Pipeline data processing method and system, computer device, and storage medium

Abstract

The application relates to a pipeline data processing method, system, computer device and storage medium. The method comprises the following steps: scanning and detecting a to-be-detected pipeline based on a detection device to obtain a three-dimensional pipeline model corresponding to the to-be-detected pipeline and thickness detection data of the to-be-detected pipeline at each detection point; calibrating indexes according to original pipeline parameters of the to-be-detected pipeline and the thickness detection data at each detection point to obtain index coordinate points of each detection point; calibrating colors of the to-be-detected pipeline according to the index coordinate points to obtain a planar color difference matrix diagram corresponding to the to-be-detected pipeline; the planar color difference matrix diagram is used for representing a wall thickness thinning degree of the to-be-detected pipeline; and the three-dimensional pipeline model is updated by marking on the three-dimensional pipeline model according to a preset index standard, the planar color difference matrix diagram and the thickness detection data to obtain a target pipeline model. The method can realize automatic detection of the to-be-detected pipeline, improve detection accuracy, improve detection efficiency and improve intuitiveness of detection data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pipeline detection, in particular to a pipeline data processing method and system, computer equipment and storage medium. BACKGROUND

[0002] With the development of pipeline technology, pipelines are widely used in nuclear power, thermal power, petroleum and chemical industries. However, FAC (low accelerated corrosion) erosion can cause changes in the wall thickness of metal pipelines, affecting the safety of pipeline use. Therefore, it is necessary to monitor the wall thickness of the pipeline.

[0003] In related technologies, manual measurement is used to detect the wall thickness of the pipeline. However, manual detection can only meet the needs of single-point detection. When replacing the detection point, the detection equipment needs to be manually moved, which reduces the detection efficiency. Moreover, manual detection has large errors, resulting in inaccurate detection data of the pipe wall thickness. In addition, the manual detection method cannot intuitively feel the trend of the change in the pipe wall thickness.

[0004] Therefore, how to improve the accuracy of the detection data, improve the detection efficiency, and improve the intuitiveness of the detection data has become a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0005] Therefore, it is necessary to provide a pipeline data processing method, system, computer equipment and storage medium that can improve the accuracy of pipeline detection data, improve the detection efficiency and the intuitiveness of pipeline detection data.

[0006] In a first aspect, the present application provides a pipeline data processing method. The method comprises:

[0007] scanning and detecting a to-be-detected pipeline based on a detection device to obtain a three-dimensional pipeline model corresponding to the to-be-detected pipeline and thickness detection data corresponding to each detection point of the to-be-detected pipeline;

[0008] performing index calibration on the original pipeline parameters of the to-be-detected pipeline and the thickness detection data corresponding to each detection point to obtain index coordinate points of each detection point;

[0009] color calibrating the to-be-detected pipeline according to each index coordinate point to obtain a plane color difference matrix diagram corresponding to the to-be-detected pipeline; the plane color difference matrix diagram is used to represent the wall thickness thinning degree of the to-be-detected pipeline;

[0010] According to the preset index standard, the planar color difference matrix and the thickness detection data are marked on the three-dimensional pipeline model to update the three-dimensional pipeline model, and a target pipeline model is obtained. The target pipeline model is used to represent the wall thickness degree of the pipeline to be detected.

[0011] In one of the embodiments, the detection device is used to scan and detect the pipeline to be detected, and a three-dimensional pipeline model corresponding to the pipeline to be detected and thickness detection data corresponding to each detection point on the pipeline to be detected are obtained.

[0012] The detection probe on the detection device is used to perform annular scanning detection on the pipeline to be detected, and a three-dimensional pipeline model of the pipeline to be detected is obtained.

[0013] The wall thickness of each detection point on the same radial surface of the pipeline to be detected is detected, and corresponding thickness detection data is obtained.

[0014] The detection device is moved, and the step of detecting the wall thickness of each detection point on the same radial surface of the pipeline to be detected to obtain corresponding thickness detection data is repeatedly performed until the detection of the pipeline to be detected is completed.

[0015] In one of the embodiments, the step of detecting the wall thickness of each detection point on the same radial surface of the pipeline to be detected to obtain corresponding thickness detection data includes:

[0016] The radial surface on the pipeline to be detected is positioned, and the positioned position is set as a detection point. The wall thickness at the detection point is detected to obtain corresponding detection data.

[0017] A preset angle is rotated at the detection point, and the rotated position is set as a detection point. The wall thickness at the detection point is detected to obtain corresponding detection data.

[0018] The step of rotating a preset angle at the detection point, setting the rotated position as a detection point, and detecting the wall thickness at the detection point to obtain corresponding detection data is repeatedly performed until the detection of the radial surface is completed.

[0019] The detection data corresponding to each detection point is obtained, and the detection data corresponding to each detection point is recognized and positioned to obtain the thickness detection data.

[0020] In one of the embodiments, the original pipeline parameters include an original pipeline wall thickness and a design service life.

[0021] The index calibration is performed according to the original pipeline parameters of the pipeline to be detected and the thickness detection data corresponding to each detection point, and index coordinate points of each detection point are obtained.

[0022] According to the original pipe wall thickness, the thickness detection data corresponding to each detection point is evaluated to obtain a thickness index corresponding to each detection point;

[0023] According to the thickness detection data corresponding to each detection point, the inner wall morphology of the pipeline to be tested is determined, and the inner wall morphology is evaluated to obtain a morphology index corresponding to each detection point;

[0024] According to the design life, the pipeline to be tested is evaluated to obtain a life index;

[0025] According to the thickness index, the morphology index and the life index, an index coordinate point corresponding to each detection point is determined.

[0026] In one embodiment, the pipeline to be tested is color-coded according to the index coordinate points to obtain a plane color difference matrix diagram corresponding to the pipeline to be tested, including:

[0027] The three-dimensional pipeline model is converted into a plane diagram, and the coordinates of each detection point on the plane diagram are obtained;

[0028] At the coordinates of each detection point on the plane diagram, color coding is performed according to a predetermined color coding rule and the index coordinate points corresponding to each detection point to obtain a plane color difference matrix diagram corresponding to the pipeline to be tested.

