A method and system for accurately identifying and detecting internal defects of mold steel

Abstract

The present invention relates to the field of mold steel detection technology, and specifically discloses a method and system for accurately identifying and detecting internal defects of mold steel, including: obtaining multiple probe path lines of the mold steel detection surface, wherein the mold steel detection surface includes an axial detection surface and a radial detection surface, and each of the probe path lines is used for mobile detection by an ultrasonic probe; obtaining echo signals of multiple detection points of each probe on each probe path line, and obtaining echo enrichment area information according to each detection point echo signal; obtaining two-dimensional defect graphic information and defect graphic depth information corresponding to each detection point echo signal according to the echo enrichment area information; generating a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to each detection point echo signal. The present invention can effectively reduce misjudgment and improve the reliability of detection by obtaining echo signals of multiple detection points of the probe on each probe path line and comprehensively analyzing these signals.

Description

Technical Field

[0001] The present invention relates to the technical field of die steel detection, and in particular to a method and system for accurately identifying and detecting internal defects of die steel. Background Art

[0002] Mold steel refers to special steel used to make molds. Molds are tools used to shape various materials (such as plastics, metals, glass, etc.) in industrial production and are widely used in many industries such as automobiles, aviation, home appliances, electronics, and medical treatment. The quality of mold steel directly affects the service life, processing accuracy, and production efficiency of the mold, so the requirements for mold steel are very high.

[0003] During the ultrasonic testing of existing mold steel, part of the ultrasonic sound beam is directly reflected back to the probe through the inner surface of the mold steel wall, while the other part is reflected by the defective surface and transmitted into the mold steel wall. After multiple reflections, it is received by the probe, which easily causes confusion of multiple reflected waves and leads to misjudgment of internal defects of the mold steel. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for accurately identifying and detecting internal defects of mold steel, so as to solve the technical problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for accurately identifying and detecting internal defects of mold steel, comprising:

[0007] Acquire multiple probe path lines of the mold steel detection surface, wherein the mold steel detection surface includes an axial detection surface and a radial detection surface, and each probe path line is used for mobile detection by an ultrasonic probe;

[0008] Acquire echo signals of multiple detection points of each probe on each probe path line, and acquire echo enrichment area information according to each of the detection point echo signals;

[0009] Acquire two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information;

[0010] Generate a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point, wherein the defect scanning image includes a two-dimensional defect axial image and a two-dimensional defect radial image;

[0011] Generate a three-dimensional image based on the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and obtain the defect shape information and defect position information based on the three-dimensional image;

[0012] Defect type information is acquired according to the two-dimensional defect axial image and the two-dimensional defect radial image, and defect state information of the mold steel is generated according to the defect type information, defect shape information and defect position information.

[0013] Preferably, the step of obtaining echo signals of multiple detection points of each probe on each probe path line, and obtaining echo enrichment area information according to each of the detection point echo signals, comprises:

[0014] Obtain all equally spaced detection points on each probe path line;

[0015] Obtaining an initial pulse wave of the probe at each of the detection points;

[0016] Acquire multiple detection point echo signals at each detection point based on the initial pulse wave, wherein each detection point echo signal includes an echo time and an echo amplitude;

[0017] Establishing a two-dimensional echo signal schematic diagram for each detection point according to a plurality of echo times and echo amplitudes;

[0018] Acquire the echo amplitude change value of each echo signal according to the echo signal schematic diagram;

[0019] Obtaining an amplitude threshold interval, and determining whether the echo amplitude change value of each of the echo signals is within the amplitude threshold interval;

[0020] If it is located, then all echo signals within the amplitude threshold interval are acquired, and the echo signals within the amplitude threshold interval are used as the first marked echo signals;

[0021] Acquire the echo time variation value of each echo signal according to the echo signal schematic diagram;

[0022] Obtaining the delay rate of each echo signal according to the echo time variation value;

[0023] Acquire a time delay threshold interval, and determine whether the delay rate of each of the echo signals is within the time delay threshold interval;

[0024] If it is, then all echo signals within the time delay threshold interval are acquired, and the echo signals within the time delay threshold interval are used as second marked echo signals;

[0025] Compare all first marker echo signals with all second marker echo signals, and use the signal that matches the first marker echo signal and the second marker echo signal as the third marker signal;

[0026] All third marker signals are acquired, and all third marker signals are used as echo enrichment region information.

[0027] Preferably, the step of acquiring two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information comprises:

[0028] Obtaining the number of all third marker signals in the echo enrichment region information, and using it as the number of enriched echoes;

[0029] Acquire the echo amplitude of each third marker signal in the echo enrichment area information, and use it as the enriched echo amplitude;

[0030] Acquire the echo time variation value of each third marker signal in the echo enrichment area information, and acquire the arrival distance variation value of the echo of each third marker signal according to the delay rate;

[0031] Map the arrival distance change value as the abscissa and the enriched echo amplitude as the ordinate to a two-dimensional coordinate system to generate data points;

[0032] Obtain all enriched echo quantities on each probe path line and map all data points, and link all data points to obtain two-dimensional defect graphic information;

[0033] Acquiring the echo velocity and echo time of all third marker signals in the echo enrichment area information;

[0034] Obtain defect depth information based on echo velocity and echo time;

[0035] The defect depth information of all third marking signals is acquired to obtain the defect pattern depth information.

[0036] Preferably, the step of generating a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point includes:

[0037] Acquire all probe path lines on the axial detection surface and use them as a first path line set;

[0038] Obtaining two-dimensional defect graphic information of all probe path lines in the first path line set, and using it as the first defect graphic;

[0039] All first defect images are spliced ​​and integrated to obtain a two-dimensional defect axial image;

[0040] Acquire all probe path lines on the radial detection surface and use them as a second path line set;

[0041] Obtaining two-dimensional defect graphic information of all probe path lines in the second path line set, and using it as the second defect graphic;

[0042] All second defect graphics are spliced ​​and integrated to obtain a two-dimensional defect radial image;

[0043] The two-dimensional defect axial image on the axial detection surface and the two-dimensional defect radial image on the radial detection surface are collected to obtain a two-dimensional defect scanning image.

[0044] Preferably, the step of generating a three-dimensional image according to the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and obtaining the defect shape information and the defect position information according to the three-dimensional image includes:

[0045] Get the preset three-dimensional coordinate system;

[0046] Acquire a plurality of first positioning points according to the two-dimensional defect axial image;

[0047] Acquire a first positioning depth of each first positioning point according to defect pattern depth information corresponding to the two-dimensional defect axial image;

[0048] Acquire multiple second positioning points according to the two-dimensional defect radial image,

[0049] Acquire a second positioning depth of each second positioning point according to defect pattern depth information corresponding to the two-dimensional defect radial image;

[0050] Mapping the corresponding first positioning point to a preset three-dimensional coordinate system according to the first positioning depth to obtain a first defect three-dimensional image;

[0051] Mapping the corresponding second positioning point to a preset three-dimensional coordinate system according to the second positioning depth, combining it with the first defect three-dimensional image, eliminating the positioning points where the first positioning point and the second positioning point overlap, and obtaining a three-dimensional image;

[0052] Acquire defect shape information from the three-dimensional image, wherein the defect shape information includes defect length, width, height information, shape information, and boundary information;

[0053] The defect position information is obtained from the three-dimensional image, where the defect position information is the specific coordinate position of the defect in the three-dimensional coordinate system.

[0054] Preferably, the step of acquiring defect type information according to the two-dimensional defect axial image and the two-dimensional defect radial image comprises:

[0055] Extracting a first defect feature from the two-dimensional defect axial image by edge detection, wherein the first defect feature includes defect axial length information, defect axial shape information, and defect axial boundary information;

[0056] Extracting a second defect feature from the two-dimensional defect radial image by edge detection, wherein the second defect feature includes defect radial length information, defect radial shape information, and defect radial boundary information;

[0057] The first defect feature and the second defect feature are compared with the preset feature to obtain defect type information.

