Ultrasonic TOFD data processing and SAFT imaging integrated application method

Abstract

The invention provides an ultrasonic TOFD data processing and SAFT imaging integrated application method based on MATLAB (matrix laboratory). The method comprises the following steps: carrying out data extraction and conversion processing on ultrasonic time of flight diffraction (TOFD) flaw detection data of a to-be-tested block to obtain a three-dimensional imaging data matrix, a scanning single-point diagram and a scanning grey-scale map; traversing data points near each imaging point in the three-dimensional imaging data matrix, outputting an SAFT imaging picture, and determining defect point range information in the to-be-tested block; and performing elliptical imaging on data points in a certain range in the three-dimensional imaging data matrix, acquiring echo signals of upper and lower end points of the defect in the elliptical imaging according to a scanning single-point diagram, and searching an optimal defect point position by respectively utilizing an averaging method, a Gaussian probability distribution method and an optimization algorithm for Euclidean distance. According to the method, TOFD and SAFT imaging can be combined, integration of data processing and imaging is achieved, a user can complete all related operations on one platform, and the requirements for rapid defect detection and imaging are met.

Description

Technical Field

[0001] The present invention relates to the field of ultrasonic testing technology, and in particular to an integrated application method of ultrasonic TOFD (Time of Flight Diffraction) data processing and SAFT (Synthetic Aperture Focusing Technique) imaging. Background Art

[0002] Ultrasonic testing technology is an important means of non-destructive testing of materials and structures, and is widely used in aerospace, automobile manufacturing, nuclear power, petrochemical and other fields. The main advantage of this technology is that it can accurately evaluate its internal defects and integrity without damaging the material and structure. With the continuous advancement of industrial technology, the accuracy and reliability of ultrasonic testing technology are increasingly valued, especially in fields with extremely high safety requirements.

[0003] The core of ultrasonic testing technology is to use the propagation characteristics of ultrasonic waves to detect defects inside materials. When ultrasonic waves pass through materials, any tiny defects (such as cracks, pores, inclusions, etc.) will cause the sound waves to be reflected or attenuated, and thus captured by the detection equipment. In order to improve the sensitivity and accuracy of defect detection, researchers have proposed a variety of ultrasonic scanning and imaging technologies, and TOFD and SAFT are two important methods.

[0004] The TOFD method uses two broadband narrow pulse probes, one transmitting and one receiving, for detection. The probes are arranged symmetrically with respect to the center line of the weld. The transmitting probe generates a non-focused longitudinal wave beam that is incident on the workpiece at a certain angle, of which part of the beam propagates along the near surface and is received by the receiving probe, and part of the beam is received by the probe after being reflected by the bottom surface. The receiving probe determines the position and height of the defect by receiving the diffraction signal at the tip of the defect and its time difference.

[0005] The SAFT method is developed from synthetic aperture radar and uses a small aperture single-element transducer to achieve high-resolution imaging. SAFT is an imaging technology based on multi-channel signal processing that generates high-quality images by synthesizing ultrasonic signals at different locations. SAFT technology can improve the signal-to-noise ratio of imaging, overcome many limitations of traditional ultrasonic imaging, and adapt it to defect detection of complex geometries.

[0006] Although TOFD and SAFT methods have important application value in the field of ultrasonic testing, their combination in teaching and practical application is still insufficient. At present, there is still a lack of corresponding comprehensive software tools, which limits their popularization and application effect.

[0007] In the practical application of ultrasonic testing, software such as MATLAB is widely used in signal processing and data analysis. MATLAB has become an important tool for researchers and engineers to perform signal processing due to its powerful computing power and rich toolboxes. However, the current application of MATLAB toolboxes has shortcomings in the following aspects.

[0008] Dependence on a specific software environment: MATLAB programs usually require to be run in a specific MATLAB environment, which places high demands on the user's programming skills, especially for non-professional users and users with no programming experience.

[0009] At present, the disadvantages of the ultrasonic detection method in the prior art include:

[0010] 1. Lack of data processing software combining TOFD and SAFT imaging:

[0011] Disadvantages: In the field of teaching, there is currently almost no data processing software that combines TOFD and SAFT technologies. This limits students and researchers' comprehensive understanding and application of these two important technologies, resulting in a lack of necessary tool support when conducting ultrasonic testing.

