Pipeline welding seam nondestructive testing method and system based on ultrasonic technology

Abstract

The invention relates to the technical field of analyzing materials by utilizing an ultrasonic technology, in particular to a pipeline welding seam nondestructive testing method and system based on the ultrasonic technology, and the method comprises the following steps: acquiring echo signals collected by each ultrasonic probe at a welding seam position of a pipeline; analyzing the similarity degree of the time domain local features of the echo signals of each ultrasonic probe and the ultrasonic probe at the adjacent position under the same wavelet transform scale, and determining position similar probes and position similar parameters of each ultrasonic probe; according to the position similar parameters of the ultrasonic probe and the change difference of the echo signals of the ultrasonic probe and the corresponding position similar probe under each scale, determining a correction coefficient under each scale, and correcting a detail coefficient of the echo signals of the ultrasonic probe under each scale; obtaining a reconstruction signal based on the corrected detail coefficient under each scale; and comparing the reconstruction signal of each ultrasonic probe with the standard echo signal to detect the weld defect. By adopting the method, false detection and missing detection of tiny defects can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of analyzing materials using ultrasonic technology, and particularly to a non-destructive testing method and system for pipeline welds based on ultrasonic technology. Background Art

[0002] Pipelines are often used to transport liquids, gases or other chemical substances and are widely used in industrial fields such as petroleum, natural gas and chemical engineering. During the construction process of pipeline projects, the quality control of welds at pipeline bends is crucial. As the key connection part of the pipeline, the quality of welds directly affects the operation efficiency and safety performance of the entire pipeline system. Any minor defect may lead to serious safety accidents such as leakage and explosion. Only by detecting and repairing weld defects in a timely manner can the safe operation of pipeline projects be ensured.

[0003] Common defect types at pipeline welds include cracks, lack of penetration, uneven fusion line structure and base metal folding, etc. Using ultrasonic technology for non-destructive testing can comprehensively detect all welds without damaging the welds. By performing 100% non-destructive testing on welds, potential defects can be discovered and repaired, ensuring that the welds meet the specified standards and design requirements, improving the detection efficiency, and thus enhancing the quality and reliability of the entire pipeline system.

[0004] In ultrasonic-based weld detection, weld defects of welded pipes are manifested in the form of waveform changes. Due to various factors such as environmental noise and electrical interference, the signal data received by ultrasonic probes often contains a large amount of noise components. These noise interferences will seriously affect the identification of minor defects, resulting in problems such as defect misidentification and missed detection. Summary of the Invention

[0005] In order to solve the technical problem of defect misidentification and missed detection caused by noise interference, the purpose of the present invention is to provide a non-destructive testing method and system for pipeline welds based on ultrasonic technology, and the specific technical solutions adopted are as follows: The present invention provides a non-destructive testing method for pipeline welds based on ultrasonic technology, and the method includes: Obtaining echo signals collected by each ultrasonic probe at the weld position of the pipeline; Analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, and determining the position similar probes and position similar parameters of each ultrasonic probe; Determining the correction coefficient at each scale according to the position similar parameters of the ultrasonic probe and the change differences of the echo signals of the ultrasonic probe and the corresponding position similar probes at each scale; Respectively correct the detail coefficients of the echo signals of the ultrasonic probe at each scale according to the correction coefficients at each scale; Perform inverse wavelet transform based on the corrected detail coefficients at each scale to obtain a reconstructed signal; Compare the reconstructed signals of each ultrasonic probe with the standard echo signal respectively to perform weld defect detection.

[0006] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, and determining the position similar probes and position similar parameters of each ultrasonic probe, including: For each ultrasonic probe respectively, analyze the similarity degree of the time-domain local features of the echo signals of the ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, and obtain the position correlation between the echo signal of the ultrasonic probe and the echo signals of each adjacent position ultrasonic probe; Take the maximum value in the position correlations as the position similar parameter, and determine the adjacent position ultrasonic probe corresponding to the maximum value as the position similar probe.

[0007] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, analyzing the similarity degree of the time-domain local features of the echo signals of the ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, and obtaining the position correlation between the echo signal of the ultrasonic probe and the echo signals of each adjacent position ultrasonic probe, including: Calculate the overlapping degree and waveform shape similarity between the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions at the same wavelet transform scale; Determine the position correlation between the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions according to the overlapping degree and the waveform shape similarity.

[0008] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, before determining the correction coefficients at each scale according to the position similar parameters of the ultrasonic probe and the change differences of the echo signals of the ultrasonic probe and the corresponding position similar probes at each scale, the method further includes: Determine the signal correction factors of the echo signals of each ultrasonic probe at each level according to the detail coefficients of the echo signals of each ultrasonic probe at each level of the wavelet transform scale; For each of the ultrasonic probes, based on the differences between the signal correction factors of the ultrasonic probe and the corresponding position-similar probe at each level, determine the variation differences of the echo signals of the ultrasonic probe and the corresponding position-similar probe at each scale.

[0009] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, the determining of the signal correction factors of the echo signals of each ultrasonic probe at each level according to the detail coefficients of the echo signals of each ultrasonic probe at each level of the wavelet transform scale includes: For each of the ultrasonic probes, based on the detail coefficients of the echo signal of the ultrasonic probe at each level of the wavelet transform scale, determine the degree of signal energy fluctuation at each level; Based on the degree of signal energy fluctuation at each level, determine the mutation levels; Determine the degree of uneven attenuation of the local peaks existing at the same target time in each of the mutation levels; Based on the degree of signal energy fluctuation and the degree of uneven attenuation, determine the signal correction factors of the echo signals of the ultrasonic probe at each level.

