Ultrasonic testing method, system, equipment and medium for butt weld false defects of steel plate

Abstract

The application discloses a steel plate butt joint weld false defect ultrasonic detection method, system, equipment and medium, relates to the weld detection technical field, and the method comprises the following steps: setting a plurality of detection regions on the butt joint weld of the steel plate based on the structure parameters and surface characteristic data of the obtained steel plate to be detected; taking each detection region as a basic unit, performing multi-frequency and multi-angle ultrasonic scanning according to the first detection parameter, and obtaining corresponding echo signal data; analyzing and identifying potential false defect signals, calculating corresponding false defect characteristic values according to the false defect signals; taking each detection region as a basic unit, performing false defect characteristic analysis according to the second detection parameter, and determining the reliability evaluation data of the false defects; based on the false defect reliability evaluation data and the false defect characteristic values corresponding to each detection region, analyzing the false defect condition of the butt joint weld of the steel plate, and generating a final weld quality comprehensive evaluation result; the application improves the detection accuracy of the steel plate butt joint weld detection.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of weld detection, in particular to a steel plate butt joint weld pseudo-defect ultrasonic detection method, system, device and medium. BACKGROUND

[0002] Welded joints are often the weakest link in steel structures, especially in applications such as bridges and buildings that have extremely high safety requirements. Through weld detection, potential defects such as cracks, pores, incomplete fusion or incomplete penetration can be found, thereby avoiding accidents during use. In other words, steel plate weld detection is an important link to ensure welding quality and structural safety.

[0003] The existing steel plate butt joint weld ultrasonic detection may have the problem of pseudo-defect interference: due to the influence of factors such as the diversity of the inspected workpiece, the complex internal structure, and the surface roughness, various surface waves, deformation waves, and structure reflection waves may appear in the instrument screen. These pseudo-defects can seriously affect the identification and determination of internal defects in the weld, for example, surface waves are transverse waves that propagate along the surface of the workpiece, which cannot reflect the true situation of the defect, but are easily mistaken for defect waves, causing misjudgment. In addition, root weld bead reflection waves, deformation waves (longitudinal waves), upper surface reflection waves (transverse waves), and excess height reflection waves may also cause misjudgment or missed judgment. Therefore, to solve the problem of misjudgment or missed judgment and improve the detection accuracy of steel plate butt joint weld detection. SUMMARY

[0004] In order to improve the detection accuracy of steel plate butt joint weld detection and effectively solve the problem of misjudgment or missed judgment in steel plate butt joint weld detection, the application provides a steel plate butt joint weld pseudo-defect ultrasonic detection method, system, device and medium.

[0005] In the first aspect, the application achieves the purpose of the invention by adopting the following technical scheme:

[0006] The steel plate butt joint weld pseudo-defect ultrasonic detection method comprises:

[0007] Obtaining the structure parameters and surface characteristic data of the steel plate butt joint weld to be detected, and setting a plurality of detection regions on the steel plate butt joint weld based on the structure parameters and surface characteristic data;

[0008] Taking each detection region as a basic unit, using an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter to obtain corresponding echo signal data; analyzing and identifying potential pseudo-defect signals according to the echo signal data, and calculating corresponding pseudo-defect characteristic values according to the pseudo-defect signals;

[0009] Take each detection area as a basic unit, and perform pseudo-defect feature analysis according to a preset second detection parameter to determine the reliability evaluation data of the pseudo-defect.

[0010] Based on the pseudo-defect reliability evaluation data and the pseudo-defect feature value corresponding to each detection area, the pseudo-defect conditions of the butt weld of the steel plate are comprehensively analyzed to generate a final comprehensive evaluation result of the weld quality.

[0011] By adopting the above technical solution, a plurality of detection areas are set on the butt weld of the steel plate to be detected to achieve comprehensive coverage and detailed analysis in the process of weld pseudo-defect detection, which is beneficial to capture potential subtle defects in the butt weld of the steel plate, reduce misjudgment caused by complex weld geometry, and improve the detection accuracy of weld pseudo-defect detection. The ultrasonic detection equipment is used to perform multi-frequency (different frequency bands from low frequency to high frequency) and multi-angle (such as different incident angles) scanning according to a preset first detection parameter, which increases the sensitivity to different types of pseudo-defect signals. The multi-dimensional weld defect data acquisition mode enables the system to more accurately distinguish between real defects and pseudo-defects. Further, the potential pseudo-defect signals are identified and their feature values are calculated through defect feature analysis of the echo signals, which provides a quantitative basis for subsequent pseudo-defect evaluation and improves the accuracy of identification. The pseudo-defect feature analysis is performed according to a preset second detection parameter to determine the reliability evaluation data of the defect, and then based on the pseudo-defect reliability evaluation data and the pseudo-defect feature value corresponding to each detection area, comprehensive analysis is performed to generate a final comprehensive evaluation result of the weld quality. The comprehensive evaluation result of the weld quality not only reflects the overall quality condition of the weld, but also emphasizes the influence of the pseudo-defect, thereby realizing efficient and accurate detection of the pseudo-defect of the butt weld of the steel plate and effectively solving the problems of misjudgment or omission in the detection of the butt weld of the steel plate.

[0012] In a preferred example of the present application, the structure parameters and surface characteristic data of the butt weld of the steel plate to be detected are obtained, and a plurality of detection areas are set on the butt weld of the steel plate based on the structure parameters and surface characteristic data, specifically including: data preprocessing is performed on the structure parameters and surface characteristic data of the butt weld of the steel plate to be detected to obtain preprocessed structure parameters and surface characteristic data.

[0013] Based on the preprocessed structure parameters and surface characteristic data, a weld shape analysis algorithm is used to identify the geometric features of the weld, including weld height, width and inclination angle.

[0014] According to the geometric features of the weld and the predicted detection rules, a plurality of detection areas are divided on the weld, and the plurality of detection areas cover the key positions and potential defect prone areas of the weld.

