1. A key parameter identification method for an aircraft modal test is characterized by comprising the following steps:

s1, setting the prediction accuracy and the sensitivity degree of the influence on the dynamic characteristics as classification double indexes, and classifying the structural parameters of the aircraft modal test based on the classification double indexes;

and step S2, performing a targeted modal test based on the classification result of the structure parameters in the step S1, and identifying key parameters of the modal test.

2. A method for identifying key parameters for a modal test of an aircraft according to claim 1, characterized in that: in step S1, the method for classifying the structural parameters by using the classification dual index includes:

setting a prediction accuracy threshold, comparing the prediction accuracy of the structural parameter with the prediction accuracy threshold, and performing secondary classification on the structural parameter into a high prediction accuracy class and a low prediction accuracy class based on the prediction accuracy threshold;

setting a sensitivity threshold, comparing the sensitivity of the structural parameters on the influence of the dynamic characteristics with the sensitivity threshold, and classifying the structural parameters into a category with high sensitivity on the influence of the dynamic characteristics and a category with low sensitivity on the influence of the dynamic characteristics based on the sensitivity threshold;

and performing secondary classification on the structural parameters based on the predictive accuracy threshold and performing secondary classification based on the sensitivity threshold to realize four-classification on the structural parameters to obtain an A class, a B class, a C class and a D class.

3. A method of identifying key parameters for a modal test of an aircraft according to claim 2, characterized in that: the four-classification method of the structural parameters comprises the following steps:

selecting a plurality of structural parameters as model training parameters, and comparing the prediction accuracy and the sensitivity degree of the model training parameters on the influence of dynamic characteristics with a prediction accuracy threshold and a sensitivity degree threshold respectively, wherein,

if the prediction accuracy of the model training parameter is greater than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is greater than the sensitivity degree threshold, the model training parameter is marked as a C type;

if the prediction accuracy of the model training parameter is greater than the prediction accuracy threshold and the sensitivity of the model training parameter on the influence of the dynamic characteristics is less than the sensitivity threshold, the model training parameter is calibrated to be in a D category;

if the prediction accuracy of the model training parameter is smaller than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is larger than the sensitivity degree threshold, the model training parameter is calibrated to be in the A category;

if the prediction accuracy of the model training parameter is smaller than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is smaller than the sensitivity degree threshold, the model training parameter is marked as a type B;

selecting a plurality of model training parameters of known classes as model training samples respectively, wherein the prediction accuracy and the sensitivity degree on dynamic characteristic influence of the model training parameters are used as sample characteristics of the model training samples, and the classes of the model training parameters are used as sample labels of the model training samples;

applying the model training samples to a Bayes classifier to perform four-classification training to obtain a parameter classification model, wherein the parameter classification model is used for automatically identifying the classification of the structural parameters, the sample characteristics of the model training samples are used as the input of the Bayes classifier, and the sample labels of the model training samples are used as the output of the Bayes classifier;

and inputting the prediction accuracy and the sensitivity degree of the structural parameters to be classified on the influence of the dynamic characteristics into a parameter classification model, and outputting the classification of the structural parameters to be classified.

4. A method of identifying key parameters for a modal test of an aircraft according to claim 3, characterized in that: the result of the four-classification of the structural parameters includes a class a, a class B, a class C, and a class D, wherein,

the A category is characterized in that the structural parameters have the attributes of low prediction accuracy and high sensitivity on the influence of dynamic characteristics;

the class B is characterized in that the structural parameters have the attributes of low prediction accuracy and low sensitivity on the influence of dynamic characteristics;

the C category is characterized in that the structural parameters have the attributes of high prediction accuracy and high sensitivity on the influence of dynamic characteristics;

the class D is characterized in that the structural parameters have the attributes of high prediction accuracy and low sensitivity to dynamic characteristic influence.

5. A key parameter identification method for aircraft modal testing according to claim 4, characterized in that: in step S2, the method for performing a targeted modal test based on the classification result of the structural parameter includes:

determining key parameters belonging to the A category in the structural parameters by using the modal test model correction method;

and establishing a deviation-considered structure dynamics model, carrying out a material object test on the key parameters belonging to the class A by using the structure dynamics model, and realizing the conversion of the key parameters from the class A to the class C, so that the prediction accuracy of the key parameters is improved from low to high, and the dynamic characteristic prediction result output by the structure dynamics model is in a prediction deviation range.

