A method for modeling and dynamic distributed parameter identification of electromagnetic transducers considering electro-magnetic-mechanical-acoustic coupling

Abstract

The application discloses a kind of electromagnetic transducer modeling and dynamic distributed parameter confirmation method considering electro-magnetic-mechanical-acoustic coupling, comprising: constructing electromagnetic transducer system dynamic multi-physical field distributed parameter model DPM;Based on parallel genetic algorithm PGA model optimization method;The dynamic multi-physical field distributed parameter model DPM includes: constructing excitation circuit equivalent model, the excitation circuit equivalent model includes several excitation main loop units, several air gap leakage magnetic loop units and several permanent magnet loop units;Construct mechanical structure equivalent model, the mechanical structure equivalent model includes system radiation plate face, spring system and rubber plate face and so on physical model.The PGA algorithm is optimized to DPM model parameter in the application, improves the performance efficiency of electromagnetic transducer, and provides a new method for the design of electromagnetic transducer.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of high-performance design of electromagnetic transducers, particularly to a modeling method for designing dynamic magnetic circuit optimization. TECHNICAL BACKGROUND

[0002] With the increasing number of underwater operations, electromagnetic transducers are increasingly widely used in the fields of ocean exploration, submarine detection, ocean environment monitoring, underwater communication, etc. As an important part of underwater systems, underwater acoustic sensors undertake the key task of transmitting and receiving underwater acoustic signals. Their performance is directly related to the reliability, accuracy and real-time performance of the system. Therefore, how to effectively improve the performance, accuracy and stability of underwater acoustic sensors has become a problem to be solved in the field of ocean engineering.

[0003] Traditional electromagnetic transducer optimization design methods usually rely on experience or parameter adjustment based on a single optimization algorithm. However, these methods have limitations such as slow convergence speed, easy to fall into local optimal solution, high computational complexity, etc. Moreover, electromagnetic transducers have the characteristics of multi-physical field coupling of electric-magnetic-mechanical-acoustic, and their performance is not only related to the driving circuit, but also affected by various structural parameters. Therefore, building a multi-physical field dynamic coupling model is the key to equipment optimization design, and existing models cannot describe the multi-physical field multi-parameter dynamic characteristics. Therefore, the present application builds a dynamic multi-physical field distributed parameter model DPM of the underwater acoustic sensor system considering the magnetic leakage of the excitation circuit, and uses parallel genetic algorithm PGA as a general optimization model method for electromagnetic transducers on the DPM model. SUMMARY

[0004] To solve the above modeling defects, the present application discloses a modeling and dynamic distributed parameter confirmation method for electromagnetic transducers considering electric-magnetic-mechanical-acoustic coupling.

[0005] To achieve the above purpose, the technical scheme of the present application is as follows:

[0006] A modeling and dynamic distributed parameter confirmation method for electromagnetic transducers considering electric-magnetic-mechanical-acoustic coupling, comprising the following steps:

[0007] Step one, build a dynamic multi-physical field distributed parameter model DPM of the electromagnetic transducer system, which includes an excitation circuit equivalent model, a mechanical structure equivalent model and a sound source equivalent model;

[0008] Step two, use parallel genetic algorithm PGA to optimize the dynamic multi-physical field distributed parameter model DPM of the electromagnetic transducer system to obtain the dynamic distributed parameters of the dynamic multi-physical field distributed parameter model DPM of the electromagnetic transducer system.

[0009] Further improvement, the step one includes the following steps:

[0010] S101, construct the equivalent model of excitation loop;

[0011] S102, construct the equivalent model of mechanical structure;

[0012] S103, construct the equivalent model of sound source.