[0015] By adopting the technical scheme, the data preprocessing eliminates the noise, abnormal value and inconsistency in the original data of the structural parameters and surface characteristic data of the butt weld of the steel plate, improves the quality of the basis data for subsequent analysis, ensures that all subsequent calculations and analysis are based on accurate and reliable data, and simultaneously uses an advanced weld form analysis algorithm to identify the geometric characteristics such as the height, width and inclination angle of the weld, so as to not only accurately capture the actual form of the weld, but also help to more accurately plan a detection path and determine key detection points, thereby improving the detection efficiency and precision, according to the geometric characteristics of the weld and the predicted detection rules, a plurality of detection areas are reasonably divided on the weld, the detection areas particularly cover the key parts and potential defect prone areas of the weld, so as to ensure the comprehensiveness and pertinence of the detection, and through scientific and reasonable area division, unnecessary repeated detection is avoided, and meanwhile, each area that may have a problem can be fully checked, so that the overall detection coverage and accuracy are improved.

[0016] In a preferred example of the present application: the detection area is taken as a basic unit, and a multi-frequency and multi-angle ultrasonic wave scanning is performed on the weld in each detection area according to a preset first detection parameter by using an ultrasonic detection device, so as to obtain corresponding echo signal data; potential pseudo-defect signals are identified according to the echo signal data, and corresponding pseudo-defect characteristic values are calculated according to the pseudo-defect signals, specifically including:

[0017] The first detection parameter includes a frequency range, a scanning angle, a scanning frequency and a gain setting of the ultrasonic wave;

[0018] For each detection area, a multi-frequency and multi-angle scanning is performed on the weld in the detection area according to a preset first detection parameter by using an ultrasonic detection device;

[0019] The echo signal data generated in the scanning process is received and recorded, and the echo signal data includes an echo amplitude, a phase and an arrival time;

[0020] The echo signal data is analyzed by using a signal processing technology, potential pseudo-defect signals are identified, and corresponding initial pseudo-defect characteristic values are calculated according to the characteristics of the pseudo-defect signals;

[0021] The initial pseudo-defect characteristic values are compared with a preset pseudo-defect judgment standard to obtain a comparison result, the initial pseudo-defect characteristic values are optimized based on the comparison result, and corresponding pseudo-defect characteristic values are obtained.

[0022] By adopting the technical scheme, the first detection parameters such as the frequency range, the scanning angle, the scanning frequency and the gain setting of the ultrasonic wave are set, the weld in each detection area is scanned at multiple frequencies and multiple angles, different types of echo signals can be captured, such as pseudo-defect signals caused by complex structures or surface characteristics, compared with a single frequency and angle scanning mode, the multi-frequency and multi-angle scanning significantly improves the distinguishing ability of real defects and pseudo-defects, echo signal data provides rich pseudo-defect gap information sources, and the reliability of defect identification of the weld pseudo-defect is improved, further, the echo signal data is analyzed in depth by using signal processing technologies such as wavelet transform and Fourier transform, feature information representing real defects can be effectively extracted, potential pseudo-defect signals can be more accurately identified, initial pseudo-defect characteristic values are calculated according to the characteristics, and the quality of basic data for a subsequent optimization process is ensured.

[0023] In a preferred example of the present application: based on the pseudo-defect reliability evaluation data and the pseudo-defect characteristic values corresponding to each detection area, the pseudo-defect conditions of the butt weld of the steel plate are comprehensively analyzed, specifically including:

[0024] Obtain historical detection data, and obtain weld defect occurrence probability data based on the historical detection data;

[0025] According to the pseudo-defect reliability evaluation data and the weld defect occurrence probability data, the defect influence degree data is calculated.

[0026] By adopting the technical scheme, the pseudo-defect reliability evaluation data and the weld defect occurrence probability data are combined to calculate the influence degree data of the pseudo-defect, by comprehensively considering various factors such as the position, size, shape of the pseudo-defect and its performance under different working conditions, a more comprehensive and accurate evaluation model is provided, which not only can identify the existence of the pseudo-defect, but also can quantify the potential impact on the overall structure safety, providing strong support for decision-making; by introducing the double verification mechanism of historical data and pseudo-defect reliability evaluation data, the misjudgment and omission problems caused by relying on single detection are greatly reduced, potential problems can be more comprehensively captured, and the robustness and reliability of the entire detection system are improved.

[0027] In a preferred example of the present application: taking each detection area as a basic unit, pseudo-defect feature analysis is performed according to the preset second detection parameters to determine the reliability evaluation data of the pseudo-defect, specifically including:

[0028] The second detection parameters include weld geometric complexity, welding process type, material attribute and environmental condition;

[0029] The target detection area is divided into average grids, and all grids involved in a single detection area are determined;

[0030] assigning a second grid score to each grid in the single detection area according to a second detection parameter;

[0031] extracting an arithmetic mean of the second grid scores of all grids in the single detection area to calculate a second detection parameter discrimination score of the single detection area;

[0032] calculating reliability evaluation data of the pseudo defect by using a comprehensive index method and the second detection parameter discrimination score.

[0033] By adopting the above technical solution, the weld geometric complexity, the welding process type, the material attribute and the environmental condition are introduced as the second detection parameter, the characteristics of the pseudo defect are comprehensively evaluated from multiple dimensions, not only the physical characteristics of the weld itself are considered, but also the influence of external factors is combined; the target detection area is divided into average grids, ensuring that all grids in each detection area can be analyzed in detail. The gridding processing method improves the spatial resolution and can capture more subtle structural changes. The arithmetic mean of the second grid scores of all grids is extracted to calculate the second detection parameter discrimination score of the single detection area. The qualitative description is converted into quantitative data, so that the pseudo defect characteristics can be accurately quantified, and the scientificity and reliability of the evaluation are enhanced.

