Iron loss estimation device, iron loss estimation method and iron loss characteristic creation method

Abstract

To estimate the iron loss without using numerical calculation.SOLUTION: An iron loss estimation device 1 that estimates the iron loss of a structure formed from electrical steel comprises a characteristic value acquisition unit 22 that acquires a characteristic value related to the crystal orientation from analysis data that analyzes the evaluation cross-section of the structure to be evaluated, and an iron loss characteristic value acquisition unit 23 that acquires an iron loss characteristic value corresponding to the characteristic value related to the crystal orientation acquired by the characteristic value acquisition unit 22 from iron loss characteristic information in which the characteristic value related to the crystal orientation and the iron loss characteristic value are pre-associated.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present disclosure relates to an iron loss estimation device, an iron loss estimation method, and an iron loss characteristic creation method. [Background technology]

[0002] For example, punching is often used to process electromagnetic steel sheets used in rotating electrical machines such as motors and generators into a predetermined shape. Although punching has cost advantages over other manufacturing methods, it has the problem of increased iron loss due to processing. The increase in iron loss due to punching is mainly caused by plastic deformation and introduction of residual stress at the processing edge during punching, shape changes at the processing edge, etc., which depend on the edge shape of the punching die, clearance, processing speed, etc.

[0003] The edge shape of the punching die changes due to die wear during mass production. Therefore, appropriate manufacturing control is important to control product performance. One method for appropriate manufacturing control is to estimate the iron loss characteristic value of the product and evaluate the performance based on the estimated iron loss characteristic value.

[0004] For example, Patent Document 1 discloses a method for calculating the equivalent plastic strain distribution and residual stress distribution that occur in a non-uniform manner in the plate thickness direction near the punched end face due to punching based on a numerical analysis of the punching process, and for calculating the amount of increase in iron loss due to the punching process using an evaluation index obtained as a result of the calculation. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2015-193926 A Summary of the Invention [Problem to be solved by the invention]

[0006] In the method of calculating the iron loss increase described in Patent Document 1, it is important to input values ​​as accurate as possible as input data for numerical calculations. However, some input data, such as die clearance, is not easily available, making it difficult to input accurate values.

[0007] The present disclosure has been made in consideration of the above circumstances, and has an object to provide an iron loss estimation device, an iron loss estimation method, and an iron loss characteristics creation method that are capable of estimating iron loss without using numerical calculations. [Means for solving the problem]

[0008] One aspect of the present disclosure is an iron loss estimation device that estimates iron loss of a structure formed from electromagnetic steel sheets, the iron loss estimation device including: a characteristic value acquisition unit that acquires a characteristic value related to crystal orientation from analysis data obtained by analyzing an evaluation cross-section of the structure to be evaluated; and an iron loss characteristic value acquisition unit that acquires, from iron loss characteristic information in which a characteristic value related to crystal orientation and an iron loss characteristic value are previously associated with each other, the iron loss characteristic value that corresponds to the characteristic value related to crystal orientation acquired by the characteristic value acquisition unit.

[0009] One aspect of the present disclosure is an iron loss estimation method for estimating iron loss of a structure formed from electromagnetic steel sheets, the iron loss estimation method including: a characteristic value acquisition step of acquiring a characteristic value related to crystal orientation from analysis data obtained by analyzing an evaluation cross-section of the structure to be evaluated; and an iron loss characteristic value acquisition step of acquiring, from iron loss characteristic information in which a characteristic value related to crystal orientation and an iron loss characteristic value are previously associated with each other, an iron loss characteristic value corresponding to the characteristic value related to crystal orientation acquired in the characteristic value acquisition step.

[0010] One aspect of the present disclosure is a program for causing a computer to function as the iron loss estimation device.

