A method and device for calculating the defect detection rate of manual ultrasonic shear wave testing

Abstract

The present invention discloses a method and apparatus for calculating the defect detection rate of manual ultrasonic shear wave testing. The method comprises the following steps: S1: prefabricating a test plate containing defects and performing radiographic testing on the test plate to detect defect information; S2: plotting an amplitude-distance correction curve and calculating a threshold equivalent based on the implemented testing standard; S3: scanning with a manual shear wave detection probe to record defect information where the threshold value of the defect reaches 50% or more of the threshold equivalent; S4: combining the test results of steps S1 and S3, calculating model parameters α0 and α1 through logistic regression analysis; S5: polishing or height measurement of defects where the threshold value reaches 50% or more of the threshold equivalent to obtain defect height information, and calculating model parameters β0, β1, and σ0 through linear regression analysis; S6: finally, calculating the defect detection rate based on the obtained model parameters. This calculation method is more accurate and reliable, and is beneficial for evaluating the defect detection rate (POD) of ultrasonic shear wave testing of thin plates.

Description

Technical Field

[0001] The present invention relates to a method for calculating an ultrasonic detection defect rate, and in particular to a method for calculating a manual ultrasonic shear wave detection defect detection rate. Background Art

[0002] Whether buried defects can be detected is very important for structural safety assessment. At present, many researchers have studied the defect detection rate (POD) of non-destructive testing and drawn the defect detection rate (POD) curve. On the one hand, it can evaluate the reliability of the test results and then evaluate the reliability of the structure; on the other hand, it can evaluate the testing process and evaluate the quality of the testing process through the defect detection rate.

[0003] For non-destructive testing methods such as radiographic testing and magnetic particle testing, logistic regression analysis is usually used to calculate POD, as shown in formula (2):

[0004]

[0005] Where a is the defect size, and m and σ are parameters calculated by regression analysis.

[0006] Ultrasonic testing is widely used in quality control and safety testing of industrial equipment in aerospace, hydropower, and nuclear power plants due to its sensitivity to crack defects, lack of impact on the human body and the environment, and its low cost and convenience. The signal response amplitude model is often used to calculate the POD for ultrasonic testing defect detection rates, as shown in Equations (3) and (4):

[0007]

[0008]

[0009] Formula (3) expresses the relationship between signal amplitude and defect size, where β0, β1, σ0 and a th Calculated by regression analysis. In many studies, it is believed that the logarithm of the defect size and the logarithm of the signal response amplitude are in a linear relationship. A threshold is set. When the signal response amplitude exceeds the threshold, the defect can be detected. Figure 3 As shown. In the signal response amplitude model, a generally refers to the absolute height, relative height or area of ​​the defect. However, the following deficiencies exist in current research: (1) The defect detection rate should be related to both length and height. Using defect height or relative height alone to evaluate the defect detection rate is not accurate enough, especially in manual inspection. The scanning behavior of inspectors increases the uncertainty of the inspection process. Long defects are easily detected by the sound beam, while short defects are easily missed. (2) Although the area can reflect the length and height of the defect to a certain extent, experiments have shown that among the two-dimensional factors affecting the area (length × height), the influence of height on POD is much more sensitive than length.

[0010] Therefore, providing a method for accurately and reliably calculating the defect detection rate of manual ultrasonic shear wave detection is a technical problem to be solved by the present invention. Summary of the Invention

[0011] Currently, existing technologies lack an optimized calculation method for the defect detection rate of manual ultrasonic testing.

[0012] To solve the above technical problems, the present application discloses a method for calculating the defect detection rate of manual ultrasonic shear wave testing, comprising the following steps:

[0013] S1: Prefabricate a test plate with defects, perform radiographic inspection on the test plate with defects, and detect defect information;

[0014] S2: Draw an amplitude distance correction curve according to the detection standard implemented, and calculate the threshold equivalent;

[0015] S3: Scan with a manual shear wave detection probe and record defect information where the threshold of the defect reaches more than 50% of the threshold equivalent;

[0016] S4: combining the detection results of step S1 and step S3, calculating the model parameters α0 and α1 through logistic regression analysis;

[0017] S5: For defects whose threshold value reaches more than 50% of the threshold equivalent, polishing or height measurement is performed to obtain defect height information, and model parameters β0, β1, and σ0 are calculated through linear regression analysis;

[0018] S6: Finally, the defect detection rate is calculated based on the obtained model parameters. The calculation formula is as follows:

[0019]

[0020] Among them, l represents the defect length parameter, h represents the defect height parameter, and a th stands for threshold equivalent.

