Title of the invention: Method for evaluating the cleanliness of steel materials
Technical field
[0001]
The present invention relates to a method for evaluating the cleanliness of steel materials.
Background technology
[0002]
Conventionally, the rolling fatigue life of steel used for applications where rolling fatigue occurs, such as bearing steel, has a strong correlation with the amount of non-metal inclusions in the steel, especially the amount of oxide-based inclusions. It is known that there is. Therefore, the amount of non-metal inclusions in steel is measured by the JIS method (JIS-G0555) or ASTM (American Force Material Testing Association): E45 method, and the results are fed back to the steelmaking process to maintain a constant level. Quality steel, or higher quality steel, was produced.
[0003]
In addition, since the amount of oxide-based inclusions in steel naturally has a strong correlation with the oxygen content of steel, the oxygen content in steel is used in the production of steels that require cleanliness, such as steel for bearings. Various steelmaking methods that are effective in improving cleanliness, such as molten steel degassing, vacuum smelting, and ladle smelting, have been adopted in order to reduce the amount of steel.
Here, with the development of steelmaking technology in recent years, it has become possible to reduce the oxygen content of steel as much as possible, but when the oxygen content of steel becomes low, the amount of non-metal inclusions in steel is very small. And it becomes smaller. Therefore, in the above-mentioned JIS method and ASTM method, the measurement is performed in a region close to the detection limit, and therefore, there are some cases where it is not appropriate for the evaluation of the cleanliness level.
[0004]
In addition, the extreme value statistical method is adopted as a method for evaluating small inclusions of several tens of μm, which has higher measurement accuracy than the JIS method and ASTM method. The extremum statistical method is a popular evaluation method at present. The evaluation method is to observe 15 to 30 samples in a unit area of ​​about 100 mm 2 to 200 mm 2, record the maximum inclusion diameter for each sample, and use a statistical method to record the maximum inclusions present in the assumed area. It is to estimate the diameter.
[0005]
However, since the extremum statistical method is an evaluation method using statistics that evaluates a certain area and predicts the maximum inclusion diameter existing in the assumed area, it is not only the preparation of the sample but also the evaluation and analysis. Also had the problem that it took a lot of time and load.
Ultrasonic flaw detection is a method for evaluating cleanliness that has high measurement accuracy and can be performed in a short time, as opposed to the problems in conventional cleanliness evaluation methods such as the JIS method, ASTM method, and extreme value statistical method. Is used to evaluate the cleanliness of steel. For example, in Patent Document 1, as a method for evaluating the cleanliness of a steel material by an ultrasonic flaw detection method, ultrasonic waves having a frequency of 25 MHz to 100 MHz are sent to the steel material, and the diameter included in the surface layer portion from the surface of the steel material to a predetermined depth. It is disclosed to measure the number of inclusions of 20 μm or larger.
Prior art literature
Patent documents
[0006]
Patent Document 1: Japanese Unexamined Patent Publication No. 2012-177684
Outline of the invention
Problems to be solved by the invention
[0007]
By the way, in the case of the method described in Patent Document 1, regarding the radial position (diametrical position) of the steel material, when the center of the steel material is 0% and the surface is 100%, a flaw is detected at a position of 50% or more. There is. However, if the radial position for flaw detection is 50% or more of the above, depending on the diameter and material of the steel material, the ultrasonic transmission amount at a position near the surface and the ultrasonic transmission amount at a position close to 50% The difference is large, and the minimum size of inclusions that can be detected becomes large at a position close to 50%, which may reduce the reliability of cleanliness.
[0008]
Therefore, the present invention has been made by paying attention to the above-mentioned problems, and in the method of evaluating the cleanliness of a steel material by an ultrasonic flaw detection method, highly reliable data can be quickly obtained, and the cleanliness of the steel material can be obtained quickly. The purpose is to provide an evaluation method.
Means to solve problems
[0009]
According to one aspect of the present invention, ultrasonic flaw detection is performed so as to detect at least a part of the steel material in a range of 90% or more and 100% or less at a radial position where the center of the steel material is 0% and the surface is 100%. A method for evaluating the cleanliness of a steel material is provided, which evaluates the cleanliness based on the size and number of inclusions in the steel material obtained by the ultrasonic flaw detection.
