Supersonic aircraft noise audible visualization method and device

Abstract

The invention discloses a supersonic aircraft noise audible visualization method and device, and relates to the field of aviation acoustics. Firstly, supersonic aircraft engine parameters are obtained; and calculating noise data generated by different parts of the supersonic aircraft engine through a data prediction algorithm. Secondly, carrying out superposition and dynamic correction on noise data of different parts; and constructing a three-dimensional model of the aircraft and the flight scene. And finally, superposing the noise test virtual scene with a real scene, testing the supersonic aircraft engine, and displaying a test result. According to the method, on the basis of the mixed reality technology, an approval person and a designer are allowed to experience personally and evaluate the noise influence in a virtual environment, so that whether the design meets regulatory requirements or not is more effectively verified, abstract noise data are converted into audible and visual immersive experience, complex noise prediction data are displayed in a real-time and three-dimensional mode, and the method is more practical. And a designer can intuitively find the noise problem.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of aeroacoustics, and more particularly, to a supersonic aircraft noise audible visualization method and device. BACKGROUND

[0002] With the rapid development of the civil aviation field, supersonic aircraft has an important influence on people's daily life and economic life. By speeding up to reduce flight time, the development of the civil aviation field or other fields is more convenient and fast. Supersonic aircraft must adhere to the safety baseline and green bottom while meeting the needs of people's fast travel.

[0003] The main problem faced by supersonic aircraft certification is the noise problem of the community near the airport. Supersonic aircraft noise is mainly caused by high jet noise during takeoff. Related researchers study how to more effectively control aircraft engine noise from noise sources, propagation and audience, etc., to the extent that it can be accepted, and to reduce the impact on people's life, study and work.

[0004] At present, the noise prediction and analysis means lack of intuitiveness, and the existing approval process relies on traditional ground measurement and numerical simulation, which is difficult to reproduce the noise propagation law under complex flight scenes. At the same time, the output results are mostly in the form of numerical tables and two-dimensional charts. This abstract expression form makes the noise data and the actual auditory perception disjointed, and the approval personnel, design engineers and the public cannot intuitively understand the spatial distribution characteristics and actual impact of the noise, which brings great inconvenience to airworthiness compliance verification, noise reduction scheme optimization and community communication. SUMMARY

[0005] Therefore, the present application provides a supersonic aircraft noise audible visualization method and device to solve the problem that the existing supersonic aircraft noise analysis method cannot intuitively understand the spatial distribution characteristics and actual impact of the noise.

[0006] To achieve the above purpose, the present scheme is as follows: A supersonic aircraft noise audible visualization method, comprising: obtaining supersonic aircraft engine parameters; calculating noise data generated by different components of the supersonic aircraft engine through a data prediction algorithm; superimposing and dynamically correcting the noise data of different components to obtain total engine noise; constructing an aircraft and flight scene three-dimensional model to obtain a noise test virtual scene; superimposing the noise test virtual scene and the real scene, testing the supersonic aircraft engine, and displaying the test results.

[0007] An ultrasonic aircraft noise audible visualization device comprises: A parameter acquisition unit acquires ultrasonic aircraft engine parameters, flight trajectories and aerodynamic characteristics; A data prediction unit calculates noise data generated by different components of the ultrasonic aircraft engine through a data prediction algorithm; A noise processing unit superimposes and dynamically corrects the noise data of different components to obtain total engine noise; A virtual scene construction unit constructs a three-dimensional model of the aircraft and flight scene to obtain a noise test virtual scene; A virtual-real interaction unit superimposes the noise test virtual scene and the real scene to test the ultrasonic aircraft engine, and displays the test results.

[0008] According to the specific embodiments provided by the present application, the following technical effects are disclosed: The ultrasonic aircraft noise audible visualization method provided by the present application acquires ultrasonic aircraft engine parameters, flight trajectories and aerodynamic characteristics; calculates noise data generated by different components of the ultrasonic aircraft engine through a data prediction algorithm; superimposes and dynamically corrects the noise data of different components to obtain total engine noise; constructs a three-dimensional model of the aircraft and flight scene to obtain a noise test virtual scene; superimposes the noise test virtual scene and the real scene to test the ultrasonic aircraft engine, and displays the test results. Based on the mixed reality technology, the present application allows the approval personnel and designers to "experience" and evaluate the noise impact in the virtual environment, so as to more effectively verify whether the design meets the regulatory requirements, convert the abstract noise data into audible and visual immersive experience, and present the complex noise prediction data in real time and stereoscopically, so that the designers can intuitively find noise problems. BRIEF DESCRIPTION OF DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiment or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present application, and those skilled in the art can obtain other drawings according to the provided drawings without creative labor.

