Proximity effect risk analysis method and system for noise sensitive area

Abstract

The invention provides an adjacent avoidance effect risk analysis method and system for a noise sensitive area, and the method comprises the steps: obtaining a noise source sound power frequency spectrum and a three-dimensional scene model containing a sensitive area and an obstacle, and generating an initial sound ray set carrying energy, phase and frequency; a sound ray path is tracked in the 3D model, and phase disturbance and amplitude fluctuation caused by atmospheric turbulence are calculated; reflection, diffuse scattering, transmission and vibration re-radiation generated by the action of sound rays and the surface of an obstacle; the method comprises the following steps of: arranging a virtual receiver array in a noise sensitive area according to a diffraction effect when a sound ray arrives at the edge, and reconstructing a time domain sound pressure signal of each receiving point by performing coherent superposition on complex sound pressure reaching the sound ray; psychoacoustic indexes such as loudness are calculated on the basis of the signals and fused into a comprehensive risk index representing the neighbor effect through a preset weighting model.

Description

Technical Field

[0001] This application belongs to the field of NIMBY (Not In My Backyard) risk analysis, and in particular relates to a method and system for NIMBY risk analysis in noise-sensitive areas. Background Technology

[0002] The increasing construction of large-scale industrial facilities, energy projects, and transportation hubs poses a serious threat to the quality of life in noise-sensitive areas such as surrounding residential communities due to the noise generated during their operation. This public resistance, or NIMBY (Not In My Backyard) effect, caused by negative externalities such as noise, has become a focus of widespread social concern and a difficult problem that must be carefully addressed in project planning. Noise impact assessments for such projects primarily rely on prediction methods based on empirical formulas such as the ISO 9613 standard or simplified numerical models. Among these, the ray-based method is widely used in outdoor sound field prediction because it can intuitively simulate the propagation path of sound waves in complex three-dimensional scenes and effectively handle issues such as reflection and obstruction. The ray-based method abstracts the sound energy radiated by a sound source into a large number of energy-carrying sound rays. By tracing the propagation trajectory of each sound ray and its interaction with obstacles in the environment, the sound energy reaching the receiving point is statistically analyzed to predict the sound pressure level. However, existing noise prediction methods based on the ray-based method often oversimplify environmental factors. For example, they typically ignore the subtle perturbations of sound wave phase and amplitude caused by inhomogeneous media such as atmospheric turbulence, which can lead to significant errors over long distances. When simulating the interaction between sound rays and obstacle surfaces, most models only consider ideal specular reflection, lacking effective computational models for complex physical phenomena commonly found in real-world scenarios, such as diffuse scattering, sound wave transmission, and secondary radiation generated by structural vibrations. Furthermore, existing methods handle sound wave diffraction, especially the complex paths around obstacle edges, in a rather coarse manner. Traditional noise assessment systems often use single physical quantities such as A-weighted sound pressure level as core indicators, failing to comprehensively and accurately reflect the subjective perception and psychological aversion to noise. While psychoacoustic parameters such as loudness, sharpness, and roughness have been proven to better characterize the disturbing nature of noise, few methods currently integrate physical simulation of sound propagation with multi-dimensional psychoacoustic analysis to form a comprehensive and systematic assessment tool capable of quantifying the risk of the NIMBY (Not In My Backyard) effect. Summary of the Invention

[0003] To address the aforementioned issues, this application proposes a method for analyzing the NIMBY (Not In My Backyard) effect risk in noise-sensitive areas, comprising the following steps: Obtain the sound power spectrum of the noise source and a three-dimensional scene model including noise-sensitive areas and obstacles; based on the sound power spectrum and frequency-directivity relationship, generate an initial set of sound rays carrying initial energy, phase, and frequency information; In the three-dimensional scene model, the propagation path of the sound ray is traced. Based on the atmospheric turbulence model, the phase perturbation and amplitude fluctuation caused by atmospheric inhomogeneity to the complex amplitude of the sound ray are calculated. When the sound ray interacts with the surface of an obstacle, the specular reflection, frequency-related diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound ray are calculated according to the acoustic properties and geometry of the obstacle surface material. When the sound ray path approaches the edge of the obstacle, the changes in the sound ray path, phase, and energy caused by edge diffraction are calculated based on the unified geometric diffraction theory. A virtual receiver array is deployed within the noise-sensitive area. The time-domain sound pressure signal of each receiver location in the virtual receiver array is reconstructed by coherently superimposing the complex sound pressures of all arrival sound rays at each receiver location. Based on the time-domain sound pressure signals at each receiver location in the virtual receiver array, psychoacoustic indices including at least loudness, sharpness, roughness, and fluctuation intensity are calculated, and the psychoacoustic indices are fused into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect through a preset weighted model.

