Pipeline inspection data alignment method and system, storage medium and electronic device

Abstract

The present application relates to pipeline detection data alignment method, system, storage medium and electronic equipment, including: obtaining the first internal detection data and the second internal detection data of the to-be-tested pipeline in the front and back two times of pipeline internal detection;Determine the to-be-compared pipe joint without repair record between two internal detections in all pipe joints of the to-be-tested pipeline, and respectively compare the first internal detection data and the second internal detection data of each to-be-compared pipe joint, and determine each to-be-compared pipe joint with each comparison result as comparison success as the target pipe joint;Get and respectively compare the first mirror image and the second mirror image of each target pipe joint, and obtain the defect feature alignment result of each target pipe joint of the to-be-tested pipeline.The present application aligns the internal detection data of the pipeline, effectively avoids the feature missing, false alarm and non-corresponding problems caused by detection, and provides more accurate data for pipeline internal detection.

Description

Technical Field

[0001] This invention relates to the field of pipeline inspection technology, and more particularly to a pipeline inspection data alignment method, system, storage medium, and electronic device. Background Technology

[0002] Internal pipeline inspection technology is currently the most effective method for assessing the condition of pipelines. As pipelines age, most have already undergone two or more rounds of internal inspection. Comparative analysis of multiple internal inspection results can yield defect development parameters such as corrosion rate, leading to a better evaluation of the pipeline's condition.

[0003] With the continuous development of internal inspection technology, an increasing number of internal inspection service providers are qualified to conduct pipeline internal inspections. However, the inspection results provided by these different providers vary significantly, making it difficult to provide accurate results. This poses a considerable challenge to the comparative analysis of pipeline internal inspection results. Therefore, there is an urgent need to provide a technical solution to address these technical problems. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method, system, storage medium, and electronic device for aligning detection data within a pipeline.

[0005] The technical solution of the pipeline detection data alignment method of the present invention is as follows:

[0006] Acquire the first and second pipe section inspection data for each pipe section of the pipeline under test during two consecutive pipeline internal inspections;

[0007] Among all pipe sections of the pipeline to be tested, the pipe section to be compared is identified that has no maintenance record between two pipeline inspections. The weld features of the first and second pipe section inspection data of each pipe section to be compared are compared to obtain the comparison result of each pipe section to be compared.

[0008] Each pipe segment to be compared that has a successful comparison result is identified as a target pipe segment. The first pipe segment defect data of any target pipe segment is obtained from the detection data inside the first pipe segment of any target pipe segment. The second pipe segment defect data of any target pipe segment is obtained from the detection data inside the second pipe segment of any target pipe segment. This process continues until the first pipe segment defect data and the second pipe segment defect data of each target pipe segment are obtained.

[0009] Based on the first pipe segment defect data of any target pipe segment, a first mirrored image of the target pipe segment is generated, and based on the second pipe segment defect data of the target pipe segment, a second mirrored image of the target pipe segment is generated, until the first mirrored image and the second mirrored image of each target pipe segment are obtained.

[0010] Defect features are compared between the first and second mirrored images of each target pipe section to obtain the defect feature alignment result for each target pipe section of the pipeline under test.

[0011] The beneficial effects of the pipeline detection data alignment method of the present invention are as follows:

[0012] The method of this invention effectively avoids problems such as feature loss, false alarms, and mismatches caused by the detection process by aligning the internal inspection data of the pipeline, thus providing more accurate data for pipeline internal inspection.

[0013] Based on the above scheme, the pipeline detection data alignment method of the present invention can be further improved as follows.

[0014] Furthermore, before the step of obtaining the first pipe section detection data and the second pipe section detection data for each pipe section of the pipeline under test during two consecutive pipe section internal inspections, the method further includes:

[0015] Obtain the first original pipe section detection data and the second original pipe section detection data for each pipe section of the pipeline under test during two consecutive pipe section detections;

[0016] The steps of obtaining the first and second pipe section detection data for each pipe section of the pipeline under test during two consecutive pipeline internal inspections include:

[0017] Based on the pipeline feature standardization database, the detection data inside the first original pipe section of each pipe segment is standardized to obtain the detection data inside the first pipe section of each pipe segment, and the detection data inside the second original pipe section of each pipe segment is standardized to obtain the detection data inside the second pipe section of each pipe segment.

[0018] Furthermore, the detection data inside the first pipe section and the detection data inside the second pipe section both include: features of the first pipe section, features of the second pipe section, features of the third pipe section, and features of the fourth pipe section;

[0019] The step of comparing weld features in the inspection data of the first and second pipe sections of any pipe section to be compared, to obtain the comparison result of the pipe section to be compared, includes:

[0020] The first pipe section features, second pipe section features, third pipe section features, and fourth pipe section features in the first pipe section detection data and the second pipe section detection data of any pipe section to be compared are compared sequentially.

[0021] If each feature of any pipe section to be compared is successfully matched, the comparison result of any pipe section to be compared is determined to be a successful comparison; otherwise, the comparison result of any pipe section to be compared is determined to be a failed comparison.

