Measurement and inversion reconstruction method of helicopter rotor sound radiation sphere in acoustic wind tunnel

Abstract

The present application relates to a kind of acoustic wind tunnel inside helicopter rotor sound radiation sphere measurement and inversion reconstruction method, it is related to helicopter aerodynamic acoustics wind tunnel test technology and acoustic target characteristic technical field, include: in acoustic wind tunnel using hemispherical far-field noise measuring device measurement helicopter rotor radiated noise, obtain the noise signal of different azimuth of rotor and construct rotor sound radiation sphere model;Based on the sound propagation theory in flow field, construct the propagation model of the surface of sound radiation sphere model to microphone position, and based on the influence of background noise, establish the sound propagation equation of the surface of sound radiation sphere model to microphone in hemispherical far-field noise measuring device;Sound propagation equation is converted to solve least square problem, and the sound source distribution of the surface of sound radiation sphere model is obtained, and the noise of helicopter rotor far field arbitrary position is reconstructed.Can be applied to in acoustic wind tunnel, high background noise and other complex environments reconstruct helicopter rotor sound radiation sphere, carry out practical research and application.

Description

Technical Field

[0001] This invention relates to the fields of helicopter aeroacoustic wind tunnel testing technology and acoustic target characteristics technology, specifically to a method for measuring and reconstructing the acoustic radiation sphere of a helicopter rotor inside an acoustic wind tunnel. Background Technology

[0002] Helicopters utilize rotors for power and control, possessing unique capabilities such as vertical takeoff and landing, hovering, and low-altitude, low-speed flight. Their operational and speed ranges effectively fill the gaps in speed and space capabilities for modern air-to-ground equipment, leading to their widespread application in military and civilian fields such as disaster relief, equipment transport, public security, and reconnaissance patrols. However, vibration and noise are major challenges in the practical application of helicopters, significantly impacting their comfort, safety, and stealth capabilities. Helicopter noise primarily includes aerodynamic noise generated by the rotor and tail rotor, engine noise, and mechanical noise from the transmission mechanism. However, rotor-generated aerodynamic noise is the most significant component of helicopter noise due to its high intensity, low frequency, slow attenuation in the atmosphere, and longest propagation distance, thus having a crucial impact on helicopter performance. Rotor aerodynamic noise includes thickness noise, load noise, blade vortex interference (BVI) noise, high-speed pulse (HSI) noise, and broadband noise. These different types of rotor noise have different generation mechanisms, and their propagation mechanisms in the spatial flow field are extremely complex, necessitating the establishment of a helicopter rotor noise radiation sphere model to evaluate the helicopter rotor noise radiation characteristics. Acoustic wind tunnel testing is an important tool for studying the aerodynamic noise of helicopter rotors. Therefore, establishing a method for measuring and reconstructing the acoustic radiation sphere of helicopter rotors within an acoustic wind tunnel is of great significance for evaluating the noise characteristics of helicopters and guiding rotor noise reduction design. Summary of the Invention

[0003] The technical problem to be solved by this application is to provide a method for measuring and reconstructing the acoustic radiation sphere of a helicopter rotor in an acoustic wind tunnel. This method is applicable to reconstructing the acoustic radiation sphere of a helicopter rotor in complex environments such as acoustic wind tunnels and high background noise, and is suitable for practical research and application.

[0004] One embodiment provides a method for measuring and reconstructing the acoustic radiation sphere of a helicopter rotor in an acoustic wind tunnel, including:

[0005] The noise radiated by the helicopter rotor is measured in an acoustic wind tunnel using a hemispherical far-field noise measurement device to obtain noise signals from different directions of the rotor. The helicopter rotor is placed at the center of the hemispherical far-field noise measurement device, which is equipped with multiple microphones arranged at different directions of the helicopter rotor. The noise radiated by the helicopter rotor is measured through each microphone to obtain noise signals from different directions.

