JP2006138865A - Evaluation method for cleanliness of alloy steel for highly clean structure - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an evaluation method for cleanliness of alloy steel for highly clean structure, having high reliability for high cleanliness. <P>SOLUTION: This evaluation method for cleanliness of alloy steel for highly clean structure comprises performing a rough ultrasonic flaw detection for detecting at least positions and numbers of nonmetallic inclusions in an inspection sample at a predetermined flaw detection scanning pitch is performed for a predetermined inspection volume, performing precise ultrasonic flaw detection for detecting grain sizes of the inclusions detected by the rough ultrasonic flaw detection with a flaw detection scanning pitch narrower than that in the rough ultrasonic flaw detection, and measuring the number of massy or granular oxide-based inclusions having a grain size of 25 μm or more. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a method for evaluating the cleanliness of a highly clean structural alloy steel, and more particularly to a method for evaluating the cleanliness of a steel material having a high cleanliness reliability.

Due to recent improvements in metallurgical technology, the cleanliness of steel has been greatly improved, and medium to large non-metallic inclusions in steel materials exceeding 20 microns (in this specification, including medium-type inclusions, simply “large-size inclusions”). ”, Mainly CaO—Al ₂ O ₃ —MgO system is much smaller and smaller in size (in this specification,“ non-metallic inclusions ”are simply referred to as“ inclusions ”). Sometimes). Under such circumstances, it is very difficult to detect medium to large inclusions that occur accidentally or with a very low probability.

However, non-metallic inclusions such as oxide inclusions (eg Al ₂ O ₃ , MgO · Al ₂ O ₃ , CaO + MgO · Al ₂ O ₃ etc.) and nitride inclusions are used for bearing steel and machine structures, for example. Steel materials such as carbon steel are likely to cause fatigue failure and remain a problem.

By the way, at present, as an inspection method for checking the cleanliness of a metal material such as a steel material, a method of collecting a test piece from a metal material to be analyzed and inspecting the surface of the test piece with an optical microscope is generally used. Taking steel as an example, `` JIS G 0555 Microscopic testing method for non-metallic inclusions in steel '', which has been adopted as a standard method for evaluating inclusions in steel, `` ASTM E45 Standard Practice for Determining the Inclusion Content of The method using a microscope such as “Steel”, “DIN50602”, and “ISO4967” has a problem that the detection accuracy of large inclusions is low because the inspection area of the inspection sample is as small as 100 to 200 mm ² / piece, for example. It was. In the past, it has been desired to inspect large volumes, but there has been no suitable method.

  In addition, as another method, a method of extracting inclusions from a metal material by acid dissolution and evaluating the particle size of the inclusions with a microscope, or a method of observing the inclusions that have been dissolved and floated by dissolving the metal material by an EB dissolution method Has been proposed (see, for example, Patent Document 1 and Patent Document 2). However, in the acid dissolution method, the inclusions may be dissolved in the acid or the inclusions may be dissolved to reduce the diameter. In addition, it takes time to dissolve the acid, resulting in inferior speed of treatment and it is difficult to cope with the mass production process of the product. In addition, the EB dissolution method is a method in which a small piece of about a few grams to be a test sample is dissolved, and the inclusions that have floated are observed with a microscope, but the inclusions may be melted and aggregated. No solution has been found.

Therefore, it has been desired that a steel material that needs to be inspected for a large volume has been given a more reliable cleanliness evaluation.
JP-A-9-125199 JP-A-9-125200

  It is an object of the present invention to provide a method for evaluating the cleanliness of a highly clean structural alloy steel that is highly reliable with high cleanliness.