[0010] Figure 1 The ultrasonic aircraft noise audible visualization method flowchart provided by the embodiment of the present application; Figure 2 The noise airworthiness certification point schematic diagram provided by the embodiment of the present application; Figure 3 The prediction PNLT of the standard take-off procedure at the lateral certification point provided by the embodiment of the present application; Figure 4Predicted PNLT for the standard takeoff procedure provided in this embodiment of the invention in the flight over certification point; Figure 5 Predictive PNLT at the lateral certification point for the advanced takeoff procedure provided in this embodiment of the invention; Figure 6 Predictive PNLT of the advanced takeoff procedure provided in this embodiment of the invention for overflight certification points; Figure 7 This is a schematic diagram of a UI panel in a flight path scenario provided by an embodiment of the present invention; Figure 8 The jet noise at the measurement point during the standard takeoff procedure provided in this embodiment of the invention; Figure 9 This refers to the wideband noise at the fan outlet at the measurement point during the standard takeoff procedure provided in this embodiment of the invention. Figure 10 The total noise at the lateral measurement point under the advanced takeoff procedure provided in this embodiment of the invention; Figure 11 This is a schematic diagram of the structure of the supersonic aircraft noise audible visualization device provided in an embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] First, combined Figure 1 This invention provides a method for audible visualization of supersonic aircraft noise, as illustrated in the embodiments of the present invention. Figure 1 As shown, the method includes: Step S01: Obtain the parameters of the supersonic aircraft engine.

[0013] Specifically, the parameters of the supersonic engine are obtained based on the design documents.

[0014] Step S02: Calculate the noise data generated by different components of the supersonic aircraft engine using a data prediction algorithm.

[0015] Specifically, by analyzing engine parameters, flight trajectory and aerodynamic characteristics, considering flight test environment, Doppler effect and acoustic effects such as propagation, and combining propagation fuselage aeroacoustic prediction and fuselage interaction effect, the noise spectrum, sound pressure level and directivity angle generated by supersonic aircraft under different takeoff procedures are calculated.

[0016] Step S03: The noise data of different components are superimposed and dynamically corrected to obtain the total engine noise.

[0017] Specifically, by superimposing the dimensionless mean square sound pressures obtained from the fan, combustion chamber, turbine, and jet noise prediction models, the far-field dimensionless mean square sound pressures of the entire engine under standard and advanced takeoff procedures can be obtained, which is the total engine noise.

[0018] A comparison of standard takeoff procedures and advanced takeoff procedures, such as... Figure 2 As shown, three certification points are considered: the lateral approach, the flyby approach, and the post-rotation (PR) approach. The PR approach, located 8,000 feet after brake release (shortly after the PR) and directly below the flight path, can exhibit significant differences between the two procedures, as it is closer to the brake release point than the lateral approach and flyby approach. Table 1 lists the Effective Perceived Noise Level (EPNL) values ​​predicted for the two takeoff procedures at the three measurement points using the Data Prediction Algorithm (ANOPP2) and the Auralization (NAF) method, respectively.

[0019] Table 1

[0020] like Figure 3 and Figure 4 The figures show the predicted single-tone corrected perceived noise level (PNLT) and polar angle at the 4-foot observation point for both lateral and overflight certification points under standard takeoff procedures. At both points, jet noise is dominant; core engine noise is approximately 16 dB lower than total noise at the lateral point and approximately 13 dB lower at the overflight point. Figure 5 and Figure 6 The figures show the predicted single-tone corrected perceived noise level (PNLT) and polar angle at the 4-foot observation point for the advanced takeoff procedure at the lateral and overflight certification points, respectively. Compared to the standard takeoff procedure, the advanced takeoff procedure reduces the maximum PNLT by 1.8 dB at the lateral point and by 0.5 dB at the overflight point.

[0021] Noise reduction in standard takeoff procedures can be described using the Effective Perceived Noise Level (EPNL) metric, but this time-integrated metric may not effectively convey the noise impact to non-acoustic personnel. Therefore, predicted values ​​are converted into audible sounds. Using source data generated by a data prediction algorithm as a starting point, sound is synthesized and propagated to ground observers. The broadband component is synthesized by filtering random noise, and the monotone component is synthesized by assigning a random phase to each component.

