CN111859726A - Large-size shell structure intermediate frequency sound radiation forecasting method based on local optimization - Google Patents

Large-size shell structure intermediate frequency sound radiation forecasting method based on local optimization Download PDF

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CN111859726A
CN111859726A CN202010476533.2A CN202010476533A CN111859726A CN 111859726 A CN111859726 A CN 111859726A CN 202010476533 A CN202010476533 A CN 202010476533A CN 111859726 A CN111859726 A CN 111859726A
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成玮
王桦瑀
陈雪峰
张鹏
韩圣明
杨志勃
张兴武
高琳
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Xian Jiaotong University
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Abstract

The invention discloses a local optimization-based method for forecasting medium-frequency sound radiation of a shell structure, which comprises the steps of firstly establishing a structural model of the shell structure based on the size parameters of the shell structure; then, grid division is carried out on the structural model, the subsystems are divided based on the grid model, the subsystems with the mode number of 3-5 are taken as SEA subsystems, the boundary coupling relation of the subsystems in the SEA subsystems and the fluid acoustic environment around the structure are established, and then intermediate-frequency model parameters of the high-energy contribution subsystems of the SEA subsystems are obtained by adopting a transient method; the method can improve the forecasting precision of the radiation sound field while reducing the model parameter test, can provide reliable basis for the vibration and noise reduction work of the naval vessel, and has important theoretical significance and engineering application value.

Description

Large-size shell structure intermediate frequency sound radiation forecasting method based on local optimization
Technical Field
The invention relates to the field of mechanical vibration reduction and noise reduction, in particular to a local optimization-based medium-frequency sound radiation forecasting method for a large-size shell structure.
Background
The realization of rapidity is a pursuit target of large-size shell structure equipment such as current underwater aircrafts, ships, airplanes and the like, the structural quality is developed to be light weight, the power of power equipment is increased, the problems of equipment vibration and radiation noise are increasingly highlighted, and the quality performance and the service performance of the equipment are reduced. The accurate prediction of the sound radiation of the shell structure equipment can fully reveal the distribution of a noise sound field, so as to scientifically guide the vibration and noise reduction of the submarine, and has important engineering significance for improving the equipment performance. The vibration excitation source of the large-size shell equipment has the characteristics of large amplitude and wide spectrum, sound radiation prediction needs to be carried out in a wide frequency band, an effective result cannot be obtained by adopting a single analysis method, and a structural radiation sound field is usually predicted by adopting a Hybrid FE-SEA method in a high frequency band. The model parameters of the SEA subsystem need to be estimated by adopting the Hybrid FE-SEA method for calculation, however, in the practical engineering problem, the theoretical method for estimating the model parameters of the SEA subsystem has larger errors due to the complexity and irregularity of the structure, so the experimental method needs to be adopted for obtaining the model parameters of the SEA subsystem, but the shell structures of submarines, ships and the like have huge equipment volume and a large number of subsystems, so the difficulty in measuring the model parameters is great, and the theoretical method can only be adopted for estimating the parameters, so the intermediate frequency radiation sound field prediction precision is lower.
Disclosure of Invention
Aiming at the problems of difficulty in partitioning subsystems of the medium-frequency sound radiation in a large-size shell structure and difficulty in testing model parameters, the invention aims to provide a method for forecasting the medium-frequency sound radiation in the large-size shell structure based on local parameter optimization, reasonably partitions the medium-frequency model SEA subsystems, tests a small number of subsystem model parameters locally, and improves the precision of sound radiation forecasting while reducing the test quantity of the model parameters.
