Sound effect optimization method and device based on coaxial speaker echo wall speaker

Abstract

The present invention relates to the technical field of sound effect optimization, and discloses a sound effect optimization method and device based on a coaxial speaker whispering gallery speaker. The method comprises: performing acoustic response measurement and acoustic feature analysis on the coaxial speaker whispering gallery speaker to obtain a frequency domain acoustic response characteristic curve; performing acoustic partition calculation on the internal space of the coaxial speaker whispering gallery speaker to obtain spatial layout parameters of an acoustic processing unit; performing acoustic center positioning calculation on the coaxial speaker to obtain spatial coordinate parameters and axial inclination parameters of the coaxial speaker; performing sound reflection angle calculation and material combination optimization on the inner wall structure of the whispering gallery speaker to obtain inner wall geometric curvature parameters and box material lamination parameters; performing sound pressure level frequency response curve analysis and sound phase positioning accuracy measurement on the inner wall geometric curvature parameters and box material lamination parameters to obtain speaker acoustic performance verification data. The present invention ensures the uniformity of the sound field inside the speaker, thereby improving the acoustic performance of the speaker.

Description

Technical Field

[0001] The present invention relates to the technical field of sound effect optimization, and in particular to a sound effect optimization method and device based on a coaxial speaker whispering gallery speaker. Background Art

[0002] As an important part of high-fidelity audio systems, coaxial speaker sound bar speakers have received extensive attention in the field of audio reproduction due to the consistency of their sound source points and the omnidirectional characteristics of sound wave radiation. However, traditional speaker design methods mainly rely on experience accumulation and repeated experiments, lacking systematic acoustic optimization theory guidance, resulting in difficulty in achieving ideal sound phase positioning accuracy and frequency band response characteristics.

[0003] In practical applications, due to the highly nonlinear and multi-parameter coupling characteristics of the acoustic system, how to accurately establish the mapping relationship between acoustic parameters and speaker performance, and how to effectively deal with the uncertainty in the measurement data, are still key issues that need to be solved. In addition, the acoustic processing design inside the sound bar directly affects the uniformity of the sound field and the stability of the sound image positioning. Traditional design methods make it difficult to accurately grasp the optimal layout of the acoustic processing unit, and lack systematic optimization methods for the inner wall structure and material combination, which seriously restricts the improvement of the overall acoustic performance of the speaker. Summary of the invention

[0004] The present invention provides a method and device for optimizing the sound effect of a coaxial speaker whispering gallery speaker. The present invention ensures the uniformity of the sound field inside the speaker, thereby improving the acoustic performance of the speaker.

[0005] In a first aspect, the present invention provides a method for optimizing sound effects based on a coaxial speaker sound bar speaker, the method comprising:

[0006] The acoustic response measurement and acoustic characteristics analysis of the coaxial speaker echo bar speaker are carried out to obtain the frequency domain acoustic response characteristic curve;

[0007] Based on the frequency domain acoustic response characteristic curve, an acoustic partition calculation is performed on the internal space of the coaxial speaker whispering gallery speaker to obtain the spatial layout parameters of the acoustic processing unit;

[0008] According to the spatial arrangement parameters of the acoustic processing unit, the acoustic center positioning calculation is performed on the coaxial speaker to obtain the spatial coordinate parameters and axial inclination parameters of the coaxial speaker;

[0009] Based on the spatial coordinate parameters and the axial inclination parameters, the sound reflection angle of the inner wall structure of the whispering gallery speaker is calculated and the material combination is optimized to obtain the inner wall geometric curvature parameters and the box material lamination parameters;

[0010] The sound pressure level frequency response curve analysis and the sound phase positioning accuracy measurement are performed on the inner wall geometric curvature parameters and the box material lamination parameters to obtain the speaker acoustic performance verification data.

[0011] In a second aspect, the present invention provides a sound effect optimization device based on a coaxial speaker echo gallery speaker, and the sound effect optimization device based on a coaxial speaker echo gallery speaker comprises:

[0012] The measurement module is used to measure the acoustic response and analyze the acoustic characteristics of the coaxial speaker echo bar speaker to obtain the frequency domain acoustic response characteristic curve;

[0013] A calculation module, for performing acoustic partition calculation on the internal space of the coaxial speaker whispering gallery speaker box based on the frequency domain acoustic response characteristic curve, and obtaining the spatial arrangement parameters of the acoustic processing unit;

[0014] A positioning module, used to perform acoustic center positioning calculation on the coaxial speaker according to the spatial arrangement parameters of the acoustic processing unit, and obtain the spatial coordinate parameters and axial inclination parameters of the coaxial speaker;

[0015] An optimization module, for calculating the sound reflection angle and optimizing the material combination of the inner wall structure of the whispering gallery speaker based on the spatial coordinate parameters and the axial inclination parameters, so as to obtain the inner wall geometric curvature parameters and the box material lamination parameters;

[0016] The analysis module is used to perform sound pressure level frequency response curve analysis and sound phase positioning accuracy measurement on the inner wall geometric curvature parameters and the box material lamination parameters to obtain speaker acoustic performance verification data.

[0017] The third aspect of the present invention provides a computer device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the computer device executes the above-mentioned sound optimization method based on the coaxial speaker echo wall speaker.

[0018] A fourth aspect of the present invention provides a computer-readable storage medium, which stores instructions. When the computer-readable storage medium is run on a computer, it enables the computer to execute the above-mentioned sound optimization method based on the coaxial speaker echo bar speaker.

[0019] In the technical solution provided by the present invention, a Bayesian reasoning model is introduced to perform acoustic feature analysis, and the prior probability distribution and likelihood function of acoustic parameters are established in combination with the sound phase positioning measurement data and the frequency band response measurement data. The boundary element analysis method is used to establish the sound pressure transfer equation, and the frequency domain acoustic response characteristic curve is obtained by frequency domain conversion, thereby realizing the accurate description and quantitative analysis of the acoustic characteristics of the speaker. Based on the acoustic partitioning calculation technology, an efficient acoustic processing unit is formed by reasonably arranging the sound absorbing materials and the acoustic reflector, thereby ensuring the uniformity of the sound field inside the speaker. Through the sound wave propagation path analysis and the acoustic center positioning calculation, the optimal installation position and inclination parameters of the coaxial speaker are accurately determined, thereby ensuring the accuracy of the sound image positioning. By utilizing the sound reflection angle calculation and the material combination optimization technology, the optimal combination of the inner wall geometric curvature parameters and the box material lamination parameters is obtained, thereby improving the acoustic performance of the speaker. The acoustic posterior probability calculation method is used to perform performance verification, and a complete speaker acoustic performance evaluation system is established through the sound pressure level frequency response curve analysis and the sound phase positioning accuracy measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0021] Figure 1 Schematic diagram of the steps of the sound effect optimization method based on the coaxial speaker echo bar speaker in an embodiment of the present invention;

[0022] Figure 2 It is a structural schematic diagram of a sound effect optimization device based on a coaxial speaker whispering gallery speaker in an embodiment of the present invention;

[0023] Figure 3 It is a schematic block diagram of the structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The embodiments of the present invention provide a method and device for optimizing the sound effects of a coaxial speaker sound bar speaker. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the sound effect optimization method based on the coaxial speaker echo bar speaker in the embodiment of the present invention includes:

[0026] Step S1, performing acoustic response measurement and acoustic characteristic analysis on the coaxial speaker echo gallery speaker to obtain a frequency domain acoustic response characteristic curve;

