Information processing device, system, program, and presentation method

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, and presentation method

[0001] The present invention relates to an information processing device and the like.

[0002] There is a social need to identify the elastic constants of objects in fields such as material selection and material processing. For objects with simple linear shapes, such as rod-shaped materials, the elastic constants can be obtained using tensile tests. On the other hand, for objects with complex shapes, the objects must be molded into shapes that meet specifications in order to perform measurements. Furthermore, for objects with mechanical anisotropy, it is necessary to measure tensile and shear loads from various directions using multiple different test methods, making it difficult to determine the elastic constants.

[0003] Conventionally, known methods for determining the elastic constant of such an object include a method for determining the elastic constant by inverse analysis using numerical analysis techniques such as Resonant Ultrasound Spectroscopy (hereinafter sometimes referred to as the "RUS method"), which vibrates a solid body and calculates the resonance mode of the resonance frequency, and the Finite Element Method (FEM) (see, for example, Patent Document 1 and Non-Patent Documents 1 to 4). However, the above methods have room for improvement in terms of accuracy, etc.

[0004] JP 2003-207390 Public Relations

[0005] LB Beardslee et al., 'Determining material properties of components with complex shapes using Resonant Ultrasound Spectroscopy'Applied Acoustics 178 (2021) 108014J,Rossin et al., 'Assessment of grain structure evolution with resonant ultrasound spectroscopy in additively manufactured nickel alloys'A Materials Characterization 167 (2020) 110501M Janovska' et al., 'Characterization of bonding quality of a cold-sprayed deposit by laser resonant ultrasound spectroscopy' Ultrasonics 106 (2020) 106140Jili Plesek et al., 'Using finite element method for the determination of elastic moduli by resonant ultrasound spectroscopy' J. Acoust. Soc. Am. 116 (1), July 2004 282-287

[0006] The present invention proposes a new method for easily determining (presenting) the elastic constants of an object with a complex shape.

[0007] The information processing device, system using the information processing device, program, and presentation method of the present invention comprise an acquisition unit that acquires measurement results of measuring the resonance frequency and vibration mode at the resonance frequency of an object, and a determination unit that presents an elastic constant based on a plurality of input elastic values ​​and the measurement results, wherein the determination unit uses the plurality of input elastic values ​​to create a first contour diagram for each estimated vibration mode at the estimated resonance frequency of the object, creates a second contour diagram for each measured vibration mode at a measured resonance frequency corresponding to the estimated resonance frequency based on the measurement results, updates the input elastic value using a genetic algorithm based on the similarity between the first contour diagram and the second contour diagram, and presents the elastic constant based on the input elastic value that satisfies a set condition.

[0008] According to the present invention, it is possible to more easily determine the elastic constant of an object for which it has been difficult to determine the elastic constant using conventional methods or for which complicated measurements have been required.

[0009] 1 is a block diagram showing an example of the configuration of an information processing system; 2 is a flowchart showing an example of the flow of information processing; 3 is a diagram showing a specific example of a measured vibration mode of a sample and an estimated vibration mode of the sample; 4 is a diagram showing a specific example of a processing result in a vibration mode comparison unit; 5 is a diagram showing an example of a comparison result between an elastic constant output by an information processing device and an elastic constant obtained by another method; 6 is a diagram showing a specific example of a projection of a measured and estimated vibration mode onto an orthogonal plane;

[0010] An example of an embodiment of the present invention will be described below with reference to the drawings. In the description of the drawings, the same elements are designated by the same reference numerals, and duplicate descriptions may be omitted. Furthermore, the components described in this embodiment are merely examples, and are not intended to limit the scope of the present invention.

[0011] [Embodiment] Hereinafter, an example of an embodiment for realizing the information processing technology of the present invention will be described.

[0012] 1 is a diagram showing an example of the system configuration of an information processing system 1 according to one aspect of the present embodiment. In the information processing system 1, for example, an information processing device 100, a sample vibration mode measurement device 200, and a sample shape measurement device 300 are connected. The information processing system 1 may also be referred to as a material analysis system or an elastic constant determination system.

[0013] In the information processing system 1 and information processing device 100 of the present invention, an object to be analyzed (measured) can be analyzed without any restrictions on, for example, the following items: - Material type (e.g., metal, ceramic, composite material, etc.) - Material form (e.g., three-dimensional shape of the material) - Measurement environment (e.g., measurement temperature environment) In other words, the information processing device 100 can calculate the elastic constant of an object without being restricted by the three-dimensional shape of the object.

[0014] The sample vibration mode measurement device 200 has a function of measuring the resonant frequencies of an object whose elastic constant is to be determined and the vibration modes (resonant modes) corresponding to each resonant frequency. The sample vibration mode measurement device 200 may measure the vibration modes and resonant frequencies of the object by, for example, a laser Doppler method.

[0015] The sample shape measuring device 300 has a function of measuring the three-dimensional shape of an object. The sample shape measuring device 300 may acquire the shape (size and shape) of the object by, for example, contact 3D scanning in which a probe is brought into contact to acquire the three-dimensional shape, or non-contact 3D scanning using LiDAR (Light Detection and Ranging) or the like.

[0016] The information processing device 100 has a function of determining the elastic constant of an object based on, for example, 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. The information processing device 100 may also be called a material analysis device or an elastic constant presentation device.

[0017] 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 determination unit 120 includes an elastic parameter setting unit 130, an analysis unit 140, a vibration mode comparison unit 150, and an elastic parameter update unit 160. These may be functional units (functional blocks) included in a processing unit (processing device) or control unit (control device) (not shown) of the information processing device 100, and may include processing circuits such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), and FPGA (Field Programmable Gate Array).

