JP2001141704A - Method for evaluating cleanliness of metallic material by ultrasonic flaw detection - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method for quickly evaluating the cleanliness of a metallic material with high precision and high reliability. SOLUTION: n-Pieces of detection parts are set in prescribed positions of a metallic material to be inspected, and a scanning for intra-metallic nonmetallic inclusion is performed by ultrasonic flaw detection for every inspection part to detect the maximum nonmetallic inclusion diameter aj (j=1, n), and the estimated maximum nonmetallic inclusion diameter amax in the metallic material to be inspected is calculated from the detected maximum nonmetallic inclusion diameter aj (j=1, n) every each inspection position by use of the equation 1 to evaluate the cleanliness of the metallic material to be inspected. Linear regression expression of maximum nonmetallic inclusion diameter aj (j=1, n) and a standardized variable yj (j=1, n) a=ty+u...1 wherein n = frequency of inspections, standardized variable yj=-ln[-ln j/(n+1)}] (j=1, n), t = regression coefficient, and u = constant.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for evaluating the cleanliness of a metal material. More specifically, a predetermined inspection site of a metal material to be inspected is scanned by an ultrasonic flaw detection method, and nonmetallic inclusions contained therein (for example,
Oxide, nitride, sulfide, etc.), and from these data, calculate the estimated maximum non-metallic inclusion diameter in the test target metal material using a predetermined formula to determine the cleanliness of the test target metal material. It is about the method of evaluation.

[0002]

2. Description of the Related Art With the recent improvement in metallurgical technology, the cleanliness of metallic materials such as steel has been greatly improved, and non-metallic inclusions in medium to large metallic materials exceeding 20 microns have been further reduced and large. It is also getting smaller. Under such circumstances, it is very difficult to detect a large inclusion that occurs accidentally or with a very low probability.

[0003] However, under such circumstances, no technology has been developed that can actually evaluate and guarantee the cleanliness of metal materials.

At present, as a standard inspection method for checking the cleanliness of a metal material, a method using an optical microscope is standard. However, in this method, the area to be inspected is about 1000 mm ^2.
It cannot be used as a method for evaluating the cleanliness of a metal material having high cleanliness as described above (JIS G 0555, ASTM E45, ASTMA).
295, DIN 50602, ISO 4967, etc.).

Further, a method of extracting inclusions from a metallic material by acid dissolution and evaluating the particle size of the inclusions with a microscope has been proposed.
A method has been proposed in which a metal material is melted by a melting method and inclusions that have floated are observed with a microscope (Japanese Patent Application Laid-Open No. 9-1 / 1991).
25199, JP-A-9-125200), inclusions are dissolved in an acid, or inclusions themselves are melted and aggregated,
Neither of these methods can be used to evaluate the cleanliness of highly clean metallic materials.

Furthermore, the above-described methods are inferior in processing speed, for example, it takes a long time to dissolve the acid, and it is also difficult to cope with mass production of products.

[0007]

SUMMARY OF THE INVENTION Accordingly, the present invention provides a method for evaluating the cleanliness of a metal material in response to recent improvements in metallurgical technology and a drastic improvement in the cleanliness of metal materials such as steel. It will not be provided.

Another object of the present invention is to provide a method for quickly evaluating the cleanliness of a metal material, which is compatible with such a mass-production process of the metal material.

By the way, the present inventor aims to solve the above-mentioned first problem by changing the speculum area to the reference inspection area S ₀ =
A method for estimating the maximum inclusion diameter in the test target metal material by the procedure of the extreme value statistical method from the maximum inclusion diameter appearing in each sample, taking the number of samples n = 30 to 60 as 100 mm ² , Although it has been studied, the reliability of the prediction of the large inclusions is still low. For this reason, it has not become a technique usable for evaluating the cleanliness of metal materials.

[0010]

SUMMARY OF THE INVENTION The present invention provides means for solving the above-mentioned problems, the gist of which is as set forth in the appended claims. The details will be described below.

