Piezoelectric film acoustic sensor packaging design method, device and system

Abstract

The invention discloses a piezoelectric film acoustic sensor packaging design method, device and system, and the method comprises the steps: obtaining a pre-constructed multi-physical field coupling optimization model, a target function of the multi-physics field coupling optimization model is constructed by taking maximization of sound pressure sensitivity, minimization of frequency deviation and minimization of a parasitic common amplitude value as targets; a Bayesian global optimization algorithm is adopted, the multi-physics field coupling optimization model is solved, piezoelectric film acoustic sensor packaging parameters are obtained, a CNN model is adopted as an agent optimization model in the Bayesian global optimization algorithm and used for fitting a target function of the multi-physics field coupling optimization model, and in the solving process, the packaging parameters of the piezoelectric film acoustic sensor are obtained. The weights of different optimization sub-targets are dynamically adjusted according to the environmental parameters, and the optimization sub-targets comprise the maximum sound pressure sensitivity, the minimum frequency deviation and the minimum parasitic common amplitude value. The anti-interference performance and the stability of the piezoelectric film acoustic sensor can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of acoustic sensing technology, and in particular relates to a piezoelectric film acoustic sensor packaging design method, device and system. Background Art

[0002] With the continuous advancement of industrial automation and intelligence, fault detection and health monitoring of electrical equipment are becoming increasingly important. Mechanical vibration and partial discharge signals are particularly important in high-voltage electrical equipment, substations, distribution networks, and motor systems. They are crucial parameters for reflecting equipment operating status and potential faults. Timely and accurate monitoring of these signals can effectively prevent equipment failures, improve operational reliability, and reduce the risk of accidents.

[0003] Traditional vibration sensors typically use piezoelectric sensors, capacitive sensors, or accelerometers. However, these sensors are often large, heavy, and sensitive to environmental interference. They are also prone to performance degradation in environments with high temperature, high humidity, or strong electromagnetic interference. Partial discharge detection typically relies on traditional electrical or ultrasonic sensors, which are difficult to tightly integrate with equipment and suffer from poor measurement signal accuracy and stability.

[0004] Micro-electro-mechanical systems (MEMS) technology, due to its miniaturization, high precision, low power consumption, and high integration, has gradually become a key technology in the sensor field. MEMS acoustic sensors, in particular, can accurately capture weak mechanical vibration and electrical discharge signals through their sensitive diaphragms responding to vibrations or sound waves. Therefore, the use of MEMS acoustic sensors for monitoring mechanical vibration and partial discharge signals in electrical equipment holds great potential.

[0005] However, since MEMS acoustic sensors are very delicate and easily affected by the external environment, especially in the complex environment of high-voltage electrical equipment, how to effectively package MEMS acoustic sensors to improve their anti-interference and stability has become a technical problem that needs to be solved urgently. Summary of the Invention

[0006] In response to the above problems, the present invention proposes a piezoelectric film acoustic sensor packaging design method, device and system, which can improve the anti-interference performance and stability of the piezoelectric film acoustic sensor.

[0007] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0008] In a first aspect, the present invention provides a piezoelectric thin film acoustic sensor packaging design method, comprising:

[0009] Obtaining a pre-built multi-physics field coupling optimization model, wherein the objective function of the multi-physics field coupling optimization model is constructed with the goal of maximizing sound pressure sensitivity, minimizing frequency shift, and minimizing parasitic resonance amplitude;

[0010] A Bayesian global optimization algorithm is used to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor. The CNN model is used as a proxy optimization model in the Bayesian global optimization algorithm to fit the objective function. During the solution process, the weights of different optimization sub-goals are dynamically adjusted according to environmental parameters. The optimization sub-goals include maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude.

[0011] In combination with the first aspect, optionally, the mathematical expression of the objective function of the multi-physics field coupling optimization model is:

[0012] ,

[0013] Where, The objective function for the multiphysics coupled optimization model is is the sound pressure sensitivity, is the frequency offset, is the parasitic resonance amplitude, 、 、 are all weight coefficients; the sound pressure sensitivity, frequency shift and parasitic resonance amplitude are all calculated based on the elastic stiffness, piezoelectric constant, dielectric constant, structural parameters and constitutive equation of the piezoelectric film;

[0014] The constraints of the multi-physics field coupling optimization model include:

[0015] Piezoelectric film thickness ,in, is the minimum thickness of the piezoelectric film, is the maximum thickness of the piezoelectric film;

[0016] Cavity depth ,in, is the working wavelength;

[0017] Piezoelectric film radius , in, is the minimum radius of the piezoelectric film, is the maximum value of the piezoelectric film radius;

[0018] Resonant frequency ,in, is the center frequency of the target frequency band, is the target bandwidth.