In order to achieve the purpose, the invention adopts the following technical scheme:
a local optimization-based method for forecasting medium-frequency sound radiation in a large-size shell structure comprises the following steps:
step 1), establishing a geometric model of the shell structure according to geometric information of the shell structure;
step 2), carrying out grid division on a geometric model of the shell structure to obtain a shell structure grid model, carrying out subsystem division on the shell structure based on the shell structure grid model to obtain a plurality of subsystems, and taking the subsystem with the mode number of 3-5 as an SEA subsystem;
step 3), establishing a boundary coupling relation of each subsystem and a fluid acoustic environment around the structure, and then obtaining intermediate frequency model parameters of the high-energy contribution subsystem of the intermediate frequency acoustic radiation model SEA subsystem by adopting a transient method;
And 4, establishing a structural response equation of the intermediate frequency acoustic radiation model of the shell structure by locally correcting intermediate frequency model parameters of an SEA subsystem in the intermediate frequency model, applying frequency to be vibration excitation in a corresponding intermediate frequency range, and solving the structural response equation of the intermediate frequency acoustic radiation model of the shell structure to obtain a radiation sound field of the shell structure so as to realize the intermediate frequency acoustic radiation forecast of the large-size shell structure.
Furthermore, the geometric information of the shell structure is measured and subjected to structural analysis, and a geometric model of the shell structure is established according to the analysis result.
Further, the geometric information in the step 1) includes the geometric shape and the form and position size of each part in the structure, and the structure analysis object includes a bearing part, a vibration transmission part and a mass part.
Further, the subsystem division method adopts the step of dividing the subsystems along the axial direction.
Further, an internal loss factor of the high-energy contribution subsystem is obtained by adopting a transient attenuation method:
Figure RE-GDA0002694574270000031
Figure RE-GDA0002694574270000032
in the formula:Tn-an internal loss attenuation rate; etai-the internal loss factor of subsystem i; a. theTn(t1)—— t1Amplitude of the time decay Rate Curve, ATn(t2)——t2Amplitude of the time decay rate curve; omegac-the center frequency.
Further, locally correcting intermediate frequency model parameters of an SEA subsystem in the intermediate frequency model in the step 4) to establish a structural response equation of the shell model:
Determining the displacement response of the subsystem as:
Figure RE-GDA0002694574270000033
Figure RE-GDA0002694574270000034
in the formula: ddIs the dynamic stiffness matrix of the finite element model subsystem, SffTo be a cross-spectrum of the excitation forces applied to the finite element sub-system,
Figure RE-GDA0002694574270000035
is the average dynamic stiffness matrix of subsystem i, EiTo the vibrational energy of subsystem i, niIs the modal density of subsystem i;
because each subsystem is power balanced, the power balance equation of the FE-SEA coupled system is as follows:
Figure RE-GDA0002694574270000036
in the formula: etaiIs the internal loss factor of subsystem i; piIs the input power of the sub-system i,
Figure RE-GDA0002694574270000037
for input power produced by forces exerted on a deterministic system, ηikThe vibration power flow is transferred from the coupling sub-system i to the coupling loss factor of the coupling sub-system k.
Compared with the prior art, the invention has the following beneficial technical effects:
the invention relates to a method for forecasting medium frequency sound radiation of a large-size shell structure based on local parameter optimization, which constructs a shell structure grid model through grid division, divides subsystems based on the grid model, takes subsystems with 3-5 mode numbers as SEA subsystems, establishes boundary coupling relation of the subsystems in the SEA subsystems and fluid acoustic environment around the structure, obtains medium frequency model parameters of a high-energy contribution subsystem of the medium frequency sound radiation model SEA subsystems by adopting a transient method, establishes a shell structure medium frequency sound radiation model structure response equation through locally correcting the medium frequency model parameters of the SEA subsystems in the medium frequency model, reduces model parameter testing amount while ensuring enough forecasting precision of sound radiation, applies vibration excitation with frequency in corresponding medium frequency band, solves the shell structure medium frequency sound radiation model structure response equation to obtain a shell structure radiation sound field, the method has the advantages that the intermediate frequency sound radiation forecasting of the shell structure is realized, more accurate acoustic response solving is obtained, and compared with the traditional intermediate frequency sound radiation forecasting method, the method reduces model parameter testing and improves the forecasting precision of the radiation sound field.
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Fig. 1 is a structure of a test bed of a geometric model of a shell structure according to an embodiment of the present invention.
