A design method for ventilated sound-insulating metamaterials based on sound quality

Abstract

The present invention provides a method for designing a ventilated sound-insulating metamaterial based on sound quality, comprising: collecting target noise for spectral analysis to determine the primary sound-insulating frequency band of the metamaterial; determining the annoyance of a sound sample of the target noise and calculating psychoacoustic parameters of the sound sample; analyzing the annoyance and psychoacoustic parameters to obtain an annoyance correlation model; modeling the acoustic metamaterial structure and calculating transmission loss, adjusting the sound-insulating frequency band of the metamaterial to a specified target frequency band by adjusting parameters of the acoustic metamaterial structure; calculating the transmission coefficient of the acoustic metamaterial structure, obtaining psychoacoustic parameters based on the transmission coefficient, establishing an annoyance correlation model, and obtaining noise annoyance; and adjusting parameters based on the noise annoyance of different acoustic metamaterial structures to obtain an acoustic metamaterial structure with optimal sound quality. The present invention uses the sound quality annoyance as the basis for metamaterial design effectiveness, significantly reducing the sound quality annoyance within a limited size.

Description

Technical Field

[0001] The present 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] Noise reduction is a problem in engineering that is both ancient and ever-changing, both traditional and challenging. Noise pollution seriously impacts human health and has become a recognized environmental issue worldwide. Noise pollution also affects the hearing system. Excessive exposure to sound initially causes a temporary threshold shift. With continued exposure, this temporary threshold shift can lead to a permanent shift, resulting in hearing loss.

[0003] To prevent noise-induced hearing loss, effectively blocking low-frequency sound waves and attenuating noise energy based on the three key elements of noise propagation—the source, the transmission path, and the receiver—has always been a challenging task. By analogy with photonic crystals, MS Kushwaha et al. first proposed the concept of phononic crystals in 1993. They used plane wave methods to calculate the elastic bandgap along the shear polarization direction for a composite medium composed of nickel pillars in an aluminum alloy matrix, thus giving rise to the concept of 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-isolating metamaterials, they can achieve good sound absorption and isolation peaks within a specified frequency range through preliminary design. The drawback is that they only have one sound wave band gap with a relatively narrow frequency band. To achieve broadband sound absorption and isolation, more units are usually required to be coupled, which greatly increases the size of the metamaterial. Therefore, when the size is limited, it is very necessary to maximize the use of the sound absorption and isolation bandwidth of the material.

[0005] Since the 1930s, a large number of noise evaluation indicators have been proposed. The International Organization for Standardization (ISO) recommended the weighted sound level and the Noise Rating Number (NR) for steady-state noise early on. For a long time, the A-weighted sound level was the primary objective parameter for noise evaluation, with the C-weighted sound level also occasionally used. Other objective parameters based on the A-weighted sound level were also used, such as the cumulative percentage A-weighted sound level, noise intensity, and noise pollution level.

[0006] The A- and C-levels are frequency-domain weighted representations of the sound pressure level (SPL), roughly simulating the human ear's perception of loudness. However, the human ear's subjective perception of sound is closely related to the time and frequency domain characteristics of the acoustic signal, not solely to loudness. Real-world sounds, especially noise, exhibit vastly different time and frequency domain characteristics. Therefore, traditional weighted sound level measures, which primarily reflect loudness, cannot fully capture the human ear's subjective perception of noise. Summary of the Invention

[0007] The purpose of the present invention is to address the shortcomings of the existing technology in that it cannot better reflect people's subjective perception of sound. Instead, it provides 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 degree is used as the basis for the design effect of the metamaterial, so that the sound quality annoyance degree is greatly reduced within a limited size.

[0008] To achieve the above objectives, the technical solutions provided by the present invention are:

[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, Helmholtz resonator cavity depth, and cavity length to adjust the metamaterial's sound insulation band 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 the annoyance degree of each sound sample;

[0018] (13) Calculating 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 loudness includes:

[0020] (a) Using the 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. 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, resulting in 20 characteristic bands. The sound pressure level in each characteristic band is calculated.