[0010] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, the determining of the degree of signal energy fluctuation at each level according to the detail coefficients of the echo signal of the ultrasonic probe at each level of the wavelet transform scale includes: Based on the detail coefficients of the echo signal of the ultrasonic probe at each moment at each level of the wavelet transform scale, determine the signal energy at each moment at each level; Respectively determine the energy value span of the signal energy at each moment in each level; Based on the sum of the energy value spans at each level, determine the total energy value span; For each level, based on the proportion of the energy value span of the level in the total energy value span, determine the degree of signal energy fluctuation of the level.

[0011] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, the determining of the degree of uneven attenuation of the local peaks existing at the same target time in each of the mutation levels includes: Perform local peak detection on each of the mutation levels to determine the local wave peaks at several moments in each of the mutation levels; Screen the local wave peaks existing at the same target time in each of the mutation levels to obtain a candidate wave peak set; Determine the degree of uneven attenuation of the local wave peaks in the candidate wave peak set as the level changes.

[0012] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, determining the degree of non-uniform attenuation of the local peaks in the candidate peak set as the level changes includes: Determining the difference between the local peaks of each group of adjacent levels in the candidate peak set; Determining the signal mean value at the target moment in the candidate peak set; Determining the exponential decay factor of the candidate peak set according to the signal mean value; Determining the degree of non-uniform attenuation of the local peaks in the candidate peak set as the level changes according to the ratio of the difference between the local peaks of each group of adjacent levels to the exponential decay factor.

[0013] According to the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention, comparing the reconstructed signals of each ultrasonic probe with the standard echo signal respectively to perform weld defect detection includes: Comparing the reconstructed signals of each ultrasonic probe with the standard echo signal respectively to establish a defect feature model; Judging whether there is a defect in the weld according to the defect feature model; If there is a defect, determining the type, position and size of the defect.

[0014] The present invention provides a pipeline weld non-destructive testing system based on ultrasonic technology. The system includes a memory and a processor; the memory is used to store executable program codes; the processor is used to call and run the executable program codes from the memory to implement the pipeline weld non-destructive testing method based on ultrasonic technology provided by the present invention.

[0015] The present invention has the following beneficial effects: By analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, finding the position-similar probes of each ultrasonic probe and determining the position-similarity parameters, and then determining the correction coefficients at each scale according to the position-similarity parameters of the ultrasonic probes and the change differences of the echo signals of the ultrasonic probes and the corresponding position-similar probes at each scale, correcting the detail coefficients of the echo signals of the ultrasonic probes at each scale, and performing inverse wavelet transform based on the corrected detail coefficients at each scale to obtain the reconstructed signal, so that tiny defect signals can be retained in the reconstructed signal, avoiding the problem of easy misdetection and missed detection of tiny defects caused by directly deleting the high-frequency components according to the original detail coefficients, and improving the accuracy of defect detection for welds. Description of the Drawings

[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0017] Figure 1 Schematic flowchart of a pipeline weld non-destructive testing method based on ultrasonic technology provided by an embodiment of the present invention; Figure 2 Schematic waveform diagram of the first group of echo signals provided by an embodiment of the present invention; Figure 3 Schematic waveform diagram of the second group of echo signals provided by an embodiment of the present invention; Figure 4 Schematic waveform diagram of the third group of echo signals provided by an embodiment of the present invention; Figure 5 Schematic waveform diagram of the fourth group of echo signals provided by an embodiment of the present invention; Figure 6 Schematic diagram of the wavelet transform process provided by an embodiment of the present invention; Figure 7 Schematic overall flowchart of a pipeline weld non-destructive testing method based on ultrasonic technology provided by an embodiment of the present invention; Figure 8 Schematic structural diagram of a pipeline weld non-destructive testing system based on ultrasonic technology provided by an embodiment of the present invention. Detailed implementation manners

[0018] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in combination with the accompanying drawings and preferred embodiments, detail the specific implementation manners, structures, features, and effects of a pipeline weld non-destructive testing method and system based on ultrasonic technology proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0020] The following will specifically describe the specific solutions of a pipeline weld non-destructive testing method and system based on ultrasonic technology provided by the present invention in combination with the accompanying drawings.

[0021] Please refer toFigure 1 , which shows a schematic flow chart of a non-destructive testing method for pipeline welds based on ultrasonic technology provided by an embodiment of the present invention, including the following steps: Step 102, obtain the echo signals collected by each ultrasonic probe at the weld position of the pipeline.

[0022] In one embodiment, a phased array ultrasonic testing device can be used. Place the phased array ultrasonic probe on the outer surface of the weld. The ultrasonic probe is closely attached to the weld surface to ensure no air bubbles or gaps, covering the entire detection area of the weld. Detect the weld position of the pipeline and collect a set of ultrasonic echo signals at the weld position. Each set of echo signals includes a time series and corresponding amplitude information.

[0023] Figure 2 , Figure 3 , Figure 4 and Figure 5 respectively show the waveform schematic diagrams of 4 sets of echo signals, which respectively represent the echo signals collected by ultrasonic probes at different positions.

[0024] In one embodiment, the echo signals can be corrected in the time domain by adjusting the time reference of the signals to eliminate the error at the measurement moment and obtain the accurate echo signals at the corresponding moments.

[0025] Step 104, analyze the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, and determine the position similar probes and position similar parameters of each ultrasonic probe.

[0026] Among them, the ultrasonic probes at adjacent positions refer to the two ultrasonic probes adjacent to a certain ultrasonic probe. The position similar parameter characterizes the similarity degree of the time-domain local features of the echo signals of the ultrasonic probe and the corresponding position similar probe at the same wavelet transform scale.

