Quantitative evaluation method for size of microscopic defect in steel

Abstract

The invention discloses a quantitative evaluation method for the size of a microscopic defect in a steel material, which utilizes an ultrasonic mechanical scanning device to detect the microscopic defect in a certain depth range below the surface of a steel plate, and comprises the following steps: 1) adopting three same-frequency and zoom sensor groups to be matched with the ultrasonic mechanical scanning device to scan to obtain a microscopic defect imaging result image group; 2) measuring a position point of a signal exceeding a threshold value in each scanning image; 3) extracting the ultrasonic signals of all the position points exceeding the threshold value signal, and intercepting the time domain signal length of the same detection depth; 4) comparing whether the super-threshold signal position points of the same scanning position point in each scanning image are overlapped or not, and grouping all the super-threshold signal position points; and 5) comparing the threshold signal position points of the same scanning position point one by one to form a quantitative evaluation basis. The invention aims to solve the problems of low efficiency, inaccuracy, incompleteness and the like in the prior art.

Description

Technical Field

[0001] The invention relates to a quantitative evaluation and detection technology for microscopic defects inside steel, and more specifically, to a method for quantitatively evaluating the size of microscopic defects inside steel. Background Art

[0002] As the iron and steel metallurgical industry places increasingly higher demands on the cleanliness of molten steel for steelmaking, microscopic defect control technology has become very important. Qualified inspection of steel microscopic defects by steel companies is an important part of ensuring steel quality. However, due to the small size of microscopic defects, especially larger microscopic defect particles, which are randomly distributed inside the steel, they have a great impact on the performance of the steel and the quality and safety of the product.

[0003] At present, the technologies for detecting microscopic defects in steel include optical quantitative metallographic microscope analysis, large sample electrolysis method and ASIN fully automatic non-metallic inclusion analysis system in steel. Among them, quantitative metallographic microscope is a traditional optical quantitative metallographic analysis and inspection method used to analyze inclusion defects. The equipment analysis means are accurate. Advanced quantitative metallographic devices have combined metallographic microscope with image analyzer, which has the advantages of fast, convenient and accurate. However, the equipment is relatively expensive, the analysis results of quantitative metallographic are also greatly affected by human factors, and it takes a lot of time to prepare metallographic samples; there are also differences in the results between different operators, and the contrast between the whole batch of samples of the material becomes worse; the inspection time is also long, and the workload for the operator is very large, so the cost of quantitative metallographic analysis of internal inclusions in the material is very high. It is estimated that it takes one year to detect a sample with a volume of 200mm×200mm×8mm. The large sample electrolysis method was first invented by the Germans. Later, with the development of continuous casting, the cleanliness requirements of steel became higher and higher, and this method was developed and applied. Electrolysis is an important method for separating inclusions from steel. Small samples (200g) are often electrolyzed in sulfate solution to obtain inclusions and anode mud. Carbides are dissolved with acid, and then chemical methods are used to analyze the inclusion components such as silicon dioxide, calcium oxide, aluminum oxide, and manganese dioxide. This method is mainly used to analyze large inclusions larger than 50μm in steel. It can achieve the classification of inclusion sizes (about 50μm, 50-100μm, >100μm), and can analyze the composition of inclusions. The analysis process includes electrolysis, elutriation, reduction, and separation. The separated inclusions are subjected to particle size classification, morphology photography, and quantitative composition analysis by electron probe. This method uses physical methods to separate inclusions. The carbides are washed out by elutriation, while the inclusions and iron compounds are protected, and the inclusions are separated by reduction and magnetic separation. In order to capture more large inclusions, the sample size needs to be increased. For samples weighing 3-5kg, the electrolysis time is 7-15 days. Its disadvantage is that the electrolysis time is very long (days), and usually only about 2kg of matrix material can be analyzed. It is not representative, environmentally friendly, and very expensive. The ASIN fully automatic non-metallic inclusion analysis system in steel is a comprehensive analysis system newly launched by Zeiss that integrates an application-oriented scanning electron microscope, automatic analysis of a high-speed energy spectrum detector, and supporting fully automatic inclusion analysis software. The system integrates a large sample chamber with multiple interfaces and a complete electronic optical system, which can observe the surface morphology of various metal materials and automatically realize the comprehensive research and analysis of inclusions. It can accurately detect inclusions from submicron to below 1μm, and phase identify composite inclusions. Compared with micro-ultrasonic quantification, it still has the disadvantages of only detecting the sample surface, small samples, time-consuming, and expensive.

