step: post-processing the far-field noise signal of the aircraft to obtain a spectrum signal and a directivity characteristic signal.

[0022] The present invention also provides a confirmation device for the far-field noise signal of an aircraft for closing a penetrable surface. The device is used to implement the described confirmation method. The device includes: a division module for dividing the closed penetrable surface into multiple non-overlapping integration surfaces;

[0023] a calculation module for respectively calculating the time-domain sound pressure signals at the same observation point for each integration surface;

[0024] a judgment module for judging whether there is turbulence passing through each integration surface. If there is no turbulence passing through the integration surface, the obtained signal is the far-field noise signal. If there is turbulence passing through the integration surface, the obtained signal is a flow disturbance signal including non-sound sources;

[0025] a purification processing module for purifying the flow disturbance signal to obtain a purified far-field noise signal for the integration surface;

[0026] a summation calculation module for performing summation calculation on the far-field noise signals of each obtained integration surface and the purified far-field noise signal to obtain the far-field noise signal of the aircraft for the closed penetrable surface.

[0027] The present invention also provides an electronic device, which includes:

[0028] a memory storing executable instructions;

[0029] a processor that runs the executable instructions in the memory to implement the described method.

[0030] The present invention also provides a computer storage medium, on which a computer program is stored. The computer program is executed by a processor to implement the described method.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The method for confirming the far-field noise signal of an aircraft for closing a penetrable surface in the present invention divides the closing penetrable surface into multiple non-overlapping integration surfaces; calculates the time-domain sound pressure signals at the same observation point for each integration surface respectively; determines whether there is turbulence passing through each integration surface. If there is no turbulence passing through the integration surface, the obtained signal is the far-field noise signal. If there is turbulence passing through the integration surface, the obtained signal is the sound pressure signal; purifies the sound pressure signal to obtain the purified far-field noise signal for this integration surface; sums up the far-field noise signals of each obtained integration surface and the purified far-field noise signal to obtain the far-field noise signal of the closing penetrable surface of the aircraft. The present invention only requires a closed integration surface, overcomes the complexity of the existing method that requires multiple downstream closed surfaces, is simple and convenient to operate, and has practicability; the calculation method does not need to modify the sound source equation (the traditional flow field solution calculates the N-S flow equation, and its calculation result is used as the input of the FW-H equation for far-field noise calculation. Some researchers have partially modified the N-S equation according to their own needs to improve the accuracy. Different researchers have different modification methods, so there are different sound source equations). It only needs to post-process the noise calculation result and has practicability; the present invention only needs to separately integrate the closed integration surface and purify the noise calculation result of the downstream integration surface according to the noise calculation result of the upstream integration surface, and filter out the pseudo sound. The calculation is simple and convenient. Description of the Drawings

[0033] Figure 1 It is a schematic diagram of the single-layer penetrable integration surface of the present invention;

[0034] Figure 2 It is a schematic diagram of the purification process of the present invention;

[0035] Figure 3 It is a schematic diagram of the transient flow velocity on the integration surface of the present invention;

[0036] Figure 4 It is a schematic diagram of the transient density distribution on the integration surface of the present invention;

[0037] Figure 5 It is a schematic diagram of the transient pressure distribution on the integration surface of the present invention;

[0038] Figure 6 It is a schematic diagram of the integration surface used in the average method of the traditional multi-layer penetrable integration surface;

[0039] Figure 7 It is the integration surface used in the single-layer penetrable integration surface filtering method of the present invention;

[0040] Figure 8 It is a schematic diagram of the comparison of prediction results (directly below the nozzle) when the observation angle of the present invention is 90 degrees;

[0041] Figure 9 It is a schematic diagram of the comparison of the predicted results (downstream of the nozzle) at an observation angle of 170 degrees of the present invention. Detailed implementation manners

[0042] For a better understanding of the technical solution of the present invention, the content of the present invention includes but is not limited to the following detailed implementation manners, and similar technologies and methods should be regarded as within the scope of protection of the present invention. To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0043] It should be clear that the embodiments described in the present invention are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work shall fall within the scope of protection of the present invention.

