Design method of ventilated sound insulation metamaterial based on sound quality

Abstract

The invention provides a sound quality-based ventilated sound insulation metamaterial design method, which comprises the following steps of: acquiring target noise for spectral analysis, and determining a main sound insulation frequency band of a metamaterial; determining the annoyance degree of a sound sample of the target noise, and calculating psychoacoustic parameters of the sound sample; analyzing the annoyance degree and the psychoacoustic parameters to obtain an annoyance degree correlation model; modeling the acoustic metamaterial structure and calculating transmission loss, and adjusting the sound insulation frequency band of the metamaterial to a specified target frequency band by adjusting the parameters of the acoustic metamaterial structure; the transmission coefficient of the acoustic metamaterial structure is calculated, psychological acoustic parameters are obtained according to the transmission coefficient, an annoyance degree correlation model is established, and the noise annoyance degree is obtained; and adjusting parameters based on the noise annoyance degree under different acoustic metamaterial structures to obtain the acoustic metamaterial structure with the optimal sound quality. According to the invention, the sound quality annoyance degree is used as the basis of the metamaterial design effect, so that the sound quality annoyance degree is greatly reduced under the limited size.

Description

Technical Field

[0001] The invention belongs to the technical field of sound insulation metamaterial design, and in particular relates to a design method of ventilated sound insulation metamaterial based on sound quality. Background Art

[0002] The noise reduction problem is an old and new, traditional and challenging problem in the engineering field. Noise pollution seriously affects people's health and has become one of the recognized environmental problems in the world today. Noise pollution has an impact on the hearing system. Excessive exposure of the hearing system to sound will initially produce a temporary threshold shift. After excessive exposure, this temporary threshold shift will lead to permanent shift, that is, hearing loss.

[0003] In order to avoid noise-induced hearing loss, it has always been a very challenging task to effectively block low-frequency sound waves and attenuate the energy of noise from an energy perspective based on the three elements of the noise propagation process: the sound source, the propagation path, and the receiver. By analogy with photonic crystals, MS Kushwaha et al. first proposed the concept of phononic crystals in 1993, and used the plane wave method to calculate the elastic wave bandgap in the shear polarization direction for the composite medium formed by nickel columns in an aluminum alloy matrix, thus giving birth to acoustic metamaterials.

[0004] Acoustic metamaterials refer to new acoustic materials or structures composed of specially designed artificial acoustic microstructure units periodically arranged in an elastic medium. Acoustic metamaterials can form a band gap for sound waves of a specific frequency, thereby effectively controlling low-frequency noise. As for sound-absorbing and sound-insulating metamaterials, they can achieve a good sound absorption and sound insulation peak within a specified frequency range through preliminary design. The defect is that there is only one sound wave band gap with a narrow frequency band. To achieve broadband sound absorption and sound insulation, more units are usually required to be coupled, which will greatly increase the size of the metamaterial. Therefore, under the condition of size limitations, it is very necessary to maximize the use of the sound absorption and sound insulation bandwidth of the material.

[0005] Since the 1930s, people have proposed a large number of evaluation indicators for noise evaluation. The International Organization for Standardization (ISO) recommended the weighted sound level and the noise rating number (NR) for steady-state noise. For a long time, the objective parameter for evaluating noise has been mainly A-weighted sound level, and C sound level is also used in some cases. At the same time, other objective parameters based on A sound level are also used, such as: cumulative percentage A sound level, noise density, noise pollution level, etc.

[0006] A-level and C-level are frequency-domain weighted forms of sound pressure level, which roughly simulate the human ear's perception of sound loudness. However, people's subjective perception of sound is closely related to the time domain and frequency domain characteristics of the sound signal, and does not depend solely on loudness. Various sounds in reality, especially noise, have very different time domain and frequency domain characteristics. Therefore, the traditional weighted sound level that mainly reflects the loudness of sound cannot fully represent people's subjective perception of noise. Summary of the invention

[0007] The purpose of the present invention is to solve the shortcomings of the prior art that it cannot better reflect people's subjective feelings about sound, and to provide a design method for ventilated sound-insulating metamaterials based on sound quality. For sounds with noise frequencies concentrated in the range of 500Hz-1000Hz, the sound quality annoyance is used as the basis for the design effect of the metamaterial, so that the sound quality annoyance is greatly reduced under limited dimensions.