6. A method for identifying key parameters for a modal test of an aircraft according to claim 5, characterized in that: the method for determining the key parameters by using the modal test model correction method comprises the following steps:

based on the deviation of the structural parameters, establishing a characteristic equation, wherein the characteristic equation is as follows:

；

in the formula (I), the compound is shown in the specification,in the form of a structural stiffness matrix,for the purpose of the matrix increment(s),for quality matrix, matrix incrementDelta matrix deltaAndin order to ensure the balance of the equations,is a mode-shape matrix and is characterized in that,is a modal mass array;

the incremental effects are integrated to obtain a localized matrix L, and the matrix L is expressed by the formula:

；

in the formula, mode shape matrixThe mode shape corresponding to the non-deviation state is included;in the form of a structural stiffness matrix,for the purpose of the matrix increment(s),for quality matrix, matrix incrementDelta matrix deltaAndin order to ensure the balance of the equations,is a mode-shape matrix and is characterized in that,is a modal mass array;

selecting a main modeling error by checking a localized vector q, wherein the modeling error is expressed by the formula:

；

in the formula (I), the compound is shown in the specification,the gas weight number reflects the degree of consistency between the h-th order modal test data and the analysis data, L is a localized matrix,is the first in the L matrixiGo to the firsthThe value of the column, N is the total number of matrices,is as followsiN is the total number of modeling errors;

setting an error threshold above whichAnd (4) the corresponding structural parameters reuse the structural dynamic model to carry out deviation evaluation on the behavior characteristic prediction result.

7. The method for identifying key parameters for the modal testing of the aircraft according to claim 6, wherein: the method for carrying out deviation assessment on the predicted result of the action characteristic by reusing the structure dynamics model comprises the following steps:

if the predicted result of the dynamic characteristic is within the range of the predicted deviation, the error threshold value is higherDetermining the corresponding structural parameters as key parameters belonging to the category A;

if the predicted result of the dynamic characteristic is not within the range of the predicted deviation, the error threshold is decreased and increased to be higher than the error thresholdThe number of corresponding structural parameters.

8. The method for identifying key parameters for the modal testing of the aircraft according to claim 7, wherein: the material object test is used for improving the prediction accuracy of the key parameters with high sensitivity to the dynamic characteristics and low prediction accuracy so as to improve the dynamic characteristic prediction accuracy of the structural dynamic model.

9. The method as claimed in claim 8, wherein the key parameters have the same attributes as those of the parameters in the category a, the key parameters are performance of key structural characteristics of the aircraft and important points of interest of the modal test of the aircraft, and the accuracy of the dynamic characteristic prediction result output by the structural dynamics model after the category a is changed to the category C of the key parameters is improved, so as to ensure that the modal test performed by using the key parameters can more accurately describe the dynamic characteristics of the aircraft.

10. A method according to claim 9, wherein the structural parameters are the representation of the structural characteristics of the aircraft and the parameters expressed directly in the structural dynamics model, and the modal test concerns are transformed to the use of the structural characteristics to evaluate the dynamic characteristics of the aircraft.

Background

In the process of developing aircrafts such as a carrier rocket and the like, a modal test is the most direct and reliable method for obtaining the dynamic characteristics of the aircrafts, and the test is arranged in the process of developing aircrafts except for aircrafts with strong inheritance. The traditional modal test directly measures the dynamic characteristic parameters of the whole arrow, including the array type, the frequency, the array type slope and the like, and corrects the structural dynamic model according to the overall parameters, so that the dynamic characteristic shown by the structural dynamic model is consistent with the actual test result. The structural dynamic model can show correct dynamic characteristics and does not represent that the structural characteristics such as rigidity, mass and the like are consistent with the reality, which is allowed in engineering development. However, once the structure is locally adjusted, since it is difficult to judge the accuracy of the structural parameters of the dynamic model, it is often difficult to obtain the dynamic characteristics of a new state by replacing the local model, and the modal test still needs to be performed again.