[0027] It is understandable that the execution subject of the present invention can be a sound effect optimization device based on a coaxial speaker sound bar, or a terminal or a server, which is not limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0028] Specifically, multi-point acoustic measurements and time-domain sampling are performed on the coaxial speaker echo bar. Through high-precision microphone arrays and professional audio equipment, the acoustic output signals of the speakers at different spatial positions are captured, and the collected sound pressure signals are sampled in the time domain at high frequency to form a time-domain sound pressure response sequence, recording the sound pressure changes of the speakers at different times. The time-domain sound pressure response sequence is subjected to discrete Fourier transform to convert the time-domain signal to the frequency domain. In the frequency domain, the frequency components of the signal are displayed, and unified frequency band response data is generated through standardization processing to reflect the acoustic characteristics of the coaxial speaker echo bar at different frequencies, including its frequency response range, resonant frequency and energy distribution. Acoustic cross-correlation analysis is performed on the standardized frequency band response data. By comparing the sound wave phase and time delay relationship between different measurement points, the spatial positioning information of the speaker sound source is extracted. By analyzing the acoustic cross-correlation data, the distribution characteristics of the sound source in space are determined, and these data are mapped to three-dimensional spatial coordinates. Based on this mapping, the energy distribution in the sound field is quantified by using the spatial integral operation of the sound image localization surface to obtain the sound phase localization measurement data, which reflects the localization accuracy of the sound source of the speaker and the consistency of the sound field. The sound phase localization measurement data is combined with the standardized frequency band response data and input into the Bayesian reasoning model to construct a prior distribution function. The Bayesian reasoning model combines the existing measurement data with empirical knowledge by introducing the statistical probability method to form a prior probability distribution of acoustic parameters. This distribution reflects the probability density of the acoustic characteristic parameters of the speaker within different possible value ranges. The prior probability distribution of acoustic parameters is obtained by calculating the probability density of the prior distribution function. The prior probability distribution of acoustic parameters is matched with the existing acoustic theoretical model to construct an acoustic likelihood function model. The matching process combines theoretical and measured data, and adjusts the model parameters to make it consistent with the actual acoustic characteristics. After the acoustic likelihood function model is constructed, a normalization coefficient operation is performed on it to ensure that the function can correctly reflect the relative possibility of acoustic parameters and form an acoustic likelihood function. According to the prior probability distribution of acoustic parameters and the acoustic likelihood function, the sound field simulation calculation is performed by combining boundary element analysis and frequency domain conversion technology. Boundary element analysis establishes acoustic boundary conditions on the inner and outer surfaces of the speaker, calculates the propagation path and interference characteristics of the sound wave inside the speaker, and thus reflects the acoustic structural performance of the speaker. Frequency domain conversion converts time domain data into frequency domain characteristics, showing the response characteristics of the speaker at different frequencies. Finally, the frequency domain acoustic response characteristic curve is obtained.

[0029] Based on the prior probability distribution of acoustic parameters and the acoustic likelihood function, a three-dimensional geometric model of the coaxial speaker echo bar speaker is established to represent the physical structure of the speaker, including the speaker unit, the inner wall geometry, and the details of the shell material. The three-dimensional geometric model is discretized and divided into a large number of finite boundary units by refining the geometric structure to generate boundary element mesh data. Acoustic boundary conditions are assigned to the boundary element mesh data to reflect the acoustic propagation characteristics in the actual speaker. The sound pressure transfer matrix equation is constructed by assigning a specific sound pressure value or acoustic velocity condition to each grid node. The transfer matrix equation describes the association between different acoustic nodes. The transfer matrix is ​​assembled according to the number of the acoustic node to form a global solution model. By solving the model, the numerical solutions of the sound pressure distribution inside and outside the speaker are obtained. These numerical solutions reflect the propagation path of the sound wave in the space inside and outside the speaker and the law of sound pressure change. Based on the numerical solution of the sound pressure distribution, boundary integral processing and sound field reconstruction are performed. The boundary integral processing summarizes the local acoustic characteristics into the overall sound field performance by numerically integrating the acoustic parameters of the grid unit. Through the sound field reconstruction technology, the numerical solution is mapped from the discrete domain back to the continuous domain to generate a complete time domain sound pressure response function. The time domain sound pressure response function is subjected to fast Fourier transform and frequency band decomposition to convert the time domain signal into a frequency domain signal and generate frequency band acoustic response data. The frequency band acoustic response data is subjected to transfer function synthesis and polar coordinate transformation to extract the phase-frequency characteristic data. Transfer function synthesis is to generate a function that describes the dynamic characteristics of the system by comprehensive calculation of the frequency band data; while polar coordinate transformation can intuitively represent the phase and amplitude characteristics of the acoustic response. Phase correction calculation and frequency domain compensation analysis are performed using the phase-frequency characteristic data. Phase correction aims to adjust the phase consistency of the signals in each frequency band of the speaker and reduce the impact of phase distortion on sound positioning. Frequency domain compensation improves the uniformity of frequency domain performance by optimizing the energy distribution between frequency bands. After this step, the frequency domain compensation coefficient is obtained, which is used to correct the frequency response performance of the speaker. Based on the frequency domain compensation coefficient, the amplitude-frequency characteristic analysis is performed. By calculating the frequency domain data, a frequency domain acoustic response characteristic curve of the speaker in the entire frequency range is generated, showing the sound pressure amplitude and phase changes of the speaker at different frequencies.

[0030] Step S2, based on the frequency domain acoustic response characteristic curve, performing acoustic partition calculation on the internal space of the coaxial speaker echo gallery speaker to obtain the spatial layout parameters of the acoustic processing unit;

[0031] Specifically, the frequency domain acoustic response characteristic curve is analyzed for sound pressure distribution and divided into frequency bands. The focus of sound pressure distribution analysis is to locate the high-pressure area and low-pressure area in the sound field, so as to identify the energy concentration point of the sound wave, while the frequency band division divides the overall acoustic response into specific frequency intervals, so as to analyze the sound field characteristics of different frequency bands more targeted. Through this step, the frequency band sound field data is generated to reflect the propagation characteristics of the sound wave inside the speaker and the energy distribution of different frequency bands. The sound reflection area is identified based on the frequency band sound field data. By analyzing the reflection path and density of the sound wave on the inner wall of the speaker, the area with the most frequent sound reflection is found, and the data of the sound reflection intensive area is obtained. These areas directly determine the distribution of standing waves inside the speaker and the unevenness of the sound field. Acoustic zoning planning and spatial mapping are performed for the sound reflection intensive area. By combining the sound reflection area with the internal geometric structure of the speaker, the optimal layout position coordinates of the sound absorbing material are calculated, so as to effectively reduce the reflection intensity of the sound wave in these areas, while improving the clarity and balance of the sound. Based on the coordinates of the arrangement position of the sound-absorbing material, the spatial orientation of the acoustic reflector is calculated. The function of the reflector is to redirect the sound waves at the appropriate position to optimize the diffusion and coverage of the sound field. At this stage, the calculation needs to consider not only the physical size and inclination of the reflector, but also to ensure that its arrangement does not interfere with the functions of other acoustic units. After calculation, the specific spatial orientation data of the reflector is obtained, including the three-dimensional coordinate position and the installation angle. By inputting the arrangement position of the sound-absorbing material and the spatial orientation data of the reflector into the finite difference calculation model, the acoustic boundary impedance distribution inside the speaker is obtained, reflecting the absorption and reflection characteristics of the inner wall of the speaker to the sound waves in different areas. In order to optimize the boundary design, the frequency response analysis of the acoustic boundary impedance distribution is carried out to obtain the boundary acoustic characteristic function. The combination design of the acoustic processing unit is carried out according to the boundary acoustic characteristic function. Based on the characteristic function, the unit spacing parameters are optimized to ensure that the role of each acoustic unit can be maximized. At the same time, through the spatial uniformity analysis, the arrangement between the units is adjusted to make it more reasonable in spatial distribution, avoid the phenomenon of excessive concentration or sparseness of the local sound field, form a processing unit layout plan, and define the position and arrangement of each acoustic unit. Input the processing unit layout plan into the boundary element model to perform sound field superposition calculation. Simulate the sound field effect of all units in the combined working state, and obtain the comprehensive performance data of the sound field inside the speaker by calculating the combined acoustic effect function. Perform frequency response characteristic analysis on the combined acoustic effect function, optimize the unit combination parameters, and obtain the optimized acoustic unit combination parameters. Based on the optimized unit combination parameters, perform spatial coordinate transformation to obtain the three-dimensional layout coordinates of each acoustic processing unit. In order to ensure that these arrangements can meet the physical limitations of the actual speaker design, the three-dimensional layout coordinates are geometrically constrained. Through constraints such as material thickness, internal space size and installation process, the spatial layout parameters of the acoustic processing unit suitable for the actual speaker design are obtained.