[0029] In one embodiment, the index standard includes a color difference index standard and a wall thickness index standard;

[0030] According to the predetermined index standard, the plane color difference matrix diagram and the thickness detection data, the three-dimensional pipeline model is labeled to update the three-dimensional pipeline model to obtain a target pipeline model, including:

[0031] According to the color difference index standard, the plane color difference matrix diagram is labeled;

[0032] The labeled plane color difference matrix diagram is converted into a three-dimensional model to obtain a color difference pipeline model;

[0033] According to the wall thickness index standard and the thickness detection data, the color difference pipeline model is labeled to obtain the target pipeline model.

[0034] In a second aspect, the present application also provides a pipeline data processing system. The system comprises:

[0035] A detection device for scanning and detecting a pipeline to be tested to obtain a three-dimensional pipeline model corresponding to the pipeline to be tested and thickness detection data corresponding to each detection point of the pipeline to be tested;

[0036] An index calibration module is configured to calibrate indexes according to the original pipeline parameters of the pipeline to be detected and the thickness detection data corresponding to each detection point, so as to obtain index coordinate points of each detection point.

[0037] A color calibration module is configured to calibrate colors of the pipeline to be detected according to the index coordinate points, so as to obtain a plane color difference matrix diagram corresponding to the pipeline to be detected; the plane color difference matrix diagram is used to represent the wall thickness thinning degree of the pipeline to be detected.

[0038] An updating module is configured to mark on the three-dimensional pipeline model according to a preset index standard, the plane color difference matrix diagram and the thickness detection data, so as to update the three-dimensional pipeline model and obtain a target pipeline model; the target pipeline model is used to represent the wall thickness degree of the pipeline to be detected.

[0039] In a third aspect, the present application further provides a computer device. The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the steps of the pipeline data processing method when executing the computer program.

[0040] In a fourth aspect, the present application further provides a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program implements the steps of the pipeline data processing method when executed by a processor.

[0041] In a fifth aspect, the present application further provides a computer program product. The computer program product comprises a computer program, and the computer program implements the steps of the pipeline data processing method when executed by a processor.

[0042] The pipeline data processing method, system, computer device and storage medium described above can improve the detection efficiency of the pipeline to be detected and the accuracy of the thickness detection data by scanning the pipeline to be detected by a detection device to obtain the thickness detection data. Then, the pipeline to be detected is converted into a three-dimensional pipeline model, and the index coordinate points corresponding to each detection point are determined according to the thickness detection data and the original pipeline parameters. Then, the pipeline to be detected is color calibrated according to the index coordinate points to obtain a plane color difference matrix diagram. Then, the three-dimensional pipeline model is marked according to the index standard, the plane color difference matrix diagram and the thickness detection data to obtain a target pipeline model, thereby improving the intuitiveness of the thickness detection data and facilitating intuitive understanding of the change trend of the pipeline wall thickness. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 FIG. 1 is a flowchart of a pipeline data processing method in an embodiment;

[0044] Figure 2A flowchart of the steps of acquiring thickness detection data in one embodiment;

[0045] Figure 3 A structural diagram of a detection device and a pipeline to be detected in one embodiment;

[0046] Figure 4A A structural diagram of a detection device and a pipeline to be detected in another embodiment;

[0047] Figure 4B A structural diagram of a detection device and a pipeline to be detected in another embodiment;

[0048] Figure 5 A diagram of selecting a measurement zero point of a pipeline to be detected in one embodiment;

[0049] Figure 6 A flowchart of the steps of determining an index coordinate point in one embodiment;

[0050] Figure 7 A structural diagram of converting a three-dimensional pipeline model of a pipeline to be detected into a plan view in one embodiment;

[0051] Figure 8 A coordinate diagram of a plan view in one embodiment;

[0052] Figure 9 A plan view color difference matrix diagram corresponding to a pipeline to be detected in one embodiment;

[0053] Figure 10 A structural diagram of a target pipeline model in one embodiment;

[0054] Figure 11 A structural block diagram of a pipeline data processing system in one embodiment;

[0055] Figure 12 An internal structural diagram of a computer device in one embodiment.

[0056] In the drawings, reference numerals are used to refer to the same or similar elements throughout the several views of the drawings.

[0057] 301, detachable lock; 302, fixed telescopic shaft; 303, fixed support device; 304, roller telescopic shaft; 305, movable roller; 306, track connecting rod; 307, laser scanning device; 308, rotating telescopic shaft; 309, longitudinal telescopic shaft; 310, power traction and supply device; 311, flexible connecting shaft; 312, electromagnetic ultrasonic thickness measurement device; 313, signal transmission device; 314, magnetic roller; 315, detection probe telescopic shaft; 316, detection probe; 317, probe auxiliary movable roller; 318, control device. DETAILED DESCRIPTION

[0058] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not intended to limit the present application.

[0059] In one embodiment, as shown in Figure 1 A pipeline data processing method is provided. The method is applied to a terminal in this embodiment. It should be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and can be implemented through the interaction of the terminal and the server. The terminal can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers and the like. The server can be implemented by an independent server or a server cluster composed of multiple servers. The method includes the following steps in this embodiment:

[0060] In step 102, the detection device is used to scan and detect the pipeline to be measured, so as to obtain the three-dimensional pipeline model corresponding to the pipeline to be measured and the thickness detection data of the pipeline to be measured at each detection point.

[0061] The detection device can be a device used for scanning and detecting the pipeline to be measured. The detection device can include a laser scanning device. When the detection device is used to scan and detect the pipeline to be measured, the thickness detection data of the pipeline to be measured and the three-dimensional pipeline model corresponding to the pipeline to be measured can be obtained. The detection device can realize full-coverage detection of the pipeline.

[0062] The pipeline to be measured can be a pipeline used for thickness detection. The pipeline to be measured can be a metal fire-fighting pipeline, such as a fire-fighting pipeline of a nuclear power plant, a fire-fighting pipeline of a thermal power plant, a fire-fighting pipeline of a thermal power plant, a fire-fighting pipeline of a petrochemical plant, and the like.

[0063] The detection point can be a position point used for detecting the pipeline to be measured. The position point can be pre-set or temporarily selected, and the present application does not make specific limitations in this regard.

[0064] Exemplarily, the detection device for full-coverage detection of the pipeline is used to scan and detect the pipeline to be measured at each detection point of the pipeline to be measured, so as to obtain the thickness detection data corresponding to each detection point. Then, the three-dimensional pipeline model corresponding to the pipeline to be measured is established according to the thickness detection data.

[0065] In some embodiments, after obtaining the thickness detection data, a thickness histogram of the pipeline to be measured can be made, and the thickness histogram is used to represent the wall thickness variation trend of the pipeline to be measured.

