Airport aircraft noise calculation and prediction method and device

Abstract

The invention relates to the technical field of noise calculation and prediction, in particular to an airport aircraft noise calculation and prediction method and device. Constructing a dynamic noise source physical model, a sound source propagation attenuation physical model, a terrain influence mapping physical model and a meteorological dynamic correction physical model, and calculating the dynamic sound power level, the lateral diffraction correction factor, the geometric attenuation, the terrain attenuation and the atmospheric attenuation of the noise source according to the constructed physical models; calculating to obtain a sound pressure level prediction value of the receiving point; and the measured value and the predicted value can be subjected to space-time matching to optimize the parameters of the sound propagation path in each physical model. According to the technical scheme, the measured value and the predicted value are dynamically coupled, meanwhile, multiple complex factors are considered, the prediction accuracy in the complex environment is remarkably improved, and technical support is provided for civil aviation noise treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of noise calculation and prediction, and particularly to an airport aircraft noise calculation and prediction method and device. Background Art

[0002] With the rapid development of the global civil aviation industry, airport aircraft noise pollution has become an important factor restricting airport expansion and urban planning. Existing airport noise prediction methods mainly rely on simplified physical sound field models (such as ray tracing method, geometric acoustics model) or empirical statistical models, which have the following significant defects in practical applications: Traditional models have serious deficiencies in dealing with the sound field distortion effects of terrain reflection, meteorological time-varying characteristics, and aircraft real-time attitude.

[0003] There is a lack of an effective dynamic coupling mechanism between measured data and the prediction model, and a closed-loop correction of the noise field cannot be achieved. This means that in practical applications, even if a large amount of measured noise data is obtained, these data cannot be fed back to the prediction model in real time to optimize and correct the model, making it difficult to timely correct the deviation between the prediction result and the actual noise situation, and reducing the reliability and practicality of the prediction.

[0004] In complex terrain scenarios, the traditional model takes a long time to calculate the three-dimensional sound field propagation.

[0005] Therefore, the current method of using traditional models for noise calculation and prediction has problems of insufficient consideration of complex factors and lack of a dynamic coupling mechanism. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide an airport aircraft noise calculation and prediction method and device to solve the problems of insufficient consideration of complex factors and lack of a dynamic coupling mechanism in the existing noise calculation and prediction methods.

[0007] According to the first aspect of the embodiments of the present invention, an airport aircraft noise calculation and prediction method is provided, including: Obtain aircraft flight track data and real-time meteorological data; Based on the engine model, thrust level, and flight phase, establish a dynamic noise source physical model; based on the dynamic noise source physical model, calculate the dynamic sound power level of the noise source according to the aircraft flight track data; Construct a sound source propagation attenuation physical model including a spherical wave model and a cylindrical wave model. When the aircraft altitude is greater than a preset altitude, the spherical wave model is used, otherwise the cylindrical wave model is used; based on the sound source propagation attenuation physical model, calculate the geometric attenuation according to the sound propagation distance, and calculate the lateral diffraction correction factor according to the aircraft roll angle, diffraction edge length, and incident angle; Construct a terrain influence mapping physical model based on the pre-acquired three-dimensional digital elevation model; calculate the sound path difference based on the terrain influence mapping physical model, and calculate the terrain attenuation according to the sound path difference, the sound wave wavelength, the straight-line distance from the sound source to the receiving point, and the ground reflection coefficient; Construct a meteorological dynamic correction physical model according to the real-time meteorological data; calculate the atmospheric attenuation based on the atmospheric absorption coefficient and the straight-line distance from the sound source to the receiving point based on the meteorological dynamic correction physical model; Calculate the predicted sound pressure level value at the receiving point according to the dynamic sound power level, geometric attenuation, atmospheric attenuation, terrain attenuation, and lateral diffraction correction factor of the noise source; Obtain the actual monitoring data of the ground noise at the receiving point, perform spatio-temporal matching on the actual monitoring data and the predicted sound pressure level value, and optimize the parameters of the sound propagation path in each physical model according to the matching result.