[0021] According to an embodiment of the present application, the defect information includes a buried defect position, a defect type, a defect height, a defect length, and a reflection amplitude.

[0022] According to an embodiment of the present application, step S2 specifically includes: measuring the parameters of the detection probe and drawing an amplitude distance correction curve before ultrasonic shear wave detection, and then producing an evaluation line, a quantitative line and a scrap line based on the amplitude distance correction curve, where the evaluation line represents the threshold equivalent.

[0023] According to the embodiment of the present application, step S3 specifically includes: the detection probe scanning mode adopts a zigzag scanning, the detection probe emits a pulse signal, when the sound beam hits or approaches the defect, the ultrasonic wave will be reflected back, and the reflection amplitude data is obtained; when the threshold value of the defect is judged to be more than 50% of the threshold equivalent, the defect information of the defect is recorded.

[0024] According to an embodiment of the present application, step S4 specifically includes: using the ray detection result of step S1 as a standard, and calculating the model parameters α0 and α1 through logistic regression analysis based on the recorded reflection amplitude results.

[0025] According to an embodiment of the present application, the entire process of step S4 collects more than 60 reflection amplitude data for calculation.

[0026] According to an embodiment of the present application, step S5 specifically includes: polishing all defects and measuring the defect height, or not polishing but measuring the height through an ultrasonic detection method to obtain the defect height; taking the natural logarithm of the reflected amplitude and defect height measured by the defect, and then performing linear regression analysis to obtain parameters β0, β1 and σ0.

[0027] According to an embodiment of the present application, the entire process of step S5 measures more than 30 pieces of defect height data for calculation.

[0028] Another aspect of the present application discloses an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for calculating the defect detection rate of manual ultrasonic shear wave detection as described above are implemented.

[0029] The present application also discloses a non-transitory computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method for calculating the defect detection rate of manual ultrasonic shear wave detection as described above are implemented.

[0030] The beneficial effects of the technical solution of the present invention compared with the prior art are:

[0031] 1. The calculation method of this application is based on the characteristics of manual ultrasonic detection, combined with the traditional logistic regression model and signal response amplitude model. The logistic regression model is used to calculate whether the defect is hit, and the signal response amplitude model is used to calculate whether the defect reflection amplitude meets the detection requirements. The method adopted in this application combines the advantages of traditional calculation models and improves the evaluation accuracy.

[0032] 2. For detection situations where defect length or defect height is used as a model parameter, the existing technology generally uses length or height alone to calculate the defect detection rate. Experiments have shown that such a detection method will overestimate the actual defect detection rate. The calculation model of this application can simultaneously consider the impact of defect length and defect height on the detection rate, significantly improving the evaluation accuracy.

[0033] 3. Regarding the use of defect area as a model parameter, tests have shown that among the two-dimensional factors affecting defect detection rate (area x height), height is much more sensitive than length. Existing methods that solely use area as a defect detection rate evaluation parameter place length and height at the same sensitivity level, failing to accurately assess defect detection rates. The proposed calculation method, which takes the natural logarithm of the defect amplitude and height, demonstrates greater accuracy than existing methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of a method for calculating the defect detection rate of manual ultrasonic shear wave testing in an embodiment of the present invention;

[0035] Figure 2 Schematic diagram of a detection probe search method according to an embodiment of the present invention;

[0036] Figure 3 is a linear relationship diagram between defect size, value and signal response amplitude in the prior art;

[0037] Figure 4 The figure is a comparison chart of the calculation results of the slag inclusion defect detection rate by the method of the present invention and the traditional method respectively;

[0038] Figure 5 The figure is a comparison chart of the calculation results of the crack defect detection rate by the method of the present invention and the traditional method respectively;

[0039] Figure 6 The figure is a comparison chart of the calculation results of the porosity defect detection rate by the method of the present invention and the traditional method;

[0040] Figure 7 The figure is a comparison chart of the calculation results of the incomplete penetration defect detection rate by the method of the present invention and the traditional method respectively;

[0041] Figure 8 The figure is a comparison chart of the calculation results of the detection rate of unfused defects by the method of the present invention and the traditional method respectively.

[0042] Description of reference numerals:

[0043] 1. Defective test panel, 2. Detection probe.