[0013] Further improvement, in step S101, the equivalent model of excitation loop is as follows:

[0014] The magnetic circuit parameters of excitation loop are calculated according to the following formula:

[0015]

[0016] Wherein, Rmi, Rairj and Rtk are the equivalent magnetic resistance of the i-th linear excitation stack unit, the j-th linear air gap unit and the k-th permanent magnet unit respectively; h is the effective path of magnetic flux of excitation stack unit; Dk is the magnetization direction thickness of permanent magnet unit; μ ri , μ tk And μ0 are the magnetic permeability of excitation stack block material, the magnetic permeability of permanent magnet and the magnetic permeability of vacuum respectively; si, sj and sk are the effective area of magnetic flux of excitation stack unit, air gap unit and permanent magnet unit respectively; dm and Δx(t) are the initial magnetic flux effective path of air gap and the dynamic air gap change during system operation respectively; t represents time, G tk Indicates the magnetic conductance of the k-th permanent magnet unit, Rmia indicates the instantaneous side excitation magnetic resistance of permanent magnet unit, and Rmib indicates the reverse side excitation magnetic resistance of permanent magnet unit;

[0017] Finally, according to the same direction of excitation loop unit and the magnetic flow or the reverse magnetic flow, the loop equivalent circuit module is established, and the main magnetic flux equation and the total magnetic flux equation are obtained by using the Thevenin equivalent principle and the superposition principle:

[0018]

[0019] Wherein, And Indicate the main magnetic flux and the total magnetic flux in the excitation equivalent circuit respectively, E i Indicates the magnetic flow source generated by the i-th independent loop, R mi And R mei Indicate the main magnetic and total magnetic flux loop resistance in the i-th excitation equivalent circuit respectively;

[0020] Through the above equivalent circuit model, the total magnetic flux of excitation main loop is calculated, and the electric-magnetic coupling module is constructed, which is as follows:

[0021]

[0022] Wherein, u(t), i(t), R cu And N respectively represent the time-varying voltage of the excitation source, the time-varying current of the whole excitation loop, the coil resistance and the number of turns of the coil;

[0023] The driving model part is as follows:

[0024]

[0025] Wherein, F em (i(t), x(t)) is the driving magnetic force, W em is the driving magnetic field energy in the air gap, E em is the main magnetic dynamic formula in the air gap, is the main magnetic resistance in the air gap; x represents the time-varying space air gap, i(t) represents the applied excitation current, B represents the excitation main magnetic flux magnetic field, H represents the excitation main magnetic flux magnetic field intensity, S represents the effective cross-sectional area in the direction of the perpendicular magnetic field;

[0026] Based on this, the electro-magnetic module is completed.

[0027] Further improvement, in step S102, the mechanical structure equivalent model is as follows:

[0028] Calculate the time-varying mechanical vibration velocity dx(t) / dt:

[0029]

[0030] Wherein, R S is the equivalent damping coefficient of the electromagnetic transducer system, M S is the equivalent total mass of the electromagnetic transducer system, K S is the equivalent total stiffness of the electromagnetic transducer system; x(t) represents the time-varying air gap.

[0031] Further improvement, in step S103, the sound source equivalent model is as follows:

[0032] Calculate the instantaneous far sound point position sound pressure P(x(t)):

[0033]

[0034] Wherein, ρ0 is the medium density, m S is the effective mass of the sound radiation part, S r is the effective area of the radiation part, r is the linear distance from the instantaneous far sound point to the sound source; f is the vibration frequency, w is the angular velocity, and k is the vibration wave number;

[0035] According to the sound pressure, the sound pressure level of the far sound point and the sound power are obtained, as follows:

[0036]

[0037] where TCR is the effective sound pressure level at the remote point, P ext (10,0,0) is the sound pressure at the listening point at 10 meters, conj(P ext (10,0,0)) is the conjugate coefficient of P ext (10,0,0) at 10 meters, P0 is the reference sound pressure of the medium.

[0038] The power η is then given by equation (12) as follows:

[0039]

[0040] where P em is the effective power input to the excitation source.

[0041] Further improvement, in the step two, the parallel genetic algorithm PGA is used to optimize the dynamic multi-physical field distribution parameter model DPM of the electromagnetic transducer system, and the dynamic distribution parameter when the dynamic multi-physical field distribution parameter model DPM of the electromagnetic transducer system has the highest efficiency is taken as the final dynamic distribution parameter.

