Equivalent circuit model of balanced armature loudspeaker and parameter identification method and system

Abstract

The invention discloses an equivalent circuit model of a balanced armature type loudspeaker and a parameter identification method and system, the model is faster, more convenient and more efficient than finite element modeling, and compared with a traditional equivalent circuit model, the model can accurately predict displacement and sound radiation of the balanced armature type loudspeaker; on the basis of the equivalent circuit model, in order to facilitate identification and simplify the model, an accurate identification algorithm is given on the basis of simplifying the model, and the algorithm does not need complex material parameters and can accurately identify relevant parameters of the balanced armature type loudspeaker only through time domain signals. The identified parameters can be directly used for analyzing the performance of the balanced armature type loudspeaker, and the difficulty of analyzing the performance of the loudspeaker is greatly reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of loudspeakers, and in particular relates to an equivalent circuit model and a parameter identification method and system for a balanced armature loudspeaker. Background Art

[0002] Balanced armature loudspeakers, also known as moving iron loudspeakers, are often used in portable devices such as hearing aids. Currently, there are numerous performance analysis methods for this type of loudspeaker, primarily categorized as equivalent circuit analysis, finite element modeling, and a combined finite element-equivalent circuit modeling approach. The equivalent circuit method can analytically and in detail explain the impact of various parameters on the speaker's ultimate performance. However, its modeling of the mechanical and acoustic-mechanical variables is inaccurate. For example, the simplified modeling of the coupled structure between the balanced armature and the suspension, as well as the lack of consideration for the non-piston vibration radiation of the diaphragm, prevent the equivalent circuit method from being effectively used. The finite element modeling method suffers from complex models and requires a long time to calculate. The finite element-equivalent circuit modeling approach combines the advantages of the equivalent circuit, significantly reducing computational time. However, the equivalent circuit analysis method can only be used for a portion of the structure. The coupling between the balanced armature and the suspension, as well as the non-piston vibration radiation of the diaphragm, require computational analysis using the finite element method, which cannot completely address the complexity and time-consuming nature of finite element modeling.

[0003] Currently, system identification methods based on equivalent circuit models have been widely used in the electroacoustic industry to measure speaker parameters. For example, applying the LMS algorithm to identify speaker units can achieve accurate identification. The LMS algorithm has become mature in the more common dynamic coil speakers and is still in use today. However, due to the lack of an accurate model for balanced armature speakers, there is currently no parameter identification algorithm for balanced armature speakers. If the performance of the speaker is to be analyzed, all the mechanical and structural parameters of the speaker-related materials must be obtained and substituted into the multiple complex formulas corresponding to each parameter before the speaker can be analyzed using the equivalent circuit model. It is very difficult to obtain materials for a single speaker, and it is even more impossible to provide all the materials and parameters during the supply process of each different model of balanced armature speaker. This seriously restricts the performance analysis of balanced armature speakers. Summary of the Invention

[0004] In order to address the deficiencies in the prior art, the present invention provides an equivalent circuit model and a parameter identification method and system for a balanced armature loudspeaker. The proposed model can accurately analyze the performance of the loudspeaker, and the identification method can obtain the relevant parameters of the loudspeaker model only through the time domain signal, thereby greatly reducing the difficulty of parameter acquisition and facilitating the performance analysis of the balanced armature loudspeaker.

[0005] The present invention adopts the following technical solutions.

[0006] A first aspect of the present invention provides an equivalent circuit model of a balanced armature loudspeaker, comprising models of the loudspeaker's electrical end and electrical transformer, mechanical end, mechanoacoustic transformer, and acoustic end;

[0007] The mechanical end adopts a model in which the armature and suspension are coupled in parallel;

[0008] The model coefficients of the force-acoustic variable are:

[0009]

[0010] Among them, δ is the effective radiation coefficient of the balanced armature speaker, l d is the speaker diaphragm length, x pin is the coordinate of the fulcrum connecting the armature and the diaphragm, x0 is the coordinate of the edge of the diaphragm away from the fulcrum, S d is the diaphragm area of ​​the speaker.

[0011] Preferably, the electrical end adopts an AC source V s , resistor R E and inductor L E Series model;

[0012] The power transformer model includes the coefficient T and the force C Φ ;

[0013] The acoustic side uses a model established based on its structure.

[0014] Preferably, the armature adopts R cm ,M cm and C cm A series model where R cm ,M cm and C cm Represent the force resistance, mass and force compliance of the armature respectively;

[0015] The suspension adopts M m ,C m and R m Series model, where M m ,C m and R m They represent the mass, force compliance and force resistance of the suspension respectively.