[0022] Step S04: Construct a 3D model of the aircraft and flight scenario to obtain a virtual scenario for noise testing.

[0023] Specifically, 3ds Max and SolidWorks were used to build 3D models of aircraft and flight scenes, and Unity 3D was used to build a virtual scene for noise testing and develop an interactive interface.

[0024] Step S05: Overlay the virtual noise test scene with the real scene to test the supersonic aircraft engine and display the test results.

[0025] Specifically, leveraging the characteristics of HoloLens 2, a virtual model is stably placed into the real environment, and natural interaction is achieved through HoloLens 2 gesture recognition, voice commands, and visual tracking. By setting gestures, touching buttons, and moving the viewpoint, the noise of supersonic aircraft is made audible and visual. The real environment is replicated as a virtual scene to simulate the process of measuring aircraft reference noise, realizing a virtual-real interactive mode. Real-time data streams from the distributed acoustic sensor arrays of different components of the supersonic aircraft engine are superimposed onto the real space in the form of a 3D heatmap. The UI panel in the flight path scene is as follows: Figure 7 As shown. Figure 8 The jet noise at the measurement point during standard takeoff procedures; Figure 9 The fan exhaust broadband noise at the measurement point during standard takeoff procedure; Figure 10 The total noise at the lateral measurement point under advanced takeoff procedures.

[0026] Next, this embodiment of the invention will describe the process of step S02, which involves calculating the noise data generated by different components of a supersonic aircraft engine using a data prediction algorithm. The process is as follows: Engine noise sources include jet noise, core engine noise, broadband noise from fan inlet and outlet, and single-tone noise from rotor-stator interactions. Fuselage noise sources include main and nose landing gear, leading-edge slats, trailing-edge flaps, and trailing-edge noise from the wings and horizontal stabilizer. Aircraft noise is primarily dominated by jet noise. Noise propagation effects include spherical diffusion, Doppler shift and convective amplification, atmospheric absorption, and reflection based on grassy ground cover. The results are evaluated and compared under simulated propagation conditions.

[0027] (1) The noise spectrum, sound pressure level, and directivity angle of the combustion chamber were calculated using the SAE model. The SAE model is as follows: (1) in, This represents the far-field mean square sound pressure level of the combustion chamber in the 1 / 3 octave band. It is the total sound power. It uses the engine reference area. The dimensionless combustion chamber inlet area. This is the aircraft's Mach number, which takes into account the effects of the aircraft's forward flight. It is the polarization pointing angle. It is a directional function, and its data is listed in Table 2.

[0028] Table 2 Combustion Chamber Directivity Levels, 10

[0029]

[0030] in, f It is the center frequency of the 1 / 3 octave band of the combustion chamber, S( f ) is the spectrum function, which is The function, whose data is listed in Table II. Peak frequency Given by the following formula: (2) Table 3 Combustion chamber spectrum levels, 10

[0031]

[0032]

[0033] It is a dimensionless distance from the sound source to the observer, defined as: (3) in, It is the distance from the sound source to the observer. It is the engine reference area.

[0034] Sound power Related to the inlet and outlet conditions of the combustion chamber, defined as: (4) in, It is the mass flow rate at the combustion chamber inlet. It is the dimensionless total temperature at the combustion chamber inlet. It is the dimensionless total temperature at the combustion chamber outlet. The total pressure at the combustion chamber inlet. H It is the turbine transmission gain factor. This is the turbine transmission loss function. Turbine transmission loss can be calculated using one of the following empirical functions: (5) Among them, the first function Based on the temperature drop at the low-pressure turbine design point Calculate turbine transmission losses. The second function. Turbine transmission losses are calculated based on the ratio of the characteristic impedances of all turbine stages.

[0035] ζ is the characteristic impedance ratio, defined as the product of the local density and the speed of sound at the turbine exit divided by the product of the local density and the speed of sound at the combustion chamber exit. (6) in, , These represent the local density and sound velocity at the turbine outlet, respectively. , These represent the local density and sound velocity at the combustion chamber outlet, respectively.

[0036] Total noise is the mean square pressure multiplied by the number of engines, Ne. The sound pressure level (SPL) is defined as follows: (7) in, For environmental density, For ambient sound speed, For reference pressure, 2×10 -5 Pa.