[0004] Optionally, generating an initial set of acoustic rays carrying initial energy, phase, and frequency information based on the acoustic power spectrum and frequency-directivity relationship includes: The acoustic power spectrum is divided into multiple frequency bands, and the center frequency of each frequency band is determined. The Monte Carlo method is used to emit a predetermined number of sound rays from the noise source location, wherein the number of sound rays allocated to each frequency band is proportional to the sound power of the frequency band; The initial energy of each sound ray is determined based on the total sound power of the frequency band and the number of sound rays allocated to the frequency band. The initial phase is randomly assigned within the interval [0, 2π]. The initial propagation direction is determined based on the center frequency of the frequency band where the sound ray is located and a preset frequency-directivity relationship.

[0005] Optionally, when the sound ray interacts with the surface of an obstacle, calculating the specular reflection, frequency-dependent diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound ray based on the acoustic properties and geometry of the obstacle surface material includes: When a sound ray collides with the surface of an obstacle, the direction of specular reflection is calculated based on the surface normal and the angle of incidence at the point of collision. Based on the frequency-dependent absorption, scattering, and transmission coefficients of the surface, the incident sound energy is divided into three parts: absorbed, reflected, and transmitted. The reflected energy is distributed between specular reflection and diffuse scattering according to the scattering coefficient, and corresponding specular reflection sound rays and diffuse scattering sound rays are generated. The transmitted energy is used to generate new sound rays that pass through obstacles, and the effect of structural vibrations on the characteristics of the transmitted sound rays is taken into account.

[0006] Optionally, when the sound path approaches the edge of an obstacle, the changes in the sound path, phase, and energy caused by edge diffraction are calculated based on the unified geometric diffraction theory, including: When the distance between the sound propagation path and the edge of the obstacle is less than a preset threshold, diffraction calculation is triggered; Identify a diffraction point on the edge of the obstacle that satisfies Keller's law of diffraction, and generate a new diffracted sound ray from the diffraction point; The diffraction coefficients of the unified geometric diffraction theory are calculated based on the geometric relationship between the incident sound ray, the diffracted sound ray and the edge of the obstacle, and the sound ray frequency. Multiplying the complex amplitude of the incident sound ray by the diffraction coefficient yields the initial complex amplitude of the new diffracted sound ray.

[0007] Optionally, the step of deploying a virtual receiver array within the noise-sensitive area and reconstructing the time-domain sound pressure signal at each receiver location in the virtual receiver array by coherently superimposing the complex sound pressures of all arriving sound rays at each receiver includes: Each virtual receiver is defined as a receiving volume with a preset geometry and size; Acquire all sound rays whose ends fall within the receiving volume of a single receiver; Record the complex sound pressure pi, frequency fi, and total propagation time ti for each arriving sound ray i, and reconstruct the frequency domain response at the receiver by coherent superposition based on pi, fi, and ti; Perform an inverse Fourier transform on the frequency domain response to obtain the time-domain sound pressure signal at the receiver location.

[0008] Optionally, based on the time-domain sound pressure signals at each receiver location in the virtual receiver array, a psychoacoustic index including at least loudness, sharpness, roughness, and fluctuation intensity is calculated, and the psychoacoustic index is fused into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect using a preset weighted model, including: Calculate the loudness, sharpness, roughness, and wave intensity values ​​of the time-domain sound pressure signal according to international or national standards; The calculated psychoacoustic index values ​​were normalized. The normalized psychoacoustic index values ​​are integrated into a comprehensive risk index through a weighted model. The weight coefficients in the weighted model are pre-set based on expert knowledge, empirical data, and / or specific application scenarios.

[0009] Furthermore, this application also proposes a risk analysis system for the NIMBY (Not In My Backyard) effect in noise-sensitive areas, comprising the following units: The initial sound ray generation unit acquires the sound power spectrum of the noise source and a three-dimensional scene model containing noise-sensitive areas and obstacles; based on the sound power spectrum and frequency-directivity relationship, it generates an initial sound ray set carrying initial energy, phase, and frequency information. The influence calculation unit tracks the sound ray propagation path in the three-dimensional scene model, and calculates the phase perturbation and amplitude fluctuation caused by atmospheric inhomogeneity to the complex amplitude of the sound ray based on the atmospheric turbulence model; when the sound ray interacts with the surface of an obstacle, it calculates the specular reflection, frequency-related diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound ray according to the acoustic properties and geometry of the obstacle surface material; when the sound ray path approaches the edge of the obstacle, it calculates the changes in the sound ray path, phase, and energy caused by edge diffraction based on the unified geometric diffraction theory. The time-domain sound pressure signal reconstruction unit deploys a virtual receiver array within the noise-sensitive area and reconstructs the time-domain sound pressure signal at each receiver location in the virtual receiver array by coherently superimposing the complex sound pressures of all arrival sound rays at each receiver. The risk index generation unit calculates psychoacoustic indices, including at least loudness, sharpness, roughness, and fluctuation intensity, based on the time-domain sound pressure signals at each receiver location in the virtual receiver array. Then, it integrates these psychoacoustic indices into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect through a preset weighting model.