[0008] Preferably, the sound propagation attenuation physical model, the terrain influence mapping physical model, and the meteorological dynamic correction physical model all include a sound propagation path; Before calculating the lateral diffraction correction factor and the terrain attenuation, it further includes: calculating the Fresnel number of the sound propagation path according to the obstacle height, the sound wave wavelength, and the total propagation distance; if the Fresnel number is greater than a preset value, the sound propagation path is an effective diffraction path, and calculate the lateral diffraction correction factor; otherwise, do not calculate the lateral diffraction correction factor.

[0009] Preferably, performing spatio-temporal matching on the actual monitoring data and the predicted sound pressure level value, and optimizing the parameters of the sound propagation path in each physical model according to the matching result, includes: Use the Kalman filter algorithm to perform spatio-temporal matching on the actual monitoring data and the predicted sound pressure level value; Compare the actual monitoring data after matching with the predicted sound pressure level value, and generate a dynamic correction gain matrix according to the comparison result; Calculate the corrected state vector according to the actual monitoring data, the predicted sound pressure level value, and the dynamic correction gain matrix; Update the parameters of the sound propagation path in the sound propagation attenuation physical model, the terrain influence mapping physical model, and the meteorological dynamic correction physical model according to the state vector.

[0010] Preferably, the method further includes: Construct a convolutional neural network, input the historical noise spectrum, historical meteorological parameters, and terrain feature map into the convolutional neural network, and output the sound field inversion weight matrix; When constructing the physical models of sound source propagation attenuation, terrain influence mapping, and meteorological dynamic correction, the model parameters are adjusted using the acoustic field inversion weight matrix.

[0011] Preferably, the dynamic sound power level of the noise source is calculated by the following formula:

[0012]

[0013] where, is the reference sound power level corresponding to the i th thrust level in the noise-power-distance database; is the real-time thrust level of the engine; is the i th thrust level of the engine; is the speed correction term; is the real-time airspeed of the aircraft; is the reference airspeed; is the dynamic sound power level.

[0014] Preferably, the geometric attenuation is calculated according to the sound propagation distance, including: If the altitude of the aircraft is greater than the preset altitude, the spherical wave attenuation calculation formula is:

[0015] If the altitude of the aircraft is less than the preset altitude, the cylindrical wave attenuation calculation formula is:

[0016] where, is the geometric attenuation; and represent different propagation distances respectively.

[0017] Preferably, the lateral diffraction correction factor is calculated by the following formula:

[0018] where, is the lateral diffraction correction factor; β is the roll angle of the aircraft; is the length of the diffraction edge; is the incident angle.

[0019] Preferably, the terrain attenuation is calculated, including: The sound path difference is calculated by the following formula:

[0020] where, is the sound path difference; is the horizontal distance from the sound source to the obstacle; is the horizontal distance from the obstacle to the receiving point; is the vertical height from the vertex of the obstacle to the propagation path; Calculate the barrier attenuation according to the following formula:

[0021] where, is the sound wave wavelength; is the barrier attenuation; Calculate the reflection attenuation according to the following formula:

[0022] where, is the ground reflection coefficient; is the straight-line distance from the sound source to the receiving point; is the reflection attenuation; Take the sum of the barrier attenuation and the reflection attenuation as the terrain attenuation.

[0023] Preferably, calculating the atmospheric attenuation includes: Adopt the line-by-line integration model to calculate the atmospheric absorption coefficient:

[0024] where, is the atmospheric absorption coefficient; is the absorption coefficient of the gas component; is the density correction function; Calculate the atmospheric attenuation through the following formula:

[0025] where, is the atmospheric attenuation; is the straight-line distance from the sound source to the receiving point.

[0026] According to the second aspect of the embodiments of the present invention, there is provided an airport aircraft noise calculation and prediction device, including: A main controller, and a memory connected to the main controller; The memory stores program instructions; The main controller is configured to execute the program instructions stored in the memory to execute the method described in any one of the above.