[0044] The present invention provides a method for confirming the far-field noise signal of an aircraft for closing a penetrable surface, and the method includes the following steps:

[0045] The first step: Divide the closed penetrable surface into a plurality of non-overlapping integration surfaces;

[0046] The second step: Calculate the time-domain sound pressure signals at the same observation point for each integration surface respectively;

[0047] The third step: Determine whether there is turbulence passing through each integration surface. If there is no turbulence passing through the integration surface, the obtained signal is the far-field noise signal. If there is turbulence passing through the integration surface, the obtained signal is the sound pressure signal;

[0048] The fourth step: Purify the sound pressure signal to obtain the purified far-field noise signal of the integration surface;

[0049] The fifth step: Perform a summation calculation on the far-field noise signals of each integration surface obtained in the third step and the purified far-field noise signal to obtain the far-field noise signal of the aircraft for the closed penetrable surface.

[0050] Further, in the second step, the calculation is performed based on the FW-H integral equation.

[0051] Further, the integration surface includes an upstream integration surface and a downstream integration surface, and there is turbulence on the downstream integration surface.

[0052] Further, the fourth step specifically includes: S21. Perform a wavelet transform on the sound pressure signal to obtain the transformed sound pressure signal;

[0053] S22. Compare and process the absolute value of the transformed wavelet coefficient with a set threshold to obtain a new wavelet coefficient,

[0054] S23. Perform an inverse wavelet transform on the transformed sound pressure signal based on the new wavelet coefficients to obtain a noise time-domain signal;

[0055] S24. Calculate the cross-correlation coefficient between the noise time-domain signal and the far-field noise signal of the integration surface adjacent to the integration surface to which it belongs;

[0056] S25. Iteratively calculate the cross-correlation coefficient until the cross-correlation coefficient reaches the maximum value. At this time, the obtained noise time-domain signal is used as the purified far-field noise signal.

[0057] Further, the S22 specifically includes: if the absolute value of the wavelet coefficient is greater than the threshold, the wavelet coefficient is set to 0; if the absolute value of the wavelet coefficient is less than or equal to the set threshold, the wavelet coefficient remains unchanged, thereby obtaining new wavelet coefficients.

[0058] Further, the multiple non-overlapping integration surfaces include at least three non-overlapping integration surfaces.

[0059] Further, the method further includes a sixth step: post-process the far-field noise signal of the aircraft to obtain a spectrum signal and a directivity characteristic signal.

[0060] Specifically, the specific process of the present invention is as follows:

[0061] The present invention proposes a method for calculating the far-field noise of an aircraft applicable to a closed penetrable surface.

[0062] The closed penetrable surface, also known as the closed integration surface, where the "closed" indicates that the surface includes a flow region, and the penetrable surface is a geometric surface through which both fluid and sound can flow. The corresponding to the penetrable surface is the non-penetrable surface, which is the surface of the aircraft body, that is, neither fluid nor sound can flow through. The method proposed by the present invention is to use a single-layer closed penetrable surface. The advantage of a single layer is that it is relatively simple to generate such a surface, and the subsequent calculation of noise is also simple. The multi-layer means there are multiple single layers. The disadvantage is that it is relatively complex to generate multi-layers, and the distance between multi-layers needs to be adjusted depending on experience. The difference between upstream and downstream is to divide the closed penetrable surface into a region with turbulent flow (i.e., vortex waves) passing through and a region without turbulent flow passing through. The upstream is the region without vortex waves passing through, and the downstream is the region with vortex waves passing through. The specific process of the method for calculating the far-field noise of an aircraft applicable to a closed penetrable surface is as follows:

[0063] The first step: Divide the overall closed integration surface into a combination of multiple integration surfaces. For example, it is divided into an upstream integration surface and a downstream integration surface, or, Figure 1As shown, the overall closed integration surface S is divided into S1, S2, and S3: S = S1 + S2 + S3. S1 and S2 are upstream integration surfaces, and S3 is the downstream integration surface. There is no overlap between these three surfaces. If there is overlap between the surfaces, it will lead to double-counting of the noise radiation of the overlapping surface. Therefore, there is no overlap between the three surfaces.