[0066] In some embodiments, a ratio between the thickness detection data and the design wall thickness of the pipeline to be detected can be calculated, then different thickness intervals are set according to different ratios, and different colors are used to represent the thinning degree of different thickness intervals, so as to update the three-dimensional pipeline model to obtain a pipeline inner wall three-dimensional topography simulation diagram.

[0067] In step 104, index calibration is performed according to the original pipeline parameters of the pipeline to be detected and the thickness detection data corresponding to each detection point, so as to obtain index coordinate points of each detection point.

[0068] The original pipeline parameters can refer to the design parameters of the pipeline to be detected. The original pipeline parameters can include but are not limited to the pipe diameter size, the original pipeline wall thickness, the pipe diameter length, the design life, etc.

[0069] The index calibration can refer to calibrating the thickness detection data of each detection point according to a pre-set index calibration rule. For example, the index of each detection point can include but is not limited to three levels of A, B and C, A indicating normal, B indicating slight, and C indicating severe.

[0070] The index coordinate point can refer to a way of representing the data condition of each detection point by using the above index. For example, when the index includes the thickness index, the topography index and the life index of the pipeline to be detected, the corresponding index coordinate point can be represented as (thickness index, topography index, life index).

[0071] For example, the life index of the pipeline to be detected can be determined according to the current service life and the design life of the pipeline to be detected, the thickness index of the pipeline to be detected can be determined according to the thickness detection data and the design wall thickness, the thickness change trend of the pipeline to be detected can be determined according to the thickness detection data of each detection point, and then the topography index can be determined, and finally the index coordinate points of each detection point can be determined according to the thickness index, the topography index and the life index.

[0072] In step 106, color calibration is performed on the pipeline to be detected according to each index coordinate point, so as to obtain a corresponding plane color difference matrix diagram of the pipeline to be detected. The plane color difference matrix diagram is used to represent the wall thickness thinning degree of the pipeline to be detected.

[0073] The color calibration can refer to color filling calibration of the detection point according to the specific index level of each index coordinate point and a pre-set color calibration rule. For example, when the index coordinate point of a certain detection point is (A, A, A), green color can be used for calibration, when the index coordinate point of a certain detection point is (C, C, C), black color can be used for calibration, and so on.

[0074] The planar color difference matrix image can refer to an image obtained by color marking on a planar image of the pipeline to be detected. The image is used to represent the wall thickness thinning degree of the pipeline to be detected. For example, when the index level of the index coordinate point is lower, a deeper color is used for color marking, and when the color of the planar color difference matrix image is deeper, it indicates that the wall thickness thinning degree of the region is heavier, and the erosion by the scouring is more serious.

[0075] Exemplarily, a preset color marking rule is obtained, and then the pipeline to be detected is color marked according to the color marking rule and the index coordinate point of each detection point, to obtain a corresponding planar color difference matrix image.

[0076] In step 108, the three-dimensional pipeline model is marked according to the preset index standard, the planar color difference matrix image and the thickness detection data, to update the three-dimensional pipeline model, and obtain a target pipeline model. The target pipeline model is used to represent the wall thickness degree of the pipeline to be detected.

[0077] The index standard can refer to a standard used for marking the three-dimensional pipeline model. The index standard is preset, and can be related to the purpose of the pipeline to be detected. For example, when the pipeline to be detected is a fire-fighting pipeline, the index standard can include the parameter standard required by laws and regulations of the fire-fighting pipeline, the industry standard of the fire-fighting pipeline, and the like.

[0078] Exemplarily, the three-dimensional pipeline model is marked according to the preset index standard, the planar color difference matrix image and the thickness detection data, to obtain the target pipeline model.

[0079] The pipeline data processing method of the embodiment of the present application improves the detection efficiency of the pipeline to be detected by scanning and detecting the pipeline to be detected by the detection device, and improves the accuracy of the thickness detection data. Then, the pipeline to be detected is converted into a three-dimensional pipeline model, and the index coordinate point corresponding to each detection point is determined according to the thickness detection data and the original pipeline parameters. Then, the pipeline to be detected is color marked according to each index coordinate point, to obtain a planar color difference matrix image. Then, the three-dimensional pipeline model is marked according to the index standard, the planar color difference matrix image and the thickness detection data, to obtain a target pipeline model. Therefore, the thickness detection data is improved in intuitiveness, and is convenient for intuitively understanding the change trend of the pipeline wall thickness.

[0080] Please refer to Figure 2 In some embodiments, step 102 includes but is not limited to the following steps:

[0081] In step 202, the three-dimensional pipeline model of the pipeline to be detected is obtained by performing annular scanning detection on the pipeline to be detected based on a detection probe on the detection device.

[0082] The detection probe can refer to a probe used for thickness detection of the pipeline to be detected.

[0083] The circular scanning detection can refer to detecting around the pipeline to be detected once.

[0084] Exemplarily, the detection probe can be used to position on the pipeline to be detected first to determine the detection points, and then the pipeline to be detected is detected based on the detection points, and after the circular scanning detection of the pipeline to be detected is completed, the three-dimensional pipeline model of the pipeline to be detected is obtained.

[0085] In step 204, the wall thickness of each detection point on the same radial plane of the pipeline to be detected is detected to obtain the corresponding thickness detection data.

[0086] The radial plane can refer to a plane formed along the radial direction of the pipeline to be detected.

[0087] The wall thickness detection can refer to detecting the wall thickness of the pipeline to be detected.

[0088] Exemplarily, a plurality of detection points are arranged on the radial plane of the pipeline to be detected, and the wall thickness of the pipeline to be detected is detected at each detection point by using the detection probe to obtain the thickness detection data corresponding to each detection point.

[0089] In step 206, the detection device is moved, and the step of detecting the wall thickness of each detection point on the same radial plane of the pipeline to be detected is circularly executed to obtain the corresponding thickness detection data until the detection of the pipeline to be detected is completed.

[0090] After the wall thickness detection of all detection points on a certain radial plane is completed, the detection device is moved to reach the next position, and the wall thickness detection of all detection points on the radial plane where the reached position is located is performed to obtain the corresponding thickness detection data. Step 204 is circularly executed until the detection of the pipeline to be detected is completed.

[0091] For example, assuming that the pipe diameter length of the pipeline to be detected is L, the moving length of the detection device is D each time, and the moving times is N, when L=D*N, it can be indicated that the detection of the pipeline to be detected has been completed.