Effect of the invention
[0010]
According to one aspect of the present invention, it is possible to provide a method for evaluating the cleanliness of a steel material, which can quickly acquire highly reliable data in the method for evaluating the cleanliness of a steel material by an ultrasonic flaw detection method.
A brief description of the drawing
[0011]
FIG. 1 is a schematic diagram showing a configuration of an ultrasonic flaw detection inspection device according to an embodiment of the present invention.
FIG. 2 is a graph showing the relationship between the radial position and the cleanliness index in Example 1.
FIG. 3 is a graph showing the ratio of the number of inclusions to each evaluation volume in Example 2.
Embodiment for carrying out the invention
[0012]
The following detailed description illustrates many specific details by exemplifying embodiments of the invention to provide a complete understanding of the invention. However, it is clear that one or more embodiments can be implemented without the description of such particular details. Also, the drawings are schematic representations of well-known structures and equipment for the sake of brevity.
[0013]

FIG. 1 shows a schematic configuration diagram of an ultrasonic flaw detection inspection device 1 used in the method for evaluating the cleanliness of a steel material according to an embodiment of the present invention. The ultrasonic flaw detection inspection device 1 is a device for evaluating the cleanliness of a round bar 2 made of a steel material, and as shown in FIG. 1, a probe 11, a water tank 12, and three motors 13 to 15 are included. It includes a motor controller 16, a flaw detector 17, a calculation unit 18, and a chuck device 19. The steel material to which inclusions are evaluated is bearing steel in the present embodiment, but is particularly limited as long as it is a steel material in which defects occur due to non-metal inclusions (for example, high-cleanliness steel such as hardened steel). Not done. Examples of products suitable for the present invention include rolling bearings, ball screws, linear guides, traction drive transmissions, electric brakes, and the like.
[0014]
The probe 11 is a focal type ultrasonic probe, which transmits ultrasonic waves and detects the reflected echo to detect the round bar 2. Further, in the ultrasonic flaw detection method in the present embodiment, the vertical flaw detection method is used. That is, the probe 11 is provided directly above the center line of the round bar 2 in the water tank 12, and the transmission direction of the ultrasonic wave is set downward in the vertical direction.
The water tank 12 stores water, which is an ultrasonic transmission medium. The probe 11 is provided in the water in the water tank 12.
[0015]
The three motors 13 to 15 receive the control signal of the motor controller 16 and move the probe 11 in the directions parallel to the x-axis, the y-axis, and the z-axis, respectively. The x-axis, y-axis, and z-axis are axes that are orthogonal to each other, the x-axis direction and the y-axis direction are parallel to the horizontal direction, and the z-axis direction is parallel to the vertical direction. Further, the y-axis direction is a direction parallel to the longitudinal direction of the round bar 2.
[0016]
The operation of the motor controller 16 is controlled by input to the calculation unit 18, and the positions of the probe 11 and the round bar 2 are controlled by controlling the rotation direction, rotation speed, and rotation angle of the three motors 13 to 15. A device that controls relationships.
The flaw detector 17 is connected to the probe 11 and monitors the size of inclusions detected from the flaw detection frequency, the reflected echo and the intensity of the reflected echo of the probe 11, and the measurement results thereof are sent to the calculation unit 18. Remember.
[0017]
The arithmetic unit 18 is a computer system such as a personal computer having an arithmetic processing function, is configured to include a ROM, RAM, CPU, etc., and is described later by executing various dedicated programs stored in advance in the ROM or the like. Realize the function on the software. Further, the calculation unit 18 stores the measurement result calculated by the flaw detector 17.
The chuck device 19 is a tool for fixing the round bar 2 and fixes both ends of the round bar 2 in the longitudinal direction. Further, the chuck device 19 can rotate the round bar 2 around the center line by rotating under the driving force of a rotation driving device (not shown). The rotation of the chuck device 19 may be controlled by the motor controller 16.
[0018]
In the cleanliness evaluation method according to the present embodiment, the round bar 2 is rotated in a certain direction by using the chuck device 19, and the round bar 2 is ultrasonically detected by the probe 11. The round bar 2 may be in a rolled state, but is preferably one that has been heat-treated after rolling and the surface has been turned and polished. The cutting allowance on the surface of the round bar 2 by turning and polishing is not particularly limited, but may be 1 mm in thickness (2 mm in terms of diameter).
