Nondestructive testing method and system for pipeline welds based on ultrasonic technology

Abstract

The present invention relates to the field of material analysis technology using ultrasonic technology, and specifically to a nondestructive testing method and system for pipeline welds based on ultrasonic technology. The method comprises: obtaining echo signals collected by each ultrasonic probe at the weld location of the pipeline; analyzing the similarity of the time domain local characteristics of the echo signals of each ultrasonic probe with those of an adjacent ultrasonic probe at 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 based on the position-similar parameters of the ultrasonic probes and the variation differences between the echo signals of the ultrasonic probes and the corresponding position-similar probes at each scale, and correcting the detail coefficients of the ultrasonic probe echo signals at each scale; obtaining a reconstructed signal based on the corrected detail coefficients at each scale; and comparing the reconstructed signals of each ultrasonic probe with standard echo signals to detect weld defects. This method can reduce the risk of false detection or missed detection of minor defects.

Description

Technical Field

[0001] The present invention relates to the technical field of material analysis using ultrasonic technology, and in particular to a pipeline weld non-destructive testing method and system based on ultrasonic technology. Background Art

[0002] Pipelines are often used to transport liquids, gases, or other chemicals and are widely used in industries such as the oil, natural gas, and chemical industries. During pipeline construction, quality control of welds at pipeline breakpoints is crucial. As a critical connection point, the quality of welds directly impacts the operational efficiency and safety of the entire pipeline system. Even the slightest defect can lead to serious safety incidents such as leaks and explosions. Prompt detection and repair of weld defects through inspection ensures the safe operation of pipeline projects.

[0003] Common defects in pipeline welds include cracks, incomplete penetration, uneven fusion line structure, and folding of the base material. Non-destructive testing using ultrasonic technology can comprehensively inspect all welds without destroying them. 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 detection efficiency, and thus improving the quality and reliability of the entire pipeline system.

[0004] In ultrasonic weld inspection, weld defects are manifested as waveform changes. However, due to various factors, such as environmental noise and electrical interference, the signal data received by the ultrasonic probe often contains a high level of noise. This noise interference can seriously affect the identification of minor defects, leading to problems such as false or missed detections. Summary of the Invention

[0005] In order to solve the technical problem of false or missed defect detection caused by noise interference, the present invention aims to provide a pipeline weld nondestructive testing method and system based on ultrasonic technology. The technical solution adopted is as follows:

[0006] The present invention provides a non-destructive testing method for pipeline welds based on ultrasonic technology, the method comprising:

[0007] Acquire echo signals collected by each ultrasonic probe at the weld position of the pipeline;

[0008] Analyzing the similarity of the time domain local features of the echo signals of each ultrasonic probe and the ultrasonic probe at an adjacent position at the same wavelet transform scale, and determining the position similar probes and position similarity parameters of each ultrasonic probe;

[0009] determining a correction coefficient at each scale based on a position similarity parameter of the ultrasound probe and a difference in change of echo signals of the ultrasound probe and a corresponding similarly positioned probe at each scale;

[0010] Correcting the detail coefficient of the echo signal of the ultrasonic probe at each scale according to the correction coefficient at each scale;

[0011] Perform inverse wavelet transform based on the corrected detail coefficients at each scale to obtain the reconstructed signal;

[0012] The reconstructed signals of each ultrasonic probe are compared with the standard echo signals to detect weld defects.

[0013] According to the ultrasonic technology-based nondestructive testing method for pipeline welds provided by the present invention, the similarity of the time domain local features of the echo signals of each ultrasonic probe and the adjacent ultrasonic probe at the same wavelet transform scale is analyzed to determine the position similarity probes and position similarity parameters of each ultrasonic probe, including:

[0014] For each of the ultrasound probes, analyzing the similarity of the time domain local features of the echo signals of the ultrasound probe and the echo signals of the adjacent ultrasound probes at the same wavelet transform scale, and obtaining the position correlation between the echo signal of the ultrasound probe and the echo signals of the adjacent ultrasound probes;

[0015] The maximum value in the position correlation is used as a position similarity parameter, and the adjacent position ultrasound probe corresponding to the maximum value is determined as a position similar probe.

[0016] According to the ultrasonic technology-based nondestructive testing method for pipeline welds provided by the present invention, the similarity of the time domain local features of the echo signals of the ultrasonic probe and the echo signals of the ultrasonic probes at adjacent positions at the same wavelet transform scale is analyzed to obtain the position correlation between the echo signals of the ultrasonic probe and the echo signals of the ultrasonic probes at each of the adjacent positions, including:

[0017] Calculating the degree of overlap and waveform shape similarity between the echo signal of the ultrasound probe and the echo signal of an adjacent ultrasound probe at the same wavelet transform scale;

[0018] The position correlation between the echo signal of the ultrasonic probe and the echo signal of the ultrasonic probe at the adjacent position is determined according to the overlap degree and the waveform shape similarity.

[0019] According to the ultrasonic technology-based nondestructive testing method for pipeline welds provided by the present invention, before determining the correction coefficient at each scale based on the position similarity parameter of the ultrasonic probe and the difference in change of the echo signal of the ultrasonic probe and the corresponding similarly positioned probe at each scale, the method further includes:

[0020] determining, according to the detail coefficients of the echo signals of the ultrasound probes at the levels of the wavelet transform scales, the signal correction factors of the echo signals of the ultrasound probes at the levels;

[0021] For each of the ultrasound probes, the difference in the change of the echo signals of the ultrasound probe and the corresponding similarly located probe at each scale is determined based on the difference between the signal correction factors of the ultrasound probe and the corresponding similarly located probe at each level.