[0022] Further, the step of obtaining the first pipe segment defect data of any target pipe segment from the first pipe segment internal inspection data, and obtaining the second pipe segment defect data of any target pipe segment from the second pipe segment internal inspection data, includes:

[0023] Based on the digital feature database of pipeline defects and the first pipe section defect data of any target pipe section, obtain and generate a first mirrored image of any target pipe section according to the pixel value and defect location corresponding to each pipeline defect in the first pipe section defect data of any target pipe section;

[0024] Based on the digital feature database of pipeline defects and the second pipe section defect data of any target pipe section, a second mirrored image of any target pipe section is generated according to the pixel value and defect location corresponding to each pipeline defect in the second pipe section defect data of any target pipe section.

[0025] Furthermore, the first and second mirrored images contain multiple sets of corresponding preset regions;

[0026] The step of comparing the defect features of the first and second mirrored images of any target pipe section to obtain the defect feature alignment result of any target pipe section includes:

[0027] Create a blank pipe section mirror containing three dimensions of any of the target pipe sections;

[0028] When the pixel values ​​of any set of corresponding preset regions in the first and second mirrored images of any target pipe segment are the same, and the difference in length and width of the preset region is less than a preset threshold, then the third dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value corresponding to the defect.

[0029] If any preset region in the first mirrored image of any target pipe segment has a defect, and the preset region in the second mirrored image of any target pipe segment does not have a defect, then the first dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value corresponding to the defect.

[0030] If any preset region in the first mirrored image of any target pipe segment does not have a defect, and the preset region in the second mirrored image of any target pipe segment has a defect, then the second dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value corresponding to the defect.

[0031] If any set of corresponding preset regions in the first and second mirrored images of any target pipe segment have defects of different types, then the first dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value of the first mirrored image in the preset region, and the second dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value of the second mirrored image in the preset region.

[0032] In the blank pipe section image, the pixel values ​​of the preset area without defects are filled to obtain the defect feature alignment result of any target pipe section.

[0033] The technical solution of the pipeline in-situ detection data alignment system of the present invention is as follows:

[0034] It includes: an acquisition module, a first processing module, a second processing module, a third processing module, and a running module;

[0035] The acquisition module is used to: acquire the first pipe section detection data and the second pipe section detection data of each pipe section of the pipeline under test during two consecutive pipe section internal inspections;

[0036] The first processing module is used to: identify, among all pipe sections of the pipeline to be tested, the pipe section to be compared that has no maintenance record between two pipeline inspections, and compare the weld features of the first pipe section inspection data and the second pipe section inspection data of each pipe section to be compared to obtain the comparison result of each pipe section to be compared.

[0037] The second processing module is used to: determine each pipe segment to be compared as a target pipe segment if the comparison result is successful, and obtain the first pipe segment defect data of the target pipe segment from the detection data inside the first pipe segment of the target pipe segment, and obtain the second pipe segment defect data of the target pipe segment from the detection data inside the second pipe segment of the target pipe segment, until the first pipe segment defect data and the second pipe segment defect data of each target pipe segment are obtained;

[0038] The third processing module is used to: generate a first mirrored image of any target pipe segment based on the first pipe segment defect data of any target pipe segment, and generate a second mirrored image of any target pipe segment based on the second pipe segment defect data of any target pipe segment, until the first mirrored image and the second mirrored image of each target pipe segment are obtained.

[0039] The operation module is used to: compare the defect features of the first and second mirrored images of each target pipe section to obtain the defect feature alignment result of each target pipe section of the pipeline under test.

[0040] The beneficial effects of the pipeline in-situ detection data alignment system of the present invention are as follows:

[0041] The system of this invention effectively avoids problems such as missing features, false alarms, and mismatches caused during detection by aligning the internal detection data of the pipeline, thus providing more accurate data for pipeline internal detection.

[0042] Based on the above solution, the pipeline detection data alignment system of the present invention can be further improved as follows.

[0043] Furthermore, it also includes: a preprocessing module; the preprocessing module is used for:

[0044] Obtain the first original pipe section detection data and the second original pipe section detection data for each pipe section of the pipeline under test during two consecutive pipe section detections;

[0045] The acquisition module is specifically used for:

[0046] Based on the pipeline feature standardization database, the detection data inside the first original pipe section of each pipe segment is standardized to obtain the detection data inside the first pipe section of each pipe segment, and the detection data inside the second original pipe section of each pipe segment is standardized to obtain the detection data inside the second pipe section of each pipe segment.

[0047] Furthermore, the detection data within the first and second pipe sections both include: features of the first pipe section, features of the second pipe section, features of the third pipe section, and features of the fourth pipe section; the first processing module is specifically used for:

[0048] The first pipe section features, second pipe section features, third pipe section features, and fourth pipe section features in the first pipe section detection data and the second pipe section detection data of any pipe section to be compared are compared sequentially.

[0049] If each feature of any pipe section to be compared is successfully matched, the comparison result of any pipe section to be compared is determined to be a successful comparison; otherwise, the comparison result of any pipe section to be compared is determined to be a failed comparison.