[0058] The present invention also discloses a mold steel internal defect accurate identification and detection system, which is characterized by comprising:

[0059] A first acquisition module is used to acquire multiple probe path lines of a mold steel detection surface, wherein the mold steel detection surface includes an axial detection surface and a radial detection surface, and each of the probe path lines is used for mobile detection by an ultrasonic probe;

[0060] A second acquisition module is used to acquire echo signals of multiple detection points of each probe on each probe path line, and acquire echo enrichment area information according to the echo signal of each detection point;

[0061] A third acquisition module is used to acquire two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information;

[0062] A fourth acquisition module, used to generate a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point, wherein the defect scanning image includes a two-dimensional defect axial image and a two-dimensional defect radial image;

[0063] A fifth acquisition module, used to generate a three-dimensional image according to the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and to acquire defect shape information and defect position information according to the three-dimensional image;

[0064] The sixth acquisition module is used to acquire defect type information according to the two-dimensional defect axial image and the two-dimensional defect radial image, and generate defect status information of the mold steel according to the defect type information, defect shape information and defect position information.

[0065] Preferably, the second acquisition module includes:

[0066] A first acquisition unit, used for acquiring all equidistant detection points on each probe path line;

[0067] A second acquisition unit, used for acquiring an initial pulse wave of the probe at each of the detection points;

[0068] A third acquisition unit, configured to acquire a plurality of detection point echo signals at each of the detection points based on the initial pulse wave, wherein each of the detection point echo signals includes an echo time and an echo amplitude;

[0069] a fourth acquisition unit, configured to establish a two-dimensional echo signal schematic diagram for each of the detection points according to a plurality of echo times and echo amplitudes;

[0070] A fifth acquisition unit, used for acquiring an echo amplitude change value of each echo signal according to the echo signal schematic diagram;

[0071] a sixth acquisition unit, configured to acquire an amplitude threshold interval, and determine whether the echo amplitude change value of each of the echo signals is within the amplitude threshold interval;

[0072] If it is located, then all echo signals within the amplitude threshold interval are acquired, and the echo signals within the amplitude threshold interval are used as the first marked echo signals;

[0073] a seventh acquisition unit, configured to acquire an echo time variation value of each echo signal according to the echo signal schematic diagram;

[0074] an eighth acquisition unit, configured to acquire a delay rate of each echo signal according to the echo time variation value;

[0075] a ninth acquisition unit, configured to acquire a time delay threshold interval, and determine whether the delay rate of each of the echo signals is within the time delay threshold interval;

[0076] If it is, then all echo signals within the time delay threshold interval are acquired, and the echo signals within the time delay threshold interval are used as second marked echo signals;

[0077] a tenth acquisition unit, configured to compare all first marker echo signals with all second marker echo signals, and use the signals that match the first marker echo signals and the second marker echo signals as third marker signals;

[0078] The eleventh acquisition unit is used to acquire all third marker signals and use all third marker signals as echo enrichment area information.

[0079] Preferably, the third acquisition module includes:

[0080] a twelfth obtaining unit, configured to obtain the number of all third marker signals in the echo enrichment region information, and use the number as the enriched echo number;

[0081] a thirteenth obtaining unit, configured to obtain the echo amplitude of each third marker signal in the echo enrichment region information, and use it as the enriched echo amplitude;

[0082] a fourteenth acquisition unit, configured to acquire an echo time variation value of each third marker signal in the echo enrichment area information, and acquire an arrival distance variation value of the echo of each third marker signal according to the delay rate;

[0083] A fifteenth acquisition unit is used to map the arrival distance change value as the abscissa and the enriched echo amplitude as the ordinate to a two-dimensional coordinate system to generate data points;

[0084] A sixteenth acquisition unit is used to acquire all data points of all enriched echo quantity mappings on each probe path line, and link all data points to obtain two-dimensional defect graphic information;

[0085] a seventeenth acquisition unit, configured to acquire the echo velocity and echo time of all third marker signals in the echo enrichment region information;

[0086] An eighteenth acquisition unit, used to obtain defect depth information according to the echo velocity and the echo time;

[0087] The nineteenth acquisition unit is used to acquire the defect depth information of all third marking signals to obtain defect pattern depth information.

[0088] Preferably, the fourth acquisition module includes:

[0089] a twentieth acquisition unit, configured to acquire all probe path lines on the axial detection surface and use them as a first path line set;

[0090] A twenty-first acquisition unit, configured to acquire two-dimensional defect pattern information of all probe path lines in the first path line set, and use the two-dimensional defect pattern information as the first defect pattern;

[0091] A twenty-second acquisition unit is used to splice and integrate all the first defect patterns to obtain a two-dimensional defect axial image;

[0092] A twenty-third acquisition unit, configured to acquire all probe path lines on the radial detection surface and use them as a second path line set;

[0093] A twenty-fourth acquisition unit, used to acquire two-dimensional defect pattern information of all probe path lines in the second path line set, and use it as the second defect pattern;

[0094] A twenty-fifth acquisition unit is used to splice and integrate all the second defect patterns to obtain a two-dimensional defect radial image;

[0095] The twenty-sixth acquisition unit is used to collect the two-dimensional defect axial image on the axial detection surface and the two-dimensional defect radial image on the radial detection surface to obtain a two-dimensional defect scanning image.

[0096] The beneficial effects of the present application are as follows: the present invention can effectively reduce misjudgment and improve the reliability of detection by acquiring the echo signals of multiple detection points of the probe on each probe path line and comprehensively analyzing these signals. The echo signal of each detection point includes echo time and echo amplitude, and these information can be used to establish a two-dimensional echo signal schematic diagram. By analyzing these schematic diagrams, the echo amplitude change value and echo time change value of each echo signal can be obtained. Further, by setting the amplitude threshold interval and the time delay threshold interval, the echo signals that meet the conditions can be screened out, and these signals are considered to be echo enrichment area information. The acquisition of echo enrichment area information helps to identify potential defect areas, thereby improving the accuracy and reliability of detection. Then, by analyzing the echo enrichment area information, two-dimensional defect graphic information and defect graphic depth information are generated, which can more intuitively display the shape and position of the defect. After that, by acquiring the two-dimensional defect graphic information corresponding to all probe path lines, and generating defect axial images and defect radial images, the defect distribution inside the mold steel can be fully displayed. By acquiring a preset three-dimensional coordinate system, the defect axial image and the defect radial image are mapped to the same coordinate system to generate a complete three-dimensional image. By obtaining the defect shape and position information from the generated three-dimensional image, the type, severity and specific location of the defect can be evaluated more accurately. Finally, the first defect feature is extracted from the defect axial image and the second defect feature is extracted from the defect radial image through edge detection. By comparing them with the preset features, the defect type can be accurately identified and the defect status information of the mold steel can be generated. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] Figure 1 The figure is a schematic diagram of a method flow of an embodiment of the present application.

[0098] Figure 2 A schematic diagram of the system structure of an embodiment of the present application.

[0099] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0100] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0101] like Figure 1 As shown, the present application provides a method for accurately identifying and detecting internal defects of mold steel, comprising:

[0102] S1. Acquire multiple probe path lines of a mold steel detection surface, wherein the mold steel detection surface includes an axial detection surface and a radial detection surface, and each probe path line is used for mobile detection by an ultrasonic probe;

[0103] S2, obtaining echo signals of multiple detection points of each probe on each probe path line, and obtaining echo enrichment area information according to the echo signal of each detection point;

[0104] S3, acquiring two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information;

[0105] S4, generating a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point, wherein the defect scanning image includes a two-dimensional defect axial image and a two-dimensional defect radial image;

[0106] S5, generating a three-dimensional image according to the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and obtaining the defect shape information and the defect position information according to the three-dimensional image;

[0107] S6. Acquire defect type information according to the two-dimensional defect axial image and the two-dimensional defect radial image, and generate defect state information of the mold steel according to the defect type information, defect shape information and defect position information.