In order to solve the above-mentioned problems, the following means were adopted in the method for evaluating the cleanliness of the steel alloy for high cleanliness structure according to the present invention.
(1) Rough ultrasonic flaw detection for detecting at least the position and number of non-metallic inclusions in the inspection sample at a predetermined flaw detection scanning pitch is performed for a predetermined inspection volume, and the flaw detection scanning pitch is made narrower than rough ultrasonic flaw detection. Cleaning of high-clean structural alloy steel that performs precision ultrasonic flaw detection to detect the particle size of inclusions detected by coarse ultrasonic flaw detection and measures the number of massive or granular oxide inclusions having a particle size of 25 μm or more Degree evaluation method.
(2) The method for evaluating the cleanliness of the high cleanliness structural alloy steel according to (1), wherein the precision ultrasonic flaw detection is performed only for inclusions whose positions are specified by rough ultrasonic flaw detection.
(3) Particles present in a predetermined reference volume from a predetermined inspection volume and the number of massive or granular oxide inclusions having a particle diameter of 25 μm or more obtained by rough ultrasonic inspection and precision ultrasonic inspection Volume-converted to the number of massive or granular oxide inclusions having a diameter of 25 μm or more, and volume-converted to a predetermined reference volume, the number of massive or granular oxide-based inclusions having a particle diameter of 25 μm or more is predetermined. The steel having been confirmed to be less than or equal to the number of steels is selected as steel having high cleanliness and having high reliability, and the cleanliness evaluation of the high cleanliness structural alloy steel according to (1) or (2) above Method.
(4) The size of the inspection sample is such that the scanning area can be set to 10 to 10,000 mm 2 and the inspection depth can be set to 0.5 to 50 mm when performing rough ultrasonic flaw detection. The method for evaluating the cleanliness of the highly clean structural alloy steel according to any one of the above.
(5) Record the position where the reflected wave signal was obtained from the reflected wave signal obtained by the rough ultrasonic flaw detection, the positive half wave intensity and negative half wave intensity of the reflected wave, and the waveform of the reflected wave signal. From these records, only the reflected wave signal having a MURAI value of less than 0.6 shown in the following formula (A) is used as a lump or granular oxide inclusion having a particle size of 25 μm or more, and The method for evaluating the cleanliness of the alloy steel for highly clean structure according to any one of (1) to (4), wherein the number is measured.

MURAI value = P / (P + N) (A)
P: Positive half-wave intensity, N: Negative half-wave intensity (6) The test sample is a test sample prepared from high cleanliness aluminum killed steel containing Al ≧ 0.005 wt%. The evaluation method of the cleanliness of the high clean structural alloy steel according to any one of the above.

  ADVANTAGE OF THE INVENTION According to this invention, it can be set as the evaluation method of the cleanliness of the alloy steel for highly clean structure with high reliability with high cleanliness. Further, according to the present invention, it is possible to provide a high clean structural alloy steel that has a long life even under severe conditions and has little variation in the remaining life.

The method for evaluating the cleanliness of the high clean structural alloy steel of the present invention is obtained by performing ultrasonic inspection in two ways, rough inspection and precision inspection, detecting inclusions contained in the steel material, and obtaining by ultrasonic inspection. Based on the measured data, the number of inclusions having a particle size (in this specification, the particle size of a massive or granular inclusion may be simply referred to as “inclusion diameter”) is 25 μm or more, and the object to be analyzed This is to evaluate the cleanliness of the metal material. As a result, the steel that is confirmed to be 10 or less per 3000 mm ³ of the reference volume of the steel to be inspected is selected as a steel having high cleanliness and high reliability. Two types of ultrasonic inspection, rough inspection and precision inspection, provide a steel with high reliability of inclusions. According to the method of evaluating the cleanliness of the high clean structural alloy steel of the present invention, the number of inclusions having a particle size of 25 μm or more is determined by the two types of ultrasonic flaw detection of rough flaw detection and precision flaw detection. Those that are confirmed to be 10 or less per 3000 mm ³ are selected as products. More preferably, the number of inclusions is 5 or less per 3000 mm ³ of the reference volume of the steel to be inspected.

  Further, as the highly clean structural alloy steel to be analyzed of the present invention, the cleanliness of the inclusions as described above is clarified, and the highly clean structural alloy steel having an oxygen content of 6 ppm or less is used. It is mentioned as a preferable form. In addition, as such high clean structural alloy steel, high clean structural alloy steel is carbon steel for machine structure, structural alloy steel with guaranteed hardenability, nickel chromium steel, nickel chromium molybdenum steel, chromium steel, Examples include chrome molybdenum steel, nickel molybdenum steel, manganese steel for machine structures, manganese chrome steel, high temperature alloy steel bolt steel, special purpose alloy steel steel bar steel, aluminum chrome molybdenum steel steel and bearing steel steel. Such steels are, for example, carbon steel for machine structural use (JIS G 4051), structural steel with guaranteed hardenability (JIS G 4052), nickel chrome steel (JIS G 4102). ), Nickel-chromium-molybdenum steel (JIS G 4103), chromium-steel steel (JIS G 4104), chromium-molybdenum steel (JIS G 4105), manganese steel for machine structures / manganese-chromium steel (JIS G 4106), high temperature Alloy steel bolt material (JIS G 4107), special purpose alloy steel bolt rod material (JIS G 4108), aluminum chrome molybdenum steel material (JIS G 4202), and bearing steel material JIS G 4051, JIS G 4104 And carbon steel, medium carbon alloy steel, case-hardened steel, and the like.

  The high clean structural alloy steel obtained by the present invention is a high clean structural alloy steel with high cleanliness accuracy with respect to inclusions, long life even under severe conditions, and little variation in remaining life.

  Next, detection of the particle size of inclusions will be described.

  The rough flaw detection is performed to detect at least the position and number of inclusions, and then the fine flaw detection is performed only on the inclusions detected by the rough flaw detection, and the size of the inclusion is mainly detected by the fine flaw detection ( taking measurement.