[0042] Further improvement, the parallel genetic algorithm PGA specifically optimizes the following steps:

[0043] Initialize the characteristic parameters of the population, define the parameters of the dynamic multi-physical field distribution parameter model DPM of the electromagnetic transducer system; randomly initialize the population number Xi; the parameters of the dynamic multi-physical field distribution parameter model DPM of the electromagnetic transducer system include the thickness of the permanent magnet unit and the number of turns of the coil;

[0044] Initial population set, in the constructed dynamic multi-physical field distribution parameter model DPM of the electromagnetic transducer system, the initial size of each component is brought into the excitation circuit equivalent model, the mechanical structure equivalent model and the sound source equivalent model, and the fitness F(X i ) is obtained by subtracting the initial position air gap position from the embedded iron position vector x(t) as the expected value, then the population set is evaluated for fitness, the qualified excellent individuals are selected, a new population set is reconstituted and taken as the parent generation;

[0045] To ensure that the generated offspring population is diverse enough, different population set individuals are crossed to generate more combined parameter sets;

[0046] Meanwhile, to increase the diversity of the population and introduce a dynamic mutation probability during the operation, the diversity is increased and the convergence is accelerated, and the probability formula is:

[0047]

[0048] where P max is initial mutation probability, λ is adjustment coefficient, t is current generation number; P mutation (t) is dynamic mutation probability, which changes with the superposition of offspring;

[0049] The individuals of the last generation are sorted through fitness evaluation, and the individuals with the best fitness are selected to enter the next generation, and when an optimal solution is found or the maximum generation number G max , the population Xi with the best fitness is automatically selected by the system, and at this time, the optimal transducer structure design parameters are obtained.

[0050] Further improvement, the fitness calculation method is as follows:

[0051]

[0052] When F(X i ) ensures the validity of the solution to meet the condition, the fitness is obtained by subtracting the expected value from the embedded iron position vector x(t) with the initial position air gap position as the expected value; otherwise, the fitness is 0, wherein Voltage_pluse i represents the excitation voltage, D1 i , D2 i , D3 i , D4 i respectively represent the thickness of the four area permanent magnet units, N i represents the number of turns of the coil of the current generation individual, P(Voltage_pluse i , D1 i , D2 i , D3 i , D4 i , N i ) represents the set sound pressure of the current generation individual.

[0053] Further improvement, the crossbreeding cross formula is as follows:

[0054]

[0055] Wherein, X childi represents the offspring population, respectively represent the selection of corresponding characteristic parameters from the parent population meeting the fitness, and then combined into a new excellent population.

[0056] The advantages of the present application are as follows:

[0057] The present application establishes an electromagnetic transducer system dynamic multi-physical field distribution parameter model DPM considering electro-magnetic-mechanical-acoustic coupling, and realizes fast solving of the dynamic distribution parameters through parallel genetic algorithm PGA, which is beneficial to the fast design and optimization of the electromagnetic transducer. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 For the modeling and dynamic distributed parameter identification method of the electromagnetic transducer considering the electro-magnetic-mechanical-acoustic coupling in the present application;

[0059] Figure 2 For the modeling and dynamic distributed parameter identification method of the electromagnetic transducer considering the electro-magnetic-mechanical-acoustic coupling in the present application;

[0060] Figure 3 For the equivalent diagram of the rubber ring microelement in example 1, wherein figure (a) is a topological view of the hollow rubber ring, figure (b) is an equivalent rectangular rubber strip composed of two-by-two mutual intersection and sorting after cutting the rubber ring into microelements, and figure (c) is a stretched state of the equivalent rubber strip;

[0061] Figure 4 For the waveform diagram and sound pressure level calculation diagram of the transient sound pressure at the far sound point in the present application. DETAILED DESCRIPTION