[0012] 2. Environmental limitations of traditional MATLAB programs:

[0013] Disadvantages: The existing MATLAB program relies on a specific software environment and requires users to have certain programming skills. This creates a high threshold for many non-professional users, making it difficult for them to process data smoothly. At the same time, during the imaging calculation process, the modification of internal parameters is relatively complicated, which is not convenient for users to flexibly adjust according to specific circumstances, affecting the user experience.

[0014] 3. Insufficient functional integration:

[0015] Disadvantages: Current solutions often separate data processing and imaging functions and lack integrated tools. This requires users to use multiple different software tools to operate, increasing work complexity and learning costs, and reducing work efficiency.

[0016] 4. SAFT imaging algorithm is inefficient:

[0017] Disadvantages: Traditional SAFT imaging algorithms are inefficient and slow, take a long time to process, and cannot meet the needs of rapid defect detection. This is particularly important in practical applications, especially in scenarios that require timely feedback and quick decision-making. Summary of the invention

[0018] The present invention provides an integrated application method of ultrasonic TOFD data processing and SAFT imaging, so as to realize the combination of TOFD and SAFT imaging and enhance the understanding and application ability of ultrasonic detection technology.

[0019] In order to achieve the above object, the present invention adopts the following technical scheme.

[0020] An integrated application method of ultrasonic TOFD data processing and SAFT imaging, comprising:

[0021] Extract and convert the ultrasonic diffraction TOFD flaw detection data of the test block to obtain a three-dimensional imaging data matrix, a scanning single point image and a scanning grayscale image;

[0022] Traversing the data points near each imaging point in the three-dimensional imaging data matrix, according to the law that the imaging points move from left to right, the range of the data points will also move from left to right, outputting a synthetic aperture focusing technology SAFT imaging image, comparing the scanning grayscale image with SAFT imaging images of different imaging ranges, and determining the defect point range information in the block to be tested according to the comparison result;

[0023] The scanning mapping method is used to perform elliptical imaging on the data points within a certain range in the three-dimensional imaging data matrix, and the echo signals of the upper and lower endpoints of the defect in the elliptical imaging are obtained according to the scanning single point diagram. The averaging method, Gaussian probability distribution method and Euclidean distance optimization algorithm are used to find the optimal defect point position in the test block.

[0024] Preferably, the data extraction and conversion processing of the ultrasonic diffraction time-of-flight TOFD flaw detection data of the block to be tested to obtain a three-dimensional imaging data matrix, a scanning single point image and a scanning grayscale image includes:

[0025] Read the data points in the TOFD flaw detection data of the test block, extract and save the parameter values ​​of each data point, which include delay, range, resolution, compression ratio, attenuation and wave number. For a set of TOFD flaw detection data read, determine the position of the first data point according to the delay, and determine the time corresponding to each data point according to the resolution to obtain a two-dimensional slice of the imaging data matrix. Perform the above operation on each set of TOFD flaw detection data, and then arrange them from small to large according to the wave number to obtain a three-dimensional imaging data matrix wave_data_t;

[0026] A certain slice of the three-dimensional imaging data matrix is ​​taken out to draw a scanning single point diagram, where the x-axis coordinate is time and the y-axis coordinate is amplitude. The amplitude data in the three-dimensional imaging data matrix wave_data_t is used to draw a grayscale diagram, where the maximum sound pressure value is normalized to 1 and assigned the highest grayscale.

[0027] Preferably, the data points near each imaging point in the three-dimensional imaging data matrix are traversed, and according to the law that the imaging points move from left to right, the range of the data points will also move from left to right, and the synthetic aperture focusing technology SAFT imaging diagram is output, including:

[0028] For the point to be imaged in the space of the block to be tested, determine how many groups of two-dimensional slice data of the three-dimensional imaging data matrix are used to image the point, that is, determine the single-point imaging range. For each group of data in the single-point imaging range, recalculate the Euclidean distance between the point and the two probes each time, calculate the propagation time based on the distance value and the speed of sound, traverse the time of the data points near the propagation time, and according to the rule of moving from left to right when calculating the imaging point, after obtaining a group of data corresponding to the amplitude of the point, repeat the operation until all data groups in the single-point imaging range are traversed, and average all amplitudes, which is the SAFT imaging value of the point in the current single-point imaging range. After performing this operation on all points in the imaging area, the SAFT imaging diagram in the current single-point imaging range is obtained.