[0108] As described in the above steps S1-S6, the present invention ensures that the probe can cover the entire detection surface during the detection process by obtaining multiple probe path lines of the axial detection surface and the radial detection surface of the mold steel. Specifically, the multiple probe path lines of the axial detection surface and the radial detection surface can ensure that the probe can detect in different directions and positions, avoiding detection blind spots caused by improper path planning. The design of these path lines needs to take into account the geometric shape and internal structure of the mold steel to ensure that the probe can be evenly distributed on the entire detection surface, thereby improving the coverage and reliability of the detection. The internal structure of the mold steel is complex and there may be various types of defects, such as cracks, pores, inclusions, etc. These defects will generate different echo signals in ultrasonic testing. Traditional detection methods usually rely on the echo signal of a single detection point, but due to the complexity and noise inside the mold steel, the echo signal of a single detection point may be affected by multiple factors, resulting in misjudgment. The present invention significantly improves the comprehensiveness and reliability of internal defect detection of mold steel through multi-path detection and comprehensive analysis. Specifically, the method first obtains multiple probe path lines on the axial detection surface and radial detection surface of the mold steel to ensure that the probe can perform comprehensive detection in different directions and positions, avoiding detection blind spots caused by improper path planning. The design of the path line fully considers the geometric shape and internal structure of the mold steel to ensure that the probe can be evenly distributed on the entire detection surface, thereby improving the coverage and reliability of the detection. During the detection process, the probe obtains echo signals of multiple detection points on each path line, which include echo time and echo amplitude. By establishing a two-dimensional echo signal schematic diagram, analyzing the echo amplitude change value and echo time change value of each echo signal, setting the amplitude threshold interval and time delay threshold interval, and screening out qualified echo signals, which are considered to be echo enrichment area information. The acquisition of echo enrichment area information helps to identify potential defect areas, reduce misjudgment, and improve the reliability of detection. Furthermore, by analyzing the echo enrichment area information, two-dimensional defect graphic information and defect graphic depth information are generated, which can more intuitively display the shape and position of the defect and improve the accuracy of detection. The specific steps include obtaining the number of enriched echoes, echo amplitude and echo time change values ​​in the echo enrichment area information, calculating the echo arrival distance change value, generating data points and linking to generate two-dimensional defect graphic information. In order to fully display the defect distribution inside the mold steel, this method obtains the two-dimensional defect graphic information of all probe path lines from the axial and radial detection surfaces, and generates a two-dimensional defect axial image and a two-dimensional defect radial image. These images can analyze defects from different angles and improve the accuracy and reliability of detection. In addition, in order to more intuitively display the three-dimensional characteristics of the defect, this method maps the two-dimensional defect axial image and the two-dimensional defect radial image to the same coordinate system through a preset three-dimensional coordinate system to generate a three-dimensional image. From the generated three-dimensional image, the length, width, height, shape information and boundary information of the defect can be obtained to improve the accuracy of defect assessment.Finally, in order to accurately evaluate the defect status of the mold steel, the method extracts the first defect feature and the second defect feature, including length information, shape information and boundary information, from the two-dimensional defect axial image and the two-dimensional defect radial image through edge detection. These features are compared with the preset feature library to accurately identify the defect type and generate the defect status information of the mold steel. In summary, the present invention significantly improves the comprehensiveness, accuracy and reliability of internal defect detection of mold steel through technical means such as multi-path detection, echo signal analysis, and two-dimensional and three-dimensional image generation, providing strong support for the quality control and maintenance of mold steel.

[0109] In one embodiment, the step of acquiring two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information includes:

[0110] S201, obtaining all equidistant detection points on each probe path line;

[0111] S202, obtaining an initial pulse wave of the probe at each detection point;

[0112] S203, acquiring a plurality of detection point echo signals at each detection point based on the initial pulse wave, wherein each detection point echo signal includes an echo time and an echo amplitude;

[0113] S204, establishing a two-dimensional echo signal schematic diagram for each detection point according to a plurality of echo times and echo amplitudes;

[0114] S205, obtaining an echo amplitude change value of each echo signal according to the echo signal schematic diagram;

[0115] S206, obtaining an amplitude threshold interval, and determining whether the echo amplitude change value of each echo signal is within the amplitude threshold interval;

[0116] If it is located, then all echo signals within the amplitude threshold interval are acquired, and the echo signals within the amplitude threshold interval are used as the first marked echo signals;

[0117] S207, obtaining an echo time variation value of each echo signal according to the echo signal schematic diagram;

[0118] S208, obtaining a delay rate of each echo signal according to the echo time variation value;

[0119] S209, obtaining a time delay threshold interval, and determining whether the delay rate of each of the echo signals is within the time delay threshold interval;

[0120] If it is, then all echo signals within the time delay threshold interval are acquired, and the echo signals within the time delay threshold interval are used as second marked echo signals;

[0121] S210, comparing all first marker echo signals with all second marker echo signals, and taking the signal that matches the first marker echo signal and the second marker echo signal as the third marker signal;

[0122] S211. Acquire all third marker signals, and use all third marker signals as echo enrichment region information.