[0062] In order to facilitate the understanding of the present application, the device of the present application will be described more fully below with reference to the related drawings. Embodiments of the device are shown in the drawings. However, the device can be realized in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0063] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "principle", "method", "theorem" should be understood broadly, for example, it can be an equivalent principle, or a superposition method, or a Hooke's theorem, etc. For ordinary skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0064] EMBODIMENT

[0065] The present embodiment provides a dynamic multi-physical field distributed parameter model DPM modeling method for an electromagnetic transducer system, taking a double-sided belt permanent magnet piston transducer as an example but not including or limited to the structure of the present example, and the main steps include:

[0066] S101, an excitation loop equivalent model is constructed, and the specific process is as follows:

[0067] Based on the equivalent circuit idea, each component of the excitation total loop part is regarded as a separate excitation unit, and a plurality of unit main magnetic loop unit equivalent modules are established, and the leakage magnetic loop of each unit is analyzed, including:

[0068] A plurality of excitation main loop units:

[0069]

[0070] Several air gap loop units:

[0071]

[0072] Several permanent magnet loop units:

[0073]

[0074] Where Rmi, Rairj and Rtk are the equivalent magnetic resistance of the i-th linear excitation stack unit, the j-th linear air gap unit and the k-th permanent magnet unit respectively; h is the effective path of the magnetic current of the excitation stack unit; Dk is the thickness of the magnetization direction of the permanent magnet unit; μ ri , μ tk and μ0 are the magnetic permeability of the excitation stack block material, the magnetic permeability of the permanent magnet and the magnetic permeability of vacuum respectively; si, sj and sk are the effective area of the magnetic current of the excitation stack unit, the air gap unit and the permanent magnet unit respectively; dm and Δx(t) are the initial effective path of the magnetic current of the air gap and the dynamic air gap change during system operation respectively, G tk represents the magnetic permeability of the permanent magnet (PM), Rmia represents the PM transient side excitation magnetic resistance, and Rmib represents the PM reverse time side excitation magnetic resistance.

[0075] Finally, according to the arrangement of the excitation loop unit in the same direction of the magnetic current or the reverse magnetic current, the loop equivalent circuit module is established, and the main magnetic flux and total magnetic flux equations are obtained by using the Thevenin equivalent principle and the superposition principle, and the magnetic flux form is as follows:

[0076]

[0077] Where, and represent the main magnetic flux and total magnetic flux in the excitation equivalent loop respectively, E i represents the magnetic current source generated by the i-th independent loop;

[0078] Through the above equivalent circuit model, the total magnetic flux of the excitation main loop can be calculated, and the electric-magnetic coupling module is constructed, and the form is as follows:

[0079]

[0080] Where u(t), i(t), R cu and N represent the time-varying voltage of the excitation source, the time-varying current of the whole excitation loop return flow, the coil resistance and the number of turns of the coil.

[0081] The driving model part is as follows:

[0082]

[0083] wherein F em (i(t),x(t)) is the driving magnetic force, W em is the driving magnetic field energy in the air gap, E em is the driving magnetic energy in the air gap, x represents the time-varying air gap, i(t) represents the applied excitation current, B represents the excitation main magnetic flux magnetic field, H represents the excitation main magnetic flux magnetic field strength, and S represents the effective cross-sectional area in the perpendicular magnetic field direction.

[0084] Based on this, the electro-magnetic module is built;

[0085] S102, a mechanical equivalent model is built, and the specific process is as follows:

[0086] According to the mechanical balance equation, Newton's second law and the mass conservation principle, the system balance equation is obtained:

[0087]

[0088] wherein R S is the equivalent damping coefficient of the system, M S is the equivalent total mass of the system, and K S is the equivalent total stiffness of the system.