[0019]
In ultrasonic flaw detection, it is preferable that the frequency of the ultrasonic wave transmitted from the probe 11 is 30 MHz or more and 70 MHz or less. By setting the frequency of ultrasonic flaw detection in such a range, inclusions having a minimum dimension of about 30 μm can be detected. Further, when the frequency of the ultrasonic wave is increased, smaller inclusions can be detected, but at the same time, the attenuation of the ultrasonic wave becomes large, so that the measurement time per evaluation volume becomes long. Lowering the frequency is advantageous in terms of measurement time because the attenuation of the ultrasonic waves is small, but the minimum size of the detectable inclusions is large and the evaluation of cleanliness may be erroneous. That is, when only large inclusions can be detected, or when only large inclusions are targeted for measurement, the larger the inclusions, the smaller the number of inclusions per evaluation volume. Therefore, if the evaluation volume is not increased, large inclusions will be generated. Despite its existence, it is possible to miss inclusions. Although there is a trade-off with the evaluation volume, if the above frequency range is used, an appropriate cleanliness evaluation can be performed in an appropriate measurement time. More preferably, the frequency of the ultrasonic wave is 40 MHz or more and 60 MHz or less, and more preferably 50 MHz.
[0020]
The size of the inclusions may be an index indicating the size of the inclusions, and may be the diameter of the inclusions. Further, the size of the inclusions is not limited to the diameter of the inclusions, and may be another index such as √area. That is, in the steel material evaluation method according to the present embodiment, as will be described later, the cleanliness is evaluated based on the size of the inclusions, which is an index indicating the size of the inclusions, and the number of inclusions. Further, the minimum dimension of the inclusion is not limited to the minimum diameter of the inclusion, and the minimum value of another index such as √area may be used.
[0021]
Further, in the present embodiment, by performing ultrasonic flaw detection while rotating the round bar 2, the range of a specific depth from the surface of the round bar 2 is continuously measured in the circumferential direction. At this time, the range of a specific depth of the round bar 2 on which ultrasonic flaw detection is performed is set to 90% or more and 100% or less in the radial position. The radial position indicates the position of the round bar 2 in the radial direction when the center of the round bar 2 is 0% and the surface of the round bar 2 is 100% in a cross section orthogonal to the longitudinal direction of the round bar 2. .. In this range, ultrasonic flaw detection may be performed in the entire range, or ultrasonic flaw detection may be performed in a part of the range. That is, in the radial position, ultrasonic flaw detection is performed in at least a part of the range of 90% or more and 100% or less. When the radial position of the round bar 2 is in the range of 90% or more and 100% or less, the difference in cleanliness of the steel material becomes remarkable. Therefore, by detecting this range, it is possible to acquire highly reliable cleanliness data.
[0022]
Further, in ultrasonic flaw detection, the evaluation volume, which is the volume of ultrasonic flaw detection of the round bar 2, is set to 60,000 mm 3 or more, preferably 100,000 mm 3 or more. The evaluation volume is the volume of the region to be detected by the round bar 2 in the ultrasonic flaw detection performed continuously while rotating the round bar 2. When the evaluation volume is less than 60,000 mm 3, the cleanliness cannot be evaluated accurately because the number of non-metal inclusions, which is the cleanliness, varies widely. Therefore, the cleanliness can be evaluated accurately by setting the evaluation volume to 60,000 mm 3 or more, and the cleanliness can be evaluated with higher accuracy by setting the evaluation volume to 100,000 mm 3 or more. The upper limit of the evaluation volume is not particularly limited, but is preferably 200,000 mm 3. When the evaluation volume exceeds 200,000 mm 3, the time required for flaw detection becomes long, and there is no significant difference in the evaluation accuracy of cleanliness as compared with the case where the evaluation volume is 100,000 mm 3 or more and 200,000 mm 3 or less.
[0023]
Furthermore, super sound In wave flaw detection, the probe 11 sends the flaw detection result such as the intensity of the reflected echo to the flaw detector 17. The flaw detection result by the flaw detector 17 is recorded in the calculation unit 18, and the dimensions of the detected inclusions are calculated. That is, the calculation unit 18 records the dimensions and the number of inclusions included in the evaluation volume. By setting the frequency of the ultrasonic wave to 30 MHz or more and 70 MHz, the number and dimensions of inclusions having a minimum detected dimension of about 30 μm or more are recorded as a result.