[0032] Step S3, performing acoustic center positioning calculation on the coaxial speaker according to the spatial arrangement parameters of the acoustic processing unit, and obtaining the spatial coordinate parameters and axial inclination parameters of the coaxial speaker;

[0033] Specifically, an acoustic coordinate system is established based on the spatial arrangement parameters of the acoustic processing unit. Through the acoustic coordinate system, a complete geometric modeling of the sound field is performed in three-dimensional space, and the acoustic energy distribution function is used to describe the energy intensity distribution of sound waves at different positions. By performing gradient analysis on the acoustic energy distribution function, an acoustic energy flow vector field is obtained, which is used to characterize the direction and intensity changes of sound energy propagating in space. By performing divergence calculation on the acoustic energy flow vector field, the sound source radiation field distribution inside the speaker is generated. The sound source radiation field distribution reflects the divergence mode of the speaker sound waves inside and around the speaker. The sound source radiation field distribution is decomposed by frequency band, and the entire frequency domain range is divided into multiple frequency bands. The sound field data of each frequency band is extracted separately to form sub-band sound field data. Based on the sub-band sound field data, the sound wave propagation path is tracked and analyzed. The sound wave propagation path tracking calculates the propagation trajectory of the sound wave from the sound source to the listening position and draws a sound wave propagation trajectory diagram. The sound wave propagation trajectory diagram is path optimized to eliminate redundant reflection paths and standing wave interference to obtain the main sound wave propagation path. The main sound wave propagation path represents the propagation route where the sound wave energy is most concentrated. The main sound wave propagation path is subjected to spatial geometric analysis to locate the convergence point of the sound wave. By calculating the spatial coordinates of the sound wave convergence point, it is defined as the acoustic center of the coaxial speaker, and the initial acoustic center coordinates of the speaker are determined. Based on the acoustic center coordinates, a local coordinate system is established to analyze the radiation directivity of the speaker. In the local coordinate system, the intensity distribution diagram of the sound field is obtained by calculating the sound wave energy density distribution, and the main axis direction of the sound wave radiation is determined by the main direction analysis. The determined sound wave radiation main axis is transformed with the global space reference coordinate system to calculate the initial axial angle parameter of the speaker. In order to ensure the accuracy of the directivity, the axial angle parameter is spatially projected to eliminate the error in the coordinate transformation and generate the axial inclination data. The axial inclination data represents the angle between the main radiation direction of the speaker and the horizontal plane. By calculating the directivity of the sound wave on the axial inclination data, the directivity factor is obtained to quantify the sound radiation capability of the speaker at different angles. The directivity factor is optimized to improve the directivity and sound coverage of the speaker and obtain the optimal axial inclination parameter. After obtaining the optimal inclination parameters, the final coaxial speaker space coordinate parameters and axial inclination parameters are calculated by combining the initial acoustic center coordinates and transforming the coordinate system.

[0034] Step S4: Based on the spatial coordinate parameters and the axial inclination parameters, the sound reflection angle of the inner wall structure of the whispering gallery speaker is calculated and the material combination is optimized to obtain the inner wall geometric curvature parameters and the box material lamination parameters;

[0035] Specifically, a sound wave reflection model is established based on spatial coordinate parameters and axial inclination parameters, which simulates the propagation and reflection behavior of sound waves on the inner wall of the speaker. The incident angle function of the sound wave is calculated through the law of acoustic reflection. The incident angle function is the change of the incident angle when the sound wave intersects the inner wall at different positions. Its specific form is closely related to the geometric shape of the inner wall and the propagation path of the sound wave. The spatial distribution of the sound wave incident angle function is analyzed, and the reflection angle distribution function is constructed to reflect the sound wave reflection characteristics of the inner wall in different areas. The reflection angle distribution function is surface fitted to accurately describe the geometric shape of the inner wall surface. The result of the surface fitting needs to meet the requirements of curvature continuity, so the curvature continuity analysis is performed on the fitted surface to evaluate the smoothness and transition characteristics of the surface. On this basis, the surface optimization calculation is performed in combination with the curvature continuity parameter, and the geometric characteristics of the inner wall surface are analyzed using differential geometry analysis tools to obtain the optimized inner wall geometric curvature parameters. These parameters describe the specific geometric form of the inner wall, including curvature change, surface smoothness and its influence on the sound wave propagation path. The optimized inner wall geometric curvature parameters are acoustically analyzed, and the acoustic boundary integral method is used to calculate the acoustic energy flow density distribution of the inner wall, and the acoustic energy attenuation data is calculated based on this. The acoustic energy attenuation data reflects the energy loss of sound waves on the inner wall and is an important basis for optimizing the inner wall material combination. According to the acoustic energy attenuation data, material impedance matching analysis is performed, and a material combination sequence is generated by selecting materials with different acoustic impedances and optimizing their arrangement order. The sound wave absorption coefficient is calculated for the material combination sequence to obtain the material sound absorption characteristic function. The sound absorption characteristic function describes the sound absorption effect of the material in different frequency ranges. The sound absorption characteristic function is decomposed into multiple frequency bands, and the optimization combination analysis is performed for each frequency band to design the most suitable laminated structure scheme for the performance of the speaker. The laminated structure scheme clarifies the specific arrangement and layer thickness of each material in the inner wall. Based on the laminated structure scheme, acoustic transmission calculation and frequency response analysis are performed to evaluate the impact of the material combination on the speaker performance, and the laminated combination parameters are optimized accordingly. The laminated combination parameters reflect the transmission characteristics and sound absorption performance of the material combination in the frequency domain. After the optimization is completed, the optimized lamination combination parameters are matched with the inner wall geometric curvature parameters to form the final lamination parameters of the cabinet material. Structural constraints are imposed on the cabinet material lamination parameters to ensure that the optimization results meet the manufacturing process and physical limitations of the speaker. In the process of structural constraints, practical factors such as material strength, thickness restrictions, processing difficulty and cost are considered. After constraint adjustment, the optimized inner wall geometric curvature parameters and cabinet material lamination parameters are finally obtained.

[0036] Step S5: Perform sound pressure level frequency response curve analysis and sound phase positioning accuracy measurement on the inner wall geometric curvature parameters and the box material lamination parameters to obtain speaker acoustic performance verification data.

[0037] Specifically, the inner wall geometric curvature parameters and the box material lamination parameters are input into the Bayesian inference model. By constructing the posterior distribution function, the Bayesian method is used to combine the prior distribution of acoustic parameters with the experimental measurement data to calculate the posterior probability density of acoustic parameters. The posterior probability density function reflects the possibility distribution of each acoustic parameter under the known measurement data and the acoustic theory assumptions. The optimal values ​​of the acoustic parameters are determined by performing maximum likelihood analysis on the posterior probability density function. These optimal values ​​are the parameter combinations that best match the theoretical model with the actual acoustic performance. The optimal values ​​of the acoustic parameters are applied to the acoustic response simulation, and the simulation results are refined by frequency band decomposition to generate sub-band performance data to describe the acoustic response characteristics of the speaker in different frequency ranges. The sound pressure distribution data of the speaker in space is obtained by measuring the sound pressure level based on the sub-band performance data. The sound pressure distribution data is an important reflection of the sound field performance. The measured frequency response curve is generated by analyzing the spectrum of these data. The measured frequency response curve is smoothed to eliminate high-frequency noise and random errors in the measurement process, and the sound pressure level frequency response characteristic curve is obtained. The sound pressure level frequency response characteristic curve is divided into multiple frequency bands according to the frequency range to generate frequency band response data. After the frequency band response data is input into the sound phase localization model, the sound source localization characteristics are calculated. The sound phase localization model generates a sound image spatial position function by analyzing the distribution and propagation characteristics of the sound generated by the speaker in space. The sound image spatial position function describes the specific position distribution of the sound source in three-dimensional space, and through three-dimensional reconstruction, the actual accuracy of the sound phase localization is intuitively presented. The three-dimensional reconstruction results reflect the sound phase localization performance of the speaker in different frequency bands. Based on the sound phase localization accuracy data, statistical analysis is performed to generate positioning accuracy evaluation parameters, including positioning error distribution, average error value and maximum deviation value, which can quantitatively describe the accuracy of the speaker in sound image localization. By combining the positioning accuracy evaluation parameters with the sound pressure level frequency response characteristic curve, a comprehensive evaluation is conducted to comprehensively measure the acoustic performance of the speaker, including its frequency response uniformity, positioning accuracy, sound field coverage, and frequency band balance, and ultimately generate speaker acoustic performance verification data.