[0034] In a preferred example of the present application: based on the pseudo defect reliability evaluation data and the pseudo defect characteristic value corresponding to each detection area, the pseudo defect conditions of the butt weld of the steel plate are comprehensively analyzed, and a final weld quality comprehensive evaluation result is generated, specifically including:

[0035] Taking each detection area as a basic unit, the corresponding pseudo defect influence degree data is taken as row vector data, and the corresponding pseudo defect reliability evaluation data is taken as column vector data, which are input into a preset quality evaluation matrix to obtain corresponding weld quality grade data;

[0036] According to the weld quality grade data corresponding to each detection area, a quality comprehensive evaluation result of the entire butt weld of the steel plate is obtained;

[0037] The weld is comprehensively verified by a multi-modal non-destructive testing technology to obtain the final weld quality comprehensive evaluation result.

[0038] By adopting the technical scheme, the welding quality is evaluated by using a systematic mathematical model, the false defect characteristics in a single detection area are considered, and the data of multiple detection areas are integrated through matrix operation, the quality comprehensive evaluation result of the entire butt welding seam of the steel plate is obtained according to the welding quality grade data corresponding to each detection area, the overall quality condition of the welding seam is quickly judged by the staff, then the welding seam is comprehensively verified by combining multiple non-destructive detection technologies such as X-ray detection and magnetic powder detection, and the reliability and accuracy of the evaluation result are ensured, and the mutual verification between different detection technologies can effectively reduce the misjudgment or missed detection problem caused by a single technology.

[0039] In a second aspect, the application aims to achieve the following technical solutions:

[0040] The steel plate butt welding seam false defect ultrasonic detection system applies the steel plate butt welding seam false defect ultrasonic detection method as described above, and the system comprises:

[0041] A data acquisition module is configured to acquire the structure parameters and surface characteristic data of the butt welding seam of the steel plate to be detected, and set a plurality of detection areas on the butt welding seam of the steel plate based on the structure parameters and surface characteristic data.

[0042] An ultrasonic scanning module is configured to use an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to preset first detection parameters, to obtain corresponding echo signal data, and to analyze and identify potential false defect signals according to the echo signal data, and to calculate corresponding false defect characteristic values, with each detection area as a basic unit.

[0043] A false defect characteristic analysis module is configured to perform false defect characteristic analysis according to preset second detection parameters, to determine false defect reliability evaluation data, with each detection area as a basic unit.

[0044] A comprehensive evaluation module is configured to comprehensively analyze the false defect condition of the butt welding seam of the steel plate based on the false defect reliability evaluation data and the false defect characteristic values corresponding to each detection area, and to generate a final welding quality comprehensive evaluation result.

[0045] By adopting the technical scheme, the data acquisition module ensures comprehensive coverage of key parts of the weld and potential defect-prone areas, and high-precision data acquisition provides a reliable basis for subsequent detection and analysis; the ultrasonic scanning module can capture different types of echo signals, including pseudo-defect signals caused by complex structures or surface characteristics, which not only improves the ability to distinguish between real defects and pseudo-defects, but also reduces the missed detection problem that may be caused by single frequency and angle scanning; the pseudo-defect feature analysis module performs pseudo-defect feature analysis according to the preset second detection parameter (such as weld geometric complexity, welding process type, material attribute, environmental condition, etc.), determines pseudo-defect reliability evaluation data, and the comprehensive evaluation module: based on the pseudo-defect reliability evaluation data and the pseudo-defect feature value corresponding to each detection area, the comprehensive evaluation module comprehensively analyzes the pseudo-defect condition of the butt weld of the steel plate, and generates a final comprehensive evaluation result of the weld quality. Through the combination of the matrix evaluation model and the multi-modal non-destructive testing technology, the comprehensive evaluation module provides a scientific, accurate and reliable evaluation result.

[0046] In a third aspect, the application aims to achieve the technical solutions as follows:

[0047] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above-mentioned steel plate butt weld pseudo-defect ultrasonic detection method when executing the computer program.

[0048] In a fourth aspect, the application aims to achieve the technical solutions as follows:

[0049] A computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the above-mentioned steel plate butt weld pseudo-defect ultrasonic detection method.

[0050] In summary, the present application includes at least one of the following beneficial technical effects:

[0051] 1. The multi-dimensional weld defect data acquisition method enables the system to more accurately distinguish between real defects and false defects; further, by analyzing the defect characteristics of the echo signal, potential false defect signals are identified and their characteristic values are calculated, providing a quantitative basis for subsequent false defect evaluation, improving the accuracy of identification, according to the preset second detection parameter for false defect characteristic analysis, to determine the reliability evaluation data of the defects, and then based on the false defect reliability evaluation data and false defect characteristic values corresponding to each detection area, comprehensive analysis is performed to generate the final weld quality comprehensive evaluation result, which not only reflects the overall quality of the weld, but also emphasizes the impact of false defects, thereby achieving efficient and accurate detection of steel plate butt weld false defects, effectively solving the problem of misjudgment or omission in steel plate butt weld detection; 2. The weld geometric complexity, welding process type, material properties and environmental conditions are introduced as the second detection parameter, which comprehensively evaluates the characteristics of the false defects from multiple dimensions, not only considering the physical characteristics of the weld itself, but also combining the influence of external factors; the target detection area is divided into an average grid to ensure that all grids in each detection area can be analyzed in detail. The grid processing method improves the spatial resolution and can capture finer structural changes. The arithmetic mean of the second grid score of all grids is extracted to calculate the second detection parameter discrimination score of the single detection area, which converts qualitative description into quantitative data, allowing the false defect characteristics to be accurately quantified and enhancing the scientificity and reliability of the evaluation;

[0052] 3. A systematic mathematical model is used to evaluate the weld quality, which not only considers the false defect characteristics in a single detection area, but also integrates data from multiple detection areas through matrix operations. According to the weld quality grade data corresponding to each detection area, the quality comprehensive evaluation result of the entire steel plate butt weld is obtained, which facilitates the staff to quickly judge the overall quality of the weld. Then, through the combination of X-ray detection, magnetic powder detection and other non-destructive testing techniques, the weld is comprehensively verified to ensure the reliability and accuracy of the evaluation results. The mutual verification between different detection techniques can effectively reduce the misjudgment or omission problems that may be caused by a single technique. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 is a flowchart of the steel plate butt weld false defect ultrasonic detection method in an embodiment of the present application;

[0054] Figure 2 is a flowchart of step S1 in the steel plate butt weld false defect ultrasonic detection method in an embodiment of the present application;

[0055] Figure 3 is a device schematic diagram in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The application will be further described in detail below with reference to the accompanying drawings.