[0123] As described in the above steps S201-S211, the present invention can ensure that the probe can evenly cover the entire path line during the detection process by obtaining all equidistant detection points on each probe path line, thereby improving the comprehensiveness and reliability of the detection. Specifically, first, the spacing between the detection points is determined according to the length of the probe path line and the required detection density. Then, the detection points are arranged at equal intervals on each probe path line to ensure that each detection point can obtain a valid echo signal. In this way, the detection blind area caused by the uneven distribution of the detection points can be avoided, and the accuracy and reliability of the detection can be improved. The basic principle of ultrasonic detection is to detect defects inside the material by emitting ultrasonic pulses and receiving their echoes. The quality of the initial pulse wave directly affects the reliability and accuracy of the echo signal. If the initial pulse wave is unstable or of poor quality, it may cause the echo signal to be distorted, affecting the detection results. By obtaining the initial pulse wave of the probe at each detection point, it can be ensured that the ultrasonic pulse emitted during each detection is stable and of good quality. Specifically, the probe emits a standard initial pulse wave at each detection point, and the frequency, amplitude and duration of the pulse wave are strictly calibrated. In this way, the initial conditions for each test can be ensured to be consistent, the error caused by the instability of the initial pulse wave can be reduced, and the accuracy and reliability of the test can be improved; in ultrasonic testing, the echo signal contains important information about the internal structure of the material. The echo signal of each test point includes the echo time and the echo amplitude, which can be used to determine whether there are defects inside the material and their location and size. However, due to the complexity and noise inside the material, the echo signal of a single test point may be affected by multiple factors, resulting in misjudgment. By obtaining multiple test point echo signals at each test point based on the initial pulse wave, misjudgment can be effectively reduced and the reliability of the test can be improved. Specifically, after the probe transmits the initial pulse wave at each test point, it receives multiple echo signals. Each echo signal includes the echo time and the echo amplitude, which can be used to establish a two-dimensional echo signal schematic diagram. By analyzing these schematic diagrams, the echo amplitude change value and the echo time change value of each echo signal can be obtained, and the echo signals that meet the conditions can be further screened out. This can improve the accuracy and reliability of detection, reduce misjudgments caused by unstable echo signals at a single detection point, and at the same time, by establishing a two-dimensional echo signal diagram for each detection point based on multiple echo times and echo amplitudes, the change trend of the echo signal can be more intuitively displayed, improving the accuracy and reliability of detection. Specifically, the echo time and echo amplitude information of multiple echo signals at each detection point are first extracted, and then this information is plotted in a two-dimensional coordinate system. The horizontal axis represents the echo time, and the vertical axis represents the echo amplitude. In this way, a two-dimensional echo signal diagram for each detection point can be generated, which is convenient for technicians to quickly understand and analyze the detection results; and in ultrasonic testing, the amplitude change of the echo signal reflects the structural changes inside the material.If there is a defect in a certain area, the amplitude of the echo signal may change significantly. Therefore, by analyzing the amplitude change value of the echo signal, it is possible to preliminarily determine whether there is a defect in the area. However, the traditional detection method can usually only provide the echo amplitude information of a single detection point, and it is difficult to fully evaluate the change trend of the echo signal. By obtaining the echo amplitude change value of each echo signal according to the echo signal schematic diagram, the change trend of the echo signal can be more comprehensively evaluated, and the accuracy and reliability of the detection can be improved. Specifically, the echo amplitude value of each echo signal is first extracted from the two-dimensional echo signal schematic diagram, and then the amplitude difference between adjacent echo signals is calculated. These amplitude differences reflect the amplitude change trend of the echo signal. By setting a certain threshold, the echo signals with significant amplitude changes can be screened out, and these signals may be indications of defective areas. This can improve the accuracy and reliability of detection, reduce the misjudgment caused by the insignificant change of the echo amplitude at a single detection point, and by obtaining the amplitude threshold interval and judging whether the echo amplitude change value of each echo signal is within the amplitude threshold interval, the echo signals with significant amplitude changes can be effectively screened out, and the accuracy and reliability of detection can be improved. Specifically, first, a reasonable amplitude threshold interval is set based on experience or experimental data. Then, the echo amplitude change value of each echo signal is extracted from the two-dimensional echo signal schematic diagram, and it is determined whether these change values ​​are within the amplitude threshold interval. If the echo amplitude change value of a certain echo signal is within the amplitude threshold interval, it is used as the first marker echo signal. This can effectively reduce misjudgments caused by factors such as noise and improve the accuracy and reliability of detection; by obtaining the echo time change value of each echo signal according to the echo signal schematic diagram, the change trend of the echo signal can be more comprehensively evaluated to improve the accuracy and reliability of detection. Specifically, the echo time value of each echo signal is first extracted from the two-dimensional echo signal schematic diagram, and then the time difference between adjacent echo signals is calculated. These time differences reflect the time change trend of the echo signal. By setting a certain threshold, echo signals with significant time changes can be screened out, which may be an indication of defective areas. This can improve the accuracy and reliability of detection and reduce misjudgment caused by unclear echo time changes at a single detection point. By obtaining the delay rate of each echo signal based on the echo time change value, the change trend of the echo signal can be more accurately evaluated, thereby improving the accuracy and reliability of detection. Specifically, firstly, the echo time change value of each echo signal is extracted from the two-dimensional echo signal schematic diagram, and then the delay rate of each echo signal is calculated. The delay rate can be calculated using the following formula:.

[0124] ;

[0125] Where T is the delay rate, Δt is the echo time change value, and t0 is the echo time of the initial pulse wave.

[0126] By calculating the delay rate of each echo signal, the changing trend of the echo signal can be more accurately evaluated, and the accuracy and reliability of the detection can be improved; in ultrasonic detection, the delay rate of the echo signal is one of the important bases for judging defects. However, due to the complexity and noise inside the material and other factors, the delay rate of the echo signal may be affected by various factors, resulting in misjudgment. The present invention obtains the time delay threshold interval and determines whether the delay rate of each echo signal is within the time delay threshold interval. It can effectively screen out echo signals with significant delay rates and improve the accuracy and reliability of detection. Specifically, first, a reasonable time delay threshold interval is set based on experience or experimental data. Then, the delay rate of each echo signal is extracted from the two-dimensional echo signal schematic diagram, and it is determined whether these delay rates are within the time delay threshold interval. If the delay rate of a certain echo signal is within the time delay threshold interval, it is used as the second marker echo signal. This can effectively reduce misjudgments caused by factors such as noise, and improve the accuracy and reliability of detection; by comparing all first-marker echo signals with all second-marker echo signals, and using the signals that meet the first-marker echo signals and the second-marker echo signals as third-marker signals, potential defect areas can be more accurately identified, and the accuracy and reliability of detection can be improved. Specifically, first, all first-marker echo signals are compared with all second-marker echo signals to find echo signals that meet both significant amplitude changes and significant delay rates. These echo signals are used as third-marker signals. In this way, misjudgments caused by insignificant single indicators can be effectively reduced, and the accuracy and reliability of detection can be improved; finally, by obtaining all third-marker signals and using all third-marker signals as echo enrichment area information, potential defect areas can be more accurately identified, and the accuracy and reliability of detection can be improved. Specifically, first, all third-marker signals are extracted, and these signals meet both the conditions of significant amplitude changes and significant delay rates. Then, these third-marker signals are used as echo enrichment area information. The acquisition of echo enrichment area information helps to further analyze and confirm potential defect areas, and provides basic data for subsequent defect identification and quantitative analysis. This can improve the accuracy and reliability of detection and reduce misjudgments caused by the insignificance of a single indicator. Through the above steps, the present invention can effectively solve the problems of misjudgment, insufficient detection coverage, inaccurate defect assessment, etc. in ultrasonic detection, and improve the comprehensiveness, accuracy and reliability of internal defect detection of mold steel.

[0127] In one embodiment, the step of acquiring two-dimensional defect pattern information and defect pattern depth information according to the echo enrichment area information includes:

[0128] S301, obtaining the number of all third marker signals in the echo enrichment region information, and using it as the number of enriched echoes;

[0129] S302, acquiring the echo amplitude of each third marker signal in the echo enrichment region information, and using it as the enriched echo amplitude;

[0130] S303, obtaining an echo time variation value of each third marker signal in the echo enrichment area information, and obtaining an arrival distance variation value of the echo of each third marker signal according to the delay rate;

[0131] S304, mapping the arrival distance change value as the abscissa and the enriched echo amplitude as the ordinate to a two-dimensional coordinate system to generate data points;

[0132] S305, obtaining all data points mapped by the number of all enriched echoes on each probe path line, and linking all data points to obtain two-dimensional defect graphic information;

[0133] S306, acquiring the echo velocity and echo time of all third marker signals in the echo enrichment region information;

[0134] S307, obtaining defect depth information according to the echo velocity and the echo time;

[0135] S308 , acquiring defect depth information of all third marking signals to obtain defect pattern depth information.