[0038] In the embodiment of the present invention, the acoustic characteristic analysis is performed by introducing the Bayesian reasoning model, and the prior probability distribution and likelihood function of the acoustic parameters are established by combining the sound phase positioning measurement data and the frequency band response measurement data. The sound pressure transfer equation is established by using the boundary element analysis method, and the frequency domain acoustic response characteristic curve is obtained by frequency domain conversion, thereby realizing the accurate description and quantitative analysis of the acoustic characteristics of the speaker. Based on the acoustic partitioning calculation technology, an efficient acoustic processing unit is formed by reasonably arranging the sound absorbing materials and the acoustic reflector, thereby ensuring the uniformity of the sound field inside the speaker. Through the sound wave propagation path analysis and the acoustic center positioning calculation, the optimal installation position and inclination parameters of the coaxial speaker are accurately determined, thereby ensuring the accuracy of the sound image positioning. By using the sound reflection angle calculation and the material combination optimization technology, the optimal combination of the inner wall geometric curvature parameters and the box material lamination parameters is obtained, thereby improving the acoustic performance of the speaker. The acoustic posterior probability calculation method is used for performance verification, and a complete speaker acoustic performance evaluation system is established through the sound pressure level frequency response curve analysis and the sound phase positioning accuracy measurement.

[0039] In a specific embodiment, the process of executing step S1 may specifically include the following steps:

[0040] Perform multi-point acoustic measurement and time-domain sampling on the coaxial speaker echo bar to obtain the time-domain sound pressure response sequence, and perform discrete Fourier transform on the time-domain sound pressure response sequence to obtain standardized frequency band response data;

[0041] Performing acoustic cross-correlation analysis on the standardized frequency band response data to obtain sound source spatial localization data, and performing three-dimensional coordinate mapping and sound image localization surface spatial integration operations on the sound source spatial localization data to obtain sound phase localization measurement data;

[0042] Input the sound phase localization measurement data and the standardized frequency band response data into the Bayesian inference model, construct the Bayesian prior distribution function, and obtain the acoustic parameter prior probability distribution through probability density calculation;

[0043] The acoustic parameter prior probability distribution is matched with the acoustic theoretical model to obtain an acoustic likelihood function model, and the acoustic likelihood function model is normalized to obtain an acoustic likelihood function;

[0044] According to the prior probability distribution of acoustic parameters and the acoustic likelihood function, boundary element analysis and frequency domain conversion are performed on the coaxial speaker echo bar speaker to obtain the frequency domain acoustic response characteristic curve.

[0045] Specifically, a high-precision microphone array is used to perform multi-point acoustic measurements on the coaxial speaker echo bar. measurement points, each of which collects the time domain sound pressure signal through a microphone, denoted as ,in , represents different measurement points, is the time variable, These sampling signals record the time-domain acoustic output of the speaker at different spatial points, forming a time-domain sound pressure response sequence . Perform discrete Fourier transform. The formula for Fourier transform is: ;

[0046] in, is the frequency, is an imaginary unit. The discrete Fourier transform discretizes the above formula into: ;

[0047] in, is the number of sampling points, is the frequency index, Indicates The measurement point is In order to eliminate the systematic errors between different measurement points, the frequency domain data is standardized to form standardized frequency band response data. , whose expression is: ;

[0048] This normalization process ensures that the frequency domain data of each measurement point are compared at the same scale. Acoustic cross-correlation analysis is performed on the normalized frequency band response data. The cross-correlation function is used to describe the phase relationship of acoustic wave propagation between two measurement points, and its expression is: ;

[0049] in, For time delay, It is the measuring point and By finding The maximum position of the sound wave is estimated, and the propagation time of the sound wave between the two measurement points is estimated to obtain the spatial positioning data of the sound source. The sound source spatial positioning data is mapped to the three-dimensional coordinate system. Assume that the propagation distance of the sound wave between different measurement points is ,in is the speed of sound. The location of the sound source in three-dimensional space is calculated by triangulation The positioning data of all measurement points are spatially integrated on the sound image positioning surface to calculate the sound phase positioning measurement data: ;

[0050] in, is the spatial distribution area of ​​the measurement points, is the sound image localization function. The sound phase localization measurement data and the standardized frequency band response data are input into the Bayesian inference model to construct the prior distribution function. The key formula of Bayesian inference is: ;

[0051] in, is the acoustic parameter, is the measurement data, is the posterior distribution, is the likelihood function, is the prior distribution, is a normalization constant. By calculating the probability density, the prior probability distribution of the acoustic parameters is obtained. The prior probability distribution is matched with the acoustic theoretical model to construct an acoustic likelihood function model. The acoustic likelihood function model is expressed as: ;

[0052] in, For the The data of the measurement points are obtained by normalizing the coefficients. The final acoustic likelihood function is obtained. According to the prior probability distribution of the acoustic parameters and the likelihood function, boundary element analysis and frequency domain conversion are performed. Boundary element analysis is based on the Helmholtz equation: ;

[0053] in, is the Laplace operator, is the sound pressure, is the wave number. The equation is solved by the boundary element method and combined with the frequency domain conversion to finally obtain the frequency domain acoustic response characteristic curve.

[0054] In a specific embodiment, the execution step performs boundary element analysis and frequency domain conversion on the coaxial speaker echo bar sound box according to the prior probability distribution of acoustic parameters and the acoustic likelihood function to obtain the frequency domain acoustic response characteristic curve, which may specifically include the following steps:

[0055] Based on the prior probability distribution of acoustic parameters and the acoustic likelihood function, a three-dimensional geometric model of the coaxial speaker echo gallery speaker is established, and the three-dimensional geometric model is discretized to obtain boundary element mesh data;

[0056] Assign acoustic boundary conditions to the boundary element grid data to obtain the sound pressure transfer matrix equation, and assemble and solve the sound pressure transfer matrix equation according to the acoustic node number to obtain the numerical solution of the sound pressure distribution;

[0057] The numerical solution of the sound pressure distribution is subjected to boundary integral processing and sound field reconstruction to obtain the time-domain sound pressure response function, and the time-domain sound pressure response function is subjected to fast Fourier transform and frequency band decomposition to obtain the sub-band acoustic response data;

[0058] Perform transfer function synthesis and polar coordinate transformation on the sub-frequency band acoustic response data to obtain phase-frequency characteristic data, and perform phase correction calculation and frequency domain compensation based on the phase-frequency characteristic data to obtain the frequency domain compensation coefficient;

[0059] The amplitude-frequency characteristic analysis is performed based on the frequency domain compensation coefficient to obtain the frequency domain acoustic response characteristic curve.

[0060] Specifically, the geometric characteristics and material parameters of the speaker are determined according to the prior probability distribution and likelihood function of the acoustic parameters to establish its three-dimensional geometric model. , where each Represents the specific acoustic properties of the speaker, such as the inner wall curvature, material impedance, and speaker unit position. The acoustic prior probability distribution is expressed through the Bayesian inference model as: ;

[0061] in, is the posterior distribution, is the likelihood function, which describes the probability of measured data under given parameters; is the prior distribution, representing the initial knowledge of the parameters; is a normalization constant. Using the optimization algorithm to maximize , and get the optimal values ​​of the acoustic parameters. After determining these parameters, construct a three-dimensional geometric model of the speaker. For example, assume that the speaker is a complex coaxial structure with a curvature of The inner wall surface of the speaker unit is By expressing these geometric characteristics parametrically, a complete three-dimensional model is generated. This model is discretized into a boundary element mesh, and the total number of discrete points is set to Each grid point The coordinates of , and the geometric continuity between adjacent grids is satisfied. After discretization, acoustic boundary conditions are assigned to the grids, including the acoustic pressure Harmonic Particle Speed . According to the Helmholtz equation: ;

[0062] in is the Laplace operator, is the sound pressure, is the wave number, is the frequency, is the speed of sound. By using the boundary element method, this equation is transformed into a discrete form on the grid: ;

[0063] in, and is the influence coefficient matrix, respectively related to the point and This discretized form forms a sound pressure transfer matrix equation. The sound pressure transfer matrix is ​​assembled according to the grid node number to form a global matrix: ;

[0064] in, is the assembled system matrix, is the sound pressure value vector of all nodes, is the boundary condition vector. By numerically solving, we get the numerical solution of the sound pressure distribution: The numerical solution of sound pressure is used to reconstruct the sound field through boundary integral processing. The formula for sound field reconstruction is: ;

[0065] in, and is the Green function, describing the To the observation point After obtaining the sound field reconstruction, the time domain sound pressure signal is transformed into Convert to frequency domain: ;

[0066] The discrete form of the fast Fourier transform is: ;

[0067] in, is the number of sampling points, is the frequency index. For frequency domain data Perform frequency band decomposition to divide the acoustic response data into different frequency bands. For example, divide the low frequency band , mid-band , high frequency band The transfer function is calculated for each frequency band:

[0068] ;

[0069] in, and are the frequency domain values ​​of the output and input sound pressures respectively. The frequency band data is transformed into polar coordinates to obtain the phase-frequency characteristic data, including the amplitude and Phase : ;

[0070] Use the phase-frequency characteristic data to perform phase correction and adjust To ensure phase consistency in different frequency bands. Calculate compensation coefficients through frequency domain compensation : ;

[0071] Apply the compensation coefficient to the amplitude-frequency characteristic analysis to generate the frequency domain acoustic response characteristic curve: ;

[0072] in, This is the amplitude-frequency response curve after compensation, showing the frequency domain acoustic performance of the speaker.