[0057] In an embodiment, as shown in the accompanying drawings, the application discloses a steel plate butt weld pseudo-defect ultrasonic detection method, which specifically comprises the following steps: Figure 1

[0058] S1: Obtain the structure parameters and surface characteristic data of the steel plate butt weld to be detected, and set a plurality of detection regions on the steel plate butt weld based on the structure parameters and surface characteristic data.

[0059] In this embodiment, the structure parameters include but are not limited to the geometric characteristics of the weld, such as height, width, and inclination angle; and the surface characteristic data includes the roughness, cleanliness, and coating condition of the weld surface.

[0060] Specifically, the three-dimensional geometric data of the weld is obtained using a laser scanner, a 3D camera, or a contact measurement tool; and the surface characteristic information is obtained through an optical microscope, a surface profilometer, or the like, and the data acquisition accuracy needs to reach the millimeter level.

[0061] S2: Take each detection region as a basic unit, and use an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to preset first detection parameters to obtain corresponding echo signal data; analyze and identify potential pseudo-defect signals according to the echo signal data, and calculate corresponding pseudo-defect characteristic values according to the pseudo-defect signals.

[0062] In this embodiment, the first detection parameters include the frequency range (such as 0.5 MHz to 10 MHz) of the ultrasonic wave, the scanning angle (such as 0 to 80°), the scanning speed, and the gain setting.

[0063] Specifically, according to the preset first detection parameters, the working frequency and the incident angle of the ultrasonic probe are adjusted, and in each detection region, a phased array ultrasonic flaw detector is used for multi-frequency and multi-angle scanning to receive and record the echo signal data; the echo signal data is analyzed in real time to identify potential pseudo-defect signals and calculate corresponding pseudo-defect characteristic values; and when the ultrasonic probe is scanned, the scanning speed and the probe position need to be kept stable.

[0064] S3: Take each detection region as a basic unit, and perform pseudo-defect characteristic analysis according to preset second detection parameters to determine the reliability evaluation data of the pseudo-defect.

[0065] ​In the embodiment, the second detection parameter includes weld geometry complexity, welding process type, material attribute, environmental condition, etc.; the weld geometry complexity refers to the complexity of the weld structure, including but not limited to the height, width, inclination angle of the weld, joint form (such as butt joint, corner joint), welding process type refers to the specific welding method and technical parameters, such as manual arc welding, submerged arc automatic welding, gas shielded welding, etc., and process parameters such as welding current, voltage, welding speed; the material attribute refers to the physical and chemical properties of the welding material, including but not limited to the strength, toughness, thermal expansion coefficient, thermal conductivity of the material, etc.; the environmental condition refers to the environmental factors during and after welding, such as temperature, humidity, corrosive medium, external stress, etc.

[0066] Specifically, in step S3, specifically includes:

[0067] S31: performing average grid division on the target detection area to determine all grids involved in a single detection area.

[0068] In the embodiment, each detection area is divided into a plurality of uniformly distributed small units (grids), and the selection of the grid size should consider the weld geometry complexity and the resolution of the detection device, and can be self-defined according to expert knowledge and experience, to ensure that the data in each grid can represent the local characteristics of the area, that is, according to the geometric size of the weld and the expected detection accuracy, a suitable grid size is selected, which should be small enough to capture subtle changes, but not too fine to cause excessive calculation, and each grid is assigned a unique coordinate identifier for subsequent data processing and analysis.

[0069] S32: assigning each grid in a single detection area according to the second detection parameter to obtain a second grid score.

[0070] In the embodiment, the second detection parameter of each grid is obtained by field measurement or historical record query, and the weight of each second detection parameter in evaluation is determined according to actual engineering experience and theoretical analysis.

[0071] S33: extracting the arithmetic mean of the second grid scores of all grids in a single detection area to calculate the second detection parameter discrimination score of the single detection area.

[0072] Specifically, the average value of all grid scores in each detection area is calculated as the second detection parameter discrimination score of the detection area.

[0073] For example, the welding quality of the pressure vessel of a nuclear power plant is directly related to the safe operation of the nuclear reactor. Due to the special and extremely high requirements of the working environment of the nuclear power plant, any small weld defect can cause serious safety hazards. When assigning grid parameters to the weld of the pressure vessel, each grid is quantitatively evaluated according to the weld geometric complexity, welding process type, material properties and environmental conditions, and a corresponding score is assigned. For example, a higher weight is assigned to the grid in the high stress area.

[0074] S34: Calculate the reliability evaluation data of the pseudo defect using the comprehensive index method and the second detection parameter discrimination score.

[0075] Specifically, the comprehensive index method is commonly used for multi-factor evaluation, and the calculation formula is where I is the comprehensive index, ω i is the weight of the i-th factor, x i is the branch of the i-th factor, and n is the number of factors.

[0076] Suppose there is a detection area that is divided into 5 grids, each of which is assigned a value according to the second detection parameter, and the second detection parameter discrimination score of each grid is calculated by the weighted average method. The reliability evaluation data of the pseudo defect in the detection area will be calculated using the comprehensive index method.