[0136] As described in the above steps S301-S308, the present invention can more accurately evaluate the range and density of the echo-enriched area by obtaining the number of all third marker signals in the echo-enriched area information and using it as the number of enriched echoes. Specifically, firstly, all third marker signals are extracted from the echo-enriched area information, and these signals simultaneously meet the conditions of significant amplitude change and significant delay rate. Then, the number of these third marker signals is counted and used as the number of enriched echoes. The statistics of the number of enriched echoes are helpful to further analyze and confirm the potential defect area; and the echo amplitude is an important parameter in ultrasonic detection, which reflects the strength of the echo signal. In the echo-enriched area, the change of the echo amplitude can provide important information about the location and size of the defect. However, the traditional detection method can usually only provide the echo amplitude information of a single detection point, and it is difficult to comprehensively evaluate the echo amplitude change in the echo-enriched area. By obtaining the echo amplitude of each third marker signal in the echo-enriched area information and using it as the enriched echo amplitude, the echo amplitude change in the echo-enriched area can be more comprehensively evaluated, and the accuracy and reliability of the detection can be improved. Specifically, the echo amplitude value of each third marker signal is extracted from the echo enrichment area information and used as the enriched echo amplitude. These amplitude values ​​reflect the intensity change of the echo signal and help identify potential defect areas. In this way, the echo amplitude change in the echo enrichment area can be more accurately evaluated, the accuracy and reliability of detection can be improved, and the misjudgment caused by the unclear echo amplitude change at a single detection point can be reduced; echo time change and delay rate are important parameters in ultrasonic detection, reflecting the time change of the echo signal propagating inside the material. In the echo enrichment area, the echo time change and the delay rate change can provide important information about the location and size of the defect. However, the traditional detection method can usually only provide the echo time information of a single detection point, and it is difficult to comprehensively evaluate the echo time change and delay rate change in the echo-enriched area. By obtaining the echo time change value of each third marker signal in the echo-enriched area information, and obtaining the arrival distance change value of the echo of each third marker signal according to the delay rate, the echo time change and delay rate change in the echo-enriched area can be more accurately evaluated, and the accuracy and reliability of the detection can be improved. In ultrasonic detection, the arrival distance change value of the echo signal and the enriched echo amplitude are mapped to a two-dimensional coordinate system, which can more intuitively display the change trend of the echo signal. The traditional detection method can usually only provide echo signal information of a single dimension, and it is difficult to intuitively display the change trend of the echo signal. By mapping the arrival distance change value as the horizontal coordinate and the enriched echo amplitude as the vertical coordinate to generate data points in a two-dimensional coordinate system, the change trend of the echo signal can be more intuitively displayed, and the accuracy and reliability of the detection can be improved.Specifically, the arrival distance change value of each third marker signal is first used as the horizontal coordinate, and the enriched echo amplitude is used as the vertical coordinate, and mapped to the two-dimensional coordinate system to generate data points; in ultrasonic testing, two-dimensional defect graphic information is an important basis for evaluating internal defects in mold steel. By linking all data points to generate two-dimensional defect graphic information, the shape and position of the defect can be more intuitively displayed. By obtaining all data points mapped by the number of enriched echoes on each probe path line, and linking all data points to generate two-dimensional defect graphic information, the shape and position of the defect can be more intuitively displayed, and the accuracy and reliability of detection can be improved. Specifically, first obtain all data points mapped by the number of enriched echoes on each probe path line, and then link these data points to generate two-dimensional defect graphic information; echo velocity and echo time are important parameters in ultrasonic testing, reflecting the speed and time of echo signal propagation inside the material. In the echo-enriched area, the changes in echo velocity and echo time can provide important information about the location and size of the defect. By obtaining the echo velocity and echo time of all third marker signals in the echo-enriched area information, the echo velocity and echo time changes in the echo-enriched area can be more accurately evaluated, and the accuracy and reliability of detection can be improved. Specifically, the echo velocity and echo time values ​​of each third marker signal are extracted from the echo-enriched area information. These values ​​reflect the speed and time changes of the echo signal propagating inside the material, which helps to identify potential defect areas. By obtaining the defect depth information based on the echo velocity and echo time, the depth of the defect can be more accurately evaluated, and the accuracy and reliability of detection can be improved. Specifically, the echo velocity and echo time values ​​of each third marker signal are first extracted from the echo-enriched area information. Then, according to the basic principle of ultrasonic propagation, the defect depth of each third marker signal is calculated. By obtaining the defect depth information of all third marker signals, the defect graphic depth information is obtained, and the depth distribution of the defect can be more accurately evaluated, and the accuracy and reliability of detection can be improved. Specifically, the defect depth information of all third marker signals is first extracted from the echo-enriched area information. Then, these defect depth information are summarized to generate complete defect graphic depth information. The generation of defect graphic depth information helps to further analyze and confirm potential defect areas, providing basic data for subsequent defect identification and quantitative analysis.

[0137] In one embodiment, the step of generating a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point includes:

[0138] S401, acquiring all probe path lines on the axial detection surface and using them as a first path line set;

[0139] S402, obtaining two-dimensional defect graphic information of all probe path lines in the first path line set, and using it as a first defect graphic;

[0140] S403, stitching and integrating all first defect patterns to obtain a two-dimensional defect axial image;

[0141] S404, acquiring all probe path lines on the radial detection surface and using them as a second path line set;

[0142] S405, obtaining two-dimensional defect pattern information of all probe path lines in the second path line set, and using it as the second defect pattern;

[0143] S406, stitching and integrating all the second defect patterns to obtain a two-dimensional defect radial image;

[0144] S407 , collecting the two-dimensional defect axial image on the axial detection surface and the two-dimensional defect radial image on the radial detection surface to obtain a two-dimensional defect scanning image.

[0145] As described in the above steps S401-S406, the present invention can ensure that the probe can cover the entire axial detection surface during the detection process by obtaining all probe path lines on the axial detection surface and using them as the first path line set, thereby improving the comprehensiveness and reliability of the detection. Specifically, firstly, according to the geometric shape and size of the axial detection surface, a plurality of probe path lines are designed to ensure that these path lines can be evenly distributed on the entire axial detection surface. In ultrasonic testing, two-dimensional defect graphic information is an important basis for evaluating internal defects of mold steel. By obtaining the two-dimensional defect graphic information on each probe path line, the shape and position of the defect can be more intuitively displayed. By obtaining the two-dimensional defect graphic information of all probe path lines in the first path line set and using them as the first defect graphic, the defect distribution on the entire axial detection surface can be more comprehensively evaluated, thereby improving the accuracy and reliability of the detection. Specifically, firstly, the two-dimensional defect graphic information on each probe path line is extracted from the first path line set. This information includes the shape, position and size of the defect. Then, these two-dimensional defect graphic information are integrated together to form a first defect graphic; then, by splicing and integrating all the first defect graphics, a two-dimensional defect axial image is obtained, which can more intuitively show the distribution of defects in the axial direction and improve the accuracy and reliability of detection. Specifically, firstly, the two-dimensional defect graphic information of all probe path lines in the first path line set is spliced ​​and aligned to ensure that the position of each defect graphic in the axial direction is consistent. Then, these defect graphics are merged into an overall two-dimensional defect axial image. In this way, comprehensive information about the defect distribution on the entire axial detection surface can be generated, which is convenient for technicians to quickly understand and analyze the detection results; similarly, by obtaining all probe path lines on the radial detection surface and using them as the second path line set, it can be ensured that the probe can cover the entire radial detection surface during the detection process, thereby improving the comprehensiveness and reliability of the detection. Specifically, firstly, according to the geometric shape and size of the radial detection surface, multiple probe path lines are designed to ensure that these path lines can be evenly distributed on the entire radial detection surface, and then by obtaining the two-dimensional defect graphic information of all probe path lines in the second path line set and using them as the second defect graphic, the defect distribution on the entire radial detection surface can be more comprehensively evaluated, thereby improving the accuracy and reliability of detection. Specifically, firstly, the two-dimensional defect graphic information on each probe path line is extracted from the second path line set, which includes the shape, position and size of the defect.Then, these two-dimensional defect graphic information are spliced ​​and integrated together to form a second defect graphic (when splicing and integrating the two-dimensional defect graphic information, the two-dimensional defect graphic on each probe path line can be first subjected to Canny edge detection to extract clear edge information, and then these edge information can be spliced ​​together to form a complete second defect graphic); by splicing and integrating all the second defect graphics, a two-dimensional defect radial image is obtained, which can more intuitively display the radial distribution of defects and improve the accuracy and reliability of detection. Specifically, first, the two-dimensional defect graphic information of all probe path lines in the second path line set is spliced ​​and aligned to ensure that the radial position of each defect graphic is consistent. Then, these defect graphics are merged into an overall two-dimensional defect radial image; through the above steps, all probe path lines on the axial detection surface and the radial detection surface are obtained, and the corresponding two-dimensional defect graphic information is generated, so that the defect distribution inside the mold steel can be more comprehensively evaluated.