[0092] The following will be described in combination with Figure 3 , Figure 4A and Figure 4BThe step of using the detection device to detect the wall thickness in the embodiments of the present application is described in detail. In the embodiments, the detection device includes, but is not limited to, a detachable lock 301, a fixed telescopic shaft 302, a fixed support device 303, a roller telescopic shaft 304, a moving roller 305, a track connecting rod 306, a laser scanning device 307, a rotating telescopic shaft 308, a longitudinal telescopic shaft 309, a power traction and supply device 310, a flexible connecting shaft 311, an electromagnetic ultrasonic thickness gauge 312, a signal transmission device 313, a magnetic roller 314, a detection probe telescopic shaft 315, a detection probe 316, a probe auxiliary moving roller 317, and a control device 318.

[0093] The specific operation process of the detection device is as follows: first, open the detachable lock 301, and install the track 319 on the pipe 300 to be detected; then adjust the fixed telescopic shaft 302, and attach the fixed support device 303 to the surface of the pipe 300 to be detected to complete the fixing of the track 319. Adjust the roller telescopic shaft 304, and attach the moving roller 305 to the surface of the pipe to realize the longitudinal movement of the track 319 on the surface of the pipe 300 to be detected. Place the magnetic roller 314 in the track groove, and control the power traction and supply device 310 to output power through the control device 318 to realize the movement control of the detection device. The control device can also control the laser scanning device 307 to complete the scanning of the pipe 300 to be detected to establish a three-dimensional pipe model of the pipe 300 to be detected. The control device 318 is also used to control the electromagnetic ultrasonic thickness gauge 312, the signal transmission device 313, the magnetic roller 314, the detection probe telescopic shaft 315, and the detection probe 316 to realize the wall thickness detection of the pipe 300 to be detected, and transmit the corresponding thickness detection data to the target terminal through the signal transmission device 313. The target terminal can be a terminal for storing thickness detection data, such as a personal computer, a mobile phone, etc.

[0094] In the embodiments, the control device 318 communicates with other components in the detection device through network connection.

[0095] The technical solution of the embodiments of the present application realizes automatic detection of the pipe to be detected through the detection device, and improves the detection efficiency and the accuracy of the detection data.

[0096] As Figure 5As shown, in some embodiments, step 202 includes but is not limited to the following steps: positioning at a radial plane on the pipeline to be measured, and setting the positioned position as a detection point, performing wall thickness detection at the detection point to obtain corresponding detection data; rotating a preset angle at the detection point, and setting the rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data; cyclically performing the steps of rotating a preset angle at the detection point, and setting the rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data, until the detection at the radial plane is completed; obtaining the detection data corresponding to each detection point, and identifying and positioning the detection data corresponding to each detection point to obtain thickness detection data.

[0097] Specifically, after the detection device is installed on the pipeline to be measured, positioning is performed at a certain radial plane of the pipeline to be measured, and a fixed orientation (such as 12 o'clock orientation) is taken as a 0-degree point (such as Figure 5 As shown, the 0-degree point is an initial detection point (measurement zero point), then wall thickness detection is performed at the detection point to obtain corresponding detection data, and then a preset angle (such as 2πR / D, where R is the radius of the pipeline, and D is the diameter of the probe, that is, the ratio of the circumferential length of the pipeline to the diameter of the probe is the preset angle) is rotated in a preset direction (such as clockwise direction), to reach a rotated position, and the rotated position is set as a detection point, then wall thickness detection is performed at the position to obtain corresponding detection data, and wall thickness detection is performed on the pipeline to be measured after rotating the preset angle again, until the entire detection on the radial plane is completed (such as when the rotated angle is 360 degrees, it indicates that the entire detection is completed). After completing the wall thickness detection of all detection points on a certain radial plane, the corresponding thickness detection data is obtained after identifying and positioning all detection data. The identifying and positioning can refer to calibration and reset processing of the detection data.

[0098] Please refer to Figure 6 In some embodiments, the original pipeline parameters include the original pipeline wall thickness and the design life. Step 104 includes but is not limited to the following steps:

[0099] Step 602: judging the thickness detection data corresponding to each detection point according to the original pipeline wall thickness to obtain the thickness index corresponding to each detection point.

[0100] The original pipeline wall thickness can refer to the design wall thickness of the pipeline to be measured.

[0101] The thickness index can refer to the relative index of the thickness detection data relative to the original pipeline wall thickness. For example, when the thickness detection data is close to the original pipeline wall thickness, the corresponding thickness index is normal.

[0102] Exemplarily, the average original pipe wall thickness value of the to-be-tested pipe can be taken as a relative zero point, and each certain value different from the average original pipe wall thickness value can be taken as a scale (for example, each 6.25% difference is taken as a scale). If the difference between the thickness detection data and the relative zero point is within plus or minus one scale, the corresponding thickness index is A (normal). If the difference between the thickness detection data and the relative zero point is within plus or minus two scales, the corresponding thickness index is B (slight). If the difference between the thickness detection data and the relative zero point is out of plus or minus two scales, the corresponding thickness detection index is C (serious).

[0103] In step 604, the inner wall morphology of the to-be-tested pipe is determined according to the thickness detection data corresponding to each detection point, and the inner wall morphology is evaluated to obtain a morphology index corresponding to each detection point.

[0104] The inner wall morphology of the pipe can refer to the shape of the inner wall of the to-be-tested pipe. The inner wall morphology of the pipe can directly show the thickness change trend of the to-be-tested pipe.

[0105] The morphology index can refer to an evaluation index corresponding to the inner wall morphology of the pipe.

[0106] Exemplarily, the inner wall morphology of the to-be-tested pipe is first determined according to the thickness detection data corresponding to each detection point, and then the inner wall morphology is evaluated. When the inner wall morphology of the to-be-tested pipe is characterized by uniform thinning, the corresponding morphology index is A (normal). When the inner wall morphology of the to-be-tested pipe is characterized by point-like thinning, the corresponding morphology index is B (slight). When the inner wall morphology of the to-be-tested pipe is characterized by large-scale pits, the corresponding morphology index is C (serious).

[0107] In step 606, the to-be-tested pipe is evaluated according to the design life to obtain a life index.

[0108] The life index can refer to an evaluation index of the current service life of the pipe.