[0006] Construct a rotor acoustic radiation sphere model; the radius of the acoustic radiation sphere model is not less than the rotor radius and is less than the radius of the hemispherical far-field noise measurement device;

[0007] Based on the theory of sound propagation in a flow field, a propagation model from the surface of the sound radiation sphere model to the microphone position is constructed, and based on the influence of background noise, the sound propagation equation from the surface of the sound radiation sphere model to the microphone is established.

[0008] The sound propagation equation is transformed into a least squares problem, and the sound source distribution on the surface of the sound radiation sphere model is obtained by solving the least squares problem.

[0009] Based on the sound source distribution on the surface of the helicopter rotor acoustic radiation sphere, the noise at any position in the far field of the helicopter rotor is reconstructed.

[0010] In one embodiment, the radius of the hemispherical far-field noise measurement device is greater than or equal to four times the rotor radius, the microphone azimuth angle of the hemispherical far-field noise measurement device covers azimuth angle measurement from 60° to 360°, and the azimuth angle resolution of the microphone is less than or equal to 60°.

[0011] In one embodiment, the angle between the microphone and the plane below the rotor blade covers at least 0° to 70°, with an angular resolution of less than or equal to 10°.

[0012] In one embodiment, the construction of a propagation model from the surface of the sound radiation sphere model to the microphone position based on the theory of sound propagation in a flow field, and the establishment of a sound propagation equation from the surface of the sound radiation sphere model to the microphone based on the influence of background noise, includes:

[0013] Signal analysis is performed based on the acquired noise signals from different directions of the rotor, and filtering is performed to suppress the influence of background noise in order to obtain sound pressure signals with higher rotor noise signal-to-noise ratios from different directions.

[0014] Construct the sound transmission matrix from the sound source to the microphone on the surface of the acoustic radiation sphere model;

[0015] Based on the relationship between sound pressure signal, sound transmission matrix, background noise and the sound source intensity of each sound source, a sound propagation equation is constructed.

[0016] In one embodiment, constructing the sound propagation equation based on the relationship between the sound pressure signal, the sound transmission matrix, background noise, and the sound source intensity of each sound source includes:

[0017]

[0018]

[0019]

[0020] in, Indicates sound pressure level. The background noise is represented by m, which represents the index of the hemispherical far-field noise measurement device. 1 ≤ m ≤ M, and M represents the number of hemispherical far-field noise measurement devices. The value represents the intensity of the sound source, n represents the index of the sound source, 1≤n≤N, and N represents the number of sound sources; Let represent the sound transfer function from the nth sound source to the mth microphone. Represents pi (π). Let i represent the base of the natural numbers, and let i represent the imaginary number. This represents the sound propagation delay time from the nth sound source to the mth microphone; This represents the Mach number of the wind tunnel flow field. This indicates the spatial location of the nth sound source. This indicates the spatial position of the m-th microphone. Let c denote the norm of the vector, c denote the speed of sound, and f denote the analysis frequency of the noise.

[0021] In one embodiment, the step of converting the sound propagation equation into a least squares problem and solving the least squares problem includes converting the sound propagation equation into a least squares problem and solving the least squares problem using Tikhonov regularization theory.

[0022] In one embodiment, the step of converting the sound propagation equation into a least-squares problem and solving the least-squares problem using Tikhonov regularization theory includes:

[0023]

[0024] in, Let p represent the sound pressure matrix composed of all sound pressure levels, G represent the sound transmission matrix, and a represent the sound source intensity matrix composed of all sound source intensities. Represents the regularization parameter. Let L denote the 2-norm and L denote the regularization matrix.

[0025] In one embodiment, regularization parameters are defined. for ( eigenvalues), where 0.1%≤ ≤10%, This indicates taking the maximum value. This indicates the conjugate transpose.

[0026] In one embodiment, reconstructing the noise at any position in the far field of the helicopter rotor based on the sound source distribution on the surface of the helicopter rotor's acoustic radiation sphere includes:

[0027] Based on the obtained sound source intensity, the sound pressure at each measuring point is calculated, and the sound field distribution is reconstructed.