[0146] In one embodiment, the step of generating a three-dimensional image according to the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and obtaining the defect shape information and the defect position information according to the three-dimensional image includes:

[0147] S501, obtaining a preset three-dimensional coordinate system;

[0148] S502, acquiring a plurality of first positioning points according to the two-dimensional defect axial image;

[0149] S503, obtaining a first positioning depth of each first positioning point according to the defect pattern depth information corresponding to the two-dimensional defect axial image;

[0150] S504, acquiring a plurality of second positioning points according to the two-dimensional defect radial image,

[0151] S505, obtaining a second positioning depth of each second positioning point according to the defect pattern depth information corresponding to the two-dimensional defect radial image;

[0152] S506, mapping the corresponding first positioning point to a preset three-dimensional coordinate system according to the first positioning depth to obtain a first defect three-dimensional image;

[0153] S507, mapping the corresponding second positioning point to a preset three-dimensional coordinate system according to the second positioning depth, combining it with the first defect three-dimensional image, removing the positioning points where the first positioning point and the second positioning point overlap, and obtaining a three-dimensional image;

[0154] S508, obtaining defect shape information from the three-dimensional image, wherein the defect shape information includes defect length, width, height information, shape information, and boundary information;

[0155] S509 , obtaining defect position information from the three-dimensional image, where the defect position information is the specific coordinate position of the defect in the three-dimensional coordinate system.

[0156] As described in the above steps S501-S509, the present invention presets a three-dimensional coordinate system. This coordinate system usually includes an X-axis, a Y-axis and a Z-axis, which correspond to the radial, axial and depth directions of the mold steel respectively. The purpose of the preset three-dimensional coordinate system is to provide a unified reference framework for subsequent image mapping and analysis, ensuring that all detection data can be accurately located and compared in the same coordinate system, and then after obtaining the preset three-dimensional coordinate system, it is necessary to extract multiple first positioning points from the two-dimensional defect axial image. These positioning points are key points in the two-dimensional defect axial image, and usually indicate the location of the defect. Through image processing technology (such as edge detection, feature extraction, etc.), these positioning points can be accurately extracted from the two-dimensional defect axial image. After extracting the first positioning point, it is necessary to obtain the first positioning depth of each first positioning point according to the defect graphic depth information corresponding to the two-dimensional defect axial image. In this step, by analyzing the echo signal of each first positioning point, the corresponding depth information is calculated. Specifically, according to the echo time and echo velocity of the echo signal, the specific depth of each first positioning point inside the mold steel can be calculated. After obtaining the first positioning point and its depth information, it is necessary to extract multiple second positioning points from the two-dimensional defect radial image. These positioning points also represent the position of the defect, but they are obtained from the radial angle. Through image processing technology (such as edge detection, feature extraction, etc.), these positioning points can be accurately extracted from the two-dimensional defect radial image. After extracting the second positioning point, it is necessary to obtain the second positioning depth of each second positioning point according to the defect pattern depth information corresponding to the two-dimensional defect radial image. In this step, the echo signal of each second positioning point is analyzed to calculate its corresponding depth information. Specifically, according to the echo time and echo velocity of the echo signal, the specific depth of each second positioning point inside the mold steel can be calculated. According to the depth information of each first positioning point, it is mapped from the two-dimensional defect axial image to the corresponding position in the three-dimensional coordinate system. This step generates a first defect three-dimensional image, which preliminarily shows the distribution of defects inside the mold steel in the axial direction. According to the depth information of each second positioning point, it is mapped from the two-dimensional defect radial image to the corresponding position in the three-dimensional coordinate system. This step generates a second defect three-dimensional image. Then, the first defect three-dimensional image and the second defect three-dimensional image are combined, and the overlapping positioning points in the two images are eliminated, and finally a complete three-dimensional image is generated. After the complete three-dimensional image is generated, the shape information of the defect needs to be extracted from the image. Specifically, through image processing technology (such as edge detection, contour extraction, etc.), the length, width, height, shape and boundary information of each defect point can be obtained. After extracting the shape information of the defect, the specific location information of each defect point needs to be obtained from the three-dimensional image. Specifically, by analyzing each defect point in the three-dimensional image, its location information can be converted into a specific coordinate position in the three-dimensional coordinate system.

[0157] In one embodiment, the step of acquiring defect type information according to the two-dimensional defect axial image and the two-dimensional defect radial image comprises:

[0158] S601, extracting a first defect feature from the two-dimensional defect axial image by edge detection, wherein the first defect feature includes defect axial length information, defect axial shape information, and defect axial boundary information;

[0159] S602, extracting a second defect feature from the two-dimensional defect radial image by edge detection, wherein the second defect feature includes defect radial length information, defect radial shape information, and defect radial boundary information;

[0160] S603: Compare the first defect feature and the second defect feature with the preset feature to obtain defect type information.

[0161] As described in the above steps S601-S603, in the field of non-destructive testing, especially in ultrasonic testing, the two-dimensional defect axial image can provide key information about the axial distribution of defects. However, reading this information directly from the image is often not intuitive and accurate enough. The present invention extracts the first defect feature from the two-dimensional defect axial image through edge detection, which can more accurately identify and quantify the characteristics of the defect. Specifically, edge detection algorithms (such as Canny, Sobel, etc.) can be used to identify the boundaries in the image, thereby extracting the defect axial length information, axial shape information and axial boundary information of the defect. For example, the defect axial length information can be obtained by measuring the distance between the defect edges; the axial shape information can be obtained by analyzing the continuity and curvature of the defect edge; the axial boundary information can be obtained by detecting the clarity and continuity of the defect edge; in the field of non-destructive testing, especially in ultrasonic testing, the two-dimensional defect radial image can provide key information about the radial distribution of defects. Similar to the axial image, reading this information directly from the image is often not intuitive and accurate enough. Extracting the second defect feature from the two-dimensional defect radial image through edge detection can more accurately identify and quantify the characteristics of the defect. Specifically, edge detection algorithms (such as Canny, Sobel, etc.) can be used to identify the boundaries in the image, thereby extracting the defect radial length information, radial shape information and radial boundary information of the defect. For example, the defect radial length information can be obtained by measuring the distance between the defect edges; the radial shape information can be obtained by analyzing the continuity and curvature of the defect edge; the radial boundary information can be obtained by detecting the clarity and continuity of the defect edge. In the field of non-destructive testing, especially ultrasonic testing, accurately identifying and classifying defect types is a key step in evaluating the quality of materials or components. By extracting the first defect feature and the second defect feature from the two-dimensional defect axial image and the two-dimensional defect radial image, the defect can be analyzed in more detail, and by comparing the extracted first defect feature and the second defect feature with the preset feature, the defect type can be accurately identified and classified. Specifically, the preset feature library contains feature information of various common defect types, such as cracks, pores, inclusions, etc. By comparing the extracted features with the preset features, the similarity or matching degree can be calculated. For example, the matching degree can be evaluated by calculating the Euclidean distance or cosine similarity between feature vectors. When the matching degree exceeds a certain threshold, it can be considered that the detected defect belongs to a certain specific type. In addition, machine learning algorithms (such as support vector machines, neural networks, etc.) can be used to automatically classify defect types to further improve the accuracy and efficiency of classification.

[0162] like Figure 2 As shown, the present invention also provides a mold steel internal defect accurate identification and detection system, comprising:

[0163] A first acquisition module 1 is used to acquire multiple probe path lines of a mold steel detection surface, wherein the mold steel detection surface includes an axial detection surface and a radial detection surface, and each of the probe path lines is used for mobile detection by an ultrasonic probe;

[0164] The second acquisition module 2 is used to acquire echo signals of multiple detection points of each probe on each probe path line, and acquire echo enrichment area information according to the echo signal of each detection point;

[0165] The third acquisition module 3 is used to acquire two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information;

[0166] A fourth acquisition module 4 is used to generate a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point, wherein the defect scanning image includes a two-dimensional defect axial image and a two-dimensional defect radial image;

[0167] A fifth acquisition module 5, used to generate a three-dimensional image according to the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and to acquire defect shape information and defect position information according to the three-dimensional image;

[0168] The sixth acquisition module 6 is used to acquire defect type information according to the two-dimensional defect axial image and the two-dimensional defect radial image, and generate defect state information of the mold steel according to the defect type information, defect shape information and defect position information.