[0073] In a specific embodiment, the process of executing step S2 may specifically include the following steps:

[0074] Perform sound pressure distribution analysis and frequency band division on the frequency domain acoustic response characteristic curve to obtain frequency band sound field data, and identify the sound reflection area based on the frequency band sound field data to obtain sound reflection intensive area data;

[0075] Perform acoustic zoning planning and spatial mapping based on the data of the sound reflection intensive area to obtain the coordinates of the sound absorption material layout position, and calculate the position of the acoustic reflection plate based on the coordinates of the sound absorption material layout position to obtain the spatial orientation data of the reflection plate;

[0076] Finite difference calculation is performed based on the coordinates of the sound-absorbing material arrangement position and the spatial orientation data of the reflector to obtain the acoustic boundary impedance distribution, and frequency response analysis is performed on the acoustic boundary impedance distribution to obtain the boundary acoustic characteristic function;

[0077] According to the boundary acoustic characteristic function, the acoustic processing unit combination design is carried out to obtain the unit spacing parameter, and the spatial uniformity of the unit spacing parameter is analyzed to obtain the processing unit layout plan;

[0078] Input the processing unit layout scheme into the boundary element model to perform sound field superposition calculation to obtain the combined acoustic effect function, and perform frequency response characteristic analysis on the combined acoustic effect function to obtain the unit combination parameters;

[0079] The spatial coordinate transformation is performed based on the unit combination parameters to obtain the three-dimensional layout coordinates of the acoustic processing unit, and the three-dimensional layout coordinates are subjected to geometric constraint processing to obtain the spatial layout parameters of the acoustic processing unit.

[0080] Specifically, the sound pressure distribution analysis is performed on the frequency domain acoustic response characteristic curve to extract the sound pressure changes of the sound field inside the speaker at different frequencies. Assuming the frequency domain acoustic response curve Describe the sound pressure level as a function of frequency By analyzing the peaks, valleys and slopes in the curve, the sound pressure characteristics in different frequency ranges can be identified. Divided into multiple sub-bands ,satisfy The data of each sub-band is expressed as: ;

[0081] Generate frequency band sound field data , these data reflect the sound pressure characteristics in different frequency bands. Based on the frequency band sound field data, the sound reflection area is identified. Assume that the sound reflection distribution function of the inner wall of the speaker is , which represents the sound energy reflection density in three-dimensional space. The acoustic field model is superimposed and analyzed to calculate the location of the reflection-intensive area. The acoustic energy reflection intensity is calculated using the following formula: ;

[0082] in are spatial coordinates, The unit is energy density. By setting the threshold , identify the reflection-intensive area, satisfy The point set is the data of the sound reflection intensive area. According to the data of the sound reflection intensive area, acoustic zoning planning and space mapping are carried out, with the goal of optimizing the layout of the sound absorbing material. Through geometric analysis, the sound reflection intensive area is mapped to the inner wall surface, and the layout position coordinates of the sound absorbing material are calculated. For each , taking into account material coverage and thickness. The optimal position and angle of the acoustic reflector are calculated using an optimization algorithm. The spatial orientation data of the reflector is expressed as: ;

[0083] in is the spatial position of the reflector, is the inclination angle of the reflector. After obtaining the coordinates of the sound-absorbing material layout and the spatial orientation data of the reflector, a finite difference calculation is performed based on these data to determine the acoustic boundary impedance distribution. Assume that the acoustic boundary impedance of the inner wall is , which is determined by the physical parameters of the sound absorbing material and the reflector, and its calculation formula is: ;

[0084] in is the sound pressure, is the particle velocity. Using the impedance distribution , further frequency response analysis is performed to obtain the boundary acoustic characteristic function , which is defined as:

[0085] in and are the sound pressure amplitudes of the reflected and incident sound waves, respectively. According to the boundary acoustic characteristic function, the combination of acoustic processing units is designed. Assume that the coverage area of ​​each unit is , the center distance is By optimizing , determine the unit spacing parameters to make the sound field uniform. Use spatial uniformity analysis to calculate the unit layout plan so that the acoustic treatment unit covers the key areas of the inner wall. Input the layout plan into the boundary element model to perform sound field superposition calculation. Calculate the combined acoustic effect function using the Helmholtz integral formula: ;

[0086] in is the boundary integration region, is the Green's function, describing the sound wave from arrive The propagation of the combined acoustic effect function Perform frequency response characteristic analysis to obtain unit combination parameters Through the spatial coordinate transformation of these parameters, the three-dimensional layout coordinates of the acoustic processing unit are obtained. The three-dimensional layout coordinates are geometrically constrained to ensure that the design meets the actual physical constraints. The geometric constraints include the minimum spacing between units, material thickness restrictions, and processing constraints, and ultimately the optimized acoustic treatment unit spatial layout parameters are obtained.

[0087] In a specific embodiment, the process of executing step S3 may specifically include the following steps:

[0088] An acoustic coordinate system is established based on the spatial arrangement parameters of the acoustic processing unit, and the acoustic energy distribution function is obtained through three-dimensional spatial geometric calculation. The acoustic energy distribution function is subjected to gradient analysis to obtain the acoustic energy flow vector field.

[0089] Perform divergence calculation on the sound energy flow vector field to obtain the sound source radiation field distribution, and perform frequency band decomposition on the sound source radiation field distribution to obtain frequency band sound field data;

[0090] The sound wave propagation path is tracked based on the frequency band sound field data to obtain a sound wave propagation trajectory diagram, and the path of the sound wave propagation trajectory diagram is optimized to obtain the main sound wave propagation path;

[0091] Perform spatial geometric analysis on the main sound wave propagation path to obtain the coordinates of the sound wave convergence point, and use the coordinates of the sound wave convergence point as the acoustic center of the coaxial speaker to obtain the coordinates of the acoustic center;

[0092] A local coordinate system is established based on the coordinates of the acoustic center, and the sound field intensity distribution is obtained by calculating the sound wave energy density. The main direction of the sound field intensity distribution is analyzed to obtain the main axis of sound wave radiation.

[0093] The main axis of the acoustic wave radiation is transformed with the spatial reference coordinate system to obtain the axial angle parameter, and the axial angle parameter is spatially projected to obtain the axial inclination angle data;

[0094] The acoustic wave directivity is calculated for the axial tilt angle data to obtain the directivity factor, and the directivity factor is optimized to obtain the optimal axial tilt angle parameter;

[0095] The coordinate system is transformed based on the acoustic center coordinates and the optimal axial tilt angle parameters to obtain the spatial coordinate parameters and axial tilt angle parameters of the coaxial speaker.

[0096] Specifically, based on the spatial arrangement parameters of the acoustic processing unit ,in Indicates the spatial position of each acoustic processing unit and establishes a three-dimensional acoustic coordinate system inside the entire speaker. This coordinate system takes the center of the speaker as the origin and covers all the space inside the speaker. Describes the energy intensity at each point in the sound field and is defined as: ;

[0097] in, Yes In frequency The sound pressure under The unit is energy density ( Hz). The acoustic energy distribution function in the entire space is obtained by numerical calculation to describe the energy distribution law in the sound field. Perform gradient analysis to obtain the acoustic energy flow vector field , defined as: ;

[0098] in, It is the gradient vector of the sound energy distribution. Its direction indicates the direction of sound energy flow, and its magnitude indicates the intensity of energy change. , which reflects how sound energy propagates in space. By performing divergence calculation on the sound energy flow vector field, we can obtain the distribution of the sound source radiation field. The positive and negative values ​​of the divergence value indicate the radiation and absorption areas of the sound source, where: ;

[0099] Through frequency band decomposition, the entire radiation field is decomposed into sound field data of multiple frequency bands ,in Indicates The sound field distribution in each frequency band. Based on the sound field data of each frequency band, the sound wave propagation path tracking analysis is carried out. The sound wave propagation path is determined by analyzing the propagation trajectory of the sound wave from the source point to the target point. Assume that the propagation speed of the sound wave is , the path tracing formula is: ;