[0004] There is also the use of ultrasonic mechanical imaging methods to analyze microscopic defects in steel, especially to prevent the hazards of large microscopic defects, and relevant standards have been formed for high-quality products. Although ultrasonic mechanical imaging is used to detect microscopic defects inside steel, there are still many factors that affect the test results, and there are differences in judgment between different operators.

[0005] Although there are technical means to detect and analyze microscopic defects in recent years, they only have advantages in certain analytical aspects, and there is a general problem of low detection and analysis efficiency. At present, there is no detection technology that can quickly detect and quantitatively evaluate microscopic defects in steel. The current methods for steel companies to test whether microscopic defects in steel are qualified still have the embarrassing situation of lack of means and cannot adapt to the development of steel metallurgy. Summary of the invention

[0006] In view of the defects that the methods for detecting microscopic defects in the prior art are still very imperfect, the purpose of the present invention is to provide a method for quantitatively evaluating the size of microscopic defects inside steel materials to solve the existing problems of low efficiency, inaccuracy, incompleteness, etc.

[0007] To achieve the above object, the present invention adopts the following technical solution:

[0008] A method for quantitatively evaluating the size of microscopic defects inside steel is provided, which uses an ultrasonic mechanical scanning device to detect microscopic defects within a certain depth range below the surface of a steel plate, and comprises the following steps:

[0009] 1) Using three sensor groups with the same frequency and variable focus to cooperate with the ultrasonic mechanical scanning device to scan and obtain a group of microscopic defect imaging result images;

[0010] 2) measuring the super-threshold signal position points in each scanning image;

[0011] 3) Extract the ultrasonic signals of all super-threshold signal positions and intercept the time domain signal length of the same detection depth;

[0012] 4) comparing whether the super-threshold signal position points of the same scanning position points in each scanning image overlap, and grouping all the super-threshold signal position points;

[0013] 5) Compare the super-threshold signal positions of the same scanning position one by one to form a quantitative evaluation basis.

[0014] Preferably, in step 1), the frequency of the three sensor groups is 25 MHz to 50 MHz;

[0015] The focal lengths of the three sensor groups are respectively long focal length, medium focal length and short focal length.

[0016] Preferably, in step 2), the threshold value in each scan image is determined by anatomical verification.

[0017] Preferably, in step 4), all super-threshold signal position points are grouped according to the following rules:

[0018] A) For a certain same scanning position point, the detection results of the short-focus sensor group show obvious reflection signal echoes, but do not exceed the threshold, while the detection results of the long-focus sensor group and the medium-focus sensor group have no obvious echoes;

[0019] B) For a certain same scanning position point, the detection result of the short-focus sensor group exceeds the threshold, while the detection results of the long-focus sensor group and the medium-focus sensor group do not exceed the threshold;

[0020] C) For a certain same scanning position point, the detection results of the short-focus sensor group and the medium-focus sensor group both exceed the threshold, while the detection result of the long-focus sensor group does not exceed the threshold;

[0021] D) In ​​the scanning image of the sensor group at the medium focus, there are adjacent over-threshold signal position points, and at these position points, the detection results of the sensor group at the long focus do not exceed the threshold value;

[0022] E) In the scanning image of the long-focus sensor group, there is a position point where the signal exceeds the threshold value, and at this position point, the detection results of the short-focus sensor group and the medium-focus sensor group both exceed the threshold value.