[0037] Power level is defined as: (8) in, For engine reference area, This is the reference power.

[0038] (2) The noise spectrum, sound pressure level and directivity angle of the turbine are calculated using the Peart & Dunn model.

[0039] The Peart & Dunn model is: (9) (10) Calculation of turbine broadband noise: (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) in, For the spectrum function, For quality flow, This refers to the turbine outlet relative to the blade tip Mach number. For environmental density, For ambient sound speed, This represents the tip Mach number of the last stage blades in the turbine. The turbine outlet axial flow Mach number. This refers to the high-pressure turbine speed. The speed of sound at the turbine outlet. The total temperature at the turbine outlet. The dimensionless turbine outlet static temperature. Here, R is the specific heat ratio at the turbine outlet, and R is the gas constant for dry air. For turbine outlet static temperature, For frequency parameters, This is the center frequency of the turbine's 1 / 3 octave band. The basic blade passing frequency, B For the number of leaves, Let be the turbine rotor diameter. The turbine broadband noise is calculated. Temperature conversion constant: (twenty one) (twenty two) (twenty three) (twenty four) in, Let be the source intensity constant. For the spectrum function, This represents the relative tip velocity of the last-stage turbine rotor.

[0040] The total turbine noise mean square sound pressure level is obtained by adding the obtained 1 / 3 octave bandwidth and the mean square sound pressure level of each tone. For each frequency value, polar pointing angle, and azimuth pointing angle, the total turbine noise mean square sound pressure level can be obtained: (25) (26).

[0041] in, The mean square sound pressure level of the octave band is... The mean square sound pressure level of a single tone. For reference pressure.

[0042] (3) Calculate the noise spectrum, sound pressure level and directivity angle of the Heidmann fan.

[0043] The Heidmann fan noise prediction model is as follows: (27) in, Design frequency for the fan, The rotor-stator distance.

[0044] The formula for calculating the sound pressure level of the fan inlet broadband noise at 1 / 3 octave band under standard atmospheric sea level conditions is: (28) in, For the fan discrete single-tone frequency, It is the polarization pointing angle. This is the dimensionless total fan temperature rise calculated using ambient temperature. It is a dimensionless fan reference temperature rise. Is using Dimensionless mass flow rate It is environmental density. It is the speed of ambient sound. It is a dimensionless reference mass flow rate. Let be the intensity function of the first sound source. It is the design point fan rotor relative to blade tip Mach number. It is the Mach number of the fan rotor relative to the blade tip. This is the direction correction function. For the spectrum function, It is a frequency parameter.

[0045] First sound source intensity function : (29) Spectrum function : (30) in, This represents the geometric mean frequency deviation.

[0046] Direction correction function As shown in Table 4: Table 4

[0047] Calculate the discrete single-tone noise at the fan inlet: (31) in, n It is a single-tone harmonic number. The incoming flow distortion elimination factors are shown in Table 5: Table 5

[0048] Discrete single-tone noise in a fan originates from the passing frequency of the basic blades and its harmonics; that is, the sound pressure level of the discrete single-tone noise is at the passing frequency of the basic blades. multiples of Output: (32) In order to characterize discrete single-tone noise over a 1 / 3 octave band, this frequency should be within a 1 / 3 octave band bandwidth and satisfy the following: .

[0049] The upper and lower bounds of the frequency for a 1 / 3 octave band are as follows: (33) At this time, the intensity function of the first sound source for: (34) Spectrum function It concerns the presence of imported guide vanes and single-tone cutoff factors. The function is mainly defined by its expression as follows: (35) Spectrum function There are three scenarios: A. No imported guide vanes and hour: (36) in, (37) Where V represents the number of stator blades and B represents the number of rotating blades.

[0050] B. No imported guide vanes and hour: (38) C. When there are imported guide vanes: (39) Spectrum function The corrected spectrum function for the front-pass single tone of a fan with inlet air distortion is expressed as follows: (40) Calculate the combined single-tone noise of the fan inlet: When the relative Mach number of the fan blade tip is greater than 1, noise is generated due to the effect of the shock wave. (41) in, Design frequency for the fan, The sound pressure levels of the corresponding three monotone components are expressed as: (42) i =1,2,3 correspond to 1 / 2, 1 / 4, and 1 / 8 of the center frequency, respectively, representing the first source intensity function of each monotone component. It differs from the expression for the spectrum function S.