[0011]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The invention described in claim 1 of the present application is
"N inspection sites are set at a predetermined portion of the metal material to be inspected, and the non-metallic inclusions in the metal are scanned by ultrasonic flaw detection for each inspection site, and the maximum non-metallic inclusion diameter a _j (j = 1, n)
Then, from the detected maximum non-metallic inclusion diameter a _j (j = 1, n) for each detected site, the following equation (1) is obtained.
A metal characterized in that the estimated maximum non-metallic inclusion diameter a _max in the test target metal material is calculated by (1 ′), (a) and (b) to evaluate the cleanliness of the test target metal material. Material cleanliness evaluation method. [Equation 1] Linear regression equation of maximum non-metallic inclusion diameter a _j (j = 1, n) and normalization variable y _j (j = 1, n) a = ty + u (1) Here, n = number of inspections Normalized variable y _j = −ln [−ln ｛j / (n + 1)]] (j = 1
n) t = regression coefficient u = constant [Equation 1 '] Estimated maximum non-metallic inclusion diameter a in the test object metal
Formula for calculating _max a _max = t × y _max + u (1 ′) where V _o = inspection reference volume (mm ³ ) V = volume to be predicted (mm ³ ) T ( recursive _{period) = (V + V o)} / V o y max ( normalized variable) = - ln [-ln {( T-1) / T]
] [Formula A] 30 ≦ V / V ₀ ≦ 10000 (1) [Formula 2] 1 ≦ V ₀ ≦ 400000 (2) ” It is.

First, the present inventor found that as a result of various studies, 20
In a situation where non-metallic inclusions in a metal material exceeding a micron are further reduced and the size is reduced, large-sized inclusions that occur accidentally or with a very low probability are detected by microscopic observation. We concluded that the method was extremely difficult. It was considered that such large inclusions did not always appear on the test surface, but rather were often hidden and not observed.

For this reason, it has been considered that the evaluation and the quality assurance of the cleanliness of the metal material using the method by microscopic observation are inferior in the speed of processing, and it is practically difficult to cope with the mass production process of the product.

As a result of various studies, the inventor of the present invention has conceived of using an ultrasonic flaw detection method, particularly a high-frequency focus type apparatus. The ultrasonic flaw detection method is basically a non-destructive inspection method, and can be expected to have advantages such as rough sample preparation, large volume inspection, and rapid inspection.

By basically adopting the ultrasonic flaw detection method, non-metallic inclusions (for example,
With respect to the maximum diameter of oxides, nitrides, sulfides, etc.), the present invention has succeeded in achieving the effect of enabling inspection of 1,000 to tens of thousands times as large as the conventional one.

Next, the next feature of the present invention resides in that n inspection sites to be subjected to ultrasonic flaw detection are set in a predetermined portion of a metal material to be inspected.

The inspection site is set, for example, at the top, middle, and bottom of a continuous cast steel piece to be inspected as shown in FIG. Set to a site that is likely to occur. It is preferable to collect a plurality (for example, three) of sample pieces having the same shape from the set inspection site. Thereby, all parts can be inspected efficiently. In addition, if the inspection part (inspection sample) is set at all the top, middle, and bottom parts of the metal material to be inspected, parts corresponding to the initial, middle, and end stages of casting can be inspected.

The number n is 30 to 6 in statistical calculation.
0 is preferred.

The area scanned by ultrasonic flaw detection for each inspection site (inspection sample) is, for example, a maximum area of 700 × 700 m.
A range from m ² to a minimum area of 1.0 × 1.0 mm ² is possible. The flaw detection depth is 0.1mm to 5mm
The degree is normal (average depth about 1 mm).

Therefore, the normal scanning area according to the method of the present invention is (20-100 mm) × (20-100 mm) = 400
~10000mm ² / number and then, when the number n = 30 to 60 pieces test site (test sample), scanning inspection area per charge is 12000~600000mm ² / charge, taking into account the depth volume → area converted (× 100 Doubled layer) is 1,200,000 to 60,000,000 mm ² / charge. Therefore, the inspection area of the conventional optical microscope is at most 1000 mm ² / charge, but the inspection has been performed 1,000 to tens of thousands times as large as this.

Next, in the present invention, the maximum non-metallic inclusion diameter a _j (j = 1, n) is detected for each of the inspection sites. As a method for detecting the maximum non-metallic inclusion diameter a _j , there are a method of inspecting n pieces from different portions, a method of dividing one large specimen, and the like.

A method for determining the maximum non-metallic inclusion diameter a _j (j = 1, n) in each test site or test sample is as follows.
Compare the ultrasonic wave height data with each other to find the maximum value of the ultrasonic wave height data, convert the maximum value of the ultrasonic wave height data to obtain the maximum non-metallic inclusion diameter, and convert the ultrasonic wave height data calculating a nonmetallic inclusion diameter data D _i, the method of determining the maximum non-metallic inclusion diameter from non-metallic inclusion size in data D _i, may be any method.

Next, the maximum non-metallic inclusion diameter a _j (j = 1, n) for each inspection site detected in this way is calculated from the above-mentioned equations (1) and (1 ′) in the metal material to be inspected. _Is calculated as the estimated maximum non-metallic inclusion diameter a _max .

This formula extracts inclusions in steel by acid dissolution,
Or it was obtained by cutting and observing with a microscope to determine the dimensions, and by making the ultrasonic wave height and diameter correspond,
The maximum non-metallic inclusion diameter a _max in the entire test target metal material has been successfully estimated with extremely high accuracy from partial data of the test target metal material.