[0027] It can be understood that for the ultrasonic probes arranged in a circular array, due to the similar materials in the pipeline weld area, the signal propagation paths of the probes at different positions are roughly similar, and in the same weld area, the scanning areas of the adjacent probes overlap, and there is similarity in the echo signals obtained from the probes at different positions. Therefore, by performing similarity analysis on the echo signals of the ultrasonic probes arranged in a circular array, the position similar probes of each ultrasonic probe can be found, and further signal denoising analysis can be carried out by combining the similar features shown by the echo signals of the ultrasonic probe and the corresponding position similar probe in the same weld area.

[0028] In one embodiment, the Daubechies wavelet (db4) can be selected as the wavelet basis function, the decomposition level is set to n levels, and the collected echo signal is subjected to wavelet transform to obtain a series of wavelet coefficients at different scales. The wavelet coefficients include the approximation coefficients (original approximation coefficients) and detail coefficients (original detail coefficients) at each scale level. Among them, the approximation coefficients contain the main features of the echo signal, and the detail coefficients reflect the change details of the echo signal. As Figure 6 shown, the process of decomposing the echo signal by wavelet transform can be represented as a tree structure composed of a low-pass filter and a high-pass filter. Among them, LPF represents the low-pass filter, HPF represents the high-pass filter, L1, L2, and L3 respectively represent the low-frequency components at different scales, H represents the high-frequency component of the original signal (the echo signal before wavelet transform), H1, H2, and H3 respectively represent the high-frequency components at different scales, S represents the original signal, and the decomposed cA1, cA2, and cA3 respectively represent the approximation coefficients of the low-frequency components at different scales, and cD1, cD2, and cD3 respectively represent the detail coefficients of the high-frequency components at different scales.

[0029] Step 106: Determine the correction coefficients at each scale according to the position similarity parameters of the ultrasonic probe and the change differences of the echo signals of the ultrasonic probe and the corresponding position-similar probes at each scale.

[0030] In one embodiment, the signal correction factors of the echo signal of the ultrasonic probe at each scale level can be calculated, and then the change differences of the echo signals of the ultrasonic probe and the corresponding position-similar probes at each scale can be determined according to the differences between the signal correction factors of the ultrasonic probe and the corresponding position-similar probes at each level.

[0031] In one embodiment, the correction coefficients at each scale can be determined according to the ratio between the position similarity parameters of the ultrasonic probe and the change differences at each scale.

[0032] In one embodiment, the correction coefficients at each scale can be determined according to the following formula: where, represents the correction coefficient at the jth scale. represents the normalization process. represents the position similarity parameter of the ultrasonic probe at the bth position. represents the signal correction factor of the ultrasonic probe at the jth scale level. represents the signal correction factor of the position-similar probe of the ultrasonic probe at the jth scale level. It represents the difference in the signal correction factor of the echo signals of the ultrasonic probe and the echo signals of the corresponding position-similar probes at the j-th scale level, and is used to measure the change difference of the echo signals of the ultrasonic probe and the corresponding position-similar probes at the same scale. The smaller the difference, the greater the similarity of the change of the mutation signals in the echo signals, and the greater the possibility that the mutation signals belong to the defect signals. Then, the greater the degree to which the detail coefficients of the echo signals of the ultrasonic probe need to be enhanced. It represents a minimum hyperparameter, which is used to avoid the situation where the denominator is equal to 0.

[0033] It can be understood that since when the interference noise shows signal energy with the same frequency as the defect, the correction purpose cannot be accurately achieved based on the signal change at a single position, and different probe positions will result in different degrees of noise interference in the collected signals. Therefore, there are obvious differences in the detail coefficients of the signal decomposition at different positions. However, when the probe positions are similar, due to the overlap of the detection areas, the energy manifestation degrees of the ultrasonic signals when scanning the same small defect area are relatively consistent. Therefore, the consistency of the similar signals in the wavelet transform can be used for denoising. Therefore, in the above embodiments, by combining the position similarity parameters between the position-similar probes and the change differences of the echo signals at each scale, the signal attenuation correlation between the similar positions is determined as the correction coefficient, so as to accurately distinguish which parts are noise and which parts are the details of the small defect areas, accurately correct the detail coefficients, reduce the denoising strength in the areas with strong small defect signals, and enhance the denoising effect in the areas with strong noise.

[0034] Step 108: Respectively correct the detail coefficients of the echo signals of the ultrasonic probe at each scale according to the correction coefficients at each scale.

[0035] In one embodiment, the corrected detail coefficient at this scale can be determined according to the product of the correction coefficient at the same scale and the original detail coefficient (i.e., the detail coefficient before correction).

[0036] In one embodiment, the detail coefficients of the echo signals of the ultrasonic probe at each scale can be corrected according to the following formula: Wherein, represents the detail coefficient at the k-th moment at the j-th scale level after correction. represents the correction coefficient at the j-th scale level. represents the original detail coefficient (i.e., the detail coefficient before correction) at the k-th moment at the j-th scale level.

[0037] Step 110: Perform inverse wavelet transform based on the corrected detail coefficients at each scale to obtain a reconstructed signal.

[0038] In one embodiment, an inverse wavelet transform can be performed on the corrected detail coefficients and the original approximation coefficients at each scale to obtain a reconstructed signal.

[0039] In one embodiment, the reconstructed signal can be determined according to the following formula: where, represents the reconstructed signal. represents the detail coefficient at the k-th moment in the j-th scale level after correction. represents the original approximation coefficient at the k-th moment in the j-th scale level. represents the selected wavelet basis function. represents the decomposition scale function.

[0040] Step 112, compare the reconstructed signals of each ultrasonic probe with the standard echo signal respectively for weld defect detection.