[0169] In one embodiment, the second acquisition module 2 includes:

[0170] A first acquisition unit, used for acquiring all equidistant detection points on each probe path line;

[0171] A second acquisition unit, used for acquiring an initial pulse wave of the probe at each of the detection points;

[0172] A third acquisition unit, configured to acquire a plurality of detection point echo signals at each of the detection points based on the initial pulse wave, wherein each of the detection point echo signals includes an echo time and an echo amplitude;

[0173] a fourth acquisition unit, configured to establish a two-dimensional echo signal schematic diagram for each of the detection points according to a plurality of echo times and echo amplitudes;

[0174] A fifth acquisition unit, used for acquiring an echo amplitude change value of each echo signal according to the echo signal schematic diagram;

[0175] a sixth acquisition unit, configured to acquire an amplitude threshold interval, and determine whether the echo amplitude change value of each of the echo signals is within the amplitude threshold interval;

[0176] If it is located, then all echo signals within the amplitude threshold interval are acquired, and the echo signals within the amplitude threshold interval are used as the first marked echo signals;

[0177] a seventh acquisition unit, configured to acquire an echo time variation value of each echo signal according to the echo signal schematic diagram;

[0178] an eighth acquisition unit, configured to acquire a delay rate of each echo signal according to the echo time variation value;

[0179] a ninth acquisition unit, configured to acquire a time delay threshold interval, and determine whether the delay rate of each of the echo signals is within the time delay threshold interval;

[0180] If it is, then all echo signals within the time delay threshold interval are acquired, and the echo signals within the time delay threshold interval are used as second marked echo signals;

[0181] a tenth acquisition unit, configured to compare all first marker echo signals with all second marker echo signals, and use the signals that match the first marker echo signals and the second marker echo signals as third marker signals;

[0182] The eleventh acquisition unit is used to acquire all third marker signals and use all third marker signals as echo enrichment area information.

[0183] In one embodiment, the third acquisition module 3 includes:

[0184] a twelfth obtaining unit, configured to obtain the number of all third marker signals in the echo enrichment region information, and use the number as the enriched echo number;

[0185] a thirteenth obtaining unit, configured to obtain the echo amplitude of each third marker signal in the echo enrichment region information, and use it as the enriched echo amplitude;

[0186] a fourteenth acquisition unit, configured to acquire an echo time variation value of each third marker signal in the echo enrichment area information, and acquire an arrival distance variation value of the echo of each third marker signal according to the delay rate;

[0187] A fifteenth acquisition unit is used to map the arrival distance change value as the abscissa and the enriched echo amplitude as the ordinate to a two-dimensional coordinate system to generate data points;

[0188] A sixteenth acquisition unit is used to acquire all data points of all enriched echo quantity mappings on each probe path line, and link all data points to obtain two-dimensional defect graphic information;

[0189] a seventeenth acquisition unit, configured to acquire the echo velocity and echo time of all third marker signals in the echo enrichment region information;

[0190] An eighteenth acquisition unit, used to obtain defect depth information according to the echo velocity and the echo time;

[0191] The nineteenth acquisition unit is used to acquire the defect depth information of all third marking signals to obtain defect pattern depth information.

[0192] In one embodiment, the fourth acquisition module 4 includes:

[0193] a twentieth acquisition unit, configured to acquire all probe path lines on the axial detection surface and use them as a first path line set;

[0194] A twenty-first acquisition unit, configured to acquire two-dimensional defect pattern information of all probe path lines in the first path line set, and use the two-dimensional defect pattern information as the first defect pattern;

[0195] A twenty-second acquisition unit is used to splice and integrate all the first defect patterns to obtain a two-dimensional defect axial image;

[0196] A twenty-third acquisition unit, configured to acquire all probe path lines on the radial detection surface and use them as a second path line set;

[0197] A twenty-fourth acquisition unit, used to acquire two-dimensional defect pattern information of all probe path lines in the second path line set, and use it as the second defect pattern;

[0198] A twenty-fifth acquisition unit is used to splice and integrate all the second defect patterns to obtain a two-dimensional defect radial image;

[0199] The twenty-sixth acquisition unit is used to collect the two-dimensional defect axial image on the axial detection surface and the two-dimensional defect radial image on the radial detection surface to obtain a two-dimensional defect scanning image.

[0200] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, value library or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0201] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0202] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent results or equivalent process changes made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for accurately identifying and detecting internal defects of mold steel, characterized in that: include: Acquire multiple probe path lines of the mold steel detection surface, wherein the mold steel detection surface includes an axial detection surface and a radial detection surface, and each probe path line is used for mobile detection by an ultrasonic probe; Obtain all equally spaced detection points on each probe path line; Obtaining an initial pulse wave of the probe at each of the detection points; Acquire multiple detection point echo signals at each detection point based on the initial pulse wave, wherein each detection point echo signal includes an echo time and an echo amplitude; Establishing a two-dimensional echo signal schematic diagram for each detection point according to a plurality of echo times and echo amplitudes; Acquire the echo amplitude change value of each echo signal according to the echo signal schematic diagram; Obtaining an amplitude threshold interval, and determining whether the echo amplitude change value of each of the echo signals is within the amplitude threshold interval; If it is located, then all echo signals within the amplitude threshold interval are acquired, and the echo signals within the amplitude threshold interval are used as the first marked echo signals; Acquire the echo time variation value of each echo signal according to the echo signal schematic diagram; Obtaining the delay rate of each echo signal according to the echo time variation value; Acquire a time delay threshold interval, and determine whether the delay rate of each of the echo signals is within the time delay threshold interval; If it is, then all echo signals within the time delay threshold interval are acquired, and the echo signals within the time delay threshold interval are used as second marked echo signals; Compare all first marker echo signals with all second marker echo signals, and use the signal that matches the first marker echo signal and the second marker echo signal as the third marker signal; Acquire all third marker signals, and use all third marker signals as echo enrichment area information; Acquire two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information; Generate a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point, wherein the defect scanning image includes a two-dimensional defect axial image and a two-dimensional defect radial image; Generate a three-dimensional image based on the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and obtain the defect shape information and defect position information based on the three-dimensional image; Defect type information is acquired according to the two-dimensional defect axial image and the two-dimensional defect radial image, and defect state information of the mold steel is generated according to the defect type information, defect shape information and defect position information.

2. The method for accurately identifying and detecting internal defects of mold steel according to claim 1, characterized in that: The step of acquiring two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information comprises: Obtaining the number of all third marker signals in the echo enrichment region information, and using it as the number of enriched echoes; Acquire the echo amplitude of each third marker signal in the echo enrichment area information, and use it as the enriched echo amplitude; Acquire the echo time variation value of each third marker signal in the echo enrichment area information, and acquire the arrival distance variation value of the echo of each third marker signal according to the delay rate; Map the arrival distance change value as the abscissa and the enriched echo amplitude as the ordinate to a two-dimensional coordinate system to generate data points; Obtain all enriched echo quantities on each probe path line and map all data points, and link all data points to obtain two-dimensional defect graphic information; Acquiring the echo velocity and echo time of all third marker signals in the echo enrichment area information; Obtain defect depth information based on echo velocity and echo time; The defect depth information of all third marking signals is acquired to obtain the defect pattern depth information.