[0077] The existing second detection parameter is:

[0078]

[0079] Suppose we assign the following weights to each second detection parameter:

[0080] Weld geometric complexity: 0.3; welding process type: 0.25; material properties: 0.25; environmental conditions: 0.2.

[0081] Calculate the comprehensive index of each grid:

[0082] For each grid, we multiply the score of the second detection parameter by the corresponding weight and then sum to get the comprehensive index.

[0083] Grid 1: I1 = (0.3 x 8) + (0.25 x 7) + (0.25 x 9) + (0.2 x 6) = 2.4 + 1.75 + 2.25 + 1.2 = 7.6.

[0084] Grid 2: I2 = (0.3 x 7) + (0.25 x 8) + (0.25 x 8) + (0.2 x 7) = 7.5.

[0085] Grid 3 I3 = (0.3 x 9) + (0.25 x 9) + (0.25 x 9) + (0.2 x 8) = 8.7.

[0086] Grid 4: I4 = (0.3 x 6) + (0.25 x 7) + (0.25 x 7) + (0.2 x 6) = 6.6.

[0087] Grid 5: I5 = (0.3 x 8) + (0.25 x 8) + (0.25 x 8) + (0.2 x 7) = 7.8.

[0088] The formula for calculating the weighted average comprehensive index is:

[0089] Assuming that the weight of each grid is the same, i.e. the weight of each grid is 0.2, W = (0.2 x 7.6) + (0.2 x 7.5) + (0.2 x 8.7) + (0.2 x 6.6) + (0.2 x 7.8) / 1.0 = 7.64, so the pseudo defect reliability evaluation data of the detection area is calculated as 7.64.

[0090] S4: Based on the pseudo defect reliability evaluation data and the pseudo defect characteristic value corresponding to each detection area, the pseudo defect condition of the butt weld of the steel plate is comprehensively analyzed, and a final weld quality comprehensive evaluation result is generated.

[0091] In this embodiment, the comprehensive analysis also includes an analysis mode of comprehensive verification using multi-modal non-destructive testing technology (including X-ray detection and magnetic powder detection).

[0092] Specifically, in step S4, specifically comprising:

[0093] S41: Taking each detection area as a basic unit, the corresponding pseudo defect influence degree data is taken as row vector data, and the corresponding pseudo defect reliability evaluation data is taken as column vector data, which is input into a preset quality evaluation matrix to obtain corresponding weld quality grade data.

[0094] Specifically, the pseudo defect influence degree data reflects the influence of the pseudo defect on the overall performance of the weld, and based on historical detection data and current detection results, the influence degree of the pseudo defect on the overall performance of the weld in each detection area is calculated, including but not limited to the position, size, shape of the pseudo defect and its performance under different working conditions; the pseudo defect reliability evaluation data is analyzed according to the second detection parameter to determine the reliability evaluation data of the pseudo defect in each detection area; the weld quality grade data is the weld quality grade corresponding to each detection area, which can be represented by letters or numbers, such as A level, B level, etc.

[0095] S42: According to the weld quality grade data corresponding to each detection area, the quality comprehensive evaluation result of the entire butt weld of the steel plate is obtained.

[0096] For example, the pseudo-defect influence degree is expressed in a range of 0 to 10; the pseudo-defect reliability evaluation is a reflection of the probability of the existence of the pseudo-defect and the potential influence of the pseudo-defect on the structural safety, and ranges from 0 to 10.

[0097] A quality evaluation matrix Q is designed first, where each element q ij represents the weld quality level under a specific pseudo-defect influence degree i and pseudo-defect reliability evaluation j, and the quality evaluation matrix Q is as follows:

[0098]

[0099] where A to N represent different quality levels, decreasing from best to worst. For example, A represents the highest quality level, and N represents the lowest quality level. The pseudo-defect influence degree data is taken as a row vector R, R = [8, 7, 9, 6, 8]; the pseudo-defect reliability evaluation data is taken as a column vector C, C = [7, 8, 9, 7, 8], and then the corresponding value in the quality evaluation matrix is searched, grid 1 (pseudo-defect influence degree 8, pseudo-defect reliability evaluation 7), the position (8, 7) in the matrix is searched, and the quality level q 8，7 = H is obtained; for grid 2 (pseudo-defect influence degree 7, pseudo-defect reliability evaluation 8), the position (7, 8) in the matrix is searched, and the quality level q 7，8 = H is obtained; for grid 3 (pseudo-defect influence degree 9, pseudo-defect reliability evaluation 9), the position (9, 9) in the matrix is searched, and the quality level q 9，9 = M is obtained; for grid 4 (pseudo-defect influence degree 6, pseudo-defect reliability evaluation 7), the position (6, 7) in the matrix is searched, and the quality level q 6，7 = G is obtained; for grid 5 (pseudo-defect influence degree 8, pseudo-defect reliability evaluation 8), the position (8, 8) in the matrix is searched, and the quality level q 8，8 = H is obtained.

[0100] Thus, the quality comprehensive evaluation result is obtained as grid 1: quality level H; grid 2: quality level H; grid 3: quality level M; grid 4: quality level G; and grid 5: quality level H.

[0101] S43: The weld is comprehensively verified by the multi-modal non-destructive testing technology to obtain the final weld quality comprehensive evaluation result.

[0102] In this embodiment, the multi-modal non-destructive testing technology includes ultrasonic testing, X-ray testing, magnetic powder testing, and penetration testing; and the weld quality comprehensive evaluation result contains the specific conditions of each detection area and the description of the overall quality condition.

[0103] Specifically, appropriate non-destructive testing equipment and technology are selected according to the specific conditions.