[0016] A second aspect of the present invention provides a method for identifying parameters of a balanced armature loudspeaker, comprising:

[0017] Step 1: Establish an equivalent circuit model of the balanced armature loudspeaker, and convert the acoustic mechanism of the acoustic end to the mechanical end to obtain a simplified equivalent circuit model of the balanced armature loudspeaker and establish its loop equation;

[0018] Step 2: discretizing the loop equation of the simplified equivalent circuit model to obtain a discretized equation;

[0019] Step 3: Based on the discretized equation and the current parameters of the balanced armature speaker, obtain the predicted signal of the balanced armature speaker, calculate the error between the predicted signal and the measured signal of the balanced armature speaker, and update the parameters according to the error until the termination condition is reached, and use the current parameters as the identified parameters.

[0020] Preferably, in step 1, the equivalent circuit model is simplified as follows:

[0021] The acoustic mechanism of the acoustic end adopts the acoustic compliance C AB The acoustic back cavity is represented by the finite element model, and is merged into the mechanical end. The first combined force is obtained by combining the model coefficients of the force-acoustic variable. mAB :

[0022] C mAB The force C of the mechanical end suspension m Merge to get the second combined force

[0023] Preferably, in step 1, the loop equation established according to the simplified equivalent circuit model is:

[0024]

[0025]

[0026]

[0027] Substituting formula (9) in the loop equation into formula (8) yields:

[0028]

[0029] Among them, R E and L E The resistance and inductance of the electrical end model;

[0030] u is voltage, i is current; t represents the time signal;

[0031] x is the total displacement of the loop, v is the total velocity of the loop;

[0032] x2 is the displacement of the balanced armature speaker, v2 is the velocity of the balanced armature speaker;

[0033] K Φ C Φ The reciprocal of K cm It is C cm The reciprocal of K mt It is C mtThe reciprocal of

[0034] T is the coefficient of the power transformer model; C Φ is the force compliance of the power transformer model;

[0035] R cm ,M cm and C cm is the force resistance, mass and force compliance of the armature part in the mechanical end model;

[0036] M m and R m is the mass and resistance of the suspension in the mechanical end model.

[0037] Preferably, the discretization process of the loop equation is as follows:

[0038] In the linear range, formula (7) is discretized to obtain formula (11), formula (8) is discretized to obtain formula (12), and formula (9) and formula (10) are discretized to obtain formulas (13) and (14):

[0039]

[0040]

[0041]

[0042]

[0043] Among them, T s is the sampling interval;

[0044] v[n] is the total loop velocity at the nth position;

[0045] T[n] is the coefficient of the power transformer at the nth position;

[0046] R E [n], L E [n] is the resistance and inductance of the electrical terminal at the nth position;

[0047] i m [n]、i m [n-1] is the measured current signal at the nth and n-1th positions;

[0048] u p [n], x 2p [n] is the predicted voltage signal and predicted displacement signal of the nth position;

[0049] x[n], x[n-1], x[n-2] represent the total loop displacements at the nth, n-1th, and n-2th positions;

[0050] K Φ [n] is C Φ The reciprocal of [n], C Φ [n] is the force compliance of the power transformer at the nth position;

[0051] x2[n], x2[n-1], x2[n-2] represent the displacements of the balanced armature loudspeaker at the n-th, n-1-th, and n-2-th positions; d1[n], d2[n], σ x2 [n], c1[n], c2[n], σ x [n], σ x3 [n] are the correlation coefficients of the nth position:

[0052]

[0053]

[0054]

[0055] Among them, ω cmz [n],ζ m [n], ω cm [n],ζ cm [n], ω mz [n], ω m [n] is the process quantity at the nth position;

[0056] R cm [n],M cm [n] and C cm [n] is the force resistance, mass and force compliance of the armature part in the mechanical end model at the nth position, K cm [n] is C cm the reciprocal of [n];

[0057] M m [n] and R m [n] is the mass and resistance of the suspension in the mechanical end model at the nth position;

[0058] K mt [n] is the second combined force order C at the nth position mt the reciprocal of [n];

[0059] And according to the backward Euler method, the total loop speed v[n] at the nth position satisfies:

[0060]

[0061] Preferably, in step 3, the parameters include: resistance and inductance at the electrical end, coefficients of the power transformer model, force resistance and mass of the armature part at the mechanical end, force resistance and mass of the suspension, and the inverse of the force compliance of the power transformer model, the inverse of the force compliance of the armature part in the mechanical end model, and the inverse of the second combined force compliance;

[0062] The signals include voltage signals, current signals, and displacement signals.