[0029] Preferably, the scanning mapping method is used to perform elliptical imaging on data points within a certain range in the three-dimensional imaging data matrix, and echo signals of the upper and lower endpoints of the defect in the elliptical imaging are obtained according to the scanning single point diagram, and the averaging method, Gaussian probability distribution method and optimization algorithm for Euclidean distance are used to find the optimal defect point position in the block to be tested, including:

[0030] Use the scanning mapping method to perform elliptical imaging on the data points within a certain range in the three-dimensional imaging data matrix, obtain the time of the echo signal of the upper and lower endpoints of the defect in the elliptical imaging according to the scanning single point diagram, and calculate the sum of the Euclidean distances from the point to the two transmitting and receiving probes according to the time and the sound speed. After running all the data groups, obtain the matrix of the sum of the Euclidean distances from the upper and lower endpoints to the two transmitting and receiving probes, take the positions of the two transmitting and receiving probes as the focus of the ellipse, take the sum of the Euclidean distances of the upper and lower endpoints as twice the axis length of the ellipse, draw a series of ellipses with different foci and axis lengths, and find and record the intersection of each ellipse with other ellipses;

[0031] 4. According to the coordinates of the intersection of each ellipse with other ellipses, take the average values ​​of the horizontal and vertical coordinates respectively, and use the obtained x and y average values ​​as the optimal defect point position;

[0032] 5. Take the intersection of each ellipse and other ellipses as the center and use Gaussian probability distribution to calculate the intersection with the maximum probability distribution value superposition, and use the intersection as the optimal defect point position;

[0033] 6. Use the intersection of each ellipse and other ellipses to calculate the Euclidean distance, obtain the intersection corresponding to the minimum Euclidean distance, and use the intersection as the optimal defect point location.

[0034] It can be seen from the technical solutions provided by the above-mentioned embodiments of the present invention that the method of the present invention can combine TOFD with SAFT imaging, improve the understanding and application capabilities of ultrasonic detection technology, and reduce the requirements for personal programming capabilities of users by designing an application independent of the MATLAB environment, so that non-professional users or users with no programming experience can also easily use the software for data processing and imaging, thereby improving the user's operational convenience and lowering the threshold for using ultrasonic software.

[0035] Additional aspects and advantages of the present invention will be given in part in the following description, which will become obvious from the following description, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0037] Figure 1 A TOFD flaw detection principle provided by an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of measuring defect height using a multi-point mapping method provided by an embodiment of the present invention;

[0039] Figure 3 A basic principle diagram of synthetic aperture focusing provided by an embodiment of the present invention;

[0040] Figure 4 A processing flow chart of an integrated application method of ultrasonic TOFD data processing and SAFT imaging based on MATLAB provided in an embodiment of the present invention;

[0041] Figure 5 A schematic diagram of a TOFD software interface provided by an embodiment of the present invention;

[0042] Figure 6 A schematic diagram of a SAFT software interface provided by an embodiment of the present invention;

[0043] Figure 7 A schematic diagram of a TOFD spectrum diagram and a SAFT imaging comparison diagram (the red line is the -6DB limit) provided in an embodiment of the present invention.

[0044] Figure 8 A schematic diagram of a scanning mapping software interface provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0046] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or coupling. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0047] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0048] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0049] The TOFD method provided by the embodiment of the present invention has the following flaw detection principle: Figure 1As shown, the processing process includes: when the ultrasonic detection test block has a crack defect of a certain height, diffraction occurs at the end point of the defect. TOFD uses the diffraction waves generated by the sound beam at the two ends or end angles of the crack to locate and quantify the defect. The transmitting probe and the receiving probe are placed symmetrically on both sides of the defect. When the ultrasonic beam propagates from a high-impedance medium to a low-impedance medium. The phase of the beam changes after reflection at the interface. If the beam is a negative period before encountering the interface, it will change to a positive period after reflection at the interface. When the beam passes through the upper end point and the bottom surface, the reflection and phase change at the heterogeneous interface, so the waveform phase is similar. When the beam passes through the lower end point, it is equivalent to the beam circling the bottom of the defect, and the phase does not change, which is similar to the phase of the straight wave.