[0011] One aspect of the present disclosure is an iron loss characteristic creation method for creating iron loss characteristic information for estimating iron loss in a structure formed from electromagnetic steel sheets, the iron loss characteristic creation method including a test piece creation step of creating a plurality of test pieces with different iron loss characteristic values, an iron loss measurement step of measuring the iron loss characteristic value of each of the test pieces, an analysis data acquisition step of acquiring analysis data obtained by analyzing an evaluation cross section obtained by cutting each of the test pieces, and a characteristic creation step of acquiring a characteristic value related to crystal orientation from the analysis data of each of the test pieces, and creating iron loss characteristic information using the acquired characteristic value and the iron loss characteristic value. Effect of the Invention

[0012] According to the present disclosure, an effect is achieved in that it is possible to estimate iron loss without using numerical calculations. [Brief description of the drawings]

[0013] [Figure 1] 1 is a flowchart showing an example of a procedure of an iron loss characteristic creation method according to an embodiment of the present disclosure. [Diagram 2] FIG. 2 is a diagram showing an example of a test piece used in a method for producing an iron loss characteristic according to an embodiment of the present disclosure. [Diagram 3] FIG. 2 is a diagram illustrating an example of a KAM map according to an embodiment of the present disclosure. [Figure 4] 10 is a diagram for explaining an appropriate range of a threshold value φ used in calculating an orientation difference characteristic value in an iron loss characteristic creation method according to an embodiment of the present disclosure. FIG. [Diagram 5] FIG. 4 is a diagram illustrating an example of iron loss characteristic information according to an embodiment of the present disclosure. [Figure 6] FIG. 2 is a diagram illustrating an example of a hardware configuration of an iron loss estimation device according to an embodiment of the present disclosure. [Figure 7] FIG. 2 is a functional configuration diagram showing functions of an iron loss estimation device according to an embodiment of the present disclosure. [Figure 8] 4 is a flowchart illustrating an example of a processing procedure of an iron loss estimation method according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, an iron loss estimation device, an iron loss estimation method, and an iron loss characteristics creation method according to an embodiment of the present disclosure will be described with reference to the drawings. The iron loss estimation device 1 (see FIG. 7) according to this embodiment is a device that estimates the iron loss value (magnetic characteristics) of a structure (evaluation target) punched out of an electromagnetic steel sheet. Examples of the structure include a transformer, a core material of a motor (generator), such as a rotor and a stator.

[0015] Before describing the iron loss estimation device 1 of this embodiment, a method for creating iron loss characteristic information used by the iron loss estimation device 1 will be described below.

[0016] FIG. 1 is a flowchart showing an example of the procedure of the iron loss characteristic creating method according to this embodiment. First, a plurality of test pieces having different shapes are prepared (SA1: test piece preparation step). The test piece is preferably made using the same steel type as the electromagnetic steel sheet used in the structure to be evaluated, but is not limited thereto. For example, if the grade of the electromagnetic steel sheet is the same, the test piece may be made using an electromagnetic steel sheet of a different steel type. The test piece is made according to a standard such as JIS C 2550, for example, with a thickness of the structure to be evaluated. For example, since the JIS specifies the recommended number of test pieces for each thickness, the test piece is made by punching a laminated electromagnetic steel sheet in which thin plate-like electromagnetic steel sheets are laminated in a number corresponding to the thickness (for example, about 10 to 80 sheets). Examples of punched shapes include an Epstein test piece and a ring test piece. FIG. 2 is a diagram showing an example of a ring test piece. Various conditions such as the thickness of the test piece (for example, t in FIG. 2) and the punched shape (for example, D / 2, d / 2, Lp in FIG. 2) may be appropriately determined according to the structure to be evaluated. In this embodiment, as an example, a plurality of ring test pieces having different inner diameters (d / 2 in FIG. 2) and outer diameters (D / 2 in FIG. 2) are prepared.

[0017] Next, the iron loss characteristic value of each test piece is measured (SA2: iron loss measurement step). Examples of the iron loss characteristic value include the iron loss value, the amount of iron loss increase, and the iron loss deterioration rate. In this embodiment, the case where the iron loss deterioration rate ΔW, which is the value obtained by dividing the iron loss value (W / kg) after punching by the iron loss value (W / kg) before punching, is used as the iron loss characteristic value will be described as an example.

[0018] The iron loss can be measured by any known method. Examples include the wattmeter method, the bridge method, and the calorimeter method. The wattmeter method is a method in which an AC current is passed through a coil to obtain the loss from the power measurement, the bridge method is a method in which the AC impedance of the coil is measured to obtain the loss, and the calorimeter method is a method in which an AC current is passed through a coil to obtain the loss from the heat generation amount. In addition, the measurement conditions for the iron loss (magnetic flux density, frequency) can be set to appropriate values ​​as appropriate.

