A pipeline defect monitoring method and device based on ultrasonic guided wave tomography

Abstract

The present invention discloses a pipeline defect monitoring method and device based on ultrasonic guided wave tomography. The method and device collect monitoring signals of a pipeline by controlling an ultrasonic guided wave transducer array to obtain a plurality of monitoring signals, and select an optimal reference signal corresponding to each monitoring signal from a pre-constructed reference signal database; calculate a signal difference coefficient between each monitoring signal and its corresponding optimal reference signal, and calculate a defect probability corresponding to each signal difference coefficient, and superimpose a defect probability distribution map corresponding to each generated defect probability to generate a first defect probability RAPID tomography image; perform image preprocessing on the first defect probability RAPID tomography image, and obtain and extract pipeline defect information in a second defect probability RAPID tomography image. Compared with the prior art, the present invention extracts defect probability information through an ultrasonic guided wave RAPID tomography image generated by monitoring signals and reference signals, and can improve the reliability of defect detection.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline structure monitoring, and in particular to a pipeline defect monitoring method and device based on ultrasonic guided wave tomography. Background Art

[0002] The safe operation of oil and gas pipelines is related to the national economic lifeline and people's livelihood security, and plays an irreplaceable role in many industrial and civilian fields. The long-term safe operation of oil and gas pipelines is inseparable from an economical, practical, safe and reliable non-destructive testing and structural safety and health monitoring method. Although there are many non-destructive testing and structural safety and health monitoring methods, the advantages are obvious but the disadvantages are also very prominent. Ultrasonic guided wave non-destructive testing technology can achieve the advantages of single-point excitation long-distance detection and full-section detection, which is very suitable for long-distance monitoring of oil and gas pipelines.

[0003] Existing ultrasonic guided wave monitoring technologies are basically based on single-channel detection technology. Although single-channel ultrasonic guided wave detection technology can meet general detection needs, it has a single function and cannot achieve other more advanced and effective functions. It loses the information dimension of the guided wave detection signal, omits a large amount of detection information, and the detection results are relatively unstable. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a pipeline defect monitoring method and device based on ultrasonic guided wave tomography, which can obtain pipeline defect information by generating an ultrasonic guided wave RAPID tomography image through multiple monitoring signals and their corresponding optimal reference signals, thereby improving the reliability of defect detection.

[0005] In order to solve the above technical problems, the present invention provides a pipeline defect monitoring method based on ultrasonic guided wave tomography, comprising:

[0006] Controlling the ultrasonic guided wave transducer array to collect monitoring signals from the pipeline to obtain a plurality of monitoring signals, and performing mean normalization processing on the plurality of monitoring signals to obtain a first mapping amplitude of each monitoring signal;

[0007] Acquire a pipeline temperature of the pipeline, and select an optimal reference signal corresponding to each monitoring signal from a pre-constructed reference signal database based on the pipeline temperature and the first mapping amplitude;

[0008] Calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it to obtain multiple signal difference coefficients; calculate the defect probability corresponding to each signal difference coefficient based on a preset defect probability calculation formula, generate a defect probability distribution map corresponding to each defect probability, superimpose all defect probability distribution maps, and generate a first defect probability RAPID tomographic image;

[0009] The first defect probability RAPID tomography image is subjected to image preprocessing to obtain a second defect probability RAPID tomography image, and pipeline defect information is extracted from the second defect probability RAPID tomography image to obtain pipeline defect information, wherein the image preprocessing includes filtering, enhancement, binarization, and edge extraction.

[0010] In a possible implementation, before controlling the ultrasonic guided wave transducer array to collect monitoring signals for the pipeline, the method further includes:

[0011] An ultrasonic guided wave transducer array is arranged on the pipeline, wherein the ultrasonic guided wave transducer array comprises a transmitting transducer array and a receiving transducer array, and the transmitting transducer array comprises 12 transmitting transducers, and the receiving transducer array comprises 12 receiving transducers;

[0012] All transmitting transducers in the transmitting transducer array are evenly arranged on the circumference of the first end of the pipeline in the order of transmitting transducer numbers, and all receiving transducers in the receiving transducer array are evenly arranged on the circumference of the second end of the pipeline in the order of receiving transducer numbers.

[0013] In a possible implementation, the ultrasonic guided wave transducer array is controlled to collect monitoring signals from the pipeline to obtain multiple monitoring signals, specifically including:

[0014] Controlling each transmitting transducer in the transmitting transducer array to transmit ultrasonic guided wave signals to all receiving transducers in sequence, so that each receiving transducer receives the ultrasonic guided wave signals transmitted by all transmitting transducers in sequence;

[0015] Each ultrasonic guided wave signal received by each receiving transducer is used as a monitoring signal, and a signal tag is set for each monitoring signal, wherein the signal tag includes a transmitting transducer number and a receiving transducer number.

