Method for evaluating metal fatigue, the program, and the device

Abstract

To provide a metal fatigue evaluation method capable of obtaining a further reliable evaluation result.SOLUTION: The metal fatigue evaluation method for determining an evaluation index indicating the degree of metal fatigue in an evaluation target of metal, includes acquiring diffraction ring data indicating a diffraction ring formed by irradiating the evaluation target with a beam exhibiting a diffraction property, determining peak intensity distribution of the diffraction ring with respect to an azimuth in the acquired diffraction ring data or half peak width distribution with respect to an azimuth in the diffraction ring data acquired in a data acquisition step, as data distribution, and then determining the evaluation index on the basis of a removal result obtained by removing a waviness component contained in the data distribution from the determined data distribution.SELECTED DRAWING: Figure 10

Description

Technical Field

[0001] The present invention relates to a metal fatigue evaluation method, a metal fatigue evaluation program, and a metal fatigue evaluation device for evaluating the degree of metal fatigue using a diffraction ring.

Background Art

[0002] Damage to a device due to metal fatigue may lead to an unexpected stop of a process or an accident, etc., so it is important and desired to evaluate the degree of metal fatigue. A technique for evaluating the degree of this metal fatigue is disclosed in, for example, Patent Document 1.

[0003] In this Patent Document 1, X-ray diffraction is performed on a fatigue part identified by observing a corroded part due to a phase change to martensite, the change amount of the half-value width of martensite and the change amount of retained austenite are measured, and the fatigue degree is obtained from the measurement results.

[0004] Generally, when the periodicity of a crystal is high, a strong diffracted wave (Bragg reflection wave) is generated in the direction defined by the periodic interval and the periodic direction. On the other hand, since metal fatigue generates dislocations in a metal crystal, it disturbs the periodicity of the lattice of the metal crystal. For this reason, a spread occurs in the reflection direction of the Bragg reflection wave, and as a result, the half-value width (spread from the peak position) of the diffracted wave changes. Therefore, it is presumed that the degree of metal fatigue can be evaluated as in Patent Document 1 by evaluating the half-value width of the diffracted wave due to Bragg reflection in a crystal lattice.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] Incidentally, since the evaluation of metal fatigue is important as described above, it is preferably more reliable, and there is room for improvement in the evaluation method for evaluating the degree of metal fatigue by X-ray diffraction.

[0007] The present invention has been made in view of the above circumstances, and an object thereof is to provide a metal fatigue evaluation method, a metal fatigue evaluation program, and a metal fatigue evaluation apparatus capable of obtaining more reliable evaluation results.

Means for Solving the Problems

[0008] As a result of various studies, the present inventor has found that the above object can be achieved by the following present invention. That is, a metal fatigue evaluation method according to one aspect of the present invention is a method for obtaining an evaluation index representing the degree of metal fatigue in an evaluation object of metal, including a data acquisition step of acquiring diffraction ring data representing a diffraction ring formed by irradiating a beam having a property of diffracting on the evaluation object, a distribution processing step of obtaining, as a data distribution, a peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step, or a half-value width distribution with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step, and an index processing step of obtaining the evaluation index based on a removal result obtained by removing a waviness component included in the data distribution from the data distribution obtained in the distribution processing step.

[0009] Such a metal fatigue evaluation method obtains a more reliable evaluation result because the evaluation index is obtained based on a removal result obtained by removing a waviness component that is noise from the data distribution.

[0010] In another aspect, in the above metal fatigue evaluation method, the evaluation index is a uniformity index representing the degree of uniformity of the data distribution. Preferably, in the above metal fatigue evaluation method, the evaluation index is a uniformity index representing the degree of uniformity of the peak intensity in the diffraction ring with respect to the azimuth angle, or a uniformity index representing the degree of uniformity of the half-value width in the diffraction ring with respect to the azimuth angle.

[0011] When the metal to be evaluated is in the initial state, the number of crystal grains in the X-ray irradiation region is insufficient, so the diffraction ring has a spotty shape. However, as metal fatigue progresses, the number of crystal grains increases due to the refinement (cell structure formation) of crystal grains accompanying dislocation growth, and the diffraction ring becomes uniform. Since the metal fatigue evaluation method obtains the uniformity index representing the degree of uniformity of the data distribution as the evaluation index representing the degree of metal fatigue, the degree of metal fatigue can be evaluated more appropriately.

[0012] In another aspect, in the above metal fatigue evaluation method, the uniformity index is the standard deviation in the data distribution or the division result obtained by dividing the standard deviation in the data distribution by the average value of the data distribution. Preferably, in the above metal fatigue evaluation method, the uniformity index is the standard deviation of the peak intensity distribution in the diffraction ring with respect to the azimuth angle, or the division result obtained by dividing the standard deviation of the peak intensity in the diffraction ring with respect to the azimuth angle by the average value of the peak intensity distribution. Preferably, in the above metal fatigue evaluation method, the uniformity index is the standard deviation of the full-width at half-maximum distribution in the diffraction ring with respect to the azimuth angle, or the division result obtained by dividing the standard deviation of the full-width at half-maximum in the diffraction ring with respect to the azimuth angle by the average value of the full-width at half-maximum distribution.

[0013] According to this, a metal fatigue evaluation method can be provided that obtains the standard deviation in the data distribution or the division result obtained by dividing the standard deviation in the data distribution by the average value of the data distribution as the uniformity index, that is, the evaluation index. When the division result is used as the uniformity index, the above metal fatigue evaluation method divides the standard deviation by the average value, so the influence of the variation in the beam irradiation time on the evaluation index can be reduced.

[0014] In another aspect, in the above metal fatigue evaluation method, the index processing step includes a waviness component extraction step of extracting the waviness component included in the data distribution from the data distribution obtained in the distribution processing step, and an index calculation step of obtaining the evaluation index based on the removal result obtained by removing the waviness component extracted in the waviness component extraction step from the data distribution obtained in the distribution processing step.

[0015] Since such a method for evaluating metal fatigue extracts the waviness component and then generates the removal result, known extraction processes for extracting the waviness component can be used, and the removal result obtained by simply removing the waviness component from the data distribution can be generated.

