Method and device for predicting underwater sound absorption performance life of sound absorption material for submarine

Abstract

The invention discloses a submarine sound absorption material underwater sound absorption performance life prediction method and device, and relates to the technical field of deep learning. The method comprises the following steps: constructing a life prediction model integrating a macroscopic composite sound absorption model, a micro-fluid model, a micro-fluid model and a micro-perforated plate-like micro-structure model; acquiring a sound absorption material to be detected, inputting the sound absorption material to be detected into the model, calculating a sound wave loss transmission parameter value by utilizing a microscopic fluid model, a microscopic fluid model and a micro-perforated plate-like microscopic structure model, and inputting the sound wave loss transmission parameter value into the macroscopic composite sound absorption model to obtain sound absorption coefficients and sound pressures at different aging times; and determining the sound absorption performance and the material life according to the sound absorption coefficient curve and the sound pressure distribution diagram. According to the method, microstructure changes caused by aging are considered, a sound absorption coefficient curve at any time point is obtained, and life prediction of the long-term sound absorption performance of the underwater sound absorption material is achieved.

Description

Technical Field

[0001] The present application relates to the field of deep learning technology, and in particular to a method and device for predicting the underwater sound absorption performance and life span of a sound-absorbing material for submarines. Background Art

[0002] With the rapid development of marine resource development and underwater equipment technology, underwater sound-absorbing materials, as core functional materials for suppressing sound wave reflection and enhancing stealth performance, have attracted considerable attention for their long-term service reliability. However, when these materials are immersed in seawater for a long time, they are affected by complex factors such as salt corrosion, osmotic pressure, and microbial action. Their microporous structures and micro-perforated plate-like microstructures gradually degrade (e.g., average pore diameter expansion and pore radius changes). This leads to dynamic evolution of sound wave transmission parameters (porosity, flow resistivity, etc.), which in turn causes a decrease in sound absorption performance.

[0003] Some existing research uses finite element simulation (such as COMSOL software) to model the acoustic properties of underwater sound-absorbing materials. For example, these methods employ the JCA equivalent fluid model or the DB-Miki model to calculate the transmission parameters (such as porosity and flow resistivity) of porous materials, and then verify the sound absorption coefficient curves through experimental verification. However, these existing technologies primarily rely on optimizing static structural parameters and fail to consider microstructural changes caused by aging.

[0004] Therefore, there is an urgent need to develop a life prediction method that integrates multi-physics field simulation and structural evolution mathematical models to predict the life of sound-absorbing materials by considering the microstructural changes caused by aging. Summary of the Invention

[0005] Based on this, it is necessary to provide a method and device for predicting the underwater sound absorption performance life of submarine sound-absorbing materials in response to the above technical problems.

[0006] The present invention adopts the following technical solutions: The present invention provides a method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material, comprising: Constructing a life prediction model for underwater sound absorption performance of submarine sound-absorbing materials; the life prediction model for underwater sound absorption performance of submarine sound-absorbing materials is obtained by integrating a macro composite sound absorption model, a micro fluid model, a meso fluid model, and a micro-perforated plate-like mesostructure model; Obtaining parameters of the sound-absorbing material to be tested and inputting them into a prediction model for underwater sound absorption performance and life of submarine sound-absorbing materials; According to the parameters of the sound-absorbing material to be tested, the transmission parameter value of the sound wave loss of the sound-absorbing material to be tested is calculated through the micro-fluid model, the meso-fluid model and the micro-perforated plate-like meso-structure model; The transmission parameter value of the sound wave loss of the sound-absorbing material to be tested is input into the macro composite sound absorption model to obtain the sound absorption coefficient and sound pressure of the sound-absorbing material to be tested at different aging times. The sound absorption coefficient curve and sound pressure distribution diagram are then plotted to determine the sound absorption performance of the sound-absorbing material to be tested. Based on the sound absorption performance of the sound-absorbing material to be tested, the life of the sound-absorbing material to be tested is determined.