[0016] In a possible implementation, the process of building a reference signal database specifically includes:

[0017] Acquire multiple pipeline temperatures of the pipeline, and at the same pipeline temperature, control the ultrasonic guided wave transducer array to repeatedly collect reference signals from the pipeline for a preset number of times to obtain multiple groups of reference signals, wherein each group of reference signals includes multiple reference signals;

[0018] Calculating the mean square error of the maximum amplitude of the reference signal envelope of each group of reference signals, and screening the multiple groups of reference signals based on the mean square error to obtain multiple groups of screened reference signals;

[0019] Performing mean normalization processing on each of the multiple groups of filtered reference signals to obtain a mapping amplitude corresponding to each of the filtered reference signals;

[0020] A reference signal database is constructed based on all the screened reference signals obtained at different pipeline temperatures and their corresponding mapping amplitudes.

[0021] In a possible implementation, calculating the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it specifically includes:

[0022]

[0023] Where m is the number of the transmitting transducer, n is the number of the receiving transducer, t0 is the direct time of the signal from the transmitting transducer to the receiving transducer, μ represents the average value of the corresponding signal, and ΔT is the time window width.

[0024] In a possible implementation, based on a preset defect probability calculation formula, the defect probability corresponding to each signal difference coefficient is calculated respectively, specifically including:

[0025] The preset defect probability calculation formula is as follows:

[0026] P m-n (x,y)=SDC m-n S m-n (x,y);

[0027] In the formula, S m-n (x,y) is the spatial distribution function of the signal difference coefficient.

[0028] In a possible implementation, extracting pipeline defect information from the second defect probability RAPID tomographic image to obtain pipeline defect information specifically includes:

[0029] Obtain the pixel value of each pixel in the second defect probability RAPID tomography image, and compare the pixel value with the preset pixel threshold. If the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is high; if the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is low.

[0030] The present invention also provides a pipeline defect monitoring device based on ultrasonic guided wave tomography, comprising: a monitoring signal acquisition module, an optimal reference signal selection module, a defect probability RAPID tomography image generation module and a pipeline defect information extraction module;

[0031] The monitoring signal acquisition module is used to control the ultrasonic guided wave transducer array to collect monitoring signals from the pipeline to obtain multiple monitoring signals, and perform mean normalization processing on the multiple monitoring signals to obtain a first mapping amplitude of each monitoring signal;

[0032] The optimal reference signal selection module is used to obtain the pipeline temperature of the pipeline, and select the optimal reference signal corresponding to each monitoring signal from a pre-built reference signal database based on the pipeline temperature and the first mapping amplitude;

[0033] The defect probability RAPID tomographic image generation module is used to calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it, obtain multiple signal difference coefficients, calculate the defect probability corresponding to each signal difference coefficient based on a preset defect probability calculation formula, generate a defect probability distribution map corresponding to each defect probability, superimpose all defect probability distribution maps, and generate a first defect probability RAPID tomographic image;

[0034] The pipeline defect information extraction module is used to perform image preprocessing on the first defect probability RAPID tomography image to obtain a second defect probability RAPID tomography image, and perform pipeline defect information extraction on the second defect probability RAPID tomography image to obtain pipeline defect information, wherein the image preprocessing includes filtering, enhancement, binarization, and edge extraction.

[0035] In a possible implementation, the monitoring signal acquisition module is further used to:

[0036] An ultrasonic guided wave transducer array is arranged on the pipeline, wherein the ultrasonic guided wave transducer array comprises a transmitting transducer array and a receiving transducer array, and the transmitting transducer array comprises 12 transmitting transducers, and the receiving transducer array comprises 12 receiving transducers;

[0037] All transmitting transducers in the transmitting transducer array are evenly arranged on the circumference of the first end of the pipeline in the order of transmitting transducer numbers, and all receiving transducers in the receiving transducer array are evenly arranged on the circumference of the second end of the pipeline in the order of receiving transducer numbers.

[0038] In a possible implementation, the monitoring signal acquisition module is used to control the ultrasonic guided wave transducer array to acquire monitoring signals from the pipeline to obtain multiple monitoring signals, specifically including:

[0039] Controlling each transmitting transducer in the transmitting transducer array to transmit ultrasonic guided wave signals to all receiving transducers in sequence, so that each receiving transducer receives the ultrasonic guided wave signals transmitted by all transmitting transducers in sequence;

[0040] Each ultrasonic guided wave signal received by each receiving transducer is used as a monitoring signal, and a signal tag is set for each monitoring signal, wherein the signal tag includes a transmitting transducer number and a receiving transducer number.