[0027] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: It can be understood that the technical solution shown in the present invention can obtain aircraft flight track data and real-time meteorological data, construct a physical model of a dynamic noise source, a physical model of sound source propagation attenuation, a physical model of terrain influence mapping, and a physical model of meteorological dynamic correction, and calculate the dynamic sound power level of the noise source, the lateral diffraction correction factor, the geometric attenuation, the terrain attenuation, and the atmospheric attenuation according to the constructed physical models, and then calculate the predicted sound pressure level value at the receiving point; it can also match the measured value and the predicted value in space and time to optimize the parameters of the sound propagation path in each physical model. The technical solution shown in the present invention realizes the dynamic coupling of the measured value and the predicted value, and at the same time, considering various complex factors, significantly improves the prediction accuracy in complex environments, providing technical support for civil aviation noise control.

[0028] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0030] Figure 1 is a schematic diagram of the steps of a method for calculating and predicting airport aircraft noise according to an exemplary embodiment; Figure 2 is a schematic block diagram of the process of a method for calculating and predicting airport aircraft noise according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are only examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0032] In one embodiment, referring to Figure 1 and Figure 2 , a method for calculating and predicting airport aircraft noise is provided, including: Step S11, obtaining aircraft flight track data and real-time meteorological data.

[0033] The aircraft flight track data includes the trajectory during the operation of the aircraft and the speed data during the operation; the real-time meteorological data mainly includes the data that can have a significant impact on the propagation of aircraft noise, including temperature and humidity, wind speed gradient data, etc.

[0034] Step S12: Establish a physical model of the dynamic noise source based on the engine model, thrust level, and flight phase; calculate the dynamic sound power level of the noise source according to the aircraft flight track data based on the physical model of the dynamic noise source.

[0035] During different flight phases of the aircraft, such as takeoff, cruise, and landing, there are significant differences in its operating state and noise generation mechanism. At the same time, for different types of engines, due to differences in design structure, working principle, and technical level, the noise characteristics generated during operation are also different. The thrust level refers to the current thrust level of the engine, such as 70%, 85%, or 100%. Therefore, when constructing the physical model of the dynamic noise source, it needs to be constructed according to the engine model, thrust level, and flight phase.

[0036] It should be noted that the dynamic sound power level of the noise source is calculated by the following formula:

[0037]

[0038] where is the reference sound power level corresponding to the i th thrust level in the noise-power-distance database; is the real-time thrust level of the engine; is the i th thrust level of the engine; is the speed correction term; is the real-time airspeed of the aircraft; is the reference airspeed; is the dynamic sound power level.

[0039] Step S13: Construct a physical model of sound source propagation attenuation including a spherical wave model and a cylindrical wave model. When the aircraft altitude is greater than the preset altitude, the spherical wave model is used; otherwise, the cylindrical wave model is used. Based on the physical model of sound source propagation attenuation, calculate the geometric attenuation according to the sound propagation distance, and calculate the lateral diffraction correction factor according to the aircraft roll angle, diffraction edge length, and incident angle.

[0040] Geometric attenuation of sound propagation is the core link of aircraft noise prediction. Its essence is to calculate the diffusion loss of sound energy with distance through the geometric characteristics of sound wave propagation.

[0041] First, when constructing the physical model of sound source propagation attenuation, a dynamic switching mechanism is introduced. The preset height can be set to 300 meters. When the aircraft altitude is greater than 300 meters, it is determined that this is the high-altitude region at this time. When the aircraft altitude is less than or equal to 300 meters, it is determined that this is the low-altitude region at this time. Therefore, when the aircraft altitude > 300m, the spherical wave model is enabled. This is because in the high-altitude environment, sound waves approximately spread evenly in all directions, conforming to the propagation characteristics of spherical waves. Through this formula, the attenuation amount of the sound pressure level caused by the diffusion of sound energy on the spherical surface with the increase of the propagation distance in the high-altitude region can be calculated. When the altitude ≤ 300m, it switches to the cylindrical wave model. In the low-altitude environment, due to the influence of factors such as the ground, the propagation of sound waves is closer to the characteristics of cylindrical waves. Compared with the spherical wave attenuation model, the cylindrical wave attenuation can more accurately reflect the change of the sound pressure level of sound waves spreading with distance in the low-altitude environment, improving the accuracy of near-field prediction.