[0007] Preferably, the transmission parameter type of the acoustic wave loss of the sound absorbing material to be detected is determined by the polarization resistance of the sound absorbing material to be detected in seawater and the content of heavy metal elements in the corrosion products on its surface.

[0008] Preferably, the transmission parameter values ​​include: a first static flow resistivity, a second static flow resistivity, a thermal characteristic length, a tortuosity, a viscous characteristic length and a porosity.

[0009] Preferably, calculating the static flow resistivity and thermal characteristic length specifically includes: The thickness of the sound-absorbing material to be tested, the pressure difference between the material inlet and outlet, and the material flow rate are input into the microfluid model to calculate the static flow resistivity. σ 1. The formula is: ; Where d is the material thickness, ΔP is the pressure difference between the material inlet and outlet, and u is the material flow rate; The fluid volume and fluid-solid interface area are input into the microfluid model to calculate the thermal characteristic length Λ´ , the formula is: ; Where V f is the volume of the fluid in the domain; S is the fluid-solid interface area.

[0010] Preferably, calculating the tortuosity and the viscous characteristic length specifically includes: Calculate the tortuosity based on the average value of the electric field strength in the z-axis direction α ∞ , the formula is: ; Where, z 〉is the average value of the electric field intensity along the z-axis; Calculate the viscous characteristic length based on the electric field strength Λ , the formula is: ; Where E is the electric field intensity.

[0011] Preferably, calculating the porosity specifically includes: Calculate the porosity based on the volume of air in the sound-absorbing material and the total volume of air and skeleton in the sound-absorbing material. φ , the formula is: ; Where, φ is the porosity; V a is the volume of air in the porous sound-absorbing material; V t is the total volume of air and skeleton in the porous sound-absorbing material; r is the average radius of the polyurethane cavity before aging; a is the side length of the cube.

[0012] Preferably, calculating the transfer impedance parameter specifically includes: The pressure difference between the material inlet and outlet and the material velocity are input into the micro-perforated plate microstructure model to calculate the transfer impedance parameters. , the formula is: ; Where, Δ P is the pressure difference between the material inlet and outlet; ν hole is the material speed.

[0013] Preferably, the macro composite sound absorption model restores the wall of the pulse sound tube, which is a perfect reflector in actual measurement, through acoustic hard boundary conditions, and the sound wave incident mode is vertical incidence.

[0014] Preferably, the macroscopic composite sound absorption model considers its rigid skeleton as a solid and the air in the pores as a fluid.

[0015] A device for predicting underwater sound absorption performance and life of a submarine sound-absorbing material, comprising: Model building module, used to build underwater sound absorption performance and life prediction model for submarine sound absorption materials; A data acquisition module is used to obtain parameters of the sound-absorbing material to be tested; A parameter solving module is used to calculate the transmission parameter value of the sound wave loss of the sound absorbing material to be detected according to the parameters of the sound absorbing material to be detected; The life prediction module is used to draw a sound absorption coefficient curve and a sound pressure distribution diagram based on the sound absorption coefficient and sound pressure of the sound absorption material to be tested at different aging times, and determine the sound absorption performance of the sound absorption material to be tested; based on the sound absorption performance of the sound absorption material to be tested, the life of the sound absorption material to be tested is determined.

[0016] The present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material is implemented.