[0016] In another aspect, in the above-described method for evaluating metal fatigue, in the waviness component extraction step, the data distribution obtained in the distribution processing step is filtered by filtering using a Gaussian filter or the waviness component is extracted by envelope processing for extracting an envelope.

[0017] Since such a method for evaluating metal fatigue uses filtering or envelope processing for extracting the waviness component, the waviness component can be extracted by a simple process.

[0018] A metal fatigue evaluation program according to another aspect of the present invention is a program that is executed by a computer and obtains an evaluation index representing the degree of metal fatigue in an evaluation target of metal, and includes a data acquisition step of acquiring diffraction ring data representing a diffraction ring formed by irradiating a beam having a property of diffracting on the evaluation target, a distribution processing step of obtaining, as a data distribution, a peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step or a half-value width distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step, and an index processing step of obtaining the evaluation index based on a removal result obtained by removing a waviness component included in the data distribution from the data distribution obtained in the distribution processing step.

[0019] A metal fatigue evaluation apparatus according to another aspect of the present invention is an apparatus for obtaining an evaluation index representing the degree of metal fatigue in a metal to be evaluated, and includes a data acquisition unit that acquires diffraction ring data representing a diffraction ring formed by irradiating a beam having a property of diffracting on the evaluation target, a distribution processing unit that obtains, as a data distribution, a peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit, or a half-width distribution with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit, and an index processing unit that obtains the evaluation index based on a removal result obtained by removing a waviness component included in the data distribution from the data distribution obtained by the distribution processing unit.

[0020] Such a metal fatigue evaluation program and metal fatigue evaluation apparatus obtain the evaluation index based on a removal result obtained by removing a waviness component, which is noise, from the data distribution, so that a more reliable evaluation result can be obtained.

Advantages of the Invention

[0021] The metal fatigue evaluation method, metal fatigue evaluation program, and metal fatigue evaluation apparatus according to the present invention can obtain a more reliable evaluation result.

Brief Description of the Drawings

[0022]

Figure 1

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Figure 10

Embodiments for Carrying Out the Invention

[0023] Hereinafter, one or more embodiments of the present invention will be described with reference to the drawings. However, the scope of the invention is not limited to the disclosed embodiments. In each figure, components denoted by the same reference numerals are the same components, and the description thereof will be omitted as appropriate. In this specification, when referring to generics, reference numerals without subscripts are used, and when referring to individual components, reference numerals with subscripts are used.

[0024] The metal fatigue evaluation device in the embodiment is a device for obtaining an evaluation index representing the degree of metal fatigue in the metal object to be evaluated. This metal fatigue evaluation device includes a data acquisition unit that acquires diffraction ring data representing a diffraction ring formed by irradiating a beam having a property of diffracting on the evaluation object, a distribution processing unit that obtains, as a data distribution, the peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit, or the half-width distribution with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit, and an index processing unit that obtains the evaluation index based on a removal result obtained by removing the waviness component included in the data distribution from the data distribution obtained by the distribution processing unit. Hereinafter, such a metal fatigue evaluation device, as well as the metal fatigue evaluation method and metal fatigue evaluation program implemented thereon, will be described more specifically.

[0025] FIG. 1 is a block diagram showing the configuration of a metal fatigue evaluation apparatus according to an embodiment. FIG. 2 is a block diagram showing an example of the configuration of a data acquisition unit in the metal fatigue evaluation apparatus. FIG. 2A shows the overall configuration, and FIG. 2B shows the relationship between the imaging unit 15 and the evaluation target Ob. FIG. 3 is a diagram for explaining the change state of a diffraction ring as metal fatigue progresses. FIG. 4 is a diagram showing, as an example, a diffraction ring, a peak intensity distribution with respect to the azimuth angle of the diffraction ring, its average value, and its standard deviation. FIG. 4A shows the diffraction ring, and FIG. 4B shows the peak intensity distribution (distribution of peak intensities at each position in the circumferential direction of the diffraction ring) with respect to the azimuth angle α in the diffraction ring shown in FIG. 4A, its average value μ, and its standard deviation σ. The horizontal axis in FIG. 4B is the azimuth angle α [deg] from 0° to 360°, and the vertical axis is the peak value of the diffraction intensity (Diffraction Intensity [counts]).

[0026] The metal fatigue evaluation apparatus D in the embodiment includes, for example, as shown in FIG. 1, a data acquisition unit 1, a control processing unit 2, an input unit 3, an output unit 4, an interface unit (IF unit) 5, and a storage unit 6.

[0027] The data acquisition unit 1 is a device that is connected to the control processing unit 2 and acquires diffraction ring data representing a diffraction ring formed by irradiating a beam having a property of diffracting on an evaluation target of a metal (including an alloy) according to the control of the control processing unit 2. More specifically, for example, in the present embodiment, the data acquisition unit 1 includes an irradiation unit that irradiates the beam, and an imaging unit that images a diffraction ring formed by irradiating the evaluation target with the beam by the irradiation unit and generates diffraction ring data representing the diffraction ring.

[0028] More specifically, as shown in FIG. 2, the data acquisition unit 1 includes a high-voltage power supply 11, a cooling unit 12, a control unit 13, an X-ray irradiation unit 14, and an imaging unit 15. The high-voltage power supply 11 is a device that supplies a high voltage for accelerating an electron beam to the X-ray irradiation unit 14. The cooling unit 12 is a device that cools the X-ray irradiation unit 14. The control unit 13 is a device that controls the operation of the entire data acquisition unit 1. Note that the control unit 13 may be used in common with a control unit 21 described later that is functionally configured in the control processing unit 2.

[0029] The X-ray irradiation unit 14 includes an X-ray generator that causes an electron beam to collide with a target to generate X-rays, and an X-ray irradiation tube that irradiates an evaluation target Ob with the generated X-rays as a thin X-ray beam. The X-ray generator is, for example, an X-ray tube (vacuum tube) for accelerating an electron beam at a high voltage and causing it to collide with an anode to generate CrKα characteristic X-rays. The X-ray irradiation tube is, for example, a pinhole collimator that irradiates the generated X-rays as a thin parallel beam.