[0022] According to the ultrasonic technology-based nondestructive testing method for pipeline welds provided by the present invention, 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 wavelet transform scale includes:

[0023] For each of the ultrasound probes, determining the signal energy fluctuation degree at each level according to the detail coefficient of the echo signal of the ultrasound probe at each level of the wavelet transform scale;

[0024] Determining the mutation level according to the signal energy fluctuation degree of each level;

[0025] Determining the degree of attenuation unevenness of local peaks existing at the same target time for each of the mutation levels;

[0026] The signal correction factors of the echo signal of the ultrasonic probe at each level are determined according to the signal energy fluctuation degree and the attenuation unevenness degree.

[0027] According to the ultrasonic technology-based nondestructive testing method for pipeline welds provided by the present invention, determining the signal energy fluctuation degree at each level based on the detail coefficient of the echo signal of the ultrasonic probe at each wavelet transform scale level includes:

[0028] Determining the signal energy at each moment at each level according to the detail coefficient of the echo signal of the ultrasound probe at each moment at each wavelet transform scale level;

[0029] Determining the energy value span of the signal energy at each time in each level respectively;

[0030] Determining a total energy value span according to the sum of the energy value spans of each level;

[0031] For each level respectively, the signal energy fluctuation degree of the level is determined according to the proportion of the energy value span of the level in the total energy value span.

[0032] According to the pipeline weld nondestructive testing method based on ultrasonic technology provided by the present invention, the determining of the attenuation unevenness of the local peaks existing at the same target time of each mutation level includes:

[0033] Performing local peak detection on each of the mutation levels to determine local peaks at a plurality of moments in each of the mutation levels;

[0034] Screening the local peaks existing at the same target time for each of the mutation levels to obtain a candidate peak set;

[0035] Determine the degree of uneven attenuation of the local peaks in the candidate peak set as the levels change.

[0036] According to the pipeline weld nondestructive testing method based on ultrasonic technology provided by the present invention, determining the attenuation unevenness of the local peaks in the candidate peak set as the levels change includes:

[0037] Determining the difference between local peaks of adjacent levels in each group of the candidate peak set;

[0038] Determine a signal mean value in the candidate peak set at the target time;

[0039] determining an exponential decay factor of the candidate peak set according to the signal mean;

[0040] The degree of attenuation unevenness of the local peaks in the candidate peak set as the levels change is determined according to the ratio of the difference between the local peaks of the adjacent levels and the exponential attenuation factor.

[0041] According to the pipeline weld nondestructive testing method based on ultrasonic technology provided by the present invention, the reconstructed signals of each ultrasonic probe are compared with the standard echo signal to perform weld defect detection, including:

[0042] The reconstructed signals of each ultrasonic probe are compared with the standard echo signals to establish a defect feature model;

[0043] Determining whether there is a defect in the weld according to the defect characteristic model;

[0044] If a defect is present, the type, location, and size of the defect are determined.

[0045] The present invention provides a pipeline weld nondestructive testing system based on ultrasonic technology, the system comprising 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 nondestructive testing method based on ultrasonic technology provided by the present invention.

[0046] The present invention has the following beneficial effects:

[0047] By analyzing the similarity of the time domain local features of the echo signals of each ultrasonic probe and the adjacent ultrasonic probes at the same wavelet transform scale, the position-similar probes of each ultrasonic probe are found and the position-similar parameters are determined. Then, according to the position-similar parameters of the ultrasonic probes and the difference in the change 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. Based on the corrected detail coefficients at each scale, an inverse wavelet transform is performed to obtain a reconstructed signal, so that tiny defect signals can be retained in the reconstructed signal, avoiding the problem of false detection and missed detection of tiny defects caused by directly deleting the high-frequency components according to the original detail coefficients, thereby improving the accuracy of defect detection of welds. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 A schematic flow chart of a pipeline weld nondestructive testing method based on ultrasonic technology provided by one embodiment of the present invention;

[0050] Figure 2 A schematic diagram of waveforms of a first group of echo signals provided by an embodiment of the present invention;

[0051] Figure 3 A schematic diagram of the waveform of a second group of echo signals provided by an embodiment of the present invention;

[0052] Figure 4 A schematic diagram of the waveform of a third group of echo signals provided by an embodiment of the present invention;

[0053] Figure 5 A schematic diagram of the waveform of a fourth group of echo signals provided by an embodiment of the present invention;

[0054] Figure 6A schematic diagram of a wavelet transform process provided by one embodiment of the present invention;

[0055] Figure 7 A schematic diagram of the overall process of a pipeline weld non-destructive testing method based on ultrasonic technology provided by one embodiment of the present invention;

[0056] Figure 8 A schematic structural diagram of a pipeline weld nondestructive testing system based on ultrasonic technology provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0057] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a pipeline weld nondestructive testing method and system based on ultrasonic technology proposed by the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0058] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0059] The following describes in detail a method and system for non-destructive testing of pipeline welds based on ultrasonic technology provided by the present invention with reference to the accompanying drawings.

[0060] See also Figure 1 , which shows a flow chart of a pipeline weld nondestructive testing method based on ultrasonic technology provided by one embodiment of the present invention, including the following steps:

[0061] Step 102: Acquire echo signals collected by each ultrasonic probe at the weld position of the pipeline.

[0062] In one embodiment, a phased array ultrasonic testing device can be used. A phased array ultrasonic probe is placed on the outer surface of the weld, ensuring close contact with the weld surface, free of bubbles or gaps, and covering the entire inspection area of ​​the weld. The weld location of the pipeline is inspected, and a set of ultrasonic echo signals is collected from the weld location. Each set of echo signals includes a time series and corresponding amplitude information.