[0017] At least one of the above technical solutions adopted by the present invention can achieve the following beneficial effects: The present invention provides a method for predicting the underwater sound absorption performance life of submarine sound-absorbing materials. By establishing a three-level coupling system consisting of a microscopic fluid model (pore size evolution of HBF materials), a mesoscopic structure model (change in pore radius of micro-perforated plates), and a macroscopic sound absorption performance model, the transmission parameters obtained from the corresponding microscopic model are substituted into the macroscopic model. Through dynamic mapping of the transmission parameters, the sound absorption coefficient curve at any time point can be obtained, thereby realizing the prediction of the long-term sound absorption performance life of the underwater sound-absorbing material. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 A schematic flow chart of a method for predicting underwater sound absorption performance and lifespan of a submarine sound-absorbing material provided by the present invention; Figure 2 A schematic diagram of the HBF underwater sound-absorbing material microfluid model for a method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material provided by the present invention; Figure 3 A cloud diagram of the flow field of the HBF underwater sound-absorbing material micro-fluid model for a submarine sound-absorbing material underwater sound-absorbing performance life prediction method provided by the present invention; Figure 4 The electric field cloud diagram of the HBF underwater sound-absorbing material micro-fluid model for the underwater sound-absorbing performance life prediction method of the submarine sound-absorbing material provided by the present invention; Figure 5 A 3D spacer fabric surface layer microscopic fluid model for a submarine sound-absorbing material underwater sound-absorbing performance life prediction method provided by the present invention; Figure 6 A cloud diagram of a microscopic fluid model of a 3D spacer fabric surface layer structure for a submarine sound-absorbing material underwater sound-absorbing performance life prediction method provided by the present invention; Figure 7 The fluid velocity field cloud diagram of the HBF underwater sound absorbing material microscopic fluid model at each stage of the underwater sound absorbing performance life prediction method of the submarine sound absorbing material provided by the present invention; Figure 8 The fluid pressure field cloud diagram of the HBF underwater sound absorbing material micro-fluid model at each stage of the underwater sound absorbing performance life prediction method of the submarine sound absorbing material provided by the present invention; Figure 9 The electric field cloud diagram of the HBF underwater sound absorbing material micro-fluid model at each stage of the underwater sound absorbing performance life prediction method of the submarine sound absorbing material provided by the present invention; Figure 10A microscopic model of a micro-perforated plate for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material provided by the present invention; Figure 11 A cloud diagram of a micro-perforated plate-like mesoscopic structure model for a method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material provided by the present invention; Figure 12 An SEM image of a single hole in a micro-perforated plate structure for a method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material provided by the present invention; Figure 13 The sound velocity field of the micro-perforated plate-like mesoscopic structure model at each stage of the underwater sound absorption performance life prediction method of the submarine sound absorption material provided by the present invention; Figure 14 The sound pressure field cloud diagram of the micro-perforated plate-like mesoscopic structure model at each stage of the underwater sound absorption performance life prediction method of the submarine sound absorption material provided by the present invention; Figure 15 The transfer impedance curves of micro-perforated plates at various stages of the underwater sound absorption performance life prediction method of a submarine sound absorption material provided by the present invention; Figure 16 This is a schematic diagram of a device for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material provided by the present invention. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in the specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] The following describes in detail the technical solutions provided by various embodiments of the present application in conjunction with the accompanying drawings.

[0022] Figure 1 The flowchart of the method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material according to the present invention is as follows: S101: Construct a life prediction model for underwater sound absorption performance of submarine sound-absorbing materials.

[0023] Preferably, the transmission parameter of the acoustic wave loss of the sound absorbing material to be detected is determined by the polarization resistance of the sound absorbing material to be detected in seawater and the content of heavy metal elements in the corrosion products on its surface.

[0024] Specifically, through the analysis of the complex frequency dependence function of the sound wave, the calculation formula of the sound absorption characteristics and the aging mechanism of the sound-absorbing material, the physical aging mechanism includes the analysis process of pore collapse caused by high pressure, water scouring and fatigue damage. A pressure chamber is used to simulate different water depths (such as 0~5000 meters) to test the compression rebound resilience of the material; and the attenuation of the material storage modulus with the number of cycles is determined by dynamic mechanical analysis (DMA). The chemical aging mechanism includes the analysis process of salt ion penetration and electrochemical corrosion. The electrochemical impedance spectroscopy (EIS) is used to detect the decrease in the polarization resistance (Rp) of the material in simulated seawater and the increase in the content of heavy metal elements in the surface corrosion products of energy spectrum analysis (EDS). Finally, the factors affecting the acoustic wave loss of underwater sound-absorbing materials are determined: porosity φ , tortuosity α ∞ , viscosity characteristic length Λ , thermal characteristic length Λ´、 Static flow resistivity σ And transfer impedance 6 transmission parameters.