[0109] Exemplarily, the current service life of the to-be-tested pipe is first determined, and then the design life is taken as a relative zero point, and 10% of the design life is taken as a scale. The current service life is in a positive interval if the current service life does not reach the design life, and is in a negative interval if the current service life exceeds the design life. A (normal) is greater than one scale in the positive interval, B (slight) is within one scale in the positive interval, and C (serious) is in the negative interval.

[0110] For example, when the design life is 20 years, 20 years is taken as a relative zero point. If the current service life is out of one scale (the current service life is below 18 years), A (normal) is obtained. If the current service life is within one scale (the current service life is above 18 years and below 20 years), B (slight) is obtained. If the current service life is in a negative interval (the current service life is above 20 years), C (serious) is obtained.

[0111] Step 608, according to the thickness index, the topography index and the service life index, the index coordinate point corresponding to each detection point is determined.

[0112] Exemplarily, the index coordinate point corresponding to each detection point can be expressed in the form of (thickness index, topography index, service life index).

[0113] The technical scheme of the embodiment of the present application determines the thickness index, the topography index and the service life index of each detection point, thereby determining the corresponding index coordinate point, realizes the index calibration of the thickness detection data of each detection point, improves the intuitiveness of data observation, and is beneficial to subsequent index calibration of the to-be-measured pipeline.

[0114] Please refer to Figure 7 , Figure 8 and Figure 9 In some embodiments, step 106 includes but is not limited to the following steps: converting the three-dimensional pipeline model into a plan view, and obtaining the coordinates of each detection point on the plan view; performing color calibration according to the preset color calibration rule and the index coordinate point corresponding to each detection point at the coordinates of each detection point on the plan view, to obtain the plan color difference matrix corresponding to the to-be-measured pipeline.

[0115] The color calibration rule can refer to a rule for color calibration of each detection point, and the color calibration rule is preset. For example, the more normal indexes in the index coordinate point, the lighter the color calibration, and the more serious indexes, the darker the color calibration.

[0116] Exemplarily, as shown in Figure 7 , Figure 8 and Figure 9 , first, the three-dimensional pipeline model is converted into a plan view, then the coordinates of each detection point on the plan view are obtained, and color calibration is performed according to the color calibration rule and the index coordinate point at the coordinates of each detection point on the plan view, to obtain the corresponding plan color difference matrix. For example, for a certain detection point, the more normal indexes in the index coordinate point corresponding to the detection point, the lighter the color calibration, and the more serious indexes, the darker the color calibration. For example, when the index coordinate point is (A, A, A), green color can be used for calibration, and when the index coordinate point is (C, C, C), black color can be used for calibration.

[0117] It should be noted that each index can also be color calibrated separately, and then the calibrated colors are superimposed to obtain the corresponding plan color difference matrix.

[0118] The technical scheme of the embodiment of the present application converts the three-dimensional pipeline model into a plan view, then determines the coordinate points of each detection point in the plan view, and then color calibrates each coordinate point to obtain a corresponding plan color difference matrix, thereby facilitating observation of the wall thickness change trend of the to-be-detected pipeline and improving the intuitiveness of the wall thickness detection data.

[0119] As shown in Figure 10 In some embodiments, the index standard includes a color difference index standard and a wall thickness index standard. Step 108 includes, but is not limited to, the following steps: marking the plan color difference matrix according to the color difference index standard; converting the marked plan color difference matrix into a three-dimensional model to obtain a color difference pipeline model; and marking the color difference pipeline model according to the wall thickness index standard and the thickness detection data to obtain a target pipeline model.

[0120] The color difference index standard can refer to a color difference standard for marking the plan color difference matrix. For example, when a darker color represents a more serious index, the color difference index standard can refer to a standard for marking all black areas in the plan color difference matrix.

[0121] The wall thickness index standard can refer to a thickness standard for marking the color difference pipeline model. For example, the wall thickness index standard can be a standard for marking all thicknesses in the color difference pipeline model that are lower than a preset value.

[0122] For example, first, the plan color difference matrix is marked according to the color difference index standard, then the marked plan color difference matrix is converted into a three-dimensional model to obtain a color difference pipeline model, and then the color difference pipeline model is marked according to the wall thickness index standard and the thickness detection data to obtain a target pipeline model, thereby improving the intuitiveness of the detection data and marking the areas in the to-be-detected pipeline that do not meet the color difference index standard and the wall thickness index standard to help subsequent maintenance personnel identify and locate, thereby improving the efficiency of maintenance, facilitating maintenance of the to-be-detected pipeline, and improving the safety of the to-be-detected pipeline.

[0123] It should be understood that, although each step in the flowchart involved in the above embodiments is displayed in sequence according to the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in the above embodiments can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or steps or stages in other steps.

[0124] Based on the same inventive concept, the embodiment of the present application also provides a pipeline data processing system for implementing the pipeline data processing method described above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme described in the above method.

[0125] In one embodiment, as shown in Figure 11 A pipeline data processing system is provided, comprising: a detection device 1102, an index calibration module 1104, a color calibration module 1106, and an updating module 1108, wherein:

[0126] The detection device 1102 is configured to scan and detect the pipeline under test to obtain a three-dimensional pipeline model corresponding to the pipeline under test and thickness detection data of the pipeline under test at each detection point.

[0127] The index calibration module 1104 is configured to perform index calibration according to the original pipeline parameters of the pipeline under test and the thickness detection data of each detection point to obtain index coordinate points of each detection point.

[0128] The color calibration module 1106 is configured to perform color calibration on the pipeline under test according to each index coordinate point to obtain a planar color difference matrix diagram corresponding to the pipeline under test; the planar color difference matrix diagram is used to represent the wall thickness thinning degree of the pipeline under test.

[0129] The updating module 1108 is configured to perform labeling on the three-dimensional pipeline model according to the preset index standard, the planar color difference matrix diagram, and the thickness detection data to update the three-dimensional pipeline model and obtain a target pipeline model; the target pipeline model is used to represent the wall thickness degree of the pipeline under test.

[0130] In some embodiments, the detection device 1102 comprises a detection probe, a wall thickness detection unit, and a circulation unit; wherein:

[0131] The detection probe is configured to perform annular scanning detection on the pipeline under test to obtain a three-dimensional pipeline model of the pipeline under test.

[0132] The wall thickness detection unit is configured to perform wall thickness detection on each detection point on the same radial surface of the pipeline under test to obtain corresponding thickness detection data.

