WO2024063053A1 - Information processing device, system, program, and presentation method - Google Patents

Abstract

The present invention provides a new technique for easily determining the elastic constant of an object having a complex shape.　This information processing device comprises: an acquisition unit that acquires measurement results obtained by measuring the resonance frequency of an object and a vibrational mode at the resonance frequency; and a determination unit that presents an elastic constant on the basis of a plurality of inputted elasticity values and the measurement results. The determination unit creates, by using the plurality of inputted elasticity values, a first contour diagram of the object in each estimated vibrational mode at an estimated resonance frequency, creates a second contour diagram in each measured vibrational mode at a measured resonance frequency which corresponds to the estimated resonance frequency and which is based on the measurement results, updates the inputted elasticity values by using a genetic algorithm on the basis of the similarity degree between the first contour diagram and the second contour diagram, and presents the elastic constant on the basis of inputted elasticity values that satisfy setting conditions.

Description

Information processing device, system, program, presentation method

The present invention relates to an information processing device and the like.

There is a social need to identify the elastic constants of objects in the fields of material selection and material processing.
For objects with simple linear shapes, such as rod-shaped materials, elastic constants can be obtained by using a tensile test or the like.
On the other hand, in order to measure a complex-shaped object, it is necessary to mold the object into a shape that conforms to a standard. Furthermore, in the case of objects with mechanical anisotropy, it is necessary to measure tensile loads and shear loads from various directions using several different test methods, making it difficult to determine the elastic constants.

Conventionally, methods for determining the elastic constants of such objects include ultrasonic resonance spectroscopy (hereinafter sometimes referred to as the "RUS method"), which vibrates a solid body and calculates the resonance mode of the resonant frequency. A method is known in which an elastic constant is determined by inverse analysis using a numerical analysis method such as the finite element method (FEM) (see, for example, Patent Document 1 and Non-Patent Documents 1 to 4).
However, the above method has room for improvement in terms of improving accuracy and the like.

JP2003-207390 Publication

The purpose of the present invention is to propose a new method for easily determining (presenting) the elastic constants of objects with complex shapes.

An information processing device, a system, a program, and a presentation method using the information processing device according to the present invention include an acquisition unit that acquires measurement results of measuring a resonant frequency of an object and a vibration mode at the resonant frequency, and a plurality of input elastic and a determining unit that presents an elastic constant based on the measured value and the measurement result, the determining unit using the plurality of input elastic values to determine the first contour in each estimated vibration mode at the estimated resonant frequency of the object. A second contour diagram is created for each measured vibration mode at a measured resonance frequency corresponding to the estimated resonance frequency based on the measurement results, and based on the degree of similarity between the first contour diagram and the second contour diagram. The input elasticity value is updated by a genetic algorithm, and the elasticity constant is presented based on the input elasticity value that satisfies a set condition.

According to the present invention, it is possible to more easily determine the elastic constant even for objects for which determining the elastic constant is difficult or requires complicated measurement using conventional methods.

FIG. 1 is a block diagram showing an example of the configuration of an information processing system. 5 is a flowchart showing an example of the flow of information processing. FIG. 7 is a diagram showing a specific example of a measured vibration mode of a sample and an estimated vibration mode of a sample. FIG. 7 is a diagram showing a specific example of processing results in a vibration mode comparison section. FIG. 3 is a diagram illustrating an example of a comparison result between an elastic constant output by an information processing device and an elastic constant obtained by another method. The figure which shows the specific example of the projection of the measured and estimated vibration mode to the orthogonal plane. 7 is a flowchart showing an example of the flow of information processing in a modified example.

EMBODIMENT OF THE INVENTION Hereinafter, an example of the form for implementing this invention is demonstrated with reference to drawings.
In addition, in the description of the drawings, the same elements may be denoted by the same reference numerals, and redundant description may be omitted.
Further, the components described in this embodiment are merely examples, and the scope of the present invention is not intended to be limited thereto.

[Embodiment]
An example of an embodiment for realizing the information processing technology of the present invention will be described below.

FIG. 1 is a diagram illustrating an example of a system configuration of an information processing system 1 according to an aspect of the present embodiment.
In the information processing system 1, for example, an information processing device 100, a sample vibration mode measuring device 200, and a sample shape measuring device 300 are connected.
The information processing system 1 may also be called a material analysis system or an elastic constant determination system.

In the information processing system 1 and the information processing apparatus 100 according to the present invention, the following items can be analyzed without restriction as objects to be analyzed (measured), for example.
・Material type (e.g. metal, ceramic, composite material, etc.)
・Material form (e.g. three-dimensional shape of material)
・Measurement environment (e.g. measurement temperature environment)
That is, the information processing apparatus 100 can calculate the elastic constant of the object without being limited to the three-dimensional shape of the object.

The sample vibration mode measuring device 200 has a function of measuring resonance frequencies of an object whose elastic constants are to be determined and vibration modes (resonance modes) corresponding to the respective resonance frequencies.
The sample vibration mode measuring device 200 may measure the vibration mode and resonance frequency of the object by, for example, a laser Doppler method.

The sample shape measuring device 300 has a function of measuring the three-dimensional shape of a target object.
The sample shape measuring device 300 measures the shape (size and its shape) of a target object by, for example, contact-type 3D scanning that acquires a three-dimensional shape by contacting a probe, or non-contact 3D scanning that uses LiDAR (Light Detection And Ranging) or the like. It may also be possible to obtain the

For example, the information processing device 100 determines the target object based on the vibration mode and resonance frequency of the object measured by the sample vibration mode measurement device 200 and the three-dimensional shape of the object measured by the sample shape measurement device 300. It has the function of determining the elastic constant of .
The information processing device 100 may also be referred to as a material analysis device or an elastic constant presentation device.

The information processing device 100 may include a measurement result acquisition unit 110, an elastic constant determination unit 120, and a processing program of the present invention stored in a storage unit (not shown).
The elastic constant determining unit 120 includes an elastic parameter setting unit 130 , an analyzing unit 140 , a vibration mode comparing unit 150 , and an elastic parameter updating unit 160 .
These can be, for example, functional units (functional blocks) possessed by a processing unit (processing unit) or control unit (control device) of the information processing device 100 (not shown), and are configured with processing circuits such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), and an FPGA (Field Programmable Gate Array).

For example, when the measurement result acquisition unit 110 receives as input the resonant frequency and vibration mode of the object measured by the sample vibration mode measurement device 200, the measurement result acquisition unit 110 transmits the resonant frequency and vibration mode of the object to the elastic constant determination unit 120. It has a function to output.
Hereinafter, the resonance frequency of the object acquired by the measurement result acquisition unit 110 will be referred to as a "measurement resonance frequency", and the resonance mode will be referred to as a "measurement vibration mode".