  Coarse flaw detection and precision flaw detection are to detect inclusions in an inspection sample of a steel material to be examined by ultrasonic flaw detection. In ultrasonic flaw detection, an ultrasonic wave (hereinafter sometimes referred to as a “beam”) is emitted from a probe, hits an object, detects the reflected wave, and reflects the reflected wave intensity and reflected waveform information (output as a graph). Desired information is obtained based on the waveform, the positive half-wave intensity, and the negative half-wave intensity). In scanning by the probe, ultrasonic waves are emitted and reflected waves are received at a plurality of positions with a predetermined interval of the inspection sample (this interval is referred to as “flaw detection scanning pitch” or simply “scanning pitch”).

  As for the method for evaluating the cleanliness of the high clean structural alloy steel of the present invention, rough flaw detection with a wider flaw detection scanning pitch than precision flaw detection and precision flaw detection with a flaw detection scanning pitch narrower than rough flaw detection are performed. .

  In rough flaw detection, at least the position and number of inclusions in the inspection sample are detected at a predetermined flaw detection scanning pitch. The flaw detection scanning pitch in rough flaw detection can be arbitrarily set based on the size of the inspection sample, the expected size of non-metallic inclusions, etc., but is set at least larger than in the case of precision flaw detection, preferably the focal position. And ½ of the diameter of the beam bundle from the probe. If the beam bundle is ½ or less of the diameter of the beam bundle, inclusions can be detected in a region where the reflected wave intensity is about 70% or more even in the case of rough flaw detection. For example, a reflected wave intensity of 70% means that only a reflected wave having an intensity of 70% can be obtained due to a beam shift with respect to a maximum reflected wave intensity of 100% originally obtained from the inclusion. The preferable flaw detection scanning pitch in the rough flaw detection is more specifically 30 to 150 μm, and particularly preferably 30 to 50 μm.

  Thus, the rough flaw detection is performed, and the position and number of inclusions included in the inspection volume of the inspection sample are detected. By performing rough flaw detection, it is possible to quickly specify the position and number of inclusions to be detected for a large-volume inspection sample. Note that an approximate value of the inclusion diameter in the inspection sample may be measured at the stage of the rough flaw detection.

  After performing the rough flaw detection, a precision flaw detection is performed in order to accurately detect the size of the detected inclusion. The precision flaw detection is performed by setting the flaw detection scanning pitch to be narrower than that of the rough flaw detection, and preferably the flaw detection scanning pitch is set so as to minimize the influence of attenuation in the radial direction (horizontal direction) of the ultrasonic beam. The flaw detection scanning pitch that minimizes the influence of attenuation is just above the detected one inclusion (the position where the reflected wave intensity is maximum is “directly above”, and this position is the origin). (The position directly above is the origin, the reflected wave intensity is 100%), and this probe can be moved back and forth and left and right. Although it depends on the type of high-clean structural alloy steel or probe to be inspected, specifically, the flaw detection scanning pitch in precision flaw detection is preferably 5 to 10 μm.

  The reflected wave intensity from the inclusion obtained by applying the ultrasonic beam is desirably the maximum reflected wave intensity that can be received from the inclusion from the viewpoint of improving accuracy. However, if the flaw detection scanning pitch is too large, even if the ultrasonic beam hits the inclusion, only a value smaller than the maximum reflected wave intensity that should be originally obtained from the inclusion may be obtained. The ultrasonic beam emitted from the probe has a width because it is a bundle of beams, but there is a difference in intensity between the central portion and the outer peripheral portion of the beam. In addition, there is a difference in reflected wave intensity between when the beam bundle hits the center of the inclusion and when it hits the peripheral part. The maximum reflected wave intensity that should be originally obtained is considered to be obtained when the center of the ultrasonic beam bundle hits directly above the inclusion (center of the inclusion), and this maximum value can be detected accurately. Ultrasonic flaw detection leads to accurate detection of inclusion size. That is, by performing precision flaw detection with a narrow flaw detection pitch for inclusions detected in advance by rough flaw detection, the size of inclusions can be detected with high accuracy.

  FIG. 3 and FIG. 6 show how the reflected wave intensity varies depending on the position in the radial direction (horizontal direction). Referring to FIG. 6, when the center of the probe is deviated by 15 μm from the position “0.0” of the maximum reflected wave intensity from the inclusion (reflected wave intensity 100%), the reflected wave intensity may be attenuated by 6%. Recognize.