[0025] S102: Obtain parameters of the sound-absorbing material to be tested, and input them into a lifespan prediction model for underwater sound absorption performance of submarine sound-absorbing materials.

[0026] S103: Calculating transmission parameter values ​​of acoustic wave loss of the sound absorbing material to be detected based on the parameters of the sound absorbing material to be detected through a microscopic fluid model, a mesoscopic fluid model, and a micro-perforated plate-like mesoscopic structure model.

[0027] Optionally, the transmission parameter values ​​include: a first static flow resistivity, a second static flow resistivity, a thermal characteristic length, a tortuosity, a viscous characteristic length, and a porosity.

[0028] Optionally, calculating the first static flow resistivity and thermal characteristic length specifically includes: The thickness of the sound-absorbing material to be tested, the pressure difference between the material inlet and outlet, and the material flow rate are input into the microfluid model to calculate the first static flow resistivity. σ 1. The formula is: ; Where d is the material thickness, ΔP is the pressure difference between the material inlet and outlet, and u is the material flow rate. The fluid volume and fluid-solid interface area are input into the microfluid model to calculate the thermal characteristic length. Λ´ , the formula is: ; Where Vf is the volume of the fluid in the domain; S is the fluid-solid interface area.

[0029] Optionally, calculate the tortuosity and viscous characteristic length, specifically including: Calculate the tortuosity based on the average value of the electric field strength in the z-axis direction α∞ , the formula is: ; Where, z 〉is the average value of the electric field intensity along the z-axis; Calculate the viscous characteristic length based on the electric field strength Λ , the formula is: ; Where E is the electric field intensity.

[0030] Calculate the porosity based on the volume of air in the sound-absorbing material and the total volume of air and skeleton in the sound-absorbing material. φ , the formula is: ; Where, φ is the porosity; V a is the volume of air in the porous sound-absorbing material; V t is the total volume of air and skeleton in the porous sound-absorbing material; r is the average radius of the polyurethane cavity before aging; a is the side length of the cube.

[0031] S104: Inputting the transmission parameter value of the sound wave loss of the sound-absorbing material to be tested into the macro composite sound absorption model to obtain the sound absorption coefficient and sound pressure of the sound-absorbing material to be tested at different aging times, and plotting a sound absorption coefficient curve and a sound pressure distribution diagram to determine the sound absorption performance of the sound-absorbing material to be tested; and determining the lifespan of the sound-absorbing material to be tested based on the sound absorption performance of the sound-absorbing material to be tested.

[0032] Optionally, the macro composite sound absorption model restores the wall of the pulse sound tube, which is a perfect reflector in actual measurement, through acoustic hard boundary conditions, and the sound wave incidence mode is vertical incidence.

[0033] Alternatively, a macroscopic composite sound absorption model considers its rigid skeleton as a solid and the air in the pores as a fluid.

[0034] Specifically, a macroscopic composite sound absorption model was established based on a pulsed acoustic tube underwater acoustic test system. The JCA model was selected to represent the acoustic wave propagation of underwater sound-absorbing material structures. In this model, the rigid skeleton is considered a solid, while the air in the pores is considered a fluid. To achieve equivalent substitution, the model uses two complex frequency-dependent functions:

[0035] ; ; Where: ω is the angular frequency; η is the fluid viscosity; ρ0 is the fluid density; γ is the specific heat rate; P 0 is atmospheric pressure; P r is the Prandtl number; Λ is the viscosity characteristic length; Λ´ is the thermal characteristic length; φ is the porosity; σ 1 is the static flow resistance; α ∞ For tortuosity.

[0036] Using "hard boundary conditions," we reconstruct the wall of a perfectly reflective pulse acoustic tube from actual measurements. The acoustic wave is incident vertically, with an incident sound pressure of 1 Pa. In the Materials section, we create two empty materials, naming them Polyurethane and Polyester. We define their properties and then select the corresponding domains.