Here, V / V ₀ and V ₀ are represented by the following formulas (1) and (2).
The range is as shown in b. [Formula A] 30 ≦ V / V ₀ ≦ 10000 ······· (A) [Formula B] 1 ≦ V ₀ ≦ 400,000 ····· (B) (V) , V ₀ are in units of “mm ³ ”. That is, the ratio (V / V ₀ ) between the volume of the metal material to be predicted and the inspection reference volume is set in the range shown by the formula (a), and the inspection reference volume is set. Let the magnitude of V ₀ be the range shown by equation (2). FIG. 2 shows the range indicated by the formulas A and B.

The cleanliness evaluation method of the present invention, Threshold and although intended to be done in the area of the range ABDE represented by B, V / V and more preferably V / V ₀ ≦ 50 as an upper limit of ₀
Is 00, more preferably V / V ₀ ≧ 60 as the lower limit of the other V / V _0. Further, more preferably the upper limit of V ₀ is V ₀ ≦ 40000, and more preferably a lower limit of the other V ₀ V is ₀ ≧ 10. Threshold and ABDE in the area is a range indicated by B, if more preferably the upper limit and lower limit of the upper and lower limits or V ₀ which V / V _0, as described above, the maximum intervention of inclusions in metallic materials The object diameter can be accurately predicted. Further, in the ABDE region, more preferably, in the upper and lower limits described above, the size of a sample piece to be subjected to ultrasonic flaw detection is easy to handle, and a large volume of metal is used in an inspection reference volume in a range that is easy to handle. Accurate prediction of the material is possible, and the inspection efficiency is excellent. On the other hand, when V / V ₀ <30 (the area below the straight line passing through AB in FIG. 2), the area is within the range of the actual data and does not need to be specifically predicted. Also, V ₀ > 40
In the case of 0000 (the area to the right of the straight line passing through the BD), the inspection reference volume is excessively large with respect to the volume to be predicted, and the measurement is extremely difficult. Also, V / V ₀ > 100
At 00 (the area above the straight line passing through the DE), the accuracy of the predicted volume may decrease. Further, when V ₀ <1 (region on the left side of the straight line passing through the AE), the size of the sample piece to be subjected to ultrasonic testing is small, and the detection accuracy of inclusions may decrease.

For example, when the ranges indicated by the formulas (a) and (b) are converted into weights for steel, the results are as shown in Table 1.

[0028]

[Table 1]

[0029] The invention according to claim 2 of the present application provides a method for detecting a maximum non-metallic inclusion diameter a _j (j = 1, n) for each inspection site, wherein a plurality of upper non-metallic inclusions are included for each inspection site. 2. The cleanliness evaluation of a metal material according to claim 1, wherein the maximum non-metallic inclusion diameter a _j (j = 1, n) is selected after obtaining an object diameter and removing an abnormal value from among them. The method. "

The abnormal value referred to here is a reflected wave from a cavity that is not a non-metallic inclusion, a diving diffuse reflection noise, and the like, and can be distinguished from a normal value by a waveform.
Such abnormal values are generated in a considerably large number when the temperature is about normal, but usually, for example, 5 points for each inspection site.
This can be dealt with by obtaining the non-metallic inclusion diameter data.

Thus, there is an advantage that data from a defect that is not an inclusion can be omitted.

According to a third aspect of the present invention, there is provided a method as set forth in the first or second aspect, wherein the diameter of the non-metallic inclusion is obtained by converting the ultrasonic reflected wave height data from the non-metallic inclusion. Method for evaluating cleanliness of metal materials. "

According to the present inventor's research, between the non-metallic inclusion diameter a _n and the reflected ultrasonic wave height C was found that the following relational expression holds. As a result, consistent computer processing of data is enabled, large-volume data can be handled, and high-speed and high-precision evaluation of cleanliness of metal materials has been achieved.

Non-metallic inclusion diameter a _n = p × ultrasonic reflected wave peak value C + q (4) where p and q = constant The invention described in claim 4 of the present application is based on “non-metallic inclusion diameter 4. The method for evaluating cleanliness of a metal material according to claim 3, wherein the value is calculated by using a calibration curve corresponding to an ultrasonic reflected wave height and a nonmetallic inclusion diameter.

The calibration curve is a relation between the reflected wave height of the inclusions in the metal material previously determined for each probe and the diameter of the inclusions obtained by extracting the inclusions in the metal material by acid dissolution or the like. Means a relational expression or a calibration curve. FIG. 3 shows an example.