  As described above, it is desirable that the reflected wave intensity from the inclusion is desirably the maximum reflected wave intensity that can be received from the inclusion. Even when the focal depth of the ultrasonic beam is deviated from the depth of the inclusion, the reflected wave intensity is lowered from the maximum value that should be originally obtained from the diameter of the inclusion. Therefore, it is preferable to perform depth correction (attenuation correction) on the reflected wave intensity obtained by precision flaw detection. FIG. 4 shows an example of an axial attenuation correction curve (depth correction curve). Depth correction can be performed according to the following depth correction formula (1).

<Depth correction formula>
A = B / f = B / (1 + ad + bd ² ) (1)
Where A: corrected reflected wave intensity (%)
B: Reflected wave intensity (actual measured value)
f: Correction coefficient a, b: Coefficient d: Deviation between defect depth and depth of focus
(| D | <e, e = constant)
The above depth correction can be performed according to distance amplitude compensation.

  The above-mentioned “defect” refers to a thing causing a reflected wave other than inclusions such as inclusions and cavities.

  The size of the inclusion can be expressed, for example, as the particle size of the inclusion (the maximum diameter of the inclusion, which may be referred to as “inclusion diameter” in this specification). Specifically, for example, a calibration curve between the maximum diameter of the inclusion and the reflected wave intensity is created in advance, and the maximum diameter of the inclusion can be calculated from the reflected wave intensity obtained by ultrasonic flaw detection. . The calibration curve is obtained, for example, by performing ultrasonic flaw detection to obtain the reflected wave intensity from the inclusion, cutting out the flaw detection area portion of the inspection sample subjected to this ultrasonic flaw detection, and dissolving the acid to take out the inclusion. It can create by calculating | requiring the diameter of an inclusion by SEM observation.

  The calibration curve is represented by the following formula (2) as a general formula. A specific example of the calibration curve is shown in FIG. The straight line shown in FIG. 5 is expressed as equation (2-1).

<General formula of calibration curve>
Y = PX + Q (2)
However, Y: inclusion diameter X: reflected wave intensity after correction <calibration curve type shown in FIG. 5>
Y = 0.34X + 11.85 (2-1)
Y: Inclusion diameter (μm)
X: Intensity of reflected wave after correction (%)

  Regarding the method for evaluating the cleanliness of the high clean structural alloy steel of the present invention, at least the position and number of inclusions in the inspection sample are detected in the rough flaw detection as described above. From the target for precise flaw detection, the target that generates abnormal waveform (abnormal signal) from the received signal of the reflected wave detected by rough flaw detection is not the reflected wave from the inclusion. The form to exclude is mentioned. Reflected waveform information is information obtained by receiving reflected waves. Specifically, reflected wave intensity, reflected waveform information (waveform output as a graph, positive half wave intensity, negative half wave intensity, etc.) It is information such as. The positive half wave intensity is the intensity of the reflected waveform that is above the reference line, and the negative half wave intensity is the intensity of the reflected waveform that is below the reference line.

  A cavity may be generated in the inspection sample, and a reflected wave is also generated from such a cavity. In some cases, the probe receives an irregularly reflected wave as a reflected wave signal from the outside. By excluding the reflected wave signal that is generated from things other than the inclusions that are intended for detection, it is possible to eliminate detection of extraneous objects by precision flaw detection following the rough flaw detection. Can be done.

  The abnormal signal as described above can be distinguished from an abnormal signal due to a cavity or the like, or a signal from an inclusion for detection purposes, based on the waveform of the reflected wave. The waveform itself can be detected by graphing and can be identified by looking at its shape, and positive half wave intensity or negative half wave intensity serving as an index for knowing the waveform can be detected and discriminated as a numerical value.

  The high clean structural alloy steel may have a non-negligible effect on the reflected wave intensity depending on the state of heat treatment of the high clean structural alloy steel or the characteristics of the steel. For example, steel is easily affected by the state of heat treatment. Therefore, it is preferable to calibrate the sensitivity when converting the reflected wave received by the ultrasonic flaw detector as the reflected wave intensity in advance.

  That is, a primary sensitivity calibration that performs ultrasonic flaw detection on a standard test piece for reference sensitivity calibration (abbreviated as “standard test piece S”) and determines a reference sensitivity of an ultrasonic flaw detector equipped with a probe; After the sensitivity calibration, the sensitivity calibration amount is obtained from the reflected wave intensity from the standard test piece A for obtaining the sensitivity calibration amount and the reflected wave intensity from the test piece B having the same shape as the standard test piece A. It is preferable to perform in advance a sensitivity calibration including a secondary sensitivity calibration for performing calibration before performing the rough flaw detection.

  The standard test piece S is subjected to ultrasonic flaw detection, and the reference sensitivity of the ultrasonic flaw detection apparatus is set. Examples of the standard test piece S include a test piece having FBH (Flat Bottom Hole, 1/16 inch (0.4 mm)), and specifically, a standard test piece B-020 defined in ASTM E127 is exemplified. Is done. The primary correction can be performed by storing the reflected wave intensity from the standard test piece S in the apparatus.