[0018] The measurement result acquisition unit 110 has a function of receiving, for example, the resonant frequency and vibration mode of the object measured by the sample vibration mode measurement device 200 as input, and outputting the resonant frequency and vibration mode of the object to the elastic constant determination unit 120. Hereinafter, the resonant frequency of the object acquired by the measurement result acquisition unit 110 will be referred to as the "measured resonant frequency," and the resonant mode will be referred to as the "measured vibration mode."

[0019] The measurement result acquisition unit 110 may have a function of, for example, receiving as input three-dimensional shape data of the object measured by the sample shape measurement device 200, and outputting the three-dimensional shape data of the object to the elastic constant determination unit 120. Furthermore, the three-dimensional shape data of the object may be received not based on the measurement results in the sample shape measurement device 300, but for example, by receiving CAD data of the object from a CAD data storage server (not shown).

[0020] The elastic parameter setting unit 130 has a function of setting initial values ​​of elastic parameters used in the mathematical analysis in the analysis unit 140, for example.

[0021] The analysis unit 140 has a function of calculating, for example, by the finite element method, a resonance frequency and a vibration mode of an object having a three-dimensional shape, assuming that the object has the set elastic parameters, based on the three-dimensional shape data and the elastic parameters set in the elastic parameter setting unit 130. The analysis unit 140 may also be referred to as a mathematical analysis unit 140. Hereinafter, the resonance frequency of the object model calculated by mathematical analysis will be referred to as an "estimated resonance frequency," and the resonance mode will be referred to as an "estimated vibration mode."

[0022] The vibration mode comparison unit 150 has the function of, for example, comparing the measured vibration mode at each measured resonance frequency acquired by the measurement result acquisition unit 110 with the estimated vibration mode at each resonance frequency corresponding to each measured resonance frequency calculated by the analysis unit 140, and determining whether the estimated vibration mode is significantly different from the measured vibration mode.

[0023] The elastic parameter update unit 160 has a function of determining whether or not to update the elastic parameters based on, for example, the determination result in the vibration mode comparison unit 150. Furthermore, when it is determined that the elastic parameters should be updated, for example, the elastic parameter update unit 160 has a function of updating the elastic parameters using, for example, an evaluation function based on the estimated resonance frequency and the measured resonance frequency.

[0024] Furthermore, the elastic parameter update unit 160 has a function of outputting the elastic parameters as elastic constants (determined results) when the evaluation function satisfies a setting condition described later, for example.

[0025] Here, the "output" of the elastic constant (determination result) may include not only the display of the judgment result on the device itself (display output), but also, for example, the output of the judgment result to another functional unit on the device itself (internal output), or the output (external output) or transmission (external transmission) of the judgment result to a device other than the device itself (external device).

[0026] [Information Processing Procedure] Fig. 2 is a flowchart showing an example of an information processing procedure according to this embodiment. The processing in the flowchart in Fig. 2 is realized, for example, by the processing unit of the information processing device 100 reading out the code of a program stored in a storage unit (not shown) into a RAM (not shown) or the like and executing the code.

[0027] Each symbol S in the flowchart in Figure 2 represents a step. Note that the flowchart described below merely shows an example of the information processing procedure in this embodiment, and other steps may be added or some steps may be deleted. Also, some of the steps in the flowchart may be interchanged and executed.

[0028] 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 storage unit such as a RAM (not shown).

[0029] The elastic constant determination unit 120 also 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 input values ​​for the analysis unit 140. At this time, the sample shape measurement device 300 acquires images of the object from multiple directions to acquire the shape of the sample. While it is preferable to acquire images from multiple directions, it is also possible to measure the elastic constants even when the image is acquired from a single direction. Furthermore, as described below, the acquired data may be projected images viewed from each direction. Furthermore, when creating projected images, it is preferable to acquire them from a direction where the object has a distinctive shape, such as a flat surface, as this facilitates analysis, etc.

[0030] In the sample shape acquisition process, when the elastic constant determination unit 120 receives CAD data of the object from a CAD data storage server (not shown), it may convert the data into three-dimensional shape data and output the data as input values ​​for the analysis unit 140. Furthermore, the elastic constant determination unit 120 may obtain the density of the object from an input by a sample density measurement device (not shown) or an input unit (not shown), and input the density to the analysis unit 140.

[0031] In the sample shape acquisition process, some or all of the processes in the elastic constant determination unit 120 may be executed in the measurement result acquisition unit 110 .

[0032] Next, the elastic parameter setting unit 130 executes an initial elastic parameter setting process (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 method model, for example, and outputs them as input values ​​to the analysis unit 140.

[0033] Thereafter, the analysis unit 140 executes an analysis process using, for example, the finite element method based on the input values ​​(S140). In the analysis process using the finite element method, the analysis unit 140 calculates estimated resonance frequencies and estimated vibration modes corresponding to each estimated resonance frequency based on the input three-dimensional shape data and elastic parameters, for example, by the finite element method.

[0034] The analysis unit 140 may calculate the estimated resonant frequencies and the estimated vibration modes corresponding to each estimated resonant frequency using the boundary element method (BEM), the finite difference method (FDM), the generalized transfer stiffness coefficient method (GTSCM), or the like.

[0035] After the estimated resonant frequencies and the estimated vibration modes 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, the combination of estimated resonant frequencies 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.

[0036] Specifically, first, the vibration mode comparison unit 150 calculates, for example, the 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.

[0037] In the present invention, a contour diagram used for visualization is used to represent spatial distribution. In conventional techniques such as those described in Non-Patent Documents 1 to 4, researchers often visually determined whether or not the data were similar. Generally, to accurately measure elastic constants using the RUS method, it is necessary to compare experimental and analytical results at 4 to 5 times the number of resonant frequencies (vibration modes) of the unknown elastic constants (e.g., nine independent elastic constants for an orthotropic material), i.e., 36 to 45 resonant frequencies (vibration modes). This is extremely difficult and time-consuming to do visually. This evaluation can be automated using a contour diagram, and rapid evaluation can be performed by determining the similarity using cosine similarity, as described below.