FIG. 2 is a schematic structural diagram of an SEA subsystem division performed by a cylindrical shell using a single-curvature plate according to an embodiment of the present invention; FIG. 2(a) is a schematic diagram of the division result of the shell structure grid model along the axial direction by using 1 single-curvature plate; FIG. 2(b) is a schematic diagram of the division result of the shell structure grid model along the axial direction by using 3 single-curvature plates; FIG. 2(c) is a schematic diagram of the division result of the shell structure grid model along the axial direction by using 5 single-curvature plates; FIG. 2(d) is a schematic diagram of the division result of the shell structure grid model along the circumferential direction by using 2 single-curvature plates; fig. 2(e) is a schematic diagram of the division result of the 4 single-curvature plates along the circumferential direction of the shell structure grid model.
Fig. 3 is a comparison graph of sound radiation prediction results of different division methods of the cylindrical shell subsystem in the embodiment of the invention.
FIG. 4 is a schematic structural diagram of a sub-system division of a conical shell by using a single-curvature plate according to an embodiment of the present invention; fig. 4(a) is a schematic diagram of the division result of the conical shell structure grid model along the axial direction by using 1 single-curvature plate; FIG. 4(b) is a schematic diagram of the division result of the conical shell structure grid model along the axial direction by using 2 single-curvature plates; the figure (c) is a schematic diagram of the division result of the conical shell structure grid model along the axial direction by adopting 5 single-curvature plates; and (d) is a schematic diagram of a division result of 2 single-curvature plates along the circumferential direction of the conical shell structure grid model, and (e) is a schematic diagram of a division result of 4 single-curvature plates along the circumferential direction of the conical shell structure grid model.
FIG. 5 is a comparison graph of sound radiation prediction results of different division methods of the cone SEA subsystem according to the embodiment of the present invention.
Fig. 6 is a schematic diagram of a model of the influence of different parameters on the sound radiation prediction result according to an embodiment of the present invention.
FIG. 7 is a comparison of the internal loss factor change versus acoustic radiation prediction results in an embodiment of the present invention.
FIG. 8 is a comparison of coupling loss factor change versus acoustic radiation prediction results in an embodiment of the present invention.
FIG. 9 is a comparison of loss factor change versus acoustic radiation prediction results for subsystems of different energy contributions in an embodiment of the present invention.
Fig. 10 is a graph of an experimental scheme of dissipation factor in a high energy contributing SEA subsystem in an embodiment of the present invention.
Fig. 11 is a graph of the dissipation factor test results within the high energy contributing SEA subsystem in an embodiment of the present invention.
FIG. 12 is a diagram of the mode number of the subsystem in an embodiment of the invention.
Fig. 13 shows an FE subsystem in a frequency acoustic radiation model of a housing structure of a bench according to an embodiment of the present invention.
FIG. 14 is a model diagram of mid-frequency acoustic radiation in a laboratory bench according to an embodiment of the present invention.
Fig. 15 is a graph of the result of predicting the mid-frequency sound radiation based on the locally optimized large-size shell structure in the embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings:
Using a three-dimensional geometric model of a shell structure, constructing a shell structure grid model through grid division, dividing subsystems based on the grid model, taking subsystems with 3-5 modal numbers as SEA subsystems, establishing the boundary coupling relation of the subsystems in the SEA subsystems and the fluid acoustic environment around the structure, then obtaining intermediate frequency model parameters of a high-energy contribution subsystem of the intermediate frequency acoustic radiation model SEA subsystem by adopting a transient method, the method comprises the steps of establishing a structural response equation of a medium-frequency sound radiation model of the shell structure by locally correcting medium-frequency model parameters of an SEA subsystem in a medium-frequency model, applying frequency as vibration excitation in a corresponding medium-frequency band, and solving the structural response equation of the medium-frequency sound radiation model of the shell structure to obtain a radiation sound field of the shell structure, so that medium-frequency sound radiation forecast of the shell structure is realized, more accurate acoustic response solution is obtained, and compared with the traditional medium-frequency sound radiation forecast method, the method reduces model parameter testing and improves the forecast accuracy of the radiation sound field.
In order to illustrate the effectiveness and superiority of the method for forecasting the frequency sound radiation in a large-size shell structure based on local optimization, a shell structure experiment table is utilized, and the method is shown in fig. 1.