[0008] To achieve the above purpose, the technical solution provided by the present invention is:

[0009] A method for designing a ventilated sound-insulating metamaterial based on sound quality comprises the following steps:

[0010] Step 1: collecting target noise and performing spectrum analysis to determine the main sound insulation frequency band of the metamaterial; determining the annoyance of the sound sample of the target noise, and calculating the psychoacoustic parameters of the sound sample;

[0011] Step 2: analyzing the annoyance degree and the psychoacoustic parameters to obtain an annoyance degree correlation model between the annoyance degree and the psychoacoustic parameters;

[0012] Step 3: Model the acoustic metamaterial structure in finite element software and calculate the transmission loss, adjust the Helmholtz resonator opening diameter, the Helmholtz resonator cavity depth and the cavity length, and adjust the sound insulation frequency band of the metamaterial to the specified target frequency band;

[0013] Step 4: calculating the transmission coefficient of the acoustic metamaterial structure, obtaining psychoacoustic parameters according to the transmission coefficient, establishing the annoyance correlation model, and obtaining the noise annoyance;

[0014] Step 5: Based on the noise annoyance degree under different acoustic metamaterial structures, the cavity length of the Helmholtz resonator structure is adjusted to adjust the peak frequency of the sound insulation band, thereby obtaining an acoustic metamaterial structure with optimal sound quality.

[0015] As a further limitation of the present invention, the step 1 comprises:

[0016] (11) According to the application scenario, an artificial head is used to collect target noise, and a spectrum analysis is performed on the target noise to determine the main sound insulation frequency band of the metamaterial;

[0017] (12) conducting a subjective evaluation experiment using the collected target noise as a sound sample to obtain an annoyance degree of each sound sample;

[0018] (13) Calculate psychoacoustic parameters of the sound sample, wherein the psychoacoustic parameters include loudness, sharpness, roughness and fluctuation intensity.

[0019] As a further limitation of the present invention, (131) the step of calculating the loudness includes:

[0020] (a) Using 1 / 3 octave approximation critical band, the spectrum of the sound signal is divided into 28 sub-bands according to the 1 / 3 octave band, wherein the first 6 sub-bands are combined into one characteristic band, the 7th to 9th sub-bands are combined into one characteristic band, and the 10th and 11th sub-bands are combined into one characteristic band, thus obtaining 20 characteristic bands; the sound pressure level in each characteristic band is calculated;

[0021] (b) Add appropriate external-middle ear transfer factors to the sound pressure level in the characteristic frequency band according to the sound propagation mode and the simulated working mechanism of the human ear;

[0022] (c) Taking the characteristic sound pressure level through the outer-middle ear transfer factor in (b) as the excitation level, calculate the primary loudness;

[0023] (d) integrating the characteristic loudness at the psychoacoustic frequency to form a total loudness; wherein the total loudness of the characteristic spectrum includes the main loudness and the ramp loudness, and the calculation formula of the total loudness is:

[0024]

[0025] In formula (1), N represents the total loudness, and N' represents the characteristic loudness;

[0026] (132)The calculation formula of sharpness is:

[0027]

[0028] In formula (2), S represents sharpness, C1 represents calibration constant, n'(z) represents characteristic loudness, z represents psychoacoustic frequency, and g(z) represents weight curve;

[0029] (133) The calculation formula of roughness is:

[0030]

[0031] In formula (3), R represents the roughness, f modrepresents the modulation frequency, z represents the psychological frequency, ΔL E (z) indicates the masking depth;

[0032] The masking depth is calculated based on its physical meaning using the change in characteristic loudness of each critical band, ΔL i Substitution, ΔL i The calculation formula is:

[0033] ΔL i =20lg(N′ imax / N′ imin ) Formula (4)

[0034] In formula (4), ΔL i Indicates the change in loudness within the i-th frequency band; N′ imax Indicates the maximum value of the characteristic loudness in the i-th frequency band, N′ imin Indicates the minimum value of the characteristic loudness in the i-th frequency band;

[0035] The calculation formula for volatility intensity includes:

[0036]

[0037] In formula (5), ΔL E Indicates the masking depth, f mod represents the modulation frequency and z represents the psychological frequency.

[0038] As a further limitation of the present invention, the step 2 includes: conducting a subjective evaluation experiment on the target noise of the step 1 to obtain an annoyance degree, and performing a correlation analysis with the psychoacoustic parameters calculated in the step 1 to obtain a correlation model between the annoyance degree and each psychoacoustic parameter; wherein the correlation model includes a Zwicker annoyance degree calculation model or a multivariate linear regression model.