[0063] Figure 2 、 Figure 3 、 Figure 4 and Figure 5 Four groups of waveform diagrams of echo signals are shown, respectively representing echo signals collected by ultrasonic probes at different positions.

[0064] In one embodiment, the echo signal may be corrected in the time domain by adjusting the time reference of the signal to eliminate the error in the measurement time and obtain an accurate echo signal at the corresponding time.

[0065] Step 104 : Analyze the similarity of the time domain local features of the echo signals of each ultrasonic probe and the adjacent ultrasonic probes at the same wavelet transform scale, and determine the position similar probes and position similarity parameters of each ultrasonic probe.

[0066] The adjacent ultrasound probes refer to two ultrasound probes adjacent to a given ultrasound probe. The position similarity parameter represents the degree of similarity between the local time domain features of the echo signals of the ultrasound probe and the corresponding similarly positioned probes at the same wavelet transform scale.

[0067] It can be understood that for ultrasonic probes arranged in a circular array, since the materials of the pipeline weld area are similar, the signal propagation paths of probes at different positions are roughly similar, and in the same weld area, the scanning areas of probes at adjacent positions overlap, and the echo signals obtained by probes at different positions are similar. Therefore, by performing a 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 then further signal denoising analysis can be performed based on the similar characteristics exhibited by the echo signals of the ultrasonic probes and the corresponding position-similar probes in the same weld area.

[0068] In one embodiment, Daubechies wavelet (db4) can be selected as the wavelet basis function, and the number of decomposition layers is set to n. The collected echo signal is subjected to wavelet transform to obtain a series of wavelet coefficients at different scales. The wavelet coefficients include approximation coefficients (original approximation coefficients) and detail coefficients (original detail coefficients) at each scale level. The approximation coefficients contain the main features of the echo signal, and the detail coefficients reflect the details of the changes in the echo signal. Figure 6 As shown in the figure, the process of decomposing the echo signal by wavelet transform can be expressed as a tree structure composed of low-pass filters and high-pass filters, where LPF represents low-pass filter, HPF represents high-pass filter, L1, L2, and L3 represent low-frequency components at different scales, H represents the high-frequency component of the original signal (echo signal before wavelet transform), H1, H2, and H3 represent high-frequency components at different scales, S represents the original signal, and the decomposed cA1, cA2, and cA3 represent the approximation coefficients of the low-frequency components at different scales, and cD1, cD2, and cD3 represent the detail coefficients of the high-frequency components at different scales.

[0069] Step 106 : determining a correction coefficient at each scale based on the position similarity parameter of the ultrasound probe and the difference in change of the echo signal between the ultrasound probe and the corresponding position similar probe at each scale.

[0070] In one embodiment, the signal correction factor of the echo signal of the ultrasound probe at each scale level can be calculated, and then the difference in the change of the echo signal of the ultrasound probe and the corresponding similarly positioned probe at each scale can be determined based on the difference between the signal correction factors of the ultrasound probe and the corresponding similarly positioned probe at each level.

[0071] In one embodiment, the correction coefficient at each scale may be determined based on the ratio between the position similarity parameter of the ultrasound probe and the change difference at each scale.

[0072] In one embodiment, the correction coefficient at each scale can be determined according to the following formula:

[0073]

[0074] in, Represents the correction coefficient at the jth scale. Indicates normalization processing. Represents the position similarity parameter of the ultrasound probe at the bth position. Represents the signal correction factor of the ultrasound probe at the jth scale level. Represents the signal correction factor of the ultrasound probe at the jth scale level for a similar probe. It represents the difference in signal correction factors between the echo signals of the ultrasonic probe and the corresponding similarly positioned probe at the j-th scale level. It is used to measure the difference in change of the echo signals of the ultrasonic probe and the corresponding similarly positioned probe at the same scale. The smaller the difference, the greater the similarity of the change of the mutation signal in the echo signal, the greater the possibility that the mutation signal belongs to a defect signal, and the greater the degree to which the detail coefficient of the echo signal of the ultrasonic probe needs to be enhanced. Represents the minimum hyperparameter, which is used to avoid the situation where the denominator is equal to 0.

[0075] It can be understood that when the interference noise shows signal energy at 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 levels of noise interference in the collected signal. 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 performance of the ultrasonic signal is relatively consistent when scanning the same tiny defect area. Therefore, the consistency of similar signals in the wavelet transform can be used for denoising. Therefore, in the above embodiment, by combining the position similarity parameters between probes with similar positions and the difference in the change of the echo signal at each scale, the signal attenuation correlation between similar positions is determined as a correction coefficient, so that it can accurately distinguish which parts are noise and which parts are details of the tiny defect area, accurately correct the detail coefficient, reduce the denoising strength in areas with strong tiny defect signals, and enhance the denoising effect in areas with strong noise.

[0076] Step 108 : Correcting the detail coefficient of the echo signal of the ultrasound probe at each scale according to the correction coefficient at each scale.

[0077] In one embodiment, the corrected detail coefficient at the scale may be determined based on the product of the correction coefficient at the same scale and the original detail coefficient (ie, the detail coefficient before correction).

[0078] In one embodiment, the detail coefficient of the echo signal of the ultrasound probe at each scale may be corrected according to the following formula:

[0079]

[0080] in, Represents the corrected detail coefficient at the kth moment at the jth scale level. Represents the correction coefficient at the j-th scale level. Represents the original detail coefficient at the kth moment in the jth scale level (i.e., the detail coefficient before correction).