The inventor of the present invention has conducted various studies with the aim of creating a calibration curve for converting the diameter of inclusions from the height of the reflected ultrasonic wave, and as a result, a high-frequency probe (20 to 150 MHZ) was used in advance to determine the amount of metal contained in the metal material. The reflected wave height of inclusions was investigated and the conditions for obtaining the reflected wave height from inclusions under stable conditions were grasped. The sample is subjected to acid dissolution without impairing the morphology of the inclusions, the inclusions are extracted, the diameter of the inclusions is measured by microscopic observation, and an accurate relational expression showing the relationship between the reflected wave peak value and the diameter of the inclusions ( Calibration curve) (Fig. 3).

Regression equation (example) y = 0.34x + 11.85 (correlation coefficient r = 0.96) The invention described in claim 5 of the present application is directed to “the maximum non-metallic inclusion diameter a _j ( j = 1, n), the non-metallic inclusions in the metal are scanned by ultrasonic flaw detection for each inspection site to obtain ultrasonic reflected wave height data from each non-metallic inclusion,
Find the maximum value by comparing the ultrasonic reflected wave height data,
The cleanliness evaluation of a metal material according to claim 3 or 4, wherein the maximum nonmetallic inclusion diameter a _j (j = 1, n) is calculated from the maximum value in the ultrasonic reflected wave height data. Method. ".

As described above, there is a correlation between the diameter of the non-metallic inclusion and the ultrasonic wave height data from the non-metallic inclusion, so that the ultrasonic wave height data from the non-metallic inclusion are compared. If the maximum value is obtained in this way, this ultrasonic reflected wave height data is the ultrasonic reflected wave height data from the non-metallic inclusion having the largest diameter. Therefore, first, a maximum value is obtained by comparing ultrasonic reflected wave height data from nonmetallic inclusions, and a maximum nonmetallic inclusion diameter a _j (j = 1, n) is converted from the maximum value to obtain the maximum value. Is also good.

According to the invention described in claim 6 of the present application, "n inspection sites are set in a predetermined portion of a metal material to be inspected, and non-metallic inclusions in the metal are scanned by ultrasonic flaw detection for each inspection site. To detect ultrasonic reflected wave height data I _j (j = 1, n) from the largest non-metallic inclusion at each inspection site,
From the detected ultrasonic reflected wave height data I _j (j = 1, n) from the largest non-metallic inclusion for each inspection site, the following equation (2)
And (2 ′), the estimated maximum ultrasonic reflected wave height data I _max from the estimated maximum non-metallic inclusion in the metal material to be inspected
, And then the estimated maximum ultrasonic reflected wave height data I
_A method for evaluating the cleanliness of a metal material, comprising calculating an estimated maximum nonmetallic inclusion diameter from _max and evaluating the cleanliness of the metal material to be inspected. [Equation 2] Linear regression equation of ultrasonic reflected wave height data I _j (j = 1, n) from maximum non-metallic inclusion and standardized variable y _j (j = 1, n) I = t × y + u (2) where n = the number of inspections, standardized variable y _j = −ln [−ln ｛j / (n + 1)]] (j = 1,
n) t = regression coefficient u = constant [Equation 2 '] Calculation formula (regression formula) of ultrasonic reflected wave height data I _max from estimated maximum non-metallic inclusion in test object metal (regression formula) I _max = t × y _max + u (2 ′) where V _o = inspection reference volume (mm ³ ) V = volume to perform prediction (mm ³ ) T (recursion period) = (V + V _o ) / V _o y _max (normalized variable) = -ln [-ln ｛(T-1) / T]
] [Formula A] 30 ≦ V / V ₀ ≦ 10000 (1) [Formula 2] 1 ≦ V ₀ ≦ 400000 (2) ” It is.

Similarly, since there is a correlation between the diameter of the non-metallic inclusions and the ultrasonic wave height data from the non-metallic inclusions, first, the above equation is derived from the ultrasonic wave height data from the non-metallic inclusions. by calculating the reflected ultrasonic wave height data I _max from the estimated maximum non-metallic inclusion in a test subject in the metal, then converts the estimated maximum non-metallic inclusion diameter from said estimated maximum ultrasound reflected wave height data I _max It is also a good procedure.

According to a seventh aspect of the present invention, there is provided a method for cleaning a metal material according to any one of the third to sixth aspects, wherein the ultrasonic reflected wave height data is corrected for the depth distance by the following equation (3). Degree evaluation method. " [Equation 3] Reflected wave height data B = Ultrasonic wave height data A × depth correction coefficient fd (3) where fd = 1 + ad + bd ² d = distance from focus position in metal to inclusion (| d | ≦
e) a, b, and e = constant In the practice of the present invention, it has been found that, when the position of the inclusion is shifted back and forth from the focal position, the disadvantage that the ultrasonic reflection intensity from the inclusion decreases. (FIG. 4). When this phenomenon occurs, the accuracy of the method of the present invention may be impaired.