[0050] The technical solution of a storage medium according to the present invention is as follows:

[0051] The storage medium stores instructions that, when read by a computer, cause the computer to execute the steps of the pipeline detection data alignment method of the present invention.

[0052] The technical solution of an electronic device according to the present invention is as follows:

[0053] The invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it causes the computer to perform the steps of the pipeline detection data alignment method of the present invention. Attached Figure Description

[0054] Figure 1 A flowchart illustrating a first embodiment of the pipeline in-situ detection data alignment method provided by the present invention is shown.

[0055] Figure 2 A flowchart illustrating step 150 of the first embodiment of the pipeline detection data alignment method provided by the present invention is shown.

[0056] Figure 3 A flowchart illustrating a second embodiment of the pipeline in-situ detection data alignment method provided by the present invention is shown.

[0057] Figure 4 A schematic diagram of a pipe feature standardization database is shown in any embodiment of the pipe in-pipe detection data alignment method provided by the present invention;

[0058] Figure 5 This diagram illustrates the digitization process in any embodiment of the pipeline in-situ detection data alignment method provided by the present invention;

[0059] Figure 6 A schematic diagram of a digital feature database of pipeline defects is shown in any embodiment of the pipeline in-pipe detection data alignment method provided by the present invention.

[0060] Figure 7 A schematic diagram of pipe section defect data is shown in any embodiment of the pipe internal detection data alignment method provided by the present invention;

[0061] Figure 8 A schematic diagram of a mirrored image in digital form is shown in any embodiment of the pipeline inspection data alignment method provided by the present invention;

[0062] Figure 9 This diagram illustrates a grayscale image corresponding to a mirrored image in any embodiment of the pipeline detection data alignment method provided by the present invention.

[0063] Figure 10 A schematic diagram of an embodiment of the pipeline inspection data alignment system provided by the present invention is shown. Detailed Implementation

[0064] Figure 1A flowchart illustrating a first embodiment of a pipeline inspection data alignment method provided by the present invention is shown. Figure 1 As shown, it includes the following steps:

[0065] Step 110: Obtain the first and second pipe section inspection data for each pipe section of the pipeline under test during two separate pipeline inspections.

[0066] In this context: ① The pipeline under test is an arbitrarily selected oil and gas pipeline, and each pipeline contains multiple pipe sections. ② Pipeline in-situ inspection technology is used to inspect the physical condition of the pipeline under test to obtain status data and defect data, etc. ③ The first pipe section in-situ inspection data is the data from a previous pipeline in-situ inspection of a particular pipe section. ④ The second pipe section in-situ inspection data is the data from a subsequent pipeline in-situ inspection of a particular pipe section.

[0067] It should be noted that: ① The internal detection time of the first pipe section detection data in any pipe segment is earlier than the internal detection time of the second pipe section detection data. ② The internal detection time of the first pipe section detection data in each pipe segment is the same (or falls within the same internal detection time period), and the internal detection time of the second pipe section detection data in each pipe segment is the same (or falls within the same internal detection time period). ③ The internal detection data of the first and second pipe sections can be raw data or data after standardization. In this embodiment, standardized data is used for illustration.

[0068] Step 120: Among all pipe sections of the pipeline to be tested, identify the pipe section to be compared that has no maintenance record between the two pipeline inspections, and compare the weld features of the first and second pipe section inspection data of each pipe section to be compared to obtain the comparison result of each pipe section to be compared.

[0069] The criteria are as follows: ① The maintenance record of the pipeline under test includes events such as repairs, pipe replacements, and rerouting that occurred on the pipeline between two pipeline inspections. For example, if a pipe section with weld codes 5-6 in the pipeline under test was rerouted, increasing its length by 5m, then that pipe section has a maintenance record. ② The pipe section to be compared is a pipe section in the pipeline under test that has no maintenance record. For example, if a pipe section with weld codes 7-8 in the pipeline under test has no maintenance record, then that pipe section is the pipe section to be compared. ③ The comparison result includes: successful comparison or unsuccessful comparison. For example, the inspection data within the pipe section is divided into four parts for comparison. If each of the four parts of the inspection data within the first and second pipe sections of a pipe section to be compared is successfully compared, then the comparison result of the pipe section to be compared is considered successful; otherwise, the comparison result of the pipe section to be compared is considered unsuccessful.

[0070] Step 130: Determine each pipe segment to be compared that has a successful comparison result as a target pipe segment, and obtain the first pipe segment defect data of any target pipe segment from the detection data inside the first pipe segment of any target pipe segment, and obtain the second pipe segment defect data of any target pipe segment from the detection data inside the second pipe segment of any target pipe segment, until the first pipe segment defect data and the second pipe segment defect data of each target pipe segment are obtained.