[0104] In an embodiment, as shown in FIG. 1, in step S1, the structural parameters and surface characteristic data of the butt weld of the steel plate to be detected are acquired, and based on the structural parameters and surface characteristic data, a plurality of detection regions are set on the butt weld of the steel plate, which specifically includes: Figure 2

[0105] S11: The structural parameters and surface characteristic data of the butt weld of the steel plate to be detected are preprocessed to obtain preprocessed structural parameters and surface characteristic data.

[0106] Specifically, the data preprocessing includes cleaning the original data, removing noise and invalid data, data smoothing processing and data standardization processing, and unifying different dimensional data to the same scale for subsequent analysis

[0107] S12: Based on the preprocessed structural parameters and surface characteristic data, a weld form analysis algorithm is used to identify the geometric features of the weld, including weld height, width and inclination angle.

[0108] In this embodiment, a suitable weld form analysis algorithm is selected according to specific requirements, such as edge detection algorithm (Canny, Sobel), template matching algorithm or convolutional neural network (CNN).

[0109] S13: According to the geometric features of the weld and the predicted detection rules, a plurality of detection regions are divided on the weld, and the plurality of detection regions cover the key parts and potential defect prone areas of the weld.

[0110] In this embodiment, a plurality of detection regions are divided on the weld in combination with the geometric features (such as height, width and inclination angle) of the weld. The size and shape of each region are ensured to be appropriate.

[0111] Specifically, for regions located at the edge of the weld or irregular in shape, special treatment is needed to ensure the effectiveness and representativeness of the data.

[0112] In an embodiment, in step S2, using each detection region as a basic unit, a plurality of frequency and multi-angle ultrasonic scans are performed according to a pre-set first detection parameter using an ultrasonic detection device to obtain corresponding echo signal data; potential false defect signals are analyzed and identified according to the echo signal data, and corresponding false defect feature values are calculated according to the false defect signals, which specifically includes:

[0113] S21: The first detection parameter includes the frequency range, scanning angle, scanning frequency and gain setting of the ultrasonic wave.

[0114] ​Specifically, the ultrasonic frequency range refers to the frequency range used during ultrasonic scanning, typically between 0.5 MHz and 10 MHz, with different frequencies suitable for detecting different types of defects; the scanning angle refers to the angle of the ultrasonic probe relative to the weld surface, typically between 0° and 70°, and multi-angle scanning can capture echo signals in different directions; the scanning frequency refers to the speed and frequency of the probe movement during ultrasonic scanning, ensuring coverage of all critical areas; the gain setting refers to the sensitivity setting of the ultrasonic device, affecting the strength of the received signal.

[0115] S22: For each detection area, use the ultrasonic detection device to perform multi-frequency, multi-angle scanning of the weld in the detection area according to the preset first detection parameter.

[0116] S23: Receive and record the echo signal data generated during scanning, including echo amplitude, phase, and arrival time.

[0117] In this embodiment, the phase refers to the phase difference between the echo signal and the transmitted signal, providing information about the internal structure of the material; the arrival time refers to the time difference from transmitting the ultrasonic wave to receiving the echo, used to calculate the defect location.

[0118] S24: Analyze the echo signal data using signal processing techniques to identify potential false defect signals, and calculate the corresponding initial false defect feature values based on the characteristics of the false defect signals.

[0119] In this embodiment, the initial false defect feature values are based on the false defect features identified from the echo signal, including location, size, shape, etc.

[0120] Specifically, the echo signal is preprocessed for denoising, smoothing, etc. to improve signal quality, and filters, spectral analysis tools, or machine learning algorithms are applied to extract key features of the false defect signal, such as amplitude, phase, arrival time, etc. Based on the extracted features, the initial false defect feature values are calculated.

[0121] S25: Compare the initial false defect feature values with the preset false defect judgment standard to obtain a comparison result, and optimize the initial false defect feature values based on the comparison result to obtain corresponding false defect feature values.

[0122] In this embodiment, the optimized false defect feature values are the final false defect feature values obtained by comparing and optimizing the preset standard, which more accurately reflect the true situation of the false defects.

[0123] Specifically, according to a large amount of experimental data and expert opinions, the pseudo-defect judgment criteria such as size threshold and shape features are set; the initial pseudo-defect characteristic values are compared with the preset criteria to determine whether they meet the criteria; for the characteristic values that do not meet the criteria, further analysis and adjustment are performed to ensure their authenticity and reliability, and the results are confirmed through multiple verifications to ensure that they meet the actual situation.

[0124] In an embodiment, in step S4, specifically includes:

[0125] S401: Obtain historical detection data, and obtain weld defect occurrence probability data based on the historical detection data.

[0126] In the present embodiment, relevant detection reports, maintenance records and other historical data are collected, the collected data are cleaned and arranged, repeated or invalid data are removed, and the arranged data are analyzed using a statistical analysis tool to calculate the defect occurrence probability of different types of welds under different working conditions. For example, it is found that the welds at certain specific positions are more prone to cracks in a high-salt-mist environment.

[0127] S402: Calculate defect impact degree data based on the pseudo-defect reliability evaluation data and the weld defect occurrence probability data.

[0128] Specifically, the pseudo-defect reliability evaluation data and the weld defect occurrence probability data are combined to form a basic data set for comprehensive evaluation, the weights of the pseudo-defect reliability evaluation data and the weld defect occurrence probability data in the impact degree evaluation are determined according to actual engineering experience and theoretical analysis, and a mathematical model (such as a comprehensive index method, in actual application, a fuzzy evaluation method or a weighted average method) is used to process the above data to calculate the defect impact degree data of each detection area.

[0129] It should be understood that the sequence numbers of the steps in the above embodiments do not mean the order of execution, and the execution order of the processes should be determined according to their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0130] In an embodiment, a steel plate butt weld pseudo-defect ultrasonic detection system is provided, which corresponds to the steel plate butt weld pseudo-defect ultrasonic detection method in the above embodiment.