[0100] in, It's time The position of the sound wave, It's time The propagation speed of sound waves, is the initial position. The sound wave propagation trajectory diagram is obtained by numerical integration, and the main sound wave propagation path is extracted by path optimization algorithm (such as the shortest path method or the energy concentration path method). The main sound wave propagation path is spatially analyzed to find the convergence point of the sound wave. Assume that the main path is at time The position below is , the convergence point of the sound waves satisfies: ;

[0101] That is, the path converges at this point. Solving the above equations yields the coordinates of the point where the sound waves converge , and define it as the acoustic center of the coaxial speaker. Based on the acoustic center coordinates , establish a local coordinate system , used to describe the sound field intensity distribution The sound field intensity is defined as:

[0102] ;

[0103] in, It is a local volume unit. The principal axis of sound wave radiation is calculated by principal direction analysis. , the principal axis direction is determined by the following formula: ;

[0104] in, is the local coordinate position. Convert to the global coordinate system through the coordinate transformation matrix It is expressed as: ;

[0105] Further calculation of axial angle parameters : ;

[0106] in, is the reference axis of the global coordinate system. Perform spatial projection to obtain axial tilt angle data for sound wave directivity calculation. The directivity factor is defined as: ;

[0107] in, is the intensity at a specific angle, is the average intensity. , get the optimal axial inclination parameters. Based on the acoustic center coordinates and the optimal axial inclination parameters , complete the coordinate system transformation and determine the spatial coordinate parameters and axial inclination parameters of the coaxial speaker.

[0108] In a specific embodiment, the process of executing step S4 may specifically include the following steps:

[0109] An acoustic wave reflection model is established based on the spatial coordinate parameters and the axial inclination parameters, and the acoustic wave incident angle function is calculated by the acoustic reflection law. The spatial distribution of the acoustic wave incident angle function is analyzed to obtain the reflection angle distribution function.

[0110] Performing surface fitting and curvature continuity analysis on the reflection angle distribution function to obtain curvature continuity parameters, and performing surface optimization calculation and differential geometry analysis based on the curvature continuity parameters to obtain inner wall geometric curvature parameters;

[0111] Perform acoustic boundary integral and acoustic energy flow density calculation on the inner wall geometric curvature parameters to obtain acoustic energy attenuation data;

[0112] According to the sound energy attenuation data, material impedance matching is performed to obtain a material combination sequence, and the sound wave absorption coefficient of the material combination sequence is calculated to obtain a material sound absorption characteristic function;

[0113] The material sound absorption characteristic function is decomposed and combined to optimize the frequency band to obtain the laminated structure scheme, and the acoustic transmission calculation and frequency response analysis are performed based on the laminated structure scheme to obtain the laminated combination parameters;

[0114] The lamination combination parameters are matched with the inner wall geometric curvature parameters to obtain the box material lamination parameters, and structural constraints are imposed on the box material lamination parameters to obtain the inner wall geometric curvature parameters and the box material lamination parameters.

[0115] Specifically, based on the known spatial coordinate parameters and axial inclination parameters , establish a sound wave reflection model. The sound wave reflection model is based on the inner wall surface equation Describe its geometric characteristics and use the law of acoustic reflection to calculate the incident angle and reflection angle of the sound wave. According to the law of reflection, the incident angle The cosine of is calculated by the following formula: ;

[0116] in, is the normal vector of the inner wall surface, is the wave vector of the incident sound wave. It is given by the following formula: ;

[0117] By traversing each point on the inner wall surface , calculate the sound wave incident angle function The spatial distribution of the incident angle function Perform spatial distribution analysis to obtain the reflection angle distribution function , reflecting the reflection characteristics of sound waves in different areas of the inner wall. Through numerical fitting methods, such as the least squares method, the reflection angle distribution function Fit to a smooth surface: ;

[0118] in, are the fitting coefficients, and is the order of the polynomial. The fitted surface must satisfy the curvature continuity requirement, and its continuity parameter Calculated by the following formula: ;

[0119] Based on curvature continuity parameters , optimize the surface geometry and adjust the distribution of curvature to make the reflection path more uniform. Using differential geometry analysis, calculate the principal curvature of each point on the surface , and ensure that it meets the design requirements in the key area, and obtain the optimized inner wall geometric curvature parameters. Based on the optimized geometric curvature parameters, the acoustic boundary integral is performed to calculate the acoustic energy flow density. The acoustic energy flux density is given by the following formula: ;

[0120] in, is the sound pressure, is the particle velocity, Indicates the real part, and * indicates conjugate. By integrating the acoustic energy flux density, the acoustic energy attenuation data is obtained. , which indicates the change of sound energy along the propagation path. According to the sound energy attenuation data , perform material impedance matching analysis. Acoustic impedance of the inner wall material Defined as: ;

[0121] By adjusting the arrangement order and combination of materials, select a material combination sequence that matches the sound absorption coefficient , and calculate the sound absorption characteristic function of each material , which is defined as: ;

[0122] in, is the characteristic impedance of air. Decompose the frequency band into low frequency, medium frequency and high frequency bands, and optimize the combination for each frequency band to form a laminated structure solution , indicating the arrangement and thickness of different materials. Based on the laminated structure scheme, acoustic transfer calculation is performed, and the frequency response analysis results are obtained using the transfer matrix method: ;

[0123] in, It is Transfer function of layer materials. Combined with laminate combination parameters and the inner wall geometric curvature parameters Perform parameter matching to determine the final lamination parameters of the box material ,in Indicates Impedance of the layer material, On this basis, considering the structural constraints, such as mechanical strength and processing technology, the optimization results are adjusted, and finally the inner wall geometric curvature parameters and material lamination parameters are obtained.

[0124] In a specific embodiment, the process of executing step S5 may specifically include the following steps:

[0125] The inner wall geometric curvature parameters and the box material lamination parameters are input into the Bayesian inference model, the posterior probability density of the acoustic parameters is calculated through the posterior distribution function, and the maximum likelihood analysis is performed on the posterior probability density to obtain the optimal value of the acoustic parameter;

[0126] Perform acoustic response simulation and frequency band decomposition on the optimal values ​​of acoustic parameters to obtain frequency band performance data;

[0127] The sound pressure level is measured based on the frequency band performance data to obtain the spatial sound pressure distribution data, and the spatial sound pressure distribution data is subjected to spectrum analysis to obtain the measured frequency response curve;

[0128] The measured frequency response curve is smoothed to obtain the sound pressure level frequency response characteristic curve, and the sound pressure level frequency response characteristic curve is divided into frequency bands to obtain the frequency band response data;

[0129] Inputting the frequency band response data into the sound phase localization model to localize the sound source, obtaining the sound image spatial position function, and performing three-dimensional reconstruction on the sound image spatial position function to obtain the sound phase localization accuracy data;

[0130] The sound phase positioning accuracy data is statistically analyzed to obtain the positioning accuracy evaluation parameters, and a comprehensive evaluation is performed based on the positioning accuracy evaluation parameters and the sound pressure level frequency response characteristic curve to obtain the speaker acoustic performance verification data.

[0131] Specifically, the optimized inner wall geometric curvature parameters And box material lamination parameters Enter the Bayesian inference model to construct the posterior distribution function of acoustic parameters. The core of the Bayesian formula is to combine the prior distribution and the likelihood function To update the probability distribution of the parameters: ;

[0132] in, represents a set of acoustic parameters, For experimental measurement data, is the posterior distribution, is the likelihood function, which describes the likelihood of data under given parameters. is the prior distribution, describing the initial assumptions about the parameters, is the normalization constant. The posterior probability density is calculated using the Bayesian inference model Finally, the optimal values ​​of acoustic parameters are determined by maximum likelihood analysis. , the following conditions are met: ;

[0133] This optimal value represents the best match between the theoretical model and the actual measured data. Perform acoustic response simulation. Assuming the sound pressure Satisfies the Helmholtz equation: ;

[0134] in, is the Laplace operator, is the wave number, is the frequency, is the speed of sound. The Helmholtz equation is numerically solved by the boundary element method to obtain the sound pressure distribution at different frequencies in three-dimensional space. . The sound pressure data Decompose by frequency band to form sub-band performance data , where each Corresponding to the acoustic performance of a frequency band. Based on the sub-band performance data, the sound pressure level is measured and the spatial sound pressure distribution data is calculated. The sound pressure level is defined as: ;