[0064] Step 2: Based on the FW-H integral equation, calculate the time-domain sound pressure signals at the same observation point for the three integration surfaces respectively. The results are P S1 (t), P S2 (t), P S3 (t). Among them, the observation point is set at a place far from the aircraft, while the integration surface is at a place close to the aircraft. Therefore, the observation point is set at a place far from the integration surface. The FW-H integral equation is a prior art, and the process of using this FW-H integral equation for calculation in the present invention is a known method, which will not be elaborated here.

[0065] Step 3: There is no turbulent flow passing through the S1 and S2 integration surfaces, and the obtained is the actual noise contribution. However, since there is turbulent flow passing through the S3 surface, the P S3 (t) contains the contribution of flow perturbation of non-sound sources. The S1 integration surface and the S2 integration surface are as Figure 1 shown. For the prediction of engine jet noise, the jet flow direction is from left to right. Therefore, there is no turbulent flow passing through the S1 and S2 surfaces, and there is turbulent flow passing through the S3 surface. Turbulence will generate noise, which is one of the sources of noise.

[0066] Step 4: Purify the time-domain sound pressure signal P S3 (t) to obtain Specifically, it includes the following steps:

[0067] 1. Perform wavelet transform on the sound pressure signal P S3 (t) calculated from the downstream integration surface S3. The specific expression is:

[0068]

[0069] Among them, represents the complex conjugate of the scaled and translated mother wavelet function ψ(t). Both t and τ represent time, t - τ represents translation, and dividing by s represents scaling. represents the scaling and translation transformation of t. The mother wavelet function uses the complex Morlet mother wavelet function, and the definition of the complex Morlet mother wavelet function is f b and f c respectively represent the bandwidth parameter and the center frequency, which is the frequency range that the mother wavelet function can distinguish and is a known quantity that is continuously adjusted with the scale scaling. j represents the imaginary unit; the scale fs Denote P S3 (t) as the sampling frequency, f represents the actual corresponding frequency, which is the frequency of interest to the user. The user will give a frequency sequence, which is a known quantity; w p (s,τ) represents the wavelet coefficient corresponding to time τ and scale s; the wavelet coefficients corresponding to different times and different scales are used as elements to form a wavelet coefficient matrix.

[0070] 2. Set the threshold for the wavelet coefficients; force the wavelet coefficients whose absolute values are greater than the threshold T to be 0, and keep the wavelet coefficients whose absolute values are less than or equal to the threshold T unchanged. The pulsating pressure of non - sound sources and the noise pulsating pressure have significant differences in the time - frequency domain. The pulsating pressure of non - sound sources (i.e., turbulent pulsating pressure) has the characteristic of fast attenuation in the time - frequency domain, so the wavelet coefficients are relatively large. While the noise pulsating pressure attenuates more slowly in the time - frequency domain, so the wavelet coefficients are relatively small. By setting the wavelet coefficient threshold, the noise pulsating pressure and the pulsating pressure of non - sound sources are separated, that is, the noise pulsating pressure is purified.

[0071] The new wavelet coefficients The calculation formula is as follows:

[0072]

[0073] where, w p (s,τ) is calculated by formula (1).

[0074] 3. Perform the inverse wavelet transform based on the new wavelet coefficient matrix to obtain the noise time - domain signal The inverse transform is to transform the new wavelet coefficient matrix to the time domain to obtain (t) signal. By using this step, the noise pulsating pressure without non - sound sources is obtained. The expression for obtaining is as follows:

[0075]

[0076] where, represents the Fourier transform of the mother wavelet function ψ(t), t represents time, s represents scale, represents the new wavelet coefficient matrix, obtained by formula (2); represents the scaling and translation of the mother wavelet function ψ(t), both t and τ represent time, t - τ represents translation, and dividing by s represents scaling, represents the scaling and translation transformation of t.