[0010] Optionally, generating an initial set of acoustic rays carrying initial energy, phase, and frequency information based on the acoustic power spectrum and frequency-directivity relationship includes: The acoustic power spectrum is divided into multiple frequency bands, and the center frequency of each frequency band is determined. The Monte Carlo method is used to emit a predetermined number of sound rays from the noise source location, wherein the number of sound rays allocated to each frequency band is proportional to the sound power of the frequency band; The initial energy of each sound ray is determined based on the total sound power of the frequency band and the number of sound rays allocated to the frequency band. The initial phase is randomly assigned within the interval [0, 2π]. The initial propagation direction is determined based on the center frequency of the frequency band where the sound ray is located and a preset frequency-directivity relationship.

[0011] Optionally, when the sound ray interacts with the surface of an obstacle, calculating the specular reflection, frequency-dependent diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound ray based on the acoustic properties and geometry of the obstacle surface material includes: When a sound ray collides with the surface of an obstacle, the direction of specular reflection is calculated based on the surface normal and the angle of incidence at the point of collision. Based on the frequency-dependent absorption, scattering, and transmission coefficients of the surface, the incident sound energy is divided into three parts: absorbed, reflected, and transmitted. The reflected energy is distributed between specular reflection and diffuse scattering according to the scattering coefficient, and corresponding specular reflection sound rays and diffuse scattering sound rays are generated. The transmitted energy is used to generate new sound rays that pass through obstacles, and the effect of structural vibrations on the characteristics of the transmitted sound rays is taken into account.

[0012] Optionally, when the sound path approaches the edge of an obstacle, the changes in the sound path, phase, and energy caused by edge diffraction are calculated based on the unified geometric diffraction theory, including: When the distance between the sound propagation path and the edge of the obstacle is less than a preset threshold, diffraction calculation is triggered; Identify a diffraction point on the edge of the obstacle that satisfies Keller's law of diffraction, and generate a new diffracted sound ray from the diffraction point; The diffraction coefficients of the unified geometric diffraction theory are calculated based on the geometric relationship between the incident sound ray, the diffracted sound ray and the edge of the obstacle, and the sound ray frequency. Multiplying the complex amplitude of the incident sound ray by the diffraction coefficient yields the initial complex amplitude of the new diffracted sound ray.

[0013] Optionally, the step of deploying a virtual receiver array within the noise-sensitive area and reconstructing the time-domain sound pressure signal at each receiver location in the virtual receiver array by coherently superimposing the complex sound pressures of all arriving sound rays at each receiver includes: Each virtual receiver is defined as a receiving volume with a preset geometry and size; Acquire all sound rays whose ends fall within the receiving volume of a single receiver; Record the complex sound pressure pi, frequency fi, and total propagation time ti for each arriving sound ray i, and reconstruct the frequency domain response at the receiver by coherent superposition based on pi, fi, and ti; Perform an inverse Fourier transform on the frequency domain response to obtain the time-domain sound pressure signal at the receiver location.

[0014] Optionally, based on the time-domain sound pressure signals at each receiver location in the virtual receiver array, a psychoacoustic index including at least loudness, sharpness, roughness, and fluctuation intensity is calculated, and the psychoacoustic index is fused into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect using a preset weighted model, including: Calculate the loudness, sharpness, roughness, and wave intensity values ​​of the time-domain sound pressure signal according to international or national standards; The calculated psychoacoustic index values ​​were normalized. The normalized psychoacoustic index values ​​are integrated into a comprehensive risk index through a weighted model. The weight coefficients in the weighted model are pre-set based on expert knowledge, empirical data, and / or specific application scenarios.

[0015] On the one hand, this invention meticulously simulates various complex physical effects such as atmospheric turbulence, frequency-related diffuse scattering, transmission, structural re-radiation, and edge diffraction in sound ray tracing, ensuring accurate reconstruction of the time-domain signal of the sound field in complex three-dimensional scenes. On the other hand, this invention abandons the traditional evaluation model that relies solely on a single physical indicator such as A-weighted sound pressure level. Instead, it calculates a series of psychoacoustic indicators, such as loudness, sharpness, and roughness, which better reflect people's subjective feelings of annoyance, and integrates them into a comprehensive risk index, so that the assessment results of noise impact can truly reflect the actual perception of residents. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a 3D model of the scene. Figure 2 A schematic diagram is generated for the initial set of vocal ray trajectories; Figure 3 This is a schematic diagram of the interaction between sound rays and a surface. Figure 4 This is a schematic diagram of edge diffraction. Figure 5 A schematic diagram of a virtual receiver receiving sound. Figure 6 This is a schematic diagram of the fusion of psychoacoustic indicators. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] In one embodiment, this application proposes a method for analyzing the NIMBY (Not In My Backyard) effect risk in noise-sensitive areas, characterized by comprising the following steps: S1, acquire the sound power spectrum of the noise source and a three-dimensional scene model including the noise-sensitive area and obstacles; generate an initial set of sound rays carrying initial energy, phase and frequency information based on the sound power spectrum and frequency-directivity relationship; The acoustic power spectrum is obtained through on-site measurements at a noise source, such as around a large transformer, using a microphone array conforming to ISO 3744 standards, or directly from the technical manual provided by the equipment manufacturer. The 3D scene model is generated by mapping the target area using LiDAR scanning or UAV oblique photography, producing point cloud data containing terrain, buildings, vegetation, and other objects. This data is then used in meshing software such as MeshLab to construct a 3D geometric model containing vertex and facet information. Figure 1 As shown.