[0135] in, To measure the sound pressure, Pa is the reference sound pressure. The sound pressure distribution of the entire space is obtained through three-dimensional sound field analysis. Then Perform spectrum analysis to extract the sound pressure level distribution at different frequencies and generate the measured frequency response curve In order to eliminate high-frequency noise and random errors in experimental measurements, the measured frequency response curve Perform data smoothing. Smoothing algorithms include moving average or Gaussian smoothing, which aims to generate a smoother and more continuous sound pressure level frequency response characteristic curve. Divide the smoothed frequency response curve by frequency band to obtain the frequency band response data , each frequency band data is used for sound phase localization analysis. The frequency band response data is input into the sound phase localization model, and the spatial position of the sound source is calculated by the time difference method or the amplitude difference method. Sound image spatial position function Defined as: ;

[0136] in, is the weight, which indicates the contribution of different frequency bands to the positioning accuracy. Mapped into space, generate sound image localization accuracy data. Perform statistical analysis on the sound image localization accuracy data and calculate the distribution characteristics of the localization error, including the mean, variance, and maximum deviation. For example, assuming the real sound source position is , calculate the positioning error as: ;

[0137] Positioning accuracy evaluation parameters include mean error , maximum deviation and standard deviation The positioning accuracy evaluation parameters and the sound pressure level frequency response characteristic curve Combined with the above, a comprehensive evaluation is conducted. The acoustic performance of the speaker is evaluated through quantitative indicators, including frequency response uniformity, positioning accuracy, and sound field coverage. Finally, the acoustic performance verification data of the speaker is generated to guide design improvements.

[0138] The above describes the sound effect optimization method based on the coaxial speaker echo bar speaker in the embodiment of the present invention. The following describes the sound effect optimization device based on the coaxial speaker echo bar speaker in the embodiment of the present invention. Please refer to Figure 2 In one embodiment of the present invention, a sound effect optimization device based on a coaxial speaker echo bar speaker includes:

[0139] The measurement module is used to measure the acoustic response and analyze the acoustic characteristics of the coaxial speaker echo bar speaker to obtain the frequency domain acoustic response characteristic curve;

[0140] A calculation module, for performing acoustic partition calculation on the internal space of the coaxial speaker whispering bar based on the frequency domain acoustic response characteristic curve, and obtaining the spatial arrangement parameters of the acoustic processing unit;

[0141] A positioning module is used to calculate the acoustic center positioning of the coaxial speaker according to the spatial arrangement parameters of the acoustic processing unit, and obtain the spatial coordinate parameters and axial inclination parameters of the coaxial speaker;

[0142] The optimization module is used to calculate the sound reflection angle and optimize the material combination of the inner wall structure of the echo gallery speaker based on the spatial coordinate parameters and axial inclination parameters, and obtain the inner wall geometric curvature parameters and the box material lamination parameters;

[0143] The analysis module is used to analyze the sound pressure level frequency response curve and measure the sound phase positioning accuracy of the inner wall geometric curvature parameters and the box material lamination parameters to obtain the speaker acoustic performance verification data.

[0144] Through the coordinated cooperation of the above-mentioned components, the Bayesian inference model is introduced to analyze the acoustic characteristics. Combined with the sound phase positioning measurement data and the frequency band response measurement data, the prior probability distribution and likelihood function of the acoustic parameters are established. The sound pressure transfer equation is established by the boundary element analysis method. The frequency domain acoustic response characteristic curve is obtained by frequency domain conversion, which realizes the accurate description and quantitative analysis of the acoustic characteristics of the speaker. Based on the acoustic partition calculation technology, an efficient acoustic processing unit is formed by the reasonable arrangement of sound absorbing materials and acoustic reflectors, which ensures the uniformity of the sound field inside the speaker. Through the analysis of the sound wave propagation path and the calculation of the acoustic center positioning, the optimal installation position and inclination parameters of the coaxial speaker are accurately determined to ensure the accuracy of the sound image positioning. By using the sound reflection angle calculation and material combination optimization technology, the optimal combination of the inner wall geometric curvature parameters and the box material lamination parameters is obtained, which improves the acoustic performance of the speaker. The acoustic posterior probability calculation method is used for performance verification, and a complete speaker acoustic performance evaluation system is established through the analysis of the sound pressure level frequency response curve and the measurement of the sound phase positioning accuracy.

[0145] Reference Figure 3 In an embodiment of the present invention, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0146] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0147] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0148] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0149] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0150] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0151] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the sound effect of a coaxial speaker whispering gallery, characterized in that: The method comprises: The acoustic response measurement and acoustic characteristics analysis of the coaxial speaker echo bar speaker are carried out to obtain the frequency domain acoustic response characteristic curve; Based on the frequency domain acoustic response characteristic curve, an acoustic partition calculation is performed on the internal space of the coaxial speaker whispering gallery speaker to obtain the spatial layout parameters of the acoustic processing unit; According to the spatial arrangement parameters of the acoustic processing unit, the acoustic center positioning calculation is performed on the coaxial speaker to obtain the spatial coordinate parameters and axial inclination parameters of the coaxial speaker; Based on the spatial coordinate parameters and the axial inclination parameters, the sound reflection angle of the inner wall structure of the whispering gallery speaker is calculated and the material combination is optimized to obtain the inner wall geometric curvature parameters and the box material lamination parameters; The sound pressure level frequency response curve analysis and the sound phase positioning accuracy measurement are performed on the inner wall geometric curvature parameters and the box material lamination parameters to obtain the speaker acoustic performance verification data.

2. The sound effect optimization method based on the coaxial speaker echo gallery speaker according to claim 1 is characterized in that: The acoustic response measurement and acoustic characteristic analysis of the coaxial speaker echo bar speaker are performed to obtain the prior probability distribution of acoustic parameters and the acoustic likelihood function, including: Performing multi-point acoustic measurement and time-domain sampling on the coaxial speaker whispering gallery to obtain a time-domain sound pressure response sequence, and performing discrete Fourier transform on the time-domain sound pressure response sequence to obtain standardized frequency band response data; Performing acoustic cross-correlation analysis on the standardized frequency band response data to obtain sound source spatial localization data, and performing three-dimensional coordinate mapping and sound image localization curved surface spatial integration operations on the sound source spatial localization data to obtain sound phase localization measurement data; Inputting the acoustic phase localization measurement data and the standardized frequency band response data into a Bayesian inference model, constructing a Bayesian prior distribution function, and obtaining an acoustic parameter prior probability distribution through probability density calculation; Performing parameter matching on the acoustic parameter prior probability distribution and the acoustic theoretical model to obtain an acoustic likelihood function model, and performing normalization coefficient operation on the acoustic likelihood function model to obtain an acoustic likelihood function; According to the acoustic parameter prior probability distribution and the acoustic likelihood function, the coaxial speaker echo gallery speaker is subjected to boundary element analysis and frequency domain conversion to obtain a frequency domain acoustic response characteristic curve.

3. The sound effect optimization method based on the coaxial speaker echo gallery sound box according to claim 2 is characterized in that: The method of performing boundary element analysis and frequency domain conversion on the coaxial speaker echo gallery sound box according to the acoustic parameter prior probability distribution and the acoustic likelihood function to obtain a frequency domain acoustic response characteristic curve includes: Based on the acoustic parameter prior probability distribution and the acoustic likelihood function, a three-dimensional geometric model of the coaxial speaker echo gallery sound box is established, and the three-dimensional geometric model is discretized to obtain boundary element mesh data; Assigning acoustic boundary conditions to the boundary element grid data to obtain a sound pressure transfer matrix equation, and assembling and solving the sound pressure transfer matrix equation according to the acoustic node numbers to obtain a numerical solution for the sound pressure distribution; Performing boundary integral processing and sound field reconstruction on the numerical solution of the sound pressure distribution to obtain a time-domain sound pressure response function, and performing fast Fourier transform and frequency band decomposition on the time-domain sound pressure response function to obtain frequency-band acoustic response data; Performing transfer function synthesis and polar coordinate transformation on the sub-frequency band acoustic response data to obtain phase-frequency characteristic data, and performing phase correction calculation and frequency domain compensation based on the phase-frequency characteristic data to obtain a frequency domain compensation coefficient; An amplitude-frequency characteristic analysis is performed based on the frequency domain compensation coefficient to obtain a frequency domain acoustic response characteristic curve.