[0021] (b) Adding appropriate external-middle ear transfer factors to the sound pressure levels in the characteristic frequency bands based on the sound propagation mode and the simulated working mechanism of the human ear;

[0022] (c) Calculate the primary loudness by taking the characteristic sound pressure level of the transfer factor through the outer and middle ear in (b) as the stimulus level;

[0023] (d) Integrating the characteristic loudness over the psychoacoustic frequency spectrum 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 for 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 for roughness is:

[0030]

[0031] In formula (3), R represents the roughness, f modrepresents the modulation frequency, z represents the psychological frequency, ΔL E (z) represents 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, step 2 includes: conducting a subjective evaluation experiment on the target noise of step 1 to obtain an annoyance degree, and performing a correlation analysis with the psychoacoustic parameters calculated in 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 multiple linear regression model.

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

[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 the spectrum of the sound sample after noise reduction processing, and obtaining the 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 transmission coefficient is calculated as follows:

[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 print the corresponding metamaterial specimen using 3D printing technology; place the metamaterial specimen in a standing wave tube, and output a sound sample of the target noise at the signal transmitting end; and use a microphone at the rear end of the metamaterial specimen to collect a sound sample of the noise after noise reduction;

[0053] Step 7: Calculate the psychoacoustic parameters of the noise sample after noise reduction and compare them with the simulation results for verification, 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 a frequency range of 500Hz-1000Hz, uses the sound quality annoyance as the basis for the design effect of the metamaterial, and significantly reduces the sound quality annoyance within a limited size.

[0056] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by 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 readily understood from the following description of the embodiments with reference to the accompanying drawings, in which:

[0058] Figure 1 :The present invention provides a design method process of a ventilated sound insulation metamaterial based on sound quality Figure 1 ;

[0059] Figure 2 :The present invention provides a design method process of a ventilated sound insulation metamaterial based on sound quality Figure 2 ;

[0060] Figure 3 : 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 of the acoustic metamaterial structure provided by the present invention;

[0062] Figure 5 : Schematic diagram of a single unit and overall structural 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] The following describes in detail embodiments of the present invention. The embodiments are exemplary and intended to explain the present invention, but are not to 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 ventilated sound-insulating metamaterials 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 Steps 1 to 5 shown, the experimental verification stage 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 using 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 subjective evaluation experiment of annoyance level in a method for grading and limiting values ​​of satisfaction with range hood sound quality published in the Journal of Applied Acoustics in September 2021.

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

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

[0072] (a) Using the 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. 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, resulting in 20 characteristic bands. The sound pressure level in each characteristic band is calculated.

[0073] (b) Adding appropriate external-middle ear transfer factors to the sound pressure levels in the characteristic frequency bands based on the sound propagation mode and the simulated working mechanism of the human ear;

[0074] (c) Calculate the primary loudness by taking the characteristic sound pressure level of the transfer factor through the outer and middle ear in (b) as the stimulus level;

[0075] (d) Integrating the characteristic loudness over the psychoacoustic frequency spectrum 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 for 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 for 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) represents 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 an annoyance level, performing a correlation analysis with the psychoacoustic parameters calculated in step 1, and obtaining a correlation model between the annoyance level and each psychoacoustic parameter; wherein the correlation model includes a Zwicker annoyance level 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, Helmholtz resonator cavity depth, and cavity length to adjust the sound insulation band of the metamaterial to the specified target frequency band.

[0093] The above-mentioned step three of the embodiment of the present invention includes: modeling the acoustic metamaterial structure and calculating the transmission loss in finite element software, 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] Among them, the acoustic metamaterial structure includes: multiple single units 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 = 10 mm, t = 1 mm, da = 2 mm, W = 12 mm, and B = 3 mm.