Therefore, a method for introducing a distance correction formula for reflection intensity has been developed (FIG. 4). According to the present invention, the accuracy of the method of the present invention can be further improved.

FIG. 4 can be expressed by the following equation.

Fd = 1−0.032667d−1.9675d ² The invention described in claim 8 of the present application is based on the description that “for some or all of the test sites, the test sites are cut out and used as test samples.
The method for evaluating the cleanliness of a metal material according to any one of claims 1 to 7, wherein scanning of nonmetallic inclusions in metal is performed by ultrasonic flaw detection. ".

By cutting out the inspection site and using it as an inspection sample, it is possible to perform n repeated continuous inspections and automatic measurement, especially by making the inspection sample the same shape in the vertical, horizontal, and thickness directions.

It is more preferable that the shape of the test sample to be cut out is such that the entire cross-section including the outer peripheral portion, the central portion, and an intermediate portion between the two can be inspected. By adopting such a shape, the worst part of the nonmetallic inclusion can be efficiently inspected.

In general, the center is the final solidification position, and the inclusions are discharged into the concentrated molten steel and the amount of the settling of the inclusions is large. The detection rate is significantly improved, and as a result, the accuracy of the cleanliness evaluation can be greatly improved.

The fine steel material and plate material include the center, including the center, the characteristics of the probe (the range of flaw detection in the depth direction), the surface entrance side dead zone, the thickness of the effective flaw detection width, and the vicinity of the opposite surface (bottom side). The thickness of the sample piece may be determined in consideration of this.

The invention according to claim 9 of the present application is characterized in that "the subject is forged before scanning the nonmetallic inclusions in the metal at each inspection site by the ultrasonic flaw detection method. 8. The method for evaluating the cleanliness of a metal material according to any one of 8.

In the case of metal materials, there are a myriad of microscopic cavities that cannot be inspected by irregular reflection when cast as is. Generally, when scanning by an ultrasonic flaw detection method, an infinite number of irregular reflections and noise due to this are generated. Inconvenience occurs. Therefore, if the subject is squeezed before ultrasonic scanning, these are compressed and the cavities disappear,
The effect of being able to inspect only necessary inclusions is obtained.

According to a tenth aspect of the present invention, there is provided the metal material according to any one of the first to ninth aspects, wherein the probe used for the ultrasonic flaw detection is a focus type high frequency probe. Cleanliness evaluation method. "

The object of the present invention is to detect minute inclusions with high accuracy. However, if a focus type high frequency probe is used, the detection capability, which is conventionally known as 波長 wavelength in a flat type, is reduced to a focus type. It was found that a remarkable effect that approximately 1/4 wavelength detection ability was obtained was obtained.

Further, it is preferable that the flaw detection pitch be equal to or less than 1/2 of the effective diameter of the beam bundle at the focal position of the focus type high frequency probe. In this method, the focus beam bundle of the probe can be grasped by using a test piece having a special minute artificial defect. .

[0054] The invention described in the claims 11, "according to one of claims 1 to 10, characterized in that the surface roughness R _{ma x} of the material surface to incident ultrasound or less 5.0μm Is a method for evaluating the cleanliness of metal materials. "

As a result of research on the method of the present invention utilizing the ultrasonic flaw detection method, it is effective to set the surface roughness R _max of the material surface to 5.0 μm or less from the viewpoint of ultrasonic attenuation and noise generation prevention. It turned out to be.

The method for reducing the surface roughness R _max of the material surface to 5.0 μm or less is not particularly limited.
For example, wet polishing may be performed on the material surface.

The evaluation method of the present invention is applicable to various metal materials including Mg alloy, Al alloy, Ti alloy, Cr alloy, Fe alloy, Co alloy, Ni alloy, Cu alloy, Zn alloy, Ag alloy, and Au alloy. Although widely applicable, preferred examples include Fe alloys and Ni alloys, and more preferred are aluminum killed steel and the like, such as suppressing bubbles and lowering the oxygen content that is a source of inclusions. It is suitable for a steel type or an alloy to which aluminum is added for the purpose of deoxidation, and more specifically, a high cleanliness aluminum killed steel containing Al ≧ 0.005 wt% is preferable.

[0058]

Embodiments of the present invention will be described below in detail. In addition, although the following Example shows the example using a steel material, the evaluation method of this invention is not limited to the following Examples.

[Example 1] 1. Test target metal material and its treatment As a test target metal material, manufactured by a continuous casting method,
Using a round bar-shaped steel piece as shown in FIG. 1 of 165 t high carbon Cr bearing steel (for a rod tube), the cleanliness was evaluated by the method of the present invention.