[0028] In one embodiment, calculating the sound pressure at each measuring point based on the acquired sound source intensity and reconstructing the sound field distribution includes: based on the acquired sound source intensity, according to Calculate the sound pressure at any position in the far field of the helicopter rotor and reconstruct the sound field distribution of the helicopter rotor; where, Let k represent the sound pressure at any point k in the far field of the reconstructed helicopter rotor. This represents the position coordinates of any point k in the far field of the helicopter rotor.

[0029] The beneficial effects of this invention are:

[0030] Because it is based on the theory of sound propagation in the flow field, it constructs a propagation model from the surface of the acoustic radiation sphere model to the microphone position, and establishes the sound propagation equation from the surface of the acoustic radiation sphere model to the microphone in the hemispherical far-field noise measurement device based on the influence of background noise. Thus, it can start from the actual environmental conditions of the acoustic wind tunnel, comprehensively consider the influence of the acoustic wind tunnel flow field and background noise on the measurement and inversion of the acoustic radiation sphere of the helicopter rotor, and effectively evaluate the noise characteristics and far-field radiation characteristics of the helicopter rotor. Furthermore, because it transforms the sound propagation equation into solving a least squares problem, and solves the least squares problem to obtain the sound source distribution on the surface of the acoustic radiation sphere model, it can reconstruct the acoustic radiation sphere of the helicopter rotor in complex environments such as acoustic wind tunnels and high background noise, and invert the noise at any position in the far field of the helicopter rotor. This can support research on helicopter acoustic stealth, low-noise flight trajectory optimization, and acoustic detection technology in practical applications. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the measurement and inversion reconstruction method of the acoustic radiation sphere of a helicopter rotor in an acoustic wind tunnel according to an embodiment of this application.

[0032] Figure 2 This is a schematic diagram of a hemispherical far-field noise measurement device according to an embodiment of this application;

[0033] Figure 3 This application Figure 1 A schematic diagram of the method flow of one embodiment of step S30;

[0034] Figure 4 This is a schematic diagram of the typical helicopter rotor acoustic radiation sphere inversion result according to an embodiment of this application;

[0035] Figure 5 This is a schematic diagram comparing the sound field reconstruction and measurement results of a helicopter rotor acoustic radiation sphere at a measuring point location, according to an embodiment of this application.

[0036] In the diagram: 01, helicopter rotor; 02, sound radiation sphere; 03, equivalent sound source; 04, microphone. Detailed Implementation

[0037] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0038] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0039] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0040] To facilitate the explanation of the inventive concept of this application, the inversion technology of the acoustic radiation sphere of the helicopter rotor is briefly described below.

[0041] Currently, there are two main methods for inverting the acoustic radiation sphere of helicopter rotors. The first method involves measuring helicopter rotor noise from multiple angles and then reconstructing the rotor acoustic radiation sphere using bilinear interpolation. The second method is based on the rotor acoustic radiation sphere inversion method using an equivalent sound source.

[0042] However, the applicant found in their research that the first method can only assess the directivity of helicopter rotor aerodynamic noise, but cannot accurately describe the radiation characteristics of helicopter rotor aerodynamic noise, nor can it reconstruct the far-field sound field of the helicopter rotor. As for the second method, it does not consider the influence of the acoustic wind tunnel flow field on sound propagation, nor the influence of background noise on acoustic measurements. The propagation equation and the solution of the equivalent sound source are difficult to meet practical needs, and it is not suitable for reconstructing the acoustic radiation sphere of the helicopter rotor in complex environments such as acoustic wind tunnels and high background noise, making it difficult to conduct practical research and applications.

[0043] In view of this, this application provides a method for measuring and reconstructing the acoustic radiation sphere of a helicopter rotor in an acoustic wind tunnel. Based on the theory of sound propagation in a flow field, a propagation model is constructed from the surface of the acoustic radiation sphere model to the microphone position. Furthermore, considering the influence of background noise, an acoustic propagation equation is established from the surface of the acoustic radiation sphere model to the microphone in the hemispherical far-field noise measurement device. This allows for a comprehensive consideration of the influence of the acoustic wind tunnel flow field and background noise on the measurement and inversion of the helicopter rotor acoustic radiation sphere, effectively evaluating the helicopter rotor noise characteristics and its far-field radiation characteristics. Moreover, since the acoustic propagation equation is transformed into solving a least-squares problem, and this least-squares problem is solved to obtain the sound source distribution on the surface of the acoustic radiation sphere model, and the noise at any far-field position of the helicopter rotor is inverted, the acoustic radiation sphere of the helicopter rotor can be reconstructed in complex environments such as acoustic wind tunnels and high background noise environments. This supports practical research on helicopter acoustic stealth, low-noise flight trajectory optimization, and acoustic detection technology.