[0063] Preferably, in step 3, obtaining a predicted signal of the balanced armature loudspeaker according to the discretized equation and the current parameters of the balanced armature loudspeaker, calculating the error between the predicted signal and the measured signal of the balanced armature loudspeaker, and updating the parameters according to the error, specifically includes:

[0064] 1) Based on the measured displacement signal and current parameters, iterate v[n] according to formulas (12) and (15), and substitute it into formula (11), combined with the discretized measured current signal i m [n]、i m [n-1], get the discretized predicted voltage signal u p [n];

[0065] According to the discretized predicted voltage signal u p [n] and measured voltage signal u m [n] Calculate the voltage error and update some parameters based on the voltage error, including the resistance and inductance of the electrical terminal at the n+1th position and the coefficient of the power transformer: R E [n+1], L E [n+1] and T[n+1];

[0066] 2) Based on the measured displacement signal and the current parameters, iterate x[n-1] according to formula (13) and substitute it into formula (14), combined with the discretized measured current signal i m [n-1], get the discretized predicted displacement signal x 2p [n];

[0067] According to the discretized predicted displacement signal x 2p [n] and the measured displacement signal x 2m [n] Calculate the displacement error and update the remaining parameters based on the displacement error.

[0068] Preferably, in step 3, the termination condition is: when the error is less than the set tolerance or the maximum number of iterations is reached.

[0069] A third aspect of the present invention provides a parameter identification system for a balanced armature loudspeaker, comprising:

[0070] A modeling module is used to establish an equivalent circuit model of a balanced armature loudspeaker and convert the acoustic mechanism of the acoustic end of the equivalent circuit model of the balanced armature loudspeaker to the mechanical end, thereby obtaining a simplified equivalent circuit model of the balanced armature loudspeaker and establishing its loop equation;

[0071] A discretization module, configured to discretize the loop equation of the simplified equivalent circuit model to obtain a discretized equation;

[0072] The parameter identification module is used to obtain the predicted signal of the balanced armature speaker based on the discretized equation and the current parameters of the balanced armature speaker, calculate the error between the predicted signal and the actual measured signal of the balanced armature speaker, and update the parameters according to the error until the termination condition is reached, and use the current parameters as the identified parameters.

[0073] A terminal includes a processor and a storage medium; the storage medium is used to store instructions;

[0074] The processor is configured to operate according to the instructions to execute the steps of the method.

[0075] A computer-readable storage medium stores a computer program, which implements the steps of the method when executed by a processor.

[0076] Compared with the prior art, the beneficial effects of the present invention include at least:

[0077] The present invention proposes an equivalent circuit model for a balanced armature loudspeaker. The proposed model accurately models the mechanical end and the force-acoustic variable device, which is faster, more convenient and more efficient than finite element modeling. Compared with the traditional equivalent circuit model, the model of the present invention can accurately predict the displacement and sound radiation of the balanced armature loudspeaker, making up for the shortcomings of the traditional equivalent circuit model.

[0078] The present invention proposes for the first time a parameter identification algorithm for balanced armature speakers. In the more common dynamic coil speaker units, parameter identification has been widely popularized and used. It is an important method for analyzing and using speakers and actively controlling speakers. However, there is a lack of parameter identification algorithms for balanced armature speakers, which restricts the performance analysis of balanced armature speakers. Based on the proposed equivalent circuit model, the present invention simplifies the model for the convenience of identification. On the basis of the simplified model, an accurate parameter identification algorithm for balanced armature speakers is given, which can greatly reduce the difficulty of balanced armature speaker performance analysis. It does not require complex material parameters and can accurately identify the relevant parameters of the speaker only through time domain signals. These identified parameters can be directly used for speaker performance analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 The traditional model of the equivalent circuit of a balanced armature loudspeaker;

[0080] Figure 2 The equivalent circuit model of the balanced armature loudspeaker proposed in the present invention;

[0081] Figure 3 Flowchart for modeling the equivalent circuit of a balanced armature loudspeaker;

[0082] Figure 4 The equivalent circuit model of the simplified balanced armature loudspeaker proposed by the present invention is used for loudspeaker parameter identification;

[0083] Figure 5 A schematic block diagram of the parameter identification process of a balanced armature loudspeaker;

[0084] Figure 6 Flowchart of the balanced armature loudspeaker parameter identification algorithm. DETAILED DESCRIPTION

[0085] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0086] Embodiment 1 of the present invention provides an equivalent circuit model of a balanced armature loudspeaker, including models of the loudspeaker's electrical end and electrical transformer, mechanical end, mechanoacoustic transformer, and acoustic end, as follows:

[0087] (1) Model the electrical terminals and power transformers.

[0088] Traditional models such as Figure 1 As shown, there are defects in the mechanical end and the force-acoustic variable modeling, which cannot accurately predict the displacement and sound radiation of the balanced armature loudspeaker.

[0089] The electrical end is currently more mature and is modeled as an AC source V s , resistor R E and inductor L E .