[0042] The method of adjusting the model in real time according to the actual flight altitude can better fit the real situation of sound wave propagation at different altitudes, ensuring the accuracy of the calculation of the geometric attenuation amount.

[0043] It should be noted that calculating the geometric attenuation amount according to the sound propagation distance includes: If the aircraft altitude is greater than the preset altitude, spherical wave attenuation , indicating that for every doubling of the distance , the sound pressure level attenuates by 6 dB.

[0044] If the aircraft altitude is less than the preset altitude, cylindrical wave attenuation , indicating that for every doubling of the distance , the sound pressure level attenuates by 3 dB.

[0045] Among them, is the geometric attenuation amount; and represent different propagation distances respectively.

[0046] Preferably, in another embodiment, before calculating the lateral diffraction correction factor, the Fresnel number of the sound propagation path can also be calculated according to the obstacle height, sound wave wavelength and total propagation distance; if the Fresnel number is greater than the preset value, the sound propagation path is an effective diffraction path, and the lateral diffraction correction factor is calculated; otherwise, the lateral diffraction correction factor is not calculated.

[0047] This is because, due to the roll angle β of the aircraft changing the diffraction path of sound waves, it is necessary to determine whether the sound propagation path in the physical model is an effective diffraction path.

[0048] The Fresnel number is calculated by the following formula :

[0049] In this formula, is the height of the obstacle (such as a building or a mountain); is the total propagation distance; is the sound wave wavelength, which is calculated by the following formula:

[0050] is the speed of sound, is the frequency.

[0051] After calculating the Fresnel number, if ≥0.6, it indicates that the sound propagation path is an effective diffraction path, and the contribution of diffracted sound energy is retained; otherwise, it is regarded as complete occlusion.

[0052] After determining the effective diffraction path, calculate the lateral diffraction correction factor: It should be noted that the lateral diffraction correction factor is calculated by the following formula:

[0053] where, is the lateral diffraction correction factor; β is the roll angle of the aircraft; is the length of the diffraction edge; is the incident angle. The length of the diffraction edge refers to the key side length related to diffraction on the obstacle when the sound wave encounters the obstacle and undergoes diffraction during propagation. The incident angle refers to the angle between the sound wave propagation direction and the normal line of the obstacle surface at the diffraction point.

[0054] The traditional geometric attenuation model ignores the diffraction and wavefront distortion phenomena during the sound wave propagation when calculating the aircraft noise propagation. However, in actual situations, especially in the low-altitude complex terrain environment, the influence of these factors on the noise propagation cannot be ignored. Therefore, this embodiment calculates the lateral diffraction correction factor, which can more accurately calculate the noise propagation in the complex environment.

[0055] Step S14: Construct a terrain influence mapping physical model based on the pre-acquired three-dimensional digital elevation model; calculate the sound path difference based on the terrain influence mapping physical model, and calculate the terrain attenuation amount according to the sound path difference, the sound wave wavelength, the straight-line distance from the sound source to the receiving point, and the ground reflection coefficient.

[0056] The three-dimensional digital elevation model (Digital Elevation Model, abbreviated as DEM) is a model for digitally expressing the terrain surface morphology.

[0057] It should be noted that calculating the terrain attenuation amount includes: Calculate the sound path difference by the following formula:

[0058] Among them, is the sound path difference, which refers to the length difference of different propagation paths during the propagation of sound waves; is the horizontal distance from the sound source to the obstacle; is the horizontal distance from the obstacle to the receiving point; is the vertical height from the vertex of the obstacle to the propagation path.

[0059] Judge whether it is an effective diffraction path through the Fresnel number:

[0060] Among them, , is the total propagation distance. When , retain the diffraction path, otherwise it is regarded as complete occlusion.

[0061] Calculate the barrier attenuation according to the following formula:

[0062] Among them, is the sound wave wavelength; is the barrier attenuation. In this formula, , represents the barrier attenuation for a single obstacle; , represents the barrier attenuation for multiple obstacles.