[0023] Preferably, in step 5), when comparing the same scanning position points one by one, the following conditions must be met:

[0024] The detection result of the short-focus sensor group exceeds the threshold value;

[0025] The detection results of the short-focus sensor group, the medium-focus sensor group, and the long-focus sensor group all exceed the threshold value;

[0026] When there are adjacent over-threshold signal position points in the scanned images of the short-focus sensor group and the medium-focus sensor group, it is determined whether the detection result of the long-focus sensor group exceeds the threshold.

[0027] Preferably, the surface of the steel plate is polished;

[0028] The surface roughness of the steel plate after polishing is at micron level.

[0029] The invention provides a method for quantitatively evaluating the size of microscopic defects inside steel. Through the detection step of the same frequency zoom sensitivity difference method, a certain fixed frequency ultrasonic wave is selected, and three focal lengths of short, medium and long at the frequency are selected. Under three technical conditions that can detect microscopic defects and have slight sensitivity differences, the purpose of rapid and graded quantitative detection of microscopic defects measured in steel samples is achieved, and the number and size of microscopic defects of the inspected steel plate are intuitively characterized in the form of microscopic defect distribution images of the third-order sensitivity channel (corresponding to the three different focal lengths). The method is very beneficial to workers in steel smelting, analysis and research in the rapid and large-scale analysis of different cleanliness levels of steel, as well as material analysis in failure accidents. It also provides a highly sensitive and quantitative analysis detection technology for the quality determination of high-quality steel. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic flow chart of the method for quantitatively evaluating the size of microscopic defects inside steel of the present invention;

[0031] Figure 2 It is a distribution diagram of microscopic defects above the minimum size level (level V) in a quantitative steel plate sample by the same frequency zoom sensitivity difference method in an embodiment of the method for quantitatively evaluating the size of microscopic defects inside a steel material of the present invention;

[0032] Figure 3 It is a distribution diagram of microscopic defects of smaller size level (level IV) or above in a steel plate sample using the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects inside a steel material of the present invention;

[0033] Figure 4 It is a distribution diagram of microscopic defects of medium size or above (grade III) in a quantitative steel plate sample by the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects in steel materials of the present invention;

[0034] Figure 5 It is a distribution diagram of microscopic defects of larger size level (level II) or above in a steel plate sample using the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects inside a steel material of the present invention;

[0035] Figure 6 It is a distribution diagram of microscopic defects above the large size level (level I) in a quantitative steel plate sample by the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects inside steel materials of the present invention;

[0036] Figure 7Schematic diagram of the signal intensity characteristics of the minimum size level (level V) microscopic defects in a quantitative steel plate sample by the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects in steel materials of the present invention, (a) indicates that the high-order sensitivity channel has a strong reflection signal, (b) indicates that the middle-order sensitivity channel has a weak reflection signal, and (c) indicates that the low-order sensitivity channel has no obvious reflection signal;

[0037] Figure 8 Schematic diagram of the signal intensity characteristics of the smaller size level (level IV) micro defects in the quantitative steel plate sample by the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of micro defects in the steel material of the present invention, (a) is a high-order sensitivity channel with a strong reflection signal, (b) is a medium-order sensitivity channel with a relatively strong reflection signal, and (c) is a low-order sensitivity channel without an obvious reflection signal;

[0038] Fig. 9 Schematic diagram of the signal intensity characteristics of medium-sized microscopic defects (grade III) in a steel plate sample using the same-frequency zoom sensitivity difference method in an embodiment of the method for quantitatively evaluating the size of microscopic defects in steel materials of the present invention, (a) indicates that a high-order sensitivity channel has a strong reflection signal, (b) indicates that a medium-order sensitivity channel has a strong reflection signal, and (c) indicates that a low-order sensitivity channel has no obvious reflection signal;