[0071] The data includes: ① The target pipe section: the pipe section to be compared that has been successfully matched. ② The inspection data within the first pipe section includes: the first circumferential weld number, the equipment data of the first pipe section, the positioning data of the first pipe section, the defect data of the first pipe section, and the length of the first pipe section; the equipment data of the first pipe section includes, but is not limited to: sleeves, tees, bends, straight pipes, valves, T-welds, flanges, pipe fittings, pipe clamps, sleeves, cathodic protection connections, supports, etc.; the positioning data of the first pipe section includes, but is not limited to: ground reference points, circumferential welds, etc.; the defect data of the first pipe section includes, but is not limited to: metal corrosion, manufacturing defects, abnormal repairs, abnormal circumferential welds, etc. ③ The inspection data within the second pipe section includes: the second circumferential weld number, the equipment data of the first pipe section, the positioning data of the first pipe section, the defect data of the first pipe section, and the length of the second pipe section; its data type is the same as that of the inspection data within the first pipe section.

[0072] Step 140: Based on the first segment defect data of any target segment, generate a first mirrored image of the target segment, and based on the second segment defect data of the target segment, generate a second mirrored image of the target segment, until the first mirrored image and the second mirrored image of each target segment are obtained.

[0073] The first mirrored image is generated based on the defect data of the corresponding first pipe section. The specific generation process is as follows: the steel pipe (a target pipe section) is unfolded and viewed as a rectangular steel plate. The plate is digitized according to the location of its feature points. First, the mirror resolution is set, with each pixel representing an area of ​​length W and width H. Next, weld markings are added. Then, the corresponding pixel values ​​are set according to the location and size of the pipe defect points. Finally, the pixel values ​​of any abnormal points are filled in, completing the pipe section mirroring and obtaining the first mirrored image of the target pipe section. The second mirrored image is generated based on the defect data of the corresponding second pipe section. The specific generation process of the second mirrored image is the same as that of the first mirrored image, and will not be elaborated further here.

[0074] Step 150: Perform defect feature comparison on the first and second mirrored images of each target pipe section to obtain the defect feature alignment result of each target pipe section of the pipeline under test.

[0075] Specifically, such as Figure 2As shown, step 150 includes:

[0076] Step 151: Create a blank pipe section image containing three dimensions of any of the target pipe sections.

[0077] The three dimensions are: the data corresponding to the first internal detection is the first dimension, the data corresponding to the second internal detection is the second dimension, and the result after aligning the two detection results is the third dimension.

[0078] Step 152: When the pixel values ​​of any set of corresponding preset regions in the first and second mirrored images of any target pipe segment are the same, and the difference in length and width of the preset region is less than a preset threshold, then the third dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value corresponding to the defect.

[0079] Among them, ① a set of corresponding preset regions refers to the same region of two corresponding mirrored images. ② Preset thresholds include: preset length threshold and preset width threshold, both of which can be set according to requirements, and no restrictions are set here.

[0080] Specifically, the corresponding pixel values ​​in each pair of mirror images are compared. If the pixel values ​​are the same and the distance in the length and width directions is less than the threshold, the third dimension of the corresponding mirror image is set to the pixel value corresponding to the defect, with the size being the size of the defect in the second mirrored image.

[0081] Step 153: If any preset region in the first mirrored image of any target tube segment has a defect, and the preset region in the second mirrored image of any target tube segment does not have a defect, then set the first dimension of the preset region in the blank tube segment mirror of any target tube segment to the pixel value corresponding to the defect.

[0082] Step 154: If any preset region in the first mirrored image of any target tube segment does not have a defect, and the preset region in the second mirrored image of any target tube segment has a defect, then set the second dimension of the preset region in the blank tube segment mirror of any target tube segment to the pixel value corresponding to the defect.

[0083] Step 155: When any set of corresponding preset regions in the first and second mirrored images of any target pipe segment have defects of different types, the first dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value of the first mirrored image in the preset region, and the second dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value of the second mirrored image in the preset region.

[0084] Specifically, if the first mirrored image has a defect but the second mirrored image does not, then the first dimension of the corresponding mirror image is set to the pixel value corresponding to the defect. If the first mirrored image is not defective but the second mirrored image has a defect, then the second dimension of the corresponding mirror image is set to the pixel value corresponding to the defect. If both the first and second mirror images have defects, but the defect types are different, then the first dimension of the mirror image is set to the pixel value of the first mirrored image, and the second dimension of the mirror image is set to the pixel value of the second mirrored image.

[0085] Step 156: In the blank pipe section image, fill the pixel values ​​of the preset area without defects to obtain the defect feature alignment result of any target pipe section.

[0086] The defect feature alignment result is: the pipe section image after filling the blank pipe section image of any target pipe section.

[0087] The technical solution of this embodiment effectively avoids problems such as feature loss, false alarms, and mismatches caused by the detection process by aligning the internal detection data of the pipeline, thus providing more accurate data for pipeline internal detection.

[0088] Figure 3 A flowchart illustrating a second embodiment of a pipeline inspection data alignment method provided by the present invention is shown. Figure 3 As shown, it includes the following steps:

[0089] Step 210: Obtain the first and second original pipe section internal detection data for each pipe section of the pipeline under test during two separate internal pipe inspections.