Disclosure of Invention

The invention aims to provide a key parameter identification method for an aircraft modal test, and the key parameter identification method is used for solving the technical problems that once a structure is locally adjusted, the structural parameter accuracy of a dynamic model is difficult to judge, the dynamic characteristic of a new state is often difficult to obtain through the replacement of a local model, and the modal test needs to be carried out again in the prior art.

In order to solve the technical problems, the invention specifically provides the following technical scheme:

a key parameter identification method for an aircraft modal test comprises the following steps:

s1, setting the prediction accuracy and the sensitivity degree of the influence on the dynamic characteristics as classification double indexes, and classifying the structural parameters of the aircraft modal test based on the classification double indexes;

and step S2, performing a targeted modal test based on the classification result of the structure parameters in the step S1, and identifying key parameters of the modal test.

As a preferable aspect of the present invention, in step S1, the method for classifying a set structural parameter by a classification dual index includes:

setting a prediction accuracy threshold, comparing the prediction accuracy of the structural parameter with the prediction accuracy threshold, and performing secondary classification on the structural parameter into a high prediction accuracy class and a low prediction accuracy class based on the prediction accuracy threshold;

setting a sensitivity threshold, comparing the sensitivity of the structural parameters on the influence of the dynamic characteristics with the sensitivity threshold, and classifying the structural parameters into a category with high sensitivity on the influence of the dynamic characteristics and a category with low sensitivity on the influence of the dynamic characteristics based on the sensitivity threshold;

and performing secondary classification on the structural parameters based on the predictive accuracy threshold and performing secondary classification based on the sensitivity threshold to realize four-classification on the structural parameters to obtain an A class, a B class, a C class and a D class.

As a preferred aspect of the present invention, the four-classification method for the structural parameters includes:

selecting a plurality of structural parameters as model training parameters, and comparing the prediction accuracy and the sensitivity degree of the model training parameters on the influence of dynamic characteristics with a prediction accuracy threshold and a sensitivity degree threshold respectively, wherein,

if the prediction accuracy of the model training parameter is greater than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is greater than the sensitivity degree threshold, the model training parameter is marked as a C type;

if the prediction accuracy of the model training parameter is greater than the prediction accuracy threshold and the sensitivity of the model training parameter on the influence of the dynamic characteristics is less than the sensitivity threshold, the model training parameter is calibrated to be in a D category;

if the prediction accuracy of the model training parameter is smaller than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is larger than the sensitivity degree threshold, the model training parameter is calibrated to be in the A category;

if the prediction accuracy of the model training parameter is smaller than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is smaller than the sensitivity degree threshold, the model training parameter is marked as a type B;

selecting a plurality of model training parameters of known classes as model training samples respectively, wherein the prediction accuracy and the sensitivity degree on dynamic characteristic influence of the model training parameters are used as sample characteristics of the model training samples, and the classes of the model training parameters are used as sample labels of the model training samples;

applying the model training samples to a Bayes classifier to perform four-classification training to obtain a parameter classification model, wherein the parameter classification model is used for automatically identifying the classification of the structural parameters, the sample characteristics of the model training samples are used as the input of the Bayes classifier, and the sample labels of the model training samples are used as the output of the Bayes classifier;

and inputting the prediction accuracy and the sensitivity degree of the structural parameters to be classified on the influence of the dynamic characteristics into a parameter classification model, and outputting the classification of the structural parameters to be classified.

As a preferred aspect of the present invention, the result of the four classifications of the structural parameters includes a class a, a class B, a class C, and a class D, wherein,

the A category is characterized in that the structural parameters have the attributes of low prediction accuracy and high sensitivity on the influence of dynamic characteristics;

the class B is characterized in that the structural parameters have the attributes of low prediction accuracy and low sensitivity on the influence of dynamic characteristics;

the C category is characterized in that the structural parameters have the attributes of high prediction accuracy and high sensitivity on the influence of dynamic characteristics;

the class D is characterized in that the structural parameters have the attributes of high prediction accuracy and low sensitivity to dynamic characteristic influence.