[0044] The arrow indicates the scanning direction of the detection probe. DETAILED DESCRIPTION

[0045] The present invention will be further described below in conjunction with the accompanying drawings and specific examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0046] according to Figure 1 As shown, the present invention discloses a method for calculating the defect detection rate of manual ultrasonic shear wave detection, which specifically includes the following steps:

[0047] S1: Prefabricate a test plate 1 containing defects, perform radiographic inspection on the test plate 1 containing defects, and detect defect information;

[0048] Specifically, a test unit is created by prefabricating a portion of defective test panels 1, eliminating the need for regular product and resulting in waste. These test panels contain defects such as pores, slag inclusions, lack of fusion, incomplete penetration, and cracks. Defect information includes the location, type, height, and length of the buried defects.

[0049] S2: Draw an amplitude distance correction curve according to the detection standard implemented, and calculate the threshold equivalent;

[0050] Specifically, in this embodiment, before ultrasonic shear wave testing, the parameters of the detection probe 2 are measured and an amplitude-distance calibration curve is plotted. Based on this amplitude-distance calibration curve, an evaluation line, a quantitative line, and a rejection line are generated. The evaluation line represents the threshold equivalent. These three lines are drawn according to NB / T47013-2015. Different standards have different lines, and some standards only require a single evaluation line.

[0051] S3: Manual shear wave detection probe 2 scans and records defect information when the threshold of the defect reaches more than 50% of the threshold equivalent;

[0052] Specifically, the test plate is scanned in a zigzag pattern according to the test process to be evaluated. The scanning direction is as follows, as quoted from the standard for ultrasonic testing of pressure equipment NB / T47013-2015: Figure 2 As shown in the figure, the scanning method follows the method used during the inspection process. The inspection probe 2 is located at different positions at different times. The inspection probe 2 emits a pulse signal. When the sound beam strikes or approaches a defect, the ultrasonic wave is reflected back, and amplitude data is obtained. When a defect is present, whether the scanning sound beam strikes or approaches the defect is a random event, and the height of the reflected amplitude is also random. The reflected amplitude data is the comparison value between the amplitude data and the evaluation line.

[0053] Furthermore, in this embodiment, step S3 detects defects, and when the threshold of the detected defect reaches more than 50% of the threshold equivalent, the defect information is recorded, including the reflection amplitude and the defect position.

[0054] S4: combining the detection results of step S1 and step S3, calculating the model parameters α0 and α1 through logistic regression analysis;

[0055] Specifically, the X-ray inspection results of step S1 are used as the standard, such as the detected defect location, defect type, and defect length, and the recorded reflection amplitude data are used to calculate the model parameters α0 and α1 through logistic regression analysis. The model parameters α0 and α1 are parameters obtained from the calculation model for defect detection rate calculation based on traditional non-destructive testing methods such as X-ray inspection and magnetic particle inspection. The calculation formula is as follows:

[0056]

[0057] Where a is the defect size, and α0 and α1 are coefficient parameters calculated by calculating the parameters m and σ in formula (2). In this embodiment, the defect size is selected as the defect length (l), and POD(a) is POD(l), which represents the probability of the sound beam hitting the defect. Figure 3 The figure shows the linear relationship between the logarithm of the instrument signal amplitude and the logarithm of the defect size. The dashed line is the threshold. When the signal exceeds the threshold, the defect will be detected. The proportion of the shaded area in the normal distribution image is the defect detection rate (POD).

[0058] Furthermore, the entire process of step S4 collects more than 60 detection data (including reflection amplitude) for calculation.

[0059] S5: For defects whose threshold value reaches more than 50% of the threshold equivalent, polishing or height measurement is performed to obtain defect height information, and model parameters β0, β1, and σ0 are calculated through linear regression analysis;

[0060] Specifically, all defects are polished and the defect height is measured, or the defect height is measured using ultrasonic testing without polishing. The natural logarithm of the measured reflection amplitude and defect height is taken, and then linear regression analysis is performed to obtain the parameters β0, β1, and σ0. The parameters β0, β1, and σ0 are derived from the signal response amplitude model commonly used for ultrasonic defect detection rate, and are calculated as follows:

[0061]

[0062]

[0063] Among them, formula (3) expresses the relationship between signal amplitude and defect size, where β0, β1, σ0 and a th Calculated by regression analysis, a threpresents the threshold equivalent; formula (4) represents the linear relationship between the logarithm of the defect size and the logarithm of the signal response amplitude.

[0064] Furthermore, the entire process of step S5 measures more than 30 pieces of defect height data for calculation.