[0090] The power transformer is modeled as a coefficient T and a force compliance C Φ T and C Φ The linear parameter can be expressed as:

[0091]

[0092]

[0093]

[0094] Among them, l M is the length of the permanent magnet in the balanced armature loudspeaker, μ r is the relative recoil permeability, B r is the effective remanence of the permanent magnet, A is the cross-sectional area between the permanent magnet and the air gap in the speaker, N is the number of voice coils in the speaker, D is the length of the air gap between the armature and the permanent magnet, and μ0 is the magnetic permeability of air (4π×10 -7 N / A 2 ).

[0095] (2) Model the mechanical end.

[0096] Figure 1 The mechanical end structure is briefly modeled, and all structures are simplified into an R mt -C mt -M mt System. S d is the diaphragm area of ​​the speaker. Z AB is the acoustic structure impedance. Traditional models cannot accurately predict the displacement and sound radiation performance of balanced armature loudspeakers. The model of the present invention is modeled at the mechanical end and the force-acoustic variable, such as Figure 2 shown.

[0097] The armature part is regarded as a cantilever with the same boundary conditions, and the armature part is modeled as R cm ,M cm and C cm The linear formula of the relevant parameters can be expressed as:

[0098]

[0099]

[0100] Where ρ is the density of the armature material, h is the armature height, w is the armature width, l is the armature length, and E is the Young's modulus of the armature material. cm is the force resistance of the armature part.

[0101] The suspension device is modeled as M m ,C m and R m , representing the mass, force compliance and force resistance of the suspension device respectively.

[0102] Considering the coupling between the armature and the suspension, R cm -M cm -C cm With R m -Mm -C m Parallel modeling. Considering the creep effect of the diaphragm, C m It can be a frequency-dependent equation.

[0103] (3) Model the force-acoustic variable device and the acoustic end.

[0104] The coefficients of the force-acoustic variable are:

[0105]

[0106] The x-axis is the line where the diaphragm is stationary, the y-axis is the displacement, and the intersection of the y-axis and the line where the diaphragm is vibrating is the origin. d is the diaphragm length of the speaker, x pin is the coordinate of the fulcrum connecting the armature and the diaphragm, and x0 is the coordinate of the edge of the diaphragm away from the fulcrum (usually 0 or a value close to 0). d is the diaphragm area of ​​the unit, i.e., the diaphragm area of ​​a balanced armature loudspeaker. Using the coefficient of the aforementioned fore-and-aft transducer as the radiation area to calculate sound radiation allows for accurate prediction of sound radiation.

[0107] The acoustic side is modeled according to its structure.

[0108] At this point, the modeling of a balanced armature loudspeaker is completed. The model proposed in the present invention can be directly used to accurately predict the electrical impedance, displacement and sound radiation performance of the balanced armature loudspeaker.

[0109] Once the relevant material and structural parameters of the model are known and combined with the above modeling formula, the linear parameter values ​​of the model can be obtained. The parameters mentioned in the model can be either linear or nonlinear. Linear parameters are constants after calculation, while nonlinear parameters are expressions related to displacement, voltage, and current, such as correlation coefficients. Figure 3 A modeling flowchart for a balanced armature loudspeaker is given.

[0110] However, under normal conditions, complex material parameters, structural parameters, etc. cannot be obtained in real time and accurately. The present invention removes the complex acoustic structure of the balanced armature loudspeaker and identifies the parameters of the loudspeaker.

[0111] Embodiment 2 of the present invention provides a method for identifying parameters of a balanced armature loudspeaker, the method comprising:

[0112] Step 1: Establishing an equivalent circuit model of the balanced armature loudspeaker, converting the acoustic mechanism of the acoustic end in the equivalent circuit model of the balanced armature loudspeaker to the mechanical end, obtaining a simplified equivalent circuit model of the balanced armature loudspeaker and establishing its loop equation;

[0113] 1) Simplify the equivalent circuit model. This step converts the simple acoustic mechanism to the mechanical end and establishes a simplified equivalent circuit model of the balanced armature loudspeaker.

[0114] The identification algorithm usually uses a speaker unit without a complex acoustic structure. The present invention removes the complex acoustic structure and uses a moving iron unit with a simple acoustic structure. It has only one back cavity, which can be measured with acoustic compliance C. AB Indicates that the acoustic back cavity is merged into the mechanical end and represented as a force-compliant C mAB :

[0115]

[0116] According to the following formula, C mAB with C m Combined into a force, expressed as C mt ,like Figure 4 shown.