[0090] Specifically, ① the first original pipe section internal test data refers to the original data of a certain pipe section of the pipeline under test during the previous internal pipe test. ② the second original pipe section internal test data refers to the original data of a certain pipe section of the pipeline under test during the subsequent internal pipe test.

[0091] It should be noted that the first and second original pipe section internal inspection data can be from the same testing company or from different testing companies. For example, if the first original pipe section internal inspection data is from GE-PII, the obtained data may include hot bends; if the second original pipe section internal inspection data is from CNPC Testing Company, the obtained data may include hot bent elbows.

[0092] Step 220: Based on the pipeline feature standardization database, standardize the first original pipe section detection data of each pipe section to obtain the first pipe section detection data of each pipe section, and standardize the second original pipe section detection data of each pipe section to obtain the second pipe section detection data of each pipe section.

[0093] Among them, ① the standardized database of pipeline features, such as Figure 4 As shown, the standardization process is as follows: when the detection data in the first original pipe section contains "hot bend" and the detection data in the second original pipe section contains "hot bent", according to the pipeline feature standardization database, "hot bend" in the detection data in the first original pipe section is converted to "hot bend", "hot bent" in the detection data in the second original pipe section is converted to "hot bend", and so on, and all features of each pipe section are standardized in sequence according to the pipeline feature standardization database.

[0094] Furthermore, after obtaining the standardized inspection data for the first and second pipe sections of each pipe segment, the inspection data for the first and second pipe sections can be digitally processed. The digital processing method corresponds to... Figure 5 The specific digitization rules are: <circumferential weld number> &<A|B> &<C|D> [&E][&F][&G][&H][&I][&J][&K][&L]<&Pipe Length>. The circumferential weld number is mandatory (enter the circumferential weld number); A and B are optional (one of two mandatory options); C and D are optional (one of two mandatory options); EL is optional; Pipe Length is mandatory and is the actual pipe length data (accurate to two decimal places). For example, if there is a hot-bent straight seam pipe between circumferential weld numbers 50 and 60, with a cathodic protection joint, and a pipe length of 5.6 meters, and this pipe section was not changed during the two inspections, then the pipe section would be digitized as "50&A&C&F&K&5.60".

[0095] Step 230: Among all pipe sections of the pipeline to be tested, identify the pipe section to be compared that has no maintenance record between the two pipeline inspections, and compare the weld features of the first and second pipe section inspection data of each pipe section to be compared to obtain the comparison result of each pipe section to be compared.

[0096] Step 240: Determine each pipe segment to be compared that has a successful comparison result as a target pipe segment, and obtain the first pipe segment defect data of any target pipe segment from the detection data inside the first pipe segment of any target pipe segment, and obtain the second pipe segment defect data of any target pipe segment from the detection data inside the second pipe segment of any target pipe segment, until the first pipe segment defect data and the second pipe segment defect data of each target pipe segment are obtained.

[0097] Step 250: Based on the first segment defect data of any target segment, generate a first mirrored image of the target segment, and based on the second segment defect data of the target segment, generate a second mirrored image of the target segment, until the first mirrored image and the second mirrored image of each target segment are obtained.

[0098] Step 260: Perform defect feature comparison on the first and second mirrored images of each target pipe section to obtain the defect feature alignment result of each target pipe section of the pipeline under test.

[0099] The technical solution of this embodiment, based on the first embodiment, further provides more accurate data for the alignment of pipeline inspection data by standardizing and digitizing the pipeline inspection data.

[0100] Preferably, based on any of the above embodiments, the detection data inside the first pipe section and the detection data inside the second pipe section both include: features of the first pipe section, features of the second pipe section, features of the third pipe section, and features of the fourth pipe section.

[0101] In the detection data within any pipe section, the first pipe section feature is: valve; the second pipe section feature is: hot bend or cold bend; the third pipe section feature is: pipe section length; and the rest are the fourth pipe section features.

[0102] The step of comparing weld features in the inspection data of the first and second pipe sections of any pipe section to be compared, to obtain the comparison result of the pipe section to be compared, includes:

[0103] The first pipe section features, second pipe section features, third pipe section features, and fourth pipe section features in the first pipe section detection data and the second pipe section detection data of any pipe section to be compared are compared sequentially.

[0104] If each feature of any pipe section to be compared is successfully matched, the comparison result of any pipe section to be compared is determined to be a successful comparison; otherwise, the comparison result of any pipe section to be compared is determined to be a failed comparison.

[0105] The weld feature comparison process for any pipe section to be compared is as follows: ① Compare the first pipe section feature in the detection data of the first pipe section and the first pipe section feature in the detection data of the second pipe section of the pipe section to be compared. If both contain valves or neither contains valves, the first pipe section feature comparison is considered successful; otherwise, the first pipe section feature comparison is considered unsuccessful. ② When the first pipe section feature comparison is successful, compare the second pipe section feature in the detection data of the first pipe section and the second pipe section feature in the detection data of the second pipe section. If both are cold-bent or hot-bent, the second pipe section feature comparison is considered successful; otherwise, the second pipe section feature comparison is considered unsuccessful. ③ When the second segment feature of the pipe section to be compared is successfully matched, the third segment feature in the detection data of the first segment of the pipe section to be compared is compared with the third segment feature in the detection data of the second segment of the pipe section to be compared. If the difference in pipe section length between the two detection results does not exceed 5% of the longer pipe section length, the comparison is considered successful; otherwise, the comparison is considered unsuccessful. ④ When the third segment feature of the pipe section to be compared is successfully matched, the fourth segment feature in the detection data of the first segment of the pipe section to be compared is compared with the fourth segment feature in the detection data of the second segment of the pipe section to be compared. If the comparison is successful, the comparison of the pipe section to be compared is considered successful.