[0039] Fig.10 Schematic diagram of the signal intensity characteristics of the relatively large-size (grade II) microscopic defects in the quantitative steel plate sample by the same-frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects in the steel material of the present invention, (a) is a high-order sensitivity channel with a strong reflection signal, (b) is a medium-order sensitivity channel with a strong reflection signal, and (c) is a low-order sensitivity channel with a weak reflection signal;

[0040] Fig.11 Schematic diagram of the anatomical morphology of the microscopic defects of the minimum size level (level V) in the steel plate sample quantitatively measured by the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects in the steel material of the present invention, (a) is a microscopic defect (level V) within 50 mm, and (b) is a microscopic defect (level V) within 50 mm;

[0041] Fig.12 Schematic diagram of the anatomical morphology of microscopic defects of smaller size level (level IV) in a steel plate sample quantitatively measured by the same frequency zoom sensitivity difference method in the embodiment of the method for quantitatively evaluating the size of microscopic defects in steel materials of the present invention, (a) is a microscopic defect within 100 mm (level IV), (b) is a microscopic defect within 100 mm (level IV);

[0042] Fig.13Schematic diagram of the anatomical morphology of medium-sized microscopic defects (grade III) in a steel plate sample quantitatively measured by the same-frequency zoom sensitivity difference method in an embodiment of the method for quantitatively evaluating the size of microscopic defects in steel materials of the present invention, (a) is a microscopic defect (grade III) within 200 mm, and (b) is a microscopic defect (grade III) within 200 mm;

[0043] Fig.14 It is a schematic diagram of the anatomical morphology of relatively large-size grade (grade II) and large-size grade (grade I) microscopic defects in a steel plate sample quantitatively measured by the same-frequency zoom sensitivity difference method in an embodiment of the method for quantitatively evaluating the size of microscopic defects inside steel materials of the present invention, (a) is a microscopic defect within 500 mm (grade II), and (b) is a microscopic defect above 500 mm (grade I). DETAILED DESCRIPTION

[0044] In order to better understand the above technical solution of the present invention, the technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0045] Combination Figure 1 As shown, the present invention provides a method for quantitatively evaluating the size of microscopic defects inside steel, which uses an ultrasonic mechanical scanning device to detect microscopic defects within a certain depth range below the surface of the steel plate, including the following steps:

[0046] 1) Use three sensor groups with the same frequency and zoom to cooperate with the ultrasonic mechanical scanning device to scan and obtain the microscopic defect imaging result image group;

[0047] 2) Determine the location points of the super-threshold signals in each scan at three sensitivities (the thresholds in each scan are determined by anatomical verification), and then compare and determine whether the points in the scan coincide;

[0048] 3) Extract the ultrasonic signals of all super-threshold signal positions and intercept the time domain signal length of the same detection depth;

[0049] 4) comparing whether the super-threshold signal position points of the same scanning position points in each scanning image overlap, and grouping all the super-threshold signal position points;

[0050] 5) Compare the super-threshold signal positions of the same scanning position one by one to form a quantitative evaluation basis.

[0051] Based on the above actual results and the quantitative evaluation model of microscopic defects, the number, size and distribution of microscopic defects at each size level are obtained.

[0052] First, the extracted steel raw materials to be analyzed are processed for appearance. On the one hand, the raw materials are processed into a thickness suitable for detection. On the other hand, the surfaces of the entire batch of samples are polished in the same way. The surface polishing process can be carried out on a specially configured processing sample grinder. The surface roughness is controlled at the micron level after processing. The purpose of processing is to ensure that the surface roughness of the sample will not have different effects on the test results or cause false test results. In doing so, the consistency of the test conditions is also guaranteed to avoid affecting the comparison effect of using short, medium and long focal lengths (also three sensitivities) sensor groups to perform the same test task, which will affect the quantitative analysis.