[0050] According to theoretical and experimental proof, if the phases of two diffraction signals are opposite, there must be a continuous defect between the two signals. Therefore, identifying phase changes is very important for evaluating defect size. Using the time difference between the upper and lower endpoints to calculate the defect height is the most important part of TOFD flaw detection.

[0051] Measure the echo time t1 and t2 of the upper and lower endpoints of the defect respectively, and use the formula

[0052]

[0053] Calculate the depth of the upper and lower endpoints and thus obtain the defect height.

[0054] The principle of scanning mapping method is: according to the definition of ellipse: if the sum of the distances from a point to two fixed points is a constant value, then the point must be located on the ellipse with the two fixed points as the focus. The relative positions of the two probes are fixed, and the sum of the distances from the defect point to the two probe incident points is a constant value, then the defect point must be located on the ellipse with the two probe incident points as the focus. Change the position of the probe, and obtain another ellipse equation where the defect point is located based on the sum of the new focal radii. The intersection of the two ellipses is the defect point.

[0055] The TOFD scanning measurement is performed point by point with two probes. The obtained data can be used to make the points where the ellipses intersect each other using the application. By using two methods, direct averaging calculation and Gaussian curve drawing, the upper and lower endpoints of the defect can be found. Figure 2 A schematic diagram of measuring defect height using a multi-point mapping method provided in an embodiment of the present invention.

[0056] The basic principle of a synthetic aperture focusing provided by an embodiment of the present invention is as follows: Figure 3As shown in the figure, the processing process includes: when an ultrasonic transceiver and transmitter probe moves along a straight line, a sound wave is emitted every distance d, and scattered signals from various points of the object are received and stored. According to the spatial position of each imaging point, the received signal is appropriately delayed or phase-delayed, and then synthesized to obtain a point-by-point focused sound image of the imaged object, which is the synthetic aperture imaging technology.

[0057] From the perspective of emission, when a probe moves to the i-th point, the sound field formed by the sound waves it emits at the previous series of points is equivalent to the sound field radiated by the delayed radiation of the array elements of the linear array. In this way, a single probe, in conjunction with its motion drive system and signal storage system, is combined into a large-scale transducer array. From the perspective of reception, if you want to obtain the imaging signal of point A in the object, you only need to add the signal amplitudes at the time when the sound propagates back and forth from point A to each measuring point in the signal obtained by the probe at each detection point. This is equivalent to treating point A as a focal point. Since any detection point in the object can be treated as a focus using the program, this gives synthetic aperture imaging a high resolution.

[0058] The processing flow chart of an integrated application method of ultrasonic TOFD data processing and SAFT imaging provided by an embodiment of the present invention is as follows: Figure 4 As shown, the process includes the following steps:

[0059] Step S10: extracting and converting the ultrasonic flaw detection data to obtain a three-dimensional imaging data matrix, a scanning single point image and a scanning grayscale image.

[0060] Figure 5 A schematic diagram of a TOFD software interface provided by an embodiment of the present invention. First, in the initial interface, Figure 5 The program extracts and processes the .dat data into a matrix format that can be used for matlab drawing and subsequent processing. For the read data, each group of data consists of 806 values, of which the first 800 values ​​are the data values ​​measured and saved by the flaw detector, and the last six values ​​are the six parameter values ​​of the group of data, which are:

[0061] 1. Delay, that is, the difference between the time corresponding to the first data point in this group of data and the time zero.

[0062] 2. Range, that is, the difference between the theoretical maximum and minimum values ​​of this group of data.

[0063] 3. Resolution, that is, the time interval between each data point in this set of data.

[0064] 4. Compression ratio, that is, the ratio of the sound pressure value displayed on the screen to the actual sound pressure value.