[0038] Furthermore, in the RUS method, the vibration modes measured by the measurement device and the vibration modes 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, this problem can be resolved by plotting the vibration modes that do not truly match in a contour map and determining the degree of similarity using cosine similarity or the like to rationally determine the degree of "match."

[0039] In generating the contour diagram, the vibration mode comparison unit 150 generates a contour diagram expressed in an RGB color system in which, for example, the value at the position where the amplitude peak value is maximum is the RGB value of (R, G, B) = (255, 0, 0), the value at the position where the amplitude peak value is minimum is the RGB value of (R, G, B) = (0, 0, 255), and the value at the position where the amplitude peak value is intermediate is the RGB value of (R, G, B) = (0, 255, 0).

[0040] The RGB values ​​are not limited to the 255 gradations described above and can be changed to 16 gradations or other values ​​as appropriate depending on the purpose. 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 maximum may be expressed using an RGB color system in which the RGB values ​​(R, G, B) = (0, 255, 0), the value at the position where the amplitude peak value is minimum (R, G, B) = (255, 0, 0), and the value at the position where the amplitude peak value is intermediate (R, G, B) = (0, 0, 255). The color space used in the contour diagram is not limited to the RGB color system. For example, the HSV (hexagonal saturation value) color system, the HLS (double hexagonal saturation value) color system, the L*a*b* color system, or grayscale may also be used.

[0041] The vibration mode comparison unit 150 then 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 measurement device 200, or to the divided areas used in the analysis process, or may be set manually. The meshes may also be configured to analyze the diagram in pixel units, which are images of the diagram.

[0042] 3 is a diagram showing a specific example of a method for comparing a contour diagram of a measured vibration mode with a contour diagram of an estimated vibration mode. In FIG. 3, a contour diagram of each measured vibration mode at a measured resonance frequency is shown on the upper left, and a contour diagram of each estimated vibration mode at an estimated resonance frequency corresponding to the measured resonance frequency on the upper left is shown on the lower left. Both contour diagrams are actually color diagrams of RGB values, but here the RGB values ​​are converted to grayscale and shown.

[0043] In Fig. 3, for example, each contour diagram is divided into a "12 x 10" mesh. Since a three-dimensional vector can be obtained from one mesh, "360 (= 12 x 10 x 3)" feature vectors can be 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."

[0044] When the measured vibration vector and estimated vibration vector corresponding to a predetermined measurement resonant frequency (mode) are calculated, the vibration mode comparison unit 150 calculates the similarity between the measured vibration vector and the estimated vibration vector, preferably using cosine similarity. Then, if the cosine similarity is equal to or greater than a threshold value (e.g., 0.6), the vibration mode comparison unit 150 determines that the measured vibration vector and estimated vibration vector at the predetermined resonant frequency are similar. Note that, if the cosine similarity is greater than the threshold value, the vibration mode comparison unit 150 may determine that the measured vibration vector and estimated vibration vector at the predetermined measurement resonant frequency are similar.

[0045] In the present invention, the cosine similarity of vector representations based on contour diagrams can be used to rationally and quickly evaluate similarity. In contrast, in the RUS method, if the timing at which the same vibration mode is observed is considered one cycle, the timing at which the amplitude peak reaches its maximum occurs twice per cycle due to vibration symmetry. Techniques using measurement devices, etc., cannot determine which of the two vibration peaks is observed. Therefore, in the finite element analysis of the present invention, two vibration modes are saved for a single resonant frequency of interest and compared with the results of the measurement device. When compared using cosine similarity, one of the two is highly similar and the other is dissimilar. Therefore, if one of the two exceeds a reasonably determined threshold for cosine similarity, it can be determined that they match accurately.

[0046] When the similarity between the measured vibration vector and the estimated vibration vector at a certain measurement resonant frequency is determined, the vibration mode comparison unit 150 similarly determines the similarity between the measured vibration modes at other measurement resonant frequencies and the corresponding estimated vibration modes. Then, the vibration mode comparison unit 150 calculates, for example, the rate at which the measured vibration vector and the estimated vibration vector are determined to be similar at all measurement resonant frequencies (hereinafter referred to as the "vibration mode similarity rate").

[0047] 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%)".

[0048] 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 resonant frequency. For example, when "M (M is a natural number)" measured vibration modes are measured and each measured vibration mode and its corresponding contour diagram are divided into "C (C is a natural number)" meshes, the vibration mode comparison unit 150 may generate "M x C x 3" dimensional feature vectors as the measured vibration vector and the estimated vibration vector. Then, the similarity (e.g., cosine similarity or the inverse of the L2 norm) between the generated "M x C x 3" dimensional measured vibration vector and the "M x C x 3" dimensional estimated vibration vector may be calculated as the vibration mode similarity rate.

[0049] 2 , when the vibration mode similarity rate is calculated in the vibration mode comparison process, the elastic parameter update unit 160 determines whether the estimated vibration mode is similar to the measured vibration mode based on the calculated vibration mode similarity rate (S160). For example, if the vibration mode similarity rate is greater than a predetermined percentage (e.g., 70%) or equal to or greater than the predetermined percentage, the elastic parameter update unit 160 determines that the estimated vibration mode is similar to the measured vibration mode (S160: YES), and executes the elastic parameter update process (S170).

[0050] In the elastic parameter update process, the elastic parameter update unit 160 updates the elastic parameters by, for example, a genetic algorithm (GA) so as to minimize the elastic parameter evaluation function. Then, the elastic parameter update unit 160 outputs the updated elastic parameters to the analysis unit 140. Here, the elastic parameter evaluation function (also referred to as an "adaptation function") may be, 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.

[0051] The elasticity parameter evaluation function is not limited to the sum of squared errors between the measured resonance frequency and the estimated resonance frequency. For example, the elasticity parameter evaluation function may be the sum of mean absolute errors between the measured resonance frequency and the estimated resonance frequency, or the sum of coefficients of determination between the measured resonance frequency and the estimated resonance frequency. Furthermore, the elasticity parameter evaluation function may be the inverse of the vibration mode similarity rate.