[0117]

[0118] 2) Establish the loop equation:

[0119] according to Figure 4 The simplified circuit shown lists the following three loop equations:

[0120]

[0121]

[0122]

[0123] Among them, K Φ =1 / C Φ ,K cm =1 / C cm ,K m =1 / C m , u is the voltage, i is the current, x is the total displacement of the loop, v is the total velocity of the loop, x2 is the displacement of the balanced armature speaker, and v2 is the velocity of the balanced armature speaker.

[0124] The parameters described in the above equations can be either linear or nonlinear. A linear parameter is a constant, while a nonlinear parameter is an expression related to the displacement x², voltage u, and current i, such as a correlation coefficient.

[0125] The above three loop equations can be processed arbitrarily and then discretized to facilitate the subsequent identification process. The present invention substitutes formula (9) in the loop equation into formula (8) to obtain:

[0126]

[0127] Step 2, discretize the loop equation to obtain a discretized equation;

[0128] The loop equation is discretized using a discretization method (including but not limited to the forward / backward Euler method, the impulse response invariance method, the zero-pole matching method, etc.) to obtain a discretized equation. For example (taking linear parameters as an example, if it is a nonlinear parameter, the following formula can be changed accordingly) the backward Euler method is used to discretize formula (7) to obtain formula (11), the zero-pole matching method is used to discretize formula (9) to obtain formula (13), and the impulse response invariance method is used to discretize formulas (8) and (10) to obtain formulas (12) and (14):

[0129]

[0130]

[0131]

[0132]

[0133] Among them, T s is the sampling interval;

[0134] v[n] is the total loop velocity at the nth position;

[0135] T[n] is the coefficient of the power transformer at the nth position;

[0136] R E [n], L E [n] is the resistance and inductance of the electrical terminal at the nth position;

[0137] i m [n]、i m [n-1] is the measured current signal at the nth and n-1th positions;

[0138] u p [n], x 2p [n] is the predicted voltage signal and predicted displacement signal of the nth position;

[0139] x[n], x[n-1], x[n-2] represent the total loop displacements at the nth, n-1th, and n-2th positions;

[0140] K Φ [n] is C Φ The reciprocal of [n], C Φ [n] is the force compliance of the power transformer at the nth position;

[0141] x2[n], x2[n-1], x2[n-2] represent the displacements of the balanced armature loudspeaker at the n-th, n-1-th, and n-2-th positions; d1[n], d2[n], σ x2 [n], c1[n], c2[n], σ x [n], σ x3 [n] are the correlation coefficients of the nth position:

[0142]

[0143]

[0144]

[0145] Among them, ω cmz [n],ζ m [n], ω cm [n],ζ cm [n], ω mz [n], ω m [n] is the process quantity at the nth position, and its expression is related to the model parameters;

[0146] R cm [n],M cm [n] and C cm [n] is the force resistance, mass and force compliance of the armature part in the mechanical end model at the nth position, K cm [n] is C cm the reciprocal of [n];

[0147] M m [n] and R m [n] is the mass and resistance of the suspension in the mechanical end model at the nth position;

[0148] K mt [n] is the second combined force order C at the nth position mt the reciprocal of [n];

[0149] And according to the backward Euler method, the total loop speed v[n] at the nth position satisfies:

[0150]

[0151] It is understood that all parameters in the model can be linear or nonlinear, such as C m It can be either a constant or an expression related to x2. The preferred solutions given in this embodiment are all calculation expressions of linear parameters. If the parameters are nonlinear (i.e. related to displacement, voltage, current), then the relevant expressions of all parameters need to have corresponding formula changes according to the discretization process, such as Cm When it is related to x and the correlation coefficient, it will become an expression related to x2[n], x2[n-1], etc. after discretization rather than a single C m [n].

[0152] Step 3: Based on the discretized equation and the current parameters of the balanced armature speaker, obtain the predicted signal of the balanced armature speaker, calculate the error between the predicted signal and the measured signal of the balanced armature speaker, and update the parameters according to the error until the termination condition is reached, and use the current parameters as the identified parameters.

[0153] like Figure 5 、 Figure 6 As shown in Figure 2, the specific identification algorithm process is as follows:

[0154] Step 31, initializing parameters, including: resistance and inductance of the electrical end, coefficients of the electric transformer model, force resistance and mass of the armature part of the mechanical end, force resistance and mass of the suspension, as well as the inverse of the force compliance of the electric transformer model, the inverse of the force compliance of the armature part in the mechanical end model, and the inverse of the second combined force compliance, i.e., initializing parameter vector [w p (0)]=[R E (0),L E (0),T(0),K Φ (0),K cm (0),R cm (0),M cm (0),K mt (0),R m (0),M m (0)], where [w p (0)] Theoretically, it can be any value. If it is far from the true value, it will take a long time to iterate;

[0155] And start identification from n=1;