[0065] 5. Attenuation, that is, the attenuation value set by the instrument when measuring this set of data.

[0066] 6. Wave number, that is, the order of the data in the dat file. For a set of data read, determine the position of the first point according to the delay, determine the time corresponding to each point according to the resolution, save the time and amplitude of these 800 data points respectively, and you can get a 800*2 two-dimensional slice of the imaging data matrix. Perform this operation on each set of data, and then arrange them from small to large according to the wave number, and you can get a complete three-dimensional imaging data matrix, recorded as wave_data_t.

[0067] When drawing a single-point scan graph, only a certain slice of the three-dimensional imaging data matrix is ​​taken out for display. When drawing, the x-axis coordinate is time and the y-axis coordinate is amplitude. Since this ultrasound imaging method does not focus on the actual value of the sound pressure, but focuses more on the relative value of the sound pressure, the amplitude of the y-axis is normalized when displayed.

[0068] When drawing the scanning grayscale image, for the amplitude data in the three-dimensional imaging data matrix wave_data_t, the maximum sound pressure value is normalized to 1 and assigned the highest grayscale. The minimum sound pressure value is normalized to -1 and assigned the lowest grayscale. When displayed, the x-axis horizontal coordinate is time, the y-axis vertical coordinate is wave number, and the grayscale is used to represent the amplitude of each point.

[0069] As an initialization data processing module, the main function of this module is to obtain a complete three-dimensional imaging data matrix wave_data_t based on the calculation and processing of the initial data. At the same time, the module outputs two graphic displays, namely the scanning single point diagram and the scanning grayscale diagram. The scanning single point diagram can be used to show the relative time relationship between the through wave and the defect echo signal received at different transmitting and receiving probe positions, and can then be used to plan the point range of the scanning image method in step S30. The scanning grayscale diagram is a wave number superposition of all the scanning single point diagrams obtained in one experiment, which can be considered as a basic diagram that has not been processed by SAFT imaging, and can then be used to compare with the SAFT imaging diagrams of different imaging ranges in step S20.

[0070] Step S20: traverse the data points near each imaging point in the three-dimensional imaging data matrix, and according to the law that the imaging points move from left to right, the range of the data points will also move from left to right, and output the SAFT imaging image.

[0071] Figure 6 A schematic diagram of a SAFT software interface provided by an embodiment of the present invention. After the initial drawing display is completed on the initial interface, you can click Figure 5The SAFT button in the apptofd interface will pass the processed 3D imaging data matrix wave_data_t to the newly opened appsaft interface, such as Figure 6 As shown in the figure, this group of data will be used for SAFT imaging. During imaging, for the point to be imaged in the test block space, it is first necessary to determine how many groups of two-dimensional slice data of the three-dimensional imaging data matrix are used to image the point, that is, to determine the single-point imaging range. After the range is determined, for each group of data in the single-point imaging range, since the SAFT scanning imaging method is used during flaw detection, the positions of the transmitting and receiving probes of each group of data are different, so for each group of data, the Euclidean distance between the point and the two probes needs to be recalculated each time, and the propagation time can be calculated based on the distance value and sound velocity.

[0072] The following steps are to find the corresponding amplitude based on the propagation time. However, since the propagation time is often not the same as any of the 800 data points, we can only find the closest approximate time and the amplitude corresponding to that time, which is considered to be the amplitude value of the imaging point.

[0073] In previous methods, it is often necessary to traverse the time of 800 data points in a set of data, and then find the point closest to the propagation time, which requires a lot of calculation time. The present invention only traverses the time of data points near the propagation time. According to the law of moving from left to right when calculating the imaging point, the propagation time will change from short to long and then short, so the time value range of the data point will also change according to this rule to ensure that the appropriate corresponding time point can be found, which greatly reduces the number of cyclic judgments and does not affect the imaging effect.