[0077] 4. Calculate and P S2 (t) or P S1(t) Perform relevant calculations. The sound pressure signals obtained from surfaces S1 and S2 are both noise contributions and do not contain the influence of the pseudo sound sources generated by vortex waves. Specifically, select P S2 (t) or P S1 (t) When performing relevant calculations, it is only necessary to select a surface where there is no vortex wave or turbulence passing through. The present invention selects P S2 (t) as an example for illustration. The purpose of calculating with P S2 (t) is to obtain the cross-correlation coefficient between the two, and determine whether the cross-correlation coefficient is the maximum. If it is not the maximum, update the threshold in step 2, and execute step 3 and this step again. In order to obtain the optimal wavelet coefficient threshold, continuous iteration is performed until the cross-correlation coefficient reaches the maximum value. At this time, it indicates that there is no pulsating pressure signal of non-sound sources in the P S2 (t) signal. The noise time-domain signal after iteration at this time contains more noise pulsating pressure signals and fewer non-sound source pulsating pressure signals, and is used as the far-field noise of the purified S3 surface. This step determines whether the wavelet coefficient threshold is optimal through the cross-correlation coefficient. Only the optimal wavelet coefficient threshold can obtain the purest noise pulsating pressure, that is, it does not contain the pollution of the pulsating pressure signal of non-sound sources. The calculation formula of the cross-correlation coefficient is as follows:

[0078]

[0079] 5. The far-field noise signal obtained by adding the far-field noise sound pressure of the S1 surface, the far-field noise sound pressure of the S2 surface, and the purified sound pressure signal of the far-field noise of the S3 surface is:

[0080]

[0081] 6. Based on the obtained sound pressure signal P(t), further post-processing can be carried out to obtain the spectrum, directivity, etc. Among them, the spectrum is obtained by performing a Fourier transform on the sound pressure signal P(t). The directivity is to obtain the noise spectra of observation points in different directions, and the change of the noise spectrum in different directions can be drawn.

[0082] Step 4 of the present invention is to purify the noise time domain. The specific process is as follows: The method first performs time-frequency decomposition on the pulsating pressure signal P S3 (t) using wavelet transform. Because there are vortex waves passing through the S3 surface, P S3 (t) is contaminated by the vortex wave signal and needs to be purified.

[0083] The Continuous Wavelet Transform (CWT) performs a continuous wavelet transform on the sound pressure time-domain signal p(τ), and the mother wavelet function is ψ(t). This mother wavelet function has locality in both the time domain and the transform domain. The transformed wavelet coefficients are functions of time t and scale s, and the scale is inversely proportional to the frequency. That is, the larger the scale, the smaller the frequency.

[0084] The CWT transform expression of the sound pressure time-domain signal, also known as the pressure time-domain signal, is as follows:

[0085]

[0086] Where is a constant considering the average value of Ψ(t), is the complex conjugate after the scaling and translation transformation of Ψ(t).

[0087] In actual processing, the Discrete Wavelet Transform (DWT) is used to decompose the pressure time-domain signal p(t). If the scale s j = 2 j , and the translation is the product of the scale s j , the orthogonal basis function ψ(t) can be expressed as:

[0088]

[0089] The calculation formula for the discrete wavelet coefficients is:

[0090]

[0091] Where s represents the discrete scale, and the wavelet function is the discrete expression of.

[0092] Since the flow pulsation pressure component in the near-field pressure is related to the local vortex wave and can be well projected onto the wavelet basis function, the near-field pressure is the pressure in the region closer to the sound source. The integration surface here is generally selected in the near-field, and the pressure on all integration surfaces is the near-field pressure. Therefore, the turbulent pulsation pressure is calculated from the flow field. The pulsation pressure on the integration surface is the turbulent pulsation pressure, which can be judged by selecting a suitable threshold. The components of the wavelet transform coefficients whose absolute values are greater than this threshold are the turbulent pulsation pressure, that is, the pressure signal obtained after the inverse transformation of the elements with larger wavelet transform coefficients is the turbulent pulsation pressure. The suitable threshold is found through continuous iteration, that is, the optimal threshold. The suitable threshold cannot be known in advance, so the present invention uses the method of continuous iteration to find it. For specific details, please refer to the previous description. The criterion for iteration is whether the cross-correlation coefficient reaches the maximum.