[0052] Furthermore, the method for updating the elastic parameters based on the elastic parameter evaluation function is not limited to the genetic algorithm, and may be, for example, simulated annealing (SA) or particle swarm optimization (PSO), or any combination of GA, SA, and PSO.

[0053] As described above, the input values ​​of the elastic constants used in the finite element method model are random, and depending on the value, the similarity rate may be extremely low. If the vibration mode similarity rate is equal to or less than a predetermined rate, the elastic parameter update unit 160 determines that the estimated vibration mode is not similar to the measured vibration mode (S160: NO), and executes elastic parameter resetting processing (S170).

[0054] In step 160, if the elastic parameter update unit 160 determines that the estimated vibration mode is not similar to the measured vibration mode, in the present invention, for example, an unconventionally large value is introduced into the estimated resonance frequency of the elastic parameter evaluation function, so that the elastic parameter evaluation function intentionally outputs a large value, and the set input value does not become the gene for the input elastic constant of the next generation in the genetic algorithm, thereby enabling the elastic constant to be determined quickly.

[0055] In the elastic parameter resetting process, the elastic parameter setting unit 130 resets the elastic parameters, for example, randomly, and outputs the reset values ​​to the finite element analysis unit 140. As a result, if the current elastic parameters are far from the true values ​​(elastic parameters that reproduce the measured vibration mode), there is a possibility that the elastic parameters can be set to a state closer to the true values ​​than by repeating the elastic parameter update process from the current elastic parameters, and as a result, the time required to determine the elastic constants can be shortened.

[0056] In the elastic parameter resetting process, the elastic constant determination unit 120 may return the elastic parameters to those before the elastic parameter update process (for example, elastic parameters of one generation before in the case of GA).

[0057] Furthermore, the elastic constant determination unit 120 may perform a process of constantly updating the elastic parameters by comparing the resonance frequencies without performing the vibration mode comparison process.

[0058] When the elastic parameter update process or the elastic parameter reset process is executed, the elastic constant determination unit 120 executes an elastic parameter evaluation value calculation process (S190). In the elastic parameter evaluation value calculation process, the elastic constant determination unit 120 calculates, for example, the number of generations of GA in the elastic parameter update process as the elastic parameter evaluation value. Note that the elastic constant determination unit 120 may also calculate, for example, the value of the elastic parameter evaluation function as the elastic parameter evaluation value.

[0059] The elastic constant determination unit 120 then determines whether the calculated elastic parameter evaluation value satisfies a set condition (S200). When the elastic parameter evaluation value is the number of generations of GA, the set condition may be, for example, that the number of generations is equal to or greater than "X" generations (e.g., "100") or more. When the elastic parameter evaluation value is the value of the elastic parameter evaluation function, the set condition may be, for example, that the elastic parameter evaluation value is equal to or less than a termination threshold value (e.g., "0.1") or less than the termination threshold value.

[0060] If it is determined that the elastic parameter evaluation value satisfies the set condition (S200: YES), the elastic constant determination unit 120 executes an elastic constant output process (S210). In the elastic constant output process, the elastic constant determination unit 120 outputs, for example, the elastic parameters at that time as the elastic constant.

[0061] Then, the information processing device 100 ends the process.

[0062] When it is determined that the elasticity parameter evaluation value does not satisfy the set condition (S200: NO), the elasticity constant determination unit 120 returns the process to step S140, for example.

[0063] Note that, for example, when the information processing device 100 determines that steps S140 to S200 have been repeated a set number of times (e.g., 10,000 times), it may output information indicating that the elastic constants could not be determined and terminate the processing. In this case, it may output information (e.g., a contour diagram) relating to the elastic parameters at the time of termination of the processing, the estimated resonant frequency, and the estimated vibration mode thereof.

[0064] Furthermore, when the information processing device 100 executes steps S140 to S200, for example, it may calculate the updated elastic parameters for each loop and the estimated resonant frequency and estimated vibration mode based on the updated elastic parameters. The output unit (not shown) of the information processing device 100 may then output the updated elastic parameters for each processing loop and the estimated resonant frequency and estimated vibration mode based on the updated elastic parameters in a manner that allows comparison with the measured resonant frequency and measured vibration mode (for example, but not limited to, generating contour diagrams of vibration modes with similar resonant frequencies and outputting them side by side). In this case, the elastic parameters for each loop may not be output. Furthermore, the output unit may output the estimated resonant frequency and estimated vibration mode (e.g., contour diagrams) for each loop of the processing process, for example, in animation format, at the end of processing.

[0065] [Example] - Information processing results of an object with known elastic constants In order to examine whether the method of the present invention determines accurate elastic constants, an object with known elastic constants in a certain direction was used for the study. The results of an experiment in which the elastic constant was determined using a SUS304 test piece, which is an isotropic metal material, are shown below. The experimental conditions were as follows: - Test piece dimensions: 11.010 (mm) x 9.019 (mm) x 1.911 (mm) - Test piece density: 7.824 (Mg / m ３ Frequency scanning range of the sample vibration mode measurement device 200: 50-300 (kHz) Resolution of the sample vibration mode measurement device 200: 0.156 (kHz) In this experiment, 14 measurement resonance frequencies were observed from the object.

[0066] The elastic parameters used in mathematical analysis can have a maximum of 21 degrees of freedom (21 variables), but here, the object was assumed to be an orthotropic material and experiments were conducted with 9 variables. Although the maximum number of elastic constants that can be determined using this method is 21, if the properties of the object can be predicted, keeping the number of elastic parameter variables to a minimum can reduce the time required for the elastic parameter update process and speed up the convergence of the elastic parameter evaluation function.