[0037] Specifically, COMSOL Multiphysics simulation software was used to construct microscopic and mesoscopic models. The Stokes flow equation and Laplace electrical equation were used to solve the transmission parameters of the microfluid model and mesoscopic fluid model (formula). The thermoviscous acoustic equation was used to solve the transfer impedance parameters of the micro-perforated plate-like mesoscopic structure model. This allowed the construction of a microfluid model for underwater sound-absorbing materials, a mesoscopic fluid model for the surface layer of a 3D spacer fabric, and a mesoscopic structure model for a micro-perforated plate-like structure.

[0038] Specifically, the static flow resistivity and thermal characteristic length of the underwater sound-absorbing material before aging were calculated using a microscopic fluid model. The tortuosity and viscous characteristic length were then calculated using the electric field cloud of the microscopic fluid model. The static flow resistivity σ2 in the 3D spacer fabric surface structure mesoscopic fluid model before aging was calculated using the fluid velocity and pressure fields calculated from the 3D spacer fabric surface structure before aging. The porosity was obtained experimentally. The transfer impedance of the sound-absorbing material was calculated using the pre-aging pore radius (spacer wire radius) combined with a micro-perforated plate-like mesostructure model.

[0039] Porosity test process: First, dry the sample and weigh its mass as m0. Then, immerse it in a beaker containing ethanol solution and weigh it to m1. Finally, place the beaker containing the sample and ethanol in a vacuum drying oven and evacuate the sample until no bubbles emerge. After completing the above process, remove the sample and weigh the mass of the container containing residual ethanol and record it as m2. Each sample is tested five times and the average value is obtained. The formula is:

[0040] ; S105: Inputting the transmission parameter value of the sound wave loss of the sound-absorbing material to be tested into the macro composite sound absorption model to obtain the sound absorption coefficient and sound pressure of the sound-absorbing material to be tested at different aging times, and plotting a sound absorption coefficient curve and a sound pressure distribution diagram to determine the sound absorption performance of the sound-absorbing material to be tested; and determining the lifespan of the sound-absorbing material to be tested based on the sound absorption performance of the sound-absorbing material to be tested.

[0041] Optionally, the macro composite sound absorption model restores the wall of the pulse sound tube, which is a perfect reflector in actual measurement, through a “hard boundary condition”, and the sound wave incidence mode is vertical incidence.

[0042] Alternatively, a macroscopic composite sound absorption model considers its rigid skeleton as a solid and the air in the pores as a fluid.

[0043] Specifically, the five transmission parameters and transfer impedance curves of the macro composite sound absorption model with aging of 0, 4, 8, and 12 months obtained above were substituted into the macro composite acoustic model with aging of 0, 4, 8, and 12 months, respectively, to analyze the underwater sound absorption performance of the underwater sound absorbing material, and then analyze whether the macro composite sound absorption model can effectively reflect the sound absorption characteristics of the F-MPPL underwater sound absorbing material.

[0044] Specifically, mathematical models were established to correlate the average pore diameter D of the underwater sound-absorbing material microfluid model with aging time t, and the pore radius R of the microperforated plate-like mesostructure model with aging time t. Ultimately, the mathematical model of average pore diameter versus aging time was used to determine the average pore diameter of the underwater sound-absorbing material microfluid model at any aging time, allowing the calculation of transmission parameters (tortuosity, viscous characteristic length, thermal characteristic length, and static flow resistivity) at any aging time. Furthermore, the mathematical model of pore radius versus aging time was used to determine the pore radius of the microperforated plate-like mesostructure model at any aging time, allowing the calculation of transmission parameters (transfer impedance) at any aging time. By modifying the transmission parameter settings of the macro-composite sound absorption model, the underwater sound absorption coefficient curve and sound pressure distribution of the F-MPPL underwater sound absorption material at any aging time were calculated, thereby clarifying how the underwater sound absorption performance of the underwater sound absorption material changes with different seawater aging times.