The method specifically comprises the following steps:
Step 1), measuring geometric information of a shell structure, carrying out structural analysis on the geometric information, and establishing a geometric model of the shell structure according to an analysis result;
the geometric information comprises the geometric shape and the form and position size of each part in the structure; the structural analysis object comprises a bearing member, a vibration transmission member and a mass member;
step 2), carrying out grid division on a geometric model of the shell structure to obtain a shell structure grid model, carrying out subsystem division on the shell structure based on the shell structure grid model to obtain a plurality of subsystems, and taking the subsystem with the mode number of 3-5 as an SEA subsystem;
specifically, the subsystem division method adopts the division of the subsystems along the axial direction.
Step 3), establishing a boundary coupling relation of each subsystem in the SEA subsystem and a fluid acoustic environment around the structure, and then obtaining intermediate frequency model parameters of the high-energy contribution subsystem of the SEA subsystem by adopting a transient method;
the intermediate frequency model parameters include an internal loss factor, a total loss factor, and a coupling loss factor.
The acceleration response signal after the shell structure is knocked by the force hammer is a real function x (t), and the corresponding Hilbert is transformed into:
Figure RE-GDA0002694574270000071
in the formula: denotes convolution.
The inverse transformation is as follows:
Figure RE-GDA0002694574270000072
the analytic signal of the resulting real function is then:
Figure RE-GDA0002694574270000073
The complex expression of u (t) is:
u(t)＝A(t)ejθt
in the formula:
Figure RE-GDA0002694574270000074
in response to the envelope of signal x (t), the instantaneous phase being
Figure RE-GDA0002694574270000075
So any real function can be re-expressed as x (t) ═ a (t) cos θ (t), which will respondTaking logarithm of the envelope of the signal, obtaining an attenuation curve, wherein the absolute value of the slope of the curve is the structural damping lambda, dividing the structural damping lambda by the frequency to obtain a damping ratio zeta which is lambda/omega, and dividing the damping ratio 2 is the average loss factor eta which is zeta/2 in the frequency band of the tested structure.
Obtaining an internal loss factor of the high-energy contribution subsystem by adopting a transient attenuation method:
Figure RE-GDA0002694574270000076
Figure RE-GDA0002694574270000077
in the formula:Tn-an internal loss attenuation rate; etai-the internal loss factor of subsystem i; a. theTn(t1)—— t1Amplitude of the time decay Rate Curve, ATn(t2)——t2Amplitude of the time decay rate curve; omegac-the center frequency.
And 4) establishing a shell model structure response equation by locally correcting the intermediate frequency model parameters of the SEA subsystem in the intermediate frequency model, applying frequency as vibration excitation in a corresponding intermediate frequency range, and solving the response equation to obtain a shell structure radiation sound field, so that the intermediate frequency sound radiation forecast of the large-size shell structure can be realized.
Establishing a shell model structural response equation by locally correcting intermediate frequency model parameters of an SEA subsystem in the intermediate frequency model in the step 4):
determining the displacement response of the subsystem as:
Figure RE-GDA0002694574270000081
Figure RE-GDA0002694574270000082
In the formula: ddIs the dynamic stiffness matrix of the finite element model subsystem, SffFor applying exciting forces to finite-element sub-systemsThe cross-spectrum is obtained by the cross-spectrum,
Figure RE-GDA0002694574270000083
is the average dynamic stiffness matrix of subsystem i, EiTo the vibrational energy of subsystem i, niIs the modal density of subsystem i;
because each subsystem is power balanced, the power balance equation of the FE-SEA coupled system is as follows:
Figure RE-GDA0002694574270000084
in the formula: etaiIs the internal loss factor of subsystem i; piIs the input power of the sub-system i,
Figure RE-GDA0002694574270000085
for input power produced by forces exerted on a deterministic system, ηikThe vibration power flow is transferred from the coupling sub-system i to the coupling loss factor of the coupling sub-system k.