3. The method for accurately identifying and detecting internal defects of mold steel according to claim 1, characterized in that: The step of generating a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point includes: Acquire all probe path lines on the axial detection surface and use them as a first path line set; Obtaining two-dimensional defect graphic information of all probe path lines in the first path line set, and using it as the first defect graphic; All first defect images are spliced ​​and integrated to obtain a two-dimensional defect axial image; Acquire all probe path lines on the radial detection surface and use them as a second path line set; Obtaining two-dimensional defect graphic information of all probe path lines in the second path line set, and using it as the second defect graphic; All second defect graphics are spliced ​​and integrated to obtain a two-dimensional defect radial image; The two-dimensional defect axial image on the axial detection surface and the two-dimensional defect radial image on the radial detection surface are collected to obtain a two-dimensional defect scanning image.

4. The method for accurately identifying and detecting internal defects of mold steel according to claim 3, characterized in that: The step of generating a three-dimensional image according to the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and obtaining the defect shape information and the defect position information according to the three-dimensional image comprises: Get the preset three-dimensional coordinate system; Acquire a plurality of first positioning points according to the two-dimensional defect axial image; Acquire a first positioning depth of each first positioning point according to defect pattern depth information corresponding to the two-dimensional defect axial image; Acquire multiple second positioning points according to the two-dimensional defect radial image, Acquire a second positioning depth of each second positioning point according to defect pattern depth information corresponding to the two-dimensional defect radial image; Mapping the corresponding first positioning point to a preset three-dimensional coordinate system according to the first positioning depth to obtain a first defect three-dimensional image; Mapping the corresponding second positioning point to a preset three-dimensional coordinate system according to the second positioning depth, combining it with the first defect three-dimensional image, eliminating the positioning points where the first positioning point and the second positioning point overlap, and obtaining a three-dimensional image; Acquire defect shape information from the three-dimensional image, wherein the defect shape information includes defect length, width, height information, shape information, and boundary information; The defect position information is obtained from the three-dimensional image, where the defect position information is the specific coordinate position of the defect in the three-dimensional coordinate system.

5. The method for accurately identifying and detecting internal defects of mold steel according to claim 1, characterized in that: The step of acquiring defect type information according to the two-dimensional defect axial image and the two-dimensional defect radial image comprises: Extracting a first defect feature from the two-dimensional defect axial image by edge detection, wherein the first defect feature includes defect axial length information, defect axial shape information, and defect axial boundary information; Extracting a second defect feature from the two-dimensional defect radial image by edge detection, wherein the second defect feature includes defect radial length information, defect radial shape information, and defect radial boundary information; The first defect feature and the second defect feature are compared with the preset feature to obtain defect type information.

6. A mold steel internal defect accurate identification and detection system, characterized in that: include: A first acquisition module is used to acquire multiple probe path lines of a mold steel detection surface, wherein the mold steel detection surface includes an axial detection surface and a radial detection surface, and each of the probe path lines is used for mobile detection by an ultrasonic probe; A second acquisition module is used to acquire echo signals of multiple detection points of each probe on each probe path line, and acquire echo enrichment area information according to the echo signal of each detection point; A third acquisition module is used to acquire two-dimensional defect pattern information and defect pattern depth information corresponding to the echo signal of each detection point according to the echo enrichment area information; A fourth acquisition module, used to generate a two-dimensional defect scanning image according to the two-dimensional defect graphic information corresponding to the echo signal of each detection point, wherein the defect scanning image includes a two-dimensional defect axial image and a two-dimensional defect radial image; A fifth acquisition module, used to generate a three-dimensional image according to the two-dimensional defect axial image and the two-dimensional defect radial image corresponding to all probe path lines and the defect pattern depth information, and to acquire defect shape information and defect position information according to the three-dimensional image; a sixth acquisition module, configured to acquire defect type information according to the two-dimensional defect axial image and the two-dimensional defect radial image, and generate defect state information of the mold steel according to the defect type information, defect shape information and defect position information; Wherein, the second acquisition module includes: A first acquisition unit, used for acquiring all equidistant detection points on each probe path line; A second acquisition unit, used for acquiring an initial pulse wave of the probe at each of the detection points; A third acquisition unit, configured to acquire a plurality of detection point echo signals at each of the detection points based on the initial pulse wave, wherein each of the detection point echo signals includes an echo time and an echo amplitude; a fourth acquisition unit, configured to establish a two-dimensional echo signal schematic diagram for each of the detection points according to a plurality of echo times and echo amplitudes; A fifth acquisition unit, used for acquiring an echo amplitude change value of each echo signal according to the echo signal schematic diagram; a sixth acquisition unit, configured to acquire an amplitude threshold interval, and determine whether the echo amplitude change value of each of the echo signals is within the amplitude threshold interval; If it is located, then all echo signals within the amplitude threshold interval are acquired, and the echo signals within the amplitude threshold interval are used as the first marked echo signals; a seventh acquisition unit, configured to acquire an echo time variation value of each echo signal according to the echo signal schematic diagram; an eighth acquisition unit, configured to acquire a delay rate of each echo signal according to the echo time variation value; a ninth acquisition unit, configured to acquire a time delay threshold interval, and determine whether the delay rate of each of the echo signals is within the time delay threshold interval; If it is, then all echo signals within the time delay threshold interval are acquired, and the echo signals within the time delay threshold interval are used as second marked echo signals; a tenth acquisition unit, configured to compare all first marker echo signals with all second marker echo signals, and use the signals that match the first marker echo signals and the second marker echo signals as third marker signals; The eleventh acquisition unit is used to acquire all third marker signals and use all third marker signals as echo enrichment area information.

7. The mold steel internal defect accurate identification and detection system according to claim 6 is characterized in that: The third acquisition module includes: a twelfth obtaining unit, configured to obtain the number of all third marker signals in the echo enrichment region information, and use the number as the enriched echo number; A thirteenth acquisition unit is used to acquire the echo amplitude of each third marker signal in the echo enrichment area information, and use it as the enriched echo amplitude; a fourteenth acquisition unit, configured to acquire an echo time variation value of each third marker signal in the echo enrichment area information, and acquire an arrival distance variation value of the echo of each third marker signal according to the delay rate; A fifteenth acquisition unit is used to map the arrival distance change value as the abscissa and the enriched echo amplitude as the ordinate to a two-dimensional coordinate system to generate data points; A sixteenth acquisition unit is used to acquire all data points mapped by the number of enriched echoes on each probe path line, and link all data points to obtain two-dimensional defect graphic information; a seventeenth acquisition unit, configured to acquire the echo velocity and echo time of all third marker signals in the echo enrichment region information; An eighteenth acquisition unit, used to obtain defect depth information according to the echo velocity and the echo time; The nineteenth acquisition unit is used to acquire the defect depth information of all third marking signals to obtain defect pattern depth information.

8. The mold steel internal defect accurate identification and detection system according to claim 6, characterized in that: The fourth acquisition module includes: a twentieth acquisition unit, configured to acquire all probe path lines on the axial detection surface and use them as a first path line set; A twenty-first acquisition unit, configured to acquire two-dimensional defect pattern information of all probe path lines in the first path line set, and use the two-dimensional defect pattern information as the first defect pattern; A twenty-second acquisition unit is used to splice and integrate all the first defect patterns to obtain a two-dimensional defect axial image; A twenty-third acquisition unit, configured to acquire all probe path lines on the radial detection surface and use them as a second path line set; A twenty-fourth acquisition unit, used to acquire two-dimensional defect pattern information of all probe path lines in the second path line set, and use it as the second defect pattern; A twenty-fifth acquisition unit is used to splice and integrate all the second defect patterns to obtain a two-dimensional defect radial image; The twenty-sixth acquisition unit is used to collect the two-dimensional defect axial image on the axial detection surface and the two-dimensional defect radial image on the radial detection surface to obtain a two-dimensional defect scanning image.

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