[0019] A method based on icosahedral recursive subdivision is used to generate uniformly distributed initial sound ray directions at the center of the sound source. The total energy of the sound source is distributed across different octave or one-third octave bands according to the sound power spectrum. Each sound ray is assigned initial energy according to the directivity coefficient of its emission direction within its corresponding band. The frequency of the sound ray is determined by random sampling from the spectral distribution of its respective band, and the initial phase is randomly assigned within the range of 0 to 2π to simulate an incoherent sound source.

[0020] S2, in the three-dimensional scene model, trace the sound propagation path, and calculate the phase perturbation and amplitude fluctuation caused by atmospheric inhomogeneity to the complex amplitude of the sound ray based on the atmospheric turbulence model; when the sound ray interacts with the surface of an obstacle, calculate the specular reflection, frequency-related diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound ray according to the acoustic properties and geometric structure of the obstacle surface material; when the sound ray path approaches the edge of the obstacle, calculate the changes in the sound ray path, phase, and energy caused by edge diffraction based on the unified geometric diffraction theory. A ray casting algorithm is used to track the intersection points of sound rays with surfaces in a 3D scene model. For atmospheric propagation, a phase screen model based on the von Kármán turbulence spectrum is introduced. Multiple virtual screens perpendicular to the propagation direction are set along the sound ray propagation path. When a sound ray passes through a screen, random phase perturbations and amplitude corrections are applied to its complex amplitude based on turbulence intensity and scale parameters. When a sound ray interacts with an obstacle surface, its frequency-related absorption and scattering coefficients are queried from a pre-defined material database. A Russian roulette algorithm is used to probabilistically determine whether specular reflection or diffuse scattering occurs. Specular reflection follows Snell's law, while diffuse scattering follows Lambert's cosine law. Sound wave transmission and re-radiation are performed by simplifying the obstacle to a thin plate model, calculating the plate's vibration velocity under sound wave excitation, and using Rayleigh integrals to calculate the sound field radiated to the other side by the plate's vibration, generating new sound rays. When the distance between the sound ray and the edge of the obstacle is less than the Fresnel zone radius, diffraction is determined to have occurred. The Unified Geometry Diffraction Theory is applied to generate a diffracted sound ray cone at the edge, and the direction, energy and phase delay of the newly generated diffracted sound ray are calculated using the UTD diffraction coefficient.

[0021] S3, a virtual receiver array is deployed in the noise-sensitive area, and the time-domain sound pressure signal of each receiver position in the virtual receiver array is reconstructed by coherently superimposing the complex sound pressure of all the sound rays arriving at each receiver. In noise-sensitive areas, such as outside residential building windows, a grid-like array of virtual spherical receivers is set up at one-meter intervals. For each receiver, all intersecting sound rays are detected, and the complex amplitude of each arriving sound ray is recorded. This complex amplitude includes all energy attenuation and phase changes during propagation. The complex amplitudes of all arriving sound rays at the same frequency are vector-summed to obtain the total complex sound pressure level of the receiver at that frequency, constructing a complete received spectrum. An inverse fast Fourier transform is performed on the received spectrum to obtain a high-fidelity time-domain sound pressure waveform at the receiver location.

[0022] S4. Based on the time-domain sound pressure signal of each receiver position in the virtual receiver array, calculate at least the psychoacoustic indices including loudness, sharpness, roughness, and fluctuation intensity, and fuse the psychoacoustic indices into a comprehensive risk index representing the NIMBY effect through a preset weighting model.

[0023] For the time-domain sound pressure signal at each receiver location, the loudness is calculated using the Zwick loudness model conforming to ISO 532-1, the sharpness is calculated using the Ores model, and the roughness and fluctuation intensity are calculated using the Daniel and Weber model. Using the analytic hierarchy process (AHP), a judgment matrix is ​​constructed through expert scoring to calculate the relative weight coefficients of loudness, sharpness, roughness, and fluctuation intensity in relation to triggering residents' aversion. After normalizing each psychoacoustic indicator, a dimensionless comprehensive risk index is obtained by linearly weighting and summing the weight coefficients. The magnitude of this comprehensive risk index is correlated with the level of risk of the NIMBY (Not In My Backyard) effect.