[0044] This application provides a method for measuring and reconstructing the acoustic radiation sphere of a helicopter rotor in an acoustic wind tunnel. Please refer to [the relevant documentation]. Figure 1 ,include:

[0045] Step S10: Measure the noise radiated by the helicopter rotor in the acoustic wind tunnel using a hemispherical far-field noise measurement device to obtain noise signals from different directions of the rotor.

[0046] Please refer to Figure 2 The helicopter rotor 01 is placed at the center of a hemispherical far-field noise measurement device. Multiple microphones 04 are installed on the hemispherical far-field noise measurement device. These microphones 04 are arranged at different positions of the helicopter rotor 01. The noise radiated by the helicopter rotor 01 is measured by each microphone 04 to obtain noise signals from different positions.

[0047] For better simulation results, please refer to Figure 2The method includes the arrangement of microphones in a hemispherical far-field noise measurement device. In one embodiment, the radius of the hemispherical far-field noise measurement device is greater than or equal to four times the rotor radius. The microphone azimuth angle of the hemispherical far-field noise measurement device covers azimuth angle measurements from 60° to 360°, and the azimuth angle resolution of the microphone is less than or equal to 60°. In a specific embodiment, the azimuth angle of the microphone is 30°, 90°, 150°, 210°, 270°, and 330°.

[0048] In one embodiment, the angle (pitch angle) between the microphone 04 and the plane below the rotor blade covers at least 0° to 70°, with an angular resolution less than or equal to 10°. In a specific embodiment, the angles between the microphone 04 and the plane below the rotor blade are 0°, 10°, 20°, 30°, 40°, 50°, 60°, and 70°, respectively.

[0049] Step S20: Construct a rotor acoustic radiation sphere model. The radius of the acoustic radiation sphere model is not less than the rotor radius, and is less than the radius of the hemispherical far-field noise measurement device.

[0050] Please refer to Figure 2 In this embodiment of the application, it is assumed that there are N equivalent sound sources O3 on the surface of the acoustic radiation sphere.

[0051] Step S30: Based on the theory of sound propagation in the flow field, construct a propagation model from the surface of the sound radiation sphere model to the microphone position, and based on the influence of background noise, establish the sound propagation equation from the surface of the sound radiation sphere model to the microphone.

[0052] In one embodiment, please refer to Figure 3 Step S30 may include:

[0053] Step S301: Based on the acquired noise signals from different directions of the rotor, perform signal analysis and filtering to suppress the influence of background noise, so as to obtain sound pressure signals with higher rotor noise signal-to-noise ratios from different directions.

[0054] Those skilled in the art will understand that analyzing noise signals and improving the signal-to-noise ratio of helicopter rotor noise can be achieved using existing techniques (such as Fourier transform and bandpass filtering), which will not be elaborated here.

[0055] In this embodiment, filtering is performed to suppress the influence of background noise in order to obtain sound pressure signals with a rotor noise signal-to-noise ratio of more than 3dB in different directions.

[0056] Step S302: Construct the sound transmission matrix from the sound source on the surface of the sound radiation sphere model to the microphone.

[0057] The acoustic transfer matrix G can be represented as:

[0058]

[0059] in, This represents the sound transfer function from the nth sound source to the mth microphone.

[0060] Step S303: Based on the relationship between the sound pressure signal, the sound transmission matrix, the background noise, and the sound source intensity of each sound source, construct the sound propagation equation.