  The secondary sensitivity calibration is performed following the primary sensitivity calibration. In the secondary sensitivity calibration, a test piece (test piece B) having the same shape as the standard test piece A is prepared from the standard test piece A and the metal material to be examined, and the reflected wave intensity of the test piece B is based on the standard test piece A. The sensitivity calibration amount Y is obtained and calibrated.

  The standard test piece A is a test piece having an artificial defect or a plate bottom surface at the focal depth position, and FIG. 8 shows an example thereof. As the material used for the standard test piece A, steel subjected to quenching and tempering treatment is preferable because of its high sensitivity.

  Sensitivity calibration uses an artificial defect or plate bottom at the depth of focus (FIG. 8) to determine the measurement sensitivity at test piece B, which is equivalent to the measurement sensitivity at standard test piece A. The sensitivity calibration amount is obtained as a difference between the reflected wave intensity at the standard specimen A and the reflected wave intensity at the specimen B. Alternatively, the sensitivity calibration amount Y is determined by the following sensitivity calibration formula (3).

<Sensitivity calibration type>
Y = 20 × log (Y ₁ / Y ₂ ) (3)
However,
Y: Calibration weight Y _1: in the test piece B, the reflected wave intensity from the artificial defect or bottom wave intensity Y _2,: Artificial in a standard test piece A, the reflected wave intensity from the artificial defect or as a bottom surface wave intensity Y _1, When using the reflected wave intensity from the defect, Y ₂ also uses the reflected wave intensity from the artificial defect with the same sensitivity, and when using the bottom wave intensity as Y ₁ , Y ₂ also uses the bottom wave intensity with the same sensitivity. Use.

  FIG. 9 shows a decrease in reflected wave intensity for four different test pieces B such as heat treatment when the reflected wave intensity for the standard test piece A is set to 100%. FIG. 9 shows the results of scanning each test piece subjected to four different treatment methods using SUJ2 as the test piece. “QT” is quenched and tempered, “N” is normalized, “A” is annealed, and “LA” is forged. The B1 echo shown in FIG. 9 is the first echo generated by the ultrasonic wave emitted from the probe hitting the defect or the bottom of the plate. As shown in FIG. 9, it is recognized that the test piece just forged is lowered to about 55 to 65%. Therefore, it is desirable to calibrate so that these reflected wave intensities are equivalent to the standard specimen A, that is, detected as 100%. In this case, the sensitivity calibration amount can be obtained as an amount obtained by converting the difference between the reflected wave intensity at the standard test piece A and the reflected wave intensity at the test piece B into decibels (dB). As can be seen from FIG. 9, the difference in reflected wave intensity from the standard specimen A tends to be different due to the difference in heat treatment. Therefore, the primary and secondary sensitivity calibrations described above are performed for each material with different treatment such as heat treatment. Preferably, it is done.

  By performing the primary sensitivity calibration and the secondary sensitivity calibration described above, it is possible to suppress a decrease in measurement accuracy due to the material characteristics of the metal material to be examined.

As the inspection sample, for example, a specimen prepared by cutting out a test piece from a highly clean structural alloy steel which is an object can be used. The number and size of the inspection samples can be appropriately determined from the volume of the metal material to be scanned to be scanned by ultrasonic flaw detection, the ultrasonic flaw detection apparatus, and the like. The following are illustrated as a preferable form. In performing ultrasonic flaw detection, the size of the inspection sample is preferably set to such a size that the scanning area can be about 10 to 10,000 mm ² and the inspection depth can be about 0.5 to 50 mm. From the viewpoint of statistical processing, it is preferable that a plurality of locations of the steel material to be inspected become inspection sites, but the number of inspection samples is not particularly limited, and ultrasonic flaw detection is performed for a predetermined inspection volume. Just do it. The inspection volume of the inspection sample actually measured by ultrasonic flaw detection is preferably at least 3000 mm ³ .

In the method for evaluating the cleanliness of the high clean structural alloy steel of the present invention, the number of predetermined inclusions per a reference volume of 3000 mm ^{3 of the} steel to be tested is specified. By setting the inspection volume, which is the volume of the inspection sample subjected to rough flaw detection, to 3000 mm ³ , the number of inclusions per 3000 mm ³ of the reference volume of the steel to be tested can be obtained, but the inspection volume is set larger. Then, the number of inclusions per reference volume of 3000 mm ³ may be obtained by volume conversion.

  In addition, steel generally has countless micro cavities as cast, and scanning by ultrasonic flaws may generate countless irregular reflections and noise, which may make inspection difficult. Thus, by rolling the inspection sample in advance, the cavity portion is pressure-bonded, and adverse effects such as irregular reflection can be suppressed.