Note that the measurement result acquisition section 110 has a function of, for example, receiving as input the three-dimensional shape data of the object measured by the sample shape measuring device 200, and outputting the three-dimensional shape data of the object to the elastic constant determining section 120. It may be made to have. Further, the three-dimensional shape data of the target object may be obtained by receiving CAD data of the target object from a CAD data storage server (not shown), for example, without depending on the measurement result of the sample shape measuring device 300.

The elasticity parameter setting unit 130 has a function of setting initial values of elasticity parameters used in the mathematical analysis in the analysis unit 140, for example.

The analysis unit 140 uses, for example, the finite element method, based on the three-dimensional shape data and the elastic parameters set in the elastic parameter setting unit 130, to determine whether the three-dimensional object has elastic parameters set. It has a function to calculate the resonant frequency and vibration mode when assuming that. The analysis section 140 may also be referred to as a mathematical analysis section 140.
In the following, the resonant frequency of the object model calculated by mathematical analysis will be referred to as "estimated resonant frequency" and the resonant mode will be referred to as "estimated vibration mode".

The vibration mode comparison unit 150 compares, for example, the measured vibration mode at each measurement resonance frequency acquired by the measurement result acquisition unit 110 and the estimated vibration at each resonance frequency corresponding to each measurement resonance frequency calculated by the analysis unit 140. It has a function of comparing the estimated vibration mode and the measured vibration mode to determine whether or not the estimated vibration mode is far different from the measured vibration mode.

The elasticity parameter updating unit 160 has a function of determining whether or not to update the elasticity parameter, for example, based on the determination result in the vibration mode comparison unit 150. Further, the elastic parameter updating unit 160 has a function of updating the elastic parameter using, for example, an evaluation function based on the estimated resonance frequency and the measured resonance frequency, when it is determined that the elastic parameter should be updated.

Furthermore, the elasticity parameter updating unit 160 has a function of outputting the elasticity parameter as an elasticity constant (determination result), for example, when the evaluation function satisfies a setting condition described later.

Here, the "output" of the elastic constant (determination result) includes not only the display of the judgment result on the own device (display output), but also the output of the judgment result on the own device to other functional parts (internal output). ), output (external output), and transmission (external transmission) of the determination result to a device other than the own device (external device).

[Information processing procedure]
FIG. 2 is a flowchart showing an example of the procedure of information processing in this embodiment.
The processing in the flowchart of FIG. 2 is realized, for example, by the processing unit of the information processing device 100 reading out a program code stored in a storage unit (not shown) into a RAM (not shown) or the like and executing it.

Each symbol S in the flowchart of FIG. 2 means a step.
Note that the flowchart described below merely shows an example of the procedure of information processing in this embodiment, and other steps may be added or some steps may be deleted. Further, some of the steps in the flowchart may be replaced and executed.

First, the measurement result acquisition unit 110 executes a sample vibration mode measurement result acquisition process (S110).
In the sample vibration mode measurement result acquisition process, the measurement result acquisition unit 110 acquires, for example, the measured resonant frequencies of the object and the measured vibration modes corresponding to each measured resonant frequency from the sample vibration mode measurement device 200, and stores them in a memory unit such as a RAM (not shown).

Furthermore, the elastic constant determination unit 120 executes a sample shape acquisition process using the sample shape measurement device 300 (S120).
In the sample shape acquisition process, the elastic constant determination unit 120 acquires three-dimensional shape data of the object from the sample shape measurement device 300 and outputs it as an input value for the analysis unit 140 .
At this time, the sample shape measuring device 300 captures images of the target object from multiple directions to obtain the shape of the target object. Although it is preferable to capture images from multiple directions, it is possible to measure the elastic constant even when capturing images from one direction. As will be described later, the acquired data may be projected images viewed from each direction. When capturing projected images, it is preferable to capture the images from a direction in which the target object has a characteristic shape such as a flat surface, as this makes analysis easier.

In addition, in the sample shape acquisition process, when the elastic constant determination unit 120 receives CAD data of the target object from a CAD data storage server (not shown), it may convert the data into three-dimensional shape data and output it as an input value for the analysis unit 140.
Furthermore, the elastic constant determination unit 120 may obtain the density of the object from a sample density measurement device (not shown) or from input via an input unit (not shown), and input the density to the analysis unit 140 .

Note that in the sample shape acquisition process, part or all of the processing in the elastic constant determination unit 120 may be executed in the measurement result acquisition unit 110.

Next, the elasticity parameter setting unit 130 executes initial elasticity parameter setting processing (S130).
In the initial elastic parameter setting process, the elastic parameter setting unit 130 randomly sets elastic constants (elastic parameters) used in the finite element model, and outputs them as input values to the analysis unit 140.

After that, the analysis unit 140 executes an analysis process using, for example, the finite element method based on the input value (S140).
In the analysis process using the finite element method, the analysis unit 140 calculates estimated resonance frequencies and estimates corresponding to the respective estimated resonance frequencies based on the input three-dimensional shape data and elastic parameters, for example, using the finite element method. Calculate the vibration mode.

The analysis unit 140 calculates the estimated resonant frequency using a boundary element method (BEM), a finite difference method (FDM), a generalized transfer stiffness coefficient method (GTSCM), or the like. and the estimated vibration mode corresponding to each estimated resonance frequency may be calculated.

When the estimated resonant frequency and the estimated vibration mode are calculated, the vibration mode comparison unit 150 executes a vibration mode comparison process (S150).
In the vibration mode comparison process, the vibration mode comparison unit 150 determines, for example, a combination of an estimated resonant frequency that is closest to each measured resonant frequency. Then, the vibration mode comparison unit 150 compares the similarity between each measured vibration mode and the estimated vibration mode to calculate the vibration mode similarity.

Specifically, first, the vibration mode comparison unit 150 calculates, for example, peak amplitude values at each position of the object for the measured vibration mode and the estimated vibration mode, and generates a spatial distribution representation of the amplitude peak values. .

In the present invention, a contour diagram used for visualization is used as a spatial distribution expression.
In conventional techniques such as Non-Patent Documents 1 to 4, researchers' experts often visually determined whether or not they were similar. Generally, in order to accurately measure elastic constants using the RUS method, the resonance frequency must be 4 to 5 times the number of unknown elastic constants, for example, 9 independent elastic constants for orthotropic materials. (vibration mode), that is, it was necessary to compare experiments and analysis at 36 to 45 resonance frequencies (vibration mode). This is very difficult and time consuming to visually inspect. This evaluation can be quickly performed by automating this evaluation using a contour diagram and determining the degree of similarity using cosine similarity, etc., which will be described later.