[0093] The near-field pressure signal contains both a noise pressure signal and a pulsating pressure signal (turbulent pulsating pressure signal) from non-acoustic sources. What is required in the present invention is the noise pressure signal, so the pulsating pressure from non-acoustic sources needs to be removed. The remaining pressure component in the near-field pressure signal is the noise pulsating pressure.

[0094] The wavelet coefficient threshold is selected and used to separate the pulsating pressure from non-acoustic sources (turbulent pulsating pressure) and the noise pressure signal. The calculation formula for the initial value T0 of the wavelet coefficient threshold in the present invention is as follows:

[0095]

[0096] where <P S3 (t) 2 > is the variance of the pressure signal P S3 (t), N s is the number of samples of P S3 (t), that is, the number of sequences of the pulsating pressure signal.

[0097] Next, the method proposed in the present invention is verified. The verification example used is the jet noise of a certain type of aircraft engine. The unsteady flow field of the jet is calculated using the commercial software PowerFLOW, and a closed penetrable surface is selected around the jet as the integration surface for FW-H. Figure 3 、 Figure 4 and Figure 5 respectively show the contour maps of the transient flow velocity, transient density, and transient pressure distribution on the penetrable integration surface. It can be seen from the figures that the velocity gradient on the downstream penetrable integration surface is the largest, mainly because the jet flow penetrates this integration surface, and these vortex waves are not entirely real physical sound sources. Therefore, if the contribution of this integration surface is included in the calculation, pseudo sound sources may be generated.

[0098] The jet noise is predicted using the traditional multi-layer penetrable integration surface averaging method and the single-layer penetrable integration surface filtering method proposed in the present invention respectively. And it is compared and verified with the verified semi-empirical prediction model of jet noise. Figure 6 The integration surface used in the traditional multi-layer penetrable integration surface averaging method is shown. Figure 7 The integration surface used in the single-layer penetrable integration surface filtering method proposed in the present invention is shown. It can be seen that compared with the multi-layer FW-H integration surface of the traditional method, the single-layer FW-H integration surface used in the method of the present invention is simpler.

[0099] Figure 8 and Figure 9 respectively show the comparison of the jet noise spectrum prediction results at two different observation angles. Three curves are shown in each figure. From Figure 8 and9 It can be seen that at the downstream observation point, the error of the traditional multi-layer penetrable integral surface averaging method is relatively large. This is mainly because the contribution of the downstream integral surface to this observation point is relatively large. When the calculation error of this integral surface is relatively large, the error of the final prediction result is also very large. The result obtained by the single-layer penetrable integral surface filtering method proposed by the present invention is closer to the result obtained by the semi-empirical prediction model, and the spectrum in the low-frequency and high-frequency ranges is also significantly improved. Moreover, the prediction result of the method of the present invention is more accurate than that of the traditional method, especially in the low-frequency and high-frequency parts.

[0100] As an embodiment disclosed by the present invention, the present invention also provides a confirmation device for the far-field noise signal of an aircraft for closing a penetrable surface. The device is used to implement the confirmation method. The device includes: a division module, configured to divide the closed penetrable surface into a plurality of non-overlapping integral surfaces;

[0101] a calculation module, configured to calculate the time-domain sound pressure signals of each integral surface at the same observation point respectively;

[0102] a judgment module, configured to judge whether there is turbulence passing through each integral surface. If there is no turbulence passing through the integral surface, the obtained is the far-field noise signal. If there is turbulence passing through the integral surface, the obtained is a flow disturbance signal including non-sound sources;

[0103] a purification processing module, configured to perform purification processing on the flow disturbance signal to obtain a purified far-field noise signal of this integral surface;

[0104] a summation calculation module, configured to perform summation calculation on the far-field noise signals of each obtained integral surface and the purified far-field noise signal to obtain the far-field noise signal of the aircraft for the closed penetrable surface.