[0030] Here, an example using X-rays is described as a beam (diffracted light) having a property of diffracting with respect to the evaluation target Ob. However, beams having a diffraction property include not only X-rays but also electromagnetic waves (including visible light, ultraviolet rays, γ-rays), neutron beams, electron beams, and the like.

[0031] The imaging unit 15 is a device that images a diffraction ring formed by irradiating an evaluation target Ob with a beam by the X-ray irradiation unit 14 and generates diffraction ring data representing the diffraction ring. The imaging unit 15 is configured to include, for example, a so-called imaging plate. In this imaging plate, the phenomenon of stimulable phosphor fluorescence emission is utilized. Roughly, a film coated with a stimulable phosphor is exposed to X-rays, and the amount of fluorescence generated by irradiating the exposed film with laser light is measured. Since the fluorescence emits light with an amount of light corresponding to the exposure amount of the X-rays, an X-ray image can be obtained by measuring the amount of light emission.

[0032] Note that the data acquisition unit 1 is, for example, an interface circuit that inputs and outputs data to and from an external device, and the external device may be a storage medium such as a USB (Universal Serial Bus) memory and an SD card (registered trademark) that stores the diffraction ring data. Alternatively, for example, the data acquisition unit 1 is an interface circuit that inputs and outputs data to and from an external device, and the external device is a drive device that reads data from a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a CD-R (Compact Disc Recordable), a DVD-ROM (Digital Versatile Disc Read Only Memory), and a DVD-R (Digital Versatile Disc Recordable) that records the diffraction ring data. Alternatively, for example, the data acquisition unit 1 is a communication interface circuit that transmits and receives communication signals to and from an external device, and the external device is connected to the communication interface circuit via a network (WAN (Wide Area Network, including a public communication network)) or a LAN (Local Area Network), and may be a server device that manages the diffraction ring data. Note that when the data acquisition unit 1 is an interface circuit or a communication interface circuit, the data acquisition unit 1 may be used in combination with the IF unit 5 (that is, the IF unit 5 may be used as the data acquisition unit 1).

[0033] Returning to FIG. 1, the input unit 3 is connected to the control processing unit 2 and inputs various data necessary for operating the metal fatigue evaluation device D, such as various commands including a command for instructing the start of evaluation, and the name of the evaluation target (e.g., serial number, etc.) to be evaluated by the metal fatigue evaluation device D. For example, it is a device such as a plurality of input switches, a keyboard, and a mouse assigned with predetermined functions. The output unit 4 is connected to the control processing unit 2 and outputs, according to the control of the control processing unit 2, commands and data input from the input unit 3, diffraction rings represented by diffraction ring data acquired by the data acquisition unit 1, and evaluation indicators obtained by the metal fatigue evaluation device D. For example, it is a device such as a display device such as a CRT display, an LCD (liquid crystal display device), and an organic EL display, or a printing device such as a printer.

[0034] The IF unit 5 is connected to the control processing unit 2 and is a circuit for inputting and outputting data, for example, between the control processing unit 2 and an external device. For example, it is an interface circuit of RS-232C using a serial communication method, an interface circuit using the Bluetooth (registered trademark) standard, and an interface circuit using the USB standard. Further, the IF unit 5 may be a communication interface circuit for transmitting and receiving communication signals with an external device, such as a data communication card or a communication interface circuit according to the IEEE802.11 standard.

[0035] The memory unit 6 is a circuit connected to the control processing unit 2 and stores various predetermined programs and various predetermined data according to the control of the control processing unit 2. The various predetermined programs include, for example, a control processing program. The control processing program includes a control program for controlling each part 1, 3 to 6 of the metal fatigue evaluation device D according to the functions of the respective parts, a distribution processing program for obtaining, as a data distribution, the peak intensity distribution of the diffraction ring with respect to the azimuth angle or the half-width distribution with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit 1, and an index processing program for obtaining the evaluation index based on the removal result of removing the undulation component included in the data distribution from the data distribution obtained by the distribution processing program. The various predetermined data include, for example, data necessary for executing these programs, such as the diffraction ring data. Such a memory unit 6 includes, for example, a ROM (Read Only Memory), which is a non-volatile memory element, an EEPROM (Electrically Erasable Programmable Read Only Memory), which is a rewritable non-volatile memory element, and the like. And the memory unit 6 includes a RAM (Random Access Memory) and the like, which serve as a working memory of the so-called control processing unit 2 for storing data and the like generated during the execution of the predetermined program. Note that the memory unit 6 may include a hard disk device capable of storing a large capacity.

[0036] The control processing unit 2 is a circuit for controlling each part 1, 3 to 6 of the metal fatigue evaluation device D according to the functions of the respective parts and obtaining an evaluation index representing the degree of metal fatigue in the evaluation object. The control processing unit 2 is configured to include, for example, a CPU (Central Processing Unit) and its peripheral circuits. When the control processing program is executed in the control processing unit 2, a control unit 21, a distribution processing unit 22, and an index processing unit 23 are functionally configured.

[0037] The control unit 21 controls each part 1, 3 to 6 of the metal fatigue evaluation device D according to the functions of the respective parts, and is in charge of the control of the entire metal fatigue evaluation device D.

[0038] The distribution processing unit 22 obtains, as a data distribution, the peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit 1, or the half-width distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit 1.

[0039] The index processing unit 23 obtains the evaluation index based on the removal result obtained by removing the waviness component included in the data distribution from the data distribution obtained by the distribution processing unit 22. The removal result may be directly obtained from the data distribution, or may be obtained by first obtaining the waviness component and then removing the obtained waviness component from the data distribution. In the latter case, as shown by the dashed line in FIG. 1, the index processing unit 23 functionally includes a waviness component extraction unit 231 and an index calculation unit 232. The waviness component extraction unit 231 extracts the waviness component included in the data distribution from the data distribution obtained by the distribution processing unit 22. The index calculation unit 232 obtains the evaluation index based on the removal result obtained by removing the waviness component extracted by the waviness component extraction unit 231 from the data distribution obtained by the distribution processing unit 22. The processing for directly obtaining the removal result and the processing for extracting the waviness component will be further described later.