Furthermore, in the RUS method, the vibration mode measured by the measuring device and the vibration mode obtained by finite element analysis do not truly match. This is due to experimental errors such as differences in density between the object and the finite element model, heterogeneity of the object, and slight errors in shape measurement.
In the present invention, it is possible to solve the problem by drawing contours of vibration modes that do not originally match, and determining the degree of "match" rationally by determining the degree of similarity using cosine similarity or the like.

In generating the contour diagram, the vibration mode comparison unit 150 calculates, for example, the value at the position where the amplitude peak value is maximum, the RGB value (R, G, B) = (255, 0, 0), and the value at the position where the amplitude peak value is the minimum. The value at the position where (R, G, B) = (0, 0, 255) is the value, and the value at the position where the amplitude peak value takes the intermediate value is the RGB value (R, G, B) = (0, 255, 0) is generated using the RGB color system.

Note that the gradations of the RGB values are not limited to the above-mentioned 255 gradations, but can be changed as appropriate, such as 16 gradations, depending on the purpose.
Further, the RGB values associated with the amplitude peak value are not limited to the above values. For example, the value at the position where the amplitude peak value is the maximum is the RGB value (R, G, B) = (0,255,0), and the value at the position where the amplitude peak value is the minimum is (R, G, B). = (255, 0, 0), and the value at the position where the amplitude peak value takes the intermediate value is expressed in the RGB color system where the RGB value is (R, G, B) = (0, 0, 255). good.
Furthermore, the color space used in the contour diagram is not limited to the RGB color system. For example, it may be an HSV (hexagonal pyramid model) color system, an HLS (bihexagonal pyramid model) color system, an L*a*b* color system, or a gray scale.

Then, the vibration mode comparison unit 150 divides the contour diagram into the set meshes, and calculates a three-dimensional vector whose value is the average value of the RGB values in each mesh. The number of meshes to be divided and the width of each mesh may be set, for example, to correspond to the measurement points in the sample vibration mode measuring device 200, or to correspond to the divided regions used in analysis processing. or you can set it manually. Furthermore, the mesh may be in a form that is analyzed in pixel units by converting the figure into an image.

FIG. 3 is a diagram showing a specific example of a method of comparing the contour diagram of the measured vibration mode and the contour diagram of the estimated vibration mode. In FIG. 3, the upper left side shows a contour diagram of each measured vibration mode at the measured resonance frequency, and the lower left side shows a contour diagram of each estimated vibration mode at the estimated resonance frequency corresponding to the measured resonance frequency on the upper left side. . Both contour diagrams are actually color diagrams of RGB values, but here the RGB values are converted to gray scale and shown.

In FIG. 3, for example, each contour diagram is divided into 12×10 meshes. Since a three-dimensional vector is obtained from one mesh, "360 (=12×10×3)" feature vectors are obtained from each of the measured vibration mode and the estimated vibration mode.
Hereinafter, the feature vector calculated from the contour diagram of the measured vibration mode will be referred to as a "measured vibration vector", and the feature vector calculated from the contour diagram of the estimated vibration mode will be referred to as an "estimated vibration vector".

When the measured vibration vector and estimated vibration vector corresponding to a predetermined measured resonance frequency (mode) are calculated, the vibration mode comparison unit 150 calculates the degree of similarity between the measured vibration vector and the estimated vibration vector, preferably by cosine similarity. Calculate using degrees. Then, when the cosine similarity is greater than or equal to a threshold value (for example, "0.6"), the vibration mode comparison unit 150 determines that the measured vibration vector and the estimated vibration vector at a predetermined resonance frequency are similar. Note that the vibration mode comparison unit 150 may determine that the measured vibration vector and the estimated vibration vector at a predetermined measured resonance frequency are similar when the cosine similarity is greater than a threshold value.

In the present invention, by determining a vector representation based on a contour diagram using a cosine similarity, it is possible to rationally and quickly evaluate the similarity.
On the other hand, in the RUS method, if the timing at which the same vibration mode is observed is defined as one cycle, the timing at which the amplitude peak reaches its maximum occurs twice in one cycle because vibration is symmetrical. Using a method using a measuring device or the like, it is not possible to determine which of these two vibration peaks is being observed. Therefore, in the finite element analysis of the present invention, two vibration modes are stored at one resonant frequency of interest and compared with the results of the measurement device. When compared based on cosine similarity, one of the two is very similar and the other is not. Therefore, if one of them reasonably exceeds the threshold determined by the cosine similarity, it can be determined that they match exactly.

When the similarity between the measured vibration vector and the estimated vibration vector at a certain measured resonance frequency is determined, the vibration mode comparison unit 150 similarly determines whether the measured vibration mode at another measurement resonance frequency and the corresponding estimated vibration mode are similar. Determine gender. Then, the vibration mode comparison unit 150 calculates, for example, the proportion of the measured vibration vector and the estimated vibration vector determined to be similar (hereinafter referred to as "vibration mode similarity rate") at all measured resonance frequencies. calculate.

For example, if the number of measured vibration modes of the object is "14" and the number of measured vibration vectors and estimated vibration vectors determined to be similar is "7", the vibration mode similarity rate is calculated as "7÷14=0.5 (50%)".

Note that in the vibration mode comparison process, the vibration mode comparison unit 150 is not limited to determining the similarity between the measured vibration vector and the estimated vibration vector for each measured resonance frequency. For example, when "M (M is a natural number)" measurement vibration modes are measured and each measurement vibration mode and the contour diagram corresponding to that measurement vibration mode are separated by "C" (C is a natural number) meshes. The vibration mode comparison unit 150 may generate "M×C×3" dimensional feature vectors as the measured vibration vector and the estimated vibration vector. Then, the degree of similarity (for example, cosine similarity or reciprocal of L2 norm) between the generated “M×C×3” dimension measured vibration vector and the “M×C×3” dimension estimated vibration vector is determined as the vibration mode. It may be calculated as a similarity rate.

Returning to FIG. 2, when the vibration mode similarity rate is calculated in the vibration mode comparison process, the elastic parameter updating unit 160 determines whether the estimated vibration mode is similar to the measured vibration mode based on the calculated vibration mode similarity rate. It is determined whether or not (S160).
For example, if the vibration mode similarity rate is greater than or equal to a predetermined percentage (for example, "70%"), the elastic parameter update unit 160 determines that the estimated vibration mode is similar to the measured vibration mode. (S160: YES), and elasticity parameter update processing is executed (S170).

In the elasticity parameter updating process, the elasticity parameter updating unit 160 updates the elasticity parameters using, for example, a genetic algorithm (GA) so as to minimize the elasticity parameter evaluation function. Then, the elasticity parameter updating section 160 outputs the updated elasticity parameter to the analysis section 140.
Here, the elastic parameter evaluation function (also referred to as "fitting function") is, for example, the sum of squared errors (Mean Squared Error (MSE)) between the measured resonance frequency and the estimated resonance frequency in each vibration mode. good.