[0065] S6: Finally, the defect detection rate is calculated based on the obtained model parameters. The calculation formula is as follows:

[0066]

[0067] Among them, l represents the defect length parameter, h represents the defect height parameter, and a th Represents the threshold equivalent. POD(l,h) represents the defect detection rate of the two-dimensional parameters of length and height.

[0068] This method combines two models of defect detection rate (POD) to calculate the POD of manual ultrasonic shear wave detection. Ultrasonic detection of defects requires two processes: (1) the sound beam hits or approaches the defect; (2) the reflected wave reaches a certain amplitude. The defect will only be identified when the sound beam hits the defect and the reflected wave amplitude is greater than a certain level. The difference between manual ultrasound and automatic ultrasound and phased array methods is that the probe scanning process requires manual operation. Irregular operation may cause the sound beam to move away from the defect, resulting in missed defect detection. This method combines the above two models based on the characteristics of manual ultrasonic detection, and calculates whether the defect is hit by formula (2), and calculates whether the defect reflection amplitude meets the detection requirements by formula (3). The present invention can simultaneously consider the influence of defect length and defect height on the detection rate, thereby improving the evaluation accuracy.

[0069] like Figures 4 to 8As shown, the traditional method and the method of the present invention are used to calculate the defects of slag inclusion, pores, cracks, incomplete penetration and incomplete fusion respectively, and the comparison results are shown in the figure. The traditional formula calculates the POD curve results of manual ultrasonic shear wave detection, and generally uses a one-dimensional parameter to calculate the defect detection rate (POD). Since the influence of height on POD is much more sensitive than length, this embodiment uses the height parameter. The test shows that if the defect detection rate is calculated by height alone, the actual defect detection rate will be overestimated. The method of the present application uses formula (1) to calculate the curve results of manual ultrasonic shear wave detection POD. This method uses length and height two-dimensional parameters to calculate POD, and considers the influence of defect length and defect height on the detection rate at the same time. Compared with the traditional method, it is much more accurate. The test shows that among the two-dimensional factors of area (length × height) that affect the defect detection rate, the influence of height on POD is much more sensitive than length. If the area is used as the defect detection rate evaluation parameter alone, the length and height are placed at the same sensitivity level, and the defect detection rate cannot be accurately evaluated. The calculation model of this application contains parameters of length and height, which are not at the same sensitivity level. The calculation results of POD are affected by length and height, and the degree of influence is inconsistent. Figures 4 to 8 As shown, the accuracy is higher than that of traditional methods. On the display screen of the ultrasonic testing instrument, Figures 4 to 8 They are all color graphs, with different colors representing the detection values, POD curves, detected defects and missed defects.

[0070] The present application also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for calculating the defect detection rate of manual ultrasonic shear wave detection are implemented as described above.

[0071] It is understood that the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0072] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the method for calculating the defect detection rate of manual ultrasonic shear wave detection provided by the above methods, and the method includes the following steps: S1: prefabricate a defective test plate 1, perform radiographic detection on the defective test plate 1, and detect defect information; S2: draw an amplitude distance correction curve according to the implemented detection standard, and calculate the threshold equivalent; S3: scan with a manual shear wave detection probe 2, and record the defect information whose threshold reaches more than 50% of the threshold equivalent; S4: combine the detection results of steps S1 and S3, and calculate the model parameters α0 and α1 through logistic regression analysis; S5: for defects whose threshold reaches more than 50% of the threshold equivalent, perform grinding or height measurement to obtain defect height information, and calculate the model parameters β0, β1, σ0 through linear regression analysis; S6: finally, calculate the defect detection rate based on the obtained model parameters.

[0073] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned methods for calculating the defect detection rate of manual ultrasonic shear wave detection.

[0074] In summary, the technical solution of this application has the following beneficial effects:

[0075] 1. The calculation method of this application is based on the characteristics of manual ultrasonic detection, combined with the traditional logistic regression model and signal response amplitude model. The logistic regression model is used to calculate whether the ultrasonic beam hits the defect or is close to the defect, and the signal response amplitude model is used to calculate whether the defect reflection amplitude meets the detection requirements. The method adopted in this application combines the advantages of traditional calculation models and improves the evaluation accuracy.

[0076] 2. For detection situations where defect length or defect height is used as a model parameter, the existing technology generally uses length or height alone to calculate the defect detection rate. Experiments have shown that such a detection method will overestimate the actual defect detection rate. The calculation model of this application can simultaneously consider the impact of defect length and defect height on the detection rate, significantly improving the evaluation accuracy.