[0061] Considering the influence of the acoustic wind tunnel flow field, assume the velocity is... In a uniform flow field, there exists a spatial location where Let n be the index of the equivalent sound source, 1≤n≤N. Then the sound field radiated by the equivalent sound source satisfies the following equation:

[0062]

[0063] in, is the sound pressure signal at a certain location in the sound field; c is the speed of sound; The sound signal radiated by the equivalent sound source at a certain time t; It is the Dirichlet function; Here, m represents the spatial location of the microphone, where 1 ≤ m ≤ M, and M represents the number of microphones. Indicates partial derivative; For the Laplace operator, x, y, and z represent the x, y, and z axes in space, respectively; For differential operators, According to the Green's function solution of the free-space wave equation, the solution to the above equation is:

[0064]

[0065] in, This represents the Mach number of the wind tunnel flow field. ; Represents pi (π). The norm of a vector. This represents the sound propagation delay time from the nth sound source to the mth microphone.

[0066] Then we have:

[0067]

[0068] The frequency domain solution can be expressed as:

[0069]

[0070]

[0071] in, Indicates the intensity of the sound source. represents the base of the natural number, i represents the imaginary number, and f represents the analysis frequency of the noise.

[0072] In the acoustic wind tunnel test of helicopter rotor aerodynamic noise characteristics, when a hemispherical far-field noise measurement device is used to measure and invert the rotor acoustic radiation sphere, the signal processing of the microphone is affected by background noise interference such as aerodynamic noise of the support device, aerodynamic noise of the wind tunnel nozzle and collector, and electrical noise. In addition to the aerodynamic noise radiated by the helicopter rotor, the aerodynamic noise radiated by the helicopter rotor is also included in the background noise of the wind tunnel.

[0073] Based on the above analysis, the sound propagation equation between the microphone array and the virtual equivalent sound source on the radiating sphere can be expressed as:

[0074]

[0075]

[0076]

[0077] in, Indicates sound pressure level. The background noise is represented by m, where m represents the microphone index, 1≤m≤M, and M represents the number of microphones. The value represents the intensity of the sound source, n represents the index of the sound source, 1≤n≤N, and N represents the number of sound sources; Let represent the sound transfer function from the nth sound source to the mth microphone. Represents pi (π). Let i represent the base of the natural numbers, and let i represent the imaginary number. This represents the sound propagation delay time from the nth sound source to the mth microphone; This represents the Mach number of the wind tunnel flow field. This indicates the spatial location of the nth sound source. This indicates the spatial position of the m-th microphone. Let c denote the norm of the vector, c denote the speed of sound, and f denote the analysis frequency of the noise.

[0078] Step S40: The sound propagation equation is converted into a least squares problem, and the least squares problem is solved to obtain the sound source distribution on the surface of the sound radiation sphere model.

[0079] Based on the sound propagation equation between the microphone array and the virtual equivalent sound source on the radiating sphere, the intensity matrix a of the sound source can be calculated from the sound pressure matrix p and the sound transmission matrix G measured by the microphone array. In actual measurements, the number of microphones M is often not equal to the number of virtual equivalent sound sources N. Therefore, the sound propagation equation is an underdetermined or overdetermined equation, and solving for the sound source intensity is a typical ill-posed problem. The sound source intensity a cannot be obtained by directly inverting the sound transmission matrix G. Therefore, in this application, the sound propagation equation is transformed into solving a least-squares problem, and solving this least-squares problem yields the sound source distribution on the surface of the sound-radiating sphere model.

[0080] In one embodiment of this application, the least squares problem is solved using Tikhonov regularization theory. This transforms the sound propagation equation into a least squares problem, which can be expressed as follows:

[0081]

[0082] in, Let p represent the sound pressure matrix composed of all sound pressure levels, G represent the sound transmission matrix, and a represent the sound source intensity matrix composed of all sound source intensities. Represents the regularization parameter. Let L denote the 2-norm and L denote the regularization matrix.

[0083] The solution to the above equation can be obtained as follows:

[0084]

[0085] in, This represents the adjustment scaling factor, which compensates for errors caused by over-regularization; This indicates the conjugate transpose. Indicates transpose. Let represent the intensity of the sound source being solved. Then we have:

[0086]

[0087] in, For intermediate parameters, .