  In addition, when using a test piece cut out from a high clean structural alloy steel as an inspection sample, as a region to be scanned by ultrasonic flaw detection, there is a peripheral region that is a rolling direction L plane and that has a D / 4 position as a center line. Is preferred. In this specification, the “D / 4 position” is a position corresponding to a ¼ distance of the diameter from the central axis or outer periphery of the test sample.

  Ultrasonic flaw detection is applied in the method for evaluating the cleanliness of the high clean structural alloy steel of the present invention, but various types of ultrasonic flaw detection devices and probes are already on the market. Can be used. As a preferred probe, a focus type high frequency probe and the like can be cited. The detection capability of the flat type probe is said to be ½ wavelength, but the focal type probe has a ¼ wavelength, and the cleanliness evaluation method of the present invention is suitably used for the focal type probe. It is suitable for detection of inclusions of about 10 to 200 μm. The probe frequency is preferably about 20 to 125 MHz.

  FIG. 2 illustrates an outline of ultrasonic flaw detection using a focus-type probe. The ultrasonic flaw detector shown in FIG. 2 includes a PC having a microprocessor, and a program for performing arithmetic processing according to the flowchart shown in FIG. 1 is incorporated in the microprocessor. By providing such a PC in an ultrasonic flaw detector, a large amount of data processing can be performed quickly.

In the method for evaluating the cleanliness of the high clean structural alloy steel of the present invention, the cleanliness of the metal material to be analyzed is determined by measuring the number of inclusions having a particle size of inclusions of 25 μm or more as described above. It is something to evaluate. And the steel which confirmed that it is 10 or less (more preferably 5 or less) per 3000 mm < ³ > of reference | standard volume of the steel of a test object is selected as steel with high reliability that it is high cleanliness. . Further, the property may be specified by a comprehensive cleanliness evaluation. For example, the overall cleanliness can be evaluated based on the inclusion data obtained as a result of the rough inspection and the precision inspection. Data obtained by rough flaw detection and precision flaw detection is the number, position, size, and the like of inclusions, and the particle size distribution can also be expressed as a histogram based on these data. Moreover, you may confirm the data which estimated the maximum inclusion diameter in the whole highly clean structural alloy steel of test object, for example using statistical methods, such as an extreme value statistical method, from the obtained actual measurement data.

  These cleanliness evaluations can be made by, for example, obtaining data on a highly clean structural alloy steel having a predetermined property in advance and comparing this data with data from another inspection sample, or desired property data. And the data of the test sample can be compared.

  As a high-clean structural alloy steel to be analyzed according to the present invention, aluminum is preferably added for the purpose of deoxidizing in order to suppress bubbles or reduce the content of oxygen that causes inclusions. Steel grades and alloys such as aluminum killed steel, and more specifically, high cleanliness aluminum killed steel containing Al ≧ 0.005 wt% can also be mentioned.

  Hereinafter, the cleanliness evaluation method of the present invention will be described in more detail with reference to examples. However, the cleanliness evaluation method of the present invention is not limited to the following examples.

<Preparation of inspection sample>
SCM420 round bar steel slabs manufactured by continuous casting method were prepared. This round bar-shaped steel piece was forged into a round 65, and an L-section test piece was cut out. Each test piece was milled to have a thickness of 10 mm, and was further polished to obtain a test sample.

<Setting basic conditions for ultrasonic flaw detection>
For ultrasonic flaw detection, an ultrasonic flaw detector equipped with a focus type high-frequency probe (50 MHz) was used. The focal position was set to 1.25 mm, and the gate was set to 1.0 to 1.5 mm.

  Table 1 shows the flaw detection conditions and their detection capabilities.

<Primary sensitivity calibration>
Ultrasonic flaw detection is performed on a flat bottom hole (φ0.4FBH) with a diameter of 0.4mm and a depth of 0.76mm of the B-020 standard test piece specified in ASTM E127, and the ultrasonic beam is applied to the φ0.4FBH. The ultrasonic flaw detector was set so that the maximum reflected wave intensity obtained when focusing was set to 100%. It is considered that the linearity of the reflected wave intensity can be maximized by setting in this way.

<Secondary sensitivity calibration>
A test piece (test piece B) having the same shape as the standard test piece is prepared from the standard test piece A and the metal material to be examined, and the defect of the test piece B (with the focus on the bottom surface of the test piece) ( A sensitivity calibration amount Y for matching the reflected wave intensity of the bottom surface of the test piece with the reflected wave intensity of the defect of the standard test piece A (bottom surface of the test piece) was obtained and set in the ultrasonic flaw detector. The sensitivity calibration amount Y is obtained as a calibration amount that uses the bottom of the plate at the depth of focus so that the reflected wave measurement sensitivity of the standard specimen A and the measurement sensitivity of the specimen B are the same. . Specifically, focusing on the bottom of the production of a 1.5 mm thick plate from the quenching and tempering material (base) of high carbon chromium bearing steel and the quenching material (metal material to be tested) of SCM420, The measurement sensitivity was calibrated so that the bottom wave strength in the quenching material of SCM420 was equal to the bottom strength in the quenching and tempering material of high carbon chromium bearing steel.