FIG. 2(a) is a schematic diagram of the division result of the shell structure grid model along the axial direction by using 1 single-curvature plate; FIG. 2(b) is a schematic diagram of the division result of the shell structure grid model along the axial direction by using 3 single-curvature plates; FIG. 2(c) is a schematic diagram of the division result of the shell structure grid model along the axial direction by using 5 single-curvature plates; FIG. 2(d) is a schematic diagram of the division result along the radial direction (circumferential direction) of the shell structure mesh model by using 2 single-curvature plates; fig. 2(e) is a schematic diagram of the division result along the radial direction (circumferential direction) of the shell structure grid model by using 4 single-curvature plates; then, forecasting is performed on the divided subsystems, and the result is shown in fig. 3, fig. 3 is a forecast result diagram of the method for dividing the cylindrical shell subsystem, where c2 represents the forecast result of the subsystem after being divided by using 2 single-curvature plates in the circumferential direction, c4 represents the forecast result of the subsystem after being divided by using 4 single-curvature plates in the circumferential direction, x1 represents the forecast result of the subsystem after being divided by using one single-curvature plate in the axial direction of the shell structure grid model, x3 represents the forecast result of the subsystem after being divided by using 3 single-curvature plates in the axial direction of the shell structure grid model, x5 represents the forecast result of the subsystem after being divided by using 5 single-curvature plates in the axial direction of the shell structure grid model, as can be seen from the result in fig. 3, when the number of the subsystem modes is sufficient, the finer forecasting effect of the subsystem division is better, and when the 2 subsystems are divided in the circumferential direction, the prediction result generates larger errors, and the errors are reduced after the circumferential division number is increased; when the subsystems are divided along the axial direction, the error and the variance of the forecast result are small; therefore, when the cylindrical shell divides the subsystem, the calculation precision of the result of dividing the subsystem along the axial direction is higher than that of dividing the subsystem along the circumferential direction; under the condition that the modal density is sufficient, the calculation accuracy can be improved by increasing the number of the subsystems divided along the circumferential direction.
Fig. 4(a) adopts 1 single-curvature plate dividing subsystem, (b) adopts 2 single-curvature plates dividing subsystem along the axial direction, (c) adopts 5 single-curvature plates dividing subsystem along the axial direction, (d) adopts 2 single-curvature plates dividing subsystem along the circumferential direction, and (e) adopts 4 single-curvature plates dividing subsystem along the circumferential direction.
As shown in fig. 4(a) -4 (e), the prediction test is performed after the conical shell is divided into subsystems by using single-curvature plates, and the test result is shown in fig. 5, where c2 represents the prediction result of the subsystems after the conical shell is divided along the circumferential direction of the conical shell structure grid model by using 2 single-curvature plates; c4 shows the forecasting result of the subsystem after 4 single-curvature plates are divided along the circumferential direction of the conical shell structure grid model; x1 represents the forecasting result of the subsystem after the single-curvature plate is adopted to divide along the axial direction of the conical shell structure grid model; x2 represents the prediction result of the subsystem after the subsystem is divided by adopting 2 single-curvature plates along the axial direction of the conical shell structure grid model, x5 represents the prediction result of the subsystem after the subsystem is divided by adopting 5 single-curvature plates along the axial direction of the conical shell structure grid model, and the results shown in fig. 5 show that the more detailed the subsystem is divided, the higher the prediction precision is; in fig. 5, when 2 subsystems are divided in the circumferential direction, the prediction result has a large error, and the error is reduced after the number of the circumferential divisions is increased; when the subsystems are divided in the axial direction, the error and variance of the prediction result are small. Therefore, when the conical shell structure divides the subsystems, the calculation accuracy of the result of dividing the subsystems along the axial direction is higher than that of dividing the subsystems along the circumferential direction, and under the condition that the modal density is sufficient, the calculation accuracy can be improved by increasing the number of the subsystems divided along the circumferential direction. c represents the circumferential direction and x represents the axial direction.
Fig. 6 is a schematic diagram of a model of the influence of different parameters on the sound radiation prediction result, where the model includes: and 4 SEA subsystems, namely a single-curvature plate is adopted to simulate a cylindrical subsystem, two flat plates simulate circular cover plates at two ends, and a cavity subsystem is arranged inside the two flat plates.