[0041] In a possible implementation, the optimal reference signal selection module is further used to construct a reference signal database, which specifically includes:

[0042] Acquire multiple pipeline temperatures of the pipeline, and at the same pipeline temperature, control the ultrasonic guided wave transducer array to repeatedly collect reference signals from the pipeline for a preset number of times to obtain multiple groups of reference signals, wherein each group of reference signals includes multiple reference signals;

[0043] Calculating the mean square error of the maximum amplitude of the reference signal envelope of each group of reference signals, and screening the multiple groups of reference signals based on the mean square error to obtain multiple groups of screened reference signals;

[0044] Performing mean normalization processing on each of the multiple groups of filtered reference signals to obtain a mapping amplitude corresponding to each of the filtered reference signals;

[0045] A reference signal database is constructed based on all the screened reference signals obtained at different pipeline temperatures and their corresponding mapping amplitudes.

[0046] In a possible implementation, the defect probability RAPID tomographic image generation module is used to calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it, specifically including:

[0047]

[0048] Where m is the number of the transmitting transducer, n is the number of the receiving transducer, t0 is the direct time of the signal from the transmitting transducer to the receiving transducer, μ represents the average value of the corresponding signal, and ΔT is the time window width.

[0049] In a possible implementation, the defect probability RAPID tomographic image generation module is used to calculate the defect probability corresponding to each signal difference coefficient based on a preset defect probability calculation formula, specifically including:

[0050] The preset defect probability calculation formula is as follows:

[0051] P m-n (x,y)=SDC m-n S m-n (x,y);

[0052] In the formula, S m-n (x,y) is the spatial distribution function of the signal difference coefficient.

[0053] In a possible implementation, the pipeline defect information extraction module is used to extract pipeline defect information from the second defect probability RAPID tomography image to obtain pipeline defect information, specifically including:

[0054] Obtain the pixel value of each pixel in the second defect probability RAPID tomography image, and compare the pixel value with the preset pixel threshold. If the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is high; if the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is low.

[0055] The present invention also provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the pipeline defect monitoring method based on ultrasonic guided wave tomography as described in any one of the above items is implemented.

[0056] The present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the pipeline defect monitoring method based on ultrasonic guided wave tomography as described in any one of the above.

[0057] The pipeline defect monitoring method and device based on ultrasonic guided wave tomography in the embodiment of the present invention have the following beneficial effects compared with the prior art:

[0058] The pipeline monitoring signal is collected by controlling the ultrasonic guided wave transducer array to obtain multiple monitoring signals, and the multiple monitoring signals are mean-normalized to obtain a first mapping amplitude of each monitoring signal; the pipeline temperature of the pipeline is obtained, and based on the pipeline temperature and the first mapping amplitude, the optimal reference signal corresponding to each monitoring signal is selected from a pre-constructed reference signal database; the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it is calculated to obtain multiple signal difference coefficients; based on a preset defect probability calculation formula, the defect probability corresponding to each signal difference coefficient is calculated respectively, and a defect probability distribution map corresponding to each defect probability is generated, and all defect probability distribution maps are superimposed to generate a first defect probability RAPID tomography image; the first defect probability RAPID tomography image is image preprocessed to obtain a second defect probability RAPID tomography image, and pipeline defect information is extracted from the second defect probability RAPID tomography image to obtain pipeline defect information, wherein the image preprocessing includes filtering, enhancement, binarization, and edge extraction. Compared with the prior art, the technical solution of the present invention acquires multiple monitoring signals and generates ultrasonic guided wave RAPID tomographic images based on the multiple monitoring signals and their corresponding optimal reference signals, so as to obtain the defect probability information of the pipeline. Compared with the single-channel ultrasonic guided wave detection information, it is more comprehensive and can improve the reliability of defect detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a flow chart of an embodiment of a pipeline defect monitoring method based on ultrasonic guided wave tomography provided by the present invention;

[0060] Figure 2 It is a structural schematic diagram of an embodiment of a pipeline defect monitoring device based on ultrasonic guided wave tomography provided by the present invention;

[0061] Figure 3 It is a schematic diagram of the arrangement of an ultrasonic guided wave transducer array according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] Example 1

[0064] See also Figure 1 , Figure 1FIG. 1 is a flow chart of an embodiment of a pipeline defect monitoring method based on ultrasonic guided wave tomography provided by the present invention. Figure 1 As shown, the method includes steps 101 to 104, which are specifically as follows:

[0065] Step 101: Control the ultrasonic guided wave transducer array to collect monitoring signals from the pipeline to obtain multiple monitoring signals, and perform mean normalization processing on the multiple monitoring signals to obtain a first mapping amplitude of each monitoring signal.

[0066] In one embodiment, an ultrasonic guided wave transducer array is arranged in the pipeline, and the ultrasonic guided wave transducer array is connected to the ultrasonic guided wave monitoring equipment, wherein the ultrasonic guided wave transducer array includes a transmitting transducer array and a receiving transducer array, and the transmitting transducer array includes 12 transmitting transducers, and the receiving transducer array includes 12 receiving transducers.