[0041] Among them, weld defect detection is used to determine whether there are defects in the weld, as well as the type, location and size of the defects.

[0042] In the above non-destructive testing method for pipeline welds based on ultrasonic technology, by analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, the position-similar probes of each ultrasonic probe are found and the position-similarity parameters are determined. Then, according to the position-similarity parameters of the ultrasonic probes and the variation differences of the echo signals of the ultrasonic probes and the corresponding position-similar probes at each scale, the correction coefficients at each scale are determined, and the detail coefficients of the echo signals of the ultrasonic probes at each scale are corrected. An inverse wavelet transform is performed based on the corrected detail coefficients at each scale to obtain a reconstructed signal, so that tiny defect signals can be retained in the reconstructed signal, avoiding the problem of easy misdetection and missed detection of tiny defects caused by directly deleting high-frequency components according to the original detail coefficients, and improving the accuracy of defect detection for welds.

[0043] In one embodiment, analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale, and determining the position-similar probes and position-similarity parameters of each ultrasonic probe includes: respectively for each ultrasonic probe, analyzing the similarity degree of the time-domain local features of the echo signals of the ultrasonic probe and the ultrasonic probes at adjacent positions at the same wavelet transform scale to obtain the position correlation between the echo signal of the ultrasonic probe and the echo signals of each adjacent-position ultrasonic probe; taking the maximum value in the position correlation as the position-similarity parameter, and determining the adjacent-position ultrasonic probe corresponding to the maximum value as the position-similar probe.

[0044] With Figure 3Taking the echo signal of the ultrasonic probe at the b-th position as an example, for the echo signals of ultrasonic probes at different positions, in the time domain after wavelet transform, the echo signals of ultrasonic probes at adjacent positions show a certain waveform similarity in the local characteristics of the time domain. When the propagation path of the echo signal and the nature of the defect are the same, the mutation of the echo signal at a certain moment shows a similar pattern at different positions. For example, the reflections of the defect show a similar pattern at different positions. For example: Figure 3 and Figure 4 the mutation at a certain moment in shows a similar pattern. Therefore, by analyzing the echo signal b(t) of the ultrasonic probe at the b-th position (i.e., Figure 3 the echo signal shown) and the echo signals a(t) and c(t) of the ultrasonic probes at adjacent positions (i.e., the ultrasonic probe at the a-th position and the ultrasonic probe at the c-th position) (i.e., Figure 2 and Figure 4 the echo signals shown), in the local characteristics of the time domain under the same wavelet transform scale, the position-similar probes of the ultrasonic probe at the b-th position can be determined from the ultrasonic probes at the a-th position and the c-th position.

[0045] In one embodiment, the position-similarity parameter can be determined according to the following formula: where, represents the position-similarity parameter corresponding to the ultrasonic probe at the b-th position. represents the position correlation between the echo signal of the ultrasonic probe at the b-th position and the echo signal of the ultrasonic probe at the a-th position. represents the position correlation between the echo signal of the ultrasonic probe at the b-th position and the echo signal of the ultrasonic probe at the c-th position. represents taking the maximum value.

[0046] In the above embodiment, by analyzing the similarity degree of the local characteristics of the time domain of the echo signals of the ultrasonic probe and the ultrasonic probes at adjacent positions under the same wavelet transform scale, the position correlations between the echo signal of the ultrasonic probe and the echo signals of each adjacent-position ultrasonic probe are obtained. Then, the maximum value in the position correlations is used as the position-similarity parameter, and the adjacent-position ultrasonic probe corresponding to the maximum value is determined as the position-similar probe, so that the position-similar probes and position-similarity parameters corresponding to each ultrasonic probe can be accurately determined.

[0047] In one embodiment, the similarity degree of the time-domain local features of the echo signals of the analysis ultrasound probe and the adjacent-position ultrasound probes at the same wavelet transform scale is analyzed to obtain the position correlation between the echo signal of the ultrasound probe and the echo signals of the adjacent-position ultrasound probes respectively, including: calculating the overlapping degree and the waveform shape similarity between the echo signal of the ultrasound probe and the echo signals of the adjacent-position ultrasound probes at the same wavelet transform scale; and determining the position correlation between the echo signal of the ultrasound probe and the echo signals of the adjacent-position ultrasound probes according to the overlapping degree and the waveform shape similarity.

[0048] In one embodiment, the overlapping degree can be determined according to the integral result of the product of the echo signal of the ultrasound probe and the echo signals of the adjacent-position ultrasound probes at the same wavelet transform scale.

[0049] In one embodiment, the waveform shape similarity can be determined according to the DTW distance (Dynamic Time Warping distance) between the echo signal of the ultrasound probe and the echo signals of the adjacent-position ultrasound probes at the same wavelet transform scale.

[0050] In one embodiment, the position correlation can be determined according to the ratio between the overlapping degree and the waveform shape similarity.

[0051] In one embodiment, the position correlation can be determined according to the ratio of the integral result of the product of the echo signal of the ultrasound probe and the echo signals of the adjacent-position ultrasound probes at the same wavelet transform scale to the DTW distance. It can be understood that processing the mutual property (i.e., the integral result of the product) between two echo signals with the DTW distance to reduce the influence of the data amplitude on the waveform can calculate the position correlation of the echo signals more accurately.

[0052] In one embodiment, taking the ultrasound probe at the b-th position as an example, the position correlation between the echo signal of the ultrasound probe and the echo signals of the adjacent-position ultrasound probes can be calculated according to the following formula: Wherein, represents the position correlation between the echo signal of the ultrasound probe at the b-th position and the echo signal of the ultrasound probe at the a-th position. represents the echo signal data amplitude of the echo signal of the ultrasound probe at the b-th position at the t-th moment. represents the echo signal data amplitude of the echo signal of the ultrasound probe at the a-th position at the moment. is used to measure the overlapping degree between the echo signal of the ultrasound probe at the b-th position and the echo signal of the ultrasound probe at the a-th position at the same wavelet transform scale. represents the echo signal and The DTW distance between them. Represents a minimum value hyperparameter used to avoid the denominator being equal to 0.

[0053] And so on. The position correlation between the echo signal of the ultrasonic probe at the b-th position and the echo signal of the ultrasonic probe at the c-th position can be calculated using the same principle.

[0054] In the above embodiment, by calculating the overlap degree and waveform shape similarity between the echo signal of the ultrasonic probe and the echo signal of the ultrasonic probe at the adjacent position under the same wavelet transform scale, and then based on the overlap degree and waveform shape similarity, the influence of the data amplitude on the waveform can be reduced, thereby accurately determining the position correlation between the echo signal of the ultrasonic probe and the echo signal of the ultrasonic probe at the adjacent position.

[0055] In one embodiment, before determining the correction coefficient at each scale according to the position similarity parameter of the ultrasonic probe and the change difference of the echo signals of the ultrasonic probe and the corresponding position similarity probe at each scale, the method further includes: determining the signal correction factor of the echo signal of each ultrasonic probe at each level according to the detail coefficient of the echo signal of each ultrasonic probe at each level of the wavelet transform scale; for each ultrasonic probe respectively, determining the change difference of the echo signals of the ultrasonic probe and the corresponding position similarity probe at each scale according to the difference between the signal correction factors of the ultrasonic probe and the corresponding position similarity probe at each level.

[0056] In the above embodiment, by determining the signal correction factor of the echo signal of each ultrasonic probe at each level according to the detail coefficient of the echo signal of each ultrasonic probe at each level of the wavelet transform scale, the change situation of the echo signal can be accurately measured. Then, according to the difference between the signal correction factors of the ultrasonic probe and the corresponding position similarity probe at each level, the change difference of the echo signals of the ultrasonic probe and the corresponding position similarity probe at each scale can be accurately determined. The smaller the difference, the greater the similarity of the change of the mutation signal in the echo signal, and the greater the possibility that the mutation signal belongs to the defect signal. Therefore, the greater the degree to which the detail coefficient of the echo signal of the ultrasonic probe needs to be enhanced. Thus, the correction coefficient can be accurately determined according to the accurate change difference.

[0057] In one embodiment, according to the detail coefficients of the echo signals of each ultrasonic probe at each level of the wavelet transform scale, determining the signal correction factors of the echo signals of each ultrasonic probe at each level includes: for each ultrasonic probe, determining the degree of signal energy fluctuation at each level according to the detail coefficients of the echo signal of the ultrasonic probe at each level of the wavelet transform scale; determining the mutation level according to the degree of signal energy fluctuation at each level; determining the degree of uneven attenuation of the local peaks existing at the same target time at each mutation level; and determining the signal correction factors of the echo signals of the ultrasonic probe at each level according to the degree of signal energy fluctuation and the degree of uneven attenuation.

[0058] In one embodiment, the signal energy at each moment at each level can be determined according to the detail coefficients of the echo signal of the ultrasonic probe at each level of the wavelet transform scale, and then the degree of signal energy fluctuation at each level can be determined according to the signal energy at each moment at each level.

[0059] In one embodiment, the signal energy of the echo signal at a certain moment at a certain level can be determined according to the square of the detail coefficient of the echo signal at that moment at that level. For example: if the detail coefficient of the echo signal at the j-th level and the k-th moment is , then the signal energy of the echo signal at the j-th level and the k-th moment is , where t represents the time period length for collecting the echo signal.

[0060] It can be understood that if the degree of signal energy fluctuation at a certain level is significantly higher than that at other levels, it indicates that there may be relatively obvious defect signals at this level, and this level can be marked as the mutation level.

[0061] In one embodiment, the level with the degree of signal energy fluctuation greater than or equal to the preset threshold can be determined as the mutation level. For example: the preset threshold can be set to 0.5.

[0062] In one embodiment, since for the signals in the mutation level with a relatively large degree of signal energy fluctuation and a lower degree of uneven attenuation, the possibility of belonging to micro defect signals is greater, and it is necessary to enhance their detail performance degrees at different levels. Therefore, the signal correction factor is positively correlated with the degree of signal energy fluctuation and negatively correlated with the degree of uneven attenuation.

[0063] In one embodiment, the signal correction factors of the echo signals of the ultrasonic probe at each level can be determined according to the ratio between the degree of signal energy fluctuation and the degree of uneven attenuation at each level, and the formula is as follows: where represents the signal correction factor at the j-th level. Indicates the degree of signal energy fluctuation at the j-th level. Indicates the degree of attenuation non-uniformity.

[0064] In the above embodiments, since the micro-defect signals generated at the weld are ultrasonic echoes caused by the existence of real defects, the detected reflected echo signal states are stable and will exhibit sharp fluctuations in the high-frequency wavelet detail coefficients. Even at different levels of wavelet transform scales, the defect signals will still show relevant characteristics at the same time position. However, due to the lack of specific rules, the noise interference shows random fluctuations in amplitude between the levels of wavelet transform. Therefore, by analyzing the energy fluctuation of the echo signal at different levels and finding the local peaks with sudden increases in amplitude at different levels, the presence of micro-defect signals in the signal can be accurately determined. Since in the mutation level, the degree of signal energy fluctuation is large and the lower the degree of attenuation non-uniformity of the signal, the greater the possibility of belonging to a micro-defect signal, and it is necessary to enhance its detail performance at different levels. Therefore, according to the degree of signal energy fluctuation and the degree of attenuation non-uniformity, the signal correction factor of the echo signal of the ultrasonic probe at each level can be accurately determined.