[0019] In combination with the first aspect, optionally, the input parameters of the CNN model include the elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of the piezoelectric film, and the output parameter is the objective function The true value of , its loss function is:

[0020] ,

[0021] Where, is the loss function; is the total number of acquisition points, each of which includes the elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of the piezoelectric film. For the Collection points, is the output value of the CNN model, is the true value, is the regularization term, is the coefficient of the regularization term.

[0022] In combination with the first aspect, optionally, the Bayesian global optimization algorithm is used to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor, specifically including:

[0023] Based on the current proxy model, find the parameter points of the optimal acquisition function, which include 、 、 , elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of piezoelectric films;

[0024] Based on the parameter point, the value of the objective function of the multi-physics field coupling optimization model is calculated;

[0025] The parameters 、 、 , the elastic stiffness, piezoelectric constant, dielectric constant, structural parameters and objective function values ​​of the piezoelectric film are taken as new parameter points and added into the observation data set to obtain an updated observation data set;

[0026] The surrogate model is retrained and updated using the updated observation dataset until the objective function of the multiphysics coupled optimization model converges.

[0027] In conjunction with the first aspect, optionally, dynamically adjusting the weights of different optimization sub-objectives according to environmental parameters specifically includes:

[0028] Weighting based on temperature parameters The adjustment formula used is:

[0029] ,

[0030] ,

[0031] Where, is the adjusted weight, is the absolute difference between the current temperature and the reference temperature, is the current temperature, is the reference temperature, is the initial weight, is the temperature threshold;

[0032] Weighting based on vibration amplitude parameters The adjustment formula used is:

[0033] ,

[0034] Where, is the adjusted weight, is the initial weight, is the vibration amplitude detected by the vibration sensor, is the vibration amplitude threshold.

[0035] In conjunction with the first aspect, optionally, dynamically adjusting the weights of different optimization sub-objectives according to environmental parameters further includes:

[0036] Weighting based on temperature parameters and vibration amplitude parameters The adjustment formula used is:

[0037] .

[0038] In combination with the first aspect, optionally, after the step of solving the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor, the method further includes:

[0039] Obtaining a resonant frequency shift detected by a vibration sensor;

[0040] According to the resonance frequency offset fed back by the vibration sensor, the bias voltage is adjusted based on the PID algorithm. , the adjusted bias voltage It is used to control the deformation of the piezoelectric film so that the absolute value of the frequency offset is less than the set frequency offset threshold.

[0041] In combination with the first aspect, optionally, the PID algorithm uses the following formula to calculate the adjusted bias voltage :

[0042] ,

[0043] Where, 、 、 They are proportional gain, integral gain and differential gain respectively, express time, is the resonant frequency shift; express moment, is the integration operator; express The resonant frequency shift at that moment.

[0044] In a second aspect, the present invention provides a piezoelectric thin film acoustic sensor packaging design device, comprising:

[0045] A multi-physics coupling optimization model acquisition module is used to acquire a pre-built multi-physics coupling optimization model, wherein the objective function of the multi-physics coupling optimization model is constructed with the goal of maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude;

[0046] The packaging parameter design module is used to use a Bayesian global optimization algorithm to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor. The CNN model is used as a proxy optimization model in the Bayesian global optimization algorithm to fit the objective function. During the solution process, the weights of different optimization sub-goals are dynamically adjusted according to environmental parameters. The optimization sub-goals include maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude.

[0047] In a third aspect, the present invention provides a piezoelectric film acoustic sensor package design system, comprising a storage medium and a processor;

[0048] The storage medium is used to store instructions;

[0049] The processor is configured to operate according to the instructions to execute the method according to any one of the first aspects.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The present invention constructs a multi-physics field coupling optimization model with the goal of maximizing sound pressure sensitivity, minimizing frequency offset and minimizing parasitic resonance amplitude. During the solution process, the CNN model is used as a proxy optimization model of the Bayesian optimization algorithm, breaking through the limitations of traditional single-objective optimization and effectively improving the anti-interference and stability of MEMS piezoelectric film acoustic sensors.