[0089] In the above formula, R S is the equivalent damping coefficient of the system, including R σ1 and R σ2 , that is:

[0090] R S = R σ1 + R σ2 ;

[0091] R σ1 is the mechanical damping coefficient of the transducer system itself, and R σ2 is the mechanical damping coefficient added by the external environment of the transducer;

[0092] In the above formula, M S is the equivalent total mass of the system, including m0 and m r , that is:

[0093] M S = m0+m r ;

[0094] m0 is the total mass of the radiation domain of the transducer itself, and m r is the mass added by the external environment of the transducer;

[0095] In the above formula, k S is the equivalent total stiffness of the system, including the stiffness k σ1 provided by the spring and the tension stiffness kσ2 ;

[0096] According to R σ2 and m r To express the coefficient relationship between acceleration and velocity, let velocity x(t) / dt and acceleration x 2 (t) / dt 2 If velocity is considered a resistive element, then acceleration is considered a capacitive element; therefore, its additional radiation resistance equation can be obtained as follows:

[0097]

[0098] Where k is the effective wavenumber, a is the effective radius of the radiation domain, and C0 is the sound velocity of the sound propagation medium.

[0099] The reciprocating motion of the rubber sheet is equivalent to the axial stretching of the rubber strip along its center, thus simplifying the complex disk-driven motion into a simple rubber stretching motion. For example... Figure 3 As shown, during the stretching process of rubber, the equivalent change in the Young's modulus of the sheet is due to the existence of its own Poisson's ratio E. The volume change of the rubber body before and after vertical stretching is as follows. Figure 3 As shown in (c), under the action of vertical tensile force, the rubber body undergoes deformation in both longitudinal and transverse directions, that is, transverse deformation t in the horizontal direction. xv and vertical tensile deformation t hv .

[0100] According to the generalized Hooke's law, let the average tensile stress of the rubber body be σ. t Its strain constitutive equation can be expressed as:

[0101] σ t =σ1+σ2=E t ε

[0102] In the formula, σ1 is the stress of the rubber body without considering the influence of the internal and external constraint plates, and σ2 is the stress corresponding to the transverse deformation component of the rubber body after considering the influence of internal and external constraints.

[0103] Let E be the tensile modulus of elasticity of an unconstrained rubber body under simple tension. 0t The expression for σ1 is:

[0104]

[0105] In the formula Let E be the initial elastic modulus of the rubber body, and E be its engineering strain.

[0106] Considering the partial stress σ2 caused by the constraint of the inner and outer rubber bodies, under tensile force p t When the rubber body undergoes a tiny unit deformation under the action of force, based on the principle that the volume of the rubber body remains constant in the initial stage of stretching, the equilibrium equation is obtained:

[0107] hx·L0= 2x a (t hv +h)·L0+2t xv (h+t hv )·L0

[0108] The vertical tensile deformation t hv and the horizontal transverse deformation t xv at the eccentric position can be obtained from the formula

[0109]

[0110] The relationship between the tensile force increment dp t and the distance increment dx a from the center is:

[0111]

[0112] Substituting the formula into the formula, the tensile force p a at the position x t is obtained:

[0113]

[0114] Area-integrating the formula (6) gives the tensile stress:

[0115]

[0116] The longitudinal elastic modulus E t of the rubber in pure tensile state is obtained from the above formula;

[0117]

[0118] In the formula, ξ(t hv ) is the longitudinal elongation coefficient, and k is the rubber transverse coefficient.

[0119] The above calculation is equivalent to calculating the tensile state according to the longitudinal compression parameters of the rubber body. The tensile longitudinal elastic modulus of the rubber body is 0.2 times the compression longitudinal elastic modulus, i.e. the calculation formula of the longitudinal elastic modulus E t of the rubber in pure tensile state is:

[0120] E t = 0.2E 0t (1+kS 2 )

[0121] In the formula, S is the transverse compression area of the rubber body, and k is the hardness correction coefficient of the rubber body.

[0122] Therefore, the theoretical calculation formula of the vertical stiffness of the rubber body in the pure tensile state of the inner and outer clamping iron is:

[0123]

[0124] Based on this, all parameters of the mechanical part are defined, and the magnetic-mechanical coupling module is realized.