[0045] Specifically, this embodiment uses the sample states of the sound-absorbing material to be tested at different aging time points (0 months, 4 months, 8 months, 12 months, etc.) and the microstructure images at different aging times to analyze the porosity φ, tortuosity α ∞ , the changes of structural parameters such as viscous characteristic length Λ, thermal characteristic length Λ´, static flow resistivity σ1 and static flow resistivity σ2, and input them into the underwater sound absorption performance life prediction model of submarine sound absorption materials; (1) HBF underwater sound-absorbing material microfluid model Since the size of hollow glass microspheres is extremely small, the fluid domain of the polyurethane unit cell model is mainly considered in the modeling process. The microscopic fluid model of HBF underwater sound absorbing material is as follows: Figure 2 shown.

[0046] The fluid velocity field and fluid pressure field calculated by the microscopic fluid model of HBF underwater sound absorbing material before aging are as follows: Figure 3 shown.

[0047] The above flow field distribution can be used to calculate the static flow resistivity σ1 and thermal characteristic length Λ´ of the microscopic fluid model of the HBF underwater sound-absorbing material before aging, which can be calculated by Equation (1) and Equation (2) respectively.

[0048] (1); Where: d is the material thickness; Δ P is the pressure difference between the material inlet and outlet; u is the material flow rate.

[0049] (2); Where: V f is the volume of fluid in the domain; S is the fluid-solid interface area.

[0050] Figure 4 The electric field distribution calculated by the microfluid model of HBF underwater sound absorbing material before aging.

[0051] Based on this, the tortuosity of the microscopic fluid model of the HBF underwater sound absorbing material before aging is α ∞ and viscosity characteristic length Λ They can be calculated by formula (3) and formula (4) respectively.

[0052] (3); Where: E z 〉 is the average value of the electric field intensity along the z direction.

[0053] (4); Where: E is the electric field strength.

[0054] (2) 3D spacer fabric surface structure microscopic fluid model Figure 5 The modeling process of the microscopic fluid model for the surface layer of 3D spacer fabric. φ Calculated by formula (5):

[0055] (5); Six transport parameters of the equivalent fluid model before aging (porosity φ, tortuosity α ∞ , viscous characteristic length Λ, thermal characteristic length Λ´, static flow resistivity σ1 and static flow resistivity σ2) are solved. Then, the definition of porosity is used to derive the porosity of the F-MPPL underwater sound absorbing material after aging (4, 8, and 12 months), and then the corresponding transmission parameters are obtained. According to the experimentally measured porosity of the F-MPPL underwater sound absorbing material aged for 0, 4, 8, and 12 months and formula (6), the radii r1, r2, and r3 values ​​of the microfluid model of the HBF underwater sound absorbing material after aging (4, 8, and 12 months) can be derived. Finally, by changing the average pore size parameters of the microfluid model of the HBF underwater sound absorbing material after aging (4, 8, and 12 months), the fluid velocity field of the microfluid model of the HBF underwater sound absorbing material at each aging stage is calculated as follows: Figure 7 As shown, the fluid pressure field (such as Figure 8 As shown) and the electric field cloud diagram is as follows Figure 9 As shown in the figure, the corresponding transmission parameters (tortuosity α) of the microscopic model after aging (4, 8, and 12 months) are finally obtained. ∞ , viscous characteristic length Λ, thermal characteristic length Λ´, static flow resistivity σ1).

[0056] (6); Where: φ is the porosity; V a is the volume of air in the porous sound-absorbing material; V t is the total volume of air and skeleton in the porous sound-absorbing material; r is the average radius of the polyurethane cavity before aging; a is the side length of the cube.

[0057] Previous studies have shown that the surface of the 3D spacer fabric of the F-MPPL underwater sound absorbing material does not change significantly during seawater aging, so the static flow resistivity σ 2 Changes during seawater aging are negligible.

[0058] Finally, the six transport parameters (porosity, φ , tortuosity α ∞ , viscosity characteristic length Λ , thermal characteristic length Λ´ , static flow resistance σ 1 and static flow resistance σ 2) The results can be substituted into the JCA equivalent fluid model and the DB-Miki equivalent flow / model for corresponding calculations.