[0067] In one embodiment, all the transmitting transducers in the transmitting transducer array are evenly arranged on the circumference of the first end of the pipeline in the order of the transmitting transducer numbers, and all the receiving transducers in the receiving transducer array are evenly arranged on the circumference of the second end of the pipeline in the order of the receiving transducer numbers. Figure 3 As shown, Figure 3 This is a schematic diagram of the arrangement of an ultrasonic guided wave transducer array according to an embodiment of the present invention. In the figure, T1-T12 are 12 transmitting transducers, and R1-R12 are 12 receiving transducers.

[0068] In one embodiment, the pipeline area between the transmitting transducer array and the receiving transducer array is the pipeline monitoring area, and defect monitoring of the pipeline is mainly to detect pipeline defects in the pipeline monitoring area. Based on the connection relationship between the ultrasonic guided wave transducer array and the ultrasonic guided wave monitoring equipment, the pipeline defects in the pipeline monitoring area can be monitored by the ultrasonic guided wave monitoring equipment.

[0069] In one embodiment, the transmitting transducer array and the receiving transducer array are mainly used to transmit and receive torsional mode ultrasonic guided wave signals, and the ultrasonic guided wave waveform is a 128 Hz sine wave with 5 cycles.

[0070] In one embodiment, each transmitting transducer in the transmitting transducer array is controlled to transmit an ultrasonic guided wave signal to all receiving transducers in turn, so that each receiving transducer receives the ultrasonic guided wave signals transmitted by all transmitting transducers in turn, each ultrasonic guided wave signal received by each receiving transducer is used as a monitoring signal, and a signal mark is set for each monitoring signal, wherein the signal mark includes the transmitting transducer number and the receiving transducer number.

[0071] Specifically, when the ultrasonic guided wave monitoring equipment collects signals, the transmitting transducer T1 transmits the ultrasonic guided wave, and the receiving transducers R1 to R12 receive the ultrasonic guided wave signals respectively, which are marked as S1-1 to S1-12, and stored as the collected monitoring signals; then the transmitting transducers T2 to T12 transmit in sequence, and the above signal collection process is repeated. The received signals are marked and stored as Sm-n, where m is the transmitting transducer number and n is the receiving transducer number.

[0072] In one embodiment, mean normalization processing is performed on the collected multiple monitoring signals, and the amplitudes of the monitoring signals are mapped to a range of -1 to 1, so as to obtain a first mapping amplitude of each monitoring signal.

[0073] Step 102: Obtain the pipeline temperature of the pipeline, and select the optimal reference signal corresponding to each monitoring signal from a pre-constructed reference signal database based on the pipeline temperature and the first mapping amplitude.

[0074] In one embodiment, during normal operation of the pipeline, the ultrasonic guided wave monitoring device collects reference signals at different pipeline temperatures and establishes a reference signal database, which serves as a basis for subsequent pipeline defect identification and extraction.

[0075] In one embodiment, reference signals are collected by acquiring multiple pipeline temperatures of the pipeline. At the same pipeline temperature, the ultrasonic guided wave transducer array is controlled to repeatedly collect reference signals from the pipeline for a preset number of times to obtain multiple groups of reference signals, wherein each group of reference signals includes multiple reference signals.

[0076] Specifically, before the reference signal is collected, the temperature of the pipeline is measured with a thermometer and the pipeline temperature is recorded; preferably, the temperature of the pipeline can also be measured with a temperature sensor arranged on the pipeline to obtain the pipeline temperature.

[0077] At the same pipeline temperature, each transmitting transducer in the transmitting transducer array is controlled to transmit ultrasonic guided wave signals to all receiving transducers in turn, so that each receiving transducer receives the ultrasonic guided wave signals transmitted by all transmitting transducers in turn, each ultrasonic guided wave signal received by each receiving transducer is used as a reference signal, and a signal mark is set for each monitoring reference, wherein the signal mark includes the transmitting transducer number and the receiving transducer number.

[0078] At the same pipeline temperature, a preset number of times is set, and the reference signal of the pipeline is repeatedly collected based on the preset number of times, so as to obtain multiple groups of reference signals at the same pipeline temperature; preferably, the preset number of times can be 15 to 20 times, and can also be set arbitrarily based on user needs.

[0079] In one embodiment, the mean square error of the maximum amplitude of the reference signal envelope of each group of reference signals is calculated, and based on the mean square value, the multiple groups of reference signals are screened to obtain multiple groups of screened reference signals.

[0080] Specifically, for multiple groups of reference signals obtained at the same pipeline temperature, the mean square error of the maximum amplitude of the envelope of each group of reference signals is calculated, and each group of reference signals is screened with 20% of the maximum amplitude of the envelope of the reference signal as a threshold. If the mean square error is greater than the threshold, the group of reference signals is discarded; if the mean square error is less than the threshold, the group of reference signals is used as the screened reference signals, and the screened reference signals and their corresponding pipeline temperatures are stored in the reference signal database.