[0053] In step 1), the frequencies of the three sensor groups are the same frequency between 25MHz and 50MHz, and the focal lengths of the three sensor groups are long focus, medium focus and short focus (i.e., low sensitivity, medium sensitivity and high sensitivity), respectively, forming a combination of three-channel sensor groups. After scanning the processed samples, three defect distribution maps of microscopic defects with different sensitivity levels are obtained. In the scanning test, the step length and starting position of the mechanical scanning are guaranteed to be exactly the same. From the relationship between the size and volume of microscopic defects, the number of large-sized microscopic defects is small, and correspondingly, a larger volume needs to be detected to be found.

[0054] Executing step 2) will inevitably result in a small number of microscopic defects that can be measured by a low-sensitivity scan image, which is determined by its low sensitivity. When ultrasonic waves propagate in steel, for a specific material, the propagation speed of the ultrasonic waves in it is constant. If an ultrasonic frequency in a certain high-frequency band is used for detection, its wavelength is also the corresponding specific wavelength. For a specific microscopic defect in steel, the energy after reflection is different for three different incident energies. When the propagation speed and frequency of ultrasonic waves in steel are constant, the wavelength is the same, and under the same gain, the higher the energy of the reflected signal, the smaller the defect target of the microscopic defect that can be found.

[0055] The time range for extracting the detection signal determined in step 3) corresponds to a certain depth range below the surface of the steel being inspected and at the focus of the short focal length sensor group. Under the same gain conditions, the result of the short focal length sensor group has the highest sensitivity, and the sensitivity of the sensor group with the longest focal length within this depth range is the lowest.

[0056] Therefore, when using the detection results of short, medium and long focal lengths (also high, medium and low sensitivities), the defect target sizes of the microscopic defects that can be detected are different. At the same threshold height in the time domain signal, the microscopic defects that can be detected by the low-order sensitivity channel are relatively large in size, while in the scanning image obtained by detection using the high-order sensitivity channel, smaller microscopic defects that cannot be measured by the low and medium-order sensitivity channels can be detected, so the number is the largest and the size can be the smallest. This is determined by the relatively highest sensitivity corresponding to the short focal length at the focus.

[0057] The ultrasonic signals of all mechanical positions of super-threshold signals are extracted, and the signal segments of the same monitoring depth are intercepted. The purpose of this is to compare whether two or more connected super-threshold micro-defect signals are at the same depth position in the sample when a large micro-defect appears. If the depth positions of two connected super-threshold micro-defect signals are different, it means that the signals of these two positions should be generated by two different relatively large micro-defect reflections; if the depth positions of two connected super-threshold micro-defect signals are the same, it means that the super-threshold signals of these two positions are generated by the same large micro-defect reflection.

[0058] In step 4), all super-threshold signal locations are grouped according to the following rules:

[0059] A) For a certain same scanning position point, the detection results of the short-focus sensor group show obvious reflection signal echo, but do not exceed the threshold, while the detection results of the long-focus sensor group and the medium-focus sensor group have no obvious echo;

[0060] B) For a certain same scanning position point, the detection result of the short-focus sensor group exceeds the threshold, while the detection results of the long-focus sensor group and the medium-focus sensor group do not exceed the threshold;

[0061] C) For a certain same scanning position point, the detection results of the short-focus sensor group and the medium-focus sensor group both exceed the threshold, while the detection result of the long-focus sensor group does not exceed the threshold;

[0062] D) In ​​the scanning diagram of the mid-focus sensor group, there are adjacent over-threshold signal position points, and at these position points, the detection results of the telephoto sensor group do not exceed the threshold value;

[0063] E) In the scanning image of the long-focus sensor group, there is a position point where the signal exceeds the threshold value, and at this position point, the detection results of the short-focus sensor group and the medium-focus sensor group both exceed the threshold value.

[0064] In step 5), when comparing the same scanning position points one by one, the following conditions must be met:

[0065] The detection result of the short-focus sensor group exceeds the threshold;

[0066] The detection results of the short-focus sensor group, the medium-focus sensor group, and the long-focus sensor group all exceeded the threshold;

[0067] When there are adjacent over-threshold signal position points in the scanned images of the short-focus sensor group and the medium-focus sensor group, it is determined whether the detection result of the long-focus sensor group exceeds the threshold.