[0019] Next, analytical data is obtained by analyzing the evaluation cross-section cut from each test piece (SA3: analytical data acquisition process). For example, an analytical test is performed on the crystal orientation of the evaluation cross-section of each test piece. Here, the evaluation cross-section is preferably a vertical cross-section (longitudinal cross-section) cut perpendicular to the magnetic flux direction. Another example of an analytical test is electron backscattered diffraction measurement (EBSD: Electron Back Scattered Diffraction Pattern). When performing EBSD, attention should be paid to edge sagging between the embedding resin and the material. The measurement step size should be sufficiently small compared to the crystal grain size, and an optimal value should be selected.

[0020] In this embodiment, the analysis data is a local misorientation distribution of the evaluation cross section, specifically, a KAM (Kernel Average Misorientation) map. The KAM map is a map showing the misorientation between a certain measurement point and a site adjacent to or near the measurement point. The larger the distortion, the larger the misorientation, and when there is no distortion, the misorientation is zero. The KAM value corresponds to the crystal rotation between the measurement points and qualitatively corresponds to the magnitude of local deformation. Therefore, the KAM value has a strong correlation with the deterioration rate of iron loss.

[0021] An example of a KAM map is shown in FIG. 3. FIG. 3 shows a KAM map when the longitudinal section A of the ring piece shown in FIG. 2 is used as the evaluation section. The KAM map shown in FIG. 3 illustrates a case where KAM1st, which is the crystal orientation difference between the first neighboring measurement points, is used, but KAM2nd, KAM3rd, and KAM4th may also be used, which are the crystal orientation differences between the second neighboring measurement points, the third neighboring measurement points, and the fourth neighboring measurement points, respectively, and the optimal one may be selected appropriately. In FIG. 3, the minimum value is set to 0 and the maximum value is set to 5.

[0022] Next, the KAM map, which is the analysis data of each test piece, and the iron loss deterioration rate are used to create iron loss characteristic information (SA4: characteristic creation step). First, the KAM map is processed to obtain a characteristic value related to the crystal orientation. In this embodiment, the characteristic value related to the crystal orientation is the orientation difference characteristic value KAMot(φ) defined as follows:

[0023] KAMot(φ) = Area ratio where KAM value is equal to or greater than threshold φ in the evaluation section

[0024] Here, the threshold value φ can be set appropriately, but is preferably set to a value less than 3° for the following reasons. Fig. 4 is a diagram showing an example of the relationship between the orientation error characteristic value KAMot(φ) and the iron loss deterioration rate ΔW when the threshold φ is set to 1°, 2°, and 3°. Fig. 4(a) shows the case when the threshold φ is set to 1°, (b) shows the case when the threshold φ is set to 2°, and (c) shows the case when the threshold φ is set to 3°. In Fig. 4, CASE1 to CASE4 are measurement results when test pieces of the same steel type were used and the excitation conditions were each different.

[0025] As shown in Figures 4(a) and (b), when the threshold value φ is set to less than 3°, there is a strong correlation between the orientation difference characteristic value KAMot(φ) and the iron loss degradation rate ΔW, and this relationship can be expressed as a function. In contrast, as shown in Figure 4(c), when the threshold value φ is set to 3° or more, there is no correlation between the orientation difference characteristic value KAMot(φ) and the iron loss degradation rate ΔW, and it is no longer possible to find a constant relationship between the orientation difference characteristic value KAMot(φ) and the iron loss degradation rate. This is thought to be because the sample is more susceptible to the effects of sample adjustments such as edge droop. From the above results, it can be seen that the threshold value φ should be set to less than 3°, preferably 2° or less, and more preferably 1° or less.

[0026] In the characteristic creation step, for example, the orientation difference characteristic value KAMot(φ) and the iron loss deterioration rate acquired for each test piece are statistically processed to obtain a calibration curve (iron loss characteristic information). As a result, for example, the iron loss characteristic information (calibration curve) shown in FIG. 5 can be obtained.

[0027] Here, the process of creating the iron loss characteristic information may be performed manually by a person, or may be automatically created using an information processing device such as a computer. When using an information processing device, application software may be constructed that provides the iron loss degradation rate and KAM map of each test piece as input information and automatically creates the iron loss characteristic information from this input information. In addition, FIG. 5 shows the calibration curve as a linear function, but this is not limited to this example. For example, the calibration curve may be obtained as a polynomial function. In addition, the iron loss characteristic information may be created as a function, or as a table or a map.