[0074] After obtaining a set of data corresponding to the amplitude of the point, it is necessary to repeat this operation until all data groups in the single-point imaging range are traversed, and finally all amplitudes are averaged, which is the SAFT imaging value of the point in the current single-point imaging range. After performing this operation on all points in the imaging area, the SAFT imaging map in the current single-point imaging range can be obtained. From the SAFT imaging map, two groups of upper and lower peak areas can be observed. For the two points with the highest grayscale values ​​in the two groups of peaks in the SAFT imaging map, these two points can be approximately considered to be the upper and lower edges of the defect, thereby determining the relative positions of the upper and lower edges of the defect.

[0075] Comparing the scanning grayscale image obtained in step S10 with the SAFT imaging images of different imaging ranges, the scanning grayscale image can be considered as a SAFT imaging image with an imaging range of 0, in which the upper and lower defect points do not have a focusing effect, so there are no obvious two groups of peaks in the image. In the SAFT imaging image, Figure 4The middle rectangular red frame indicates the attenuation range of 6dB. By adjusting the single-point imaging range, it can be observed that as the single-point imaging range increases, the length of the rectangular red frame gradually decreases, indicating that the peak of the imaging gradually concentrates, that is, the upper and lower edges of the defect are determined more accurately. However, it should be noted that increasing the single-point imaging range will increase the calculation time, so it takes longer to obtain an image.

[0076] Figure 7 A schematic diagram of a TOFD spectrum diagram and a SAFT imaging comparison diagram (the red line is the -6DB limit) provided by an embodiment of the present invention. Since the effect of the SAFT imaging diagram is related to the single-point imaging range, the SAFT imaging effect will be improved by increasing the single-point imaging range.

[0077] Step S30: Figure 8 A schematic diagram of a scanning drawing method software interface provided by an embodiment of the present invention. After the initial drawing display is completed on the initial interface, the scanning image method function is used, such as Figure 8 As shown in the figure, the data points within a certain range of the three-dimensional imaging data matrix processed by the apptofd interface are used to draw an ellipse for imaging. In addition to using the general averaging method to find the optimal defect point location, the Gaussian probability distribution and the optimization algorithm for the Euclidean distance are innovatively used to find the optimal defect point location. The output data is the defect point location map and coordinate information obtained by three different methods.

[0078] After completing the scanning of single point image and grayscale image on the initial interface, you can use the scanning image method function, such as Figure 7 Using the 3D imaging data matrix processed by the apptofd interface, the scanning single-point diagram was first redrawn on the left because the scanning single-point diagram can be used to show the relative time relationship between the through wave and the defect echo signal received at different transmitting and receiving probe positions. Two groups of obvious peaks can be observed from the scanning single-point diagram. Theoretical analysis shows that these two groups of waveforms are the echo signals of the upper and lower endpoints of the defect received by the receiving probe.

[0079] First, you need to manually select a suitable automatic reading range, which can be determined by displaying the scanned single-point diagram in the left column. Use the up and down keys on the keyboard to change the size of the scanned single-point diagram to be viewed, and use the left and right keys to change the selected range point. After selecting the "starting position", you can switch to the "end position" and repeat the above operation to select the end position. By specifying the automatic reading range, the program will automatically find the time corresponding to the two maximum values ​​in the range, that is, the time of the echo signal received at the upper and lower endpoints of the defect, and calculate the sum of the Euclidean distances from the point to the two transceiver probes based on the time and sound speed. After running all the data groups, a matrix of the sum of the Euclidean distances from the upper and lower endpoints to the two transceiver probes can be obtained. Using this matrix, by taking the positions of the two transceiver probes as the focus of the ellipse and the sum of the Euclidean distances of the upper and lower endpoints as twice the axis length of the ellipse, a series of ellipses with different focuses and axis lengths can be drawn, and the intersection of each ellipse with other ellipses can be found and recorded for subsequent imaging and finding the location of the defect point.

[0080] Note that since the defect is strip-shaped during flaw detection, this method is actually used to obtain the coordinates of the top and bottom points of the defect. The following method takes the calculation of the top defect position as an example, and the calculation method for the bottom defect position is the same.