[0024] In an optional embodiment, generating an initial set of acoustic rays carrying initial energy, phase, and frequency information based on the acoustic power spectrum and frequency-directivity relationship includes: The acoustic power spectrum is divided into multiple frequency bands, and the center frequency of each frequency band is determined. The Monte Carlo method is used to emit a predetermined number of sound rays from the noise source location, wherein the number of sound rays allocated to each frequency band is proportional to the sound power of the frequency band; The initial energy of each sound ray is determined based on the total sound power of the frequency band and the number of sound rays allocated to the frequency band. The initial phase is randomly assigned within the interval [0, 2π]. The initial propagation direction is determined based on the center frequency of the frequency band where the sound ray is located and a preset frequency-directivity relationship.

[0025] A broadband noise source, such as the noise of an industrial fan ranging from 20 Hz to 10,000 Hz, is decomposed into multiple standard third-octave bands. Assuming the total acoustic power of the fan is 100 watts, and a simulation is planned to emit one million sound rays, if the measured acoustic power of the third-octave band at the 1000 Hz center frequency is 15 watts, accounting for 15% of the total power, then 150,000 sound rays will be assigned to this band, providing 1000 Hz frequency information. The initial energy of each sound ray assigned to the 1000 Hz band is set to the total acoustic power of the 1000 Hz band divided by the number of sound rays, i.e., 15 watts divided by 150,000, resulting in 0.0001 watts of energy per sound ray. The initial phase of each sound ray is a randomly generated value between 0 and 2π radians, for example, 2.14 radians, ensuring the incoherent characteristics of the sound source. Figure 2 As shown. The initial emission direction of the sound ray is determined based on the directivity data corresponding to the 1000 Hz frequency. If the noise is distributed in a dipole pattern at the 1000 Hz frequency, the sound ray will have a greater probability of being emitted in a direction perpendicular to the dipole axis.

[0026] In an optional embodiment, when the sound ray interacts with the surface of an obstacle, calculating the specular reflection, frequency-dependent diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound ray based on the acoustic properties and geometry of the obstacle surface material includes: When a sound ray collides with the surface of an obstacle, the direction of specular reflection is calculated based on the surface normal and the angle of incidence at the point of collision. Based on the frequency-dependent absorption, scattering, and transmission coefficients of the surface, the incident sound energy is divided into three parts: absorbed, reflected, and transmitted. The reflected energy is distributed between specular reflection and diffuse scattering according to the scattering coefficient, and corresponding specular reflection sound rays and diffuse scattering sound rays are generated. The transmitted energy is used to generate new sound rays that pass through obstacles, and the effect of structural vibrations on the characteristics of the transmitted sound rays is taken into account.

[0027] Suppose a sound ray with a frequency of 500 Hz and an energy of 0.0001 watts is incident on a concrete wall at a 45-degree angle. Based on the acoustic parameters of the wall material at 500 Hz, its frequency-dependent absorption coefficient is set to 0.08, its scattering coefficient to 0.3, and its transmission coefficient to 0.01. When the sound ray collides with the wall, 0.000008 watts of energy are absorbed and dissipated by the wall.

[0028] The remaining energy is distributed according to the reflection and transmission coefficients. The total reflected energy is the incident energy minus the absorption and transmission portions, i.e., 0.0001 multiplied by 1 - 0.08 - 0.01 = 0.000091 watts. This portion of energy is further divided according to the scattering coefficient of 0.3. 70% of the energy, i.e., 0.0000637 watts, forms a new specularly reflected sound ray with an exit angle equal to the incident angle of 45 degrees; the remaining 30% of the energy, i.e., 0.0000273 watts, forms one or more diffusely scattered sound rays, whose directions are randomly distributed following Lambert's cosine law. 0.000001 watts of energy penetrates the wall, forming a transmitted sound ray, such as... Figure 3 As shown, its phase and energy may be finely adjusted due to the re-radiation of the wall vibration.

[0029] In an optional embodiment, when the sound path approaches the edge of an obstacle, the changes in the sound path, phase, and energy due to edge diffraction are calculated based on the unified geometric diffraction theory, including: When the distance between the sound propagation path and the edge of the obstacle is less than a preset threshold, diffraction calculation is triggered; Identify a diffraction point on the edge of the obstacle that satisfies Keller's law of diffraction, and generate a new diffracted sound ray from the diffraction point; The diffraction coefficients of the unified geometric diffraction theory are calculated based on the geometric relationship between the incident sound ray, the diffracted sound ray and the edge of the obstacle, and the sound ray frequency. Multiplying the complex amplitude of the incident sound ray by the diffraction coefficient yields the initial complex amplitude of the new diffracted sound ray.