[0068] By comparing the detection results and anatomically calibrating the corresponding positions, the size level of microscopic defects in various situations can be determined one by one. In subsequent tests, the comprehensive characteristics of the signals of each order of sensitivity channels of the same frequency sensitivity difference method can be used to compare the over-threshold conditions of the results of each order of sensitivity channels at the same detection point, as well as whether the over-threshold points are connected, to form a quantitative analysis criterion.

[0069] The present invention selects a certain fixed frequency ultrasonic wave and three focal lengths of short, medium and long at the frequency through the detection steps of the same frequency zoom sensitivity difference method, and realizes the purpose of rapid classification and quantitative detection of microscopic defects detected in steel samples under three technical conditions that can detect microscopic defects and have slight sensitivity differences, and intuitively characterizes the number and size of microscopic defects of the inspected steel plate in the form of microscopic defect distribution images of three-order sensitivity channels (corresponding to the three different focal lengths). It helps material analysis workers to analyze different cleanliness conditions of steel more quickly and in batches, and provides a highly sensitive determination technical means that can be quantitatively analyzed for the quality determination of high-quality steel.

[0070] The microscopic defects within a certain depth range under the surface of the steel plate are detected by three-channel mechanical scanning detection. The main features of this detection work are: 1) The three channels all use ultrasonic sensors with a certain frequency distributed in the ultrasonic high frequency band range (25MHz~50MHz) and the acoustic field characteristics of ultrasonic pulses are exactly the same except for the focal length. The focal lengths of the three detection channels are different, which are divided into long, medium and short types, so as to form three different acoustic energy densities within a certain depth range at the focus of the short focal length sensor under the surface of the inspected material; 2) The physical positions of the grids for the three channels to perform mechanical scanning detection are completely overlapped. The scanning tasks can be performed in the same batch and sequentially, or in batches, but the measured scanning data results must be saved for subsequent comparison to obtain quantitative evaluation results.

[0071] According to the above detection method, the ultrasonic reflection signals of micro defects in the steel plate with three different focal lengths can be obtained under the same detection conditions including the high-frequency ultrasonic segment. In the detection, the step length and starting position of the detection mechanical scanning must be exactly the same. The purpose of this is to make the ultrasonic signals of different sensitivity levels measured at the same position point using the three focal lengths of long, medium and short can be compared with each other.

[0072] Example

[0073] This embodiment uses a quantitative evaluation method for the size of microscopic defects inside steel to conduct quantitative detection and analysis on a piece of steel processed according to the detection requirements.

[0074] In the experiment of quantitative determination of microscopic defects in steel by the same frequency zoom sensitivity difference method, the ultrasonic mechanical scanning equipment used includes a mechanical scanning system, a signal transmitting / receiving processing part, a signal digitization system, an ultrasonic probe, and a detection operation procedure. The low-pass and high-pass filters provided by the system are used, and the system amplitude quantization accuracy is 12 bits; the maximum data acquisition speed is 200MHz. A short focal length focused sound field is used, and three sensor groups with the same frequency of 25MHz are used. The detection results under three different sensitivity conditions of high (focal length 25mm), medium (focal length 50mm), and low (focal length 80mm) are obtained, and the corresponding thresholds are set to 90%, 70%, and 50%. The imaging detection scanning step is 1mm×1mm; the pulse voltage is 350V; the pulse width is 25MHz; and the emission energy is 470uJ.

[0075] According to the quantitative evaluation method steps of the internal microscopic defects of steel in this embodiment, the experimental results show that Figures 3 to 7 The distribution diagram of microscopic defects at each size level in Figure 2 The distribution diagram of microscopic defects above the minimum size level is shown. This level is also the distribution diagram of all microscopic defects that can be detected by the high (focal length 25mm) order sensitivity channel. After dissection, it was determined that the sensitivity level is within the microscopic defect size of 50mm (in this embodiment, it can be temporarily determined as level V).