[0052] The present invention also proposes to dynamically adjust the weights of the multi-physics field coupling optimization model constructed according to the environment to adapt to the influence of the environment and significantly improve the acoustic performance and environmental adaptability.

[0053] In order to further reduce environmental interference, the present invention adopts active piezoelectric tuning for compensation improvement as a feedback signal to achieve the weight adjustment of the target multi-physics field coupling optimization model, and ultimately reduce the environmental impact. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive work, among which:

[0055] Figure 1 The figure is a flow chart of a method for designing a piezoelectric film acoustic sensor package according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0057] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features specified as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0058] Example 1

[0059] The present invention provides a method for designing a piezoelectric film acoustic sensor package. Figure 1 As shown, the following steps are included:

[0060] (1) obtaining a pre-built multi-physics field coupling optimization model, wherein the objective function of the multi-physics field coupling optimization model is constructed with the goal of maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude;

[0061] (2) A Bayesian global optimization algorithm is used to solve the multi-physics field coupling optimization model and obtain the packaging parameters of the piezoelectric thin film acoustic sensor. The CNN model is used as a proxy optimization model in the Bayesian global optimization algorithm to fit the objective function. During the solution process, the weights of different optimization sub-goals are dynamically adjusted according to the environmental parameters. The optimization sub-goals include maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude.

[0062] In the above scheme, a multi-physics field coupling optimization model is constructed with the goals of maximizing sound pressure sensitivity, minimizing frequency offset and minimizing parasitic resonance amplitude. During the solution process, the CNN model is used as a proxy optimization model of the Bayesian optimization algorithm, breaking through the limitations of traditional single-objective optimization and effectively improving the anti-interference and stability of MEMS piezoelectric film acoustic sensors.

[0063] In a specific implementation of the embodiment of the present invention, the mathematical expression of the objective function of the multi-physics field coupling optimization model is:

[0064] ,

[0065] Where, The objective function for the multiphysics coupled optimization model is is the sound pressure sensitivity, is the frequency offset, is the parasitic resonance amplitude, 、 、 are all weight coefficients; the sound pressure sensitivity, frequency shift and parasitic resonance amplitude are all calculated based on the elastic stiffness, piezoelectric constant, dielectric constant, structural parameters and constitutive equation of the piezoelectric film;

[0066] The constraints of the multi-physics field coupling optimization model include:

[0067] Piezoelectric film thickness ,in, is the minimum thickness of the piezoelectric film, is the maximum thickness of the piezoelectric film;

[0068] Cavity depth ,in, is the working wavelength;

[0069] Piezoelectric film radius , in, is the minimum radius of the piezoelectric film, is the maximum value of the piezoelectric film radius;

[0070] Resonant frequency ,in, is the center frequency of the target frequency band, is the target bandwidth.

[0071] In the above scheme, the objective function and constraints of the multi-physics coupling optimization model are specifically defined to facilitate subsequent implementation. The constitutive equation of piezoelectric film is the core mathematical model describing the electromechanical coupling behavior of piezoelectric materials, revealing the bidirectional relationship between mechanical stress / strain and electric field / displacement. For MEMS piezoelectric films (such as aluminum nitride (AlN) or lead zirconate titanate (PZT),) this constitutive equation provides the theoretical foundation for designing sensor packaging and optimizing sensitivity and stability.

[0072] The piezoelectric effect includes the direct piezoelectric effect (mechanical energy → electrical energy) and the inverse piezoelectric effect (electrical energy → mechanical energy). Its constitutive equation can be expressed as:

[0073] Linearized piezoelectric equation (tensor form):

[0074] ,

[0075] in:

[0076] : Stress tensor (Pa), which describes the force per unit area inside the material.

[0077] : Strain tensor, describing the degree of material deformation (dimensionless).

[0078] : Electric field strength (V / m), generated by external voltage or polarization.

[0079] : Electric displacement (C / m²), which reflects the charge distribution under the combined action of the electric field and material polarization.

[0080] : Elastic stiffness matrix (Pa), which represents the stiffness characteristics of the material under a constant electric field.

[0081] : Piezoelectric stress constant (C / m²), which describes the stress caused by unit electric field or the electric displacement caused by unit strain.