[0081] In one embodiment, mean normalization is performed on each of the multiple groups of filtered reference signals, and the amplitude of each filtered reference signal is mapped to an interval of -1 to 1 to obtain a mapping amplitude corresponding to each filtered reference signal.

[0082] In one embodiment, a reference signal database is constructed based on all the screened reference signals obtained at different pipeline temperatures and their corresponding mapping amplitudes, so that the reference signal database records the reference signals at different pipeline temperatures and their corresponding mapping amplitudes.

[0083] Preferably, for high-temperature pipelines, the temperature should be gradually increased during the reference signal collection process, and a set of reference signals should be collected every 10 degrees Celsius. For normal temperature pipelines, reference signal collection should be selected when the temperature difference is relatively large as much as possible, and a set of reference signals should be collected every 3 to 5 degrees Celsius.

[0084] In one embodiment, since the pre-constructed reference signal database contains reference signals at different pipeline temperatures and their corresponding mapping amplitudes, therefore, in the pipeline defect detection process, based on the first mapping amplitude corresponding to the monitoring signal obtained in step 101 and the pipeline temperature of the pipeline obtained at the current moment, the reference signal database can be traversed based on the first mapping amplitude and the pipeline temperature, and the reference signal database is selected as the optimal reference signal for RAPID tomography analysis.

[0085] Step 103: Calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it to obtain multiple signal difference coefficients; based on a preset defect probability calculation formula, calculate the defect probability corresponding to each signal difference coefficient respectively, generate a defect probability distribution map corresponding to each defect probability, superimpose all defect probability distribution maps, and generate a first defect probability RAPID tomography image.

[0086] In one embodiment, the signal difference coefficient (SDC) of the reference signal Sm-n and the monitoring signal Mm-n is calculated using the following formula:

[0087]

[0088] Where m is the number of the transmitting transducer, n is the number of the receiving transducer, t0 is the direct time of the signal from the transmitting transducer to the receiving transducer, μ represents the average value of the corresponding signal, and ΔT is the time window width.

[0089] In one embodiment, the defect probability distribution diagram in the adjacent area is reconstructed according to the calculated signal difference coefficient of a path from the transmitting transducer to the receiving transducer. The defect probability Pm-n(x, y) of a path from the transmitting transducer to the receiving transducer can be reconstructed by the following formula:

[0090] P m-n (x,y)=SDC m-n S m-n (x,y);

[0091] In the formula, S m-n (x,y) is the spatial distribution function of the signal difference coefficient.

[0092] In one embodiment, by calculating the defect probability near each path from the transmitting transducer to the receiving transducer in the entire ultrasonic guided wave transducer array, a RAPID tomographic image of the defect probability of the entire pipeline can be obtained by superposition.

[0093] Step 104: performing image preprocessing on the first defect probability RAPID tomography image to obtain a second defect probability RAPID tomography image, and extracting pipeline defect information from the second defect probability RAPID tomography image to obtain pipeline defect information, wherein the image preprocessing includes filtering, enhancement, binarization, and edge extraction.

[0094] In one embodiment, filtering is performed on the first defect probability RAPID tomographic image, which can eliminate the influence of noise introduced by complex factors such as instrument electrical noise during ultrasonic guided wave monitoring on the subsequent processing accuracy of the first defect probability RAPID tomographic image.

[0095] In one embodiment, the first defect probability RAPID tomography image is also enhanced by obtaining the grayscale value of each pixel in the first defect probability RAPID tomography image, dividing all grayscale values ​​into three segments, and performing linear enhancement processing on each grayscale value segment, wherein the value range of the grayscale value segment is 0-60, and the grayscale value segment is a tiny background signal of the pipeline, which is weakened; the value range of the grayscale value segment is 61-210, and the grayscale value segment 2 is a defect signal, which is highlighted and enhanced; the grayscale value segment 3 is 211-255, and the grayscale value segment 3 is an inherent characteristic signal of the pipeline, which is smoothed, which can solve the problem of unclear contrast between image defects and background grayscale and highlight defect features.

[0096] In one embodiment, the first defect probability RAPID tomographic image is further binarized to highlight pipeline features, improve image contrast, enhance defect edge effects, and suppress the effects of unimportant information in the image.

[0097] In one embodiment, edge extraction processing is also performed on the first defect probability RAPID tomography image. Defect edge detection can be performed on the first defect probability RAPID tomography image based on the Roberts operator to extract edge features and obtain a second defect probability RAPID tomography image, thereby achieving the purpose of defect feature extraction.

[0098] In one embodiment, the pixel value of each pixel in the second defect probability RAPID tomographic image is obtained, and the pixel value is compared with a preset pixel threshold. If the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is high, and if the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is low. The preset pixel threshold is a threshold set based on user needs.