[0081] 1: The first imaging method is to use the general method of averaging the intersection coordinates to find the optimal defect point location, such as Figure 7 The first picture in the middle column shows the locations of two defect points in green circles, and the output coordinate data is in the first column on the right. The process of finding the optimal defect point by averaging method: according to the coordinates of the intersection of each ellipse with other ellipses, the horizontal and vertical coordinates are averaged respectively, and the obtained x and y average values ​​are used as the most likely defect point location. This is the method of direct averaging algorithm. The defect point location obtained by this method is marked on the two-dimensional graph of the ellipse and its intersection by circling the point with a green circle and displaying the coordinates of the point in the first column on the right.

[0082] 2: The second method is to use Gaussian probability distribution with each intersection as the center and calculate the point where the probability distribution value overlaps the largest, such as Figure 8 The second picture in the middle column, Figure 8 The two peaks are the defect point locations, and the output coordinate data is in the second column on the right. The process of finding the optimal defect point location through Gaussian distribution: use Gaussian probability distribution to calculate with each intersection as the center, the formula is as follows, where hi = 2, ai = 0.25, bi = 0.25

[0083]

[0084] The space is discretized at intervals of 0.01. By calculating the probability value in each grid point, the point with the largest probability distribution value superposition can be obtained. This grid point is approximately considered to be the defect point. The distribution diagram of the probability value in the grid point is drawn in the second figure. The point with a larger probability value has a higher corresponding height. Figure 8 The locations of the two defect points can be clearly observed. The coordinates of the points are shown in the second column on the right.

[0085] 3: At the same time, the Euclidean distance is calculated for each intersection, and the method of finding the minimum Euclidean distance through the optimization algorithm is used to find the optimal defect point location. This method does not draw a graph, and only outputs data in the third column on the right. The process of finding the optimal defect point location through the Euclidean distance optimization algorithm: Assume that there is a point (x0, y0) in space, calculate the Euclidean distance between the point and the coordinates of other intersection points in space, and sum up all the distances to get the total distance. The purpose of optimization is to minimize the total distance by changing the coordinates of the point (x0, y0). By using the Red-tailed Hawk optimization algorithm, a set of coordinates of the point (x0, y0) that minimizes the total distance can be obtained quickly (about 1s) with a small number of cycles (20 times). The coordinates of this point are approximately considered to be the defect point location, and the coordinates of this point are displayed in the third column on the right.

[0086] The output data of this step is the defect point location map obtained by three different methods.

[0087] In summary, the method of the present invention can combine TOFD with SAFT imaging, improve the understanding and application ability of ultrasonic testing technology, and reduce the requirements for personal programming ability of users by designing an application independent of the MATLAB environment, so that non-professional users or users with no programming experience can also easily use the software for data processing and imaging, thereby improving the user's operating convenience and lowering the threshold for using ultrasonic software.

[0088] The present invention is committed to integrating multiple functions and realizing the integration of data processing and imaging, so that users can complete all related operations on one platform. At the same time, scanning mapping imaging method is added on the basis of TOFD, which can be compared with SAFT imaging, reduce the complexity brought by the use of multiple software, and improve user work efficiency.

[0089] The present invention improves the efficiency of imaging by optimizing the SAFT imaging algorithm to meet the needs of rapid defect detection and imaging in teaching, thereby enhancing the effectiveness and breadth of ultrasonic testing in actual teaching applications.

[0090] By achieving the above objectives, the present invention strives to provide users with an efficient, convenient and comprehensive ultrasonic data processing solution, and promote the development of ultrasonic detection technology in teaching and practical applications.

[0091] Those skilled in the art can understand that the accompanying drawings are only schematic diagrams of an embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0092] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention or certain parts of the embodiments.

[0093] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0094] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An integrated application method of ultrasonic TOFD data processing and SAFT imaging, characterized in that: include: Extract and convert the ultrasonic diffraction TOFD flaw detection data of the test block to obtain a three-dimensional imaging data matrix, a scanning single point image and a scanning grayscale image; Traversing the data points near each imaging point in the three-dimensional imaging data matrix, according to the law that the imaging points move from left to right, the range of the data points will also move from left to right, outputting a synthetic aperture focusing technology SAFT imaging image, comparing the scanning grayscale image with SAFT imaging images of different imaging ranges, and determining the defect point range information in the block to be tested according to the comparison result; The scanning mapping method is used to perform elliptical imaging on the data points within a certain range in the three-dimensional imaging data matrix, and the echo signals of the upper and lower endpoints of the defect in the elliptical imaging are obtained according to the scanning single point diagram. The averaging method, Gaussian probability distribution method and Euclidean distance optimization algorithm are used to find the optimal defect point position in the test block.