As a preferred embodiment of the present invention, in step S2, the method for performing a targeted modal test based on the classification result of the structural parameter includes:

determining key parameters belonging to the A category in the structural parameters by using the modal test model correction method;

and establishing a deviation-considered structure dynamics model, carrying out a material object test on the key parameters belonging to the class A by using the structure dynamics model, and realizing the conversion of the key parameters from the class A to the class C, so that the prediction accuracy of the key parameters is improved from low to high, and the dynamic characteristic prediction result output by the structure dynamics model is in a prediction deviation range.

As a preferred embodiment of the present invention, the method for determining the key parameter by using the modal test model modification method includes:

based on the deviation of the structural parameters, establishing a characteristic equation, wherein the characteristic equation is as follows:

；

in the formula (I), the compound is shown in the specification,in the form of a structural stiffness matrix,for the purpose of the matrix increment(s),for quality matrix, matrix incrementDelta matrix deltaAndin order to ensure the balance of the equations,is a mode-shape matrix and is characterized in that,is a modal mass array;

the incremental effects are integrated to obtain a localized matrix L, and the matrix L is expressed by the formula:

；

in the formula, mode shape matrixThe mode shape corresponding to the non-deviation state is included;in the form of a structural stiffness matrix,for the purpose of the matrix increment(s),for quality matrix, matrix incrementDelta matrix deltaAndin order to ensure the balance of the equations,is a mode-shape matrix and is characterized in that,is a modal mass array;

selecting a main modeling error by checking a localized vector q, wherein the modeling error is expressed by the formula:

；

in the formula (I), the compound is shown in the specification,the gas weight number reflects the degree of consistency between h-order modal test data and analysis data, and L is localThe matrix of the partial matrix is formed,is the first in the L matrixiGo to the firsthThe value of the column, N is the total number of matrices,is as followsiN is the total number of modeling errors;

setting an error threshold above whichAnd (4) the corresponding structural parameters reuse the structural dynamic model to carry out deviation evaluation on the behavior characteristic prediction result.

As a preferred aspect of the present invention, the method for evaluating the deviation of the behavior prediction result by reusing the structural dynamics model includes:

if the predicted result of the dynamic characteristic is within the range of the predicted deviation, the error threshold value is higherDetermining the corresponding structural parameters as key parameters belonging to the category A;

if the predicted result of the dynamic characteristic is not within the range of the predicted deviation, the error threshold is decreased and increased to be higher than the error thresholdThe number of corresponding structural parameters.

As a preferable scheme of the invention, the physical test is used for improving the prediction accuracy of the key parameters with high sensitivity to the dynamic characteristics and low prediction accuracy so as to improve the dynamic characteristic prediction accuracy of the structural dynamic model.

As a preferred scheme of the present invention, the key parameter has an attribute that is the same as the parameter in the category a, the key parameter is an expression in the key structural characteristic of the aircraft and a key focus of the aircraft modal test, and the precision of the dynamic characteristic prediction result output by the structural dynamics model after the key parameter is changed from the category a to the category C is improved, so as to ensure that the dynamic characteristic of the aircraft can be more accurately described by the modal test performed using the key parameter.

In a preferred embodiment of the present invention, the structural parameters are the expression of the structural characteristics of the aircraft, and the parameters are directly expressed in a structural dynamics model, and the modal test concerns are converted to the evaluation of the dynamic characteristics of the aircraft by using the structural characteristics.

Compared with the prior art, the invention has the following beneficial effects:

the invention carries out structural parameter four classification by utilizing classification double indexes set by prediction accuracy and sensitivity degree of influence on dynamic characteristics, realizes fine design of the modal test by identifying key parameters in the structural parameters, turns the attention point of the modal test from the integral dynamic characteristics to the local characteristics of the structure, can quickly and accurately master the parameters of a structure dynamic model when the structure is locally adjusted, can obtain the dynamic characteristics of a new state by replacing the local model, does not need to carry out the modal test again, and thus, expands the flexibility of the modal test.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.