[0082] : Dielectric constant matrix (F / m), representing the dielectric properties under constant strain.

[0083] 、 、 、 Direction index, value 1, 2, 3 corresponds to 、 、 In the linear piezoelectric equations, their order and combination clearly describe the directional relationship of the electromechanical coupling. By simplifying them, the number of non-zero components can be reduced, thus lowering the computational complexity.

[0084] Since the tensor form is computationally complex, a simplified matrix representation (Voigt notation) is used to compress the fourth-order tensor into a matrix:

[0085] Stress and strain vectors: ,correspond .

[0086] The piezoelectric equation simplifies to:

[0087] ,

[0088] in:

[0089] : 6×6 elastic stiffness matrix (symmetric);

[0090] : 3×6 piezoelectric constant matrix;

[0091] : 3×3 dielectric constant matrix (symmetric)

[0092] : The unit diagonal matrix.

[0093] : 6×1 strain vector, reflecting the degree of material deformation, dimensionless.

[0094] For AlN piezoelectric film, its piezoelectric constant matrix (unit: C / m²):

[0095] ,

[0096] Typical values , , .

[0097] The specific method of the sound pressure sensitivity, frequency offset and parasitic resonance amplitude includes:

[0098] Perform multi-physics coupling (parameter configuration stage):

[0099] In COMSOL, the constitutive equations are embedded in the following steps:

[0100] Defining Material Properties: Input 、 、 matrix.

[0101] Boundary condition settings:

[0102] Mechanical Boundary: Fixed support beam endpoints (displacement = 0).

[0103] Electrical boundary: applied voltage or short circuit condition (E=0).

[0104] Multiphysics coupling results:

[0105] 1. The acoustic module in COMSOL calculates the sound pressure distribution and calculates the sound pressure sensitivity from the sound pressure distribution and obtain the resonant frequency offset through the acoustic frequency simulation module .

[0106] 2. The Solid Mechanics Module in COMSOL solves the strain field ϵ.

[0107] 3. The electrostatic module in COMSOL calculates the electric field E and electric displacement D to obtain the parasitic resonance amplitude .

[0108] In a specific implementation of the embodiment of the present invention, the input parameters of the CNN model include the elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of the piezoelectric film, and its output parameter is the objective function The true value of , its loss function is:

[0109] ,

[0110] Where, is the loss function; is the total number of acquisition points, each of which includes the elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of the piezoelectric film. For the Collection points, is the output value of the CNN model, is the true value, is the regularization term, is the coefficient of the regularization term.

[0111] Bayesian optimization is an efficient strategy for global optimization of black-box functions. Its core idea is to balance exploration (unknown areas) and development (known optimal areas) through iterative optimization of surrogate models and acquisition functions. The CNN model is a method that uses deep learning to replace traditional surrogate models (such as Gaussian processes), which is suitable for processing high-dimensional parameter spaces and complex nonlinear relationships. The network structure of the CNN model includes a convolution layer, a pooling layer, and a fully connected layer; the convolution layer is used to extract local features; the pooling layer is used to reduce dimensionality and enhance robustness; the fully connected layer is used to map features to the predicted value of the objective function. The network structure of the CNN model in the embodiment of the present invention is in the prior art. In a specific implementation of the embodiment of the present invention, the Bayesian global optimization algorithm is used to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor, which specifically includes:

[0112] Based on the current proxy model, find the parameter points of the optimal acquisition function, which include 、 、 , elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of piezoelectric films;

[0113] Based on the parameter point, the value of the objective function of the multi-physics field coupling optimization model is calculated;

[0114] The parameters 、 、 , the elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of the piezoelectric film and the value of the objective function are taken as new parameter points and added into the observation data set to obtain an updated observation data set;

[0115] The surrogate model is retrained and updated using the updated observation dataset until the objective function of the multiphysics coupled optimization model converges.

[0116] In a specific implementation of the embodiment of the present invention, dynamically adjusting the weights of different optimization sub-objectives according to environmental parameters specifically includes:

[0117] Weighting based on temperature parameters The adjustment formula used is:

[0118] ,

[0119] ,

[0120] Where, is the adjusted weight, is the absolute difference between the current temperature and the reference temperature, is the current temperature, is the reference temperature, is the initial weight, is the temperature threshold;

[0121] Weighting based on vibration amplitude parameters The adjustment formula used is:

[0122] ,

[0123] Where, is the adjusted weight, is the initial weight, is the vibration amplitude detected by the vibration sensor, is the vibration amplitude threshold.