Note that the elastic parameter evaluation function is not limited to the sum of square errors between the measured resonance frequency and the estimated resonance frequency. For example, the elastic parameter evaluation function may be the sum of average absolute errors between the measured resonant frequency and the estimated resonant frequency, or the sum of the coefficients of determination between the measured resonant frequency and the estimated resonant frequency. Further, the elastic parameter evaluation function may be a reciprocal of the vibration mode similarity rate described above.

Furthermore, the elastic parameter updating method based on the elastic parameter evaluation function is not limited to the genetic algorithm. For example, it may be updated using simulated annealing (SA), particle swarm optimization (PSO), or any combination of GA, SA, and PSO. It's okay.

As mentioned above, the input values of the elastic constants used in the finite element method model are random, and depending on the values, the similarity rate may be extremely low. If the vibration mode similarity rate is less than or equal to the predetermined ratio, the elasticity parameter updating unit 160 determines that the estimated vibration mode is not similar to the measured vibration mode (S160: NO), and performs the elasticity parameter resetting process. Execute (S170).

In step 160, if the elasticity parameter updating unit 160 determines that the estimated vibration mode is not similar to the measured vibration mode, the present invention adds, for example, the estimated resonance frequency of the elasticity parameter evaluation function to the The elasticity parameter evaluation function intentionally outputs a large value by introducing a large value, so that the set input value does not become the gene for the next generation input elasticity constant in the genetic algorithm. This makes it possible to quickly determine the elastic constants.

In the elasticity parameter resetting process, the elasticity parameter setting unit 130 randomly resets the elasticity parameters, for example, and outputs them to the finite element analysis unit 140.
As a result, if the current elastic parameter is far from the true value (elastic parameter that reproduces the measured vibration mode), the elastic parameter is set to a state closer to the true value than repeating the elastic parameter update process from the current elastic parameter. As a result, the time required to determine the elastic constants can be shortened.

Note that, in the elasticity parameter resetting process, the elasticity constant determination unit 120 may return to the elasticity parameter before executing the elasticity parameter update process (for example, the elasticity parameter of one generation ago in the case of GA).

Furthermore, the elastic constant determination unit 120 may perform a process of constantly updating the elastic parameters by comparing resonance frequencies without executing the vibration mode comparison process.

When the elasticity parameter update process or the elasticity parameter reset process is executed, the elasticity constant determination unit 120 executes the elasticity parameter evaluation value calculation process (S190).
In the elasticity parameter evaluation value calculation process, the elasticity constant determining unit 120 calculates, for example, the number of GA generations in the elasticity parameter update process as the elasticity parameter evaluation value.
Note that the elastic constant determination unit 120 may, for example, calculate the value of the elastic parameter evaluation function as the elastic parameter evaluation value.

Then, the elastic constant determining unit 120 determines whether the calculated elastic parameter evaluation value satisfies the setting conditions (S200).
When the elasticity parameter evaluation value is the number of generations of GA, the setting condition may be, for example, that the number of generations is equal to or greater than "X (for example, "100")" generations, or larger than "X" generations. In addition, when the elasticity parameter evaluation value is the value of the elasticity parameter evaluation function, the setting condition is, for example, that the elasticity parameter evaluation value is less than or equal to the end threshold (for example, "0.1") or smaller than the end threshold. Good too.

When determining that the elastic parameter evaluation value satisfies the setting condition (S200: YES), the elastic constant determining unit 120 executes elastic constant output processing (S210).
In the elastic constant output process, the elastic constant determining unit 120 outputs, for example, the elastic parameter at that point in time as an elastic constant.

Then, the information processing device 100 ends the process.

If it is determined that the elastic parameter evaluation value does not satisfy the setting conditions (S200: NO), the elastic constant determining unit 120 returns the process to step S140, for example.

Note that, for example, when determining that the steps from S140 to S200 have been repeated a set number of times (for example, "10000" times), the information processing apparatus 100 outputs information indicating that the elastic constant could not be determined, and continues the process. It may be configured to end. In this case, information (for example, a contour diagram) regarding the elastic parameters, estimated resonant frequency, and its estimated vibration mode at the end of the process may be output.

Furthermore, when the information processing device 100 executes steps S140 to S200, for example, the information processing device 100 calculates the updated elasticity parameters in each loop, and the estimated resonance frequency and estimated vibration mode based on the updated elasticity parameters. It's okay. Then, the output unit (not shown) of the information processing device 100 compares the elastic parameters updated for each processing loop and the estimated resonance frequency and estimated vibration mode based on the updated elastic parameters with the measured resonance frequency and the measured vibration mode. It may be possible to output the vibration modes in any possible manner (as an example and not a limitation, vibration modes having close resonance frequencies may be contoured and output in line with each other). In this case, the elasticity parameter for each loop may not be output. Further, the output unit may output, for example, the estimated resonance frequency and estimated vibration mode (for example, a contour diagram) in each loop of the processing process in an animation format, for example, when the processing ends.

[Example]
・Information processing results for objects with known elastic constants In order to examine whether the method of the present invention determines accurate elastic constants, we conducted a study using objects that have known elastic constants in a certain direction. Ta.
The experimental results are shown in which the elastic constants were determined using a SUS304 test piece, which is an isotropic metal material, as the object.
The experimental conditions are as follows.
・Test piece size: 11.010 (mm) x 9.019 (mm) x 1.911 (mm)
・Test piece density: 7.824 (Mg/m ³ )
・Frequency scanning range of sample vibration mode measuring device 200: 50-300 (kHz)
・Resolution of sample vibration mode measuring device 200: 0.156 (kHz)
In addition, in this experiment, 14 measured resonance frequencies were observed from the object.

The elastic parameters used in the mathematical analysis can have a maximum of 21 degrees of freedom (21 variables), but here, assuming that the object is an orthotropic material, the experiment was conducted with nine variables.
The maximum number of elastic constants that can be determined using this method is 21 variables, but if the properties of the object are predictable, reducing the number of elastic parameter variables to the minimum necessary will reduce the time required for the elastic parameter update process and reduce the elasticity This is because the parameter evaluation function can converge quickly.

In the present invention, the elastic constants in the case of nine variables are Young's modulus (longitudinal elastic constant): E ₁₁ , E ₂₂ , E ₃₃ , Poisson's ratio: v ₁₂ , v ₂₃ , v ₃₁ , and shear stiffness (transverse elastic constant): G ₁₂ , G ₂₃ , G _31. The subscripts to the left of these elastic constants indicate the surface of interest, and the subscripts to the right indicate the direction in which the force is acting.