[0040] As the evaluation index, the full width at half maximum of the diffraction ring, which is common, may be used. However, in the present embodiment, a uniformity index representing the degree of uniformity of the data distribution is used. That is, the evaluation index is a uniformity index representing the degree of uniformity of the peak intensity in the diffraction ring with respect to the azimuth angle. Alternatively, the evaluation index is a uniformity index representing the degree of uniformity of the full width at half maximum in the diffraction ring with respect to the azimuth angle. Preferably, the uniformity index is the standard deviation in the data distribution, or the division result obtained by dividing the standard deviation in the data distribution by the average value of the data distribution. That is, the uniformity index is the standard deviation of the peak intensity distribution in the diffraction ring with respect to the azimuth angle, or the division result obtained by dividing the standard deviation of the peak intensity in the diffraction ring with respect to the azimuth angle by the average value of the peak intensity distribution. Alternatively, the uniformity index is the standard deviation of the full width at half maximum distribution in the diffraction ring with respect to the azimuth angle, or the division result obtained by dividing the standard deviation of the full width at half maximum in the diffraction ring with respect to the azimuth angle by the average value of the full width at half maximum distribution.

[0041] An explanation will be given as to why such a uniformity index serves as an evaluation index representing the degree of metal fatigue. FIG. 3 shows, as an example, how the diffraction ring changes with the progress of metal fatigue. FIG. 3 shows X-ray diffraction in which X-rays of CrKα are incident at an incident angle of 0° on each sample that has been given fatigue damage of 0%, 10%, 30%, 50%, and 100% respectively by a tensile-compression repeated test in which tension and compression are alternately repeated, and the resulting diffraction ring images are shown. For the tensile-compression repeated test, an ordinary fatigue testing machine for applying a vibration load is used, and the number of cycles at breakage is defined as 100% of the damage degree, and the damage degrees of 0%, 10%, 30%, and 50% are the ratios of the number of cycles to this. The sample is, as an example, a steel pipe material of a general standard used for boiler tubes. The upper part of FIG. 3 shows the diffraction ring images of each sample without electropolishing treatment, and the lower part shows the diffraction ring images of each sample with electropolishing treatment. In plan view, from left to right in order, they are the diffraction ring images of each sample with damage degrees of 0%, 10%, 30%, 50%, and 100%.

[0042] When observing FIG. 3 from left to right in order, it can be seen that the diffraction ring changes from the spotty initial state where the peak intensity is different at each position in the circumferential direction to a state where the peak intensity gradually changes to a substantially uniform shape at each position in the circumferential direction as the metal fatigue increases. Comparing this change with the observation results (not shown) of TEM (transmission electron microscope), it is presumed that the process in which a large number of fine cell structures are formed due to the dislocation growth accompanying the accumulation of fatigue damage is related to the change in which the diffraction ring becomes uniform.

[0043] Generally, when there are a sufficient number of crystal grains in the X-ray irradiation region, a uniform diffraction ring can be obtained. The results shown in FIG. 3 are presumed to contribute to the uniformization of the diffraction ring because the number of crystal grains in the X-ray irradiation region was insufficient in the initial state, resulting in a spotty diffraction ring shape, and the number of crystal grains increased due to the refinement (cell structuring) of the crystal grains accompanying dislocation growth. In the evaluation method using X-ray diffraction including residual stress measurement, in order to avoid a decrease in measurement accuracy, it is recommended that the average crystal grain size of the sample be 30 μm or less. Comparing with this guideline, the ferrite grain size in the initial state of the sample in FIG. 3 is as large as about 50 to 60 μm, which falls into the category of coarse ones in terms of X-ray diffraction measurement and is consistent with the above consideration.

[0044] From the above, it can be concluded that the phenomenon of the uniformization of the diffraction ring accompanying the accumulation of fatigue damage is due to, firstly, the refinement of the structure by dislocation growth (cell structure formation), and secondly, the change in the orientation of the microstructure. The unevenness of the diffraction ring is considered to be a physical quantity that clearly represents the change in the microstructure, and the uniformity index representing the degree of uniformity of the peak intensity in the diffraction ring can be used as a new evaluation index representing the degree of metal fatigue.

[0045] The uniformity index (= an example of an evaluation index) may be, for example, the difference between the maximum peak intensity and the minimum peak intensity with respect to the azimuth angle of the diffraction ring, the change in the half-width of the peak, etc. In this embodiment, however, the standard deviation in the peak intensity distribution of the diffraction ring with respect to the azimuth angle is used as the uniformity index. An example thereof is shown in FIG. 4. FIG. 4A shows the diffraction ring, and FIG. 4B shows the peak intensity distribution with respect to the azimuth angle α in the diffraction ring shown in FIG. 4A (the distribution of the peak intensity at each position in the circumferential direction of the diffraction ring), its average value μ, and its standard deviation σ. The horizontal axis in FIG. 4B is the azimuth angle α [deg] from 0° to 360°, and the vertical axis is the peak value of the diffraction intensity (Diffraction Intensity [counts]). The azimuth angle α is the angle from the baseline with respect to the circumferential direction of the diffraction ring clockwise when the baseline passing through the center position O of the diffraction ring is taken as the reference 0° as shown in FIG. 4A. The evaluation object Ob is STBA21, which is an example of a general standard steel pipe material used for boiler tubes, and an electrolytic polishing treatment has been carried out. The diffraction angle 2θ is 156.396°. When the standard deviation σ as the uniformity index is relatively large, the peak intensities at each position in the circumferential direction of the diffraction ring vary, and the metal fatigue is relatively small. On the other hand, when the standard deviation σ is relatively small, the peak intensities at each position in the circumferential direction of the diffraction ring are substantially uniform (with little variation), and the metal fatigue is relatively large.