[0067] 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: ν １２ , ν ２３ , ν ３１ , shear stiffness (transverse elastic constant): G １２ , G ２３ , G ３１ The left subscript of these elastic constants indicates the surface of interest, and the right subscript indicates the direction in which the force is acting.

[0068] Figure 4 shows the elastic constants determined by this method, the elastic constants calculated by a uniaxial tensile test, and the catalogue values ​​for the SUS304 test piece. From these results, it can be seen that the determination results were in harmony with the results of mechanical testing methods such as uniaxial tensile tests. Note that, since the thickness of the object was not sufficient, the E １１ ya ν １２Although it is difficult to determine the elastic constants in the thickness direction, such as the thickness direction, this method can be determined without being affected by the three-dimensional shape of the object. As a result, it is clear that there is some anisotropy in the measured specimen. From the above, this method is considered to be able to appropriately determine the elastic constants, since it obtains values ​​that are almost the same as those obtained for objects in which independent elastic constants in some directions can be obtained by tensile tests. It can also be inferred that this method has high validity for independent elastic constants that are difficult to obtain by other tensile tests.

[0069] Figure 5 shows an example of a contour diagram representing the measured vibration modes and the calculated estimated vibration modes of the SUS304 test specimen used in the experiment. In this diagram, the measured resonant frequencies (actual values) and the corresponding measured vibration modes are shown on the upper side, while the estimated resonant frequencies (analysis values ​​(simulation values)) and the corresponding measured vibration modes are shown on the lower side. In this diagram, each vibration mode is actually visualized and output as an RGB value, but in this diagram, the RGB values ​​are shown in grayscale. Furthermore, the elastic parameters used in calculating the illustrated estimated resonant frequencies and estimated vibration modes are the values ​​determined when the elastic parameter evaluation value satisfies the set conditions.

[0070] Comparing the contour diagram of the measured vibration mode with 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.

[0071] [Functions and Effects of the Embodiment] The information processing device 100 (for example, an example of an information processing device) in this embodiment includes a measurement result acquisition unit 110 (for example, an example of an acquisition unit) that acquires measurement results obtained by measuring 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 a resonance frequency), and an elastic constant determination unit 120 (for example, an example of a determination unit) that determines an elastic constant based on elastic parameters (for example, an example of a plurality of input elastic values) and the measurement results, and the determination unit determines an elastic constant based on a finite element method analysis processing result (for example, an estimated elastic constant of the object estimated based on a plurality of input elastic values). This shows an example of a configuration in which a contour diagram (e.g., an example of a first contour diagram) of an estimated vibration mode is created based on the resonance frequency and estimated vibration mode (e.g., an example of a second contour diagram), a contour diagram of a measured vibration mode is created based on the resonance frequency and vibration mode based on the measurement results, an elastic parameter update process (e.g., an example of updating input elasticity values) using GA is performed based on the distance (e.g., an example of similarity) between the first contour diagram and the second contour diagram, and an elastic constant is presented based on the input elasticity value that satisfies the number of generations (e.g., an example of a setting condition) of the GA. With this configuration, an estimated vibration mode at an estimated resonance frequency estimated based on multiple input elasticity values ​​can be compared with a vibration mode at a resonance frequency based on the measurement results via the contour diagram. Then, the input value is repeatedly updated based on the similarity of the contour diagram and an elastic parameter evaluation function (the sum of the squared 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, it is possible to more easily present elastic constants even for objects with complex vibration modes for which determining elastic constants using conventional methods has been difficult or required cumbersome measurements.

[0072] Furthermore, in this embodiment, the vibration mode comparison unit 150 (e.g., an example of a determination unit) meshes the first contour map and the second contour map, obtains a measured vibration vector and an estimated vibration vector (e.g., an example of a vector) based on the RGB values ​​of the mesh (e.g., an example of the color of the mesh), and calculates the similarity based on the vectors. With this configuration, the similarity can be calculated from the vector based on the color of the mesh of the contour map, and the similarity can be calculated more appropriately.

[0073] In addition, this embodiment shows an example of a configuration in which the similarity between the first contour map and the second contour map (for example, an example of similarity) is cosine similarity. With this configuration, the similarity can be calculated quickly and appropriately using cosine similarity.

[0074] In addition, this embodiment shows an example of a configuration in which the elastic parameter setting unit 130 performs error processing on the elastic parameter evaluation function that evaluated the vibration mode similarity rate (e.g., an example of similarity) and resets the input elasticity value when the vibration mode similarity rate (e.g., an example of similarity) is smaller than a predetermined rate (e.g., an example of a set value) or is equal to or less than the set value. With such a configuration, the input elasticity value can be reset based on the similarity, thereby speeding up processing.

[0075] In addition, this embodiment shows an example of a configuration in which the output unit includes an output unit that outputs the first contour diagram and the second contour diagram side by side for each vibration mode having a similar resonance frequency (for example, an example of a comparative output), and outputs the second contour diagram that is updated in accordance with the update of the input elasticity value. With such a configuration, it is possible to compare and check the second contour diagram that changes in accordance with the update of the input elasticity value with the first contour diagram, and to check whether the update of the input elasticity value is proceeding appropriately.

[0076] [First Modification] In the above embodiment, the similarity between the measured vibration vector and the estimated vibration vector is determined using cosine similarity in the vibration mode comparison process, but this is not limited to this. For example, the vibration mode comparison unit 150 may determine that the measured vibration vector and the estimated vibration vector at a predetermined resonance frequency are similar if the distance (e.g., L2 norm) between the measured vibration vector and the estimated vibration vector is smaller than a threshold. Note that the vibration mode comparison unit 150 may determine that the measured vibration vector and the estimated vibration vector at a predetermined resonance frequency are similar if the distance between the measured vibration vector and the estimated vibration vector is equal to or smaller than a threshold.