In each of the round bar-shaped steel slabs shown in FIG. 1, three or four inspection sites were set, and forging was performed at a forging ratio of 9 to obtain 70 × 70 from each inspection site. × 12m
A total of 30 m test pieces (test samples) were cut out. next,
Wet polishing was performed on the surface of each sample to make Rmax ≦ 4.0 μm or less. Thus, a 70 × 70 × 12 mm sample piece was obtained, and the 70 × 70 mm surface was used as a scanning surface.

[0061] 2. Sampling of Inspection Data For each sample piece processed as described above, a 62 × 62 mm portion excluding the outer circumference 4 mm of the scanning surface was used as a measurement portion, and a flaw detection test was performed at a depth of approximately 1.5 mm at a depth of approximately 1 mm. .0m
The measurement was performed for inclusions existing between m. Ultrasonic flaw detection was performed when the probe scanned a portion corresponding to the reference area, the reflected wave height was measured, and further corrected by a reflection intensity distance correction coefficient (FIG. 4) and recorded as data. For the ultrasonic flaw detection, scanning was performed under a condition of 50 to 125 MHz using a focus type probe. FIG. 5 shows a schematic diagram during ultrasonic flaw detection.

Up to five ultrasonic reflected wave peak values from each test sample are individually evaluated in descending order, and at the same time, <incident reflected wave peak value (%), detection position (x, y, z coordinates), reflected wave characteristics (Waveform inversion—that is, cavity / inclusion discrimination)>. Table 2 shows the results.

[0063]

[Table 2]

Actually, the C scope image was divided and designated, and a start point was designated and scanning was performed. After the calculation, I created a worksheet and read it into memory. The five data collection numbers include preliminary data for confirming the presence or absence of abnormalities in the measured values after the test, selecting the optimum value, and finding a solution.

The optimum value was selected for each inspection site, and the maximum reflected wave height value for each inspection site was selected.

Next, the maximum non-metallic inclusion diameter a _j (j = 1, n) was determined from the maximum reflection peak value for each inspection site by a calibration curve (the relationship between the inclusion reflection peak value-inclusion diameter). .

3. Estimation of the maximum non-metallic inclusion diameter in the test target metal material The maximum non-metallic inclusion diameter a _j (j = 1, n) for each of the 30 sample pieces (inspection sites) obtained as described above. From this, the estimated maximum non-metallic inclusion diameter a _max was determined.

First, the optimum maximum reflected wave height value for each sample piece (inspection site) obtained by excluding abnormal values such as surface wave echoes and cavity waveforms and the maximum nonmetallic inclusion diameter a obtained from the calibration curve are minimized. A ₁ , a ₂ ,... A
Defined as _j .

Here, 1, 2,...
A value obtained by calculating j twice by logarithm is a normalized variable y _j in the proviso to [Equation 1]. Table 3 shows an example of j, a _j , and y _j . In FIG. 6, the inclusion diameter is plotted in order from the smallest inclusion diameter (i.e., a ₁ ) with the abscissa representing the inclusion diameter and the ordinate representing this standardized variable. And this ●
Is a straight line that rises to the right on the right side of FIG.

[0070]

[Table 3]

Here, the largest inclusions in each test piece by the ultrasonic flaw detection test are arranged in ascending order. When marked on an extreme value probability sheet, it is represented as shown in FIG. 6, and the standardized variable y on the vertical axis is obtained by taking the logarithm of the cumulative distribution (probability) of the sample twice and linearizing it. In order to predict the maximum inclusion diameter a _max included in the region for a certain volume V, the vertical axis corresponding to the volume V (standardization variable ) May be used to determine the corresponding inclusion diameter. Y, the scaling variable for the volume V for which the prediction is made
_{The max} can be obtained from the recursion period T (= (V + V ₀ ) / V ₀ ). That is, this conversion equation is [Equation 1 '],
[Expression 1 '] The value of the vertical axis (normalization variable) corresponding to the volume V to be predicted at T (recursion period) in the proviso may be obtained.

For example, in the case of FIG. 6, for a volume of 270,000 mm ³ to be predicted, the maximum inclusion diameter indicated by a straight line rising to the right on the right is 30.3 μm. The volume of 270,000 mm ³ is 2.12 kg in terms of weight. In addition, if it is assumed that the thickness is about 1.0 mm measured by ultrasonic testing, 520 mm
This means that the maximum inclusion diameter existing in the four planes has been estimated.

4. Evaluation of cleanliness cleanliness rating test subject metal material of the test object metal material, the estimated maximum inclusion size: a _max, inspection reference volume: V _o mm ^3, volume for prediction: providing a Vmm ³ Can be.