[0046] As the peak intensity in the diffraction ring with respect to the azimuth angle is made uniform, and the half-width of the peak in the diffraction ring with respect to the azimuth angle is also made uniform, the uniformity index (= another example of an evaluation index) may be the standard deviation in the half-width distribution of the peak with respect to the azimuth angle. Alternatively, in order to reduce the influence of the variation in the beam irradiation time on the evaluation index, the uniformity index (= another example of an evaluation index) may be the division result obtained by dividing the standard deviation in the peak intensity distribution of the diffraction ring with respect to the azimuth angle by the average value of the peak intensity distribution in the diffraction ring, and the uniformity index (= another example of an evaluation index) may be the division result obtained by dividing the standard deviation in the half-width distribution with respect to the azimuth angle by the average value of the half-width distribution in the diffraction ring.

[0047] The above-mentioned Figure 4 shows the result before removing the waviness component based on the diffraction ring data acquired by the data acquisition unit 1. In the present embodiment, in order to obtain an even more reliable evaluation result, the waviness component is removed.

[0048] FIG. 5 is a graph showing the change in the X-ray penetration depth according to the incident angle and the azimuth angle. The horizontal axis of FIG. 5 is the azimuth angle α [deg], and its vertical axis is the X-ray penetration depth [μm]. FIG. 5 shows a graph of the X-ray penetration depth with respect to the azimuth angle when the incident angle Ψ0 is 0°, a graph of the X-ray penetration depth with respect to the azimuth angle when the incident angle Ψ0 is 15°, a graph of the X-ray penetration depth with respect to the azimuth angle when the incident angle Ψ0 is 30°, a graph of the X-ray penetration depth with respect to the azimuth angle when the incident angle Ψ0 is 45°, and a graph of the X-ray penetration depth with respect to the azimuth angle when the incident angle Ψ0 is 60°. FIG. 6 is a diagram for explaining the change in the peak intensity distribution of the diffraction ring with respect to the azimuth angle according to the incident angle. FIG. 6A shows the peak intensity distribution of the diffraction ring with respect to the azimuth angle when the incident angle Ψ0 is 0°, and FIG. 6B shows the peak intensity distribution of the diffraction ring with respect to the azimuth angle when the incident angle Ψ0 is 45°. Each horizontal axis in FIGS. 6A and 6B is the azimuth angle α [deg], and their respective vertical axes are the peak intensity. FIG. 7 is a diagram for explaining the separation interval extraction process. FIG. 8 is a graph showing the change rate of the uniformity index with respect to the damage degree regarding the filtering process of the Gaussian filter. FIGS. 8A and 8B are graphs obtained using the filtering process, and FIGS. 8C and 8D are graphs not using the filtering process. In FIGS. 8A and 8C, as the uniformity index, the division result of dividing the standard deviation in the peak intensity distribution of the diffraction ring with respect to the azimuth angle by the average value of the peak intensity distribution is used, and FIGS. 8A and 8C are graphs of the change rate from its initial value. Each horizontal axis of FIGS. 8A and 8C is the damage degree [%], and their vertical axes are the change rate. In FIGS. 8B and 8D, as the uniformity index, the division result of dividing the standard deviation in the half-width distribution of the diffraction ring with respect to the azimuth angle by the average value of the half-width distribution is used, and FIGS. 8B and 8D are graphs of the change rate from its initial value. The initial value is the value of the uniformity index at a damage degree of 0%. Each horizontal axis of FIGS. 8B and 8D is the damage degree [%], and their vertical axes are the change rate. FIG. 9 is a graph showing the change rate of the uniformity index with respect to the damage degree regarding the separation interval extraction process.Figures 9A and 9B are graphs obtained using the separation distance extraction process, and Figures 9C and 9D are graphs without using the separation distance extraction process. In Figures 9A and 9C, as the uniformity index, the division result obtained by dividing the standard deviation in the peak intensity distribution of the diffraction ring with respect to the azimuth angle by the average value of the peak intensity distribution is used, and Figures 9A and 9C are graphs of the change rate from its initial value. The horizontal axis of each of Figures 9A and 9C is the damage degree [%], and their vertical axis is the change rate. In Figures 9B and 9D, as the uniformity index, the division result obtained by dividing the standard deviation in the full-width at half-maximum distribution of the diffraction ring with respect to the azimuth angle by the average value of the full-width at half-maximum distribution is used, and Figures 9B and 9D are graphs of the change rate from its initial value. The initial value is the value of the uniformity index at a damage degree of 0% as described above. The horizontal axis of each of Figures 9B and 9D is the damage degree [%], and their vertical axis is the change rate. Figure 8C is the same as Figure 9C, and Figure 8D is the same as Figure 9D. That is, for easy viewing, Figures 8C and 8D are reproduced as Figures 9C and 9D.

[0049] In the measurement system shown in FIG. 4, for example, as shown in FIG. 5, the X-ray penetration depth into the material (evaluation target) varies depending on the incident angle Ψ0 and the azimuth angle α. The X-ray penetration depth is constant regardless of the azimuth angle α when the incident angle Ψ0 is 0°, but the X-ray penetration depth becomes deeper as the incident angle Ψ0 increases, and forms a valley (the deepest) at the azimuth angle α of 180°. Each graph shown in FIG. 5 was generated by simulating the influence on the diffraction intensity due to the attenuation based on the optical path difference.

[0050] The inventors investigated the influence of the change in the X-ray penetration depth shown in FIG. 5 on the peak intensity distribution of the diffraction ring with respect to the azimuth angle by actually measuring the peak intensity distribution of the diffraction ring with respect to the azimuth angle when the incident angle Ψ0 is 0°, and the peak intensity distribution of the diffraction ring with respect to the azimuth angle when the incident angle Ψ0 is 45°, respectively. The results are shown in FIG. 6. FIG. 6 shows the measurement conditions: X-ray; CrKα, diffraction angle 2θ; 156.396°, measurement object; fire STBA24J1, average spot diameter; approximately 1.7 mm when the incident angle Ψ0 is 0° and approximately 2.2 mm when the incident angle Ψ0 is 45°, surface polishing; electrolytic polishing, and the peak intensity of the diffraction ring at a damage degree of 30% was actually measured.