[0077] This allows the determination to be made based on the similarity taking into account the magnitude of the measured vibration vector and the magnitude of the estimated vibration vector, which may improve the reliability of the similarity.

[0078] [Second Modification] In the above embodiment, the vibration mode comparison process generates a contour diagram using a spatial distribution representation of the amplitude peak values ​​of each vibration mode. However, this is not limiting. 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, for example, the amplitude and phase of the vibration mode.

[0079] This makes it possible to appropriately compare the measured vibration mode with the estimated vibration mode even in a special vibration mode in which it is difficult to determine the similarity based on amplitude alone.

[0080] [Third Modification] In the above embodiment, the similarity is calculated so as to match the spatial distribution representation of the estimated vibration mode with the measured vibration mode measured by the sample vibration mode measurement device 200. However, this is not limiting. 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, the x-y plane, the y-z plane, and the 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 planes (the x-y plane, the y-z plane, and the x-z plane in this example) as those mapped by the measurement result acquisition unit 110. Then, the vibration mode comparison unit 150 may compare the spatial distribution representation (contour diagram) of the mapped measured vibration mode with the spatial distribution representation (contour diagram) of the estimated vibration mode on each plane.

[0081] Figure 6 illustrates an example of mapping between measured vibration modes and estimated vibration modes. The left side of the figure shows object data in which the three-dimensional measured vibration mode of the object is visualized in the center, with contour diagrams of the measured vibration modes mapped onto the x-y plane, y-z plane, and x-z plane, respectively, around the object data. The right side of the figure shows object data in which the three-dimensional estimated vibration mode is visualized in the center, with contour diagrams of the measured vibration modes mapped onto the x-y plane, y-z plane, and x-z plane, respectively, around the object data.

[0082] In the vibration mode comparison process, the vibration mode comparison unit 150 calculates the xy plane vibration mode similarity rate based on, for example, a contour diagram of the measured vibration mode on the xy plane and a contour diagram of the estimated vibration mode on the xy plane. If 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 update unit 160 determines that the measured vibration mode and the estimated vibration mode are not similar. Then, the vibration mode comparison unit 150 omits calculation of the vibration mode similarity rate on other planes. If it is determined that the measured vibration mode and the estimated vibration mode are similar on all planes, the elastic parameter update unit 160 determines that the measured vibration mode and the estimated vibration mode are similar.

[0083] The planes onto which the images are mapped are not limited to the xy plane, yz plane, and xz plane, but may be any three planes that are orthogonal to each other in a three-dimensional space.

[0084] In the above embodiment, the spatial distribution representation of the vibration mode as seen from the direction in which the sample vibration mode measurement device 200 observes the object is used as the comparison target. However, in this modified example, even when comparison from the observation direction is difficult, it is possible to change the observation viewpoint and perform comparison by mapping onto an appropriate plane. For example, the orthogonal plane to which the mapping is to be performed may be determined so that the planar area of ​​the three-dimensional shape of the object 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 with a complex three-dimensional shape.

[0085] In this modified example, the measurement result acquisition unit 110 (e.g., an example of an acquisition unit) projects the measured vibration mode (e.g., an example of the three-dimensional deformation of the object) onto the x-y plane, the y-z plane, and the x-z plane (e.g., an example of three mutually orthogonal planes), and the elastic constant determination unit 120 (e.g., an example of a determination unit) determines the elastic constant based on the measured vibration mode (e.g., an example of the vibration mode) and the estimated vibration mode (e.g., an example of the estimated vibration mode) in each of the three planes. In an extremely complex shape where the shape of one surface differs significantly from that of its back surface, there is a risk of determining an erroneous elastic constant based on the mode similarity of only one surface being measured. However, by determining the similarity from any angle, the accuracy of the elastic constant can be accurately determined even for an object with an extremely complex shape. With this configuration, by comparing the three-dimensional deformation of the object on each of the three projected planes, the comparison between the vibration mode and the estimated vibration mode can be performed more appropriately and quickly, resulting in a faster and more accurate determination of the elastic constant.

[0086] In the above embodiment, a contour diagram is used as an example of the spatial distribution representation of the measured vibration mode and the estimated vibration mode. However, the present invention is not limited to this. For example, a heat map may be generated without drawing three-dimensional position boundaries.

[0087] In order to represent the change over time in amplitude in the measured vibration mode and the estimated vibration mode, for example, a flow map may be generated.

[0088] Then, for example, the heat map or flow map may be divided into meshes, and the measured vibration vector and estimated vibration vector may be calculated based on the color information within each mesh, and the similarity may be calculated.

[0089] [Fifth Modification] In the above embodiment, in the initial elastic parameter setting process, the elastic parameter setting unit 130 randomly sets the elastic parameters, but this is not limited to this. For example, after determining the elastic constants, the elastic constant determination unit 120 may store the material, three-dimensional shape, and elastic constants of the object in a storage unit (not shown). Then, for example, when an object of the same or similar material and the same or similar three-dimensional shape is input as a new object of analysis, the elastic parameter setting unit 130 may set the elastic parameters by referring to past elastic constant determination results stored in the storage unit.

[0090] This allows the elastic constants of the same object to be determined instantly based on past determination results, and also creates the possibility of shortening the time required to determine the elastic constants of similar objects.

[0091] In addition, in the elastic constant output process, the elastic constant determination unit 120 may output the elastic constant based on, for example, the elastic parameter whose elastic parameter evaluation value satisfies the set condition and the elastic constant of the same or similar object determined in the past.

[0092] [Sixth Modification] In the above embodiment, the information processing device 100 ends the processing once the elastic constants are determined, but this is not limiting. As a non-limiting example, the information processing device 100 may evaluate each coefficient of the determined elastic constants in a determination unit (not shown) to determine the material properties of the object.

[0093] For example, assume that the results shown in Tables 1 to 3 below are obtained.