[0106] Preferably, based on any of the above embodiments, the step of obtaining the first pipe segment defect data of any target pipe segment from the first pipe segment internal detection data, and obtaining the second pipe segment defect data of any target pipe segment from the second pipe segment internal detection data, includes:

[0107] Based on the digital feature database of pipeline defects and the first pipe section defect data of any target pipe section, the pixel value and defect location corresponding to each pipeline defect in the first pipe section defect data of any target pipe section are obtained, and a first mirrored image of any target pipe section is generated.

[0108] Based on the digital feature database of pipeline defects and the second pipe section defect data of any target pipe section, a second mirrored image of any target pipe section is generated according to the pixel value and defect location corresponding to each pipeline defect in the second pipe section defect data of any target pipe section.

[0109] Among them, the digital feature database of pipeline defects, such as Figure 6 As shown. Based on the digital feature database of pipeline defects, the pixel value corresponding to each pipeline defect is obtained from the defect data of the first pipeline segment (defect data of the second pipeline segment) of any target pipeline segment, and then from... Figure 7The defect location corresponding to each pipe defect is obtained from the pipe section defect data shown. Figure 8 The image is a mirrored digital form, and is converted according to pixel values ​​as shown. Figure 9 The corresponding grayscale image is shown.

[0110] It should be noted that, Figure 8 In the diagram, each pixel on the horizontal axis represents 30 cm along the pipe section axis, and each pixel on the vertical axis represents 1 hour along the pipe section axis.

[0111] Figure 10 A structural diagram of an embodiment of a pipeline inspection data alignment system provided by the present invention is shown. Figure 10 As shown, the system 300 includes: an acquisition module 310, a first processing module 320, a second processing module 330, a third processing module 340, and an operation module 350;

[0112] The acquisition module 310 is used to: acquire the first pipe section detection data and the second pipe section detection data of each pipe section of the pipeline under test during two consecutive pipe section detections;

[0113] The first processing module 320 is used to: identify, among all pipe sections of the pipeline to be tested, the pipe section to be compared that has no maintenance record between two pipeline inspections, and compare the weld features of the first pipe section inspection data and the second pipe section inspection data of each pipe section to be compared to obtain the comparison result of each pipe section to be compared.

[0114] The second processing module 330 is used to: determine each pipe segment to be compared as a target pipe segment if the comparison result is successful, and obtain the first pipe segment defect data of the target pipe segment from the detection data inside the first pipe segment of the target pipe segment, and obtain the second pipe segment defect data of the target pipe segment from the detection data inside the second pipe segment of the target pipe segment, until the first pipe segment defect data and the second pipe segment defect data of each target pipe segment are obtained;

[0115] The third processing module 340 is used to: generate a first mirrored image of any target pipe segment based on the first pipe segment defect data of any target pipe segment, and generate a second mirrored image of any target pipe segment based on the second pipe segment defect data of any target pipe segment, until the first mirrored image and the second mirrored image of each target pipe segment are obtained.

[0116] The running module 350 is used to: compare the defect features of the first mirrored image and the second mirrored image of each target pipe section respectively, and obtain the defect feature alignment result of each target pipe section of the pipeline under test.

[0117] Preferably, it further includes: a preprocessing module; the preprocessing module is used for:

[0118] Obtain the first original pipe section detection data and the second original pipe section detection data for each pipe section of the pipeline under test during two consecutive pipe section detections;

[0119] The acquisition module is specifically used for:

[0120] Based on the pipeline feature standardization database, the detection data inside the first original pipe section of each pipe segment is standardized to obtain the detection data inside the first pipe section of each pipe segment, and the detection data inside the second original pipe section of each pipe segment is standardized to obtain the detection data inside the second pipe section of each pipe segment.

[0121] Preferably, the detection data within the first pipe section and the detection data within the second pipe section both include: features of the first pipe section, features of the second pipe section, features of the third pipe section, and features of the fourth pipe section; the first processing module is specifically used for:

[0122] The first pipe section features, second pipe section features, third pipe section features, and fourth pipe section features in the first pipe section detection data and the second pipe section detection data of any pipe section to be compared are compared sequentially.

[0123] If each feature of any pipe section to be compared is successfully matched, the comparison result of any pipe section to be compared is determined to be a successful comparison; otherwise, the comparison result of any pipe section to be compared is determined to be a failed comparison.

[0124] The technical solution of this embodiment effectively avoids problems such as feature loss, false alarms, and mismatches caused by the detection process by aligning the internal detection data of the pipeline, thus providing more accurate data for pipeline internal detection.