FIG. 1 is a flowchart of a key parameter identification method for code according to an embodiment of the present invention;

fig. 2 is a diagram illustrating a result of four classes of structural parameters of codes according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As shown in fig. 1, the present invention provides a method for identifying key parameters for a modal test of an aircraft, comprising the following steps:

parameters such as mass distribution condition, section diameter, skin thickness, section length, butt joint face rigidity and the like of the aerospace craft have different prediction precision on the dynamic characteristics of the whole rocket, and the influence of deviation on results is greatly different. These parameters are collectively referred to as structural parameters. Structural parameters are also parameters that are directly expressed in the structural dynamics model. The structural parameters are very different from the dynamic characteristic parameters in nature: the structural parameters are the expression of the local characteristics of the structure, and the quantity is large; the dynamic characteristic parameters are the expression of the overall dynamic characteristic of the structure, and the quantity is limited. The structural parameters are determined by the dynamic characteristic parameters, a small quantity of parameters are adopted to estimate a large quantity of parameters, the reliability is not high, the estimation of the dynamic characteristic parameters by the structural parameters has influence, but theoretically, the estimation is more reliable, so that the analysis of the flight chess mode test is mainly adjusted to the structural parameters, and the dynamic characteristic of the aircraft can be accurately described by the aircraft mode test.

S1, setting the prediction accuracy and the sensitivity degree of the influence on the dynamic characteristics as classification double indexes, and classifying the structural parameters of the aircraft modal test based on the classification double indexes;

in step S1, the method for classifying the structural parameter with the dual index setting includes:

setting a prediction accuracy threshold, comparing the prediction accuracy of the structural parameter with the prediction accuracy threshold, and performing secondary classification on the structural parameter into a high prediction accuracy class and a low prediction accuracy class based on the prediction accuracy threshold;

setting a sensitivity threshold, comparing the prediction accuracy of the structural parameters with the sensitivity threshold, and classifying the structural parameters into a category with high sensitivity on the influence of the dynamic characteristics and a category with low sensitivity on the influence of the dynamic characteristics based on the sensitivity threshold;

and performing secondary classification on the structural parameters based on the predictive accuracy threshold and performing secondary classification based on the sensitivity threshold to realize four-classification on the structural parameters to obtain an A class, a B class, a C class and a D class.

The four-classification method of the structural parameters comprises the following steps:

selecting a plurality of structural parameters as model training parameters, and comparing the prediction accuracy and the sensitivity degree of the model training parameters on the influence of dynamic characteristics with a prediction accuracy threshold and a sensitivity degree threshold respectively, wherein,

if the prediction accuracy of the model training parameter is greater than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is greater than the sensitivity degree threshold, the model training parameter is marked as a C type;

if the prediction accuracy of the model training parameter is greater than the prediction accuracy threshold and the sensitivity of the model training parameter on the influence of the dynamic characteristics is less than the sensitivity threshold, the model training parameter is calibrated to be in a D category;

if the prediction accuracy of the model training parameter is smaller than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is larger than the sensitivity degree threshold, the model training parameter is calibrated to be in the A category;

if the prediction accuracy of the model training parameter is smaller than the prediction accuracy threshold and the sensitivity degree of the model training parameter on the influence of the dynamic characteristics is smaller than the sensitivity degree threshold, the model training parameter is marked as a type B;

selecting a plurality of model training parameters of known classes as model training samples respectively, wherein the prediction accuracy and the sensitivity degree on dynamic characteristic influence of the model training parameters are used as sample characteristics of the model training samples, and the classes of the model training parameters are used as sample labels of the model training samples;

applying the model training samples to a Bayes classifier to perform four-classification training to obtain a parameter classification model, wherein the parameter classification model is used for automatically identifying the classification of the structural parameters, the sample characteristics of the model training samples are used as the input of the Bayes classifier, and the sample labels of the model training samples are used as the output of the Bayes classifier;

and inputting the prediction accuracy and the sensitivity degree of the structural parameters to be classified on the influence of the dynamic characteristics into a parameter classification model, and outputting the classification of the structural parameters to be classified.

The method can convert artificial threshold classification of the structural parameters into automatic model classification, improves the classification efficiency and precision, and has more obvious advantages especially under the condition of large quantity of the structural parameters needing classification.