[0133] The circulation unit is configured to move the detection device and cyclically perform the step of performing wall thickness detection on each detection point on the same radial surface of the pipeline under test to obtain corresponding thickness detection data until the detection of the pipeline under test is completed.

[0134] In some embodiments, the wall thickness detection unit comprises:

[0135] The positioning subunit is configured to position the radial surface on the pipeline under test and set the positioned position as a detection point, and perform wall thickness detection at the detection point to obtain corresponding detection data.

[0136] The rotating sub-unit is configured to rotate a preset angle at the detection point, set the rotated position as the detection point, and perform the wall thickness detection at the detection point to obtain corresponding detection data.

[0137] The circulating sub-unit is configured to cyclically execute the steps of rotating a preset angle at the detection point, setting the rotated position as the detection point, and performing the wall thickness detection at the detection point to obtain corresponding detection data until the detection of the radial surface is completed.

[0138] The identifying and positioning sub-unit is configured to obtain the detection data corresponding to each detection point, and perform identifying and positioning on the detection data corresponding to each detection point to obtain the thickness detection data.

[0139] In some embodiments, the original pipeline parameters include an original pipeline wall thickness and a design service life; and the index calibration module includes:

[0140] The thickness evaluation unit is configured to evaluate the thickness detection data corresponding to each detection point according to the original pipeline wall thickness to obtain a thickness index corresponding to each detection point.

[0141] The morphology evaluation unit is configured to determine the inner wall morphology of the pipeline to be measured according to the thickness detection data corresponding to each detection point, and evaluate the inner wall morphology to obtain a morphology index corresponding to each detection point.

[0142] The service life evaluation unit is configured to evaluate the pipeline to be measured according to the design service life to obtain a service life index.

[0143] The coordinate point determination unit is configured to determine an index coordinate point corresponding to each detection point according to the thickness index, the morphology index, and the service life index.

[0144] In some embodiments, the color calibration module 1106 includes:

[0145] The plan view conversion unit is configured to convert the three-dimensional pipeline model into a plan view, and obtain the coordinates of each detection point on the plan view.

[0146] The color calibration unit is configured to perform color calibration on the coordinates of each detection point on the plan view according to a preset color calibration rule and the index coordinate point corresponding to each detection point to obtain a plan color difference matrix diagram corresponding to the pipeline to be measured.

[0147] In some embodiments, the updating module 1108 includes:

[0148] The color difference annotation unit is configured to annotate the plan color difference matrix diagram according to a color difference index standard.

[0149] The three-dimensional model conversion unit is configured to convert the plan color difference matrix diagram after the annotation processing into a three-dimensional model to obtain a color difference pipeline model.

[0150] A thickness labeling unit is configured to label the color difference pipeline model according to the wall thickness index standard and the thickness detection data to obtain a target pipeline model.

[0151] The modules in the pipeline data processing system can be implemented by software, hardware, or a combination thereof. The modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to the modules.

[0152] In an embodiment, a computer device, which can be a terminal, has an internal structure as shown in Figure 12 The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to perform wired or wireless communication with external terminals. The wireless communication can be achieved through WIFI, mobile cellular network, NFC (Near Field Communication), or other technologies. The computer program is executed by the processor to implement a pipeline data processing method. The display unit of the computer device is configured to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball, or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0153] Those skilled in the art can understand that Figure 12 The structure shown in the above embodiment is only a block diagram of part of the structure related to the scheme of the present application, and does not limit the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0154] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program: based on a detection device, scanning and detecting a to-be-detected pipeline to obtain a three-dimensional pipeline model corresponding to the to-be-detected pipeline and thickness detection data corresponding to each detection point of the to-be-detected pipeline; based on original pipeline parameters of the to-be-detected pipeline and the thickness detection data corresponding to each detection point, performing index calibration to obtain index coordinate points of each detection point; based on the index coordinate points, performing color calibration on the to-be-detected pipeline to obtain a planar color difference matrix diagram corresponding to the to-be-detected pipeline; the planar color difference matrix diagram is used to represent a wall thickness thinning degree of the to-be-detected pipeline; based on a preset index standard, the planar color difference matrix diagram and the thickness detection data, performing marking on the three-dimensional pipeline model to update the three-dimensional pipeline model to obtain a target pipeline model; the target pipeline model is used to represent a wall thickness degree of the to-be-detected pipeline.

[0155] In one embodiment, the processor further implements the following steps when executing the computer program: based on a detection probe on the detection device, performing annular scanning and detection on the to-be-detected pipeline to obtain a three-dimensional pipeline model of the to-be-detected pipeline; performing wall thickness detection on each detection point on a same radial plane of the to-be-detected pipeline to obtain corresponding thickness detection data; moving the detection device and cyclically performing the step of performing wall thickness detection on each detection point on the same radial plane of the to-be-detected pipeline to obtain corresponding thickness detection data until the detection on the to-be-detected pipeline is completed.

[0156] In one embodiment, the processor further implements the following steps when executing the computer program: positioning a radial plane on the to-be-detected pipeline, setting a positioned position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data; rotating a preset angle at the detection point, setting a rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data; cyclically performing the steps of rotating a preset angle at the detection point, setting a rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data until the detection on the radial plane is completed; obtaining detection data corresponding to each detection point, and identifying and positioning the detection data corresponding to each detection point to obtain thickness detection data.

[0157] In one embodiment, the processor further implements the following steps when executing the computer program: based on original pipeline wall thickness, judging the thickness detection data corresponding to each detection point to obtain thickness indexes corresponding to each detection point; based on the thickness detection data corresponding to each detection point, determining an inner wall morphology of the to-be-detected pipeline, and judging the inner wall morphology to obtain morphology indexes corresponding to each detection point; based on a design life, judging the to-be-detected pipeline to obtain a life index; and based on the thickness indexes, the morphology indexes and the life index, determining index coordinate points corresponding to each detection point.

[0158] In one embodiment, the processor, when executing the computer program, also implements the following steps: converting the three-dimensional pipeline model into a plan view, and obtaining coordinates of each detection point on the plan view; performing color calibration on each detection point according to a preset color calibration rule and the index coordinate point corresponding to each detection point at the coordinates of the plan view corresponding to each detection point, to obtain a plan color difference matrix diagram corresponding to the pipeline under test.