[0125] The parameters and steps for implementing the corresponding functions of each module in the above embodiment of a pipeline in-situ detection data alignment system 300 can be referred to the parameters and steps in any embodiment of a pipeline in-situ detection data alignment method mentioned above, and will not be repeated here.

[0126] An embodiment of the present invention provides a storage medium, comprising: the storage medium storing instructions, which, when read by a computer, cause the computer to execute steps such as a method for aligning detection data in a pipeline. For details, please refer to the parameters and steps in any embodiment of the method for aligning detection data in a pipeline described above, which will not be repeated here.

[0127] Computer storage media include, for example, USB flash drives and external hard drives.

[0128] An electronic device provided by an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to cause the computer to perform steps such as those of a pipeline detection data alignment method. Specific details regarding the parameters and steps in any embodiment of the pipeline detection data alignment method described above are provided and will not be repeated here.

[0129] Those skilled in the art will know that the present invention can be implemented as a method, system, storage medium, and electronic device.

[0130] Therefore, the present invention can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the present invention can also be implemented as a computer program product contained in one or more computer-readable media, which contains computer-readable program code. Any combination of one or more computer-readable media can be used. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. Although embodiments of the invention have been shown and described above, it is to be understood that these embodiments are exemplary and should not be construed as limiting the invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the invention.

Claims

1. A method for aligning detection data inside a pipeline, characterized in that, include: Acquire the first and second pipe section inspection data for each pipe section of the pipeline under test during two consecutive pipeline internal inspections; Among all pipe sections of the pipeline to be tested, the pipe section to be compared is identified that has no maintenance record between two pipeline inspections. The weld features of the first and second pipe section inspection data of each pipe section to be compared are compared to obtain the comparison result of each pipe section to be compared. Each pipe segment to be compared that has a successful comparison result is identified as a target pipe segment. The first pipe segment defect data of any target pipe segment is obtained from the detection data inside the first pipe segment of any target pipe segment. The second pipe segment defect data of any target pipe segment is obtained from the detection data inside the second pipe segment of any target pipe segment. This process continues until the first pipe segment defect data and the second pipe segment defect data of each target pipe segment are obtained. Based on the first pipe segment defect data of any target pipe segment, a first mirrored image of the target pipe segment is generated, and based on the second pipe segment defect data of the target pipe segment, a second mirrored image of the target pipe segment is generated, until the first mirrored image and the second mirrored image of each target pipe segment are obtained. Defect features are compared between the first and second mirrored images of each target pipe section to obtain the defect feature alignment result for each target pipe section of the pipeline under test. The first and second mirrored images contain multiple sets of corresponding preset regions; The step of comparing the defect features of the first and second mirrored images of any target pipe section to obtain the defect feature alignment result of any target pipe section includes: Create a blank pipe section mirror containing three dimensions of any of the target pipe sections; When the pixel values ​​of any set of corresponding preset regions in the first and second mirrored images of any target pipe segment are the same, and the difference in length and width of the preset region is less than a preset threshold, then the third dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value corresponding to the defect. If any preset region in the first mirrored image of any target pipe segment has a defect, and the preset region in the second mirrored image of any target pipe segment does not have a defect, then the first dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value corresponding to the defect. If any preset region in the first mirrored image of any target pipe segment does not have a defect, and the preset region in the second mirrored image of any target pipe segment has a defect, then the second dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value corresponding to the defect. If any set of corresponding preset regions in the first and second mirrored images of any target pipe segment have defects of different types, then the first dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value of the first mirrored image in the preset region, and the second dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value of the second mirrored image in the preset region. In the blank pipe section image, the pixel values ​​of the preset area without defects are filled to obtain the defect feature alignment result of any target pipe section.

2. The pipeline detection data alignment method according to claim 1, characterized in that, Before the step of obtaining the first pipe section detection data and the second pipe section detection data for each pipe section of the pipeline under test during two consecutive pipe section internal inspections, the method further includes: Obtain the first original pipe section detection data and the second original pipe section detection data for each pipe section of the pipeline under test during two consecutive pipe section detections; The steps of obtaining the first and second pipe section detection data for each pipe section of the pipeline under test during two consecutive pipeline internal inspections include: Based on the pipeline feature standardization database, the detection data inside the first original pipe section of each pipe segment is standardized to obtain the detection data inside the first pipe section of each pipe segment, and the detection data inside the second original pipe section of each pipe segment is standardized to obtain the detection data inside the second pipe section of each pipe segment.

3. The pipeline detection data alignment method according to claim 1 or 2, characterized in that, The detection data inside the first pipe section and the detection data inside the second pipe section both include: features of the first pipe section, features of the second pipe section, features of the third pipe section, and features of the fourth pipe section; The step of comparing weld features in the inspection data of the first and second pipe sections of any pipe section to be compared, to obtain the comparison result of the pipe section to be compared, includes: The first pipe section features, second pipe section features, third pipe section features, and fourth pipe section features in the first pipe section detection data and the second pipe section detection data of any pipe section to be compared are compared sequentially. If each feature of any pipe section to be compared is successfully matched, the comparison result of any pipe section to be compared is determined to be a successful comparison; otherwise, the comparison result of any pipe section to be compared is determined to be a failed comparison.