[0039] As a further limitation of the present invention, the step three includes: modeling the acoustic metamaterial structure in finite element software and calculating the transmission loss, adjusting the sound wave propagation path by adjusting the length of the Helmholtz resonator cavity, and adjusting the sound insulation frequency band of the acoustic metamaterial to a specified target frequency band;

[0040] The acoustic metamaterial structure includes: a plurality of single units arranged in parallel, wherein the single units are in the form of Helmholtz resonators and space bending structures.

[0041] As a further limitation of the present invention, the step 4 comprises:

[0042] (41) calculating the transmission coefficient of the acoustic metamaterial structure;

[0043] (42) filtering the original signal using the transmission coefficient as a filter to obtain a spectrum of the sound sample after noise reduction processing, and obtaining a time-domain sound sample of the sound signal after noise reduction processing by inverse Fourier transform;

[0044] (43) Calculating various psychoacoustic parameters of the noise sample after sound insulation treatment, and establishing the annoyance correlation model through subjective evaluation experiments;

[0045] (44) Calculate the noise annoyance level after sound insulation treatment.

[0046] As a further limitation of the present invention, the calculation expression of the transmission coefficient is:

[0047]

[0048] In formula (6), τ represents the transmission coefficient.

[0049] As a further limitation of the present invention, the step five comprises:

[0050] By comparing the noise annoyance levels under different structures, the parameters of the acoustic metamaterial structure are adjusted to obtain an acoustic metamaterial structure with optimal sound quality.

[0051] As a further limitation of the present invention, the following steps are also included:

[0052] Step 6: Obtain the parameters of the acoustic metamaterial structure according to step 5, and use 3D printing technology to print the corresponding metamaterial specimen; place the metamaterial specimen in a standing wave tube, and output the acoustic sample of the target noise at the signal transmitting end; use a microphone at the rear end of the metamaterial specimen to collect the acoustic sample of the noise after noise reduction;

[0053] Step 7: Calculate the psychoacoustic parameters of the noise sample after noise reduction, and compare and verify with the simulation results, wherein the psychoacoustic parameters include loudness, sharpness, roughness and fluctuation intensity.

[0054] The advantages of the present invention are:

[0055] The present invention targets sounds with noise frequencies concentrated in the range of 500 Hz-1000 Hz, uses the sound quality annoyance as the basis for the design effect of the metamaterial, and greatly reduces the sound quality annoyance under limited dimensions.

[0056] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0058] Figure 1 :A design method for ventilated sound-insulating metamaterial based on sound quality provided by the present invention Figure 1 ;

[0059] Figure 2 :A design method for ventilated sound-insulating metamaterial based on sound quality provided by the present invention Figure 2 ;

[0060] Figure 3 : A schematic diagram of a single channel structure of the acoustic metamaterial structure provided by the present invention;

[0061] Figure 4 : A single channel transmission loss curve diagram of the acoustic metamaterial structure provided by the present invention;

[0062] Figure 5 : Schematic diagram of a single unit and overall structure model of the acoustic metamaterial structure provided by the present invention;

[0063] Figure 6 : The structural transmission loss and transmission coefficient curve provided by the present invention. DETAILED DESCRIPTION

[0064] Embodiments of the present invention are described in detail below. The embodiments are exemplary and intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0065] See also Figure 1 and Figure 2 The embodiment of the present invention provides a method for designing a ventilated sound-insulating metamaterial based on sound quality, including a finite element simulation stage and an experimental verification stage. The finite element simulation stage is Figure 1 and Figure 2 From step 1 to step 5 shown in the figure, the experimental verification phase is Figure 2 Steps 6 and 7 are shown. Steps 1 to 7 are as follows:

[0066] Step 1: Collect the target noise and perform spectrum analysis to determine the main sound insulation frequency band of the metamaterial; determine the annoyance of the sound sample of the target noise, and calculate the psychoacoustic parameters of the sound sample.

[0067] The above step 1 of the embodiment of the present invention includes:

[0068] (11) According to the application scenario, use an artificial head to collect target noise, perform spectrum analysis on the target noise, and determine the main sound absorption frequency band of the metamaterial;

[0069] (12) A subjective evaluation experiment is conducted with the collected target noise as a sound sample to obtain the annoyance level of each sound sample; the subjective evaluation experiment of the embodiment of the present invention can select the annoyance level subjective evaluation experiment in a method for evaluating the grading limit of sound quality satisfaction of range hoods published in the Journal of Applied Acoustics in September 2021.