[0125] S103, construct the equivalent model of the sound source, and the specific process is:

[0126] Calculate the far sound point sound pressure P(x(t)):

[0127]

[0128] Wherein, p0 is the medium density, m S The effective mass of the sound radiation part, S r is the effective area of the radiation part, r is the linear distance of the point from the sound source, f is the vibration frequency, w is the angular velocity, and k is the vibration wave number. According to the sound pressure, the sound pressure level and the sound power of the point can be obtained, as follows:

[0129]

[0130] Wherein, TCR is the sound pressure level at the point, P ext (10,0,0) is the pressure at the listening point at 10 meters, conj(P ext (10,0,0)) is the conjugate coefficient of P ext (10,0,0), and P0 is the reference sound pressure of the medium.

[0131] Then the power η is, as follows:

[0132]

[0133] Wherein, P em is the effective power of the excitation input.

[0134] Here, the machine-sound coupling model has been completed;

[0135] Based on the above magnetic circuit model, mechanical model and acoustic model, the dynamic multi-physical field distribution parameter model DPM of the electromagnetic transducer system is constructed;

[0136] The embodiment also provides a parallel genetic algorithm PGA model optimization method, which takes a double-sided band permanent magnet piston transducer as an example but does not include or limit to the structure of the example, and the main steps include:

[0137] Initialize the population:

[0138] X i =[Voltage_pluse i ,D1 i ,D2 i ,D3 i ,D4i ,N i ]

[0139] each variable Voltage_pluse i ,D1 i ,D2 i ,D3 i ,D4 i and N i Randomly initialize a certain amount of population size in its designated range, such as: PM thickness, coil turns, etc. are defined;

[0140] Fitness evaluation:

[0141] For each individual X i , the fitness value is calculated by bringing the variables contained in the sound pressure model:

[0142]

[0143] When F(X i ) ensures the validity of the solution to meet the conditions, the initial position air gap position is taken as the expected value, and the fitness is obtained by subtracting the embedded iron position vector x(t); otherwise, the fitness is 0, where Voltage_pluse i represents the excitation voltage, D1 i ,D2 i ,D3 i ,D4 i represent the thickness of the four area permanent magnet units, respectively, N i represents the number of turns of the coil of the current generation individual, P(Voltage_pluse i ,D1 i ,D2 i ,D3 i ,D4 i ,N i ); represents the set of sound pressure of the current generation individual.

[0144] Selection operation:

[0145] According to the fitness value F(Xi) from the current population, select the excellent individual for reproduction, the common selection method is roulette selection, and the selection probability formula is:

[0146]

[0147] Population crossover:

[0148] In order to ensure the diversity of the generated offspring population is rich enough, the parent individual gene is combined to generate offspring individuals; then select m offspring, and randomly select each part of the gene from k parent individuals. The crossover formula is as follows:

[0149]

[0150] Mutation operation:

[0151] By changing some genes X ij = random(min j , max j ) randomly, the diversity of the population can be increased, and dynamic mutation probability can be introduced during the running process to increase the diversity and accelerate the convergence, and the probability formula is as follows:

[0152]

[0153] In the formula, P max is the initial mutation probability, λ is the adjustment coefficient, and t is the current generation number;

[0154] Fitness ranking and selection:

[0155] The individuals of each generation are ranked by fitness evaluation, and the individuals with the best fitness are selected to enter the next generation X slected =X sorted [1:k]; finally, when a good enough solution is found or the maximum generation number G max is reached, the population Xi with the best fitness is automatically selected.

[0156] Based on this, the dynamic multi-physical field distribution parameter model DPM of the electromagnetic transducer system and the PGA model optimization method based on parallel genetic algorithm have been constructed, according to the initial values of the parameters of each part of the given model, the fitness is set, when a good enough solution is found or the maximum generation number G max is reached, the excellent parameter set is outputted and the sound source amount is outputted, as shown in Figure 4

[0157] The present application is not limited to the above-mentioned implementation method, and anyone should know that the technical solutions made under the inspiration of the present application and having the same or similar technical solutions as the present application fall within the protection scope of the present application.