[0131] The steel plate butt weld pseudo-defect ultrasonic detection system includes a data acquisition module, an ultrasonic scanning module, a pseudo-defect feature analysis module and a comprehensive evaluation module. The detailed descriptions of the functional modules are as follows:

[0132] The data acquisition module is configured to acquire structural parameter and surface characteristic data of the butt joint of the steel plate to be detected, and set a plurality of detection regions on the butt joint of the steel plate based on the structural parameter and surface characteristic data.

[0133] The ultrasonic scanning module is configured to perform multi-frequency and multi-angle ultrasonic scanning on each detection region as a basic unit by using an ultrasonic detection device according to a preset first detection parameter to obtain corresponding echo signal data, and analyze and identify potential false defect signals according to the echo signal data to calculate corresponding false defect characteristic values.

[0134] The false defect characteristic analysis module is configured to perform false defect characteristic analysis on each detection region as a basic unit according to a preset second detection parameter to determine reliability evaluation data of the false defects.

[0135] The comprehensive evaluation module is configured to comprehensively analyze the false defect condition of the butt joint of the steel plate based on the false defect reliability evaluation data and the false defect characteristic values corresponding to each detection region to generate a final comprehensive evaluation result of the weld quality.

[0136] Optionally, the data acquisition module comprises:

[0137] The preprocessing submodule is configured to perform data preprocessing on the structural parameter and surface characteristic data of the butt joint of the steel plate to be detected to obtain preprocessed structural parameter and surface characteristic data.

[0138] The morphology analysis submodule is configured to identify geometric features of the weld based on the preprocessed structural parameter and surface characteristic data by using a weld morphology analysis algorithm, the geometric features including weld height, width and inclination angle.

[0139] The region division submodule is configured to divide a plurality of detection regions on the weld according to the geometric features of the weld and a predicted detection rule, the plurality of detection regions covering key positions and potential defect prone areas of the weld.

[0140] The specific limitations of the steel plate butt joint false defect ultrasonic detection system can be referred to the limitations of the steel plate butt joint false defect ultrasonic detection method in the foregoing, and will not be described herein again. The modules in the steel plate butt joint false defect ultrasonic detection system described above can be realized by software, hardware or a combination thereof in whole or in part. The modules described above can be embedded in or independent of a processor in a computer device in a hardware form, or can be stored in a memory in a computer device in a software form, so as to be called and executed by a processor to perform operations corresponding to the modules.

[0141] In one embodiment, a computer device is provided, which can be a server, and an internal structure diagram of the computer device can be as shown in Figure 3The computer device includes a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The database of the computer device is used to store structural parameters of the butt weld of the steel plate, surface characteristic data and reliability evaluation data of the pseudo defect, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement an ultrasonic detection method for a pseudo defect of a butt weld of a steel plate.

[0142] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program:

[0143] S1: Obtain structural parameters and surface characteristic data of a butt weld of a steel plate to be detected, and set a plurality of detection regions on the butt weld of the steel plate based on the structural parameters and the surface characteristic data;

[0144] S2: Take each detection region as a basic unit, use an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter, obtain corresponding echo signal data, analyze and identify potential pseudo defect signals according to the echo signal data, and calculate corresponding pseudo defect characteristic values according to the pseudo defect signals;

[0145] S3: Take each detection region as a basic unit, perform pseudo defect characteristic analysis according to a preset second detection parameter, and determine reliability evaluation data of the pseudo defect;

[0146] S4: Based on the pseudo defect reliability evaluation data and the pseudo defect characteristic values corresponding to each detection region, comprehensively analyze the pseudo defect condition of the butt weld of the steel plate, and generate a final weld quality comprehensive evaluation result.

[0147] In one embodiment, a computer readable storage medium is provided, having a computer program stored thereon, the computer program being executed by a processor to implement the following steps:

[0148] S1: Obtain structural parameters and surface characteristic data of a butt weld of a steel plate to be detected, and set a plurality of detection regions on the butt weld of the steel plate based on the structural parameters and the surface characteristic data;

[0149] S2: taking each detection area as a basic unit, performing multi-frequency and multi-angle ultrasonic wave scanning according to a preset first detection parameter by using an ultrasonic detection device to obtain corresponding echo signal data; analyzing and identifying potential false defect signals according to the echo signal data, and calculating corresponding false defect characteristic values according to the false defect signals;

[0150] S3: taking each detection area as a basic unit, performing false defect characteristic analysis according to a preset second detection parameter to determine false defect reliability evaluation data;

[0151] S4: based on the false defect reliability evaluation data and the false defect characteristic values corresponding to each detection area, comprehensively analyzing the false defect conditions of the butt weld of the steel plate to generate a final weld quality comprehensive evaluation result.

[0152] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. 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 above-mentioned embodiments. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), 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.

[0153] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is exemplified. In actual applications, the above-mentioned functions can be completed by different functional units and modules according to needs, i.e. the internal structure of the device is divided into different functional units or modules to complete all or part of the above-mentioned functions.

[0154] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand; it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method of ultrasonic testing of butt welds of steel plates for false defects, characterized in that, The method comprises the following steps: Obtaining the structure parameters and surface characteristic data of the butt weld of the steel plate to be detected, and setting a plurality of detection regions on the butt weld of the steel plate based on the structure parameters and surface characteristic data; Taking each detection region as a basic unit, using an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter, and obtaining corresponding echo signal data; analyzing and identifying potential false defect signals according to the echo signal data, and calculating corresponding false defect characteristic values according to the false defect signals; Taking each detection region as a basic unit, performing false defect characteristic analysis according to a preset second detection parameter, and determining the reliability evaluation data of the false defects; Based on the false defect reliability evaluation data and the false defect characteristic values corresponding to each detection region, comprehensively analyzing the false defect condition of the butt weld of the steel plate, and generating a final weld quality comprehensive evaluation result; The false defect characteristic analysis according to the preset second detection parameter and the determination of the reliability evaluation data of the false defects based on each detection region as a basic unit specifically include: The second detection parameter includes weld geometric complexity, welding process type, material attribute, and environmental condition; Dividing the target detection region into average grids to determine all grids involved in a single detection region; Assigning a value to each grid in a single detection region according to the second detection parameter to obtain a second grid score; Extracting the arithmetic mean of the second grid scores of all grids in a single detection region to calculate a second detection parameter discrimination score of the single detection region; Using a comprehensive index method and the second detection parameter discrimination score to calculate the reliability evaluation data of the false defects.