[0063] Calculate the reflection attenuation according to the following formula:

[0064] Among them, is the ground reflection coefficient, taking 0.1 for asphalt pavement, 0.4 for grassland, and 0.9 for water surface; is the straight-line distance from the sound source to the receiving point; is the reflection attenuation.

[0065]

[0066] Take the sum of the barrier attenuation and the reflection attenuation as the terrain attenuation .

[0067] Step S15: Construct a meteorological dynamic correction physical model according to the real-time meteorological data; based on the meteorological dynamic correction physical model, calculate the atmospheric attenuation according to the atmospheric absorption coefficient and the straight-line distance from the sound source to the receiving point.

[0068] Fuse the temperature, humidity, and wind speed gradient data in real time, and pass through the atmospheric absorption coefficient and the refraction effect model corrects the sound field propagation loss.

[0069] It should be noted that calculating the atmospheric attenuation includes: Using the line-by-line integration model to calculate the atmospheric absorption coefficient:

[0070] where is the atmospheric absorption coefficient; is the absorption coefficient of the gas component; is the density correction function; and come from the HITRAN spectroscopic database.

[0071] Calculate the atmospheric attenuation through the following formula:

[0072] where is the atmospheric attenuation; is the straight-line distance from the sound source to the receiving point.

[0073] Step S16: Calculate the predicted sound pressure level at the receiving point according to the dynamic sound power level, geometric attenuation, atmospheric attenuation, terrain attenuation and lateral diffraction correction factor of the noise source.

[0074] The calculation formula is:

[0075] where is the predicted sound pressure level at the receiving point, is the sound power level; is the geometric attenuation; is the atmospheric attenuation; is the terrain attenuation; is the lateral diffraction correction factor.

[0076] Step S17: Obtain the actual monitoring data of the ground noise at the receiving point, perform spatio-temporal matching on the actual monitoring data and the predicted sound pressure level, and optimize the parameters of the sound propagation path in each physical model according to the matching result.

[0077] It is understandable that the technical solution shown in the present invention can obtain aircraft flight track data and real-time meteorological data, construct a physical model of a dynamic noise source, a physical model of sound source propagation attenuation, a physical model of terrain influence mapping, and a physical model of meteorological dynamic correction, and calculate the dynamic sound power level, lateral diffraction correction factor, geometric attenuation, terrain attenuation, and atmospheric attenuation of the noise source according to the constructed physical models, and then calculate the predicted sound pressure level value at the receiving point; it can also match the measured value and the predicted value in space and time to optimize the parameters of the sound propagation path in each physical model. The technical solution shown in the present invention realizes the dynamic coupling of the measured value and the predicted value, and at the same time, considering various complex factors, significantly improves the prediction accuracy in complex environments, providing technical support for civil aviation noise control.

[0078] It should be noted that the physical model of sound source propagation attenuation, the physical model of terrain influence mapping, and the physical model of meteorological dynamic correction all include the sound propagation path.

[0079] Optimizing the parameters of the sound propagation path includes: Step S21: Use the Kalman filter algorithm to match the actual monitoring data and the predicted sound pressure level value in space and time.

[0080] In specific practice, track tracking radars, ground noise monitoring arrays, and meteorological sensors are deployed to match multi-source data and predicted data in space and time for multi-source data fusion.

[0081] Step S22: Compare the matched actual monitoring data with the predicted sound pressure level value, and generate a dynamic correction gain matrix according to the comparison result .

[0082] Step S23: Calculate the corrected state vector according to the actual monitoring data, the predicted sound pressure level value, and the dynamic correction gain matrix:

[0083] Wherein, is the corrected state vector; is the predicted value, is the measured value of the ground noise monitoring array; is the observation matrix, determined by the sensor layout topology, mapping the state vector to the observation space according to the sensor layout.

[0084] The state vector contains parameters such as sound source intensity and propagation loss. As time goes by and new observation data is incorporated, the state vector is continuously updated to more accurately reflect the actual state of the noise field.