[0124] The dynamically adjusting the weights of different optimization sub-objectives according to the environmental parameters also includes:

[0125] Weighting based on temperature parameters and vibration amplitude parameters The adjustment formula used is:

[0126] .

[0127] In the above scheme, the weights of each optimization objective are dynamically adjusted based on real-time environmental feedback, aiming to prioritize suppressing the most serious performance degradation factors (such as thermal drift caused by high temperature or resonance caused by strong vibration).

[0128] Piezoelectric deformation equation:

[0129] ,

[0130] in, : strain generated in the piezoelectric film (dimensionless); : piezoelectric constant, : film thickness of the piezoelectric film, : Applied bias voltage.

[0131] Cavity depth adjustment:

[0132] ,

[0133] in, : effective length of the piezoelectric film, The cavity depth adjustment amount can compensate for the cavity resonance frequency offset caused by environmental vibration. To this end, in a specific implementation of the embodiment of the present invention, after solving the multi-physics field coupling optimization model to obtain the piezoelectric film acoustic sensor packaging parameters, the following step is also included:

[0134] Obtaining a resonant frequency shift detected by a vibration sensor;

[0135] According to the resonance frequency offset fed back by the vibration sensor, the bias voltage is adjusted based on the PID algorithm. , the adjusted bias voltage It is used to control the deformation of the piezoelectric film so that the absolute value of the frequency offset is less than a set frequency offset threshold. In a specific application, the set frequency offset threshold can be set to 0.

[0136] In a specific implementation of the embodiment of the present invention, the PID algorithm uses the following formula to calculate the adjusted bias voltage :

[0137] ,

[0138] Where, 、 、 They are proportional gain, integral gain and differential gain respectively, express time, is the resonant frequency shift, express moment, is the integration operator; express The resonant frequency shift at that moment.

[0139] In the above scheme, the inverse piezoelectric effect of the piezoelectric material is used to apply a bias voltage Control the deformation of the piezoelectric film and dynamically adjust the packaging structure parameters (such as cavity depth and support beam stiffness) to achieve active anti-interference.

[0140] Example 2

[0141] Based on the same inventive concept as that of Example 1, an embodiment of the present invention provides a piezoelectric thin film acoustic sensor packaging design device, comprising:

[0142] A multi-physics coupling optimization model acquisition module is used to acquire a pre-built multi-physics coupling optimization model, wherein the multi-physics coupling optimization model includes optimization sub-goals of maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude;

[0143] The packaging parameter design module is used to use a Bayesian global optimization algorithm to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor. During the solution process, the weights of different optimization sub-goals are dynamically adjusted according to environmental parameters. The optimization sub-goals include maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude.

[0144] The rest are the same as in Example 1.

[0145] Example 3

[0146] Based on the same inventive concept as in Example 1, an embodiment of the present invention provides a piezoelectric thin film acoustic sensor packaging design system, including a storage medium and a processor;

[0147] The storage medium is used to store instructions;

[0148] The processor is configured to operate according to the instructions to perform the method according to any one of the embodiments 1.

[0149] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0150] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0151] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0152] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0153] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which are all protected by the present invention.

[0154] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A piezoelectric film acoustic sensor packaging design method, characterized in that: include: Obtaining a pre-built multi-physics field coupling optimization model, wherein the objective function of the multi-physics field coupling optimization model is constructed with the goal of maximizing sound pressure sensitivity, minimizing frequency shift, and minimizing parasitic resonance amplitude; A Bayesian global optimization algorithm is used to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor. The CNN model is used as a proxy optimization model in the Bayesian global optimization algorithm to fit the objective function. During the solution process, the weights of different optimization sub-goals are dynamically adjusted according to environmental parameters. The optimization sub-goals include maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude.