[0051] As shown in FIG. 6, when the incident angle Ψ0 is 0°, the X-ray penetration depth is constant regardless of the azimuth angle α. Therefore, based on the peak intensity of the diffraction ring when the incident angle Ψ0 is 0°, shown in FIG. 6A, and referring to the peak intensity of the diffraction ring when the incident angle Ψ0 is 45°, shown in FIG. 6B, the relatively fine and relatively small fluctuations (increases and decreases) in the peak intensity accompanying the increase in the azimuth angle from 0° to 360° appear to be similar between the two. However, in the peak intensity of the diffraction ring when the incident angle Ψ0 is 45°, compared with the peak intensity of the diffraction ring when the incident angle Ψ0 is 0°, relatively gentle and relatively large fluctuations (increases and decreases) in the peak intensity are observed as the azimuth angle increases from 0° to 360°. Regarding the spatial frequency in the azimuth angle space, the former is a high-frequency component, and the latter is a wavy component. When the uniformity index is used as the evaluation index, the uniformity deteriorates due to this wavy component, so this wavy component becomes noise for the uniformity index.

[0052] Therefore, in this embodiment, the wavy component is removed from the data distribution, and based on the removal result, a uniformity index is obtained as an example of the evaluation index. This removal result may be obtained by first obtaining the wavy component and then removing the obtained wavy component from the data distribution, as described above. A known extraction process is used for the extraction of this wavy component.

[0053] For example, by obtaining a moving average (simple moving average) for the data distribution, the ripple component can be extracted. Alternatively, for example, by obtaining a weighted moving average for the data distribution, the ripple component can be extracted. For the weight, for example, a Gaussian function is used, and the ripple component can be extracted by filtering processing using a Gaussian filter. The results are shown in FIGS. 8A and 8B. Each graph shown in FIG. 8 is created from the measurement results shown in FIG. 6, and filtering processing using a Gaussian filter is used. In this example, the sampling interval is 0.72°, and the measurement points for obtaining the weighted moving average and two points at ±10.08° with respect to this measurement point are decimated, and a weighted moving average is obtained by performing a convolution integral with the weight of the Gaussian function for each of the three measurement points. Note that the weighted moving average may be obtained by performing a convolution integral with the weight of the Gaussian function for the measurement points for obtaining the weighted moving average and each measurement point within the range of ±10.08° with respect to this measurement point without performing the decimation. In FIG. 8, the change rate when the incident angle Ψ0 is 0° is indicated by ○, and the change rate when the incident angle Ψ0 is 45° is indicated by ■. In FIGS. 8A and 8B, in the filtering processing using a Gaussian filter for obtaining the ripple component, a weighted moving average is obtained at a total of three points, which are the measurement point and two points at ±10.08° with respect to the measurement point, but the decimation interval for obtaining the weighted moving average is not limited to this. Although not shown, the decimation intervals for obtaining the weighted moving average are set to ±0.72°, ±2.88°, ±5.04°, ±10.08°, ±20.16°, ±40.32°, ±60.48°, and ±80.64° with respect to the measurement point, respectively, and each uniformity index at each decimation interval is calculated and compared with the damage degree. When the angle representing the decimation interval is large, the correlation between the uniformity index based on the peak intensity and the damage degree cannot be obtained, and the change in the uniformity index based on the half-width is small, so there is a tendency that it becomes difficult to judge the presence or absence of damage. On the other hand, when the angle representing the decimation interval is small, the change in the uniformity index based on the half-width is small, and there is a tendency that it becomes difficult to judge the presence or absence of damage.Therefore, the decimation interval for obtaining the weighted moving average is preferably ±2° to ±40°, more preferably ±5° to ±30°. In this method, the weight of the Gaussian function does not affect the change rate from the initial value of the uniformity index (damage degree 0%). Therefore, the decimation interval is an important parameter, and the weight only needs to obtain an appropriate absolute value considering the measurement accuracy.

[0054] Alternatively, for example, for the data distribution, the wavy component can be extracted by performing envelope processing (envelope detection) to extract the envelope.

[0055] Alternatively, for example, a separation interval extraction process for directly obtaining the removal result may be used. In this separation interval extraction process, for each of a plurality of sampling points set in the data distribution, the distance (separation interval) between a straight line connecting the sampling point and an adjacent sampling point thereto and the data distribution between the sampling point and the adjacent sampling point is obtained, and the plurality of obtained distances are used as the division result. For the case where the data distribution is a peak intensity distribution, in the separation interval extraction process, first, as shown in FIG. 7, a plurality of sampling points are set at a predetermined constant interval with respect to the peak intensity distribution of the diffraction ring with respect to the azimuth angle. Next, for each of the plurality of sampling points set in this way, from the azimuth angle of 0° to 360°, the sampling point and an adjacent sampling point thereto are connected by a straight line, and the distance from this straight line to the peak intensity distribution between the sampling point and the adjacent sampling point thereto is obtained as the separation interval. Next, the plurality of separation intervals obtained in this way are sequentially connected from the azimuth angle of 0° to 360°, and a curve of the separation interval with respect to the azimuth angle is generated. Next, in order to reduce the influence of the setting position of the sampling points given to the curve of the separation interval, the setting positions of the first sampling points in each round are set to be different from each other, and such a separation interval extraction process is executed a predetermined number of times. Then, the curves of the separation interval with respect to the azimuth angle generated in each round are averaged, and one curve of the separation interval with respect to the azimuth angle (average curve) is generated as the result of the separation interval extraction process. This average curve of the separation interval with respect to the azimuth angle corresponds to the removal result obtained by removing the waviness component from the data distribution.

[0056] Graphs showing the rate of change of the uniformity index with respect to the degree of damage obtained using such separation interval extraction processing are shown in FIGS. 9A and 9B. Each graph shown in FIG. 9 is created from the measurement results shown in FIG. 6. In FIGS. 9A and 9B, the predetermined interval is 7.2°, and the predetermined number of times is 10 times. In FIG. 9, similar to FIG. 8, the rate of change when the incident angle Ψ0 is 0° is indicated by ○, and the rate of change when the incident angle Ψ0 is 45° is indicated by ■. In FIGS. 9A and 9B, the predetermined interval for removing the waviness component is 7.2°. However, although the illustration of the results for the predetermined intervals of 3.6°, 7.2° and 14.4° is omitted, substantially the same tendency is shown, and it may be about 3° to 30°, preferably about 5° to 25°.