[0156] Step 32, select a suitable step vector [μ p ], corresponding to the step size of different parameters, where the step size is based on the initial value [w p (0)] and the time domain signal size to adjust, generally speaking, the step size is 2-5 orders of magnitude smaller than the initial value;

[0157] Step 33: obtaining a predicted signal of the balanced armature speaker based on the discretized equation and current parameters of the balanced armature speaker, calculating an error between the predicted signal and the measured signal of the balanced armature speaker, and updating the parameters based on the error;

[0158] Using the discretized measured signal and the current parameter w p [n], calculate the predicted signal s of the discretized signal at point np [n], calculate the discretized prediction signal s p [n] and the discretized measured signal s m [n] and update [w p (n+1)];

[0159] The error calculation formula between the measured signal and the predicted signal is:

[0160] e[n]=s m [n]-s p [n] (16)

[0161] Among them, e[n] is the error signal of the discretized signal at point n, s m [n] is the measurement signal of the nth point of the discretized signal, s p [n] is the predicted signal of the nth point of the discretized signal. Taking the voltage signal as an example, when the discretized signal is voltage, formula (16) becomes:

[0162] e[n]=u m [n]-u p [n]

[0163] Among them, u m [n] is the measured voltage at point n, u p [n] is the predicted voltage at point n.

[0164] The parameter update formula is:

[0165]

[0166] Among them, w p [n+1] is the updated parameter of the n+1th iteration position, w p [n] is the parameter of the nth iteration position, μ p is the step size of the parameter change, e[n] is the error signal of the nth iteration position of the discretized signal, w p Refers to all parameters in the model, and each parameter is updated according to formula (17). is the instantaneous value of the gradient. For example, when the updated parameter is the coefficient T, μ p That is the update step size μ of parameter T T , formula (17) becomes:

[0167]

[0168] Formula (17) is the parameter update formula of the LMS algorithm, which can adjust the parameter update amplitude according to the error size so that the parameter approaches the correct value as soon as possible.

[0169] In step 33, there are three types of signals used to update parameters: voltage signal, current signal, and displacement signal. Any of these signals can be used with the current parameters to predict another signal to obtain a predicted signal value. Taking the prediction of voltage signal and displacement signal as an example, step 33 specifically includes:

[0170] 1) Based on the measured displacement signal and current parameters, iterate v[n] according to formulas (12) and (15), and substitute it into formula (11), combined with the discretized measured current signal i m [n]、i m [n-1], get the discretized predicted voltage signal u p [n]; The specific method is: calculate x[n] according to the measured displacement signals x2[n], x2[n-1], x2[n-2] and the current parameters through formula (12), then calculate v[n] according to formula (15), substitute v[n] into formula (11), and combine it with the measured current signal i m [n]、i m [n-1] calculate u p [n];

[0171] Using formula (16), according to the discretized predicted voltage signal u p [n] and measured voltage signal u m [n] Calculate the voltage error and use formula (17) to update the parameters according to the voltage error, that is, use formula (17) to update R E [n+1],L E [n+1], and T[n+1];

[0172] 2) Based on the measured displacement signal and the current parameters, iterate x[n-1] according to formula (13) and substitute it into formula (14), combined with the discretized measured current signal i m [n-1], get the discretized predicted displacement signal x 2p [n];

[0173] Using formula (16), according to the discretized predicted displacement signal x 2p [n] and the measured displacement signal x 2m [n] Calculate the displacement error and use formula (17) to update the remaining parameters based on the displacement error.

[0174] Step 34, set the iteration position to n=n+1;

[0175] Step 35, check whether to terminate: When the two errors obtained in 1) and 2) above are respectively continuously less than a small tolerance (e.g., continuously less than 3% of the maximum value of the time domain signal used) or the maximum number of iterations is reached, the iteration process ends and the current parameters are used as the identified parameters. Otherwise, the process returns to step 33. The duration of the iteration is determined by the error trend and generally needs to be continued until the error trend reaches a stable state.

[0176] Embodiment 3 of the present invention provides a parameter identification system for a balanced armature loudspeaker, comprising:

[0177] A modeling module is used to establish an equivalent circuit model of a balanced armature loudspeaker and convert the acoustic mechanism of the acoustic end of the equivalent circuit model of the balanced armature loudspeaker to the mechanical end, thereby obtaining a simplified equivalent circuit model of the balanced armature loudspeaker and establishing its loop equation;

[0178] A discretization module, configured to discretize the loop equation of the simplified equivalent circuit model to obtain a discretized equation;

[0179] The parameter identification module is used to obtain the predicted signal of the balanced armature speaker based on the discretized equation and the current parameters of the balanced armature speaker, calculate the error between the predicted signal and the actual measured signal of the balanced armature speaker, and update the parameters according to the error until the termination condition is reached, and use the current parameters as the identified parameters.