[0070] (13) Calculate psychoacoustic parameters of the sound sample, where the psychoacoustic parameters include loudness, sharpness, roughness, and fluctuation intensity.

[0071] More specifically, in step (13), the step of calculating the loudness (131) includes:

[0072] (a) Using 1 / 3 octave approximation critical band, the spectrum of the sound signal is divided into 28 sub-bands according to the 1 / 3 octave band, wherein the first 6 sub-bands are combined into one characteristic band, the 7th to 9th sub-bands are combined into one characteristic band, and the 10th and 11th sub-bands are combined into one characteristic band, thus obtaining 20 characteristic bands; the sound pressure level in each characteristic band is calculated;

[0073] (b) Add appropriate external-middle ear transfer factors to the sound pressure level in the characteristic frequency band according to the sound propagation mode and the simulated working mechanism of the human ear;

[0074] (c) Taking the characteristic sound pressure level through the outer-middle ear transfer factor in (b) as the excitation level, calculate the primary loudness;

[0075] (d) integrating the characteristic loudness at the psychoacoustic frequency to form a total loudness; wherein the total loudness of the characteristic spectrum includes the main loudness and the ramp loudness, and the calculation formula of the total loudness is:

[0076]

[0077] In formula (1), N represents the total loudness, and N' represents the characteristic loudness;

[0078] More specifically, in step (13), the calculation formula for the sharpness of (132) is:

[0079]

[0080] In formula (2), S represents sharpness, C1 represents calibration constant, n'(z) represents characteristic loudness, z represents psychoacoustic frequency, and g(z) represents weight curve;

[0081] More specifically, in step (13), the calculation formula of the roughness of (133) is:

[0082]

[0083] In formula (3), R represents the roughness, f modrepresents the modulation frequency, z represents the psychological frequency, ΔL E (z) indicates the masking depth;

[0084] The masking depth is calculated based on its physical meaning using the change in characteristic loudness of each critical band, ΔL i Substitution, ΔL i The calculation formula is:

[0085] ΔL i =20lg(N′ imax / N′ imin ) Formula (4)

[0086] In formula (4), ΔL i Indicates the change in loudness within the i-th frequency band; N′ imax Indicates the maximum value of the characteristic loudness in the i-th frequency band, N′ imin Indicates the minimum value of the characteristic loudness in the i-th frequency band;

[0087] The calculation formula for volatility intensity includes:

[0088]

[0089] In formula (5), ΔL E Indicates the masking depth, f mod represents the modulation frequency and z represents the psychological frequency.

[0090] Step 2: Analyze the annoyance degree and psychoacoustic parameters to obtain an annoyance degree correlation model between the annoyance degree and the psychoacoustic parameters.

[0091] The above-mentioned step 2 of the embodiment of the present invention includes: conducting a subjective evaluation experiment on the target noise in step 1 to obtain annoyance, and performing correlation analysis with the psychoacoustic parameters calculated in step 1 to obtain a correlation model between the annoyance and each psychoacoustic parameter; wherein the correlation model includes a Zwicker annoyance calculation model or a multivariate linear regression model.

[0092] Step 3: Model the acoustic metamaterial structure in finite element software and calculate the transmission loss, adjust the Helmholtz resonator opening diameter, the Helmholtz resonator cavity depth and the cavity length, and adjust the sound insulation frequency band of the metamaterial to the specified target frequency band.

[0093] The above step three of the embodiment of the present invention includes: modeling the acoustic metamaterial structure in finite element software and calculating the transmission loss, adjusting the sound wave propagation path by adjusting the length of the Helmholtz resonator cavity, and adjusting the sound insulation frequency band of the acoustic metamaterial to the specified target frequency band;

[0094] The acoustic metamaterial structure includes: multiple single units are arranged in parallel, and a single unit adopts a Helmholtz resonator and a space bending structure such as Figure 3 As shown, the transmission loss is Figure 4 shown. Figure 3 In the schematic diagram of a single channel structure, H=10mm, t=1mm, da=2mm, W=12mm, B=3mm.

[0095] Step 4: Calculate the transmission coefficient of the acoustic metamaterial structure, obtain the psychoacoustic parameters based on the transmission coefficient, establish an annoyance correlation model, and obtain the noise annoyance.