In this embodiment, the evaluation of the cleanliness of the round bar-shaped steel ingot as the metal material to be inspected is based on the estimated maximum inclusion diameter: a _max
= 30.3 μm, inspection reference volume: V _o = 3800 mm
^3. Volume for prediction: V = 270000 mm ³ .

As a comparative example, the same metal material as that used in the present example, 270000 mm ³ , was examined for inclusions by acid dissolution extraction. The maximum inclusion diameter was 35.0 μm.
m, demonstrating the high accuracy of the evaluation method of the present invention.

[Example 2] Spring steel (JIS steel type SUP)
10) was melted in an electric furnace for 150 tons. This was cast into a slab (bloom) having a cross section of 380 × 450 mm by continuous casting after RH degassing. Then, it was subjected to slab rolling to obtain a billet having a diameter of 167 mm and a weight of 2 ton. This is rolled, φ5
Was processed into a valve spring. When this spring was used, it was broken during use. When the broken portion was examined, inclusions of 60 μm were found.

On the other hand, from the rolled material subjected to the spring, a sample piece was cut out from the remaining rolled material that was stored without being subjected to the spring processing in the same manner as in Example 1 described above, and the sample piece was adjusted. As a result of ultrasonic testing and evaluation, it was estimated that the maximum inclusion diameter that could be present in about 2 ton (V = 0.255 × 10 ⁹ mm ³ ) of the rolled material subjected to the spring processing was 63 μm. In this embodiment _{2 V / V 0 = 0.255 ×} 10 9/3
800 = 67105. As described above, according to the present invention, V ₀ = 3800 mm ³ , V / V ₀
= 67105, it was confirmed that the cleanliness can be accurately evaluated.

Example 3 JI was used as the metal material to be evaluated.
The estimated maximum non-metallic inclusion diameter was determined in the same manner as in Example 1 except that S SCM steel (containing Al = 0.025%) was used. (Therefore, V ₀ = 3800 mm ³ , V =
270000 mm ³ , V / V ₀ ≒ 71.053. )
In addition, the actual measurement value of the maximum diameter of the inclusion obtained by dissolving each sample piece in acid was obtained. Table 4 shows the results.

[0079]

[Table 4]

[0080]

According to the present invention, the maximum non-metallic inclusion diameter in a large-volume metal material can be predicted accurately, with high reliability, and quickly using a small-volume test sample. be able to.

The present invention also contributes to the recent significant improvement in the cleanliness of metal materials such as steel, and contributes to the evaluation and quality assurance of the cleanliness of metal materials, which have become more demanding. An extremely useful invention that meets the needs of the industry. For a metal material user who performs mechanical processing on a metal material to produce a part, etc., if the prediction accuracy of the inclusion diameter in the material is improved, the prediction accuracy of the part strength at the design stage of the part etc. can be improved, Increased reliability to strength.
As a result, the components can be made smaller and lighter in the required range without requiring an excessive safety factor.

[Brief description of the drawings]

FIG. 1 is a diagram showing an example of setting an inspection site in a metal material to be inspected.

FIG. 2 is a diagram showing a range indicated by equations a and b.

FIG. 3 is a diagram showing a calibration curve for comparing the intensity of ultrasonic reflected waves from non-metallic inclusions with the diameter of non-metallic inclusions.

FIG. 4 is a diagram showing the relationship between the deviation from the focal position and the intensity of the reflected ultrasonic wave in ultrasonic flaw detection using a focused ultrasonic probe.

FIG. 5 is a schematic diagram showing a state of ultrasonic flaw detection by a focused ultrasonic probe.

FIG. 6 is a diagram showing a comparison between the optical microscopy (conventional method) and the method of the present invention in estimating the maximum inclusion diameter.

Claims (11)