[0180] Embodiment 4 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions;

[0181] The processor is configured to operate according to the instructions to execute the steps of the method.

[0182] Embodiment 5 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0183] Compared with the prior art, the beneficial effects of the present invention include at least:

[0184] The present invention proposes an equivalent circuit model for a balanced armature loudspeaker. The proposed model accurately models the mechanical end and the force-acoustic variable device, which is faster, more convenient and more efficient than finite element modeling. Compared with the traditional equivalent circuit model, the model of the present invention can accurately predict the displacement and sound radiation of the balanced armature loudspeaker, making up for the shortcomings of the traditional equivalent circuit model.

[0185] The present invention proposes for the first time a parameter identification algorithm for balanced armature speakers. In the more common dynamic coil speaker units, parameter identification has been widely popularized and used. It is an important method for analyzing and using speakers and actively controlling speakers. However, there is a lack of parameter identification algorithms for balanced armature speakers, which restricts the performance analysis of balanced armature speakers. Based on the proposed equivalent circuit model, the present invention simplifies the model for the convenience of identification. On the basis of the simplified model, an accurate parameter identification algorithm for balanced armature speakers is given, which can greatly reduce the difficulty of balanced armature speaker performance analysis. It does not require complex material parameters and can accurately identify the relevant parameters of the speaker only through time domain signals. These identified parameters can be directly used for speaker performance analysis.

[0186] The present disclosure may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0187] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., light through a fiber optic cable, or an electrical signal transmitted through an electrical wire).

[0188] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0189] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., utilizing an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions. The electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0190] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. An equivalent circuit model of a balanced armature loudspeaker, comprising models of the loudspeaker's electrical end and electrical transformer, mechanical end, mechanoacoustic transformer, and acoustic end, characterized by: The mechanical end adopts a model in which the armature and suspension are coupled in parallel; The model coefficients of the force-acoustic variable are: Among them, δ is the effective radiation coefficient of the balanced armature speaker, l d is the speaker diaphragm length, x pin is the coordinate of the fulcrum connecting the armature and the diaphragm, x0 is the coordinate of the edge of the diaphragm away from the fulcrum, S d is the diaphragm area of ​​the speaker.

2. The equivalent circuit model of a balanced armature loudspeaker according to claim 1, wherein: The electrical end uses an AC source V s , resistor R E and inductor L E Series model; The power transformer model includes the coefficient T and the force C Φ ; The acoustic side uses a model established based on its structure.

3. The equivalent circuit model of a balanced armature loudspeaker according to claim 1, wherein: The armature adopts R cm ,M cm and C cm A series model where R cm ,M cm and C cm Represent the force resistance, mass and force compliance of the armature respectively; The suspension adopts M m ,C m and R m Series model, where M m ,C m and R m They represent the mass, force compliance and force resistance of the suspension respectively.

4. A method for identifying parameters of a balanced armature loudspeaker, characterized in that: The method comprises: Step 1: Establish an equivalent circuit model of the balanced armature loudspeaker according to any one of claims 1 to 3, and convert the acoustic mechanism of the acoustic end to the mechanical end to obtain a simplified equivalent circuit model of the balanced armature loudspeaker and establish its loop equation; Step 2: discretizing the loop equation of the simplified equivalent circuit model to obtain a discretized equation; Step 3: Based on the discretized equation and the current parameters of the balanced armature speaker, obtain the predicted signal of the balanced armature speaker, calculate the error between the predicted signal and the measured signal of the balanced armature speaker, and update the parameters according to the error until the termination condition is reached, and use the current parameters as the identified parameters.

5. The parameter identification method according to claim 4, characterized in that: In step 1, the equivalent circuit model is simplified as follows: The acoustic mechanism of the acoustic end adopts the acoustic compliance C AB The acoustic back cavity is represented by the finite element model, and is merged into the mechanical end. The first combined force is obtained by combining the model coefficients of the force-acoustic variable. mAB : C mAB The force of the mechanical end suspension C m Merge to get the second combined force C mt :

6. The parameter identification method according to claim 5, characterized in that: In step 1, the loop equation established based on the simplified equivalent circuit model is: Substituting formula (9) in the loop equation into formula (8) yields: Among them, R E and L E The resistance and inductance of the electrical end model; u is voltage, i is current; t represents the time signal; x is the total displacement of the loop, v is the total velocity of the loop; x2 is the displacement of the balanced armature speaker, v2 is the velocity of the balanced armature speaker; K Φ C Φ The reciprocal of K cm It is C cm The reciprocal of K mt It is C mt The reciprocal of T is the coefficient of the power transformer model; C Φ is the force compliance of the power transformer model; R cm ,M cm and C cm is the force resistance, mass and force compliance of the armature part in the mechanical end model; M m and R m is the mass and resistance of the suspension in the mechanical end model.