[0099] Example 2

[0100] See also Figure 2 , Figure 2 is a schematic structural diagram of an embodiment of a pipeline defect monitoring device based on ultrasonic guided wave tomography provided by the present invention, such as Figure 2 As shown, the device includes a monitoring signal acquisition module 201, an optimal reference signal selection module 202, a defect probability RAPID tomographic image generation module 203 and a pipeline defect information extraction module 204, which are specifically as follows:

[0101] The monitoring signal acquisition module 201 is used to control the ultrasonic guided wave transducer array to acquire monitoring signals from the pipeline to obtain multiple monitoring signals, and perform mean normalization processing on the multiple monitoring signals to obtain a first mapping amplitude of each monitoring signal.

[0102] The optimal reference signal selection module 202 is used to obtain the pipeline temperature of the pipeline, and select the optimal reference signal corresponding to each monitoring signal from a pre-constructed reference signal database based on the pipeline temperature and the first mapping amplitude.

[0103] The defect probability RAPID tomographic image generation module 203 is used to calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it, obtain multiple signal difference coefficients, and based on a preset defect probability calculation formula, respectively calculate the defect probability corresponding to each signal difference coefficient, generate a defect probability distribution map corresponding to each defect probability, superimpose all defect probability distribution maps, and generate a first defect probability RAPID tomographic image.

[0104] The pipeline defect information extraction module 204 is used to perform image preprocessing on the first defect probability RAPID tomography image to obtain a second defect probability RAPID tomography image, and perform pipeline defect information extraction on the second defect probability RAPID tomography image to obtain pipeline defect information, wherein the image preprocessing includes filtering, enhancement, binarization, and edge extraction.

[0105] In one embodiment, the monitoring signal acquisition module 201 is also used to set an ultrasonic guided wave transducer array for the pipeline, wherein the ultrasonic guided wave transducer array includes a transmitting transducer array and a receiving transducer array, and the transmitting transducer array includes 12 transmitting transducers, and the receiving transducer array includes 12 receiving transducers; all transmitting transducers in the transmitting transducer array are evenly arranged on the circumference of the first end of the pipeline in the order of the transmitting transducer numbers, and all receiving transducers in the receiving transducer array are evenly arranged on the circumference of the second end of the pipeline in the order of the receiving transducer numbers.

[0106] In one embodiment, the monitoring signal acquisition module 201 is used to control the ultrasonic guided wave transducer array to collect monitoring signals for the pipeline to obtain multiple monitoring signals, specifically including: controlling each transmitting transducer in the transmitting transducer array to transmit ultrasonic guided wave signals to all receiving transducers in turn, so that each receiving transducer receives the ultrasonic guided wave signals transmitted by all transmitting transducers in turn; using each ultrasonic guided wave signal received by each receiving transducer as a monitoring signal, and setting a signal mark for each monitoring signal, wherein the signal mark includes the transmitting transducer number and the receiving transducer number.

[0107] In one embodiment, the optimal reference signal selection module 202 is also used to construct a reference signal database, which specifically includes: obtaining multiple pipeline temperatures of the pipeline, and at the same pipeline temperature, controlling the ultrasonic guided wave transducer array to repeatedly collect reference signals from the pipeline for a preset number of times to obtain multiple groups of reference signals, wherein each group of reference signals includes multiple reference signals; calculating the mean square error of the maximum amplitude of the reference signal envelope of each group of reference signals, and based on the mean square value, filtering the multiple groups of reference signals to obtain multiple groups of filtered reference signals; performing mean normalization processing on each filtered reference signal in the multiple groups of filtered reference signals to obtain a mapping amplitude corresponding to each filtered reference signal; and constructing a reference signal database based on all filtered reference signals obtained at different pipeline temperatures and their corresponding mapping amplitudes.

[0108] In one embodiment, the defect probability RAPID tomographic image generation module 203 is used to calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it, specifically including:

[0109]

[0110] Where m is the number of the transmitting transducer, n is the number of the receiving transducer, t0 is the direct time of the signal from the transmitting transducer to the receiving transducer, μ represents the average value of the corresponding signal, and ΔT is the time window width.

[0111] In one embodiment, the defect probability RAPID tomographic image generation module 203 is used to calculate the defect probability corresponding to each signal difference coefficient based on a preset defect probability calculation formula, specifically including:

[0112] The preset defect probability calculation formula is as follows:

[0113] P m-n (x,y)=SDC m-n S m-n (x,y);

[0114] In the formula, S m-n (x,y) is the spatial distribution function of the signal difference coefficient.

[0115] In one embodiment, the pipeline defect information extraction module 204 is used to extract pipeline defect information from the second defect probability RAPID tomography image to obtain pipeline defect information, specifically including: obtaining the pixel value of each pixel in the second defect probability RAPID tomography image, comparing the pixel value with a preset pixel threshold, if the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is relatively high, if the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect at the pixel is relatively low.