[0051] a. When i =1, that is, when it is half a single note: (43) (44) b. When i =2, that is, when it is 1 / 4 of a single note: (45) (46) c. When i =3, which is 1 / 8 of a single note: (47) (48) The sound source intensity constant C is related to whether or not there is an inlet guide vane: (49) Calculate the wideband noise at the fan outlet: (50) in, Let C be the intensity function of the second sound source, and C be the sound source intensity constant. At this time, the intensity function of the first sound source for: (51) Second sound source intensity function for: (52) Sound source intensity constant C: (53) Spectrum function for: (54) Calculate the discrete monotone noise at the fan outlet: (55) in, The rotor-stator distance.

[0052] At this time, the intensity function of the first sound source for: (56) Second sound source intensity function for: (57) Sound source intensity constant C: (58) Spectrum function There are two scenarios: a. Without imported guide vanes: (59) b. Without imported guide vanes: (60) Environmental corrections were applied to the calculated sound pressure levels at the fan inlet and outlet: (61) in, It is environmental density. It is the speed of ambient sound. It is the density of the fan inlet and outlet. It is the sound velocity at the fan inlet and outlet.

[0053] When calculating the forward noise of a fan over a certain distance, the sound pressure levels of each component need to be superimposed and converted into a mean square sound pressure level. At this point, the influence of distance must be considered, and the resulting mean square sound pressure level is also a function of frequency and direction angle. (62) in, Design frequency for the fan, It is the azimuth angle. It is environmental density. It is the speed of ambient sound. Reference pressure, convection gain term Correcting the sound pressure generated by flight effects It's the Mach number of the aircraft.

[0054] When considering the number of engines, the mean square sound pressure can be multiplied by the number of engines to calculate the added sound pressure, and then the sound pressure is output in the form of sound pressure level, expressed in decibels: (63) in, Design the frequency for the fan.

[0055] (4) The noise spectrum, sound pressure level and directivity angle of the jet are calculated based on the STONE model.

[0056] STONE model: (64) (65) (66) (67) in, The polarization pointing angle, This is the corrected distance from the sound source to the observer. f It is the center frequency of the jet's 1 / 3 octave band. The effective area of ​​the tail nozzle. For directional functions, For the spectrum function, The sound pressure level is for sawtooth noise reduction, while PWL is for engine sound power level. To correct the Mach number, The distance from the external nozzle surface to the measuring point. x The length of the serration from the bottom to the tip. This represents the axial offset of the noise source location of the component. To correct the pointing angle, The effective jet velocity is meters per second.

[0057] The method for superimposing the sound pressure levels of the internal, external, and mixed flows is as follows: (68) In equation (68) i This represents the airflow from the inner and outer bypass ducts, as well as the mixed airflow they form behind the engine.

[0058] (69) (70) The sound pressure at different frequency bands is obtained by formula (68), the mean square sound pressure is obtained according to (69), and finally the noise value SPL of the engine jet noise at different 1 / 3 octave bands at a certain static moment is obtained by formula (70).

[0059] Based on this, step S03, which involves superimposing and dynamically correcting the noise data from different components, is as follows: The dimensionless mean square sound pressure levels obtained from the fan, combustion chamber, turbine, and jet noise prediction models are superimposed to obtain the dimensionless mean square sound pressure level of the entire engine in the far field: (71) in, , ... These represent the mean square sound pressure levels at different locations on the engine.

[0060] (72) Dynamic correction is applied to the mean square sound pressure level to obtain the total engine noise under flight conditions, i.e., the dynamic sound pressure level under flight conditions: (73) in, The sound pressure level difference is corrected for Doppler frequency shift. For installation effect, Geometrical divergence decay, Atmospheric absorption and attenuation.

[0061] Doppler shift corrected sound pressure level difference: (74) Where λ is the angle between the aircraft's takeoff trajectory and the line connecting the aircraft and the observation point. This represents the aircraft's Mach number.

[0062] Correction based on installation effect: (75) Where N is the number of engines.

[0063] Based on geometrical divergence decay: (76) Based on atmospheric absorption attenuation correction: (77) (78) (79) in, This refers to the distance from the measurement point to the aircraft engine noise source. This refers to the distance from the measurement point to the engine during ground static testing. Indicates temperature. For each center frequency in the 1 / 3 octave band, in Equation 79 This refers to the relative humidity of the air.