As shown in fig. 2, the result of the four-classification of the structural parameters includes a class a, a class B, a class C, and a class D, wherein,

the A category is characterized in that the structural parameters have the attributes of low prediction accuracy and high sensitivity on the influence of dynamic characteristics;

the class B is characterized in that the structural parameters have the attributes of low prediction accuracy and low sensitivity on the influence of dynamic characteristics;

the class C is characterized in that the structural parameters have the attributes of high prediction accuracy and high sensitivity on the influence of dynamic characteristics;

the class D is characterized in that the structural parameters have the properties of high prediction accuracy and low sensitivity to dynamic characteristic influence.

In particular, typical parameters in class D are stiffness parameters of a relatively thick-walled, structurally simple section, such as the stiffness characteristics of a solid engine thrust chamber. The rigidity of the vibration damper is large, the influence on dynamic characteristics is not large, the vibration damper basically conforms to the assumption of a flat section in the vibration process, and the actually expressed rigidity is very close to a theoretical solution.

Typical class B parameters have a large number of segment abutment face stiffnesses for abutment bolt connections. The section has high butt joint rigidity, the structural vibration has small response at the position, but the rigidity at the position is very difficult to predict considering bolt pretightening force, a complex local structure formed by end frames, the contact condition of butt joint surfaces of the end frames and the like.

Parameters of class C are for example the mass of the structure and geometrical parameters like length, diameter, etc. which are very sensitive to dynamic influences but can be obtained or predicted very directly.

The parameters of the type A include bending rigidity of a thin skin section, rigidity of a section butt joint surface of a point connection and the like, and the parameters are difficult to obtain and have large influence on a dynamic characteristic result.

And step S2, performing targeted modal test based on the classification result of the structure parameters in the step S1, and identifying key parameters of the modal test.

The modal test needs to obtain a dynamic characteristic prediction result and ensures that the dynamic characteristic prediction result is within a prediction deviation range, and the purpose of the semi-physical modal test is also the same. After the four classification of the structural parameters is completed, the structural parameters can be classified into A, B, C and D, namely, a structural dynamic model considering the deviation can be established, the structural parameters falling in the A classification are determined as key parameters to be considered to carry out a material object test, and the key parameters are transferred from the A area to the C area, so that the deviation of the dynamic characteristic prediction result of the final structural dynamic model can meet the requirement.

Step S2, the method for performing a targeted modal test based on the classification result of the structural parameter includes:

determining key parameters belonging to the A category in the structural parameters by using a modal test model correction method;

and establishing a structural dynamics model considering the deviation, performing a material object test on the key parameters belonging to the category A by using the structural dynamics model, and realizing the conversion of the key parameters from the category A to the category C, so that the prediction accuracy of the key parameters is improved from low to high, and the dynamic characteristic prediction result output by the structural dynamics model is in a prediction deviation range.

The purpose of the material object test is to improve the prediction accuracy of key parameters which have high sensitivity to the influence of dynamic characteristics and low prediction accuracy, so as to improve the dynamic characteristic prediction accuracy of the structural dynamic model. The selection of key parameters within the structural parameters requires, to a large extent, a profound knowledge of the physical structure, the key parameters selected should be physically questionable and related to the structural dynamics model characteristics, and in fact, there are usually many correction parameters available for selection for the same suspicious point. In general, the structural parameters should be selected to be highly sensitive to dynamic characteristics, but not vice versa. That is, the dynamic behavior is sensitive to a certain structural parameter and is not a sufficient condition for selecting this parameter as a critical parameter for the physical experiment. In summary, when selecting the key parameters of the physical test, the structural parameters corresponding to the uncertainties identified in the structural dynamics model should be selected, and the structural parameters have a high sensitivity to the influence of the dynamic characteristics.

The method for determining the key parameters by using the modal test model correction method comprises the following steps:

the modal test model correction method, the selectable methods of which include a characteristic value equation balance method, a substructure energy function identification method, a most subspace method, a sensitivity sampling method and the like are all within the protection scope of the invention.