[0059] (3) Microstructure model of micro-perforated plate The spacer yarns in a 3D spacer fabric form a certain angle with the upper and lower layers. However, research has shown that the tilt of the spacer yarns has a negligible effect on the performance of the F-MPPL underwater sound-absorbing material. Therefore, in this project modeling, the spacer yarns were set to be distributed vertically. Figure 10 This is a microscopic model structure diagram of a quasi-microperforated plate. A quarter-scale simplified model is used, and its main components include a quasi-microperforated structure, background sound field, and a perfectly matched layer.

[0060] In the process of calculating transfer impedance, the thermal loss and viscous loss generated by the sound wave in a specific structure are calculated based on the thermoviscous acoustic equation. Figure 11 Figure 2 shows the sound velocity and pressure field contours calculated for a micro-perforated plate-like mesostructure model at 4000 Hz before aging. To define the sound source, this project uses the "Background Sound Field" node, with both the incident and outgoing sound waves in the form of plane waves.

[0061] The hole radius (spacer wire radius) of the micro-perforated plate-like mesostructure model before aging is 100 μm. The micro-perforated plate-like mesostructure model is calculated based on the thermoviscous acoustic equation.

[0062] (7); Where: Δ P is the pressure difference between the material inlet and outlet; ν is the material speed.

[0063] like Figure 12 As shown in the figure, the cross section of the spacer wire can be approximated as a circle. The area of ​​a single hole in 50 micro-perforated plate structures aged for 4, 8, and 12 months was calculated using ImageJ software, and the average hole radius of the micro-perforated plate micro-structure model at the corresponding stage was derived. Based on this, the modeling parameters of the micro-perforated plate micro-structure model were changed, and the sound velocity field cloud map of the micro-perforated plate micro-structure model at each aging stage at 4000 Hz was calculated (see Figure 2). Figure 13 as shown) and the sound pressure field cloud diagram (as shown Figure 14 As shown in Figure 2), the transfer impedance curve of the micro-perforated plate model after aging (4, 8, and 12 months) can be finally obtained, as shown in Figure 2. Figure 15 shown.

[0064] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.

[0065] The above is a method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding device for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material, such as Figure 16 shown.

[0066] Figure 16 A schematic diagram of a device for predicting underwater sound absorption performance and life of a submarine sound-absorbing material provided by the present invention, the device comprising: Model building module, used to build underwater sound absorption performance and life prediction model for submarine sound absorption materials; A data acquisition module is used to obtain parameters of the sound-absorbing material to be tested; A parameter solving module is used to calculate the transmission parameter value of the sound wave loss of the sound absorbing material to be detected according to the parameters of the sound absorbing material to be detected; The life prediction module is used to draw a sound absorption coefficient curve and a sound pressure distribution diagram based on the sound absorption coefficient and sound pressure of the sound absorption material to be tested at different aging times, and determine the sound absorption performance of the sound absorption material to be tested; based on the sound absorption performance of the sound absorption material to be tested, the life of the sound absorption material to be tested is determined.

Claims

1. A method for predicting the underwater sound absorption performance and life of a submarine sound-absorbing material, characterized in that: include: Constructing a life prediction model for underwater sound absorption performance of submarine sound-absorbing materials; the life prediction model for underwater sound absorption performance of submarine sound-absorbing materials is obtained by integrating a macro composite sound absorption model, a micro fluid model, a meso fluid model, and a micro-perforated plate-like mesostructure model; Obtaining parameters of the sound-absorbing material to be tested and inputting them into a prediction model for underwater sound absorption performance and life of submarine sound-absorbing materials; According to the parameters of the sound-absorbing material to be tested, the transmission parameter value of the sound wave loss of the sound-absorbing material to be tested is calculated through the microfluid model, the mesofluid model and the micro-perforated plate-like mesostructure model; The transmission parameter value of the sound wave loss of the sound-absorbing material to be tested is input into the macro composite sound absorption model to obtain the sound absorption coefficient and sound pressure of the sound-absorbing material to be tested at different aging times. The sound absorption coefficient curve and sound pressure distribution diagram are then plotted to determine the sound absorption performance of the sound-absorbing material to be tested. Based on the sound absorption performance of the sound-absorbing material to be tested, the life of the sound-absorbing material to be tested is determined.