[0081] Step 110 : performing inverse wavelet transform based on the corrected detail coefficients at each scale to obtain a reconstructed signal.

[0082] In one embodiment, an inverse wavelet transform may be performed based on the corrected detail coefficients and the original approximation coefficients at each scale to obtain a reconstructed signal.

[0083] In one embodiment, the reconstructed signal can be determined according to the following formula:

[0084]

[0085] in, Represents the reconstructed signal. Represents the corrected detail coefficient at the kth moment at the jth scale level. Represents the original approximation coefficient at the kth moment under the level of the jth scale. Represents the selected wavelet basis function. It represents the decomposition scaling function.

[0086] Step 112 : Compare the reconstructed signals of each ultrasonic probe with the standard echo signal to detect weld defects.

[0087] 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.

[0088] In the above-mentioned non-destructive testing method for pipeline welds based on ultrasonic technology, by analyzing the similarity of the time domain local characteristics of the echo signals of each ultrasonic probe and the adjacent ultrasonic probe at the same wavelet transform scale, the position-similar probes of each ultrasonic probe are found and the position-similar parameters are determined. Then, according to the position-similar parameters of the ultrasonic probes and the difference in the change of the echo signals of the ultrasonic probe and the corresponding position-similar probes at each scale, the correction coefficient at each scale is determined, and the detail coefficient of the echo signal of the ultrasonic probe at each scale is corrected. Based on the corrected detail coefficients at each scale, an inverse wavelet transform is performed to obtain a reconstructed signal, so that tiny defect signals can be retained in the reconstructed signal, avoiding the problem of false detection and missed detection of tiny defects caused by directly deleting the high-frequency components according to the original detail coefficients, thereby improving the accuracy of defect detection of welds.

[0089] In one embodiment, the degree of similarity between the time domain local features of the echo signals of each ultrasound probe and the ultrasound probe at an adjacent position at the same wavelet transform scale is analyzed to determine the position similar probes and position similarity parameters of each ultrasound probe, including: for each ultrasound probe, analyzing the degree of similarity between the time domain local features of the echo signals of the ultrasound probe and the ultrasound probe at an adjacent position at the same wavelet transform scale to obtain the position correlation between the echo signal of the ultrasound probe and the echo signals of the ultrasound probe at each adjacent position; taking the maximum value of the position correlation as the position similarity parameter, and determining the ultrasound probe at the adjacent position corresponding to the maximum value as the position similar probe.

[0090] by Figure 3 Taking the corresponding b-th position as an example, for the echo signals of ultrasonic probes at different positions, in the time domain after wavelet transformation, the echo signals of ultrasonic probes at adjacent positions show certain waveform similarity in the local characteristics of the time domain. When the propagation path of the echo signal is consistent with the nature of the defect, the sudden change of the echo signal at a certain moment shows similar patterns at different positions, such as the reflection of the defect shows similar patterns at different positions. For example: Figure 3 and Figure 4 Therefore, by analyzing the echo signal b(t) of the ultrasound probe at the bth position (i.e. Figure 3 The echo signal displayed) and the echo signals a(t) and c(t) of the adjacent ultrasound probes (i.e. the ultrasound probe at position a and the ultrasound probe at position c) (i.e. Figure 2 and Figure 4 The time domain local characteristics of the echo signal displayed) at the same wavelet transform scale can determine the position similar probe of the ultrasound probe at the bth position from the ultrasound probe at the ath position and the ultrasound probe at the cth position.

[0091] In one embodiment, the location similarity parameter can be determined according to the following formula:

[0092]

[0093] in, Represents the position similarity parameter corresponding to the ultrasound probe at the bth position. Represents the position correlation between the echo signal of the ultrasonic probe at the bth position and the echo signal of the ultrasonic probe at the ath position. It represents the position correlation between the echo signal of the ultrasonic probe at the bth position and the echo signal of the ultrasonic probe at the cth position. Indicates taking the maximum value.

[0094] In the above embodiment, by analyzing the similarity of the time domain local features of the echo signals of the ultrasonic probe and the adjacent position ultrasonic probes at the same wavelet transform scale, the position correlation of the echo signal of the ultrasonic probe and the echo signals of the ultrasonic probes at each adjacent position is obtained, and then the maximum value in the position correlation 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, which can accurately determine the position similar probe and position similarity parameter corresponding to each ultrasonic probe.

[0095] In one embodiment, the similarity of the time domain local features of the echo signals of the ultrasound probe and the echo signals of the ultrasound probes at adjacent positions at the same wavelet transform scale is analyzed to obtain the positional correlation between the echo signals of the ultrasound probe and the echo signals of the ultrasound probes at each adjacent position, including: calculating the degree of overlap and waveform shape similarity between the echo signals of the ultrasound probe and the echo signals of the ultrasound probes at adjacent positions at the same wavelet transform scale; and determining the positional correlation between the echo signals of the ultrasound probe and the echo signals of the ultrasound probes at adjacent positions based on the degree of overlap and the waveform shape similarity.

[0096] In one embodiment, the degree of overlap may be determined based on an integral result of the product of the echo signal of the ultrasound probe and the echo signal of the ultrasound probe at an adjacent position at the same wavelet transform scale.

[0097] In one embodiment, the waveform shape similarity may be determined based on a DTW distance (dynamic time warping distance) between an echo signal of an ultrasound probe and an echo signal of an adjacent ultrasound probe at the same wavelet transform scale.

[0098] In one embodiment, the position correlation may be determined based on a ratio between the degree of overlap and the similarity of the waveform shapes.

[0099] In one embodiment, positional correlation can be determined based on the ratio of the integral of the product of the echo signal of an ultrasound probe and the echo signal of an adjacent ultrasound probe at the same wavelet transform scale to the DTW distance. It will be appreciated that processing the reciprocity between two echo signals (i.e., the integral of the product) using the DTW distance reduces the impact of data amplitude on the waveform, enabling more accurate calculation of the positional correlation of the echo signals.

[0100] In one embodiment, taking the ultrasound probe at the bth position as an example, the position correlation between the echo signal of the ultrasound probe and the echo signal of the ultrasound probe at the adjacent position can be calculated according to the following formula:

[0101]

[0102] in, Represents the position correlation between the echo signal of the ultrasonic probe at the bth position and the echo signal of the ultrasonic probe at the ath position. Represents the amplitude of the echo signal data of the ultrasound probe at the bth position at the tth time. The echo signal of the ultrasonic probe at position a is The echo signal data amplitude at time. It is used to measure the degree of overlap between the echo signal of the ultrasound probe at the bth position and the echo signal of the ultrasound probe at the ath position at the same wavelet transform scale. Indicates echo signal and The DTW distance between them. Represents the minimum hyperparameter, which is used to avoid the situation where the denominator is equal to 0.

[0103] Similarly, the position correlation between the echo signal of the ultrasonic probe at the bth position and the echo signal of the ultrasonic probe at the cth position can be calculated using the same principle.

[0104] In the above embodiment, the degree of overlap and waveform shape similarity between the echo signal of the ultrasound probe and the echo signal of the ultrasound probe at an adjacent position at the same wavelet transform scale are calculated, and then based on the degree of overlap and the waveform shape similarity, the influence of the data amplitude on the waveform can be reduced, thereby accurately determining the positional correlation between the echo signal of the ultrasound probe and the echo signal of the ultrasound probe at an adjacent position.

[0105] In one embodiment, before determining the correction coefficient at each scale based on the position similarity parameter of the ultrasonic probe and the difference in the change of the echo signal of the ultrasonic probe and the corresponding position similar probe at each scale, the method also includes: determining the signal correction factor of the echo signal of each ultrasonic probe at each level based on the detail coefficient of the echo signal of each ultrasonic probe at each level of the wavelet transform scale; and determining the difference in the change of the echo signal of the ultrasonic probe and the corresponding position similar probe at each scale for each ultrasonic probe based on the difference between the signal correction factors of the ultrasonic probe and the corresponding position similar probe at each level.

[0106] In the above embodiment, the signal correction factor of the echo signal of each ultrasonic probe at each level is determined based on the detail coefficient of the echo signal of each ultrasonic probe at each wavelet transform scale level, which can accurately measure the change of the echo signal. Then, based on the difference between the signal correction factors of the ultrasonic probe and the corresponding similarly positioned probe at each level, the change difference of the echo signal of the ultrasonic probe and the corresponding similarly positioned probe at each scale can be accurately determined. The smaller the difference, the greater the change similarity of the mutation signal in the echo signal, the greater the possibility that the mutation signal belongs to a defect signal, and the greater the degree to which the detail coefficient of the echo signal of the ultrasonic probe needs to be enhanced. Therefore, the correction coefficient can be accurately determined based on the accurate change difference.

[0107] In one embodiment, the signal correction factor of the echo signal of each ultrasonic probe at each level is determined based on the detail coefficient of the echo signal of each ultrasonic probe at each level of the wavelet transform scale, including: determining the degree of signal energy fluctuation at each level for each ultrasonic probe according to the detail coefficient 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 attenuation unevenness of the local peak of each mutation level at the same target time; and determining 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 attenuation unevenness.

[0108] In one embodiment, the signal energy at each level at each moment can be determined based on the detail coefficient of the echo signal of the ultrasound probe at each level of wavelet transform scale, and then the degree of signal energy fluctuation at each level can be determined based on the signal energy at each moment at each level.

[0109] In one embodiment, the signal energy of the echo signal at a certain level and at a certain moment can be determined based on the square of the detail coefficient of the echo signal at that level and at that moment. For example, the detail coefficient of the echo signal at the jth level and at the kth moment is , then the signal energy of the echo signal at the jth level at the kth moment is , where t represents the length of the time period for collecting echo signals.

[0110] It can be understood that if the signal energy fluctuation degree of a certain layer is significantly higher than that of other layers, it indicates that there may be a more obvious defect signal in the layer, and the layer can be marked as a mutation layer.

[0111] In one embodiment, a level where the signal energy fluctuation degree is greater than or equal to a preset threshold can be determined as a mutation level. For example, the preset threshold can be set to 0.5.

[0112] In one embodiment, because signal energy fluctuations are large at the mutation level, and signals with lower attenuation unevenness are more likely to be subtle defect signals, it is necessary to enhance the level of detail 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 attenuation unevenness.

[0113] In one embodiment, the signal correction factor of the echo signal of the ultrasound probe at each level can be determined based on the ratio between the signal energy fluctuation degree and the attenuation unevenness degree at each level. The formula is as follows:

[0114]

[0115] in, represents the signal correction factor of the jth level. Indicates the degree of signal energy fluctuation at the jth level. Indicates the degree of attenuation unevenness.

[0116] In the above-described embodiment, since the tiny defect signal generated at the weld is an ultrasonic echo caused by the presence of a real defect, the detected reflected echo signal is stable and exhibits sharp fluctuations in the high-frequency wavelet detail coefficients. Even at different wavelet transform scale levels, the defect signal still exhibits related characteristics at the same time position. However, noise interference has no specific pattern and appears as random fluctuations in amplitude between wavelet transform levels. Therefore, by analyzing the energy fluctuations of the echo signal at different levels and finding local peaks with sudden increases in amplitude at different levels, the presence of tiny defect signals in the signal can be accurately determined. Because the signal energy fluctuations are large at the sudden change level, and the lower the attenuation unevenness, the more likely the signal is a tiny defect signal, and the degree of detail expression at different levels needs to be enhanced, the signal correction factor of the ultrasonic probe echo signal at each level can be accurately determined based on the signal energy fluctuations and attenuation unevenness.

[0117] In one embodiment, the degree of signal energy fluctuation at each level is determined based on the detail coefficient of the echo signal of the ultrasound probe at each level of the wavelet transform scale, including: determining the signal energy at each moment at each level based on the detail coefficient of the echo signal of the ultrasound probe at each moment at each level of the wavelet transform scale; separately determining the energy value span of the signal energy at each moment at each level; determining the total energy value span based on the sum of the energy value spans of each level; and determining the degree of signal energy fluctuation at each level based on the proportion of the energy value span of the level in the total energy value span.

[0118] In one embodiment, the energy value span of a level may be determined according to the difference between the maximum value and the minimum value of the signal energy at each moment in the level.

[0119] In one embodiment, the signal energy fluctuation degree of a level can be determined based on the ratio between the energy value span of the level and the total energy value span. The formula is as follows:

[0120]

[0121] in, Indicates the degree of signal energy fluctuation at the jth level. Represents the signal energy corresponding to the i-th frequency in the signal of the j-th level. Represents the maximum value of the signal energy at the jth level. Represents the minimum value of the signal energy at the jth level. Indicates the energy value span of the j-th level. Indicates the total span of energy values.

[0122] In the above embodiment, the energy value span of the signal energy at each moment in each layer is determined respectively, and then the degree of signal energy fluctuation of the layer can be accurately determined according to the proportion of the energy value span of the layer in the total energy value span of each layer.

[0123] In one embodiment, the degree of attenuation unevenness of local peaks existing in each mutation level at the same target time is determined, including: performing local peak detection on each mutation level to determine local peaks at several moments in each mutation level; screening local peaks existing in each mutation level at the same target time to obtain a candidate peak set; and determining the degree of attenuation unevenness of local peaks in the candidate peak set as the level changes.

[0124] In one embodiment, several moments in the mutation level j The amplitude is The local peak of can satisfy the following conditions: .in, Represents the time window. The time window can be half the length of the wavelet support. Indicates time Neighborhood time window The amplitude at each moment.

[0125] In one embodiment, for multiple levels at the same target time The existing local peaks are screened to form a set of candidate peaks: .

[0126] In the above embodiment, since the defect signal exhibits correlation at the same position in multiple mutation levels, while the distribution of noise peaks is relatively random, the energy change trend of the signal can be determined by comparing the amplitudes of local peaks at different mutation levels in the selected mutation level. Therefore, by performing local peak detection on each mutation level, local peaks at several moments in each mutation level are determined, and local peaks existing at the same target moment in each mutation level are screened to obtain a candidate peak set. Then, the degree of attenuation unevenness of the local peaks in the candidate peak set as the level changes is determined. This can accurately determine the degree of attenuation unevenness and thus accurately measure the energy change trend.

[0127] In one embodiment, determining the degree of uneven attenuation of local peaks in a 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 of the candidate peak set at a target time; determining the exponential attenuation factor of the candidate peak set based on the signal mean; and determining the degree of uneven attenuation of local peaks in the candidate peak set as the level changes based on the ratio of the difference between local peaks of each group of adjacent levels to the exponential attenuation factor.

[0128] In one embodiment, the ratios of the differences between local peaks of adjacent levels to the exponential decay factors can be determined, and then the degree of uneven attenuation of local peaks in the candidate peak set as the levels change can be determined based on the average of the ratios.

[0129] In one embodiment, the degree of attenuation non-uniformity may be determined according to the following formula:

[0130]

[0131] in, At the target time The degree of attenuation unevenness of the candidate peak set. Indicates that the signal at the target time in the jm-th mutation level There are local peaks below. Indicates that the signal at the target time in the jm+1th mutation level There are local peaks below. At the target time The difference between the local peaks of the adjacent layers below. Indicates the candidate peak set at the target time The mean value of the signal below. Represents the exponential decay factor of the candidate peak set. nm represents the number of mutation levels.

[0132] In the above embodiment, because high-frequency components decay more rapidly, the amplitude of the defective signal decays exponentially with the level of the mutation. Therefore, the ratio of the difference between local peaks at each group of adjacent levels to the exponential decay factor can accurately determine the degree of uneven attenuation of local peaks in the candidate peak set as the levels change. By calculating the signal differences between adjacent mutation levels in the candidate peak set and combining the exponential decay factor to calculate the attenuation characteristics of the signal at different levels, the variation pattern of the signal at different levels is captured. The greater the degree of variation, the more significant the noise interference in the signal, and therefore the greater the degree of correction required for the collected reflection signal. This allows the signal correction factor to be accurately determined based on the degree of attenuation unevenness.

[0133] In one embodiment, the reconstructed signals of each ultrasonic probe are compared with the standard echo signals to perform weld defect detection, including: comparing the reconstructed signals of each ultrasonic probe with the standard echo signals to establish a defect feature model; judging whether there is a defect in the weld based on the defect feature model; if a defect exists, determining the type, location and size of the defect.