FIG. 4 shows the elastic constant determined by this method, the elastic constant calculated by the uniaxial tensile test, and the catalog value of the SUS304 test piece.
These results show that the determined results were consistent with the results of mechanical testing methods such as the uniaxial tensile test.
Furthermore, since the thickness of the target is not sufficient, it is difficult to determine the elastic constants in the thickness direction such as _E11 and _ν12 in a tensile test, but this method can determine them without being affected by the three-dimensional shape of the target. I am able to do that. As a result, it can be seen that some anisotropy has occurred in the measured test piece.
From the above, this method is considered to be able to appropriately determine the elastic constants, as it is possible to obtain values that are almost the same as those obtained for objects for which independent elastic constants in some directions can be obtained in a tensile test. It will be done. Furthermore, it can be assumed that the independent elastic constants, which are difficult to obtain using other tensile tests, have high validity.

FIG. 5 shows an example of a contour diagram representation of the measured vibration mode measured in the SUS304 test piece used in the experiment and the calculated estimated vibration mode.
In this figure, the measured resonant frequencies that are actually measured values and the measured vibration modes that correspond to each measured resonant frequency are shown at the top, and the estimated resonant frequencies that are analysis values (simulation values) and the measured vibrations that correspond to each estimated resonant frequency. The modes are shown below.
In this figure, each vibration mode is actually visualized and output as RGB values, but in this figure, the RGB values are shown in grayscale.
Further, the elastic parameters used in calculating the estimated resonance frequency and estimated vibration mode shown in the figure are values obtained when it is determined that the elastic parameter evaluation value satisfies the setting conditions.

Comparing the contour diagram of the measured vibration mode and the contour diagram of the estimated vibration mode, it can be seen that the elastic parameters have been updated so that the estimated vibration mode reproduces the measured vibration mode.

[Actions and effects of embodiment]
The information processing device 100 (for example, an example of an information processing device) in this embodiment has a measurement resonance frequency (for example, an example of a resonance frequency of an object) and a measurement vibration mode (for example, an example of a vibration mode at the resonance frequency). a measurement result acquisition unit 110 (for example, an example of an acquisition unit) that acquires the measurement results obtained by measuring the a constant determining unit 120 (for example, an example of a determining unit), and the determining unit is configured to determine the estimated resonant frequency and estimated vibration mode of the object estimated based on a plurality of input elasticity values. Create a contour diagram (for example, an example of the first contour diagram) of the estimated vibration mode based on the measurement results (for example, an example of the first contour diagram), and create a contour diagram of the measured vibration mode based on the resonance frequency and vibration mode based on the measurement results (for example, the second contour diagram). example), and perform elasticity parameter update processing (e.g., an example of updating input elasticity values) using GA based on the distance (e.g., an example of similarity) between the first contour map and the second contour map. An example of a configuration is shown in which an elastic constant is presented based on an input elasticity value that is executed and satisfies the number of generations of GA (for example, an example of a setting condition).
With this configuration, the estimated vibration mode at the estimated resonant frequency estimated based on multiple input elasticity values and the vibration mode at the resonant frequency based on the measurement results can be compared using a contour diagram. be able to. Then, the input value is repeatedly updated based on the similarity of the contour diagram and the elastic parameter evaluation function (the sum of square errors between the measured resonance frequency and the estimated resonance frequency in each vibration mode), and the elastic constant can be determined. As a result, elastic constants can be more easily presented even for objects whose vibration modes are complex and for which elastic constants are difficult to determine or require complicated measurements using conventional methods.

Further, in this embodiment, the vibration mode comparison unit 150 (for example, an example of a determining unit) meshes the first contour diagram and the second contour diagram, and uses the RGB values of the mesh (for example, an example of the color of the mesh). An example of a configuration is shown in which a measured vibration vector and an estimated vibration vector (for example, an example of a vector) are obtained based on the vectors, and a degree of similarity is calculated based on the vectors.
With such a configuration, the degree of similarity can be calculated from a vector based on the color of the mesh of the contour diagram, and the degree of similarity can be calculated more appropriately.

Moreover, this embodiment shows an example of a configuration in which the degree of similarity (for example, an example of degree of similarity) between the first contour diagram and the second contour diagram is a degree of cosine similarity.
With this configuration, it is possible to quickly and appropriately calculate the similarity using cosine similarity.

Further, in the present embodiment, when the vibration mode similarity rate (for example, an example of similarity) is smaller than a predetermined rate (for example, an example of a set value) or is less than or equal to the set value, the elastic parameter setting unit 130 An example of a configuration is shown in which error processing is performed on the elasticity parameter evaluation function that evaluated the similarity rate, and the input elasticity value is reset.
With such a configuration, the input elasticity value can be reset based on the degree of similarity, and the processing speed can be increased.

Further, in this embodiment, the output unit is provided with an output unit that outputs the first contour diagram and the second contour diagram in parallel for each vibration mode having a similar resonance frequency (for example, an example of output that can be compared). An example of a configuration that outputs a second contour diagram that is updated in accordance with updating of values is shown.
With this configuration, it is possible to compare and check the second contour diagram and the first contour diagram, which change according to the update of the input elasticity value, and to check whether the input elasticity value update is progressing appropriately. You can check if there are any.

[First modification]
In the above embodiment, in the vibration mode comparison process, the degree of similarity between the measured vibration vector and the estimated vibration vector is determined by cosine similarity, but the present invention is not limited to this. For example, if the distance between the measured vibration vector and the estimated vibration vector (for example, L2 norm) is smaller than a threshold, the vibration mode comparison unit 150 determines that the measured vibration vector and the estimated vibration vector at a predetermined resonance frequency are similar. It may be determined.
Note that the vibration mode comparison unit 150 determines that the measured vibration vector and the estimated vibration vector at a predetermined resonance frequency are similar when the distance between the measured vibration vector and the estimated vibration vector is less than or equal to a threshold value. Good too.

With this, it is possible to make a determination based on the degree of similarity that takes into account the magnitude of the measured vibration vector and the magnitude of the estimated vibration vector, which may improve the reliability of the degree of similarity.

[Second modification]
In the above embodiment, in the vibration mode comparison process, a contour diagram is generated using the spatial distribution expression of the amplitude peak value of each vibration mode, but the present invention is not limited to this. For example, the vibration mode comparison unit 150 may calculate the phase of the vibration mode at each position of the object, and generate a contour diagram based on the phase.
Note that the vibration mode comparison unit 150 may generate a contour diagram based on the amplitude and phase of the vibration mode, for example.

This makes it possible to properly compare the measured vibration mode with the estimated vibration mode, even in special vibration modes where it is difficult to determine similarity based on amplitude alone.