[0094] In the results of Table 1, E, ν, and G are all the same value. １１ = E ２２ = E ３３ In the case where the Young's modulus, Poisson's ratio, and shear strength are all considered to be the same, the judgment unit judges the specimen to be isotropic. ２２ = E３３ However, E １１ are different (similarly, two of ν and G are the same, and one is different). １１ ≠E ２２ = E ３３ (E １１ = E ２２ ≠E ３３ , E ２２ ≠E １１ = E ３３ ), when two of the values ​​of Young's modulus, Poisson's ratio, and shear stiffness are considered to be the same and one of them is different, the judgment unit judges the material to be an in-plane isotropic material. On the other hand, when all of the values ​​of Young's modulus, Poisson's ratio, and shear stiffness are considered to be different, as in Table 3, the judgment unit judges the material to be orthotropic. The judgment result of the judgment unit may then be output by an output unit (not shown).

[0095] In this modified example, the degree of freedom of the elastic parameter is nine (for example, one example in which the plurality of input elastic values ​​are nine variables), and the determination unit determines whether the object is an orthotropic material, an in-plane isotropic material, or an isotropic material based on the elastic constants determined by the determination unit, and the output unit outputs the determination result. With this configuration, it is possible to appropriately determine the properties of the object (whether it is an isotropic material or an orthotropic material that contains an isotropic material).

[0096] [Seventh Modification] In the above embodiment, low-viscoelastic materials such as metals and ceramics were used as examples of the material type of the object, but the object is not limited to these. For example, the object may be a material type having viscoelastic properties (e.g., carbon fiber reinforced plastics (CFRP)) that is composed of a component that is a perfect elastic body (or can be considered a perfect elastic body) (e.g., carbon fiber) and a component that has viscoelastic properties (e.g., matrix resin). A viscoelasticity acquisition method for such an object is described below.

[0097] 7 is a flowchart showing an example of the information processing procedure in this modified example. Note that the flowchart described below merely shows an example of the information processing procedure in this modified example, and other steps may be added or some steps may be deleted. Also, some of the steps in the flowchart may be interchanged and executed. Furthermore, steps that are the same as those described above may be assigned the same reference numerals, and their explanation may be omitted.

[0098] For example, the elastic constant determination unit 120 executes a sample shape acquisition process (S120) and then executes a viscoelastic property acquisition process (S310). In the viscoelastic property acquisition process, the elastic constant determination unit 120 uses a viscoelasticity measurement device (dynamic viscoelasticity tester) (not shown) to create a viscoelastic component of the object (e.g., a test piece consisting only of a matrix resin in the case of CFRP) and acquires dynamic viscoelasticity test results for the component. Based on the dynamic viscoelasticity test results at multiple frequencies, the elastic constant determination unit 120 then calculates viscoelastic properties over a wide converted frequency band using, for example, a time-temperature conversion law. This allows the viscoelastic properties of the viscoelastic component of the material constituting the object to be measured to be acquired at frequencies corresponding to the measured resonant frequency of the object acquired in the sample vibration mode measurement result acquisition process.

[0099] The acquisition of the dynamic viscoelasticity test results and the calculation of the viscoelasticity characteristics may be performed by the measurement result acquisition unit 110.

[0100] For example, after executing the initial elastic parameter setting process (S130), the elastic constant determination unit 120 executes the complex equivalent stiffness calculation process (S320).

[0101] 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., a 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 and whose elastic parameters have been set in the initial elastic parameter setting process. Hereinafter, the representative volume element model may be abbreviated as "RVE (Representative Volume Element)."

[0102] Next, the elastic constant determination unit 120 analyzes, for example, the distortion when loads are applied to the created representative volume element model in different directions at various frequencies using the finite element method, and then calculates, for example, the complex equivalent stiffness based on the analysis results for the representative volume element model.

[0103] For example, once the complex equivalent stiffness of the representative volume element model is calculated, the elastic constant determination unit 120 executes a generalized Maxwell model coefficient identification process (S330). Hereinafter, the generalized Maxwell model may be abbreviated as "GMM." Note that the generalized Maxwell model is not limited to the generalized Maxwell model, and a Zener model (a model in which a spring element is added in parallel to the generalized Maxwell model) or the like may also be used.

[0104] In the generalized Maxwell model coefficient identification process, the elastic constant determination unit 120 identifies each coefficient of the GMM based on, for example, the complex equivalent stiffness using, for example, a genetic algorithm (GA).

[0105] More specifically, the storage modulus C' is assumed to be the following formula (1), and the loss modulus C'' is assumed to be the following formula (2). where ω is the frequency and C ０ is the elastic coefficient. Also, i indicates each Maxwell element, and c ｉ =C ｉ / C ０ is the normalized relaxation coefficient, τ ｉ = μ ｉ / C ｉ and represent the relaxation time, respectively.

[0106] At this time, for example, each coefficient C is set so that the error function defined by the following equation is less than or equal to the threshold value. ｉ is calculated using a genetic algorithm or the like. where y'model is the storage modulus of the GMM, y'exp is the storage modulus of the RVE, y''model is the loss modulus of the GMM, and y''exp is the loss modulus of the RVE.

[0107] Each coefficient C ｉ When the storage modulus and loss modulus in the GMM of the object are identified based on the elastic parameters, the analysis unit 140 performs an analysis process using, for example, the finite element method based on the elastic parameters, the storage modulus, and the loss modulus (S140).

[0108] 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, for example, step S320. 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.

[0109] If it is determined that the elastic parameter evaluation value satisfies the set condition (S200: YES), the elastic constant determination unit 120 executes an elastic constant output process (S210). In the elastic constant output process, the elastic constant determination unit 120 outputs, for example, the elastic parameter at that time, the storage modulus of the GMM, and the loss modulus of the GMM as elastic constants.

[0110] It should be noted that the storage modulus and the loss modulus are not limited to being identified by the GMM, and may be optimized simultaneously with the elastic parameters using, for example, the Williams-Landel-Ferry (WLF) equation.