[0095] Step 4: Calculate the transmission coefficient of the acoustic metamaterial structure, obtain 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 the spectrum of the sound sample after noise reduction processing, and obtaining the 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 level of 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 consists of four units spliced ​​together to form 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 back end of the metamaterial specimen to collect the noise sample after noise reduction.

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

[0108] The embodiment of the present invention targets sounds with a frequency range of 500 Hz to 1000 Hz, uses the sound quality annoyance as a basis for the design effect of the metamaterial, and significantly reduces the sound quality annoyance within a limited size.

[0109] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present invention, and these modifications or replacements should all be included in the scope of protection 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 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, Helmholtz resonator cavity depth, and cavity length to adjust the metamaterial's sound insulation band to the specified target frequency band. Step 4: Calculate the transmission coefficient of the acoustic metamaterial structure, obtain psychoacoustic parameters based on the transmission coefficient, establish the annoyance correlation model, and obtain the noise annoyance; Step 5: Based on the noise annoyance levels of 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; Specifically: Step 1 includes: (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 the annoyance degree of each sound sample; (13) Calculating psychoacoustic parameters of the sound sample, wherein the psychoacoustic parameters include loudness, sharpness, roughness, and fluctuation intensity. Wherein, the step of calculating loudness (131) includes: (a) Using the 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. 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, resulting in 20 characteristic bands. The sound pressure level in each characteristic band is calculated. (b) Adding appropriate external-middle ear transfer factors to the sound pressure levels in the characteristic frequency bands based on the sound propagation mode and the simulated working mechanism of the human ear; (c) Calculate the primary loudness by taking the characteristic sound pressure level of the transfer factor through the outer and middle ear in (b) as the stimulus level; (d) Integrating the characteristic loudness over the psychoacoustic frequency spectrum 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 for 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 the calibration constant, n′(z) represents characteristic loudness, z represents psychoacoustic frequency, and g(z) represents the weight curve; (133) The calculation formula for roughness is: In formula (3), R represents the roughness, f mod represents the modulation frequency, z represents the psychological frequency, ΔL E (z) represents the masking depth; the masking depth is calculated based on its physical meaning using the change in the characteristic loudness of each critical band, ΔL i Substitution, ΔL i The calculation formula is: ΔL i =201g(N′ imax / N′ imin ) Formula (4) 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; The calculation formula for volatility intensity includes: In formula (5), ΔL E Indicates the masking depth, f mod represents the modulation frequency, z represents the psychological frequency; Specifically, the step 2 includes: conducting a subjective evaluation experiment on the target noise in 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 multiple linear regression model; Specifically, the step three includes: modeling the acoustic metamaterial structure and calculating the transmission loss in finite element software, adjusting the sound wave propagation path by adjusting the length of the Helmholtz resonator cavity, and adjusting the sound insulation band of the acoustic metamaterial to a specified target frequency band; The acoustic metamaterial structure includes: a plurality of single units arranged in parallel, wherein the single units adopt the form of Helmholtz resonator and space bending structure; Specifically, the step 4 includes: (41) calculating the transmission coefficient of the acoustic metamaterial structure; (42) Filtering the original signal using the transmission coefficient as a filter to obtain the spectrum of the sound sample after noise reduction processing, and obtaining the 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; Among them, the calculation expression of the transmission coefficient is: In formula (6), τ represents the transmission coefficient and TL represents the transmission loss; Specifically, the step five includes: 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; The following steps are also included: Step 6: Obtain the parameters of the acoustic metamaterial structure according to step 5, and print the corresponding metamaterial specimen using 3D printing technology; place the metamaterial specimen in a standing wave tube, and output a sound sample of the target noise at the signal transmitting end; and use a microphone at the rear end of the metamaterial specimen to collect a sound sample of the noise after noise reduction; Step 7: Calculate the psychoacoustic parameters of the noise sample after noise reduction and compare them with the simulation results for verification, wherein the psychoacoustic parameters include loudness, sharpness, roughness and fluctuation intensity.

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