[Third Modification]
In the above embodiment, the similarity is calculated so that the spatial distribution expression of the estimated vibration mode coincides with the measured vibration mode measured by the sample vibration mode measurement device 200, but is not limited to this. For example, the measurement result acquisition unit 110 may map the three-dimensional measured vibration mode measured by the sample vibration mode measurement device 200 onto, for example, an x-y plane, a y-z plane, and an x-z plane. Then, in the vibration mode comparison process, the elastic constant determination unit 120 maps the estimated vibration mode calculated in the finite element method analysis process onto the same plane (in this example, the x-y plane, the y-z plane, and the x-z plane) as the one mapped by the measurement result acquisition unit 110. Then, the vibration mode comparison unit 150 may compare the spatial distribution expression (contour diagram) of the mapped measured vibration mode with the spatial distribution expression (contour diagram) of the estimated vibration mode on each plane.

FIG. 6 illustrates an example of mapping between the measured vibration mode and the estimated vibration mode.
On the left side of this figure, the object data that visualizes the three-dimensional measurement vibration mode of the object in the center, and the measurement vibration modes mapped on the xy plane, yz plane, and xz plane, respectively, are shown around it. A contour diagram of the figure is shown. In addition, on the right side of this figure, the object data that visualizes the three-dimensional estimated vibration mode in the center, and the measured vibration modes mapped on the xy plane, yz plane, and xz plane, respectively, are shown around it. A contour diagram is illustrated.

In the vibration mode comparison process, the vibration mode comparison unit 150, for example, calculates the vibration mode in the xy plane based on the contour diagram of the measured vibration mode on the xy plane and the contour diagram of the estimated vibration mode on the xy plane. Calculate the vibration mode similarity rate. When it is determined that the measured vibration mode and the estimated vibration mode are not similar based on the xy plane vibration mode similarity rate, the elastic parameter updating unit 160 determines that the measured vibration mode and the estimated vibration mode are similar. It is determined that there is no. The vibration mode comparison unit 150 then omits calculation of vibration mode similarity rates on other planes.
When it is determined that the measured vibration mode and the estimated vibration mode are similar on all planes, the elastic parameter updating unit 160 determines that the measured vibration mode and the estimated vibration mode are similar.

Note that the mapping destination plane is not limited to the xy plane, yz plane, and xz plane. Any three planes may be used as long as they are three-dimensionally orthogonal to each other.

In the above embodiment, the spatial distribution expression of the vibration mode viewed from the direction in which the sample vibration mode measuring device 200 observed the object was used as the comparison target, but in this modification, even when it is difficult to compare from the observation direction. By mapping onto an appropriate plane, it is possible to change the observation viewpoint and perform comparisons.
For example, the orthogonal plane to be mapped may be determined so that the plane area of the three-dimensional shape of the target portion after mapping is maximized.
This makes it possible to more appropriately and quickly determine the similarity between the measured vibration mode and the estimated vibration mode for an object having a complex three-dimensional shape.

In this modification, the measurement result acquisition unit 110 (for example, an example of an acquisition unit) selects the measurement vibration mode (for example, an example of three-dimensional deformation of the object) on the xy plane, the yz plane, and the xz plane. (for example, an example of three planes perpendicular to each other), and the elastic constant determination unit 120 (for example, an example of a determination unit) estimates the measured vibration mode (for example, an example of a vibration mode) in each of the three planes. A configuration is shown in which an elastic constant is determined based on a vibration mode (for example, an example of an estimated vibration mode).
For extremely complex shapes where the shape of one side is significantly different from the shape of the back side, there is a risk of obtaining incorrect elastic constants if only the mode similarity of one side is measured, but it is possible to determine the similarity from any angle. , it is possible to accurately determine the accuracy of elastic constants even for objects with extremely complex shapes.
With this configuration, by comparing the three-dimensional deformation of the object on each of the three projected planes, it is possible to more appropriately and quickly compare the vibration mode and the estimated vibration mode, and as a result, Elastic constants can be determined faster and more accurately.

[Fourth modification]
In the above embodiment, a contour diagram is used as an example of the spatial distribution representation representing the measured vibration mode and the estimated vibration mode, but the present invention is not limited to this. For example, a heat map may be generated without drawing three-dimensional position boundaries.

Note that, for example, a flow map may be generated in order to express the temporal change in amplitude in the measured vibration mode and the estimated vibration mode.

Then, for example, the heat map or flow map may be divided into meshes, and based on the color information within each mesh, the measured vibration vector and the estimated vibration vector may be calculated, and the degree of similarity may be calculated.

[Fifth Modification]
In the above embodiment, in the initial elasticity parameter setting process, the elasticity parameter setting unit 130 randomly sets the elasticity parameters, but the present invention is not limited to this.
For example, when the elastic constant determination unit 120 determines the elastic constant, the elastic constant determination unit 120 may store the material, three-dimensional shape, and elastic constant of the object in a storage unit (not shown). Then, for example, when the same or similar material and the same or similar three-dimensional shape are input as an object for a new analysis, the elastic parameter setting unit 130 may set the elastic parameters by referring to the past elastic constant determination results stored in the storage unit.

With this, it is possible to instantly determine the elastic constant for the same object based on past determination results. Furthermore, for similar objects, there is a possibility of shortening the time required to determine the elastic constant.

In the elastic constant output process, the elastic constant determination unit 120 determines the elasticity based on, for example, an elasticity parameter whose elasticity parameter evaluation value satisfies a setting condition and an elasticity constant of the same or similar object determined in the past. A constant may also be output.

[Sixth variation]
In the above embodiment, the information processing apparatus 100 terminates the process after determining the elastic constant, but the present invention is not limited thereto. As an example and not a limitation, the information processing apparatus 100 may have a determination unit (not shown) evaluate each coefficient of the determined elastic constant and determine the material properties of the object.

For example, assume that the results shown in Tables 1 to 3 below are obtained.

In the results in Table 1, E, ν, and G have the same value, and as shown in E ₁₁ = E ₂₂ = E ₃₃ , Young's modulus, Poisson's ratio, and shear stiffness all have the same values. If they can be considered to be the same, the determination unit determines that they are isotropic.
In the results of Table 2, E ₂₂ =E ₃₃ , but E ₁₁ is different (Similarly, two of ν and G are the same and one is different). In this way, E ₁₁ ≠ E ₂₂ = E ₃₃ (E ₁₁ = E ₂₂ ≠ E ₃₃ , E ₂₂ ≠ E ₁₁ = E ₃₃ ), the values of Young's modulus, Poisson's ratio, and shear stiffness are If they are considered to be the same but one is different, the determination unit determines that the materials are in-plane isotropic.
On the other hand, if the values of Young's modulus, Poisson's ratio, and shear stiffness can all be considered to be different as shown in Table 3, the determination unit determines that the material is orthotropic.
Then, the determination result of the determination unit may be outputted by an output unit (not shown).