2. The piezoelectric thin film acoustic sensor package design method according to claim 1, characterized in that: The mathematical expression of the objective function of the multi-physics field coupling optimization model is: ， Where, The objective function for the multiphysics coupled optimization model is is the sound pressure sensitivity, is the frequency offset, is the parasitic resonance amplitude, 、 、 are all weight coefficients; the sound pressure sensitivity, frequency shift and parasitic resonance amplitude are all calculated based on the elastic stiffness, piezoelectric constant, dielectric constant, structural parameters and constitutive equation of the piezoelectric film; The constraints of the multi-physics field coupling optimization model include: Piezoelectric film thickness ,in, is the minimum thickness of the piezoelectric film, is the maximum thickness of the piezoelectric film; Cavity depth ,in, is the working wavelength; Piezoelectric film radius , in, is the minimum radius of the piezoelectric film, is the maximum value of the piezoelectric film radius; Resonant frequency ,in, is the center frequency of the target frequency band, is the target bandwidth.

3. The piezoelectric thin film acoustic sensor package design method according to claim 2, characterized in that: The input parameters of the CNN model include the elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of the piezoelectric film, and its output parameter is the objective function The true value of , its loss function is: ， Where, is the loss function; is the total number of acquisition points, each of which includes the elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of the piezoelectric film. For the Collection points, is the output value of the CNN model, is the true value, is the regularization term, is the coefficient of the regularization term.

4. The piezoelectric thin film acoustic sensor package design method according to claim 3, characterized in that: The Bayesian global optimization algorithm is used to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric film acoustic sensor, specifically including: Based on the current proxy model, find the parameter points of the optimal acquisition function, which include 、 、 , elastic stiffness, piezoelectric constant, dielectric constant and structural parameters of piezoelectric films; Based on the parameter point, the value of the objective function of the multi-physics field coupling optimization model is calculated; The parameters 、 、 , the elastic stiffness, piezoelectric constant, dielectric constant, structural parameters and objective function values ​​of the piezoelectric film are taken as new parameter points and added into the observation data set to obtain an updated observation data set; The surrogate model is retrained and updated using the updated observation dataset until the objective function of the multiphysics coupled optimization model converges.

5. The piezoelectric thin film acoustic sensor package design method according to claim 4, characterized in that: The dynamic adjustment of the weights of different optimization sub-objectives according to the environmental parameters specifically includes: Weighting based on temperature parameters The adjustment formula used is: ， ， Where, is the adjusted weight, is the absolute difference between the current temperature and the reference temperature, is the current temperature, is the reference temperature, is the initial weight, is the temperature threshold; Weighting based on vibration amplitude parameters The adjustment formula used is: ， Where, is the adjusted weight, is the initial weight, is the vibration amplitude detected by the vibration sensor, is the vibration amplitude threshold.

6. The piezoelectric thin film acoustic sensor package design method according to claim 5, characterized in that: The dynamically adjusting the weights of different optimization sub-objectives according to the environmental parameters also includes: Weighting based on temperature parameters and vibration amplitude parameters The adjustment formula used is: 。 7. The method for designing a piezoelectric thin film acoustic sensor package according to claim 1, wherein: After the step of solving the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor, the method further includes: obtaining a resonant frequency shift detected by a vibration sensor; According to the resonance frequency offset fed back by the vibration sensor, the bias voltage is adjusted based on the PID algorithm. , the adjusted bias voltage It is used to control the deformation of the piezoelectric film so that the absolute value of the frequency offset is less than the set frequency offset threshold.

8. The method for designing a piezoelectric thin film acoustic sensor package according to claim 6, wherein: The PID algorithm uses the following formula to calculate the adjusted bias voltage : ， Where, 、 、 They are proportional gain, integral gain and differential gain respectively, express time, is the resonant frequency shift; express moment, is the integration operator; express The resonant frequency shift at that moment.

9. A piezoelectric film acoustic sensor packaging design device, characterized in that: include: A multi-physics coupling optimization model acquisition module is used to acquire a pre-built multi-physics coupling optimization model, wherein the objective function of the multi-physics coupling optimization model is constructed with the goal of maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude; The packaging parameter design module is used to use a Bayesian global optimization algorithm to solve the multi-physics field coupling optimization model to obtain the packaging parameters of the piezoelectric thin film acoustic sensor. The CNN model is used as a proxy optimization model in the Bayesian global optimization algorithm to fit the objective function. During the solution process, the weights of different optimization sub-goals are dynamically adjusted according to environmental parameters. The optimization sub-goals include maximizing sound pressure sensitivity, minimizing frequency offset, and minimizing parasitic resonance amplitude.

10. A piezoelectric film acoustic sensor packaging design system, characterized in that: including storage media and processors; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the method according to any one of claims 1-8.

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