[0111] In this modification, the elastic constant determination unit 120 (e.g., an example of a calculation unit) of the information processing device calculates the storage modulus and loss modulus (e.g., an example of elastic parameter values) in the GMM based on the RVE (e.g., an example of an analytical model) of a CFRP having viscoelastic properties (e.g., an example of an object having viscoelasticity), and presents the elastic constants based on a plurality of input elastic values, elastic parameter values, and measurement results. As a result, even for an object having viscoelasticity, the elastic constants can be determined by calculating the elastic parameter values ​​based on the analytical model of the object and updating, for example, the input elastic value and the elastic parameter values.

[0112] In addition, in this modification, the object is composed of a matrix resin (e.g., an example of a first component having viscoelasticity) and carbon fiber (e.g., an example of a second component different from the first component). The multiple input elasticity values ​​are input elasticity values ​​of the second component. This makes it possible to present the elastic constants of an object that is a mixture of a first component having viscoelasticity and a second component different from the first component, and whose elastic constants are difficult to determine.

[0113] Furthermore, in this modification, the information processing device includes a measurement result acquisition unit 110 (e.g., an example of a viscoelastic property acquisition unit) that acquires dynamic viscoelasticity test results and viscoelastic properties in a wide converted frequency band (e.g., an example of the viscoelastic properties of the first component), and calculates elastic parameter values ​​based on an analytical model based on the viscoelastic properties and multiple input elasticity values. This allows the elastic constant of the object to be determined by measuring the viscoelastic properties of the first component and the resonant frequency and vibration mode at the resonant frequency of the object composed of the first component and the second component.

[0114] [Other Embodiments] In another aspect of the present invention, an information processing device includes an acquisition unit that acquires measurement results of measuring the resonance frequency and the vibration mode at the resonance frequency of an object, and a determination unit that determines an elastic constant based on a plurality of input elastic values ​​and the measurement results, and the determination unit updates the input elastic value based on a spatial distribution expression based on the estimated resonance frequency and estimated vibration mode of the object estimated based on the plurality of input elastic values, and a spatial distribution expression based on the resonance frequency and vibration mode based on the measurement results, and determines the elastic constant based on the input elastic value that satisfies a set condition.

[0115] In addition, the spatial distribution representation may be a contour diagram, and the determination unit may calculate the similarity based on a vector calculated based on the contour diagram, and if the similarity is smaller than a set value or equal to or less than the set value, may reset the input elasticity value.

[0116] The determination unit may also calculate the vector based on the color of each predetermined mesh in the contour diagram.

[0117] The determination unit may also update the input elasticity value based on a genetic algorithm.

[0118] In the present invention, the type of material to be measured is not limited to low-viscoelastic materials such as metals and ceramics, but high-viscoelastic materials such as polymeric materials, which are subject to vibration damping, can also be measured. However, the elastic constants of an object such as a polymeric material can be determined by measuring the dynamic elastic modulus of the object, experimentally obtaining the relationship between the load frequency and the reference temperature for the storage modulus and loss modulus obtained from the dynamic elastic modulus, and then applying the finite element analysis of the present invention.

[0119] REFERENCE SIGNS LIST 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

1. an acquisition unit that acquires a measurement result obtained by measuring a resonance frequency of an object and a vibration mode at the resonance frequency; A determination unit that presents an elastic constant based on a plurality of input elasticity values ​​and the measurement result; Equipped with The determination unit is creating a first contour diagram for each estimated vibration mode at an estimated resonant frequency of the object using the 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; meshing the first contour map and the second contour map, and determining a vector based on the color of the mesh; updating the input elasticity value by a genetic algorithm based on a similarity between the first contour diagram and the second contour diagram obtained based on the vector; The elastic constant is presented based on the input elasticity value that satisfies a set condition. Information processing device.

2. The similarity is a cosine similarity. The information processing device according to claim 1 .

3. The determination unit resets the input elasticity value when the similarity is smaller than a set value or equal to or less than the set value. The information processing device according to claim 1 .

4. 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 .

5. The plurality of input elasticity values ​​are nine variables, a determination 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 determination unit; an output unit that outputs a determination result of the determination unit; Equipped with The information processing device according to claim 1 .

6. an output unit that outputs the first contour diagram and the second contour diagram so as to be comparable; The output unit outputs the second contour diagram that is updated in response to updating of the input elasticity value. The information processing device according to claim 1 .

7. The object is an object having viscoelasticity, a calculation unit that calculates an elasticity parameter value related to the object based on an analytical model of the object, The determination unit presents an elastic constant based on the plurality of input elastic values, the elastic parameter value, and the measurement result. The information processing device according to claim 1 .

8. the object is composed of a first component having viscoelasticity and a second component different from the first component, The plurality of input elasticity values ​​are a plurality of input elasticity values ​​related to the second structure. The information processing device according to claim 7.

9. 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 8.

10. A measurement device that measures a resonant frequency of an object and a vibration mode at the resonant frequency; An information processing device according to any one of claims 1 to 9; A system comprising:

11. A program to be executed by an information processing device including: an acquisition unit that acquires a measurement result of measuring a resonance frequency of an 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 result, The determination unit, creating a first contour diagram for each estimated vibration mode at an estimated resonant frequency of the object using the 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; meshing the first contour map and the second contour map and determining a vector based on a color of the mesh; updating the input elasticity value by a genetic algorithm based on a similarity between the first contour diagram and the second contour diagram obtained based on the vector; Presenting the elastic constant based on the input elasticity value that satisfies a set condition; A program for executing.

12. 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; meshing the first contour map and the second contour map and determining a vector based on a color of the mesh; updating the input elasticity value by a genetic algorithm based on a similarity between the first contour diagram and the second contour diagram obtained based on the vector; Presenting the elastic constant based on the input elasticity value that satisfies a set condition; Presentation methods including: