Ultrasonic detection method, system and equipment for pseudo defects of butt weld of steel plate and medium

Abstract

The invention discloses a steel plate butt weld pseudo defect ultrasonic detection method, system and device and a medium, and relates to the technical field of weld detection, the method comprises the following steps: setting a plurality of detection areas on a steel plate butt weld based on acquired structure parameters and surface characteristic data of a to-be-detected steel plate; performing multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter by taking each detection area as a basic unit to obtain corresponding echo signal data; analyzing and identifying potential pseudo-defect signals, and calculating corresponding pseudo-defect characteristic values according to the pseudo-defect signals; taking each detection area as a basic unit, performing pseudo defect feature analysis according to the second detection parameters, and determining reliability evaluation data of pseudo defects; 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 steel plate butt weld is analyzed, and a final weld quality comprehensive evaluation result is generated. According to the invention, the detection accuracy of steel plate butt weld detection is improved.

Description

Technical Field

[0001] The present application relates to the technical field of weld detection, and in particular to a method, system, equipment and medium for ultrasonic detection of pseudo-defects in butt welds of steel plates. Background Art

[0002] Welded joints are often the weakest link in steel structures, especially in applications with extremely high safety requirements such as bridges and buildings. Weld inspection can detect potential defects such as cracks, pores, lack of fusion or incomplete penetration, thereby avoiding accidents during use. That is, steel plate weld inspection is an important link to ensure welding quality and structural safety.

[0003] The existing ultrasonic detection of steel plate butt welds may have the problem of interference from pseudo defects: due to the influence of factors such as the diversity of specifications of the inspected workpieces, complex internal structures, and surface roughness, various echo signals such as surface waves, deformation waves, and structural reflection waves may appear on the instrument screen. These pseudo defects will seriously affect the identification and judgment of internal defects in the weld. For example, the surface wave is a transverse wave propagating along the surface of the workpiece. It cannot reflect the true situation of the defect, but it is easy to be mistaken for a defect wave and cause misjudgment. In addition, there are root weld nodule reflection waves, deformation waves (longitudinal waves), upper surface reflection waves (transverse waves), and residual height reflection waves, which may lead to misjudgment or missed judgment. Therefore, it is necessary to solve the problem of misjudgment or missed judgment to improve the detection accuracy of steel plate butt welds. Summary of the invention

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

[0005] In the first aspect, the invention objective of the present application is achieved by adopting the following technical solutions: The ultrasonic detection method for false defects of steel plate butt welds includes: Acquire structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and set a plurality of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data; Taking each of the detection areas 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; Taking each of the detection areas as a basic unit, performing pseudo-defect feature analysis according to a preset second detection parameter to determine reliability evaluation data of the pseudo-defect; Based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each of the detection areas, the pseudo-defect conditions of the steel plate butt weld are comprehensively analyzed to generate a final comprehensive evaluation result of the weld quality.

[0006] By adopting the above technical scheme, several detection areas are set on the steel plate butt weld of the steel plate to be detected, so as to achieve comprehensive coverage and detailed analysis in the process of weld pseudo-defect detection, which is conducive to capturing potential subtle defects inside the steel plate butt weld, reducing misjudgment caused by complex weld geometry, and improving the detection accuracy of weld pseudo-defect detection; ultrasonic detection equipment is used to perform multi-frequency (referring to different frequency bands from low frequency to high frequency) and multi-angle (such as different incident angles) scanning according to the preset first detection parameter, which increases the sensitivity to different types of pseudo-defect signals, and the multi-dimensional weld defect data collection method enables the system to more accurately distinguish between real defects and pseudo-defects; further, by The defect feature analysis of the echo signal identifies potential pseudo-defect signals and calculates their characteristic values, 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 the preset second detection parameter to determine the reliability assessment data of the defect. Then, based on the pseudo-defect reliability assessment data and pseudo-defect characteristic values ​​corresponding to each detection area, a comprehensive analysis is performed to generate the final comprehensive evaluation result of the weld quality. The comprehensive evaluation result of the weld quality not only reflects the overall quality status of the weld, but also emphasizes the influence of pseudo-defects, thereby realizing efficient and accurate detection of pseudo-defects in steel plate butt welds, and effectively solving the problem of misjudgment or missed judgment in steel plate butt weld detection.

[0007] In a preferred example of the present application: the obtaining of structural parameters and surface characteristic data of the butt weld of the steel plate to be detected, and setting a plurality of detection areas on the butt weld of the steel plate based on the structural parameters and surface characteristic data, specifically includes: performing data preprocessing on the structural parameters and surface characteristic data of the butt weld of the steel plate to be detected to obtain preprocessed structural parameters and surface characteristic data; Based on the pre-processed structural parameters and surface characteristic data, the weld morphology 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 number of detection areas are divided on the weld, and the several detection areas cover the key parts of the weld and the areas prone to potential defects.

[0008] By adopting the above technical scheme, data preprocessing eliminates noise, outliers and inconsistencies in the original data of the structural parameters and surface characteristics of the steel plate butt weld, improves the basic data quality of subsequent analysis, and ensures that all subsequent calculations and analyses are based on accurate and reliable data. At the same time, advanced weld morphology analysis algorithms are used to identify geometric features such as the height, width and inclination angle of the weld, which can not only accurately capture the actual shape of the weld, but also accurately identify geometric features to help more accurately plan the detection path and determine key detection points, thereby improving detection efficiency and accuracy. According to the geometric characteristics of the weld and the predicted detection rules, several detection areas are reasonably divided on the weld. The detection areas especially cover the key parts of the weld and the areas prone to potential defects, ensuring the comprehensiveness and pertinence of the detection. In addition, this application avoids unnecessary repeated detection through scientific and reasonable area division, while ensuring that each area where there may be problems can be fully inspected, thereby improving the overall detection coverage and accuracy.

[0009] In a preferred example of the present application, each of the detection areas is used as a basic unit, and a multi-frequency and multi-angle ultrasonic scanning is performed using an ultrasonic detection device according to a preset first detection parameter to obtain corresponding echo signal data; potential pseudo-defect signals are analyzed and identified according to the echo signal data, and corresponding pseudo-defect feature values ​​are calculated according to the pseudo-defect signals, specifically including: The first detection parameters include the frequency range, scanning angle, scanning frequency and gain setting of the ultrasonic wave; For each inspection area, an ultrasonic inspection device is used to perform multi-frequency and multi-angle scanning on the weld in the inspection area according to a preset first inspection parameter; Receive and record echo signal data generated during the scanning process, wherein the echo signal data includes echo amplitude, phase and arrival time; The echo signal data is analyzed by using signal processing technology to identify potential false defect signals, and the corresponding initial false defect characteristic values ​​are calculated according to the characteristics of the false defect signals; The initial pseudo-defect characteristic value is compared with a preset pseudo-defect determination standard to obtain a comparison result, and the initial pseudo-defect characteristic value is optimized based on the comparison result to obtain a corresponding pseudo-defect characteristic value.

[0010] By adopting the above technical scheme, the first detection parameters such as the frequency range, scanning angle, scanning frequency and gain setting of the ultrasonic wave are set, and the weld in each detection area is scanned at multiple frequencies and multiple angles, which is conducive to capturing different types of echo signals, such as pseudo-defect signals caused by complex structures or surface characteristics. Compared with the scanning method of single frequency and angle, multi-frequency and multi-angle scanning significantly improves the ability to distinguish between real defects and pseudo-defects; the echo signal data provides a rich source of pseudo-defect gap information, thereby improving the reliability of defect identification of weld pseudo-defects; further, the echo signal data is deeply analyzed using signal processing technologies such as wavelet transform and Fourier transform, which can effectively extract characteristic information representing real defects, and can more accurately identify potential pseudo-defect signals, and calculate the initial pseudo-defect characteristic value based on its characteristics, thereby ensuring the basic data quality of the subsequent optimization process.

[0011] In a preferred example of the present application: based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each of the detection areas, the pseudo-defect status of the steel plate butt weld is comprehensively analyzed, specifically including: Acquire historical detection data, and acquire weld defect occurrence probability data based on the historical detection data; Defect impact degree data is calculated based on the pseudo-defect reliability evaluation data and the weld defect occurrence probability data.

[0012] By adopting the above technical solution, the pseudo-defect reliability assessment data is combined with the weld defect occurrence probability data, and the pseudo-defect impact data is calculated. By comprehensively considering multiple factors, such as the location, size, shape of the pseudo-defect and its performance under different working conditions, a more comprehensive and accurate assessment model is provided, which can not only identify the existence of pseudo-defects, but also quantify their potential impact on the overall structural safety, providing strong support for decision-making; by introducing a dual verification mechanism of historical data and pseudo-defect reliability assessment data, the misjudgment and missed detection problems that may be caused by relying solely on a single detection are greatly reduced, potential problems can be captured more comprehensively, and the robustness and reliability of the entire detection system are improved.

[0013] In a preferred example of the present application, the pseudo-defect feature analysis is performed based on each of the detection areas as a basic unit according to the preset second detection parameters to determine the reliability evaluation data of the pseudo-defect, specifically including: The second detection parameters include weld geometry complexity, welding process type, material properties, and environmental conditions; Divide the target detection area into average grids to determine all grids involved in a single detection area; Assign a value to each grid in a single detection area according to a 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 area to calculate the second detection parameter discrimination score of the single detection area; The reliability evaluation data of the pseudo defect is calculated using the comprehensive index method and the second detection parameter discrimination score.

[0014] By adopting the above technical solution, the geometric complexity of the weld, the type of welding process, the material properties and the environmental conditions are introduced as the second detection parameters, and the characteristics of the pseudo-defects are comprehensively evaluated from multiple dimensions, which not only considers the physical characteristics of the weld itself, but also combines the influence of external factors; the target detection area is divided into average grids to ensure that all grids in each detection area can be analyzed in detail. The rasterization processing method improves the spatial resolution and can capture more subtle structural changes. By extracting the arithmetic mean of the second grid scores of all grids, the second detection parameter discrimination score of a single detection area is calculated. The qualitative description is converted into quantitative data, so that the characteristics of the pseudo-defect can be accurately quantified, which enhances the scientificity and reliability of the evaluation.

[0015] In a preferred example of the present application, based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each of the detection areas, the pseudo-defect conditions of the steel plate butt weld are comprehensively analyzed to generate the final comprehensive evaluation result of the weld quality, specifically including: Taking each of the detection areas as a basic unit, the corresponding pseudo-defect impact degree data is used as row vector data, and the corresponding pseudo-defect reliability assessment data is used as column vector data, which are input into a preset quality assessment matrix to obtain corresponding weld quality grade data; According to the weld quality grade data corresponding to each of the detection areas, a comprehensive quality evaluation result of the entire steel plate butt weld is obtained; The welds are fully verified through multimodal nondestructive testing technology to obtain the final comprehensive evaluation results of the weld quality.

[0016] By adopting the above technical solution, a systematic mathematical model is used to evaluate the quality of welds. It not only takes into account the characteristics of pseudo-defects in a single inspection area, but also integrates the data of multiple inspection areas through matrix operations. According to the weld quality grade data corresponding to each inspection area, the comprehensive quality evaluation results of the entire steel plate butt weld are obtained, which is convenient for staff to quickly judge the overall quality status of the weld. Then, by combining various non-destructive testing technologies such as X-ray testing and magnetic particle testing, the weld is comprehensively verified to ensure the reliability and accuracy of the evaluation results. The mutual verification between different detection technologies can effectively reduce the misjudgment or missed detection problems that may be caused by a single technology.

[0017] In the second aspect, the invention objective of the present application is achieved by adopting the following technical solutions: The ultrasonic detection system for pseudo-defects of butt welds of steel plates uses the ultrasonic detection method for pseudo-defects of butt welds of steel plates as described above, and the system comprises: A data acquisition module, used to obtain structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and to set a plurality of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data; The ultrasonic scanning module uses each of the detection areas as a basic unit, uses an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter, and obtains corresponding echo signal data; and analyzes and identifies potential false defect signals according to the echo signal data, and calculates corresponding false defect characteristic values; A pseudo defect feature analysis module, taking each of the detection areas as a basic unit, performs pseudo defect feature analysis according to a preset second detection parameter, and determines reliability evaluation data of the pseudo defect; The comprehensive evaluation module comprehensively analyzes the pseudo-defect status of the steel plate butt weld based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each detection area, and generates a final comprehensive evaluation result of the weld quality.

[0018] By adopting the above technical solutions, the data acquisition module ensures comprehensive coverage of key parts of the weld and areas prone to potential defects, 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 those 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 problems 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 parameters (such as weld geometric complexity, welding process type, material properties, environmental conditions, etc.) to determine the reliability evaluation data of the pseudo-defects. Comprehensive evaluation module: The comprehensive evaluation module comprehensively analyzes the pseudo-defect status of the steel plate butt weld based on the pseudo-defect reliability evaluation data and pseudo-defect feature values ​​corresponding to each detection area, and generates the final comprehensive evaluation results of the weld quality. Through the combination of matrix evaluation model and multimodal non-destructive testing technology, the comprehensive evaluation module provides scientific, accurate and reliable evaluation results.

[0019] In the third aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for ultrasonic detection of pseudo-defects in butt welds of steel plates when executing the computer program.

[0020] In a fourth aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned ultrasonic detection method for pseudo-defects of butt welds of steel plates.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: 1. The multi-dimensional weld defect data collection method enables the system to more accurately distinguish between real defects and pseudo defects; further, by analyzing the defect characteristics of the echo signal, the potential pseudo defect signal is identified and its characteristic value is calculated, which provides a quantitative basis for the subsequent pseudo defect evaluation and improves the accuracy of identification. The pseudo defect characteristic analysis is performed according to the preset second detection parameter to determine the reliability evaluation data of the defect. Then, based on the pseudo defect reliability evaluation data and pseudo defect characteristic value corresponding to each detection area, a comprehensive analysis is performed to generate the final weld quality comprehensive evaluation result. The weld quality comprehensive evaluation result not only reflects the overall quality status of the weld, but also emphasizes the influence of pseudo defects, thereby realizing efficient and accurate detection of pseudo defects in steel plate butt welds, and effectively solving the problem of misjudgment or missed judgment in steel plate butt weld detection; 2. The geometric complexity of the weld, the type of welding process, the material properties and the environmental conditions are introduced as the second detection parameters to comprehensively evaluate the characteristics of pseudo defects from multiple dimensions, which not only considers the physical properties of the weld itself, but also combines the influence of external factors; the target detection area is averagely grid-divided to ensure that all grids in each detection area can be carefully analyzed. The gridding processing method improves the spatial resolution and can capture more subtle structural changes. By extracting the arithmetic mean of the second grid scores of all grids, the second detection parameter discrimination score of a single detection area is calculated, and the qualitative description is converted into quantitative data, so that the pseudo-defect characteristics can be accurately quantified, which enhances the scientificity and reliability of the evaluation. 3. A systematic mathematical model is used to evaluate the quality of welds, which not only takes into account the characteristics of pseudo-defects in a single inspection area, but also integrates the data of multiple inspection areas through matrix operations. According to the weld quality grade data corresponding to each inspection area, the comprehensive quality evaluation results of the entire steel plate butt weld are obtained, which is convenient for staff to quickly judge the overall quality status of the weld. Then, the weld is fully verified by combining various non-destructive testing technologies such as X-ray testing and magnetic particle testing to ensure the reliability and accuracy of the evaluation results. The mutual verification between different detection technologies can effectively reduce the misjudgment or missed detection problems that may be caused by a single technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a flow chart of a method for ultrasonically detecting pseudo-defects of butt welds of steel plates in one embodiment of the present application; Figure 2This is a flow chart of step S1 in a method for ultrasonically detecting pseudo-defects in butt welds of steel plates in one embodiment of the present application; Figure 3 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The present application is further described in detail below in conjunction with the accompanying drawings.

[0024] In one embodiment, if Figure 1 As shown, the present application discloses a method for ultrasonic detection of pseudo defects in butt welds of steel plates, which specifically includes the following steps: S1: obtaining structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and setting a plurality of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data.

[0025] In this embodiment, the structural parameters include but are not limited to geometric features such as the height, width, and inclination angle of the weld; the surface characteristic data include the roughness, cleanliness, coating condition, etc. of the weld surface.

[0026] Specifically, use laser scanners, 3D cameras or contact measurement tools to obtain the three-dimensional geometric data of the weld; obtain surface characteristic information through optical microscopes, surface profilers and other equipment, and the data collection accuracy must reach the millimeter level.

[0027] S2: Taking each detection area as a basic unit, use ultrasonic detection equipment to perform multi-frequency and multi-angle ultrasonic scanning according to the preset first detection parameters to obtain corresponding echo signal data; analyze and identify potential pseudo-defect signals based on the echo signal data, and calculate the corresponding pseudo-defect characteristic value based on the pseudo-defect signal.

[0028] In this embodiment, the first detection parameters include the frequency range of the ultrasonic wave (eg, 0.5 MHz to 10 MHz), the scanning angle (eg, 0 to 80°), the scanning speed, and the gain setting.

[0029] Specifically, according to the preset first detection parameter, the operating frequency and incident angle of the ultrasonic probe are adjusted, and in each detection area, multi-frequency and multi-angle scanning is performed using a phased array ultrasonic flaw detector to receive and record echo signal data; the echo signal data is analyzed in real time to identify potential pseudo-defect signals and calculate the corresponding pseudo-defect characteristic values. When scanning with an ultrasonic probe, a stable scanning speed and probe position must be maintained.

[0030] S3: Taking each detection area as a basic unit, performing pseudo-defect feature analysis according to a preset second detection parameter to determine reliability evaluation data of the pseudo-defect.

[0031] In this embodiment, the second detection parameters include weld geometric complexity, welding process type, material properties, environmental conditions, etc.; weld geometric complexity refers to the complexity of the weld structure, including but not limited to the height, width, inclination angle, and joint form (such as butt joint and fillet joint) of the weld; the 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., as well as process parameters such as welding current, voltage, and welding speed; material properties refer to the physical and chemical properties of the welding material, including but not limited to the strength, toughness, thermal expansion coefficient, thermal conductivity, etc. of the material; environmental conditions refer to the environmental factors during and after welding, such as temperature, humidity, corrosive media, external stress, etc.

[0032] Specifically, in step S3, it specifically includes: S31: Divide the target detection area into average grids to determine all grids involved in a single detection area.

[0033] In this embodiment, each inspection area is divided into a plurality of evenly distributed small units (grids). The selection of the grid size should take into account the geometric complexity of the weld and the resolution of the inspection equipment. It can be customized based on expert knowledge and experience to ensure that the data in each grid can represent the local characteristics of the area. That is, the appropriate grid size is selected based on the geometric dimensions of the weld and the expected inspection accuracy. The grid size should be small enough to capture subtle changes, but not so fine that it results in excessive calculation. A unique coordinate identifier is assigned to each grid to facilitate subsequent data processing and analysis.

[0034] S32: Assign a value to each grid in the single detection area according to the second detection parameter to obtain a second grid score.

[0035] In this 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 the evaluation is determined based on actual engineering experience and theoretical analysis.

[0036] S33: extracting the arithmetic mean of the second grid scores of all grids in a single detection area, and calculating the second detection parameter discrimination score of the single detection area.

[0037] 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.

[0038] For example, the welding quality of nuclear power plant pressure vessels is directly related to the safe operation of nuclear reactors. Due to the special working environment and extremely high requirements of nuclear power plants, any tiny weld defects may lead to serious safety hazards. When assigning grid parameters to pressure vessel welds, each grid is quantitatively evaluated and assigned corresponding scores based on the geometric complexity of the weld, welding process type, material properties and environmental conditions. For example, a higher weight is assigned to the grid in the high stress area.

[0039] S34: Reliability evaluation data of pseudo defects is obtained by calculating the comprehensive index method and the second detection parameter discrimination score.

[0040] Specifically, the comprehensive index method is usually used for multi-factor evaluation, and the calculation formula is: Where I is the composite index, ω i is the weight of the ith factor, x i is the branch of the ith factor, and n is the number of factors.

[0041] Suppose there is a detection area, which is divided into 5 grids. Each grid 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 comprehensive index method will be used to calculate the reliability evaluation data of the pseudo-defects in the detection area.

[0042] The existing second detection parameters are: Suppose we assign the following weights to each second detection parameter: Weld geometry complexity: 0.3; welding process type: 0.25; material properties: 0.25; environmental conditions: 0.2.

[0043] Calculate a composite index for each raster: For each grid, we multiply the score of the second detection parameter by the corresponding weight and then sum them up to get the comprehensive index.

[0044] Grid 1: I1 = (0.3×8) + (0.25×7) + (0.25×9) + (0.2×6) = 2.4 + 1.75 + 2.25 + 1.2 = 7.6.

[0045] Grid 2: I2 = (0.3×7) + (0.25×8) + (0.25×8) + (0.2×7) = 7.5.

[0046] Grid 3I3 = (0.3×9) + (0.25×9) + (0.25×9) + (0.2×8) = 8.7.

[0047] Grid 4: I4 = (0.3×6) + (0.25×7) + (0.25×7) + (0.2×6) = 6.6.

[0048] Grid 5: I5 = (0.3×8) + (0.25×8) + (0.25×8) + (0.2×7) = 7.8.

[0049] The formula for calculating the weighted average composite index is:

[0050] Assuming that the weight of each grid is the same, that is, the weight of each grid is 0.2, W = (0.2×7.6) + (0.2×7.5) + (0.2×8.7) + (0.2×6.6) + (0.2×7.8) / 1.0 = 7.64, so the pseudo-defect reliability evaluation data of the detection area is calculated to be 7.64.

[0051] S4: Based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each detection area, the pseudo-defect status of the steel plate butt weld is comprehensively analyzed to generate the final comprehensive evaluation result of the weld quality.

[0052] In this embodiment, the comprehensive analysis also includes an analysis method for comprehensive verification using multimodal nondestructive testing technology (including X-ray testing and magnetic particle testing).

[0053] Specifically, in step S4, it specifically includes: S41: Taking each detection area as a basic unit, the corresponding pseudo-defect impact degree data is used as row vector data, and the corresponding pseudo-defect reliability assessment data is used as column vector data, and they are input into a preset quality assessment matrix to obtain the corresponding weld quality grade data.

[0054] Specifically, the pseudo-defect impact degree data reflects the impact of pseudo-defects on the overall performance of the weld. Based on historical detection data and current detection results, the impact degree of pseudo-defects in each detection area on the overall performance of the weld is calculated, including but not limited to the location, size, shape of the pseudo-defects and their 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-defects in each detection area, and the weld quality grade data corresponds to each detection area, which can be expressed by letters or numbers, such as Grade A, Grade B, etc.

[0055] S42: Obtain a comprehensive quality evaluation result of the entire steel plate butt weld according to the weld quality grade data corresponding to each inspection area.

[0056] For example, the impact of pseudo defects is expressed in a range of 0 to 10; pseudo defect reliability assessment reflects the probability of the existence of pseudo defects and their potential impact on structural safety, ranging from 0 to 10.

[0057] First, design a quality assessment matrix Q, where each element q ij It represents the weld quality grade under the specific pseudo defect influence degree i and pseudo defect reliability evaluation j. The quality evaluation matrix Q is as follows: Among them, 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 impact data is taken as the row vector R, R = [8, 7, 9, 6, 8]; the pseudo-defect reliability evaluation data is taken as the column vector C, C = [7, 8, 9, 7, 8]. Next, find the corresponding value in the quality evaluation matrix, grid 1 (pseudo-defect impact 8, pseudo-defect reliability evaluation 7), find the position (8, 7) in the matrix, and get the quality level q 8，7 =H; for grid 2 (pseudo defect impact degree 7, pseudo defect reliability evaluation 8), find the position (7,8) in the matrix and get the quality level q 7，8 =H; for grid 3 (pseudo defect impact degree 9, pseudo defect reliability evaluation 9), find the position (9,9) in the matrix and get the quality level q 9，9 =M; for grid 4 (pseudo defect impact degree 6, pseudo defect reliability evaluation 7), find the position (6,7) in the matrix and get the quality level q 6，7 = G; for grid 5 (pseudo defect impact degree 8, pseudo defect reliability evaluation 8), find the position (8,8) in the matrix and get the quality level q 8，8 =H.

[0058] The comprehensive quality evaluation results are as follows: Grid 1: quality level H; Grid 2: quality level H; Grid 3: quality level M; Grid 4: quality level G; Grid 5: quality level H.

[0059] S43: The welds are fully verified through multimodal nondestructive testing technology to obtain the final comprehensive evaluation results of the weld quality.

[0060] In this embodiment, the multimodal nondestructive testing technology includes ultrasonic testing, X-ray testing, magnetic particle testing, penetration testing, etc.; the comprehensive evaluation result of the weld quality includes the specific conditions of each inspection area and a description of the overall quality status.

[0061] Specifically, choose appropriate nondestructive testing equipment and technology according to the specific situation.

[0062] In one embodiment, if Figure 2As shown, in step S1, the structural parameters and surface characteristic data of the steel plate butt weld to be inspected are obtained, and a number of inspection areas are set on the steel plate butt weld based on the structural parameters and surface characteristic data, specifically including: S11: Preprocessing the structural parameters and surface characteristic data of the butt weld of the steel plate to be inspected to obtain preprocessed structural parameters and surface characteristic data.

[0063] Specifically, data preprocessing includes cleaning the original data, removing noise and invalid data, data smoothing and data standardization, and unifying data of different dimensions to the same scale for subsequent analysis. S12: Based on the preprocessed structural parameters and surface characteristic data, the weld morphology analysis algorithm is used to identify the geometric features of the weld, where the geometric features include weld height, width and inclination angle.

[0064] In this embodiment, a suitable weld morphology analysis algorithm is selected according to specific needs, such as an edge detection algorithm (Canny, Sobel), a template matching algorithm or a convolutional neural network (CNN).

[0065] S13: According to the geometric characteristics of the weld and the predicted detection rules, a number of detection areas are divided on the weld, and the several detection areas cover the key parts of the weld and the areas prone to potential defects.

[0066] In this embodiment, the weld is divided into several detection areas based on the geometric features of the weld (such as height, width, and inclination angle), ensuring that the size and shape of each area are appropriate.

[0067] Specifically, areas located at the edge of the weld or with irregular shapes require special treatment to ensure the validity and representativeness of their data.

[0068] In one embodiment, in step S2, each detection area is taken as a basic unit, and multi-frequency and multi-angle ultrasonic scanning is performed using an ultrasonic detection device according to a preset first detection parameter to obtain corresponding echo signal data; the echo signal data is analyzed and identified as a potential pseudo defect signal, and the corresponding pseudo defect characteristic value is calculated according to the pseudo defect signal, specifically including: S21: The first detection parameters include the ultrasonic frequency range, scanning angle, scanning frequency and gain setting.

[0069] Specifically, the ultrasonic frequency range refers to the frequency range used in ultrasonic scanning, which is usually between 0.5MHz and 10MHz. Different frequencies are suitable for detecting different types of defects; the scanning angle refers to the angle of the ultrasonic probe relative to the weld surface, which is usually between 0° and 70°. 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 to ensure that all critical areas are covered; the gain setting refers to the sensitivity setting of the ultrasonic equipment, which affects the strength of the received signal.

[0070] S22: For each inspection area, according to a preset first inspection parameter, an ultrasonic inspection device is used to perform multi-frequency and multi-angle scanning on the weld in the inspection area.

[0071] S23: Receive and record echo signal data generated during the scanning process, where the echo signal data includes echo amplitude, phase and arrival time.

[0072] In this embodiment, the phase refers to the phase difference between the echo signal and the transmitted signal, which provides 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, which is used to calculate the defect location.

[0073] S24: Analyze the echo signal data using signal processing technology to identify potential pseudo defect signals, and calculate corresponding initial pseudo defect characteristic values ​​according to the characteristics of the pseudo defect signals.

[0074] In this embodiment, the initial pseudo defect feature value is based on the pseudo defect features initially identified by the echo signal, including position, size, shape, etc.

[0075] Specifically, the echo signal is preprocessed by denoising and smoothing to improve the signal quality, and filters, spectrum analysis tools or machine learning algorithms are applied to extract the key features of the pseudo-defect signal, such as amplitude, phase, arrival time, etc. The initial pseudo-defect feature value is calculated based on the extracted features.

[0076] S25: Compare the initial pseudo-defect characteristic value with a preset pseudo-defect determination standard to obtain a comparison result, and optimize the initial pseudo-defect characteristic value based on the comparison result to obtain a corresponding pseudo-defect characteristic value.

[0077] In this embodiment, the optimized pseudo defect characteristic value is compared with a preset standard and optimized to obtain a final pseudo defect characteristic value, which more accurately reflects the actual situation of the pseudo defect.

[0078] Specifically, based on a large amount of experimental data and expert opinions, pseudo-defect judgment standards are set, such as size thresholds, shape characteristics, etc.; the initial pseudo-defect characteristic values ​​are compared with preset standards to determine whether they meet the standards; for characteristic values ​​that do not meet the standards, further analysis and adjustment are carried out to ensure their authenticity and reliability. The result confirmation requires multiple verifications to ensure that it conforms to the actual situation.

[0079] In one embodiment, in step S4, specifically including: S401: Acquire historical inspection data, and acquire weld defect occurrence probability data based on the historical inspection data.

[0080] In this embodiment, relevant inspection reports, maintenance records and other historical data are collected, the collected data are cleaned and sorted, duplicate or invalid data are removed, and statistical analysis tools are used to analyze the sorted data to calculate the probability of defects in different types of welds under different working conditions. For example, it is found that welds at certain specific locations are more likely to crack in a high salt fog environment.

[0081] S402: Defect impact degree data is calculated based on pseudo-defect reliability evaluation data and weld defect occurrence probability data.

[0082] Specifically, the pseudo-defect reliability assessment data and the weld defect occurrence probability data are combined to form a basic data set for comprehensive assessment. The weights of the pseudo-defect reliability assessment data and the weld defect occurrence probability data in the impact degree assessment are determined based on actual engineering experience and theoretical analysis. The above data are processed using mathematical models (such as the comprehensive index method; in actual applications, the fuzzy evaluation method and the weighted average method can also be applied) to calculate the defect impact degree data for each inspection area.

[0083] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0084] In one embodiment, a steel plate butt weld pseudo-defect ultrasonic detection system is provided, and the steel plate butt weld pseudo-defect ultrasonic detection system corresponds to the steel plate butt weld pseudo-defect ultrasonic detection method in the above embodiment.

[0085] The ultrasonic detection system for false defects in steel plate butt welds includes a data acquisition module, an ultrasonic scanning module, a false defect feature analysis module and a comprehensive evaluation module. The detailed description of each functional module is as follows: A data acquisition module is used to obtain the structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and to set a number of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data; The ultrasonic scanning module uses each detection area as a basic unit, uses ultrasonic detection equipment to perform multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter, and obtains corresponding echo signal data; and analyzes and identifies potential false defect signals according to the echo signal data, and calculates the corresponding false defect characteristic value; A pseudo defect feature analysis module, taking each detection area as a basic unit, performs pseudo defect feature analysis according to a preset second detection parameter, and determines reliability evaluation data of the pseudo defect; The comprehensive evaluation module comprehensively analyzes the pseudo-defect status of the steel plate butt weld based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each detection area, and generates the final comprehensive evaluation results of the weld quality.

[0086] Optionally, the data acquisition module includes: Preprocessing submodule: preprocess the structural parameters and surface characteristic data of the butt weld of the steel plate to be tested to obtain the preprocessed structural parameters and surface characteristic data; Morphological analysis submodule: Based on the preprocessed structural parameters and surface characteristic data, the weld morphological analysis algorithm is used to identify the geometric features of the weld, including weld height, width and inclination angle; Area division submodule: According to the geometric characteristics of the weld and the predicted detection rules, several detection areas are divided on the weld, and the several detection areas cover the key parts of the weld and the areas prone to potential defects.

[0087] For the specific limitations of the ultrasonic detection system for pseudo-defects in steel plate butt welds, please refer to the limitations on the ultrasonic detection method for pseudo-defects in steel plate butt welds mentioned above, which will not be repeated here; the various modules in the above-mentioned ultrasonic detection system for pseudo-defects in steel plate butt welds can be fully or partially implemented through software, hardware and their combination; the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of the above-mentioned modules.

[0088] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, 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 operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store structural parameters, surface characteristic data and reliability evaluation data of pseudo defects of steel plate butt welds. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for ultrasonic detection of pseudo defects in steel plate butt welds is implemented.

[0089] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: S1: obtaining structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and setting a number of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data; S2: Taking each detection area as a basic unit, using ultrasonic detection equipment 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; S3: Taking each detection area as a basic unit, performing pseudo-defect feature analysis according to a preset second detection parameter to determine reliability evaluation data of the pseudo-defect; S4: Based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each detection area, the pseudo-defect status of the steel plate butt weld is comprehensively analyzed to generate the final comprehensive evaluation result of the weld quality.

[0090] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: S1: obtaining structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and setting a number of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data; S2: Taking each detection area as a basic unit, using ultrasonic detection equipment 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; S3: Taking each detection area as a basic unit, performing pseudo-defect feature analysis according to a preset second detection parameter to determine reliability evaluation data of the pseudo-defect; S4: Based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each detection area, the pseudo-defect status of the steel plate butt weld is comprehensively analyzed to generate the final comprehensive evaluation result of the weld quality.

[0091] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this 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 and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), 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).

[0092] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0093] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for ultrasonically detecting pseudo defects in butt welds of steel plates, characterized in that: include: Acquire structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and set a plurality of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data; Taking each of the detection areas 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; Taking each of the detection areas as a basic unit, performing pseudo-defect feature analysis according to a preset second detection parameter to determine reliability evaluation data of the pseudo-defect; Based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each of the detection areas, the pseudo-defect conditions of the steel plate butt weld are comprehensively analyzed to generate a final comprehensive evaluation result of the weld quality.

2. The method for ultrasonic detection of pseudo defects in butt welds of steel plates according to claim 1, characterized in that: The step of obtaining structural parameters and surface characteristic data of the butt weld of the steel plates to be inspected, and setting a plurality of inspection areas on the butt weld of the steel plates based on the structural parameters and surface characteristic data, specifically includes: Preprocessing the structural parameters and surface characteristic data of the butt weld of the steel plate to be tested to obtain preprocessed structural parameters and surface characteristic data; Based on the pre-processed structural parameters and surface characteristic data, the weld morphology 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 number of detection areas are divided on the weld, and the several detection areas cover the key parts of the weld and the areas prone to potential defects.

3. The method for ultrasonic detection of pseudo defects in butt welds of steel plates according to claim 1, characterized in that: Taking each of the detection areas 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 specifically include: The first detection parameters include the frequency range, scanning angle, scanning frequency and gain setting of the ultrasonic wave; For each inspection area, an ultrasonic inspection device is used to perform multi-frequency and multi-angle scanning on the weld in the inspection area according to a preset first inspection parameter; Receive and record echo signal data generated during the scanning process, wherein the echo signal data includes echo amplitude, phase and arrival time; The echo signal data is analyzed by using signal processing technology to identify potential false defect signals, and the corresponding initial false defect characteristic values ​​are calculated according to the characteristics of the false defect signals; The initial pseudo-defect characteristic value is compared with a preset pseudo-defect determination standard to obtain a comparison result, and the initial pseudo-defect characteristic value is optimized based on the comparison result to obtain a corresponding pseudo-defect characteristic value.

4. The method for ultrasonic detection of pseudo defects in butt welds of steel plates according to claim 1, characterized in that: The pseudo-defect status of the steel plate butt weld is comprehensively analyzed based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each of the detection areas, specifically including: Acquire historical detection data, and acquire weld defect occurrence probability data based on the historical detection data; Defect impact degree data is calculated based on the pseudo-defect reliability evaluation data and the weld defect occurrence probability data.

5. The method for ultrasonically detecting pseudo defects of steel plate butt welds according to claim 1, characterized in that: The method of taking each of the detection areas as a basic unit and performing pseudo defect feature analysis according to a preset second detection parameter to determine the pseudo defect reliability evaluation data specifically includes: The second detection parameters include weld geometry complexity, welding process type, material properties, and environmental conditions; Divide the target detection area into average grids to determine all grids involved in a single detection area; Assign a value to each grid in a single detection area according to a 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 area to calculate the second detection parameter discrimination score of the single detection area; The reliability evaluation data of the pseudo defect is calculated using the comprehensive index method and the second detection parameter discrimination score.

6. The method for ultrasonic detection of pseudo defects in butt welds of steel plates according to claim 1, characterized in that: Based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each detection area, the pseudo-defect status of the steel plate butt weld is comprehensively analyzed to generate the final comprehensive evaluation result of the weld quality, specifically including: Taking each of the detection areas as a basic unit, the corresponding pseudo-defect impact degree data is used as row vector data, and the corresponding pseudo-defect reliability assessment data is used as column vector data, which are input into a preset quality assessment matrix to obtain corresponding weld quality grade data; According to the weld quality grade data corresponding to each of the detection areas, a comprehensive quality evaluation result of the entire steel plate butt weld is obtained; The welds are fully verified through multimodal nondestructive testing technology to obtain the final comprehensive evaluation results of the weld quality.

7. Ultrasonic detection system for false defects of steel plate butt welds, characterized by: The method for ultrasonically detecting pseudo-defects of butt welds of steel plates as claimed in any one of claims 1 to 6 is applied, wherein the system comprises: A data acquisition module, used to obtain structural parameters and surface characteristic data of the steel plate butt weld to be inspected, and to set a plurality of inspection areas on the steel plate butt weld based on the structural parameters and surface characteristic data; The ultrasonic scanning module uses each of the detection areas as a basic unit, uses an ultrasonic detection device to perform multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter, and obtains corresponding echo signal data; and analyzes and identifies potential false defect signals according to the echo signal data, and calculates corresponding false defect characteristic values; A pseudo defect feature analysis module, taking each of the detection areas as a basic unit, performs pseudo defect feature analysis according to a preset second detection parameter, and determines reliability evaluation data of the pseudo defect; The comprehensive evaluation module comprehensively analyzes the pseudo-defect status of the steel plate butt weld based on the pseudo-defect reliability evaluation data and pseudo-defect characteristic values ​​corresponding to each detection area, and generates a final comprehensive evaluation result of the weld quality.

8. The steel plate butt weld pseudo-defect ultrasonic detection system according to claim 7, characterized in that: The data acquisition module specifically includes: Preprocessing submodule: preprocessing the structural parameters and surface characteristic data of the butt weld of the steel plate to be tested to obtain preprocessed structural parameters and surface characteristic data; Morphological analysis submodule: Based on the preprocessed structural parameters and surface characteristic data, the weld morphological analysis algorithm is used to identify the geometric features of the weld, including the weld height, width and inclination angle; Area division submodule: According to the geometric characteristics of the weld and the predicted detection rules, a number of detection areas are divided on the weld, and the several detection areas cover the key parts of the weld and the areas prone to potential defects.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for ultrasonic detection of pseudo-defects in butt welds of steel plates as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for ultrasonically detecting pseudo-defects of butt welds of steel plates as claimed in any one of claims 1 to 6 are implemented.

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