<Creation of calibration curve>
A 10-mm thick test piece was hardened by round milling from a round bar-shaped steel piece of high carbon chromium bearing steel manufactured by a continuous casting method in the same manner as described in <Preparation of Inspection Sample> above. A test piece was prepared by tempering and surface polishing.

  Each test piece was subjected to rough flaw detection and precision flaw detection, and the reflected wave intensity from the inclusions was determined. Further, the inclusion diameter was determined by an acid dissolution method. That is, the flaw detection area portion of the test piece subjected to this ultrasonic flaw detection was cut out, these were acid-dissolved, the inclusions were taken out, and the inclusion diameter was determined by SEM observation.

The reflected wave intensity by ultrasonic flaw detection and the inclusion diameter by acid dissolution method are arranged in order from small to large, and the strength by ultrasonic flaw detection is correlated with the inclusion diameter measured by acid dissolution method. A calibration curve was created. A calibration curve is shown in FIG. The straight line shown in FIG. 5 is expressed as equation (2-1).
Y = 0.34X + 11.85 (2-1)
Y: Inclusion diameter (μm)
X: Intensity of reflected wave after correction (%)
Correlation coefficient r = 0.96
<Ultrasonic flaw detection of inspection sample>
Thirty test pieces of SCM420 hardened material were produced in the same manner as described in the above “Production of inspection sample”.

  Each test piece as an inspection sample was subjected to a rough flaw detection with a flaw detection area of 15 mm × 100 mm × 2 pieces (one set) and a flaw detection scanning pitch of 0.03 mm. From the reflected wave signal obtained by the rough flaw detection, the intensity of the positive half wave (P), the intensity of the negative half wave (N) and the waveform were recorded as the intensity of the reflected wave, and the position and number of inclusions were specified. Table 2 shows the data obtained by the rough flaw detection.

From the MURAI values, those that showed abnormal values that were judged to be caused by surface echoes or cavities were identified (defect No. 12).
MURAI value = P / (P + N) (4)
There is a report that the MURAI value for the reflected wave from the cavity is 0.6 to 0.7, and since it may be 0.7 or more when jumping from the surface echo, the MURAI value is abnormally 0.6 or more. Judged as value.

Precision inspection was performed only for each inclusion in each test piece whose position was specified by rough inspection. The precision flaw detection was performed with a flaw detection area of 1 × 1 mm and a flaw detection scanning pitch of 0.005 mm.

The reflected wave intensity obtained by precision flaw detection was corrected by the following depth correction formula (1-1).
f≈1-6 × d ² (Probe: at 50 MHz) (1-1)
Where f: correction coefficient d: deviation between defect depth and depth of focus (mm) (| d | ≦ 0.3)
The inclusion diameter was calculated from the corrected reflected wave intensity using a calibration curve (FIG. 5) showing the relationship between the reflected wave intensity and the inclusion diameter determined in advance. Table 3 shows the results of precision flaw detection.

  Although it was possible to identify that the defect No. 12 showed an abnormal value from the result of the rough flaw detection, in this example, the flaw detection was also performed for the defect No. 12 for confirmation. As a result, it was confirmed that an abnormal value was exhibited even when precision flaw detection was performed. Therefore, it has been clarified that those having an abnormal value in rough flaw detection can be excluded from the objects of precision flaw detection.

<Evaluation of cleanliness of steel>
Under the above-described ultrasonic flaw detection condition setting in this example, 14 types of SCM420 steel materials having different heat lots were used as the steel to be examined, and ultrasonic flaw detection was performed. Each steel to be tested is SCM420 steel material produced by continuous casting method, and each steel piece was produced as a test piece in the same manner as described in <Preparation of inspection sample> from the round bar-shaped steel piece of this steel. . For detection of inclusions (ultrasonic flaw detection), after scanning one test piece of 15 × 100 × 0.5 × 2 mm = 1500 mm ³ for each test steel, the reference volume per 3000 mm ³ The number of inclusions in terms of volume was determined.

  The rotating bending test was performed according to JISZ2273 and JISZ2274. The results are shown in Table 4.

The numerical value in parentheses in the column “Number of granular oxide inclusions” in Table 4 is the average number of inclusions when the volume is converted to a standard volume of 3000 mm ³ .