Fig. 7 is a comparison graph of the reported results of the changes of the loss factors in all the subsystems in the model of fig. 6, in which the standard value of the loss factor in the subsystem is 0.005, the error loss factors are respectively set to 0.004, 0.003 and 0.002, and the internal loss factors of all the subsystems are changed. Fig. 7 shows that when the internal loss factor of the subsystem in the model has an error within the order of magnitude, the sound pressure level prediction result has a larger error. Therefore, the internal loss factor has a large influence on the prediction result.
Fig. 8 is a comparison graph of the results of the changes of the coupling loss factors of all the subsystems in the model of fig. 6, in which the standard value of the coupling loss factor of the subsystem is 0.0005, the error coupling loss factors are respectively set to 0.0004, 0.0003 and 0.0002, and the internal loss factors of all the subsystems are changed. It can be known from fig. 8 that when the coupling loss factor of the subsystem in the model has an error within the order of magnitude, the error of the sound pressure level prediction result is small. Therefore, the coupling loss factor has little influence on the prediction result.
Fig. 9 is a comparison graph of reported results of changes in the loss factors of the individual subsystems in the model of fig. 6, where the standard internal loss factor of the subsystem is set to 0.005, the error internal loss factor is set to 0.001, and the internal loss factors of the individual subsystems are changed respectively. From fig. 9, it can be known that the error of the result is the largest when the subsystem with the error fails to measure the input end, and the error of the forecast result decreases as the error subsystem gradually moves away from the energy end. Therefore, the internal loss factor of the high-energy quantum system is the dominant factor for predicting the error of the result.
Fig. 10(a) shows a scheme for testing the internal dissipation factor of the base plate subsystem (subsystem 1), in which the base plate subsystem is suspended in a free state, a force hammer is used as an excitation source to excite a base plate in a pulse mode, a force sensor included in the force hammer acquires a transient excitation force signal, a PCB acceleration sensor is adhered to the surface of the base plate subsystem to acquire a vibration test point response acceleration signal of the subsystem, the force sensor and the acceleration sensor output voltage signals to a multi-channel data acquisition instrument COCO80, and data are analyzed according to the transient attenuation method internal dissipation factor test theory; fig. 10(b) shows the principle of the test of the loss factor test scheme in the subsystem of the base support plate (subsystem 2).
FIG. 11 is a diagram showing the result of the high-energy-contribution internal loss factor test, according to the transient excitation test process shown in FIG. 10, different excitation points are sequentially excited in sequence, and the average internal loss factor eta of each subsystem i is obtained by analyzing the attenuation rate of the corresponding acceleration response signal through multiple excitation of each excitation pointi. The result curve shows that the loss factor eta in each subsystem i can be summarizediMultiple distribution is at 10-3～10-4Order and general trend with center frequency fcThe increase is lower. The reason for this change is that: the internal loss factor measured in the anechoic chamber environment is the sum of acoustic radiation loss factor and structural loss factor, and the damping loss factor of the steel material is about 1.0 x 10-3Is an inherent property of the material; the internal loss factor of the sound radiation is controlled by the frequency and the radiation ratio, the radiation ratio is generally very small when the frequency is lower, the radiation ratio is firstly rapidly increased along with the increase of the frequency but the change rate is gradually stabilized to be about 1, and therefore, the loss factor approaches to the structural loss factor in a higher frequency band and is reduced along with the increase of the frequency in a middle frequency band.
Fig. 12 shows the mode number of the subsystem in the high frequency model, and some very fine structures in the structures are removed in the high frequency model based on the statistical and average concepts, and the fine structures are taken into account and established as the FE subsystem in the medium frequency model. And meanwhile, a subsystem with less than 3 modal numbers in the high-frequency model is established as an FE subsystem. Fig. 13 shows an FE subsystem in a frequency acoustic radiation model in a housing structure of a laboratory bench. Fig. 14 shows a middle frequency acoustic radiation model of a housing structure of a bench, where a subsystem with a mode number smaller than 5 in an SEA model is established as an FE subsystem, and the middle frequency model includes 11 FE subsystems, 33 single-curvature plate subsystems, 3 flat plate subsystems, and 10 acoustic cavity subsystems. Fig. 15 is a comparison graph of the prediction results of sound radiation of the shell structure, in which the maximum relative error of the prediction results after local model parameter correction is 8.43% compared with the maximum relative error of the sound pressure level of the experimental value, and the variance between the prediction results and the sound pressure level of the experimental value is small; the maximum relative error of the sound pressure level of the prediction result of the uncorrected model parameter is 12.67%, and the variance between the maximum relative error and the sound pressure level of the experimental value is large. Therefore, the method provided by the invention is proved to be capable of improving the forecasting precision of the radiation sound field while reducing the model parameter tests.