[0105] As an embodiment disclosed by the present invention, the present invention also provides an electronic device. The electronic device includes:

[0106] a memory, storing executable instructions;

[0107] a processor, and the processor runs the executable instructions in the memory to implement the method.

[0108] As an embodiment disclosed by the present invention, the present invention also provides a computer storage medium. A computer program is stored on the medium, and the computer program is executed by a processor to implement the method.

[0109] The terms used in the embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The singular forms "a", "the" and "said" used in the embodiments of the present invention and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise.

[0110] The foregoing description has shown and described several preferred embodiments of the present invention. As previously mentioned, it should be understood that the present invention is not limited to the forms disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be altered within the scope of the concept of the application described herein by the above teachings or the skills or knowledge in the relevant field. Any alterations and changes made by those skilled in the art without departing from the spirit and scope of the present invention shall fall within the protection scope of the appended claims of the present invention.

Claims

1. A method for confirming aircraft far-field noise signals for closed penetrable surfaces, characterized in that: The method comprises the following steps: Step 1: Divide the closed penetrable surface into multiple non-overlapping integral surfaces; Step 2: Calculate the time domain sound pressure signal of each integral surface at the same observation point; Step 3: Determine whether there is turbulence passing through each integral surface. If there is no turbulence passing through the integral surface, the far-field noise signal is obtained. If there is turbulence passing through the integral surface, the sound pressure signal is obtained. Step 4: purifying the sound pressure signal to obtain a purified far-field noise signal about the integral surface; Step 5: The far-field noise signals of each integral surface obtained in the third step and the purified far-field noise signals are summed up to obtain the aircraft far-field noise signal of the closed penetrable surface.

2. The method according to claim 1, characterized in that: In the second step, the calculation is performed based on the FW-H integral equation.

3. The method according to claim 1, characterized in that The integral surface comprises an upstream integral surface and a downstream integral surface, and turbulence exists on the downstream integral surface.

4. The method according to claim 1, characterized in that The fourth step specifically includes: S21. performing wavelet transform on the sound pressure signal to obtain a transformed sound pressure signal; S22. Compare the absolute value of the transformed wavelet coefficient with the set threshold value to obtain a new wavelet coefficient. S23. Performing an inverse wavelet transform on the transformed sound pressure signal based on the new wavelet coefficients to obtain a noise time domain signal; S24. Calculate the mutual correlation coefficient between the noise time domain signal and the far-field noise signal of the integral surface adjacent to the integral surface to which it belongs; S25. Iteratively calculate the cross-correlation coefficient until the cross-correlation coefficient reaches a maximum value. The noise time domain signal obtained at this time is used as the purified far-field noise signal.

5. The method according to claim 4, characterized in that The S22 specifically includes: if the absolute value of the wavelet coefficient is greater than the threshold, the wavelet coefficient is set to 0; if the absolute value of the wavelet coefficient is less than or equal to the set threshold, the wavelet coefficient remains unchanged, thereby obtaining a new wavelet coefficient.

6. The method according to claim 1, characterized in that The multiple non-overlapping integration surfaces include at least three non-overlapping integration surfaces.

7. The method according to claim 1, characterized in that The method also includes a sixth step: post-processing the aircraft far-field noise signal to obtain a spectrum signal and a directivity characteristic signal.

8. A device for confirming aircraft far-field noise signals of a closed penetrable surface, characterized in that: The device is used to implement the confirmation method according to any one of claims 1 to 7, and the device comprises: a division module, used to divide the closed penetrable surface into a plurality of integral surfaces that do not overlap; A calculation module, used for respectively calculating the time domain sound pressure signal of each integration surface at the same observation point; A judgment module is used to judge whether there is turbulence passing through each integral surface. If there is no turbulence passing through the integral surface, the far-field noise signal is obtained. If there is turbulence passing through the integral surface, the flow disturbance signal including non-sound sources is obtained. A purification processing module, used for purifying the flow disturbance signal to obtain a purified far-field noise signal about the integral surface; The summation calculation module is used to sum the far-field noise signals of each integral surface and the purified far-field noise signal to obtain the aircraft far-field noise signal of the closed penetrable surface.

9. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that: The medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

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