[0030] For example, a sound ray with a frequency of 200 Hz is propagating towards a high wall, with a wavelength of approximately 1.7 meters. The preset diffraction calculation trigger threshold is twice the wavelength, i.e., 3.4 meters. When the closest distance between the propagation path of the sound ray and the edge of the top of the wall is less than 3.4 meters, it is determined that significant diffraction may occur. In this case, a diffraction point is searched on the edge of the top of the wall. This diffraction point is the shortest path point connecting the sound source, the edge, and the receiving point, satisfying a generalized form of Fermat's principle, such as... Figure 4 As shown.

[0031] Once the diffraction point is determined, a new diffracted sound ray is generated from that point and directed towards the receiving area. To determine the energy and phase of this new sound ray, a complex diffraction coefficient is calculated. The inputs to the diffraction coefficient calculation include geometric parameters such as the sound ray frequency of 200 Hz, the angle between the incident sound ray and the edge of the wall, and the angle between the newly generated diffracted sound ray and the edge of the wall. If the calculated diffraction coefficient is... Then the complex sound pressure of the incident sound ray at the diffraction point will be multiplied by the aforementioned derivation coefficient. This causes the amplitude of the new diffracted sound ray to decrease to 0.2 times the original, and the phase to lead by 0.5π radians.

[0032] In an optional embodiment, the step of deploying a virtual receiver array within the noise-sensitive area and reconstructing the time-domain sound pressure signal at each receiver location in the virtual receiver array by coherently superimposing the complex sound pressures of all arrival sound rays at each receiver includes: Each virtual receiver is defined as a receiving volume with a preset geometry and size; Acquire all sound rays whose ends fall within the receiving volume of a single receiver; Record the complex sound pressure pi, frequency fi, and total propagation time ti for each arriving sound ray i, and reconstruct the frequency domain response at the receiver by coherent superposition based on pi, fi, and ti; Perform an inverse Fourier transform on the frequency domain response to obtain the time-domain sound pressure signal at the receiver location.

[0033] To assess the noise exposure of a residential building, a virtual receiver was installed at the window of a second-floor bedroom. The virtual receiver was a spherical volume with a radius of 0.5 meters. Throughout the sound ray tracing simulation, the propagation paths of all sound rays were continuously monitored. When the endpoint of a sound ray's tracing path entered the spherical volume with a radius of 0.5 meters, the sound ray was considered to have reached the virtual receiver. Figure 5 As shown. Assume that after the simulation, a total of 8500 sound rays fall within the receiver volume. For each of these 8500 arriving sound rays, record detailed information. For example, sound ray number 101, with a frequency of 400 Hz, after multiple reflections and diffractions, has a complex sound pressure level of [value missing]. The total propagation time is 0.2 seconds. All sound ray is grouped according to its frequency, and the complex sound pressure of all corresponding sound ray at each frequency is vector-summed. Coherent superposition takes into account the interference effect caused by phase difference, constructing the complete frequency domain response of the virtual receiver location. By applying inverse Fourier transform, the complex spectral signal is converted into a real sound pressure waveform that varies with time, i.e., the time domain signal.

[0034] In an optional embodiment, the calculation of psychoacoustic indices, including at least loudness, sharpness, roughness, and fluctuation intensity, based on the time-domain sound pressure signals at each receiver location in the virtual receiver array, and the fusion of these psychoacoustic indices into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect using a preset weighted model, includes: Calculate the loudness, sharpness, roughness, and wave intensity values ​​of the time-domain sound pressure signal according to international or national standards; The calculated psychoacoustic index values ​​were normalized. The normalized psychoacoustic index values ​​are integrated into a comprehensive risk index through a weighted model. The weight coefficients in the weighted model are pre-set based on expert knowledge, empirical data, and / or specific application scenarios.

[0035] Using the time-domain sound pressure signal of the window position reconstructed in the previous step, the loudness value was calculated to be 65 sonos according to the ISO 532-1 standard, and the sharpness was calculated to be 1.8 acum, the roughness to be 0.5 asper, and the ripple intensity to be 0.9 vacil according to relevant acoustic standards. These values ​​quantify the subjective perception of the human ear regarding the loudness of the sound, the irritation of the high-frequency components, and the annoyance of fast and slow amplitude modulation, respectively.

[0036] For comprehensive evaluation, psychoacoustic index values ​​with different units and dimensions need to be normalized to a dimensionless range of 0 to 1. For example, if 65 sonic values ​​fall within the preset evaluation range of 0 to 100 sonic values, their normalized value is 0.65. A comprehensive risk index is calculated based on a preset weighted model. Assuming that experts have set weights for a specific scenario as loudness 0.5, sharpness 0.3, roughness 0.1, and volatility 0.1, the comprehensive risk index will be calculated through a weighted summation, for example, 0.65 multiplied by 0.5 plus other normalized indices multiplied by their corresponding weights, resulting in a single value, such as... Figure 6 As shown, this allows for the quantification of overall acoustic discomfort or risk level.