[0028] Next, the iron loss estimation device 1 and the iron loss estimation method according to the present embodiment will be described. [Hardware configuration of iron loss estimation device 1] Fig. 6 is a diagram showing an example of a hardware configuration of an iron loss estimation device 1 according to an embodiment of the present disclosure. As shown in Fig. 6, the iron loss estimation device 1 is a so-called computer, and includes, for example, a CPU (Central Processing Unit: processor) 11, a main memory (Main Memory) 12, a secondary storage (Secondary storage: memory) 13, and the like.

[0029] The main memory device 12 is composed of writable memory such as a cache memory or a RAM (Random Access Memory), and is used as a working area for reading out the execution program of the CPU 11, writing processing data by the execution program, and the like. The secondary storage device 13 is a non-transitory computer readable storage medium, such as a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, or a semiconductor memory. The iron loss estimation device 1 may further include an external interface 14 which is an interface for connecting to an external device, a communication interface 15 for transmitting and receiving information to and from other devices, an input device 16 such as a keyboard or a pointing device, and a display 17 for displaying analysis results, etc.

[0030] [Functions of the iron loss estimation device] Fig. 7 is a functional configuration diagram showing functions of the iron loss estimation device 1 according to this embodiment. A series of processes for realizing various functions is stored in the secondary storage device 13 in the form of a program, for example, and the CPU 11 reads this program into the main storage device 12 and executes information processing and arithmetic processing to realize various functions. Note that the program may be installed in the secondary storage device 13 in advance, may be provided in a state stored in a computer-readable storage medium, or may be distributed via wired or wireless communication means. The computer-readable storage medium may be a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like.

[0031] As shown in FIG. 7, the iron loss estimation device 1 includes a characteristic information storage unit 21, a characteristic value acquisition unit 22, an iron loss characteristic value acquisition unit 23, and a performance evaluation unit 24. Iron loss characteristic information in which a characteristic value related to crystal orientation and an iron loss characteristic value are previously associated with each other is stored in the characteristic information storage unit 21. Specifically, the iron loss characteristic information created by the above-mentioned iron loss characteristic creating method is stored.

[0032] The characteristic value acquisition unit 22 acquires characteristic values ​​related to crystal orientation from analysis data obtained by analyzing an evaluation cross section of a structure to be evaluated. For example, a structure to be evaluated can be a steel plate member obtained by punching a laminated steel plate used in a product using the same method as the product. This steel plate member is cut in the lamination direction at an arbitrary position, and an EBSD measurement is performed on the cut surface to obtain a KAM map. Then, the KAM map data is processed to obtain an orientation difference characteristic value KAMot(φ) of the cut surface. Here, the threshold φ is the same as that of the iron loss characteristic information stored in the characteristic information storage unit 21 (for example, φ=1°).

[0033] The iron loss characteristic value acquisition unit 23 acquires the iron loss deterioration rate corresponding to the orientation difference characteristic value KAMot(φ) acquired by the characteristic value acquisition unit 22 from the iron loss characteristic information stored in the characteristic information storage unit 21. This makes it possible to estimate the iron loss deterioration rate of the structure to be evaluated.

[0034] The performance evaluation unit 24 performs a performance evaluation of the structure to be evaluated, for example, based on the iron loss deterioration rate. For example, it determines whether the iron loss value of the structure is equal to or less than a preset iron loss tolerance, and if it is equal to or less than the iron loss tolerance, it determines that the structure is normal. On the other hand, if the iron loss deterioration rate exceeds the iron loss tolerance, it notifies the user of a performance degradation, etc. This enables the worker to take appropriate measures, such as replacing the die used for punching, performing maintenance, etc.

[0035] Furthermore, the performance evaluation unit 24 may perform an evaluation of the variation in the iron loss deterioration rate due to manufacturing variations by statistically evaluating the evaluation results of a plurality of structures. For example, the performance evaluation unit 24 may perform an evaluation of the variation in the iron loss deterioration rate by using the average value and standard deviation of the misorientation characteristic value KAMot(φ) obtained from the EBSD measurement results of a plurality of structures.

[0036] Next, an iron loss estimation method executed by the iron loss estimation device 1 according to this embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing an example of a processing procedure of the iron loss estimation method according to this embodiment.