[0088] In classical Tikhonov regularization, L is a unit diagonal matrix in the discrete smoothing norm. =1. Then the generalized solution to the inverse problem using Tikhonov regularization is:

[0089] .

[0090] To obtain the optimal solutions for the residual norm and solution norm, the main difficulty in obtaining the Tikhonov regularization matrix lies in selecting the regularization parameter factor. The regularization parameter factor can be any value; in this embodiment, a regularization parameter is defined. for ( eigenvalues), where 0.1%≤ ≤10%, This indicates taking the maximum value.

[0091] Step S50: Based on the sound source distribution on the surface of the helicopter rotor acoustic radiation sphere, reconstruct the noise at any position in the far field of the helicopter rotor.

[0092] In one embodiment, step S50 includes: based on the acquired sound source intensity, according to Calculate the sound pressure at any position in the far field of the helicopter rotor and reconstruct the sound field distribution of the helicopter rotor; where, Let k represent the sound pressure at any point k in the far field of the reconstructed helicopter rotor. This represents the position coordinates of any point k in the far field of the helicopter rotor.

[0093] Please refer to Figure 4 (The units of the horizontal and vertical axes are m (meters)). The reconstruction results of the acoustic radiation sphere of a typical helicopter rotor model in forward flight state are given. The contour lines in the figure represent the distribution of sound sources. As can be seen from the figure, the noise sources reconstructed on the surface of the radiation sphere are mainly distributed near the rotor plane, which is consistent with the theoretical analysis results.

[0094] Please refer to Figure 5 The paper presents a comparison between the sound field reconstruction and measurement results of the sound radiation at the measurement point location based on the inversion of this invention. As shown in the figure, the sound field reconstruction error is less than 1.06 dB, and the reconstruction accuracy is high, which meets the research requirements of helicopter rotor radiation characteristics.

[0095] In this embodiment, since the propagation model from the surface of the acoustic radiation sphere model to the microphone position is constructed based on the theory of sound propagation in the flow field, and the sound propagation equation from the surface of the acoustic radiation sphere model to the microphone in the hemispherical far-field noise measurement device is established based on the influence of background noise, it is possible to start from the actual environmental conditions of the acoustic wind tunnel, comprehensively consider the influence of the acoustic wind tunnel flow field and background noise on the measurement and inversion of the acoustic radiation sphere of the helicopter rotor, and effectively evaluate the noise characteristics and far-field radiation characteristics of the helicopter rotor. Furthermore, since the sound propagation equation is transformed into solving a least squares problem, and the sound source distribution on the surface of the acoustic radiation sphere model is obtained by solving this least squares problem, the acoustic radiation sphere of the helicopter rotor can be reconstructed in complex environments such as acoustic wind tunnels and high background noise, thereby supporting the research on helicopter acoustic stealth, low-noise flight trajectory optimization, and acoustic detection technology in practice.

[0096] One embodiment of this application provides a computer-readable storage medium storing a program, the stored program including methods that can be loaded by a processor and processed in any of the above embodiments.

[0097] Those skilled in the art will understand that all or part of the functions of the various methods in the above embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, which may include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to achieve the above functions. For example, the program can be stored in the memory of a device, and when the program in the memory is executed by the processor, all or part of the above functions can be achieved. In addition, when all or part of the functions in the above embodiments are implemented by computer programs, the program can also be stored in a server, another computer, disk, optical disk, flash drive, or external hard drive, etc., and can be downloaded or copied to the memory of a local device, or the system of the local device can be updated. When the program in the memory is executed by the processor, all or part of the functions in the above embodiments can be achieved.

[0098] The above examples illustrate the present invention only to aid in understanding it and are not intended to limit the scope of the invention. Those skilled in the art can make various simple deductions, modifications, or substitutions based on the principles of this invention.

Claims

1. A method of measuring and inverse reconstructing a helicopter rotor sound radiation sphere in an acoustic wind tunnel, characterized in that, The application relates to a method for measuring noise radiated by a helicopter rotor in an acoustic wind tunnel. The helicopter rotor is arranged at the center of a hemispherical far-field noise measuring device, a plurality of microphones are arranged on the hemispherical far-field noise measuring device at different azimuths of the helicopter rotor, the noise radiated by the helicopter rotor is measured through the microphones to obtain noise signals at different azimuths. A rotor sound radiation sphere model is constructed, the radius of the sound radiation sphere model is not less than the radius of the rotor and is less than the radius of the hemispherical far-field noise measuring device. Based on the sound propagation theory in the flow field, a propagation model from the surface of the sound radiation sphere model to the microphone position is constructed, and based on the influence of background noise, a sound propagation equation from the surface of the sound radiation sphere model to the microphone is established, including: Based on the obtained noise signals at different azimuths of the rotor, signal analysis is performed, and filtering is performed to suppress the influence of background noise, so that sound pressure signals with higher noise signal-to-noise ratios at different azimuths are obtained. A sound transfer matrix from the sound source on the surface of the sound radiation sphere model to the microphone is constructed. Based on the sound pressure signal, the sound transfer matrix and the relationship between the background noise and the sound source intensity of each sound source, a sound propagation equation is constructed, including: The sound propagation equation is converted into a least square problem, and the least square problem is solved to obtain the sound source distribution on the surface of the sound radiation sphere model. wherein, represents sound pressure, represents background noise, m represents an index of a microphone, 1≤m≤M, and M represents a number of microphones; represents sound source intensity, n represents an index of a sound source, 1≤n≤N, and N represents a number of sound sources; represents a sound transfer function from the nth sound source to the mth microphone, represents a circle constant, represents a natural number base, i represents an imaginary number, represents a sound propagation delay time from the nth sound source to the mth microphone; represents a Mach number of a flow field of a wind tunnel, represents a spatial position of the nth sound source, represents a spatial position of the mth microphone, represents a norm of a vector, c represents a sound velocity, and f represents an analysis frequency of noise; According to the sound source distribution on the surface of the sound radiation sphere model of the helicopter rotor, the noise at any position in the far field of the helicopter rotor is reconstructed. The radius of the hemispherical far-field noise measuring device is greater than or equal to 4 times the radius of the rotor, the azimuth angle of the microphone of the hemispherical far-field noise measuring device covers 60 to 360 degrees, and the azimuth angle resolution of the microphone is less than or equal to 60 degrees.

2. The method of claim 1, wherein, The included angle between the microphone and the rotor blade plane is at least 0 to 70 degrees, and the angle resolution is less than or equal to 10 degrees.

3. The method of claim 1, wherein, The sound propagation equation is converted into a least square problem, and the least square problem is solved by using the Tikhonov regularization theory.

4. The method of claim 1, wherein, The sound propagation equation is converted into a least square problem, and the least square problem is solved by using the Tikhonov regularization theory.

5. The method of claim 4, wherein, According to the sound source distribution on the surface of the sound radiation sphere model of the helicopter rotor, the noise at any position in the far field of the helicopter rotor is reconstructed. wherein, represents a minimization solution, p represents a sound pressure matrix of each sound pressure component, G represents a sound transfer matrix, a represents a sound source intensity matrix of each sound source intensity component, represents a regularization parameter, represents a 2-norm, L represents a regularization matrix.

6. The method of claim 5, wherein, Defining the regularization parameter For where 0.1%≤ ≤10%, denotes taking the maximum value, denotes the conjugate transpose.

7. The method of claim 6, wherein, Based on the obtained sound source intensity, the sound pressure at each measuring point position is calculated, and the sound field distribution is reconstructed. ​ 8. The method of claim 7, wherein, The sound pressure at each measuring point position is calculated based on the acquired sound source intensity, and the sound field distribution is reconstructed, including: based on the acquired sound source intensity, according to The sound pressure at any position of the far field of the helicopter rotor is calculated, and the sound field distribution of the helicopter rotor is reconstructed; wherein, represents the sound pressure of the k point at any point of the reconstructed far field of the helicopter rotor, represents the position coordinates of the k point at any point of the far field of the helicopter rotor.

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