2. The method according to claim 1, characterized in that: The method of extracting and converting the ultrasonic diffraction time-of-flight TOFD flaw detection data of the block to be tested to obtain a three-dimensional imaging data matrix, a scanning single point image and a scanning grayscale image includes: Read the data points in the TOFD flaw detection data of the test block, extract and save the parameter values ​​of each data point, which include delay, range, resolution, compression ratio, attenuation and wave number. For a set of TOFD flaw detection data read, determine the position of the first data point according to the delay, and determine the time corresponding to each data point according to the resolution to obtain a two-dimensional slice of the imaging data matrix. Perform the above operation on each set of TOFD flaw detection data, and then arrange them from small to large according to the wave number to obtain a three-dimensional imaging data matrix wave_data_t; A certain slice of the three-dimensional imaging data matrix is ​​taken out to draw a scanning single point diagram, where the x-axis coordinate is time and the y-axis coordinate is amplitude. The amplitude data in the three-dimensional imaging data matrix wave_data_t is used to draw a grayscale diagram, where the maximum sound pressure value is normalized to 1 and assigned the highest grayscale.

3. The method according to claim 2, characterized in that: The data points near each imaging point in the three-dimensional imaging data matrix are traversed, and according to the law that the imaging point moves from left to right, the range of the data points will also move from left to right, and the synthetic aperture focusing technology SAFT imaging diagram is output, including: For the point to be imaged in the space of the block to be tested, determine how many groups of two-dimensional slice data of the three-dimensional imaging data matrix are used to image the point, that is, determine the single-point imaging range. For each group of data in the single-point imaging range, recalculate the Euclidean distance between the point and the two probes each time, calculate the propagation time based on the distance value and the speed of sound, traverse the time of the data points near the propagation time, and according to the rule of moving from left to right when calculating the imaging point, after obtaining a group of data corresponding to the amplitude of the point, repeat the operation until all data groups in the single-point imaging range are traversed, and average all amplitudes, which is the SAFT imaging value of the point in the current single-point imaging range. After performing this operation on all points in the imaging area, the SAFT imaging diagram in the current single-point imaging range is obtained.

4. The method according to claim 2, characterized in that: The method of using the scanning mapping method to perform elliptical imaging on data points within a certain range in the three-dimensional imaging data matrix, obtaining echo signals of the upper and lower endpoints of the defect in the elliptical imaging according to the scanning single point diagram, and finding the optimal defect point position in the block to be tested by using the averaging method, the Gaussian probability distribution method and the optimization algorithm for the Euclidean distance respectively, includes: Use the scanning mapping method to perform elliptical imaging on the data points within a certain range in the three-dimensional imaging data matrix, obtain the time of the echo signal of the upper and lower endpoints of the defect in the elliptical imaging according to the scanning single point diagram, and calculate the sum of the Euclidean distances from the point to the two transmitting and receiving probes according to the time and the sound speed. After running all the data groups, obtain the matrix of the sum of the Euclidean distances from the upper and lower endpoints to the two transmitting and receiving probes, take the positions of the two transmitting and receiving probes as the focus of the ellipse, take the sum of the Euclidean distances of the upper and lower endpoints as twice the axis length of the ellipse, draw a series of ellipses with different foci and axis lengths, and find and record the intersection of each ellipse with other ellipses; 1. According to the coordinates of the intersection of each ellipse with other ellipses, take the average values ​​of the horizontal and vertical coordinates respectively, and use the obtained x and y average values ​​as the optimal defect point position; 2. Take the intersection of each ellipse and other ellipses as the center and use Gaussian probability distribution to calculate the intersection with the maximum probability distribution value superposition, and use the intersection as the optimal defect point position; 3. Use the intersection of each ellipse and other ellipses to calculate the Euclidean distance, obtain the intersection corresponding to the minimum Euclidean distance, and use the intersection as the optimal defect point location.

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