[0024]
After the ultrasonic flaw detection is completed, the calculation unit 18 evaluates the cleanliness by calculating the cleanliness index, which is a cleanliness evaluation index, from the flaw detection results. Cleanliness should have a strong correlation with bearing life, but inclusion dimensions and number of inclusions are the main factors for cleanliness parameters that correlate with life. Therefore, the cleanliness index is an index calculated using the size and number of inclusions. The method for calculating the cleanliness index is not particularly limited, and may be appropriately set according to the application and the type of steel material. For example, the cleanliness index may be set so that the higher the cleanliness, the worse the cleanliness, and the larger the number of inclusions having a large size, the higher the cleanliness index. For example, as the cleanliness index, the square root √area of ​​the area of ​​inclusions used in the extreme value statistical method is calculated from the dimensions of the detected inclusions, and the size of the inclusions in which this √area is equal to or greater than a predetermined value. An index determined from the number and the number may be used.
[0025]

Although the present invention has been described above with reference to specific embodiments, it is not intended to limit the invention by these explanations. By reference to the description of the invention, one of ordinary skill in the art will appreciate the disclosed embodiments as well as other embodiments of the invention including various modifications. Therefore, it should be understood that the embodiments of the invention described in the claims also include embodiments including these variations described herein alone or in combination.
[0026]
For example, in the above embodiment, the steel material whose cleanliness is evaluated is the round bar 2, but the present invention is not limited to this example. The steel material may be a square steel bar or a plate material.
Further, in the above embodiment, as the ultrasonic flaw detection inspection device 1, the one having the configuration shown in FIG. 1 is used, but the present invention is not limited to such an example. The ultrasonic flaw detection inspection apparatus may have another configuration as long as the surface layer of the steel material can be ultrasonically flaw detected under the above conditions.
[0027]

(1) The method for evaluating the cleanliness of a steel material according to one aspect of the present invention is 90% or more and 100% of the steel material at a radial position where the center of the steel material (for example, a round bar 2) is 0% and the surface is 100%. Ultrasonic flaw detection is performed so as to detect at least a part of the following range, and the cleanliness is evaluated based on the size and number of inclusions in the steel material obtained by ultrasonic flaw detection.
According to the configuration of (1) above, highly reliable cleanliness data can be quickly acquired. As an example, ultrasonic flaw detection is performed by arranging a steel material and a probe 11 in an ultrasonic transmission medium and transmitting ultrasonic waves from the probe 11 to the steel material.
[0028]
(2) In the configuration of (1) above, the evaluation volume of the steel material to be flawed when performing ultrasonic flaw detection is 60,000 mm 3 or more.
(3) In the configuration of (2) above, the evaluation volume is 100,000 mm 3 or more.
According to the configurations (2) and (3) above, the cleanliness can be evaluated with higher accuracy.
(4) In any of the configurations (1) to (3) above, the frequency of the ultrasonic wave is set to 30 MHz or more and 70 MHz or less when performing ultrasonic flaw detection.
According to the configuration of (4) above, inclusions having a minimum dimension of about 30 μm can be detected.
(5) In any of the configurations (1) to (4) above, the steel material is a steel material used for rolling bearings, ball screws, linear guides, traction drive transmissions, or electric brakes.
Example 1
[0029]
Next, Example 1 performed by the present inventors will be described. In Example 1, the relationship between the cleanliness and the radial position was investigated by measuring the cleanliness at a plurality of radial positions of the samples of the five round bars 2 having different diameters and cleanliness. In the investigation of Example 1, the round bar 2 is ultrasonically flawed by the same method as in the above embodiment, and the focal length probe uses a probe having a frequency of 50 MHz, a vibrator diameter of 3 mm, and an underwater focal length of 12.5 mm. board. When ultrasonic flaw detection is performed, the surface of the round bar 2 to be flawed is gradually set to around 90%, around 70%, around 50%, and around 30% in the radial position with respect to the round bar 2 immediately after rolling. After grinding the round bar 2 and grinding each of them, ultrasonic flaw detection was performed in the above range. In this example, the √area was estimated from the flaw detection results such as the echo intensity from the inclusions, and the cleanliness index was calculated from the number and dimensions of the inclusions whose √area was 50 μm or more.