Claims

1. A method for modeling and confirming the dynamic distributed parameters of an electromagnetic transducer considering electro-magnetic-mechanical-acoustic coupling, characterized in that, Includes the following steps: Step 1: Construct the Dynamic Multiphysics Distributed Parameter Model (DPM) of the electromagnetic transducer system. The DPM includes an equivalent model of the excitation circuit, an equivalent model of the mechanical structure, and an equivalent model of the sound source. S101. Construct an equivalent model of the excitation circuit; the equivalent model of the excitation circuit includes several main excitation circuit units, several air gap circuit units, and several permanent magnet circuit units. S102. Construct an equivalent model of the mechanical structure; the equivalent model of the mechanical structure includes physical models of the system's radial surface, spring system, and rubber plate surface. The physical model includes the application of mechanical equilibrium equations, Newton's second law, and the principle of conservation of mass. The parameters of the mechanical equilibrium equations include mechanical damping and system nonlinear stiffness. S103. Construct an equivalent model of the sound source; Step 2: Optimize the Dynamic Multiphysics Distribution Parameter Model (DPM) of the electromagnetic transducer system using the parallel genetic algorithm PGA. The final dynamic distribution parameters are those obtained when the DPM achieves the highest efficiency. The specific optimization steps of the parallel genetic algorithm PGA are as follows: Initialize population characteristic parameters and define the parameters of the dynamic multiphysics distribution parameter model (DPM) of the electromagnetic transducer system; randomly initialize the population size X. i The parameters of the dynamic multiphysics distribution parameter model (DPM) of the electromagnetic transducer system include the thickness of the permanent magnet unit and the number of coil turns. In the initial cluster, within the constructed dynamic multiphysics distribution parameter model (DPM) of the electromagnetic transducer system, the preset initial dimensions of each component are incorporated into the equivalent models of the excitation circuit, mechanical structure, and sound source. The initial air gap position is used as the desired value and the embedded iron position vector. The fitness is obtained by subtraction. Then, the fitness of the population is evaluated, and outstanding individuals that meet the conditions are selected to form a new population and serve as the parents. To ensure that the generated offspring populations are sufficiently diverse, individuals from different population groups are cross-propagated to generate more combinatorial parameter sets. To increase population diversity, dynamic mutation probability is introduced during operation to accelerate convergence while increasing diversity. The probability formula is as follows: (13) in, P max λ is the initial mutation probability, and λ is the adjustment coefficient. t It is the current algebra; The dynamic mutation probability changes with the accumulation of offspring; Finally, individuals in each generation are ranked by fitness evaluation, and the individuals with the best fitness are selected to enter the next generation. This process continues until an optimal solution is found or the maximum number of generations G is reached. max The system automatically selects the population X with the best fitness. i， At this point, the optimal transducer structure design parameters are obtained; The fitness calculation method is as follows: (14) When F( X i To ensure the validity of the solution meets the conditions, the initial position (air gap position) is used as the expected value and the embedded position vector. The fitness is obtained by subtraction; Otherwise, the fitness is 0, where Indicates the excitation voltage. These represent the thicknesses of the permanent magnet units in the four regions. This indicates the number of coil turns in a contemporary individual within a population. This refers to the collective sound pressure of contemporary individuals within an ethnic group.