[0085] Step S24: Update the parameters of the sound propagation path in the physical model of sound source propagation attenuation, the physical model of terrain influence mapping, and the physical model of meteorological dynamic correction according to the state vector.

[0086] It can be understood that the technical solution shown in this embodiment uses the multi-source data fusion technology to integrate and analyze data of different types and sources, correct the parameters of the sound propagation path in the physical model, improve the integrity, accuracy, and reliability of the data, provide richer and higher-quality data support for noise prediction, and help improve the accuracy of the prediction results.

[0087] It should be noted that the method further includes: Construct a convolutional neural network, input historical noise spectra, historical meteorological parameters, and terrain feature maps into the convolutional neural network, and output a sound field inversion weight matrix; when constructing the physical model of sound source propagation attenuation, the physical model of sound source propagation attenuation, the physical model of terrain influence mapping, and the physical model of meteorological dynamic correction, use the sound field inversion weight matrix to adjust the model parameters.

[0088] For the constructed convolutional neural network (CNN), the input layer receives historical noise spectra, meteorological parameters, and terrain feature maps and outputs a sound field inversion weight matrix. W The convolutional neural network structure includes: a feature extraction layer: a 3×3 convolutional kernel extracts spatial frequency features; a pooling layer: max pooling reduces the dimension to 1 / 4 resolution; a fully connected layer: generates a weight matrix to dynamically adjust the model parameters.

[0089] CNN input and output: , where is historical noise spectrum data (dimensions: time, frequency, sound pressure level); is a meteorological parameter matrix (temperature, humidity, wind speed); is a terrain feature tensor (three-dimensional elevation data).

[0090] In another embodiment, an airport aircraft noise calculation and prediction device is provided, including: A main controller, and a memory connected to the main controller; The memory stores program instructions; The main controller is used to execute the program instructions stored in the memory and execute the method described in any one of the above.

[0091] It can be understood that the same or similar parts in the above embodiments can be referred to each other, and the content not detailed in some embodiments can be seen in the same or similar content of other embodiments.

[0092] It should be noted that in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be construed as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "a plurality of" refers to at least two.

[0093] Any process or method description in the flowchart or described in other ways herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in the reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0094] It should be understood that each part of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0095] Those of ordinary skill in the art of the present technology can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0096] In addition, each functional unit in various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0097] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disk, etc.

[0098] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0099] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. An airport aircraft noise calculation and prediction method, characterized in that, Including: Obtaining aircraft flight track data and real-time meteorological data; Based on the engine model, thrust level, and flight phase, establishing a physical model of the dynamic noise source; Based on the physical model of the dynamic noise source, calculating the dynamic sound power level of the noise source according to the aircraft flight track data; Constructing a physical model of sound source propagation attenuation including a spherical wave model and a cylindrical wave model. When the aircraft altitude is greater than the preset altitude, the spherical wave model is adopted, otherwise the cylindrical wave model is adopted; Based on the physical model of sound source propagation attenuation, calculating the geometric attenuation according to the sound propagation distance, and calculating the lateral diffraction correction factor according to the aircraft roll angle, diffraction edge length, and incident angle; Constructing a physical model of terrain influence mapping based on the pre-obtained three-dimensional digital elevation model; Calculating the sound path difference based on the physical model of terrain influence mapping, and calculating the terrain attenuation according to the sound path difference, sound wave wavelength, straight-line distance from the sound source to the receiving point, and ground reflection coefficient; Constructing a physical model of meteorological dynamic correction according to the real-time meteorological data; Calculating the atmospheric attenuation based on the physical model of meteorological dynamic correction according to the atmospheric absorption coefficient and the straight-line distance from the sound source to the receiving point; Calculating the predicted sound pressure level value at the receiving point according to the dynamic sound power level of the noise source, geometric attenuation, atmospheric attenuation, terrain attenuation, and lateral diffraction correction factor; Obtaining the actual monitoring data of the ground noise at the receiving point, performing spatio-temporal matching on the actual monitoring data and the predicted sound pressure level value, and optimizing the parameters of the sound propagation path in each physical model according to the matching result.