[0065] In one embodiment, determining the degree of signal energy fluctuation at each level according to the detail coefficients of the echo signal of the ultrasonic probe at each level of wavelet transform scale includes: determining the signal energy at each moment at each level according to the detail coefficients of the echo signal of the ultrasonic probe at each moment at each level of wavelet transform scale; respectively determining the energy value span of the signal energy at each moment at each level; determining the total energy value span according to the sum of the energy value spans at each level; respectively for each level, determining the degree of signal energy fluctuation at the level according to the proportion of the energy value span of the level in the total energy value span.

[0066] In one embodiment, the energy value span at the level can be determined according to the difference between the maximum value and the minimum value of the signal energy at each moment at the level.

[0067] In one embodiment, the degree of signal energy fluctuation at the level can be determined according to the ratio between the energy value span at the level and the total energy value span, and the formula is as follows: Wherein, Indicates the degree of signal energy fluctuation at the j-th level. Indicates the signal energy corresponding to the i-th frequency in the signal at the j-th level. Indicates the maximum value of the signal energy at the j-th level. Indicates the minimum value of the signal energy at the j-th level. Indicates the energy value span at the j-th level. Indicates the total energy value span.

[0068] In the above embodiments, the energy value span of the signal energy at each moment under each level is determined respectively, and then according to the proportion of the energy value span of the level in the total sum of the energy value spans of all levels, the signal energy fluctuation degree of the level can be accurately determined.

[0069] In one embodiment, determining the attenuation non-uniformity degree of the local peaks existing in each mutation level at the same target moment includes: performing local peak detection on each mutation level to determine the local wave peaks at several moments in each mutation level; screening the local wave peaks existing in each mutation level at the same target moment to obtain a candidate wave peak set; determining the attenuation non-uniformity degree of the local wave peaks in the candidate wave peak set with the change of the level.

[0070] In one embodiment, several moments in mutation level j with amplitudes of . Among them, represents the time window. The time window can take 1 / 2 of the wavelet support length. represents the moment and the amplitudes of each moment within the neighborhood time window

[0071] In one embodiment, screening the local wave peaks existing in multiple levels at the same target moment to form a candidate wave peak set: .

[0072] In the above embodiments, since the defect signals show correlation at the same position in multiple mutation levels, while the distribution of noise peaks is relatively random, so in the selected mutation levels, by comparing the amplitudes of local peaks on different mutation levels, the energy change trend of the signal can be judged. Therefore, by performing local peak detection on each mutation level to determine the local wave peaks at several moments in each mutation level, screening the local wave peaks existing in each mutation level at the same target moment to obtain a candidate wave peak set, and then determining the attenuation non-uniformity degree of the local wave peaks in the candidate wave peak set with the change of the level, the attenuation non-uniformity degree can be accurately determined, thereby accurately measuring the energy change trend.

[0073] In one embodiment, determining the non-uniform attenuation degree of local peaks in the candidate peak set as the level changes includes: determining the difference between local peaks of each group of adjacent levels in the candidate peak set; determining the signal mean value at the target time in the candidate peak set; determining the exponential decay factor of the candidate peak set according to the signal mean value; and determining the non-uniform attenuation degree of local peaks in the candidate peak set as the level changes according to the ratio of the difference between local peaks of each group of adjacent levels to the exponential decay factor.

[0074] In one embodiment, the ratio of the difference between local peaks of each group of adjacent levels to the exponential decay factor can be determined respectively, and then according to the mean value of each ratio, the non-uniform attenuation degree of local peaks in the candidate peak set as the level changes can be determined.

[0075] In one embodiment, the non-uniform attenuation degree can be determined according to the following formula: Wherein, represents the non-uniform attenuation degree of the candidate peak set at the target time under. represents the local peak existing in the signal at the target time in the jm-th mutation level. represents the local peak existing in the signal at the target time in the jm + 1-th mutation level. represents the difference between local peaks of adjacent levels at the target time under. represents the signal mean value at the target time in the candidate peak set under. represents the exponential decay factor of the candidate peak set. nm represents the number of mutation levels.

[0076] In the above embodiment, since the energy of the high-frequency component decays faster, the amplitude of the defective signal decays exponentially with the mutation level. Therefore, according to the ratio of the difference between local peaks of each group of adjacent levels to the exponential decay factor, the non-uniform attenuation degree of local peaks in the candidate peak set as the level changes can be accurately determined. By calculating the signal difference between adjacent mutation levels in the candidate peak set and combining the exponential decay factor to calculate the attenuation characteristics of the signal between different levels, the change law of the signal between different levels is captured. The greater the degree of change, the more obvious the noise interference degree in the signal. Therefore, the greater the degree of correction required for the collected reflection signal, and then the signal correction factor can be accurately determined according to the non-uniform attenuation degree.

[0077] In one embodiment, the reconstructed signals of each ultrasonic probe are respectively compared with the standard echo signal for weld defect detection, including: comparing the reconstructed signals of each ultrasonic probe with the standard echo signal respectively to establish a defect feature model; judging whether there is a defect in the weld according to the defect feature model; if there is a defect, determining the type, position and size of the defect.

[0078] In one embodiment, feature extraction can be performed on the reconstructed signals of each ultrasonic probe, the extracted features are compared with the features of the standard echo signal, and a defect feature model is established. Whether there is a defect in the weld is judged according to the defect feature model, and the type, position and size of the defect are determined. The position of the defect can be determined according to the position of the ultrasonic probe corresponding to the reconstructed signal. Among them, the extracted features can include features such as amplitude, frequency and phase.