[0057] In the graphs shown in FIGS. 8C and 9C, which do not use the filtering process and do not use the separation interval extraction process, as indicated by ○, when the incident angle Ψ0 is 0°, the standard deviation in the peak intensity distribution of the diffraction ring with respect to the azimuth angle, divided by the average value of the peak intensity distribution (uniformity index), decreases as the degree of damage increases, indicating an increase in uniformity. However, as indicated by ■, when the incident angle Ψ0 is 45°, the division result first decreases and then increases as the degree of damage increases. On the other hand, in the graph shown in FIG. 8A, which uses the filtering process, as indicated by ○ and ■ respectively, when the incident angle Ψ0 is 0° and when the incident angle Ψ0 is 45°, the division result decreases as the degree of damage increases, indicating an increase in uniformity. And in the graph shown in FIG. 9A, which uses the separation interval extraction process, as indicated by ○ and ■ respectively, when the incident angle Ψ0 is 0° and when the incident angle Ψ0 is 45°, the division result decreases as the degree of damage increases, indicating an increase in uniformity.

[0058] In the graphs shown in FIGS. 8D and 9D, which do not use the filtering process and do not use the separation distance extraction process, as shown by ○, when the incident angle Ψ0 is 0°, the standard deviation in the half-value width distribution of the diffraction ring with respect to the azimuth angle, divided by the average value of the half-value width distribution (uniformity index), decreases as the damage degree increases, indicating an increase in uniformity. However, as shown by ■, when the incident angle Ψ0 is 45°, the division result remains substantially constant regardless of the increase in the damage degree. In contrast, in the filtered graph shown in FIG. 8B, as shown by ○ and ■ respectively, when the incident angle Ψ0 is 0° and when the incident angle Ψ0 is 45°, the division result decreases as the damage degree increases, indicating an increase in uniformity. And in the graph using the separation distance extraction process shown in FIG. 9B, as shown by ○ and ■ respectively, when the incident angle Ψ0 is 0° and when the incident angle Ψ0 is 45°, the division result decreases as the damage degree increases, indicating an increase in uniformity.

[0059] Therefore, it is speculated that the undulation component affects the uniformity index as noise. By obtaining the uniformity index as an example of the evaluation index based on the removal result of removing the undulation component of the data distribution from the data distribution, the reliability of the evaluation index can be further enhanced. And due to the reduction of the difference in the division result (uniformity index) between the incident angles by the removal of this undulation component, the removal of the undulation component is also useful from the perspective of the variation in the measurement conditions in actual measurement.

[0060] These control processing unit 2, input unit 3, output unit 4, IF unit 5, and storage unit 6 can be configured by, for example, a computer such as a desktop type, notebook type, or tablet type. When the data acquisition unit 1 is an interface circuit or a communication interface circuit, the IF unit 5 can be shared with the data acquisition unit 1. Therefore, including the data acquisition unit 1, the metal fatigue evaluation device D can be configured by a computer.

[0061] Next, the operation of this embodiment will be described. FIG. 10 is a flowchart showing the operation of the metal fatigue evaluation device.

[0062] When the power supply of the metal fatigue evaluation device D with such a configuration is turned on, it executes the initialization of each necessary part and starts its operation. In the control processing unit 2, the control unit 21, the distributed processing unit 22, and the index processing unit 23 are functionally configured by executing the control processing program. In addition, if necessary, the index processing unit 23 is functionally configured with a waviness component extraction unit 231 and an index calculation unit 232.

[0063] When the evaluation start is input, in FIG. 10, first, the metal fatigue evaluation device D acquires diffraction ring data from the data acquisition unit 1 and stores it in the storage unit 6 (S1). More specifically, in the present embodiment, the data acquisition unit 1 irradiates the evaluation target Ob with an X-ray beam from the X-ray irradiation unit 14 under the control of the control unit 13, images the diffraction ring with the imaging unit 15 under the control of the control unit 13, and generates diffraction ring data representing the diffraction ring. Then, the data acquisition unit 1 outputs this diffraction ring data to the control processing unit 2.

[0064] Next, the metal fatigue evaluation device D obtains, as data distribution, the peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit 1 in process S1, or the half-width distribution with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit 1 in process S1, by the distributed processing unit 22 of the control processing unit 2, and stores it in the storage unit 6 (S2).

[0065] Next, the metal fatigue evaluation device D obtains an evaluation index based on the removal result obtained by removing the undulation component included in the data distribution from the data distribution obtained by the distribution processing unit 22 in the process S2 by the undulation index processing unit 23 of the control processing unit 2, and stores it in the storage unit 6 (S3). For example, the index processing unit 23 directly obtains the removal result from the data distribution by the separation interval extraction process, and obtains the evaluation index based on the obtained removal result. Alternatively, for example, the index processing unit 23 extracts the undulation component included in the data distribution from the data distribution obtained by the distribution processing unit 22 in the process S2 by the undulation component extraction unit 231, and the index calculation unit 232 removes the undulation component extracted by the undulation component extraction unit 231 from the data distribution obtained by the distribution processing unit 22 in the process S2 to obtain a removal result, and obtains the evaluation index based on the obtained removal result.

[0066] More specifically, in the present embodiment, the index processing unit 23 obtains the standard deviation in the peak intensity distribution of the diffraction ring with respect to the azimuth angle from which the undulation component has been removed as the uniformity index, that is, the evaluation index. Alternatively, the index processing unit 23 obtains the standard deviation in the half-width distribution with respect to the azimuth angle from which the undulation component has been removed as the uniformity index (the evaluation index). Alternatively, the index processing unit 23 obtains the division result obtained by dividing the standard deviation in the peak intensity distribution of the diffraction ring with respect to the azimuth angle from which the undulation component has been removed by the average value of the peak intensity distribution in the diffraction ring with respect to the azimuth angle as the uniformity index (the evaluation index). Alternatively, the index processing unit 23 obtains the division result obtained by dividing the standard deviation in the half-width distribution with respect to the azimuth angle from which the undulation component has been removed by the average value of the half-width distribution in the diffraction ring with respect to the azimuth angle as the uniformity index (the evaluation index).