Claims (6)

1. A local optimization-based method for forecasting medium-frequency sound radiation in a large-size shell structure is characterized by comprising the following steps:
step 1), establishing a geometric model of the shell structure according to geometric information of the shell structure;
step 2), carrying out grid division on a geometric model of the shell structure to obtain a shell structure grid model, carrying out subsystem division on the shell structure based on the shell structure grid model to obtain a plurality of subsystems, and taking the subsystem with the mode number of 3-5 as an SEA subsystem;
step 3), establishing a boundary coupling relation of each subsystem and a fluid acoustic environment around the structure, and acquiring intermediate frequency model parameters of the high-energy contribution subsystem of the intermediate frequency acoustic radiation model SEA subsystem by adopting a transient method;
and 4, establishing a structural response equation of the intermediate frequency acoustic radiation model of the shell structure by locally correcting intermediate frequency model parameters of an SEA subsystem in the intermediate frequency model, applying frequency to be vibration excitation in a corresponding intermediate frequency range, and solving the structural response equation of the intermediate frequency acoustic radiation model of the shell structure to obtain a radiation sound field of the shell structure so as to realize the intermediate frequency acoustic radiation forecast of the large-size shell structure.
2. The method for forecasting frequency acoustic radiation in a large-size shell structure based on local optimization according to claim 1, characterized in that geometric information of the shell structure is measured and subjected to structural analysis, and a geometric model of the shell structure is established according to the analysis result.
3. The method for forecasting the frequency sound radiation in the large-size shell structure based on the local optimization as claimed in claim 2, wherein the geometrical information in step 1) includes the geometrical shapes and the form and position dimensions of each component in the structure, and the structural analysis objects include a bearing part, a vibration transmission part and a mass part.
4. The method for forecasting the frequency sound radiation in the large-size shell structure based on local optimization according to claim 1, characterized in that the subsystem division method adopts the axial division of the subsystems.
5. The method for forecasting the frequency sound radiation in the large-size shell structure based on local optimization according to claim 1, characterized in that the internal loss factor of the high-energy contribution subsystem is obtained by a transient attenuation method:
Figure FDA0002516048640000021
Figure FDA0002516048640000022
in the formula:Tn-an internal loss attenuation rate; etai-the internal loss factor of subsystem i; a. theTn(t1)——t1Amplitude of the time decay Rate Curve, ATn(t2)——t2Amplitude of the time decay rate curve; omegac-the center frequency.
6. The method for forecasting the intermediate frequency sound radiation of the large-size shell structure based on the local optimization in the claim 1 is characterized in that the intermediate frequency model parameters of the SEA subsystem in the intermediate frequency model are locally corrected in the step 4) to establish a shell model structure response equation:
Determining the displacement response of the subsystem as:
Figure FDA0002516048640000023
Figure FDA0002516048640000024
in the formula: ddIs the dynamic stiffness matrix of the finite element model subsystem, SffTo be a cross-spectrum of the excitation forces applied to the finite element sub-system,
Figure FDA0002516048640000025
is the average dynamic stiffness matrix of subsystem i, EiTo the vibrational energy of subsystem i, niIs the modal density of subsystem i;
because each subsystem is power balanced, the power balance equation of the FE-SEA coupled system is as follows:
Figure FDA0002516048640000026
in the formula: etaiIs the internal loss factor of subsystem i; piIs the input power of the sub-system i,
Figure FDA0002516048640000027
for input power produced by forces exerted on a deterministic system, ηikThe vibration power flow is transferred from the coupling sub-system i to the coupling loss factor of the coupling sub-system k.
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