7. The parameter identification method according to claim 6, characterized in that: The discretization process of the loop equation is as follows: In the linear range, formula (7) is discretized to obtain formula (11), formula (8) is discretized to obtain formula (12), and formula (9) and formula (10) are discretized to obtain formulas (13) and (14): Among them, T s is the sampling interval; v[n] is the total loop velocity at the nth position; T[n] is the coefficient of the power transformer at the nth position; R E [n], L E [n] is the resistance and inductance of the electrical terminal at the nth position; i m [n]、i m [n-1] is the measured current signal at the nth and n-1th positions; u p [n], x 2p [n] is the predicted voltage signal and predicted displacement signal of the nth position; x[n], x[n-1], x[n-2] represent the total loop displacements at the nth, n-1th, and n-2th positions; K Φ [n] is C Φ The reciprocal of [n], C Φ [n] is the force compliance of the power transformer at the nth position; x2[n], x2[n-1], x2[n-2] represent the displacements of the balanced armature loudspeaker at positions n, n-1, and n-2; d1[n], d2[n], σ x2 [n], c1[n], c2[n], σ x [n], σ x3 [n], are the correlation coefficients of the nth position: Among them, ω cmz [n],ζ m [n], ω cm [n],ζ cm [n], ω mz [n], ω m [n] is the process quantity at the nth position; R cm [n],M cm [n] and C cm [n] is the force resistance, mass and force compliance of the armature part in the mechanical end model at the nth position, K cm [n] is C cm the reciprocal of [n]; M m [n] and R m [n] is the mass and resistance of the suspension in the mechanical end model at the nth position; K mt [n] is the second combined force order C at the nth position mt the reciprocal of [n]; And according to the backward Euler method, the total loop speed v[n] at the nth position satisfies:

8. The parameter identification method according to claim 5 or 7, characterized in that: In step 3, the parameters include: the resistance and inductance of the electrical end, the coefficient of the power transformer model, the force resistance and mass of the armature part of the mechanical end, the force resistance and mass of the suspension, the inverse of the force compliance of the power transformer model, the inverse of the force compliance of the armature part in the mechanical end model, and the inverse of the second combined force compliance; The signals include voltage signals, current signals, and displacement signals.

9. The parameter identification method according to claim 7, characterized in that: In step 3, based on the discretized equation and the current parameters of the balanced armature speaker, a predicted signal of the balanced armature speaker is obtained, an error between the predicted signal and the measured signal of the balanced armature speaker is calculated, and parameters are updated according to the error, which specifically includes: 1) Based on the measured displacement signal and current parameters, iterate v[n] according to formulas (12) and (15), and substitute it into formula (11), combined with the discretized measured current signal i m [n]、i m [n-1], get the discretized predicted voltage signal u p [n]; According to the discretized predicted voltage signal u p [n] and measured voltage signal u m [n] Calculate the voltage error and update some parameters based on the voltage error, including the resistance and inductance of the electrical terminal at the n+1th position and the coefficient of the power transformer: R E [n+1], L E [n+1] and T[n+1]; 2) Based on the measured displacement signal and the current parameters, iterate x[n-1] according to formula (13) and substitute it into formula (14), combined with the discretized measured current signal i m [n-1], get the discretized predicted displacement signal x 2p [n]; According to the discretized predicted displacement signal x 2p [n] and the measured displacement signal x 2m [n] Calculate the displacement error and update the remaining parameters based on the displacement error.

10. The parameter identification method according to claim 1, characterized in that: In step 3, the termination condition is: when the error is less than the set tolerance or the maximum number of iterations is reached.

11. A parameter identification system for a balanced armature loudspeaker, utilizing the parameter identification method according to any one of claims 4 to 10, characterized in that: The system comprises: A modeling module is used to establish an equivalent circuit model of a balanced armature loudspeaker and convert the acoustic mechanism of the acoustic end of the equivalent circuit model of the balanced armature loudspeaker to the mechanical end, thereby obtaining a simplified equivalent circuit model of the balanced armature loudspeaker and establishing its loop equation; A discretization module, configured to discretize the loop equation of the simplified equivalent circuit model to obtain a discretized equation; A parameter identification module is used to obtain a predicted signal of the balanced armature speaker based on the discretized equation and the current parameters of the balanced armature speaker, calculate the error between the predicted signal and the actual measured signal of the balanced armature speaker, and update the parameters according to the error until the termination condition is reached, and use the current parameters as the identified parameters.

12. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 4 to 10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 4 to 10 are implemented.

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