[0076] like Figure 3 The distribution diagram of microscopic defects above the smaller size level shown is also the distribution diagram of all super-threshold microscopic defects that can be detected by the high (focal length 25mm) order sensitivity channel, and the distribution diagram of all microscopic defects below the threshold that can be detected by the medium (focal length 50mm) order sensitivity channel. After dissection, it was determined that the microscopic defect size obtained at this sensitivity level is a microscopic defect in the range of 50mm-100mm (in this embodiment, it can be temporarily determined as level IV). In this embodiment, the number of microscopic defects of level V and level IV is relatively large.

[0077] like Figure 4The distribution diagram of microscopic defects above the medium size level is shown. This level is also the distribution diagram of all super-threshold microscopic defects that can be detected by both high- and medium-order sensitivity channels, and the distribution diagram of all microscopic defects below the threshold that can be detected by the low (focal length 80mm) order sensitivity channel. After dissection, it was determined that the microscopic defect size obtained at this sensitivity level is a microscopic defect in the range of 100mm-200mm (in this embodiment, it can be temporarily determined as level III). In this embodiment, there are 7.

[0078] like Figure 5 The distribution diagram of microscopic defects above the larger size level shown is also the distribution diagram of all connected super-threshold microscopic defects that can be detected by both the medium and high-order sensitivity channels, and the distribution diagram of all microscopic defects below the threshold that can be detected by the low-order sensitivity channel. After dissection, it was determined that the microscopic defect size obtained at this sensitivity level is a microscopic defect in the range of 200mm-500mm (which can be temporarily defined as level II in this patent). In this embodiment, there is 1.

[0079] like Figure 6 The distribution diagram of microscopic defects above the large size level shown is also the distribution diagram of all connected super-threshold microscopic defects that can be detected by both the medium and high-order sensitivity channels, and the distribution diagram of all microscopic defects above the threshold that can be detected by both the low-order sensitivity channels. After dissection, it was determined that the size of the microscopic defects obtained at this sensitivity level are all microscopic defects in the range of more than 500mm (in this embodiment, it can be temporarily determined as level I). In this embodiment, there is none.

[0080] exist Figures 3 to 7 There are four detection points marked with A, B, C, and D, which are the positions where the sensitivity exceeds the threshold under a certain sensitivity channel. Figures 7 to 10 The signals reflected by microscopic defects at corresponding positions and three low, medium and high sensitivity channels are given in FIG. A method for grouping is performed based on whether the super-threshold points at the same position in the scanning diagram of each sensitivity channel overlap.

[0081] like Figure 7 The detection results of the high-order sensitivity channel show a reflection signal echo below an obvious threshold, while the detection results of the medium- and low-order sensitivity channels show no obvious echo.

[0082] like Figure 8 The detection result of the high-order sensitivity channel exceeds the threshold, while the detection results of the medium and low-order sensitivity channels do not exceed the threshold, that is, Figures 2 to 3 There are two points marked as A and B in the figure.

[0083] like Fig. 9The detection results of the high-order and medium-order sensitivity channels both exceed the threshold, while the detection results of the low-order sensitivity channel do not exceed the threshold, that is, Figures 2 to 6 The point marked as C in the figure.

[0084] like Fig.10 In the scanning diagrams of the high- and medium-order sensitivity channels, there are adjacent over-threshold position points, and at these points, the low-order sensitivity channel results exceed the threshold.