4. The pipeline detection data alignment method according to claim 3, characterized in that, The steps of obtaining the first pipe segment defect data of any target pipe segment from the first pipe segment internal detection data and obtaining the second pipe segment defect data of any target pipe segment from the second pipe segment internal detection data include: Based on the digital feature database of pipeline defects and the first pipe section defect data of any target pipe section, obtain and generate a first mirrored image of any target pipe section according to the pixel value and defect location corresponding to each pipeline defect in the first pipe section defect data of any target pipe section; Based on the digital feature database of pipeline defects and the second pipe section defect data of any target pipe section, a second mirrored image of any target pipe section is generated according to the pixel value and defect location corresponding to each pipeline defect in the second pipe section defect data of any target pipe section.

5. A pipeline inspection data alignment system, characterized in that, include: The module consists of an acquisition module, a first processing module, a second processing module, a third processing module, and a running module. The acquisition module is used to: acquire the first pipe section detection data and the second pipe section detection data of each pipe section of the pipeline under test during two consecutive pipe section internal inspections; The first processing module is used to: identify, among all pipe sections of the pipeline to be tested, the pipe section to be compared that has no maintenance record between two pipeline inspections, and compare the weld features of the first pipe section inspection data and the second pipe section inspection data of each pipe section to be compared to obtain the comparison result of each pipe section to be compared. The second processing module is used to: determine each pipe segment to be compared as a target pipe segment if the comparison result is successful, and obtain the first pipe segment defect data of the target pipe segment from the detection data inside the first pipe segment of the target pipe segment, and obtain the second pipe segment defect data of the target pipe segment from the detection data inside the second pipe segment of the target pipe segment, until the first pipe segment defect data and the second pipe segment defect data of each target pipe segment are obtained; The third processing module is used to: generate a first mirrored image of any target pipe segment based on the first pipe segment defect data of any target pipe segment, and generate a second mirrored image of any target pipe segment based on the second pipe segment defect data of any target pipe segment, until the first mirrored image and the second mirrored image of each target pipe segment are obtained. The operation module is used to: compare the defect features of the first and second mirrored images of each target pipe section to obtain the defect feature alignment result of each target pipe section of the pipeline under test; The first and second mirrored images contain multiple sets of corresponding preset regions; The operation module is specifically used for: Create a blank pipe section mirror containing three dimensions of any of the target pipe sections; When the pixel values ​​of any set of corresponding preset regions in the first and second mirrored images of any target pipe segment are the same, and the difference in length and width of the preset region is less than a preset threshold, then the third dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value corresponding to the defect. If any preset region in the first mirrored image of any target pipe segment has a defect, and the preset region in the second mirrored image of any target pipe segment does not have a defect, then the first dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value corresponding to the defect. If any preset region in the first mirrored image of any target pipe segment does not have a defect, and the preset region in the second mirrored image of any target pipe segment has a defect, then the second dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set to the pixel value corresponding to the defect. If any set of corresponding preset regions in the first and second mirrored images of any target pipe segment have defects of different types, then the first dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value of the first mirrored image in the preset region, and the second dimension of the preset region in the blank pipe segment mirror of any target pipe segment is set as the pixel value of the second mirrored image in the preset region. In the blank pipe section image, the pixel values ​​of the preset area without defects are filled to obtain the defect feature alignment result of any target pipe section.

6. The pipeline inspection data alignment system according to claim 5, characterized in that, Also includes: Preprocessing module; The preprocessing module is used for: Obtain the first original pipe section detection data and the second original pipe section detection data for each pipe section of the pipeline under test during two consecutive pipe section detections; The acquisition module is specifically used for: Based on the pipeline feature standardization database, the detection data inside the first original pipe section of each pipe segment is standardized to obtain the detection data inside the first pipe section of each pipe segment, and the detection data inside the second original pipe section of each pipe segment is standardized to obtain the detection data inside the second pipe section of each pipe segment.

7. The pipeline inspection data alignment system according to claim 5, characterized in that, The detection data inside the first and second pipe sections both include: features of the first pipe section, features of the second pipe section, features of the third pipe section, and features of the fourth pipe section; the first processing module is specifically used for: The first pipe section features, second pipe section features, third pipe section features, and fourth pipe section features in the first pipe section detection data and the second pipe section detection data of any pipe section to be compared are compared sequentially. If each feature of any pipe section to be compared is successfully matched, the comparison result of any pipe section to be compared is determined to be a successful comparison; otherwise, the comparison result of any pipe section to be compared is determined to be a failed comparison.

8. A storage medium, characterized in that, The storage medium stores instructions that, when read by a computer, cause the computer to execute the pipeline detection data alignment method as described in any one of claims 1 to 4.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it causes the computer to perform the pipeline detection data alignment method as described in any one of claims 1 to 4.

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