In this modification, the degree of freedom of the elasticity parameter is 9 (for example, an example in which a plurality of input elasticity values are 9 variables), and the determination unit orthogonally determines the object based on the elastic constant determined by the determination unit. An example of a configuration is shown in which it is determined whether the material is an orthotropic material, an in-plane isotropic material, or an isotropic material, and the output unit outputs the determination result.
With such a configuration, the properties of the object (whether it is an isotropic material or an orthotropic material containing an isotropic material) can be appropriately determined.

[Seventh modification]
In the above embodiments, materials with low viscoelasticity such as metals and ceramics are exemplified as the material type of the object, but the material is not limited thereto. For example, it has viscoelastic properties and is composed of a composition that is a perfectly elastic body (for example, carbon fiber) and a composition that has viscoelastic properties (for example, a matrix resin). The object may be a material type (for example, CFRP (Carbon Fiber Reinforced Plastics)). The viscoelasticity acquisition method for the object will be described below.

FIG. 7 is a flowchart illustrating an example of the procedure of information processing in this modification.
Note that the flowchart described below merely shows an example of the procedure of information processing in this modification, and other steps may be added or some steps may be deleted. Further, some of the steps in the flowchart may be replaced and executed. In addition, steps that are the same as those described above may be given the same reference numerals and explanations may be omitted.

For example, after executing the sample shape acquisition process (S120), the elastic constant determination unit 120 executes the viscoelastic property acquisition process (S310).
In the viscoelastic property acquisition process, the elastic constant determination unit 120 uses a viscoelasticity measuring device (dynamic viscoelasticity tester) not shown to measure a component having viscoelasticity (for example, in the case of CFRP, a matrix) out of the target object. A test piece consisting only of resin is created, and the dynamic viscoelasticity test results of the composition are obtained. Then, the elastic constant determination unit 120 calculates the viscoelastic properties in a wide converted frequency band based on the dynamic viscoelasticity test results at a plurality of frequencies, for example, using a time-temperature conversion law.
This makes it possible to obtain the viscoelastic properties of a material that has viscoelasticity among the materials constituting the object to be measured at a frequency that corresponds to the measurement resonance frequency of the object obtained in the sample vibration mode measurement result acquisition process. .

Note that the acquisition of the dynamic viscoelasticity test results and the calculation of the viscoelastic properties may be performed in the measurement result acquisition unit 110.

For example, when the elastic constant determining unit 120 executes the initial elastic parameter setting process (S130), it executes the complex equivalent stiffness calculation process (S320).

In the complex equivalent stiffness calculation process, the elastic constant determination unit 120 generates a representative volume element model (e.g., an example of an analytical model) of an object having viscoelastic properties based on, for example, a component (e.g., matrix resin) whose viscoelastic properties have been acquired in the viscoelastic property acquisition process, and a component (e.g., carbon fiber) that is a perfect elastic body whose elastic parameters have been set in the initial elastic parameter setting process. Hereinafter, the representative volume element model may be abbreviated as "Representative Volume Element (RVE)."

Next, the elastic constant determination unit 120 analyzes, for example, the strain caused by applying loads in different directions and at various frequencies to the created representative volume element model using the finite element method. Then, the elastic constant determining unit 120 calculates the complex equivalent stiffness, for example, based on the analysis results for the representative volume element model.

For example, when the complex equivalent stiffness of the representative volume element model is calculated, the elastic constant determination unit 120 executes the generalized Maxwell model coefficient identification process (S330). Hereinafter, the generalized Maxwell model may be abbreviated as "GMM". In addition, not only the generalized Maxwell model but also the Zener model (a model in which a single spring element is added in parallel to the generalized Maxwell model) or the like may be used.

In the generalized Maxwell model coefficient identification process, the elastic constant determining unit 120 identifies each coefficient of the GMM using, for example, a genetic algorithm (GA) based on, for example, the complex equivalent stiffness.

More specifically, the storage modulus C' is assumed to be the following equation (1), and the loss elastic modulus C'' is assumed to be the equation (2) below.

However, ω is each frequency, and C ₀ is the elastic coefficient. Further, i represents each Maxwell element, c _i =C _i /C ₀ represents the normalized relaxation coefficient, and τ _i =μ _i /C _i represents the relaxation time.

At this time, for example, each coefficient C _i is determined by a genetic algorithm or the like so that the error function defined by the following equation is less than or equal to a threshold value.

However, y'model is the storage modulus of GMM, and y'exp is the storage modulus of RVE. Moreover, y''model is the loss elastic modulus of GMM, and y''exp is the loss elastic modulus of RVE.

When the storage modulus and loss modulus in the GMM of the object are identified based on each coefficient C _i , the analysis unit 140 calculates, for example, a finite Analysis processing using the element method is executed (S140).

If it is determined that the elastic parameter evaluation value does not satisfy the set condition (S200: NO), the elastic constant determination unit 120 returns the process to step S320, for example. Then, for example, based on the updated elastic parameters, the representative volume element model is recreated and the complex equivalent stiffness is calculated. Then, in the generalized Maxwell model coefficient identification process, each coefficient of the GMM is also updated based on the updated complex equivalent stiffness.

When determining that the elastic parameter evaluation value satisfies the setting conditions (S200: YES), the elastic constant determining unit 120 executes elastic constant output processing (S210).
In the elastic constant output process, the elastic constant determining unit 120 outputs, for example, the elastic parameter at that point, the storage elastic modulus of the GMM, and the loss elastic modulus of the GMM as elastic constants.

Note that the storage modulus and loss modulus are not limited to being identified by GMM. For example, the storage modulus and the loss modulus may be simultaneously optimized as elastic parameters using the Williams-Landel-Ferry formula (Williams-Landel-Ferry formula, WLF formula).

In this modification, the elastic constant determination unit 120 (for example, an example of a calculation unit) of the information processing device performs an RVE (for example, an analysis model A configuration that calculates the storage elastic modulus and loss elastic modulus (for example, an example of elastic parameter values) in GMM based on the above data (for example), and presents an elastic constant based on a plurality of input elastic values, elastic parameter values, and measurement results. An example is shown.
As a result, even for objects that have viscoelasticity, elastic parameter values can be calculated based on the analytical model of the object, and, for example, the elastic constant can be determined by updating the input elastic value and the elastic parameter value. Can be done.