[0030]
FIG. 2 shows the relationship between the radial position of the round bar 2 and the cleanliness index as a result of Example 1. Table 1 shows the diameter of the rolled material and the flaw detection position in each sample. The flaw detection position indicates a radial position for flaw detection with respect to the round bar 2 immediately after rolling. Further, the cleanliness index is set so as to increase as the number of inclusions increases and increase as the size of the inclusions increases.
[0031]
As shown in FIG. 2, the cleanliness is poor (30% position) near the center of the steel material, better at the center of the radius (50% position), and worse at the surface portion of the steel material (90-100% position). Was confirmed. This indicates that the difference between the sample with poor cleanliness and the sample with good cleanliness is remarkable on the surface of the steel material, and it is difficult to make a difference at the center position of the radius (50% position). Therefore, the cleanliness of the steel material can be improved by evaluating the inclusions contained in the steel material in the range of 10% depth (range of 90 to 100% in FIG. 1) from the surface of the steel material in the radial position of the steel material. It was confirmed that it can be evaluated with reliability. Moreover, since the order of cleanliness does not change significantly inside the steel material, the measurement from the center to the 90% position can be omitted.
[0032]
[table 1]

Example 2
[0033]
Next, Example 2 performed by the present inventors will be described. In Example 2, the relationship between the evaluation volume and the measurement accuracy was investigated by measuring the number of inclusions per the same volume by changing the evaluation volume for the samples of the three round bars 2 having different diameters and cleanliness. .. In Example 2, the round bar 2 is ultrasonically flawed by the same method as in the above embodiment, and the number of inclusions having a √area of ​​50 μm or more calculated by the same method as in Example 1 with different evaluation volumes per fixed volume. Was measured multiple times. Then, the measurement accuracy was investigated by obtaining the variation in the number of inclusions in each evaluation volume.
[0034]
FIG. 3 shows the ratio of the number of inclusions in each evaluation volume as a result of Example 2. The inclusion number ratio shown on the vertical axis of FIG. 3 is the number of each evaluation volume when the number of the measured inclusions per fixed volume is set to 1 when the number of each sample has the largest evaluation volume. It shows the ratio of. A plot with an inclusion number ratio of 1 or more shows the maximum value of the variation in the inclusion number ratio in the same evaluation volume, and a plot of 1 or less shows the minimum value of the variation in the evaluation volume. In addition, Table 2 shows the diameter of the rolled material and the evaluation volume (values ​​of the evaluation volume on the horizontal axis in FIG. 3) in each sample.
[0035]
[Table 2]

[0036]
When the evaluation volume was small, the ratio of the number of detected inclusions varied, but it was confirmed that the ratio of the number of inclusions became stable as the evaluation volume increased. In particular, it was confirmed that the variation was remarkably small in the region where the evaluation volume was 60,000 mm 3 or more, and was almost constant in the region where the evaluation volume was 100,000 mm 3 or more. From this, it was confirmed that the cleanliness can be evaluated accurately and quickly by setting the evaluation volume to 60,000 mm 3 or more, preferably 100,000 mm 3 or more as in the above embodiment.
Code description
[0037]
1 Ultrasonic flaw detection inspection device
11 probe
12 aquarium
13 to 15 motors
16 motor controller
17 flaw detector
18 Calculation unit
19 Chuck device
2 Round bar
The scope of the claims
[Claim 1]
Ultrasonic flaw detection was performed so as to detect at least a part of the steel material in the range of 90% or more and 100% or less at the radial position where the center of the steel material is 0% and the surface is 100%.
A method for evaluating the cleanliness of a steel material, which evaluates the cleanliness based on the size and number of inclusions in the steel material obtained by the ultrasonic flaw detection.
[Claim 2]
The cleanliness evaluation method for a steel material according to claim 1, wherein the evaluation volume of the steel material to be detected is 60,000 mm 3 or more when the ultrasonic flaw detection is performed.
[Claim 3]
The cleanliness evaluation method for steel materials according to claim 2, wherein the evaluation volume is 100,000 mm 3 or more.
[Claim 4]
The cleanliness evaluation method for steel materials according to any one of claims 1 to 3, wherein the frequency of the ultrasonic waves is 30 MHz or more and 70 MHz or less when the ultrasonic flaw detection is performed.
[Claim 5]
The cleanliness evaluation method for a steel material according to any one of claims 1 to 4, wherein the steel material is a steel material used for rolling bearings, ball screws, linear guides, traction drive transmissions, or electric brakes.