[0079] In one embodiment, the type, position and size of the defect can be output in the form of a graph or data. The detection results can be recorded and stored for subsequent analysis and traceability.

[0080] In the above embodiment, the reconstructed signals of each ultrasonic probe are respectively compared with the standard echo signal to establish a defect feature model. According to the defect feature model, it is possible to efficiently and accurately judge whether there is a defect in the weld and determine the type, position and size of the defect.

[0081] As Figure 7 shown, it is a schematic diagram of the overall process of the pipeline weld non-destructive testing method based on ultrasonic technology provided by an embodiment of the present invention, including the following steps: First, echo signal acquisition and preprocessing are performed, then similar position signals are determined (that is, echo signals of probes with similar positions are determined), then the signal is processed by wavelet decomposition (wavelet transform), the energy concentration at different wavelet transform scales is calculated, combined with the position similarity parameters between probes with similar positions, the correction coefficient of the detail coefficient is calculated, the detail coefficient is corrected, and finally the current detection signal is reconstructed based on the corrected detail coefficient for defect detection.

[0082] Please refer to Figure 8, which shows a schematic structural diagram of a pipeline weld non-destructive testing system based on ultrasonic technology provided by an embodiment of the present invention, including a memory and a processor; the memory is used to store executable program codes; the processor is used to call and run the executable program codes from the memory to implement the following steps: obtaining echo signals collected by each ultrasonic probe at the weld position of the pipeline; analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions under the same wavelet transform scale, and determining the position similar probes and position similar parameters of each ultrasonic probe; determining correction coefficients at each scale according to the position similar parameters of the ultrasonic probes and the variation differences of the echo signals of the ultrasonic probes and the corresponding position similar probes at each scale; respectively correcting the detail coefficients of the echo signals of the ultrasonic probes at each scale according to the correction coefficients at each scale; performing inverse wavelet transform based on the corrected detail coefficients at each scale to obtain a reconstructed signal; comparing the reconstructed signals of each ultrasonic probe with the standard echo signal respectively to perform weld defect detection.

[0083] In one embodiment, the processor further implements the following steps: respectively for each ultrasonic probe, analyzing the similarity degree of the time-domain local features of the echo signals of the ultrasonic probe and the ultrasonic probes at adjacent positions under the same wavelet transform scale, and obtaining the position correlation between the echo signal of the ultrasonic probe and the echo signals of each adjacent position ultrasonic probe; taking the maximum value in the position correlation as the position similar parameter, and determining the adjacent position ultrasonic probe corresponding to the maximum value as the position similar probe.

[0084] In one embodiment, the processor further implements the following steps: calculating the overlapping degree and waveform shape similarity of the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions under the same wavelet transform scale; determining the position correlation between the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions according to the overlapping degree and waveform shape similarity.

[0085] In one embodiment, the processor further implements the following steps: determining the signal correction factors of the echo signals of each ultrasonic probe at each level of the wavelet transform scale according to the detail coefficients of the echo signals of each ultrasonic probe at each level; respectively for each ultrasonic probe, determining the variation differences of the echo signals of the ultrasonic probe and the corresponding position similar probe at each scale according to the differences between the signal correction factors of the ultrasonic probe and the corresponding position similar probe at each level.

[0086] In one embodiment, the processor further implements the following steps: for each ultrasonic probe, determine the degree of signal energy fluctuation at each level according to the detail coefficients of the echo signal of the ultrasonic probe at each level of the wavelet transform scale; determine the mutation level according to the degree of signal energy fluctuation at each level; determine the degree of uneven attenuation of the local peaks existing at the same target time at each mutation level; determine the signal correction factor of the echo signal of the ultrasonic probe at each level according to the degree of signal energy fluctuation and the degree of uneven attenuation.

[0087] In one embodiment, the processor further implements the following steps: determine the signal energy at each moment at each level according to the detail coefficients of the echo signal of the ultrasonic probe at each level of the wavelet transform scale at each moment; respectively determine the energy value span of the signal energy at each moment at each level; determine the total energy value span according to the sum of the energy value spans at each level; for each level, determine the degree of signal energy fluctuation at the level according to the proportion of the energy value span of the level in the total energy value span.

[0088] In one embodiment, the processor further implements the following steps: perform local peak detection on each mutation level to determine several local wave peaks in each mutation level; screen the local wave peaks existing at the same target time in each mutation level to obtain a candidate wave peak set; determine the degree of uneven attenuation of the local wave peaks in the candidate wave peak set as the level changes.

[0089] In one embodiment, the processor further implements the following steps: determine the difference between the local wave peaks of each group of adjacent levels in the candidate wave peak set; determine the signal mean value at the target time in the candidate wave peak set; determine the exponential decay factor of the candidate wave peak set according to the signal mean value; determine the degree of uneven attenuation of the local wave peaks in the candidate wave peak set as the level changes according to the ratio of the difference between the local wave peaks of each group of adjacent levels to the exponential decay factor.

[0090] In one embodiment, the processor further implements the following steps: compare the reconstructed signals of each ultrasonic probe with the standard echo signal respectively to establish a defect feature model; judge whether there is a defect in the weld according to the defect feature model; if there is a defect, determine the type, position and size of the defect.