[0134] In one embodiment, feature extraction can be performed on the reconstructed signals from each ultrasonic probe. The extracted features are compared with those of the standard echo signal to establish a defect feature model. Based on the defect feature model, the presence of a defect in the weld is determined, along with the defect type, location, and size. The defect location can be determined based on the position of the ultrasonic probe corresponding to the reconstructed signal. The extracted features may include amplitude, frequency, and phase.

[0135] In one embodiment, the type, location, and size of the defect can be output in the form of a graph or data. The inspection results can be recorded and stored for subsequent analysis and tracing.

[0136] In the above embodiment, the reconstructed signal of each ultrasonic probe is compared with the standard echo signal to establish a defect feature model. Based on the defect feature model, it is possible to efficiently and accurately determine whether there is a defect in the weld and determine the type, location and size of the defect.

[0137] like Figure 7 The figure shows an overall process diagram of a nondestructive testing method for pipeline welds based on ultrasonic technology provided by an embodiment of the present invention, which includes the following steps: first, echo signal acquisition and preprocessing are performed, then similar position signals are determined (i.e., echo signals of probes with similar positions are determined), then wavelet decomposition and signal processing (wavelet transform) are performed, energy concentration at different wavelet transform scales is calculated, and correction coefficients of detail coefficients are calculated based on positional similarity parameters between probes with similar positions, and the detail coefficients are corrected. Finally, the current detection signal is reconstructed based on the corrected detail coefficients to perform defect detection.

[0138] See also Figure 8 , which shows a structural schematic diagram of a pipeline weld nondestructive 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 code; the processor is used to call and run the executable program code 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 of the time domain local characteristics of the echo signals of each ultrasonic probe and the ultrasonic probe at the adjacent position at the same wavelet transform scale, and determining the position similar probe and position similarity parameter of each ultrasonic probe; determining the correction coefficient at each scale based on the position similarity parameter of the ultrasonic probe and the change difference between the echo signals of the ultrasonic probe and the corresponding position similar probe at each scale; correcting the detail coefficient of the echo signal of the ultrasonic probe at each scale according to the correction coefficient at each scale; performing inverse wavelet transform based on the corrected detail coefficient at each scale to obtain a reconstructed signal; and comparing the reconstructed signal of each ultrasonic probe with the standard echo signal to perform weld defect detection.

[0139] In one embodiment, the processor further implements the following steps: for each ultrasound probe, analyzing the similarity of the time domain local features of the echo signals of the ultrasound probe and the ultrasound probe at the adjacent position at the same wavelet transform scale, and obtaining the position correlation between the echo signal of the ultrasound probe and the echo signals of the ultrasound probe at each adjacent position; taking the maximum value in the position correlation as the position similarity parameter, and determining the adjacent position ultrasound probe corresponding to the maximum value as the position similar probe.

[0140] In one embodiment, the processor further implements the following steps: calculating the degree of overlap and waveform shape similarity between the echo signal of the ultrasound probe and the echo signal of the ultrasound probe at an adjacent position at the same wavelet transform scale; and determining the positional correlation between the echo signal of the ultrasound probe and the echo signal of the ultrasound probe at an adjacent position based on the degree of overlap and the waveform shape similarity.

[0141] In one embodiment, the processor further implements the following steps: determining the signal correction factor of the echo signal of each ultrasonic probe at each level based on the detail coefficient of the echo signal of each ultrasonic probe at each level of wavelet transform scale; and determining the difference in change of the echo signal of the ultrasonic probe and the corresponding similarly positioned probe at each scale for each ultrasonic probe based on the difference between the signal correction factors of the ultrasonic probe and the corresponding similarly positioned probe at each level.

[0142] In one embodiment, the processor further implements the following steps: for each ultrasound probe, respectively, based on the detail coefficient of the ultrasound probe's echo signal at each wavelet transform scale level, determining the mutation level based on the signal energy fluctuation level at each level; determining the attenuation unevenness of the local peaks at each mutation level at the same target moment; and determining the signal correction factor of the ultrasound probe's echo signal at each level based on the signal energy fluctuation level and the attenuation unevenness.

[0143] In one embodiment, the processor further implements the following steps: determining the signal energy at each moment at each level based on the detail coefficient of the echo signal of the ultrasound probe at each moment at each wavelet transform scale level; determining the energy value span of the signal energy at each moment at each level respectively; determining the total energy value span based on the sum of the energy value spans of each level; and determining the degree of signal energy fluctuation of the level respectively for each level based on the proportion of the energy value span of the level in the total energy value span.

[0144] In one embodiment, the processor further implements the following steps: performing local peak detection on each mutation level to determine the local peaks at several moments in each mutation level; screening the local peaks existing in each mutation level at the same target moment to obtain a candidate peak set; and determining the degree of attenuation unevenness of the local peaks in the candidate peak set as the level changes.

[0145] In one embodiment, the processor also implements the following steps: determining the difference between local peaks of each group of adjacent levels in the candidate peak set; determining the signal mean in the candidate peak set at the target time; determining the exponential attenuation factor of the candidate peak set based on the signal mean; determining the degree of uneven attenuation of local peaks in the candidate peak set as the level changes based on the ratio of the difference between local peaks of each group of adjacent levels to the exponential attenuation factor.

[0146] In one embodiment, the processor further implements the following steps: comparing the reconstructed signals of each ultrasonic probe with the standard echo signal to establish a defect feature model; judging whether there is a defect in the weld based on the defect feature model; if there is a defect, determining the type, location and size of the defect.

[0147] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this specification.