[0096] The above step 4 of the embodiment of the present invention includes:

[0097] (41) Calculate the transmission coefficient τ of the acoustic metamaterial structure;

[0098] (42) filtering the original signal using the transmission coefficient as a filter to obtain a spectrum of the sound sample after noise reduction processing, and obtaining a time-domain sound sample of the sound signal after noise reduction processing by inverse Fourier transform;

[0099] (43) The psychoacoustic parameters of the noise sample after sound insulation treatment are calculated by formula (1)-formula (6), and the annoyance correlation model is established through subjective evaluation experiments;

[0100] (44) Calculate the noise annoyance level after sound insulation treatment.

[0101] The calculation expression of the transmission coefficient in step (41) is:

[0102]

[0103] In formula (6), τ represents the transmission coefficient.

[0104] Step 5: Based on the noise annoyance degree under different acoustic metamaterial structures, the cavity length of the Helmholtz resonator structure is adjusted to adjust the peak frequency of the sound insulation band, thereby obtaining an acoustic metamaterial structure with optimal sound quality.

[0105] The above step 5 of the embodiment of the present invention includes: by comparing the noise annoyance of different structures, adjusting the parameters of the acoustic metamaterial structure to obtain an acoustic metamaterial structure with the best sound quality. Figure 5 shown. Figure 5 (a) Schematic diagram of a single unit. The single structure consists of four sound absorption channels, where the lengths of channels 1, 2, 3, and 4 are 162.9 mm, 108.7 mm, 84.6 mm, and 74.2 mm, respectively. Figure 5(b) The overall structure is composed of four units connected in a pipe shape, with the middle part being a cavity for ventilation. Figure 6 This is the structural transmission loss and transmission coefficient curve. The transmission losses at 500Hz, 750Hz, 875Hz and 1000Hz are 24dB, 23.2dB, 23.5dB and 24.8dB respectively.

[0106] Step 6: Obtain the parameters of the acoustic metamaterial structure according to step 5, and use 3D printing technology to print the corresponding metamaterial specimen; place the metamaterial specimen in a standing wave tube, and output the sound sample of the target noise at the signal transmitting end; use a microphone at the rear end of the metamaterial specimen to collect the noise sound sample after noise reduction.

[0107] Step 7: Calculate the psychoacoustic parameters of the noise sample after noise reduction and compare and verify with the simulation results, where the psychoacoustic parameters include loudness, sharpness, roughness and fluctuation intensity.

[0108] The embodiment of the present invention targets sounds with noise frequencies concentrated in the range of 500 Hz-1000 Hz, uses the sound quality annoyance as the basis for the design effect of the metamaterial, and greatly reduces the sound quality annoyance under limited dimensions.

[0109] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should be included in the protection scope of the present invention.

Claims

1. A design method for ventilated sound-insulating metamaterial based on sound quality, characterized in that: The following steps are involved: Step 1: Collect the target noise and perform spectrum analysis to determine the main sound insulation frequency band of the metamaterial; determining annoyance of a sound sample of the target noise and calculating psychoacoustic parameters of the sound sample; Step 2: analyzing the annoyance degree and the psychoacoustic parameters to obtain an annoyance degree correlation model between the annoyance degree and the psychoacoustic parameters; Step 3: Model the acoustic metamaterial structure in finite element software and calculate the transmission loss, adjust the Helmholtz resonator opening diameter, the Helmholtz resonator cavity depth and the cavity length, and adjust the sound insulation frequency band of the metamaterial to the specified target frequency band; Step 4: Calculate the transmission coefficient of the acoustic metamaterial structure, obtain psychoacoustic parameters according to the transmission coefficient, establish the annoyance correlation model, and obtain the noise annoyance; Step 5: Based on the noise annoyance degree under different acoustic metamaterial structures, the cavity length of the Helmholtz resonator structure is adjusted to adjust the peak frequency of the sound insulation band, thereby obtaining an acoustic metamaterial structure with optimal sound quality.

2. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 1, characterized in that: The step one comprises: (11) According to the application scenario, an artificial head is used to collect target noise, and a spectrum analysis is performed on the target noise to determine the main sound insulation frequency band of the metamaterial; (12) conducting a subjective evaluation experiment using the collected target noise as a sound sample to obtain an annoyance degree of each sound sample; (13) Calculate psychoacoustic parameters of the sound sample, wherein the psychoacoustic parameters include loudness, sharpness, roughness and fluctuation intensity.

3. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 2, characterized in that: (131) The steps for calculating loudness include: (a) Using 1 / 3 octave approximation critical band, the spectrum of the sound signal is divided into 28 sub-bands according to the 1 / 3 octave band, wherein the first 6 sub-bands are combined into one characteristic band, the 7th to 9th sub-bands are combined into one characteristic band, and the 10th and 11th sub-bands are combined into one characteristic band, thus obtaining 20 characteristic bands; the sound pressure level in each characteristic band is calculated; (b) Add appropriate external-middle ear transfer factors to the sound pressure level in the characteristic frequency band according to the sound propagation mode and the simulated working mechanism of the human ear; (c) Taking the characteristic sound pressure level through the outer-middle ear transfer factor in (b) as the excitation level, calculate the primary loudness; (d) integrating the characteristic loudness at the psychoacoustic frequency to form a total loudness; wherein the total loudness of the characteristic spectrum includes the main loudness and the ramp loudness, and the calculation formula of the total loudness is: In formula (1), N represents the total loudness, and N' represents the characteristic loudness; (132)The calculation formula of sharpness is: In formula (2), S represents sharpness, C1 represents calibration constant, n'(z) represents characteristic loudness, z represents psychoacoustic frequency, and g(z) represents weight curve; (133) The calculation formula of roughness is: In formula (3), R represents the roughness, f mod represents the modulation frequency, z represents the psychological frequency, ΔL E (z) indicates the masking depth; The masking depth is calculated based on its physical meaning using the change in characteristic loudness of each critical band, ΔL i Substitution, ΔL i The calculation formula is: ΔL i =20lg(N i ' max / N i ' min ) Formula (4) In formula (4), ΔL i Indicates the change in loudness within the i-th frequency band; N i ' max Indicates the maximum value of the characteristic loudness in the i-th frequency band, N i ' min Indicates the minimum value of the characteristic loudness in the i-th frequency band; The calculation formula for volatility intensity includes: In formula (5), ΔL E Indicates the masking depth, f mod represents the modulation frequency and z represents the psychological frequency.

4. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 1, characterized in that: The step 2 includes: conducting a subjective evaluation experiment on the target noise of the step 1 to obtain an annoyance degree, and performing a correlation analysis with the psychoacoustic parameters calculated in the step 1 to obtain a correlation model between the annoyance degree and each psychoacoustic parameter; wherein the correlation model includes a Zwicker annoyance degree calculation model or a multivariate linear regression model.

5. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 1, characterized in that: The step three includes: modeling the acoustic metamaterial structure in finite element software and calculating the transmission loss, adjusting the sound wave propagation path by adjusting the length of the Helmholtz resonator cavity, and adjusting the sound insulation frequency band of the acoustic metamaterial to the specified target frequency band; The acoustic metamaterial structure includes: a plurality of single units arranged in parallel, wherein the single units are in the form of Helmholtz resonators and space bending structures.

6. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 1, characterized in that: The fourth step comprises: (41) calculating the transmission coefficient of the acoustic metamaterial structure; (42) filtering the original signal using the transmission coefficient as a filter to obtain a spectrum of the sound sample after noise reduction processing, and obtaining a time-domain sound sample of the sound signal after noise reduction processing by inverse Fourier transform; (43) Calculating various psychoacoustic parameters of the noise sample after sound insulation treatment, and establishing the annoyance correlation model through subjective evaluation experiments; (44) Calculate the noise annoyance level after sound insulation treatment.

7. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 6, characterized in that: The calculation expression of the transmission coefficient is: In formula (6), τ represents the transmission coefficient.

8. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 1, characterized in that: The step five comprises: By comparing the noise annoyance levels under different structures, the parameters of the acoustic metamaterial structure are adjusted to obtain an acoustic metamaterial structure with optimal sound quality.

9. The method for designing a ventilated sound-insulating metamaterial based on sound quality according to claim 1, characterized in that: The following steps are also included: Step 6: Obtain the parameters of the acoustic metamaterial structure according to step 5, and use 3D printing technology to print the corresponding metamaterial specimen; place the metamaterial specimen in a standing wave tube, and output an acoustic sample of the target noise at the signal transmitting end; Using a microphone at the rear end of the metamaterial specimen to collect noise samples after noise reduction; Step 7: Calculate the psychoacoustic parameters of the noise sample after noise reduction, and compare and verify with the simulation results, wherein the psychoacoustic parameters include loudness, sharpness, roughness and fluctuation intensity.

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