[0159] In one embodiment, the processor, when executing the computer program, also implements the following steps: marking on the plan color difference matrix diagram according to the color difference index standard; converting the marked plan color difference matrix diagram into a three-dimensional model to obtain a color difference pipeline model; and marking the color difference pipeline model according to the wall thickness index standard and the thickness detection data to obtain a target pipeline model.

[0160] In one embodiment, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program, when executed by a processor, implements the following steps: performing scanning detection on the pipeline under test based on a detection device to obtain a three-dimensional pipeline model corresponding to the pipeline under test and thickness detection data corresponding to each detection point of the pipeline under test; performing index calibration on the pipeline under test according to original pipeline parameters of the pipeline under test and the thickness detection data corresponding to each detection point to obtain an index coordinate point of each detection point; performing color calibration on the pipeline under test according to each index coordinate point to obtain a plan color difference matrix diagram corresponding to the pipeline under test; the plan color difference matrix diagram is used to represent a wall thickness thinning degree of the pipeline under test; and marking on the three-dimensional pipeline model according to a preset index standard, the plan color difference matrix diagram and the thickness detection data to update the three-dimensional pipeline model to obtain a target pipeline model; the target pipeline model is used to represent a wall thickness degree of the pipeline under test.

[0161] In one embodiment, the computer program, when executed by the processor, also implements the following steps: performing annular scanning detection on the pipeline under test based on a detection probe on the detection device to obtain a three-dimensional pipeline model of the pipeline under test; performing wall thickness detection on each detection point on the same radial plane of the pipeline under test to obtain corresponding thickness detection data; and moving the detection device to cyclically perform the step of performing wall thickness detection on each detection point on the same radial plane of the pipeline under test to obtain corresponding thickness detection data until the detection on the pipeline under test is completed.

[0162] In one embodiment, the computer program, when executed by the processor, further implements the following steps: positioning a radial surface on the to-be-tested pipeline, and setting the positioned position as a detection point, performing wall thickness detection at the detection point to obtain corresponding detection data; rotating a preset angle at the detection point, and setting the rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data; cyclically performing the steps of rotating a preset angle at the detection point, and setting the rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data, until the detection of the radial surface is completed; obtaining the detection data corresponding to each detection point, and identifying and positioning the detection data corresponding to each detection point to obtain thickness detection data.

[0163] In one embodiment, the computer program, when executed by the processor, further implements the following steps: judging the thickness detection data corresponding to each detection point according to the original pipeline wall thickness to obtain a thickness index corresponding to each detection point; determining the inner wall morphology of the to-be-tested pipeline according to the thickness detection data corresponding to each detection point, and judging the inner wall morphology to obtain a morphology index corresponding to each detection point; judging the to-be-tested pipeline according to the design life to obtain a life index; and determining an index coordinate point corresponding to each detection point according to the thickness index, the morphology index, and the life index.

[0164] In one embodiment, the computer program, when executed by the processor, further implements the following steps: converting the three-dimensional pipeline model into a plan view, and obtaining the coordinates of each detection point on the plan view; performing color calibration on the coordinates of each detection point on the plan view according to a preset color calibration rule and the index coordinate point corresponding to each detection point to obtain a plan color difference matrix corresponding to the to-be-tested pipeline.

[0165] In one embodiment, the computer program, when executed by the processor, further implements the following steps: annotating the plan color difference matrix according to a color difference index standard; converting the annotated plan color difference matrix into a three-dimensional model to obtain a color difference pipeline model; and annotating the color difference pipeline model according to a wall thickness index standard and the thickness detection data to obtain a target pipeline model.

[0166] In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the following steps: based on a detection device, scanning and detecting a to-be-detected pipeline to obtain a three-dimensional pipeline model corresponding to the to-be-detected pipeline and thickness detection data corresponding to each detection point of the to-be-detected pipeline; performing index calibration according to original pipeline parameters of the to-be-detected pipeline and the thickness detection data corresponding to each detection point to obtain index coordinate points of each detection point; performing color calibration on the to-be-detected pipeline according to the index coordinate points to obtain a planar color difference matrix diagram corresponding to the to-be-detected pipeline; the planar color difference matrix diagram is used to represent a wall thickness thinning degree of the to-be-detected pipeline; according to a preset index standard, the planar color difference matrix diagram and the thickness detection data, marking on the three-dimensional pipeline model to update the three-dimensional pipeline model to obtain a target pipeline model; the target pipeline model is used to represent a wall thickness degree of the to-be-detected pipeline.

[0167] In one embodiment, the computer program, when executed by the processor, further implements the following steps: based on a detection probe on the detection device, performing annular scanning and detection on the to-be-detected pipeline to obtain a three-dimensional pipeline model of the to-be-detected pipeline; performing wall thickness detection on each detection point on a same radial plane of the to-be-detected pipeline to obtain corresponding thickness detection data; moving the detection device and cyclically performing the step of performing wall thickness detection on each detection point on the same radial plane of the to-be-detected pipeline to obtain corresponding thickness detection data until the detection on the to-be-detected pipeline is completed.

[0168] In one embodiment, the computer program, when executed by the processor, further implements the following steps: positioning a radial plane on the to-be-detected pipeline, setting a positioned position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data; rotating a preset angle at the detection point, setting a rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data; cyclically performing the steps of rotating a preset angle at the detection point, setting a rotated position as a detection point, and performing wall thickness detection at the detection point to obtain corresponding detection data until the detection on the radial plane is completed; obtaining detection data corresponding to each detection point, and identifying and positioning the detection data corresponding to each detection point to obtain thickness detection data.

[0169] In one embodiment, the computer program, when executed by the processor, further implements the following steps: judging the thickness detection data corresponding to each detection point according to an original pipeline wall thickness to obtain thickness indexes corresponding to each detection point; determining an inner wall morphology of the to-be-detected pipeline according to the thickness detection data corresponding to each detection point, and judging the inner wall morphology to obtain morphology indexes corresponding to each detection point; judging the to-be-detected pipeline according to a design life to obtain a life index; and determining index coordinate points corresponding to each detection point according to the thickness indexes, the morphology indexes and the life index.

[0170] In one embodiment, the computer program, when executed by the processor, further implements the following steps: converting the three-dimensional pipeline model into a plan view, and obtaining coordinates of each detection point on the plan view; and performing color calibration on the coordinates of each detection point on the plan view according to a preset color calibration rule and an index coordinate point corresponding to each detection point, to obtain a plan color difference matrix diagram corresponding to the pipeline to be measured.