[0037] First, the structure to be evaluated is cut, and an EBSD measurement is performed on the cut surface to obtain a KAM map of the cut surface, and an orientation difference characteristic value KAMot(φ) is obtained from the obtained KAM map (SB1). Next, an iron loss deterioration rate corresponding to the orientation difference characteristic value KAMot(φ) obtained in step SA1 is obtained from the iron loss characteristic information stored in the characteristic information storage unit 21 (SB2). Next, a performance evaluation of the structure to be evaluated is performed based on the iron loss deterioration rate (SB3). For example, it is determined whether or not the iron loss deterioration rate of the structure exceeds a preset iron loss allowable value, and if it does, a notification to that effect is given.

[0038] As described above, according to the iron loss estimation device, iron loss estimation method, and iron loss characteristic creation method of this embodiment, the iron loss deterioration rate corresponding to the orientation difference characteristic value KAMot(φ) of the structure to be evaluated is obtained by using iron loss characteristic information in which the orientation difference characteristic value KAMot(φ), which is a characteristic value related to crystal orientation, is associated in advance with the iron loss deterioration rate. Here, the orientation difference characteristic value (KAMot(φ)) is a parameter that has a strong correlation with the iron loss deterioration rate ΔW. Since the iron loss evaluation rate is estimated using such an orientation difference characteristic value, it is possible to improve the estimation accuracy of the iron loss deterioration rate of the structure to be evaluated. In addition, since no numerical calculation is used as disclosed in Patent Document 1, there is no need to obtain input information that is difficult to measure, such as clearance, and the effort required for iron loss estimation can be reduced.

[0039] Furthermore, according to the iron loss estimation device, the iron loss estimation method, and the iron loss characteristics creation method according to the present embodiment, for example, the following effects can be obtained. For example, in the past, when calculating the performance of a motor using electromagnetic steel sheets during trial operation, it was only possible to obtain comprehensive losses including copper loss, iron loss, mechanical loss (bearing loss, windage loss, etc.), stray loss (loss with unknown causes), etc., and it was difficult to evaluate each of these losses individually. For this reason, for example, when an abnormality such as excessive heat occurred, it was not possible to isolate the cause of the abnormality and it was difficult to take appropriate measures.

[0040] In contrast, according to the present embodiment, the iron loss of the structure to be evaluated can be estimated with higher accuracy than in the past. This makes it possible to evaluate the iron loss separately from other losses. As a result, when an abnormality occurs, it becomes possible to evaluate the iron loss separately from other losses. This makes it possible to estimate, for example, when excessive heat occurs, whether it is due to electromagnetic Joule heat or mechanical loss. This makes it possible to perform a highly accurate cause analysis and take rational measures. Furthermore, according to the iron loss estimation device, the iron loss estimation method, and the iron loss characteristics creation method of the present embodiment, it is possible to evaluate the influence of not only the punching process but also other iron loss degradation factors including manufacturing defects, in other words, other factors involving the introduction of strain, etc.

[0041] Although the present disclosure has been described above using the embodiments, the technical scope of the present disclosure is not limited to the scope described in the above embodiments. Various modifications or improvements can be made to the above embodiments without departing from the gist of the disclosure, and the forms in which such modifications or improvements are made are also included in the technical scope of the present disclosure. In addition, the above embodiments may be appropriately combined. Furthermore, the processing flow described in the above embodiment is also one example, and unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the present disclosure.

[0042] For example, in the above embodiment, the orientation difference characteristic value KAMot(φ) is used as the characteristic value related to the crystal orientation, but this is not limited thereto. For example, the characteristic value related to the crystal orientation may be another parameter that reflects the distortion caused by punching. The orientation difference characteristic value KAMot(φ) is an area ratio, but instead of this, a volume ratio may be used. In the case of a volume ratio, for example, a method may be used in which tissue distribution data in the cross-sectional depth direction is obtained while scraping the surface of the evaluation cross-section in the depth direction, and the volume ratio of the orientation difference characteristic value is calculated using analysis data of each evaluation cross-section. An example of a tissue field analysis method in the cross-sectional depth direction is the serial sectioning method.

[0043] In the above embodiment, the case where KAM is used as the orientation difference characteristic value is described as an example, but the present invention is not limited to this. For example, a calibration curve may be created using parameters calculated based on identified crystal orientation information such as GROD (Gross Reference Orientation Deviation), GAM (Grain Average Misorientation), and GND (Geometrically Necessary Dislocation).