[0037] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, compact disc read-only memory (CD-ROM), optical storage, etc.) containing computer-usable program code.

[0038] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0039] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for analyzing the NIMBY (Not In My Backyard) effect risk in noise-sensitive areas, characterized in that, Includes the following steps: Obtain the sound power spectrum of the noise source and a three-dimensional scene model including noise-sensitive areas and obstacles; based on the sound power spectrum and frequency-directivity relationship, generate an initial set of sound rays carrying initial energy, phase, and frequency information; In the three-dimensional scene model, the propagation path of the sound rays is traced. Based on the atmospheric turbulence model, the phase perturbation and amplitude fluctuation caused by atmospheric inhomogeneity to the complex amplitude of the sound rays are calculated. When the sound rays interact with the surface of the obstacle, the specular reflection, frequency-related diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound rays are calculated according to the acoustic properties and geometric structure of the obstacle surface material. When the sound path approaches the edge of an obstacle, the changes in sound path, phase, and energy caused by edge diffraction are calculated based on the unified geometric diffraction theory. A virtual receiver array is deployed within the noise-sensitive area. The time-domain sound pressure signal of each receiver location in the virtual receiver array is reconstructed by coherently superimposing the complex sound pressures of all arrival sound rays at each receiver location. Based on the time-domain sound pressure signals at each receiver location in the virtual receiver array, psychoacoustic indices including at least loudness, sharpness, roughness, and fluctuation intensity are calculated, and the psychoacoustic indices are fused into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect through a preset weighted model.

2. The method according to claim 1, characterized in that, The step of generating an initial set of sound rays carrying initial energy, phase, and frequency information based on the sound power spectrum and frequency-directivity relationship includes: The acoustic power spectrum is divided into multiple frequency bands, and the center frequency of each frequency band is determined. The Monte Carlo method is used to emit a predetermined number of sound rays from the noise source location, wherein the number of sound rays allocated to each frequency band is proportional to the sound power of the frequency band; The initial energy of each sound ray is determined based on the total sound power of the frequency band and the number of sound rays allocated to the frequency band. The initial phase is randomly assigned within the interval [0, 2π]. The initial propagation direction is determined based on the center frequency of the frequency band where the sound ray is located and a preset frequency-directivity relationship.

3. The method according to claim 1, characterized in that, When sound rays interact with the surface of an obstacle, the method calculates specular reflection, frequency-dependent diffuse scattering, transmission, and re-radiation caused by structural vibrations of the sound rays based on the acoustic properties and geometry of the obstacle surface material, including: When a sound ray collides with the surface of an obstacle, the direction of specular reflection is calculated based on the surface normal and the angle of incidence at the point of collision. Based on the frequency-dependent absorption, scattering, and transmission coefficients of the surface, the incident sound energy is divided into three parts: absorbed, reflected, and transmitted. The reflected energy is distributed between specular reflection and diffuse scattering according to the scattering coefficient, and corresponding specular reflection sound rays and diffuse scattering sound rays are generated. The transmitted energy is used to generate new sound rays that pass through obstacles, and the effect of structural vibrations on the characteristics of the transmitted sound rays is taken into account.

4. The method according to claim 1, characterized in that, When the sound path approaches the edge of an obstacle, based on the unified geometric diffraction theory, the changes in the sound path, phase, and energy caused by edge diffraction are calculated, including: When the distance between the sound propagation path and the edge of the obstacle is less than a preset threshold, diffraction calculation is triggered; Identify a diffraction point on the edge of the obstacle that satisfies Keller's law of diffraction, and generate a new diffracted sound ray from the diffraction point; The diffraction coefficients of the unified geometric diffraction theory are calculated based on the geometric relationship between the incident sound ray, the diffracted sound ray and the edge of the obstacle, and the sound ray frequency. Multiplying the complex amplitude of the incident sound ray by the diffraction coefficient yields the initial complex amplitude of the new diffracted sound ray.

5. The method according to claim 1, characterized in that, The method involves deploying a virtual receiver array within the noise-sensitive area and reconstructing the time-domain sound pressure signal at each receiver location in the virtual receiver array by coherently superimposing the complex sound pressures of all arriving sound rays at each receiver. Each virtual receiver is defined as a receiving volume with a preset geometry and size; Acquire all sound rays whose ends fall within the receiving volume of a single receiver; Record the complex sound pressure pi, frequency fi, and total propagation time ti for each arriving sound ray i, and reconstruct the frequency domain response at the receiver by coherent superposition based on pi, fi, and ti; Perform an inverse Fourier transform on the frequency domain response to obtain the time-domain sound pressure signal at the receiver location.