[0067] Then, the metal fatigue evaluation device D outputs the obtained evaluation index from the output unit 4 by the control processing unit 2, and ends this process (S4). Note that, if necessary, the evaluation index may be output from the IF unit 5 to an external device.

[0068] Further, the user (operator) may evaluate metal fatigue by an evaluation index based on the peak intensity distribution of the diffraction ring, or may evaluate metal fatigue by an evaluation index based on the full width at half maximum distribution of the diffraction ring, or may evaluate metal fatigue by an evaluation index based on the peak intensity distribution of the diffraction ring and an evaluation index based on the full width at half maximum distribution of the diffraction ring.

[0069] As described above, the metal fatigue evaluation apparatus D in the embodiment, as well as the metal fatigue evaluation method and the metal fatigue evaluation program implemented thereon, obtain the evaluation index based on the removal result obtained by removing the waviness component, which is noise, from the data distribution, so that a more reliable evaluation result can be obtained.

[0070] The metal fatigue evaluation apparatus D, the metal fatigue evaluation method, and the metal fatigue evaluation program described above obtain a uniformity index indicating the degree of uniformity of the data distribution as an evaluation index indicating the degree of metal fatigue, so that the degree of metal fatigue can be evaluated more appropriately.

[0071] According to the above, it is possible to provide the metal fatigue evaluation apparatus D that obtains, as the uniformity index, that is, the evaluation index, the standard deviation in the data distribution or the division result obtained by dividing the standard deviation in the data distribution by the average value of the data distribution, as well as the metal fatigue evaluation method and the metal fatigue evaluation program implemented thereon. When using the division result as the uniformity index, the metal fatigue evaluation apparatus D, as well as the metal fatigue evaluation method and the metal fatigue evaluation program implemented thereon, divide the standard deviation by the average value, so that the influence of the variation in the irradiation time of the beam on the evaluation index can be reduced.

[0072] When generating the removal result after extracting the waviness component, the metal fatigue evaluation apparatus D, as well as the metal fatigue evaluation method and the metal fatigue evaluation program implemented thereon, can use a known extraction process for extracting the waviness component, and can easily generate the removal result obtained by removing the waviness component from the data distribution.

[0073] The above-described metal fatigue evaluation device D, as well as the metal fatigue evaluation method and metal fatigue evaluation program implemented thereon, use filtering processing or envelope processing for extracting the undulation component, so that the undulation component can be extracted by simple processing.

[0074] In order to describe the present invention, the present invention has been appropriately and fully described through embodiments with reference to the drawings above. However, it should be recognized that those skilled in the art can easily make changes and / or improvements to the above-described embodiments. Therefore, as long as the modified or improved forms implemented by those skilled in the art do not depart from the scope of the claims described in the claims, the modified or improved forms are construed to be included within the scope of the claims of the claims.

Explanation of Reference Numerals

[0075] D Metal fatigue evaluation device 1 Data acquisition unit 2 Control processing unit 11 High-voltage power supply 12 Cooling unit 13, 21 Control unit 14 X-ray irradiation unit 15 Imaging unit 22 Distribution processing unit 23 Index processing unit 231 Undulation component extraction unit 232 Index calculation unit

Claims

1. A method for evaluating metal fatigue for obtaining an evaluation index representing the degree of metal fatigue in a metal object to be evaluated, a data acquisition step of acquiring diffraction ring data representing a diffraction ring formed by irradiating the object to be evaluated with a beam having a property of diffracting; a distribution processing step of obtaining, as a data distribution, a peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step, or a half-value width distribution with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step; and an index processing step of obtaining the evaluation index based on a removal result obtained by removing a waviness component included in the data distribution from the data distribution obtained in the distribution processing step. A method for evaluating metal fatigue.

2. The evaluation index is a uniformity index representing the degree of uniformity of the data distribution, The method for evaluating metal fatigue according to claim 1.

3. The uniformity index is a standard deviation in the data distribution or a division result obtained by dividing the standard deviation in the data distribution by an average value of the data distribution, The method for evaluating metal fatigue according to claim 2.

4. The index processing step includes a waviness component extraction step of extracting a waviness component included in the data distribution from the data distribution obtained in the distribution processing step, and an index calculation step of obtaining the evaluation index based on a removal result obtained by removing the waviness component extracted in the waviness component extraction step from the data distribution obtained in the distribution processing step. The method for evaluating metal fatigue according to any one of claims 1 to 3.

5. In the waviness component extraction step, the waviness component is extracted from the data distribution obtained in the distribution processing step by filtering processing using a Gaussian filter or by envelope processing for extracting an envelope. The method for evaluating metal fatigue according to claim 4.

6. A metal fatigue evaluation program executed by a computer for obtaining an evaluation index representing the degree of metal fatigue in a metal object to be evaluated, a data acquisition step of acquiring diffraction ring data representing a diffraction ring formed by irradiating the object to be evaluated with a beam having a property of diffracting; a distribution processing step of obtaining, as a data distribution, a peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step, or a half-value width distribution with respect to the azimuth angle in the diffraction ring data acquired in the data acquisition step; An index processing step of obtaining the evaluation index based on a removal result obtained by removing a waviness component included in the data distribution from the data distribution obtained in the distribution processing step. A metal fatigue evaluation program.

7. A metal fatigue evaluation apparatus for obtaining an evaluation index representing the degree of metal fatigue in an evaluation target of a metal, A data acquisition unit that acquires diffraction ring data representing a diffraction ring formed by irradiating the evaluation target with a beam having a property of diffracting; A distribution processing unit that obtains, as a data distribution, a peak intensity distribution of the diffraction ring with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit, or a half-value width distribution with respect to the azimuth angle in the diffraction ring data acquired by the data acquisition unit; An index processing unit that obtains the evaluation index based on a removal result obtained by removing a waviness component included in the data distribution from the data distribution obtained by the distribution processing unit. A metal fatigue evaluation apparatus.

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