[0044] In the above embodiment, the iron loss estimation device 1 is described as having the characteristic information storage unit 21, but the storage location of the iron loss characteristic information is not limited to this. For example, the iron loss characteristic information may be stored on a cloud server, etc., and the iron loss characteristic value may be obtained from the iron loss characteristic information by accessing it via a communication line.

[0045] The iron loss estimation device, the iron loss estimation method, and the iron loss characteristic creating method described in the above-described embodiments can be understood, for example, as follows.

[0046] An iron loss estimation device (1) according to a first aspect of the present disclosure is an iron loss estimation device that estimates iron loss of a structure formed from electromagnetic steel sheets, and includes a characteristic value acquisition unit (22) that acquires a characteristic value related to crystal orientation from analysis data obtained by analyzing an evaluation cross-section of the structure to be evaluated, and an iron loss characteristic value acquisition unit (23) that acquires, from iron loss characteristic information in which a characteristic value related to crystal orientation and an iron loss characteristic value are previously associated with each other, the iron loss characteristic value that corresponds to the characteristic value related to crystal orientation acquired by the characteristic value acquisition unit.

[0047] According to the above aspect, it is possible to estimate the iron loss of the structure to be evaluated without using numerical analysis. The characteristic value related to the crystal orientation is a parameter that has a strong correlation with the iron loss. Since the iron loss characteristic value is estimated using such a characteristic value related to the crystal orientation, it is possible to improve the estimation accuracy of the iron loss deterioration rate of the structure to be evaluated. In addition, since no numerical calculation is used as disclosed in Patent Document 1, there is no need to obtain input information that is difficult to measure, such as clearance, and the effort required for iron loss estimation can be reduced.

[0048] In an iron loss estimation device according to a second aspect of the present disclosure, in the above-mentioned first aspect, the characteristic value related to crystal orientation is a region area ratio or a region volume ratio in which a local orientation difference is equal to or greater than a predetermined threshold value in the evaluation cross section.

[0049] According to the above aspect, the area ratio of the region where the local orientation difference is equal to or greater than a predetermined threshold is used as the characteristic value related to the crystal orientation. Here, the area ratio or the volume ratio of the region where the local orientation difference is equal to or greater than a predetermined threshold has a strong correlation with the iron loss. This can improve the accuracy of the iron loss estimation.

[0050] In an iron loss estimation device according to a third aspect of the present disclosure, in the above-mentioned first aspect, the characteristic value related to the crystal orientation is a region area ratio or a region volume ratio in which a local orientation difference is equal to or greater than a threshold value in the evaluation cross section, and the threshold value is set to a value less than 3°.

[0051] According to the above aspect, the characteristic value related to the crystal orientation is the area ratio or volume ratio of the region where the local orientation difference is equal to or greater than a predetermined threshold, and the threshold is set to a value less than 3°. Here, by setting the threshold to a value less than 3°, the iron loss characteristic value can be estimated using a characteristic value having a stronger correlation with iron loss. This can improve the accuracy of iron loss estimation.

[0052] An iron loss estimation method according to a fourth aspect of the present disclosure is an iron loss estimation method for estimating iron loss in a structure formed from electromagnetic steel sheets, and includes a characteristic value acquisition process (SB1) for acquiring a characteristic value related to crystal orientation from analysis data obtained by analyzing an evaluation cross-section of the structure to be evaluated, and an iron loss characteristic value acquisition process (SB2) for acquiring, from iron loss characteristic information in which characteristic values ​​related to crystal orientation and iron loss characteristic values ​​are previously associated with each other, an iron loss characteristic value corresponding to the characteristic value related to crystal orientation acquired in the characteristic value acquisition process.

[0053] A program according to a fifth aspect of the present disclosure is a program for causing a computer to function as the iron loss estimation device according to any one of the first to third aspects.