[0091] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0092] It should be noted that the above order of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0093] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. A non-destructive testing method for pipeline welds based on ultrasonic technology, characterized in that, The method includes: Obtaining echo signals collected by each ultrasonic probe at the weld position of the pipeline; Analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions under the same wavelet transform scale, and determining the position-similar probes and position-similarity parameters of each ultrasonic probe; Determining the correction coefficient at each scale according to the position-similarity parameter of the ultrasonic probe and the change difference of the echo signals of the ultrasonic probe and the corresponding position-similar probe at each scale; Respectively correcting the detail coefficients of the echo signals of the ultrasonic probe at each scale according to the correction coefficients at each scale; Performing inverse wavelet transform based on the corrected detail coefficients at each scale to obtain a reconstructed signal; Comparing the reconstructed signals of each ultrasonic probe with the standard echo signal respectively for weld defect detection.

2. The non-destructive testing method for pipeline welds based on ultrasonic technology according to claim 1, characterized in that, The analyzing the similarity degree of the time-domain local features of the echo signals of each ultrasonic probe and the ultrasonic probes at adjacent positions under the same wavelet transform scale, and determining the position-similar probes and position-similarity parameters of each ultrasonic probe includes: For each ultrasonic probe respectively, analyzing the similarity degree of the time-domain local features of the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions under the same wavelet transform scale, to obtain the position correlation between the echo signal of the ultrasonic probe and the echo signals of each adjacent-position ultrasonic probe; Taking the maximum value in the position correlations as the position-similarity parameter, and determining the adjacent-position ultrasonic probe corresponding to the maximum value as the position-similar probe.

3. The non-destructive testing method for pipeline welds based on ultrasonic technology according to claim 2, characterized in that The analyzing the similarity degree of the time-domain local features of the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions under the same wavelet transform scale, to obtain the position correlation between the echo signal of the ultrasonic probe and the echo signals of each adjacent-position ultrasonic probe includes: Calculating the overlapping degree and waveform shape similarity between the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions under the same wavelet transform scale; Determining the position correlation between the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions according to the overlapping degree and the waveform shape similarity.

4. The non-destructive testing method for pipeline welds based on ultrasonic technology according to claim 1, characterized in that, Before the determining the correction coefficient at each scale according to the position-similarity parameter of the ultrasonic probe and the change difference of the echo signals of the ultrasonic probe and the corresponding position-similar probe at each scale, the method further includes: Determining the signal correction factors of the echo signals of each ultrasonic probe at each level according to the detail coefficients of the echo signals of each ultrasonic probe at each level of the wavelet transform scale; For each ultrasonic probe respectively, determining the change difference of the echo signals of the ultrasonic probe and the corresponding position-similar probe at each scale according to the difference between the signal correction factors of the ultrasonic probe and the corresponding position-similar probe at each level.

5. The non-destructive testing method for pipeline welds based on ultrasonic technology according to claim 4, characterized in that, The determining the signal correction factors of the echo signals of each ultrasonic probe at each level according to the detail coefficients of the echo signals of each ultrasonic probe at each level of the wavelet transform scale includes: For each of the ultrasonic probes, determine the degree of signal energy fluctuation at each level of the wavelet transform scale based on the detail coefficients of the echo signal of the ultrasonic probe at each level; Determine the mutation level according to the degree of signal energy fluctuation at each level; Determine the degree of uneven attenuation of the local peaks existing at the same target time for each of the mutation levels; Determine the signal correction factor of the echo signal of the ultrasonic probe at each level according to the degree of signal energy fluctuation and the degree of uneven attenuation; 6. The non-destructive testing method for pipeline welds based on ultrasonic technology according to claim 5, characterized in that, The step of determining the degree of signal energy fluctuation at each level based on the detail coefficients of the echo signal of the ultrasonic probe at each level of the wavelet transform scale includes: Determine the signal energy at each moment at each level according to the detail coefficients of the echo signal of the ultrasonic probe at each moment at each level of the wavelet transform scale; Determine the energy value span of the signal energy at each moment at each level respectively; Determine the total energy value span according to the sum of the energy value spans at each level; For each level, determine the degree of signal energy fluctuation at that level according to the proportion of the energy value span at that level in the total energy value span; 7. The non-destructive testing method for pipeline welds based on ultrasonic technology according to claim 5, characterized in that The step of determining the degree of uneven attenuation of the local peaks existing at the same target time for each of the mutation levels includes: Perform local peak detection on each of the mutation levels to determine the local wave peaks at several moments in each of the mutation levels; Screen the local wave peaks existing at the same target time for each of the mutation levels to obtain a candidate wave peak set; Determine the degree of uneven attenuation of the local wave peaks in the candidate wave peak set as the level changes; 8. The non-destructive testing method for pipeline welds based on ultrasonic technology according to claim 7, characterized in that, The step of determining the degree of uneven attenuation of the local wave peaks in the candidate wave peak set as the level changes includes: Determine the difference between the local wave peaks of each group of adjacent levels in the candidate wave peak set; Determine the signal mean value at the target time in the candidate wave peak set; Determine the exponential decay factor of the candidate wave peak set according to the signal mean value; Determine the degree of uneven attenuation of the local wave peaks in the candidate wave peak set as the level changes according to the ratio of the difference between the local wave peaks of each group of adjacent levels to the exponential decay factor; 9. The non-destructive testing method for pipeline welds based on ultrasonic technology according to any one of claims 1 to 8, characterized in that, The step of comparing the reconstructed signals of each ultrasonic probe with the standard echo signal respectively for weld defect detection includes: Compare the reconstructed signals of each ultrasonic probe with the standard echo signal respectively to establish a defect feature model; Judge whether there is a defect in the weld according to the defect feature model; If there is a defect, determine the type, position and size of the defect; 10. A pipeline weld non-destructive testing system based on ultrasonic technology, characterized in that, The system includes a memory and a processor; the memory is used to store executable program code; the processor is used to call and run the executable program code from the memory to implement the pipeline weld non-destructive testing method based on ultrasonic technology according to any one of claims 1 to 9.

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