Based on the deviation of the structural parameters, establishing a characteristic equation, wherein the characteristic equation is as follows:

；

in the formula (I), the compound is shown in the specification,in the form of a structural stiffness matrix,for the purpose of the matrix increment(s),for quality matrix, matrix incrementDelta matrix deltaAndin order to ensure the balance of the equations,is a mode-shape matrix and is characterized in that,is a modal mass array;

the incremental effects are integrated to obtain a localized matrix L, and the matrix L is expressed by the formula:

；

in the formula, mode shape matrixThe mode shape corresponding to the non-deviation state is included;in the form of a structural stiffness matrix,for the purpose of the matrix increment(s),for quality matrix, matrix incrementDelta matrix deltaAndin order to ensure the balance of the equations,is a mode-shape matrix and is characterized in that,is a modal mass array;

selecting a main modeling error by checking a localized vector q, wherein the modeling error is expressed by the formula:

；

in the formula (I), the compound is shown in the specification,the gas weight number reflects the degree of consistency between the h-th order modal test data and the analysis data, L is a localized matrix,is the first in the L matrixiGo to the firsthThe value of the column, N is the total number of matrices,is as followsiN is the total number of modeling errors;

setting an error threshold above whichAnd (4) the corresponding structural parameters reuse the structural dynamic model to carry out deviation evaluation on the behavior characteristic prediction result.

The method for carrying out deviation assessment of the behavior characteristic prediction result by reusing the structure dynamics model comprises the following steps:

if the predicted result of the dynamic characteristic is within the range of the predicted deviation, the error threshold value is higherDetermining the corresponding structural parameters as key parameters belonging to the category A;

if the predicted result of the dynamic characteristic is not within the range of the predicted deviation, the error threshold is decreased and increased to be higher than the error thresholdThe number of corresponding structural parameters.

The material object test is used for improving the prediction accuracy of the key parameters with high sensitivity to the dynamic characteristics and low prediction accuracy so as to improve the dynamic characteristic prediction accuracy of the structural dynamic model.

Height ofValue-related structural parameters are subjected to a physical test, so that the dynamic characteristic prediction precision of the structural dynamic model can be effectively improved, and therefore an error threshold value can be set for setting the dynamic characteristic higher than the error threshold valueThe value is defined as highValue so that high can be obtainedThe structural parameters corresponding to the values reuse the structural dynamics model to carry out deviation evaluation of the action characteristic prediction result, and the height is determinedWhether the structural parameter corresponding to the value can be used as the key parameter, if highThe structural parameter corresponding to the value can not be taken as a key parameter, and the error threshold value can be relatively reduced to be higher than the error threshold valueThe number of values increases, i.e. is highThe number of values increases, and is correspondingly highAnd increasing the quantity of the structural parameters corresponding to the values, and then, carrying out deviation evaluation on the action characteristic prediction result by reusing the structural dynamics model until the key parameters are determined.

The key parameters have the same attributes as parameters in the category A, the key parameters are expressions in key structural characteristics of the aircraft and key focus points of the aircraft modal test, and the accuracy of dynamic characteristic prediction results output by the structural dynamics model after the key parameters are changed from the category A to the category C is improved, so that the dynamic characteristics of the aircraft can be more accurately described by the modal test performed by using the key parameters.

The structural parameters are the expression of the structural characteristics of the aircraft and the parameters directly expressed in the structural dynamics model, and the modal test attention points are converted into the structural characteristics for evaluating the dynamic characteristics of the aircraft.

The invention carries out structural parameter four classification by utilizing classification double indexes set by prediction accuracy and sensitivity degree of influence on dynamic characteristics, realizes fine design of the modal test by identifying key parameters in the structural parameters, turns the attention point of the modal test from the integral dynamic characteristics to the local characteristics of the structure, can quickly and accurately master the parameters of a structure dynamic model when the structure is locally adjusted, can obtain the dynamic characteristics of a new state by replacing the local model, does not need to carry out the modal test again, and thus, expands the flexibility of the modal test.

The above embodiments are only exemplary embodiments of the present application, and are not intended to limit the present application, and the protection scope of the present application is defined by the claims. Various modifications and equivalents may be made by those skilled in the art within the spirit and scope of the present application and such modifications and equivalents should also be considered to be within the scope of the present application.