From the above results, the number of inclusions having a particle size of 25 μm or more is 10 or less per 3000 mm ³ of the reference volume of the steel to be inspected and the oxygen content is 6 ppm or less (in Table 4, Highly clean structural alloy steels 1 to 10) were used as SCM420 products with high cleanliness. As is clear from Table 4, the number of inclusions having a particle size of 25 μm or more is 10 or less per 3000 mm ³ of the reference volume of the steel to be inspected, and the steel having an oxygen content of 6 ppm or less is a fatigue life test. The result of the fatigue limit measurement by the rotating bending test is good.

<Experimental example>
The variation in reflected wave intensity (%) was examined by changing the flaw detection scanning pitch by ultrasonic flaw detection. The reflected wave intensity (%) indicates how much the actually reflected wave intensity is attenuated with respect to the maximum reflected wave from the inclusion intended for detection.

  A small range including one inclusion waveform was detected at various scanning pitches, and the reflected wave intensity was recorded. The maximum reflected wave intensity at the minimum pitch (0.005 mm) was 100%. Similar investigations were performed on multiple inclusions.

  The results are shown in FIG. As shown in FIG. 10, it can be seen that the variation in reflected wave intensity (%) increases as the scanning pitch increases. That is, it can be seen that when the scanning pitch is increased, the maximum reflected wave intensity originally obtained from the inclusion intended for detection cannot be received in many cases, and the accuracy decreases.

It is a figure which shows the flowchart which shows the operation procedure of rough flaw detection and precision flaw detection. It is a figure which shows typically the outline of the ultrasonic flaw detection by a focus type probe. It is a figure which shows description of a beam diameter. It is a figure which shows a depth correction curve. It is a figure which shows the calibration curve of reflected wave intensity and inclusion diameter. It is a figure which shows the relationship between radial attenuation | damping and a flaw detection scanning pitch. It is a figure which shows the example of the test piece for depth correction curve creation. It is a figure which shows the example of the test piece for sensitivity calibration. (A) is a defect wave test piece, and (B) is a bottom wave test piece. It is a figure which shows the comparison of the intensity | strength of the defect wave and bottom face wave by two types of test pieces on the same heat processing conditions. It is a figure which shows the change of the reflected wave intensity by a flaw detection scanning pitch.

Claims (6)

Performing a rough ultrasonic flaw detection for a predetermined inspection volume to detect at least the position and number of non-metallic inclusions in the inspection sample at a predetermined flaw detection scanning pitch,
Perform a precise ultrasonic flaw detection to detect the particle size of inclusions detected by the rough ultrasonic flaw by narrowing the flaw detection scanning pitch than the rough ultrasonic flaw detection,
A method for evaluating the cleanliness of a high clean structural alloy steel, wherein the number of massive or granular oxide inclusions having a particle size of 25 μm or more is measured.   2. The method for evaluating the cleanliness of a high clean structural alloy steel according to claim 1, wherein the precision ultrasonic flaw detection is performed only for inclusions whose positions are specified by the rough ultrasonic flaw detection. From the predetermined inspection volume and the number of massive or granular oxide inclusions having a particle size of 25 μm or more obtained by the coarse ultrasonic inspection and the precision ultrasonic inspection,
In terms of the number of massive or granular oxide inclusions having a particle size of 25 μm or more present in a predetermined reference volume,
Reliability of steel having high cleanliness that the number of massive or granular oxide inclusions having a particle size converted to the predetermined reference volume of 25 μm or more is equal to or less than the predetermined number 3. The method for evaluating the cleanliness of a highly clean structural alloy steel according to claim 1 or 2, wherein the steel is selected as a steel having a high value. The size of the inspection sample is a size that allows a scanning area to be set to 10 to 10000 mm ² and an inspection depth to be set to 0.5 to 50 mm when performing the rough ultrasonic flaw detection. To 3. The method for evaluating the cleanliness of the highly clean structural alloy steel according to any one of items 1 to 3. From the reflected wave signal obtained by the rough ultrasonic flaw detection, the position where the reflected wave signal was obtained and the intensity of the positive half wave, the negative half wave intensity and the waveform as the intensity of the reflected wave are recorded,
From the record, only the reflected wave signal having a MURAI value of less than 0.6 represented by the following formula (A) is used as a massive or granular oxide inclusion having a particle size of 25 μm or more,
5. The method for evaluating the cleanliness of a highly clean structural alloy steel according to claim 1, wherein the number of the massive or granular oxide inclusions is measured.
MURAI value = P / (P + N) (A)
P: positive half wave intensity, N: negative half wave intensity 6. The cleanliness of the high cleanliness structural alloy steel according to any one of claims 1 to 5, wherein the test sample is a test sample made from a high cleanliness aluminum killed steel containing Al ≧ 0.005 wt%. Evaluation method.

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