[0054] An iron loss characteristic creation method according to a sixth aspect of the present disclosure is a method for creating iron loss characteristic information for estimating iron loss in a structure formed from electromagnetic steel sheets, and includes a test piece creation step (SA1) for creating a plurality of test pieces with different iron loss characteristic values, an iron loss measurement step (SA2) for measuring the iron loss characteristic value of each of the test pieces, an analysis data acquisition step (SA3) for acquiring analysis data obtained by analyzing an evaluation cross section obtained by cutting each of the test pieces, and a characteristic creation step (SA4) for acquiring characteristic values ​​related to crystal orientation from the analysis data of each of the test pieces, and creating iron loss characteristic information using the acquired characteristic values ​​and the iron loss characteristic values.

[0055] A seventh aspect of the present disclosure relates to an iron loss characteristic creation method according to the sixth aspect, wherein the characteristic value related to the crystal orientation is a region area ratio or a region volume ratio in which a local orientation difference is equal to or greater than a threshold value in the evaluation cross section.

[0056] An iron loss characteristic creation method according to an eighth aspect of the present disclosure is, in the sixth aspect, the characteristic value related to the crystal orientation is a region area ratio or a region volume ratio in which a local orientation difference is equal to or greater than a threshold value in the evaluation cross section, and the threshold value is set to a value less than 3°. [Explanation of symbols]

[0057] 1: Iron loss estimation device 11: CPU 12: Main memory 13:Secondary storage device 14: External interface 15: Communication interface 16: Input device 17: Display 21:Characteristics information storage section 22: Characteristic value acquisition section 23: Iron loss characteristic value acquisition section 24: Performance Evaluation Department A: Longitudinal section KAMot: Orientation difference characteristic value ΔW: Iron loss deterioration rate φ: threshold

Claims

1. An iron loss estimation device that estimates iron loss of a structure formed of electromagnetic steel sheets, a characteristic value acquiring unit that acquires characteristic values ​​related to crystal orientation from analysis data obtained by analyzing an evaluation cross section of the structure to be evaluated; an iron loss characteristic value acquisition unit that acquires, from iron loss characteristic information in which a characteristic value related to a crystal orientation and an iron loss characteristic value are previously associated with each other, an iron loss characteristic value corresponding to the characteristic value related to the crystal orientation acquired by the characteristic value acquisition unit; An iron loss estimation device comprising:

2. The iron loss estimation device according to claim 1 , wherein the characteristic value relating to the crystal orientation is a region area rate or a region volume rate in which a local orientation difference is equal to or greater than a predetermined threshold value in the evaluation cross section.

3. 2. The iron loss estimation device according to claim 1, wherein the characteristic value relating to the crystal orientation is a region area ratio or a region volume ratio in which a local orientation difference is equal to or greater than a threshold value in the evaluation cross section, and the threshold value is set to a value less than 3°.

4. A method for estimating iron loss in a structure formed of electromagnetic steel sheets, comprising: a characteristic value acquisition step of acquiring characteristic values ​​related to crystal orientation from analysis data obtained by analyzing an evaluation cross section of the structure to be evaluated; an iron loss characteristic value acquisition step of acquiring the iron loss characteristic value corresponding to the characteristic value related to the crystal orientation acquired in the characteristic value acquisition step from iron loss characteristic information in which the characteristic value related to the crystal orientation and the iron loss characteristic value are previously associated with each other; This is a computer-implemented iron loss estimation method.

5. A program for causing a computer to function as the iron loss estimation device according to any one of claims 1 to 3.

6. A method for creating iron loss characteristic information for estimating iron loss of a structure formed of electromagnetic steel sheets, comprising: a test piece preparation step of preparing a plurality of test pieces having different iron loss characteristic values; an iron loss measurement step of measuring an iron loss characteristic value of each of the test pieces; an analysis data acquisition step of acquiring analysis data obtained by analyzing an evaluation cross section obtained by cutting each of the test pieces; a characteristic creation step of acquiring a characteristic value relating to a crystal orientation from the analysis data of each of the test pieces, and creating iron loss characteristic information using the acquired characteristic value and the iron loss characteristic value; A method for creating iron loss characteristics.

7. The method for calculating iron loss characteristics according to claim 6 , wherein the characteristic value relating to the crystal orientation is a region area rate or a region volume rate in which a local orientation difference is equal to or greater than a threshold value in the evaluation cross section.

8. 7. The method for creating an iron loss characteristic according to claim 6, wherein the characteristic value relating to the crystal orientation is a region area ratio or a region volume ratio in which the local orientation difference is equal to or greater than a threshold value in the evaluation cross section, and the threshold value is set to a value less than 3°.

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