[Claims] 1. A method for setting n inspection sites in a predetermined portion of a metal material to be inspected, scanning nonmetallic inclusions in metal by ultrasonic flaw detection for each inspection site, and determining a maximum nonmetallic inclusion diameter a _j
(J = 1, n) is detected, and then the following formulas (1), (1 ′), and (a) are obtained from the detected maximum non-metallic inclusion diameter a _j (j = 1, n) for each inspection site. And b) calculating an estimated maximum non-metallic inclusion diameter a _max in the metal material to be tested to evaluate the cleanness of the metal material to be tested. [Equation 1] Linear regression equation of maximum non-metallic inclusion diameter a _j (j = 1, n) and normalization variable y _j (j = 1, n) a = ty + u (1) Here, n = number of inspections Normalized variable y _j = −ln [−ln ｛j / (n + 1)]] (j = 1
n) t = regression coefficient u = constant [Equation 1 '] Estimated maximum non-metallic inclusion diameter a in the test object metal
_max calculation formula (regression formula) a _max = t × y _max + u (1 ′) where V _o = inspection reference volume (mm ³ ) V = predicted volume (mm) ³⁾ T (recursive _{period) = (V + V o)} / V o y max ( normalized variable) = - ln [-ln {( T-1) / T]
[Formula A] 30 ≦ V / V ₀ ≦ 10000 (1) [Formula 2] 1 ≦ V ₀ ≦ 400000 (2) 2. The maximum non-metallic inclusion diameter a _{j for} each inspection site
Upon detection of (j = 1, n), a plurality of upper non-metallic inclusion diameters are obtained for each inspection site, and after removing an abnormal value from these, the maximum non-metallic inclusion diameter a _j (j = 1 , N) is selected. The method for evaluating cleanliness of a metal material according to claim 1, wherein 3. The method for evaluating cleanliness of a metal material according to claim 1, wherein the diameter of the non-metallic inclusion is calculated by converting ultrasonic reflected wave height data from the non-metallic inclusion. 4. The evaluation of cleanliness of a metal material according to claim 3, wherein the diameter of the nonmetallic inclusion is obtained by conversion using a calibration curve corresponding to the height of the reflected ultrasonic wave and the diameter of the nonmetallic inclusion. Method. 5. The maximum non-metallic inclusion diameter a _{j for} each inspection site
When detecting (j = 1, n), non-metallic inclusions in metal are scanned by ultrasonic flaw detection for each inspection site to obtain ultrasonic reflection wave height data from each non-metallic inclusion, and the ultrasonic reflection The maximum value is obtained by comparing the wave height data, and the maximum non-metallic inclusion diameter a _j (j =
The method for evaluating cleanliness of a metal material according to claim 3, wherein the value is obtained by converting (1, n). 6. An n-piece inspection site is set in a predetermined portion of a metal material to be inspected, and a non-metallic inclusion in a metal is scanned for each inspection site by an ultrasonic flaw detection method, and the maximum non-metallic material in each inspection site is determined. Ultrasonic reflected wave height data I _j from the inclusion (j = 1,
n), and then the ultrasonic reflected wave height data I _j (j =
From (1, n), the estimated maximum ultrasonic reflected wave height data I _max from the estimated maximum non-metallic inclusion in the test target metal material is calculated by the following equations (2), (2 ′), (a) and (b). and, then, cleanliness evaluation method of a metallic material, characterized in that to calculate the estimated maximum non-metallic inclusion diameter from said estimated maximum ultrasound reflected wave height data I _max assess the cleanliness of a subject metal material. [Equation 2] Linear regression equation of ultrasonic reflected wave height data I _j (j = 1, n) from maximum non-metallic inclusion and normalized variable y _j (j = 1, n) I = ty + u (2) where n = the number of inspections Standardized variable y _j = −ln [−ln ｛j / (n + 1)]] (j = 1
n) t = regression coefficient u = constant [Equation 2 '] Formula for calculating ultrasonic reflected wave height data I _max from estimated maximum non-metallic inclusions in the test object metal I _max = t × y _max + u... (2 ′) where V _o = inspection reference volume (mm ³ ) V = volume to perform prediction (mm ³ ) T (recursion period) = (V + V _o ) / V _o y _max (normalization Variable) = − ln [−ln ｛(T−1) / T]
[Formula A] 30 ≦ V / V ₀ ≦ 10000 (1) [Formula 2] 1 ≦ V ₀ ≦ 400000 (2) 7. The ultrasonic wave reflected wave height data is subjected to depth distance correction by the following equation (3).
The method for evaluating cleanliness of a metal material according to any one of the above. [Equation 3] Corrected ultrasonic reflected wave height data B = Ultrasonic reflected wave height data A / depth correction coefficient fd (3) where fd = 1 + ad + bd ² d = from focal position in metal to inclusions Distance (| d | ≦
e) a, b and e = constants 8. The method according to claim 1, further comprising: cutting out the inspection site for a part or all of the inspection site to obtain an inspection sample, and then scanning nonmetallic inclusions in the metal by ultrasonic flaw detection. The method for evaluating cleanliness of a metal material according to any one of the above. 9. The metal material according to claim 1, wherein the subject is forged before scanning the nonmetallic inclusions in the metal at each inspection site by the ultrasonic flaw detection method. Cleanliness evaluation method. 10. The method for evaluating cleanliness of a metal material according to claim 1, wherein the probe used in the ultrasonic flaw detection method is a focus type high frequency probe. 11. cleanliness evaluation method of metallic material according to any one of claims 1 to 10, characterized in that at most 5.0μm surface roughness R _max of the surface of the material to incident ultrasonic waves.