2. The method for modeling and confirming the dynamic distributed parameters of an electromagnetic transducer considering electro-magnetic-mechanical-acoustic coupling as described in claim 1, characterized in that, In step S101, the equivalent model of the excitation circuit is as follows: The magnetic circuit parameters of the excitation circuit are calculated using the following formula: (1) (2) (3) in, , and The first i The equivalent magnetic reluctance of the first linear excitation stack unit, the first j The equivalent magnetic reluctance of the first linear air gap unit and the first k Equivalent magnetic reluctance of a permanent magnet unit; h This represents the effective path of the magnetoflow in the excitation stack unit; Dk Thickness in the magnetization direction of the permanent magnet unit; , and These are the magnetic permeability of the excitation stack material, the magnetic permeability of the permanent magnet, and the vacuum magnetic permeability, respectively. si , sj and sk These represent the effective magnetic flux areas of the excitation stack unit, the air gap unit, and the permanent magnet unit, respectively; dm and These represent the effective path of the initial magnetic flux in the air gap and the dynamic change in the air gap during system operation, respectively; t represents time. Indicates the first k The magnetic permeability of a permanent magnet unit This represents the instantaneous side excitation reluctance of the permanent magnet unit. This represents the reverse-time excitation reluctance of the permanent magnet unit; Finally, by arranging the excitation circuit units in the same direction as the paramagnetic current or the antimagnetic current, a loop equivalent circuit module is established. The Thevenin equivalence principle and the superposition principle are used to obtain the main magnetic flux equation and the total magnetic flux equation: (4) (5) in, and These represent the main magnetic flux and the total magnetic flux in the equivalent excitation circuit, respectively. Indicates the first i The magnetic current source generated by an independent loop and They represent the first i The magnetic reluctance of the main magnetic and total magnetic flux loops in the equivalent excitation circuit; Based on the above equivalent circuit model, the total magnetic flux of the main excitation circuit is calculated, and the electro-magnetic coupling module is constructed in the following form: (6) in, , , N and N represent the time-varying voltage of the excitation source, the time-varying current flowing back through the entire excitation circuit, the coil resistance, and the number of coil turns, respectively. The driving model part has the following equations: (7) in, To drive the magnetic force, The energy driving the magnetic field in the air gap. It is an air-gap main magnetic drive type. The main reluctance of the air gap; x This indicates the spatial air gap that changes over time. Indicates the applied excitation current. B Indicates the main excitation magnetic flux field. H Indicates the magnetic field strength of the excitation main magnetic flux. Indicates the effective cross-sectional area perpendicular to the magnetic field direction; Based on this, the electro-magnetic module has been constructed.

3. The method for modeling and confirming the dynamic distributed parameters of an electromagnetic transducer considering electro-magnetic-mechanical-acoustic coupling as described in claim 2, characterized in that, In step S102, the equivalent model of the mechanical structure is as follows: Calculate the velocity of time-varying mechanical vibration : (8) in, denoted as the equivalent damping coefficient of the electromagnetic transducer system. The equivalent total mass of the electromagnetic transducer system. The equivalent overall stiffness of an electromagnetic transducer system; Indicates time t The changing air gap.

4. The method for modeling and confirming the dynamic distributed parameters of an electromagnetic transducer considering electro-magnetic-mechanical-acoustic coupling as described in claim 2, characterized in that, In step S103, the equivalent model of the sound source is as follows: Calculate the instantaneous sound pressure at distant sound points : (9) in, For the density of the medium, Effective mass of the sound radiation portion. The effective area of ​​the radiating part. The instantaneous linear distance between the distant sound point and the sound source; f The vibration frequency, w Its angular velocity, k The vibration wave number; The sound pressure level and sound power at distant locations are derived from the sound pressure level using the following formula: (10) (11) in, The effective sound pressure level at the far-field location. Listen for the pressure at a distance of 10 meters. for Conjugate coefficient, The reference sound pressure level for the medium; Then power As shown in equation (12): （12） in, This represents the effective power input to the excitation source.

5. The method for modeling and confirming the dynamic distributed parameters of an electromagnetic transducer considering electro-magnetic-mechanical-acoustic coupling as described in claim 1, characterized in that, The crossover formula for crossbreeding is as follows: ；(15) in, Indicates the offspring population. These represent selecting corresponding characteristic parameters from parent populations that meet fitness criteria, and then combining them to form new superior populations.

Images