[0171] In one embodiment, the computer program, when executed by the processor, further implements the following steps: marking on the plan color difference matrix diagram according to a color difference index standard; converting the marked plan color difference matrix diagram into a three-dimensional model to obtain a color difference pipeline model; and marking the color difference pipeline model according to a wall thickness index standard and thickness detection data to obtain a target pipeline model.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0173] Any combination of the technical features in the above embodiments can be made. For the sake of brevity, the foregoing description is not intended to be exhaustive or to limit the scope of the application to the precise embodiments described. Modifications or variations are possible in light of the above teachings. The embodiments were chosen and described in order to best illustrate the principles of the application and its practical application and to thereby enable others skilled in the art to best utilize the application.

[0174] The above embodiments only express several implementation manners of the application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the patent scope of the application. It should be pointed out that, for ordinary skilled persons in the art, some modifications and improvements can be made without departing from the concept of the application, and these all belong to the protection scope of the application. Therefore, the protection scope of the application should be subject to the appended claims.

Claims

1. A pipeline data processing method, characterized by, The method includes: Based on the detection device, the pipeline under test is scanned and detected to obtain the three-dimensional pipeline model corresponding to the pipeline under test and the thickness detection data of the pipeline under test at each detection point. The indexes are calibrated based on the original pipe parameters of the pipe to be tested and the thickness detection data corresponding to each detection point to obtain the index coordinate points of each detection point; the index coordinate points are composed of multiple calibration indicators, including thickness indicators, morphology indicators and life indicators. The test pipe is color-calibrated based on the coordinate points of each index to obtain a planar color difference matrix diagram corresponding to the test pipe; the planar color difference matrix diagram is used to characterize the degree of wall thickness reduction of the test pipe. The color difference matrix diagram on the plane is marked according to the color difference index standard; The annotated planar color difference matrix diagram is converted into a three-dimensional model to obtain the color difference pipeline model; The color difference pipe model is labeled according to the wall thickness index standard and the thickness detection data to obtain the target pipe model; the target pipe model is used to characterize the wall thickness of the pipe to be tested.

2. The method of claim 1, wherein, The method involves scanning and detecting the pipeline under test using a detection device to obtain a three-dimensional pipeline model and thickness detection data of the pipeline at each detection point, including: The detection probe on the detection device is used to perform a ring scan detection on the pipeline under test to obtain a three-dimensional pipeline model of the pipeline under test. The wall thickness is measured at each detection point on the same radial surface of the pipe to be tested, and the corresponding thickness measurement data is obtained. The detection device is moved and the steps of detecting the wall thickness at each detection point on the same radial surface of the pipe under test are performed repeatedly to obtain the corresponding thickness detection data until the detection of the pipe under test is completed.

3. The method of claim 2, wherein, The process of measuring the wall thickness at various detection points on the same radial surface of the pipe under test to obtain corresponding thickness measurement data includes: The radial surface of the pipe to be tested is positioned, and the position is set as the detection point. The wall thickness is measured at the detection point to obtain the corresponding test data. Rotate the device at the detection point by a preset angle, set the rotated position as the detection point, and perform wall thickness detection at the detection point to obtain the corresponding detection data. The process of rotating at the detection point by a preset angle, setting the rotated position as the detection point, and performing wall thickness detection at the detection point to obtain the corresponding detection data is repeated until the detection on the radial surface is completed. The detection data corresponding to each detection point is obtained, and the detection data corresponding to each detection point is identified and located to obtain the thickness detection data.

4. The method of claim 1, wherein, The original pipeline parameters include the original pipeline wall thickness and design life; The step of calibrating the index based on the original pipe parameters of the pipe under test and the thickness detection data corresponding to each detection point to obtain the index coordinate points of each detection point includes: Based on the original pipe wall thickness, the thickness detection data corresponding to each detection point are evaluated to obtain the thickness index corresponding to each detection point. determine the inner wall topography of the to-be-tested pipeline according to the thickness detection data corresponding to each detection point, and evaluate the inner wall topography to obtain a topography index corresponding to each detection point; evaluate the to-be-tested pipeline according to the design life to obtain a life index; determine an index coordinate point corresponding to each detection point according to the thickness index, the topography index, and the life index.

5. The method according to any one of claims 1 to 4, characterized in that, The color calibration of the to-be-tested pipeline according to each index coordinate point includes: convert the three-dimensional pipeline model into a plan view, and obtain the coordinates of each detection point on the plan view; perform color calibration according to a preset color calibration rule and the index coordinate point corresponding to each detection point at the coordinates of each detection point on the plan view to obtain the plan view color difference matrix of the to-be-tested pipeline.

6. A pipeline data processing system characterized by, The system includes: a detection device configured to scan and detect a to-be-tested pipeline to obtain a three-dimensional pipeline model corresponding to the to-be-tested pipeline and thickness detection data corresponding to the to-be-tested pipeline at each detection point; an index calibration module configured to calibrate indexes according to original pipeline parameters of the to-be-tested pipeline and the thickness detection data corresponding to each detection point to obtain index coordinate points of each detection point; the index coordinate points are composed of multiple calibration indexes, and the calibration indexes include a thickness index, a topography index, and a life index; a color calibration module configured to calibrate the color of the to-be-tested pipeline according to each index coordinate point to obtain a plan view color difference matrix of the to-be-tested pipeline; the plan view color difference matrix is used to represent the wall thickness thinning degree of the to-be-tested pipeline; an updating module configured to mark the plan view color difference matrix according to a color difference index standard; convert the marked plan view color difference matrix into a three-dimensional model to obtain a color difference pipeline model; mark the color difference pipeline model according to a wall thickness index standard and the thickness detection data to obtain a target pipeline model; the target pipeline model is used to represent the wall thickness degree of the to-be-tested pipeline.

7. The apparatus of claim 6, wherein, The detection device includes: a detection probe configured to perform annular scanning detection on the to-be-tested pipeline based on the detection probe on the detection device to obtain a three-dimensional pipeline model of the to-be-tested pipeline; a wall thickness detection unit configured to detect the wall thickness of each detection point on the same radial plane of the to-be-tested pipeline to obtain corresponding thickness detection data; a circulation unit configured to move the detection device and cyclically perform the steps of detecting the wall thickness of each detection point on the same radial plane of the to-be-tested pipeline to obtain corresponding thickness detection data until the detection of the to-be-tested pipeline is completed.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to implement the steps of the method of any one of claims 1 to 5.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 5.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 5.

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