6. The method according to claim 1, characterized in that, The method calculates psychoacoustic indices, including at least loudness, sharpness, roughness, and fluctuation intensity, based on the time-domain sound pressure signals from each receiver location in the virtual receiver array. These indices are then fused into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect using a pre-defined weighted model. Calculate the loudness, sharpness, roughness, and wave intensity values ​​of the time-domain sound pressure signal according to international or national standards; The calculated psychoacoustic index values ​​were normalized. The normalized psychoacoustic index values ​​are integrated into a comprehensive risk index through a weighted model. The weight coefficients in the weighted model are pre-set based on expert knowledge, empirical data, and / or specific application scenarios.

7. A risk assessment system for the NIMBY (Not In My Backyard) effect in noise-sensitive areas, characterized in that, Includes the following units: The initial sound ray generation unit acquires the sound power spectrum of the noise source and a three-dimensional scene model containing noise-sensitive areas and obstacles; based on the sound power spectrum and frequency-directivity relationship, it generates an initial sound ray set carrying initial energy, phase, and frequency information. The influence calculation unit tracks the sound propagation path in the three-dimensional scene model, and calculates the phase disturbance and amplitude fluctuation caused by atmospheric inhomogeneity to the complex amplitude of the sound ray based on the atmospheric turbulence model; when the sound ray interacts with the surface of the obstacle, it calculates the specular reflection, frequency-related diffuse scattering, transmission, and re-radiation caused by structural vibration of the sound ray according to the acoustic properties and geometric structure of the obstacle surface material. When the sound path approaches the edge of an obstacle, the changes in sound path, phase, and energy caused by edge diffraction are calculated based on the unified geometric diffraction theory. The time-domain sound pressure signal reconstruction unit deploys a virtual receiver array within the noise-sensitive area and reconstructs the time-domain sound pressure signal at each receiver location in the virtual receiver array by coherently superimposing the complex sound pressures of all arrival sound rays at each receiver. The risk index generation unit calculates psychoacoustic indices, including at least loudness, sharpness, roughness, and fluctuation intensity, based on the time-domain sound pressure signals at each receiver location in the virtual receiver array. Then, it integrates these psychoacoustic indices into a comprehensive risk index representing the NIMBY (Not In My Backyard) effect through a preset weighting model.

8. The system according to claim 7, characterized in that, The step of generating an initial set of sound rays carrying initial energy, phase, and frequency information based on the sound power spectrum and frequency-directivity relationship includes: The acoustic power spectrum is divided into multiple frequency bands, and the center frequency of each frequency band is determined. The Monte Carlo method is used to emit a predetermined number of sound rays from the noise source location, wherein the number of sound rays allocated to each frequency band is proportional to the sound power of the frequency band; The initial energy of each sound ray is determined based on the total sound power of the frequency band and the number of sound rays allocated to the frequency band. The initial phase is randomly assigned within the interval [0, 2π]. The initial propagation direction is determined based on the center frequency of the frequency band where the sound ray is located and a preset frequency-directivity relationship.

9. The system according to claim 7, characterized in that, When sound rays interact with the surface of an obstacle, the method calculates specular reflection, frequency-dependent diffuse scattering, transmission, and re-radiation caused by structural vibrations of the sound rays based on the acoustic properties and geometry of the obstacle surface material, including: When a sound ray collides with the surface of an obstacle, the direction of specular reflection is calculated based on the surface normal and the angle of incidence at the point of collision. Based on the frequency-dependent absorption, scattering, and transmission coefficients of the surface, the incident sound energy is divided into three parts: absorbed, reflected, and transmitted. The reflected energy is distributed between specular reflection and diffuse scattering according to the scattering coefficient, and corresponding specular reflection sound rays and diffuse scattering sound rays are generated. The transmitted energy is used to generate new sound rays that pass through obstacles, and the effect of structural vibrations on the characteristics of the transmitted sound rays is taken into account.

10. The system according to claim 7, characterized in that, When the sound path approaches the edge of an obstacle, based on the unified geometric diffraction theory, the changes in the sound path, phase, and energy caused by edge diffraction are calculated, including: When the distance between the sound propagation path and the edge of the obstacle is less than a preset threshold, diffraction calculation is triggered; Identify a diffraction point on the edge of the obstacle that satisfies Keller's law of diffraction, and generate a new diffracted sound ray from the diffraction point; The diffraction coefficients of the unified geometric diffraction theory are calculated based on the geometric relationship between the incident sound ray, the diffracted sound ray and the edge of the obstacle, and the sound ray frequency. Multiplying the complex amplitude of the incident sound ray by the diffraction coefficient yields the initial complex amplitude of the new diffracted sound ray.

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