[0064] This invention is based on mixed reality technology, which allows reviewers and designers to "experience" and assess the impact of noise in a virtual environment, thereby more effectively verifying whether the design meets regulatory requirements. It transforms abstract noise data into an immersive experience that is audible and visual, and presents complex noise prediction data in real time and in a three-dimensional way, enabling designers to intuitively discover noise problems.

[0065] The following describes the supersonic aircraft noise audible visualization device provided in the embodiments of the present invention. The supersonic aircraft noise audible visualization device described below and the supersonic aircraft noise audible visualization method described above can be referred to and correspond to each other.

[0066] First, combine Figure 11 This section introduces a device for visualizing the noise of supersonic aircraft, such as... Figure 11 As shown, the supersonic aircraft noise audible visualization device may include: Parameter acquisition unit 100 acquires parameters of the supersonic aircraft engine; The data prediction unit 200 calculates noise data generated by different components of a supersonic aircraft engine through a data prediction algorithm. The noise processing unit 300 superimposes and dynamically corrects the noise data of different components to obtain the total engine noise. Virtual scene construction unit 400 constructs a 3D model of the aircraft and flight scene to obtain a virtual scene for noise testing. The virtual-real interaction unit 500 overlays a virtual noise test scene with a real scene to test a supersonic aircraft engine and displays the test results.

[0067] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0068] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0069] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of audible visualization of supersonic aircraft noise, characterized in that, The method comprises the following steps: acquiring parameters of a supersonic aircraft engine; calculating noise data generated by different components of the supersonic aircraft engine through a data prediction algorithm; superimposing and dynamically correcting the noise data of different components to obtain total engine noise; constructing a three-dimensional model of the aircraft and flight scene to obtain a noise test virtual scene; superimposing the noise test virtual scene and the real scene to test the supersonic aircraft engine and display the test results.

2. The supersonic aircraft noise audible visualization method of claim 1, wherein, The process of constructing a three-dimensional model of the aircraft and flight scene comprises the following steps: constructing a three-dimensional model of the aircraft and flight scene using 3ds Max and solidworks, and combining Unity 3D to complete the construction of the noise test virtual scene and the development of the interactive interface.

3. The supersonic aircraft noise audible visualization method of claim 1, wherein, The process of superimposing the noise test virtual scene and the real scene comprises the following steps: superimposing real-time data streams of different components of the supersonic aircraft engine in the form of a three-dimensional heat map to the real space.

4. The supersonic aircraft noise audible visualization method of claim 1, wherein, The process of calculating noise data generated by different components of the supersonic aircraft engine through a data prediction algorithm comprises the following steps: calculating the noise spectrum, sound pressure level, and directivity angle of the combustion chamber through the SAE model; calculating the noise spectrum, sound pressure level, and directivity angle of the turbine through the Peart & Dunn model; calculating the noise spectrum, sound pressure level, and directivity angle of the Heidmann fan; calculating the noise spectrum, sound pressure level, and directivity angle of the jet based on the STONE model.

5. The supersonic aircraft noise audible visualization method of claim 4, wherein, The SAE model: ； where, is the far field mean square sound pressure of the chamber in the 1 / 3 octave band, is the total sound power, is the chamber inlet area non-dimensionalized with the engine reference area, is the aircraft Mach number, θ is the polar directivity angle, and D(θ) is the directivity function, f is the 1 / 3 octave center frequency of the chamber, S( f ) is the spectral function, is the sound source to observer distance, which is non-dimensionalized; sound power is related to the chamber inlet and outlet conditions and is defined as: ； wherein, is the combustor inlet mass flow rate, is the combustor inlet total temperature, is the combustor exit total temperature, is the combustor inlet total pressure, H is the turbine transfer gain factor, is the turbine transfer loss function: ； ； Where ζ is the characteristic impedance ratio, , These represent the local density and sound velocity at the turbine outlet, respectively. , These represent the local density and sound velocity at the combustion chamber outlet, respectively. Temperature drop at the design point of the low-pressure turbine; The total noise is the square of the pressure multiplied by the number of engines Ne, and the sound pressure level SPL is defined as follows: ； wherein, is the ambient density, is the ambient sound speed, is the reference pressure; The power level is defined as: ； wherein, is the engine reference area, is the reference power.