[0116] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0117] It should be noted that the above-mentioned embodiment of the pipeline defect monitoring device based on ultrasonic guided wave tomography is only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0118] Based on the above-mentioned embodiment of the pipeline defect monitoring method based on ultrasonic guided wave tomography, another embodiment of the present invention provides a pipeline defect monitoring terminal device based on ultrasonic guided wave tomography. The pipeline defect monitoring terminal device based on ultrasonic guided wave tomography includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the pipeline defect monitoring method based on ultrasonic guided wave tomography according to any embodiment of the present invention is implemented.

[0119] Exemplarily, in this embodiment, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program in the pipeline defect monitoring terminal device based on ultrasonic guided wave tomography.

[0120] The pipeline defect monitoring terminal device based on ultrasonic guided wave tomography can be a computing device such as a desktop computer, a notebook, a handheld computer, a cloud server, etc. The pipeline defect monitoring terminal device based on ultrasonic guided wave tomography can include, but is not limited to, a processor and a memory.

[0121] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the pipeline defect monitoring terminal device based on ultrasonic guided wave tomography, and uses various interfaces and lines to connect various parts of the entire pipeline defect monitoring terminal device based on ultrasonic guided wave tomography.

[0122] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the pipeline defect monitoring terminal device based on ultrasonic guided wave tomography by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0123] Based on the above-mentioned embodiment of the pipeline defect monitoring method based on ultrasonic guided wave tomography, another embodiment of the present invention provides a storage medium, wherein the storage medium includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the pipeline defect monitoring method based on ultrasonic guided wave tomography according to any embodiment of the present invention.

[0124] In this embodiment, the storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0125] In summary, the present invention provides a pipeline defect monitoring method and device based on ultrasonic guided wave tomography, which collects monitoring signals of the pipeline by controlling the ultrasonic guided wave transducer array to obtain multiple monitoring signals, and selects the optimal reference signal corresponding to each monitoring signal from a pre-constructed reference signal database; calculates the signal difference coefficient between each monitoring signal and its corresponding optimal reference signal, and calculates the defect probability corresponding to each signal difference coefficient, superimposes the defect probability distribution map corresponding to each generated defect probability, and generates a first defect probability RAPID tomography image; performs image preprocessing on the first defect probability RAPID tomography image, obtains and extracts pipeline defect information in the second defect probability RAPID tomography image. Compared with the prior art, the present invention extracts defect probability information through the ultrasonic guided wave RAPID tomography image generated by the monitoring signal and the reference signal, which can improve the reliability of defect detection.

[0126] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A pipeline defect monitoring method based on ultrasonic guided wave tomography, characterized in that: include: Controlling the ultrasonic guided wave transducer array to collect monitoring signals from the pipeline to obtain a plurality of monitoring signals, and performing mean normalization processing on the plurality of monitoring signals to obtain a first mapping amplitude of each monitoring signal; Acquire a pipeline temperature of the pipeline, and select an optimal reference signal corresponding to each monitoring signal from a pre-constructed reference signal database based on the pipeline temperature and the first mapping amplitude; Calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it to obtain multiple signal difference coefficients; calculate the defect probability corresponding to each signal difference coefficient based on a preset defect probability calculation formula, generate a defect probability distribution map corresponding to each defect probability, superimpose all defect probability distribution maps, and generate a first defect probability RAPID tomographic image; Performing image preprocessing on the first defect probability RAPID tomography image to obtain a second defect probability RAPID tomography image, and extracting pipeline defect information from the second defect probability RAPID tomography image to obtain pipeline defect information, wherein the image preprocessing includes filtering, enhancement, binarization, and edge extraction; The construction process of the reference signal database specifically includes: Acquire multiple pipeline temperatures of the pipeline, and at the same pipeline temperature, control the ultrasonic guided wave transducer array to repeatedly collect reference signals from the pipeline for a preset number of times to obtain multiple groups of reference signals, wherein each group of reference signals includes multiple reference signals; Calculating the mean square error of the maximum amplitude of the reference signal envelope of each group of reference signals, and screening the multiple groups of reference signals based on the mean square error to obtain multiple groups of screened reference signals; Performing mean normalization processing on each of the multiple groups of filtered reference signals to obtain a mapping amplitude corresponding to each of the filtered reference signals; A reference signal database is constructed based on all the screened reference signals obtained at different pipeline temperatures and their corresponding mapping amplitudes; The calculating of the signal difference coefficient between each monitoring signal and the corresponding optimal reference signal specifically includes: ； In the formula, S m-n is the reference signal, M m-n To monitor the signal, is the transmitting transducer number, is the receiving transducer number, is the direct signal time from the transmitting transducer to the receiving transducer, represents the average value of the corresponding signal, is the time window width; The defect probability calculation formula based on the preset defect probability calculation formula is used to calculate the defect probability corresponding to each signal difference coefficient, specifically including: The preset defect probability calculation formula is as follows: ； In the formula, is the spatial distribution function of the signal difference coefficient.

2. A pipeline defect monitoring method based on ultrasonic guided wave tomography according to claim 1, characterized in that: Before controlling the ultrasonic guided wave transducer array to collect monitoring signals for the pipeline, it also includes: An ultrasonic guided wave transducer array is arranged on the pipeline, wherein the ultrasonic guided wave transducer array comprises a transmitting transducer array and a receiving transducer array, and the transmitting transducer array comprises 12 transmitting transducers, and the receiving transducer array comprises 12 receiving transducers; All transmitting transducers in the transmitting transducer array are evenly arranged on the circumference of the first end of the pipeline in the order of transmitting transducer numbers, and all receiving transducers in the receiving transducer array are evenly arranged on the circumference of the second end of the pipeline in the order of receiving transducer numbers.

3. A pipeline defect monitoring method based on ultrasonic guided wave tomography according to claim 2, characterized in that: Control the ultrasonic guided wave transducer array to collect monitoring signals from the pipeline to obtain multiple monitoring signals, including: Controlling each transmitting transducer in the transmitting transducer array to transmit ultrasonic guided wave signals to all receiving transducers in sequence, so that each receiving transducer receives the ultrasonic guided wave signals transmitted by all transmitting transducers in sequence; Each ultrasonic guided wave signal received by each receiving transducer is used as a monitoring signal, and a signal tag is set for each monitoring signal, wherein the signal tag includes a transmitting transducer number and a receiving transducer number.

4. The pipeline defect monitoring method based on ultrasonic guided wave tomography according to claim 1, characterized in that: Extracting pipeline defect information from the second defect probability RAPID tomographic image to obtain pipeline defect information specifically includes: The pixel value of each pixel in the second defect probability RAPID tomography image is obtained, and the pixel value is compared with a preset pixel threshold. If the pixel value is greater than or equal to the preset pixel threshold, it is considered that the probability of a defect occurring in the pixel is high.

5. A pipeline defect monitoring device based on ultrasonic guided wave tomography, characterized in that: include: Monitoring signal acquisition module, optimal reference signal selection module, defect probability RAPID tomography image generation module and pipeline defect information extraction module; The monitoring signal acquisition module is used to control the ultrasonic guided wave transducer array to collect monitoring signals from the pipeline to obtain multiple monitoring signals, and perform mean normalization processing on the multiple monitoring signals to obtain a first mapping amplitude of each monitoring signal; The optimal reference signal selection module is used to obtain the pipeline temperature of the pipeline, and select the optimal reference signal corresponding to each monitoring signal from a pre-built reference signal database based on the pipeline temperature and the first mapping amplitude; The defect probability RAPID tomographic image generation module is used to calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it, obtain multiple signal difference coefficients, calculate the defect probability corresponding to each signal difference coefficient based on a preset defect probability calculation formula, generate a defect probability distribution map corresponding to each defect probability, superimpose all defect probability distribution maps, and generate a first defect probability RAPID tomographic image; The pipeline defect information extraction module is used to perform image preprocessing on the first defect probability RAPID tomography image to obtain a second defect probability RAPID tomography image, and extract pipeline defect information from the second defect probability RAPID tomography image to obtain pipeline defect information, wherein the image preprocessing includes filtering, enhancement, binarization, and edge extraction; The optimal reference signal selection module is also used to construct a reference signal database, which specifically includes: Acquire multiple pipeline temperatures of the pipeline, and at the same pipeline temperature, control the ultrasonic guided wave transducer array to repeatedly collect reference signals from the pipeline for a preset number of times to obtain multiple groups of reference signals, wherein each group of reference signals includes multiple reference signals; Calculating the mean square error of the maximum amplitude of the reference signal envelope of each group of reference signals, and screening the multiple groups of reference signals based on the mean square error to obtain multiple groups of screened reference signals; Performing mean normalization processing on each of the multiple groups of filtered reference signals to obtain a mapping amplitude corresponding to each of the filtered reference signals; A reference signal database is constructed based on all the screened reference signals obtained at different pipeline temperatures and their corresponding mapping amplitudes; The defect probability RAPID tomographic image generation module is used to calculate the signal difference coefficient between each monitoring signal and the optimal reference signal corresponding to it, specifically including: ； In the formula, S m-n is the reference signal, M m-n To monitor the signal, is the transmitting transducer number, is the receiving transducer number, is the direct signal time from the transmitting transducer to the receiving transducer, represents the average value of the corresponding signal, is the time window width; The defect probability RAPID tomographic image generation module is used to calculate the defect probability corresponding to each signal difference coefficient based on a preset defect probability calculation formula, specifically including: The preset defect probability calculation formula is as follows: ； In the formula, is the spatial distribution function of the signal difference coefficient.

6. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the pipeline defect monitoring method based on ultrasonic guided wave tomography according to any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the pipeline defect monitoring method based on ultrasonic guided wave tomography according to any one of claims 1 to 4.

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