In addition, in this modification, the target object is a matrix resin (for example, an example of a first composition having viscoelasticity) and carbon fibers (for example, an example of a second composition different from the first composition). configured. An example of a configuration is shown in which the plurality of input elasticity values are the input elasticity values of the second component.
With this, it is possible to present the elastic constant of an object for which it is difficult to determine the elastic constant in an object that is a mixture of a first composition having viscoelasticity and a second composition different from the first composition. Can be done.

In addition, in this modification, the information processing device includes a measurement result acquisition unit 110 that acquires dynamic viscoelasticity test results and viscoelastic properties in a wide converted frequency band (for example, an example of the viscoelastic properties of the first component). (for example, an example of a viscoelastic property acquisition unit), and calculates an elastic parameter value based on an analytical model based on viscoelastic properties and a plurality of input elastic values.
As a result, by measuring the viscoelastic properties of the first component, the resonant frequency of the object composed of the first component and the second component, and the vibration mode at the resonant frequency, the elasticity of the object can be measured. You can find constants.

[Other embodiments]
As another aspect of the present invention, the information processing device includes an acquisition unit that acquires measurement results obtained by measuring a resonant frequency of an object and a vibration mode at the resonant frequency; , a determining unit that determines an elastic constant, and the determining unit is configured to express a spatial distribution based on an estimated resonance frequency and an estimated vibration mode of the object estimated based on a plurality of input elastic values, and a resonant frequency based on a measurement result. The input elasticity value may be updated based on the input elasticity value and the spatial distribution expression based on the vibration mode, and the elastic constant may be determined based on the input elasticity value that satisfies the setting conditions.

In addition, the spatial distribution expression is a contour diagram, and the determination unit calculates the degree of similarity based on the vector calculated based on the contour diagram, and if the degree of similarity is smaller than the set value or less than the set value, , the input elasticity value may be reset.

Furthermore, the determining unit may calculate the vector based on the color of each predetermined mesh of the contour diagram.

Additionally, the determining unit may update the input elasticity value based on a genetic algorithm.

In the present invention, the type of material to be measured is not limited to materials with low viscoelasticity such as metals and ceramics, but also materials with high viscoelasticity that are accompanied by vibration damping phenomena such as polymeric materials can be measured. However, in order to determine the elastic constant of an object such as a polymeric material, the dynamic elastic modulus of the object is measured, and the storage modulus and loss modulus obtained from the dynamic elastic modulus are calculated using the loading frequency and reference temperature. This becomes possible by obtaining the relationship experimentally and applying the finite element analysis of the present invention.

1 Information processing system 100 Information processing device 110 Measurement result acquisition unit 120 Elastic constant determination unit 200 Sample vibration mode measurement device 300 Sample shape measurement device

Claims (13)

1. an acquisition unit that acquires a measurement result of measuring a resonant frequency of an object and a vibration mode at the resonant frequency;
   a determining unit that presents an elastic constant based on the plurality of input elasticity values and the measurement results;
   Equipped with
   The determining unit is
   using the plurality of input elasticity values to create a first contour diagram for each estimated vibration mode at the estimated resonant frequency of the object;
   creating a second contour diagram in each measurement vibration mode at a measurement resonance frequency corresponding to the estimated resonance frequency based on the measurement results;
   updating the input elasticity value by a genetic algorithm based on the similarity between the first contour diagram and the second contour diagram;
   presenting the elastic constant based on the input elasticity value that satisfies a setting condition;
   Information processing device.
2. The determining unit is
   Meshing the first contour diagram and the second contour diagram, obtaining a vector based on the color of the mesh,
   calculating the degree of similarity based on the vector;
   The information processing device according to claim 1.
3. the similarity is a cosine similarity;
   The information processing device according to claim 1.
4. The determining unit resets the input elasticity value when the similarity is smaller than a set value or less than or equal to the set value.
   The information processing device according to claim 1.
5. The acquisition unit projects the three-dimensional deformation of the object onto three mutually orthogonal planes;
   The determiner presents the elastic constant based on each of the estimated vibration modes at the estimated resonant frequency in each of the three planes.
   The information processing device according to claim 1 .
6. The plurality of input elasticity values are nine variables,
   a determining unit that determines whether the object is an orthotropic material, an in-plane isotropic material, or an isotropic material based on the elastic constant presented by the determining unit; and,
   an output unit that outputs the determination result of the determination unit;
   Equipped with
   The information processing device according to claim 1.
7. an output unit that outputs the first contour diagram and the second contour diagram in a manner that allows comparison;
   The output unit outputs the second contour diagram that is updated according to the update of the input elasticity value.
   The information processing device according to claim 1.
8. The object is a viscoelastic object,
   comprising a calculation unit that calculates an elastic parameter value regarding the object based on an analytical model of the object;
   The determining unit presents an elastic constant based on the plurality of input elasticity values, the elasticity parameter value, and the measurement result.
   The information processing device according to claim 1.
9. The object is composed of a first composition having viscoelasticity and a second composition different from the first composition,
   The plurality of input elasticity values are a plurality of input elasticity values regarding the second structure,
   The information processing device according to claim 8.
10. a viscoelasticity characteristic acquisition unit for acquiring a viscoelasticity characteristic of the first component,
    The calculation unit calculates the elasticity parameter value based on the analysis model based on the viscoelastic property and the multiple input elasticity values.
    The information processing device according to claim 9.
11. a measuring device that measures a resonant frequency of an object and a vibration mode at the resonant frequency;
    The information processing device according to any one of claims 1 to 10,
    A system equipped with
12. an acquisition unit that acquires a measurement result of measuring a resonance frequency of a target object and a vibration mode at the resonance frequency; and a determination unit that presents an elastic constant based on a plurality of input elasticity values and the measurement results. A program for causing an information processing device to execute,
    In the determining section,
    using the plurality of input elasticity values to create a first contour diagram for each estimated vibration mode at the estimated resonant frequency of the object;
    creating a second contour diagram in each measurement vibration mode at a measurement resonance frequency corresponding to the estimated resonance frequency based on the measurement result;
    updating the input elasticity value by a genetic algorithm based on the similarity between the first contour diagram and the second contour diagram;
    Presenting the elastic constant based on the input elasticity value that satisfies a setting condition;
    A program to run.
13. A method for presenting an elastic constant of an object, comprising the steps of:
    Obtaining a measurement result of measuring a resonance frequency of the object and a vibration mode at the resonance frequency;
    creating a first contour diagram for each estimated vibration mode at an estimated resonant frequency of the object using a plurality of input elasticity values;
    creating a second contour diagram in each measurement vibration mode at a measurement resonance frequency corresponding to the estimated resonance frequency based on the measurement result;
    updating the input elasticity value by a genetic algorithm based on a similarity between the first contour map and the second contour map;
    Presenting the elastic constant based on the input elasticity value that satisfies a set condition;
    Presentation methods including:

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