2. The method according to claim 1, wherein: The physical model of sound source propagation attenuation, the physical model of terrain influence mapping, and the physical model of meteorological dynamic correction all include a sound propagation path; Before calculating the lateral diffraction correction factor and terrain attenuation, it further includes: calculating the Fresnel number of the sound propagation path according to the obstacle height, sound wave wavelength, and total propagation distance; If the Fresnel number is greater than the preset value, the sound propagation path is an effective diffraction path, and the lateral diffraction correction factor is calculated; Otherwise, the lateral diffraction correction factor is not calculated.

3. The method according to claim 2, wherein Performing spatio-temporal matching on the actual monitoring data and the predicted sound pressure level value, and optimizing the parameters of the sound propagation path in each physical model according to the matching result, including: Using the Kalman filtering algorithm to perform spatio-temporal matching on the actual monitoring data and the predicted sound pressure level value; Comparing the matched actual monitoring data with the predicted sound pressure level value, and generating a dynamic correction gain matrix according to the comparison result; Calculating the corrected state vector according to the actual monitoring data, the predicted sound pressure level value, and the dynamic correction gain matrix; Updating the parameters of the sound propagation path in the physical model of sound source propagation attenuation, the physical model of terrain influence mapping, and the physical model of meteorological dynamic correction according to the state vector.

4. The method according to claim 1, wherein It further includes: Constructing a convolutional neural network, inputting historical noise spectra, historical meteorological parameters, and terrain feature maps into the convolutional neural network, and outputting a sound field inversion weight matrix; When constructing the physical model of sound source propagation attenuation, the physical model of sound source propagation attenuation, the physical model of terrain influence mapping, and the physical model of meteorological dynamic correction, the model parameters are adjusted by using the sound field inversion weight matrix.

5. The method according to claim 1, wherein: The dynamic sound power level of the noise source is calculated by the following formula: Among them, is the reference sound power level corresponding to the i th thrust level in the noise-power-distance database; is the real-time thrust level of the engine; is the i th thrust level of the engine; is the speed correction term; is the real-time airspeed of the aircraft; is the reference airspeed; is the dynamic sound power level.

6. The method according to claim 1, characterized in that, Calculating the geometric attenuation according to the sound propagation distance, including: If the aircraft height is greater than the preset height, the spherical wave attenuation calculation formula is: If the aircraft height is less than the preset height, the cylindrical wave attenuation calculation formula is: Among them, is the geometric attenuation; and respectively represent different propagation distances.

7. The method according to claim 1, wherein: The lateral diffraction correction factor is calculated by the following formula: Among them, is the lateral diffraction correction factor; β is the aircraft roll angle; is the diffraction edge length; is the incident angle.

8. The method according to claim 1, wherein Calculating the terrain attenuation, including: The sound path difference is calculated by the following formula: Among them, is the sound path difference; is the horizontal distance from the sound source to the obstacle; is the horizontal distance from the obstacle to the receiving point; is the vertical height from the vertex of the obstacle to the propagation path; The barrier attenuation is calculated according to the following formula: Among them, is the acoustic wavelength; is the barrier attenuation amount; The reflection attenuation is calculated according to the following formula: Among them, is the ground reflection coefficient; is the straight-line distance from the sound source to the receiving point; is the reflection attenuation; The sum of the barrier attenuation and the reflection attenuation is used as the terrain attenuation.

9. The method according to claim 1, characterized in that Calculating the atmospheric attenuation, including: The line-by-line integration model is used to calculate the atmospheric absorption coefficient: Among them, is the atmospheric absorption coefficient; is the absorption coefficient of the gas component; is the density correction function; The atmospheric attenuation is calculated by the following formula: Among them, is the atmospheric attenuation; is the straight-line distance from the sound source to the receiving point.

10. An airport aircraft noise calculation and prediction device, characterized in that Including: A main controller and a memory connected to the main controller; The memory stores program instructions; The main controller is configured to execute the program instructions stored in the memory and execute the method according to any one of claims 1 to 9.

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