[0148] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0149] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A non-destructive testing method for pipeline welds based on ultrasonic technology, characterized in that: The method comprises: Acquire echo signals collected by each ultrasonic probe at the weld position of the pipeline; Analyzing the similarity of the time domain local features of the echo signals of each ultrasonic probe and the ultrasonic probe at an adjacent position at the same wavelet transform scale, and determining the position similar probes and position similarity parameters of each ultrasonic probe; determining a correction coefficient at each scale based on a position similarity parameter of the ultrasound probe and a difference in change of echo signals of the ultrasound probe and a corresponding similarly positioned probe at each scale; Correcting the detail coefficient of the echo signal of the ultrasonic probe at each scale according to the correction coefficient at each scale; Perform inverse wavelet transform based on the corrected detail coefficients at each scale to obtain the reconstructed signal; The reconstructed signals of each ultrasonic probe are compared with the standard echo signals to detect weld defects; The analyzing the similarity of the time domain local features of the echo signals of each ultrasonic probe and the adjacent ultrasonic probe at the same wavelet transform scale to determine the position similar probes and position similarity parameters of each ultrasonic probe includes: For each of the ultrasound probes, analyzing the similarity of the time domain local features of the echo signals of the ultrasound probe and the echo signals of the adjacent ultrasound probes at the same wavelet transform scale, and obtaining the position correlation between the echo signal of the ultrasound probe and the echo signals of the adjacent ultrasound probes; Taking the maximum value of the position correlation as a position similarity parameter, and determining the adjacent position ultrasound probe corresponding to the maximum value as a position similar probe; According to the detail coefficient of the echo signal of each ultrasonic probe at each wavelet transform scale level, the signal correction factor of the echo signal of each ultrasonic probe at each level is determined; the correction coefficient at each scale is determined according to the following formula: in, represents the correction coefficient at the jth scale, represents normalization processing, represents the position similarity parameter of the ultrasound 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 ultrasound probe at the jth scale level of the similar probe position; Determining the signal correction factor of the echo signal of each ultrasound probe at each level according to the detail coefficient of the echo signal of each ultrasound probe at each level of wavelet transform scale includes: For each of the ultrasound probes, determining the signal energy fluctuation degree at each level according to the detail coefficient of the echo signal of the ultrasound probe at each level of the wavelet transform scale; Determining the mutation level according to the signal energy fluctuation degree of each level; Determining the degree of attenuation unevenness of local peaks existing at the same target time for each of the mutation levels; determining a signal correction factor of the echo signal of the ultrasound probe at each level according to the signal energy fluctuation degree and the attenuation unevenness degree; The level at which the signal energy fluctuation degree is greater than or equal to a preset threshold is determined as the mutation level; The signal correction factor of the echo signal of the ultrasonic probe at each level is determined according to the ratio between the signal energy fluctuation degree and the attenuation unevenness degree at each level.

2. The nondestructive testing method for pipeline welds based on ultrasonic technology according to claim 1 is characterized in that: The analyzing the similarity of the time domain local features of the echo signals of the ultrasound probe and the echo signals of the adjacent ultrasound probes at the same wavelet transform scale to obtain the position correlation between the echo signals of the ultrasound probe and the echo signals of the adjacent ultrasound probes respectively includes: Calculating the degree of overlap and waveform shape similarity between the echo signal of the ultrasound probe and the echo signal of an adjacent ultrasound probe at the same wavelet transform scale; The position correlation between the echo signal of the ultrasonic probe and the echo signal of the ultrasonic probe at the adjacent position is determined according to the overlap degree and the waveform shape similarity.

3. The nondestructive testing method for pipeline welds based on ultrasonic technology according to claim 1 is characterized in that: Determining the signal energy fluctuation degree at each level according to the detail coefficient of the echo signal of the ultrasound probe at each level of wavelet transform scale includes: Determining the signal energy at each moment at each level according to the detail coefficient of the echo signal of the ultrasound probe at each moment at each wavelet transform scale level; Determining the energy value span of the signal energy at each time in each level respectively; Determining a total energy value span according to the sum of the energy value spans of each level; For each level respectively, the signal energy fluctuation degree of the level is determined according to the proportion of the energy value span of the level in the total energy value span.

4. The nondestructive testing method for pipeline welds based on ultrasonic technology according to claim 1 is characterized in that: The determining of the attenuation unevenness of the local peaks existing at the same target time for each of the mutation levels includes: Performing local peak detection on each of the mutation levels to determine local peaks at a plurality of moments in each of the mutation levels; Screening the local peaks existing at the same target time for each of the mutation levels to obtain a candidate peak set; Determine the degree of uneven attenuation of the local peaks in the candidate peak set as the levels change.

5. The nondestructive testing method for pipeline welds based on ultrasonic technology according to claim 4 is characterized in that: The determining of the attenuation unevenness of the local peaks in the candidate peak set as the levels change includes: Determining the difference between local peaks of adjacent levels in each group of the candidate peak set; Determining a signal mean value in the candidate peak set at the target time; determining an exponential decay factor of the candidate peak set according to the signal mean; The degree of attenuation unevenness of the local peaks in the candidate peak set as the levels change is determined according to the ratio of the difference between the local peaks of the adjacent levels and the exponential attenuation factor.

6. The non-destructive testing method for pipeline welds based on ultrasonic technology according to any one of claims 1 to 5, characterized in that: The reconstructed signals of each ultrasonic probe are compared with the standard echo signals to detect weld defects, including: The reconstructed signals of each ultrasonic probe are compared with the standard echo signals to establish a defect feature model; Determining whether there is a defect in the weld according to the defect characteristic model; If a defect is present, the type, location, and size of the defect are determined.

7. A pipeline weld nondestructive 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 as described in any one of claims 1 to 6.

Images