6. The supersonic aircraft noise audible visualization method of claim 4, wherein, The Peart & Dunn model is: ； ； wherein, is the far field mean square sound pressure of the turbine in the 1 / 3 octave band, is the total sound power, is the Mach number of the aircraft, is the polar directivity angle, is the directivity function, is the frequency parameter, is the spectral function, is the dimensionless sound source to observer distance, is the engine reference area, is the sound source to observer distance; The process of calculating the noise spectrum, sound pressure level, and directivity angle of the turbine comprises the following steps: calculating the turbine broadband noise: ； ； ； ； ； ； ； ； ； ； wherein, is the mass flow, is the relative tip Mach number at turbine exit, is the ambient density, is the ambient speed of sound, is the tip Mach number of the last stage blade of the turbine, is the axial flow Mach number at turbine exit, is the high pressure turbine rotational speed, is the speed of sound at turbine exit, is the total temperature at turbine exit, is the non-dimensional static temperature at turbine exit, is the specific heat ratio at turbine exit, R is the gas constant for dry air, is the static temperature at turbine exit, is the frequency parameter, f is the center frequency of the turbine 1 / 3 octave band, is the fundamental blade passing frequency, B is the number of blades, is the turbine rotor diameter; calculating the turbine broadband noise: ； ； ； wherein, is the sound source intensity constant, is the spectral function, is the relative tip speed of the last stage turbine rotor; adding the octave band broadband and single tone square sound pressure to obtain the total turbine noise square sound pressure: ； ； wherein, is the octave band mean square sound pressure, is the single tone mean square sound pressure, is the reference pressure.

7. The supersonic aircraft noise audible visualization method of claim 4, wherein, The process of calculating the noise spectrum, sound pressure level, and directivity angle of the Heidmann fan comprises the following steps: calculating the fan inlet broadband noise: ； wherein, is the fan discrete tone frequency, is the polar directivity angle, is the fan total temperature rise non-dimensionalized using ambient temperature, is the fan reference temperature rise non-dimensionalized, is the fan total temperature rise non-dimensionalized using ambient temperature, is the mass flow non-dimensionalized, is the ambient density, is the ambient speed of sound, is the reference mass flow non-dimensionalized, is the first sound source strength function, is the design point fan rotor relative tip Mach number, is the fan rotor relative tip Mach number, is the directivity correction function, is the spectral function, is the frequency parameter; calculating the fan inlet discrete single tone noise: ； wherein is the incoming flow distortion cancellation factor, n is the single tone harmonic number; calculating the fan outlet broadband noise: ； wherein is the second sound source intensity function, C is the sound source intensity constant; calculating the fan outlet discrete single tone noise: ； wherein is the rotor-stator distance; environmentally correcting the calculated sound pressures at the fan inlet and outlet: ； wherein, f is the fan design frequency, is the azimuthal pointing angle, is the ambient density, is the ambient sound speed, is the reference pressure; ； wherein, is the aircraft Mach number, is the ambient density, is the ambient speed of sound.

8. The supersonic aircraft noise audible visualization method of claim 4, wherein, The process of superimposing and dynamically correcting the noise data of different components comprises the following steps: The noise data of different components are superimposed to obtain the engine in the far field dimensionless mean square sound pressure: ; ； wherein, , ... respectively the mean square sound pressure at different parts of the engine, is the ambient density, is the ambient sound speed, is the ambient density, is the ambient sound speed, is the fan inlet and outlet density, is the fan inlet and outlet sound speed; dynamically correcting the square sound pressure to obtain the total engine noise under flight conditions: ； wherein, is the difference in sound pressure level for Doppler shift correction, is the mounting effect, is the geometric divergence attenuation, is the atmospheric absorption attenuation.

9. An apparatus for audible visualization of supersonic aircraft noise, characterized by The method comprises the following steps: a parameter acquisition unit acquires parameters of a supersonic aircraft engine, flight path, and aerodynamic characteristics; a data prediction unit calculates noise data generated by different components of the supersonic aircraft engine through a data prediction algorithm; a noise processing unit superimposes and dynamically corrects the noise data of different components to obtain total engine noise; a virtual scene construction unit constructs a three-dimensional model of the aircraft and flight scene to obtain a noise test virtual scene; a virtual-real interaction unit superimposes the noise test virtual scene and the real scene to test the supersonic aircraft engine and display the test results.

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