2. The steel plate butt weld pseudo-defect ultrasonic testing method according to claim 1, characterized by, The obtaining of the structure parameters and surface characteristic data of the butt weld of the steel plate to be detected and the setting of a plurality of detection regions on the butt weld of the steel plate based on the structure parameters and surface characteristic data specifically include: Data preprocessing is performed on the structure parameters and surface characteristic data of the butt weld of the steel plate to be detected to obtain preprocessed structure parameters and surface characteristic data; Based on the preprocessed structure parameters and surface characteristic data, a weld form analysis algorithm is used to identify the geometric features of the weld, including weld height, width, and inclination angle; According to the geometric features of the weld and the predicted detection rules, a plurality of detection regions are divided on the weld, and the plurality of detection regions cover the key parts and potential defect prone areas of the weld.

3. The steel plate butt weld pseudo-defect ultrasonic testing method according to claim 1, characterized by, Taking each detection region as a basic unit, using an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter, and obtaining corresponding echo signal data; According to the echo signal data, potential false defect signals are analyzed and identified, and corresponding false defect characteristic values are calculated according to the false defect signals, specifically including: The first detection parameter includes the frequency range, scanning angle, scanning frequency, and gain setting of the ultrasonic wave; For each detection region, the weld in the detection region is scanned using an ultrasonic detection device according to the preset first detection parameter; receiving and recording echo signal data generated in the scanning process, the echo signal data including echo amplitude, phase and time of arrival; analyzing the echo signal data using signal processing techniques to identify potential false defect signals, and calculating corresponding initial false defect feature values according to the characteristics of the false defect signals; comparing the initial false defect feature values with preset false defect judgment criteria to obtain a comparison result, and optimizing the initial false defect feature values based on the comparison result to obtain corresponding false defect feature values.

4. The steel plate butt weld pseudo-defect ultrasonic testing method according to claim 1, characterized by, comprehensive analysis of the false defect condition of the butt weld of the steel plate based on the false defect reliability evaluation data and the false defect feature values corresponding to each detection area, specifically including: obtaining historical detection data, and obtaining weld defect occurrence probability data based on the historical detection data; calculating defect impact degree data based on the false defect reliability evaluation data and the weld defect occurrence probability data.

5. The steel plate butt weld pseudo-defect ultrasonic testing method according to claim 1, characterized by, comprehensive analysis of the false defect condition of the butt weld of the steel plate based on the false defect reliability evaluation data and the false defect feature values corresponding to each detection area, and generating a final weld quality comprehensive evaluation result, specifically including: taking each detection area as a basic unit, inputting the corresponding false defect impact degree data as row vector data and the corresponding false defect reliability evaluation data as column vector data into a preset quality evaluation matrix to obtain corresponding weld quality grade data; obtaining the quality comprehensive evaluation result of the entire butt weld of the steel plate according to the weld quality grade data corresponding to each detection area; comprehensively verifying the weld through multi-modal non-destructive testing technology to obtain the final weld quality comprehensive evaluation result.

6. An ultrasonic testing system for butt welds of steel plates, characterized by, The steel plate butt weld false defect ultrasonic detection method according to any one of claims 1-5, the system comprising: a data acquisition module for obtaining structure parameters and surface characteristic data of a steel plate butt weld to be detected, and setting a plurality of detection areas on the steel plate butt weld based on the structure parameters and surface characteristic data; an ultrasonic scanning module taking each detection area as a basic unit, using an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to preset first detection parameters to obtain corresponding echo signal data, and analyzing and identifying potential false defect signals according to the echo signal data to calculate corresponding false defect feature values; a false defect feature analysis module taking each detection area as a basic unit, performing false defect feature analysis according to preset second detection parameters to determine false defect reliability evaluation data; a comprehensive evaluation module for comprehensive analysis of the false defect condition of the butt weld of the steel plate based on the false defect reliability evaluation data and the false defect feature values corresponding to each detection area, and generating a final weld quality comprehensive evaluation result; the second detection parameters including weld geometric complexity, welding process type, material properties and environmental conditions; ​ The target detection area is averagely rastered to determine all the rasters involved in a single detection area; Each raster in the single detection area is assigned a second raster score according to a second detection parameter; An arithmetic mean of the second raster scores of all the rasters in the single detection area is extracted to calculate a second detection parameter discrimination score of the single detection area; A reliability evaluation data of the pseudo defect is calculated by using a comprehensive index method and the second detection parameter discrimination score.

7. The steel plate butt weld pseudo-defect ultrasonic testing system according to claim 6, characterized in that, The data acquisition module specifically comprises: a preprocessing submodule for preprocessing the structure parameter and surface characteristic data of the butt weld of the steel plate to be detected to obtain preprocessed structure parameter and surface characteristic data; a morphology analysis submodule for identifying the geometric features of the weld based on the preprocessed structure parameter and surface characteristic data by using a weld morphology analysis algorithm, the geometric features including the height, width and inclination angle of the weld; a region division submodule for dividing the weld into a plurality of detection areas according to the geometric features of the weld and the predicted detection rules, the plurality of detection areas covering the key parts and potential defect-prone areas of the weld.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the steel plate butt weld pseudo defect ultrasonic detection method according to any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 8. The computer program is executed by the processor to realize the steps of the steel plate butt weld pseudo defect ultrasonic detection method according to any one of claims 1 to 5.

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