[0077] 3. Regarding the use of defect area as a model parameter, tests have shown that among the two-dimensional factors affecting defect detection rate (area x height), height is much more sensitive than length. Existing methods that solely use area as a defect detection rate evaluation parameter place length and height at the same sensitivity level, failing to accurately assess defect detection rates. The proposed calculation method, which takes the natural logarithm of the defect amplitude and height, demonstrates greater accuracy than existing methods.

[0078] The above are only preferred embodiments of the present invention and do not limit the implementation mode and protection scope of the present invention. For those skilled in the art, it should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the description and illustrations of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for calculating the defect detection rate of manual ultrasonic shear wave testing, characterized in that: The following steps are involved: S1: Prefabricate a test plate containing defects, perform radiographic inspection on the test plate containing defects, and detect defect information; S2: Draw the amplitude distance correction curve according to the detection standard implemented, and calculate the threshold equivalent; S3: Scanning with a manual shear wave detection probe to record defect information when the threshold of the defect reaches more than 50% of the threshold equivalent; S4: Combining the test results of step S1 and step S3, the model parameters α0 and α1 are calculated by logistic regression analysis. The X-ray test results of step S1 are used as a standard, and the model parameters α0 and α1 are calculated by logistic regression analysis based on the recorded reflection amplitude data. The model parameters α0 and α1 are parameters obtained from a calculation model for defect detection rate calculation based on traditional non-destructive testing methods such as X-ray testing and magnetic particle testing. The calculation formula is as follows: Where a is the defect size, α0 and α1 are coefficient parameters calculated by calculating the parameters m and σ in formula (1), the defect size is selected as the defect length (l), and POD(a) is POD(l), which represents the probability of the sound beam hitting the defect; S5: For defects whose threshold value reaches 50% or more of the threshold equivalent, grinding or height measurement is performed to obtain defect height information, and model parameters β0, β1, and σ0 are calculated through linear regression analysis; S6: Finally, the defect detection rate is calculated based on the obtained model parameters. The calculation formula is as follows: Among them, l represents the defect length parameter, h represents the defect height parameter, and a th stands for threshold equivalent.

2. The method for calculating the defect detection rate of manual ultrasonic shear wave testing according to claim 1, characterized in that: The defect information includes defect location, defect type, defect height, defect length and reflection amplitude.

3. The method for calculating the defect detection rate of manual ultrasonic shear wave testing according to claim 2, characterized in that: The step S2 specifically includes: measuring the parameters of the detection probe and drawing an amplitude distance correction curve before ultrasonic shear wave detection, and then producing an evaluation line, a quantitative line and a scrap line based on the amplitude distance correction curve, wherein the evaluation line represents the threshold equivalent.

4. The method for calculating the defect detection rate of manual ultrasonic shear wave testing according to claim 2, characterized in that: The step S3 specifically includes: the detection probe scanning mode adopts a zigzag scanning mode, the detection probe emits a pulse signal, when the sound beam hits or approaches the defect, the ultrasonic wave will be reflected back, and the reflection amplitude data is obtained; when the threshold value of the defect is judged to be more than 50% of the threshold equivalent, the defect information of the defect is recorded.

5. The method for calculating the defect detection rate of manual ultrasonic shear wave testing according to claim 4, characterized in that: The step S4 specifically includes: using the ray detection result of the step S1 as a standard and the recorded reflection amplitude result to calculate the model parameters α0 and α1 through logistic regression analysis.

6. The method for calculating the defect detection rate of manual ultrasonic shear wave testing according to claim 5, characterized in that: The entire process of step S4 collects more than 60 pieces of reflected amplitude data for calculation.

7. The method for calculating the defect detection rate of manual ultrasonic shear wave testing according to claim 4, characterized in that: The step S5 specifically includes: polishing all defects and measuring the defect height, or measuring the height by ultrasonic detection method without polishing to obtain the defect height; taking the natural logarithm of the reflected amplitude and defect height measured by the defect, and then performing linear regression analysis to obtain parameters β0, β1 and σ0.

8. The method for calculating the defect detection rate of manual ultrasonic shear wave testing according to claim 7, characterized in that: The entire process of step S5 measures more than 30 pieces of data on the defect height for calculation.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for calculating the defect detection rate of manual ultrasonic shear wave detection as described in any one of claims 1 to 8 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for calculating the defect detection rate of manual ultrasonic shear wave detection as described in any one of claims 1 to 6 are implemented.

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