[0085] After the above tests, the results of anatomical verification were performed on the locations where a certain sensitivity level exceeded the threshold, such as Figures 11 to 14 As shown in the figure, the calibration method of the method of quantitatively determining microscopic defects in steel using the same frequency zoom sensitivity difference method also adopts the method of combining detection with dissection. Fig.11 Two microscopic defects within 50 mm are given (temporarily classified as Grade V in this patent). Fig.12 Two microscopic defects with a range of 50mm-100mm are given (temporarily defined as level IV in this patent). Fig.13 Two microscopic defects in the range of 100mm-200mm are given (temporarily defined as Level III in this patent). Fig.14 (a) is a microscopic defect in the range of 200mm-500mm (temporarily defined as Level II in this patent), that is, Figures 2 to 6 The microscopic defect at the point marked as C in the figure. Fig.14 (b) Microscopic defects in the range of 500 mm or more (temporarily defined as Level I in this patent), at this detection point, the 15 MHz frequency detection result exceeds the threshold.

[0086] Those skilled in the art should recognize that the above embodiments are only used to illustrate the present invention, and are not intended to limit the present invention. As long as they are within the spirit of the present invention, any changes or modifications to the above embodiments will fall within the scope of the claims of the present invention.

Claims

1. A method for quantitatively evaluating the size of microscopic defects inside steel, using an ultrasonic mechanical scanning device to detect microscopic defects within a certain depth range below the surface of a steel plate, characterized in that: The following steps are involved: 1) Using three sensor groups with the same frequency and variable focus to cooperate with the ultrasonic mechanical scanning device to scan and obtain a group of microscopic defect imaging result images; 2) measuring the super-threshold signal position points in each scanning image; 3) Extract the ultrasonic signals of all super-threshold signal positions and intercept the time domain signal length of the same detection depth; 4) comparing whether the super-threshold signal position points of the same scanning position points in each scanning image overlap, and grouping all the super-threshold signal position points; 5) Compare the super-threshold signal positions of the same scanning position one by one to form a quantitative evaluation basis.

2. The method for quantitatively evaluating the size of microscopic defects inside steel according to claim 1, characterized in that: In the step 1), the frequencies of the three sensor groups are 25 MHz to 50 MHz; The focal lengths of the three sensor groups are respectively long focal length, medium focal length and short focal length.

3. The method for quantitatively evaluating the size of microscopic defects inside steel according to claim 1, characterized in that: In step 2), the threshold value in each scan image is determined by anatomical verification.

4. The method for quantitatively evaluating the size of microscopic defects inside steel according to claim 2, characterized in that: In step 4), all super-threshold signal position points are grouped according to the following rules: A) For a certain same scanning position point, the detection results of the short-focus sensor group show obvious reflection signal echoes, but do not exceed the threshold, while the detection results of the long-focus sensor group and the medium-focus sensor group have no obvious echoes; B) For a certain same scanning position point, the detection result of the short-focus sensor group exceeds the threshold, while the detection results of the long-focus sensor group and the medium-focus sensor group do not exceed the threshold; C) For a certain same scanning position point, the detection results of the short-focus sensor group and the medium-focus sensor group both exceed the threshold, while the detection result of the long-focus sensor group does not exceed the threshold; D) In ​​the scanning image of the sensor group at the medium focus, there are adjacent over-threshold signal position points, and at these position points, the detection results of the sensor group at the long focus do not exceed the threshold value; E) In the scanning image of the long-focus sensor group, there is a position point where the signal exceeds the threshold value, and at this position point, the detection results of the short-focus sensor group and the medium-focus sensor group both exceed the threshold value.

5. The method for quantitatively evaluating the size of microscopic defects inside steel according to claim 4, characterized in that: In step 5), when comparing the same scanning position points one by one, the following conditions must be met: The detection result of the short-focus sensor group exceeds the threshold value; The detection results of the short-focus sensor group, the medium-focus sensor group, and the long-focus sensor group all exceed the threshold value; When there are adjacent over-threshold signal position points in the scanned images of the short-focus sensor group and the medium-focus sensor group, it is determined whether the detection result of the long-focus sensor group exceeds the threshold.

6. The method for quantitatively evaluating the size of microscopic defects inside steel according to claim 1, characterized in that: The surface of the steel plate is subjected to a polishing process; The surface roughness of the steel plate after polishing is at micron level.

Images