2. The method for predicting underwater sound absorption performance and life of a submarine sound absorbing material according to claim 1, characterized in that: The transmission parameter type of the acoustic wave loss of the sound absorbing material to be detected is determined by the polarization resistance of the sound absorbing material to be detected in seawater and the content of heavy metal elements in the corrosion products on its surface.

3. The method for predicting underwater sound absorption performance and life of submarine sound absorbing materials according to claim 1, characterized in that: The transmission parameter values ​​include static flow resistivity, thermal characteristic length, tortuosity, viscous characteristic length, porosity and transfer impedance.

4. The method for predicting underwater sound absorption performance and life of a submarine sound absorbing material according to claim 2, wherein: Calculate static flow resistivity and thermal characteristic length, including: The thickness of the sound-absorbing material to be tested, the pressure difference between the material inlet and outlet, and the material flow rate are input into the microfluid model to calculate the static flow resistivity. σ , the formula is: ； Where d is the material thickness, ΔP is the pressure difference between the material inlet and outlet, and u is the material flow rate; The fluid volume and fluid-solid interface area are input into the microfluid model to calculate the thermal characteristic length Λ´ , the formula is: ； Where V f is the volume of the fluid in the domain; S is the fluid-solid interface area.

5. The method for predicting underwater sound absorption performance and life of submarine sound absorbing materials according to claim 2, characterized in that: Calculates tortuosity and viscous characteristic length, including: The electric field strength and its average value in the z-axis direction are input into the microscopic fluid model to calculate the tortuosity α ∞ and viscosity characteristic length Λ , the formula is: ； ； Where, z 〉 is the average value of the electric field intensity along the z-axis; E is the electric field intensity.

6. The method for predicting underwater sound absorption performance and life of a submarine sound absorbing material according to claim 2, wherein: Calculate porosity, including: Calculate the porosity based on the volume of air in the sound-absorbing material and the total volume of air and skeleton in the sound-absorbing material. φ , the formula is: ； Where, φ is the porosity; V a is the volume of air in the porous sound-absorbing material; V t is the total volume of air and skeleton in the porous sound-absorbing material; r is the average radius of the polyurethane cavity before aging; a is the side length of the cube.

7. The method for predicting underwater sound absorption performance and life of a submarine sound absorbing material according to claim 2, wherein: Calculate transfer impedance parameters, including: The pressure difference between the material inlet and outlet and the material velocity are input into the micro-perforated plate microstructure model to calculate the transfer impedance parameters. , the formula is: ； Where, Δ P is the pressure difference between the material inlet and outlet; ν hole is the material speed.

8. The method for predicting underwater sound absorption performance and life of submarine sound absorbing materials according to claim 1, characterized in that: The macro composite sound absorption model restores the wall of the pulse sound tube, a perfect reflector, in actual measurement through acoustic hard boundary conditions, and the sound wave incident mode is vertical incidence.

9. The method for predicting underwater sound absorption performance and life of a submarine sound absorbing material according to claim 1, wherein: The macroscopic composite sound absorption model regards its rigid skeleton as a solid and the air in the pores as a fluid.

10. A device for predicting underwater sound absorption performance and life of submarine sound absorbing materials, characterized in that: include: Model building module, used to build underwater sound absorption performance and life prediction model for submarine sound absorption materials; A data acquisition module is used to obtain parameters of the sound-absorbing material to be tested; A parameter solving module is used to calculate the transmission parameter value of the sound wave loss of the sound absorbing material to be detected according to the parameters of the sound absorbing material to be detected; The life prediction module is used to draw a sound absorption coefficient curve and a sound pressure distribution diagram based on the sound absorption coefficient and sound pressure of the sound absorption material to be tested at different aging times, and determine the sound absorption performance of the sound absorption material to be tested; based on the sound absorption performance of the sound absorption material to be tested, the life of the sound absorption material to be tested is determined.

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