4. The sound effect optimization method based on the coaxial speaker echo gallery speaker according to claim 3 is characterized in that: The acoustic partition calculation is performed on the internal space of the coaxial speaker whispering gallery sound box based on the frequency domain acoustic response characteristic curve to obtain the spatial arrangement parameters of the acoustic processing unit, including: Performing sound pressure distribution analysis and frequency band division on the frequency domain acoustic response characteristic curve to obtain frequency segment sound field data, and performing sound reflection area identification based on the frequency segment sound field data to obtain sound reflection intensive area data; Performing acoustic zoning planning and spatial mapping according to the sound reflection intensive area data to obtain the coordinates of the sound absorption material arrangement position, and calculating the position of the acoustic reflection plate based on the coordinates of the sound absorption material arrangement position to obtain the spatial orientation data of the reflection plate; Performing finite difference calculation based on the coordinates of the arrangement position of the sound absorbing material and the spatial orientation data of the reflector to obtain an acoustic boundary impedance distribution, and performing frequency response analysis on the acoustic boundary impedance distribution to obtain a boundary acoustic characteristic function; Performing a combination design of acoustic processing units according to the boundary acoustic characteristic function to obtain unit spacing parameters, and performing a spatial uniformity analysis on the unit spacing parameters to obtain a processing unit layout plan; Inputting the processing unit layout scheme into a boundary element model to perform sound field superposition calculation to obtain a combined acoustic effect function, and performing frequency response characteristic analysis on the combined acoustic effect function to obtain unit combination parameters; A spatial coordinate transformation is performed based on the unit combination parameters to obtain the three-dimensional arrangement coordinates of the acoustic processing unit, and a geometric constraint process is performed on the three-dimensional arrangement coordinates to obtain the spatial arrangement parameters of the acoustic processing unit.

5. The sound effect optimization method based on the coaxial speaker echo gallery speaker according to claim 4 is characterized in that: The method of performing acoustic center positioning calculation on the coaxial speaker according to the spatial arrangement parameters of the acoustic processing unit to obtain the spatial coordinate parameters and axial inclination parameters of the coaxial speaker includes: An acoustic coordinate system is established based on the spatial arrangement parameters of the acoustic processing unit, an acoustic energy distribution function is obtained through three-dimensional spatial geometric calculation, and a gradient analysis is performed on the acoustic energy distribution function to obtain an acoustic energy flow vector field; Performing divergence calculation on the acoustic energy flow vector field to obtain a sound source radiation field distribution, and performing frequency band decomposition on the sound source radiation field distribution to obtain frequency band sound field data; Tracking the sound wave propagation path based on the frequency-band sound field data to obtain a sound wave propagation trajectory diagram, and performing path optimization on the sound wave propagation trajectory diagram to obtain a main sound wave propagation path; Performing spatial geometric analysis on the main sound wave propagation path to obtain the coordinates of the sound wave convergence point, and using the coordinates of the sound wave convergence point as the acoustic center of the coaxial speaker to obtain the coordinates of the acoustic center; A local coordinate system is established based on the acoustic center coordinates, the sound field intensity distribution is obtained by calculating the sound wave energy density, and the main direction of the sound field intensity distribution is analyzed to obtain the main axis of sound wave radiation; Performing coordinate transformation on the principal axis of acoustic wave radiation and the spatial reference coordinate system to obtain an axial angle parameter, and performing spatial projection on the axial angle parameter to obtain axial inclination angle data; Performing acoustic wave directivity calculation on the axial tilt angle data to obtain a directivity factor, and optimizing the directivity factor to obtain an optimal axial tilt angle parameter; A coordinate system transformation is performed based on the acoustic center coordinates and the optimal axial inclination angle parameters to obtain the spatial coordinate parameters and axial inclination angle parameters of the coaxial speaker.

6. The sound effect optimization method based on the coaxial speaker echo gallery sound box according to claim 5 is characterized in that: The method of calculating the sound reflection angle and optimizing the material combination of the inner wall structure of the whispering gallery speaker based on the spatial coordinate parameters and the axial inclination parameters to obtain the inner wall geometric curvature parameters and the box material lamination parameters includes: A sound wave reflection model is established based on the spatial coordinate parameters and the axial inclination parameters, a sound wave incident angle function is calculated by the acoustic reflection law, and a spatial distribution analysis is performed on the sound wave incident angle function to obtain a reflection angle distribution function; Performing surface fitting and curvature continuity analysis on the reflection angle distribution function to obtain curvature continuity parameters, and performing surface optimization calculation and differential geometry analysis based on the curvature continuity parameters to obtain inner wall geometric curvature parameters; Performing acoustic boundary integration and acoustic energy flow density calculation on the inner wall geometric curvature parameters to obtain acoustic energy attenuation data; Performing material impedance matching according to the sound energy attenuation data to obtain a material combination sequence, and calculating the sound wave absorption coefficient of the material combination sequence to obtain a material sound absorption characteristic function; Performing frequency band decomposition and combination optimization on the sound absorption characteristic function of the material to obtain a laminated structure scheme, and performing acoustic transmission calculation and frequency response analysis based on the laminated structure scheme to obtain laminated combination parameters; The lamination combination parameters are matched with the inner wall geometric curvature parameters to obtain box material lamination parameters, and structural constraints are imposed on the box material lamination parameters to obtain inner wall geometric curvature parameters and box material lamination parameters.

7. The sound effect optimization method based on the coaxial speaker echo gallery speaker according to claim 6 is characterized in that: The sound pressure level frequency response curve analysis and the sound phase positioning accuracy measurement of the inner wall geometric curvature parameters and the box material lamination parameters are performed to obtain the speaker acoustic performance verification data, including: The inner wall geometric curvature parameters and the box material lamination parameters are input into the Bayesian inference model, the posterior probability density of the acoustic parameters is calculated by the posterior distribution function, and the maximum likelihood analysis is performed on the posterior probability density to obtain the optimal value of the acoustic parameter; Performing acoustic response simulation and frequency band decomposition on the optimal values ​​of the acoustic parameters to obtain frequency band performance data; Performing sound pressure level measurement based on the frequency band performance data to obtain spatial sound pressure distribution data, and performing spectrum analysis on the spatial sound pressure distribution data to obtain a measured frequency response curve; Performing data smoothing on the measured frequency response curve to obtain a sound pressure level frequency response characteristic curve, and dividing the sound pressure level frequency response characteristic curve into frequency bands to obtain frequency band response data; Inputting the frequency-divided response data into a sound phase localization model to localize the sound source, obtaining a sound image spatial position function, and performing three-dimensional reconstruction on the sound image spatial position function to obtain sound phase localization accuracy data; The sound phase localization accuracy data is statistically analyzed to obtain a localization accuracy evaluation parameter, and a comprehensive evaluation is performed based on the localization accuracy evaluation parameter and the sound pressure level frequency response characteristic curve to obtain speaker acoustic performance verification data.

8. A sound effect optimization device based on a coaxial speaker whispering gallery speaker, characterized in that: The method for optimizing the sound effect based on the coaxial speaker echo bar speaker according to any one of claims 1 to 7, wherein the device for optimizing the sound effect based on the coaxial speaker echo bar speaker comprises: The measurement module is used to measure the acoustic response and analyze the acoustic characteristics of the coaxial speaker echo bar speaker to obtain the frequency domain acoustic response characteristic curve; A calculation module, for performing acoustic partition calculation on the internal space of the coaxial speaker whispering gallery speaker box based on the frequency domain acoustic response characteristic curve, and obtaining the spatial arrangement parameters of the acoustic processing unit; A positioning module, used to perform acoustic center positioning calculation on the coaxial speaker according to the spatial arrangement parameters of the acoustic processing unit, and obtain the spatial coordinate parameters and axial inclination parameters of the coaxial speaker; An optimization module, for calculating the sound reflection angle and optimizing the material combination of the inner wall structure of the whispering gallery speaker based on the spatial coordinate parameters and the axial inclination parameters, so as to obtain the inner wall geometric curvature parameters and the box material lamination parameters; The analysis module is used to perform sound pressure level frequency response curve analysis and sound phase positioning accuracy measurement on the inner wall geometric curvature parameters and the box material lamination parameters to obtain speaker acoustic performance verification data.

9. A computer device, characterized in that: It includes a memory and a processor, the memory stores a computer program that can be run on the processor, and is characterized in that when the processor executes the computer program, it implements the sound optimization method based on the coaxial speaker echo wall speaker according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor executes the sound optimization method based on a coaxial speaker sound bar speaker as described in any one of claims 1 to 7.

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