A pipeline inner wall defect detection method and system based on pipeline robot

Abstract

The present invention relates to the technical field of pipeline detection, and discloses a pipeline inner wall defect detection method and system based on a pipeline robot. The method comprises: collecting structural defect information of the pipeline; calculating the pipeline crack impact value based on the inner surface crack information and the internal crack information, calculating the pipeline stratification impact value based on the pipeline stratification information, calculating the pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and calculating the pipeline thickness impact value based on the pipeline deviation value; judging whether to locate the pipeline defect based on the pipeline crack impact value, the pipeline stratification impact value, and the pipeline thickness impact value, respectively, and sending the positioning information and the pipeline crack impact value to a remote terminal; and classifying the pipeline into defect levels and providing defect classification warnings based on the pipeline comprehensive defect value. The present invention significantly improves the technical level of pipeline detection and provides a reliable guarantee for the safe operation of the pipeline.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline detection, and in particular to a pipeline robot-based pipeline inner wall defect detection method and system. Background Art

[0002] Pipelines are essential infrastructure for transporting media like gas, oil, and water. Their safe operation is directly linked to the normal functioning of industrial production and social life. However, over the long term, pipelines are susceptible to internal wall defects such as cracks, delamination, and corrosion, often due to factors such as corrosion from the media, external stress, and material aging. These defects can lead to leaks or even explosions. Therefore, pipeline inner wall defect detection technology is crucial for ensuring safe pipeline operation.

[0003] Traditional methods for detecting defects on the inner wall of pipelines mainly rely on a single technology, such as X-ray or ultrasonic testing. Although these methods can identify pipeline defects to a certain extent, they have many limitations in practical applications. First, traditional methods are not sensitive enough to detect delamination defects and tiny cracks in non-metallic pipelines (such as polyethylene (PE) pipelines), and often require multiple devices for verification, resulting in low detection efficiency. Secondly, X-ray detection requires manual operation and poses a risk of radiation exposure. Especially when inspecting high-altitude or buried pipelines, operators need to climb or dig, and the safety hazards are prominent. In addition, existing ultrasonic probes are difficult to adapt to the oily and scaling environment of the inner wall of PE pipelines, and are prone to misjudgment due to interference from dirt, and dynamic cleaning cannot be achieved, which limits their application in actual engineering. More importantly, traditional detection devices lack a multi-sensor data fusion mechanism and cannot simultaneously acquire thermal imaging, acoustic and visual data, resulting in a single dimension of defect assessment and difficulty in fully reflecting the health status of the pipeline.

[0004] Therefore, it is necessary to provide a pipeline inner wall defect detection method and system based on a pipeline robot to solve the problems of traditional pipeline inner wall defect detection methods relying on a single technology, insufficient sensitivity, low efficiency, safety hazards, susceptibility to interference from dirt, and a single evaluation dimension. Summary of the Invention

[0005] In view of this, the present invention proposes a pipeline inner wall defect detection method and system based on a pipeline robot, aiming to solve the problems that traditional pipeline inner wall defect detection methods rely on a single technology and have limitations such as insufficient sensitivity, low efficiency, safety hazards, susceptibility to interference from dirt, and a single evaluation dimension.

[0006] In one aspect, the present invention proposes a pipeline inner wall defect detection method based on a pipeline robot, comprising:

[0007] Collecting structural defect information of the pipeline; wherein the structural defect information includes inner surface crack information, internal crack information, pipeline layer information and pipeline thickness information;

[0008] Calculating a pipeline crack impact value based on the inner surface crack information and the internal crack information, calculating a pipeline stratification impact value based on the pipeline stratification information, calculating a pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and calculating a pipeline thickness impact value based on the pipeline deviation value;

[0009] determining whether to locate the pipeline defect based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, respectively; and if it is determined that the pipeline defect needs to be located, sending the location information and the pipeline crack impact value to a remote terminal;

[0010] The pipeline comprehensive defect value is calculated according to the pipeline crack impact value, the pipeline delamination impact value and the pipeline thickness impact value, and the pipeline defect grade is classified and the defect grade warning is performed according to the pipeline comprehensive defect value.

[0011] Furthermore, the acquisition of pipeline structural defect information includes:

[0012] The ultrasonic phased array probe is used to scan the inner wall of the pipeline, transmit ultrasonic waves and receive reflected signals. By analyzing the amplitude, time and phase changes of the reflected signals, the inner surface crack information, internal crack information, pipeline layer information and pipeline thickness information of the inner wall of the pipeline are identified;

[0013] The image data of the inner wall of the pipeline is collected by a high-definition camera, and the inner surface crack information of the inner wall of the pipeline is identified based on image processing to supplement the inner surface crack information;

[0014] The infrared temperature measurement module collects three-dimensional temperature field data of the inner wall of the pipeline, identifies local temperature abnormality areas, and generates thermal imaging maps to supplement the inner surface crack information and obtain the final structural defect information.

[0015] Furthermore, the calculation of the pipeline crack impact value based on the inner surface crack information and the internal crack information includes:

[0016] Obtain the crack length, crack depth, and crack width of each inner surface crack and internal crack, set the crack length threshold, crack depth threshold, and crack width threshold, and calculate the pipeline crack impact value using the following formula:

[0017]

[0018] In the above formula, S1 represents the impact value of pipeline crack, Li represents the crack length value of the i-th crack, Lmax represents the crack length threshold, Di represents the crack depth value of the i-th crack, Dmax represents the crack depth threshold, Wi represents the crack width value of the i-th crack, Wmax represents the crack width threshold, a represents the crack length value weight coefficient, b represents the crack depth value weight coefficient, c represents the crack width value weight coefficient, di represents the crack position weight coefficient of the i-th crack, and b represents the total number of cracks. Among them, the value ranges of a, b and c are all [0, 1], the value range of di is (0, 1], and a+b+c=1, i=1,2,3,…,n.

[0019] Furthermore, the calculating of the pipeline stratification impact value according to the pipeline stratification information includes:

[0020] Obtaining a layer area, setting a first layer area and a second layer area, wherein the first layer area is smaller than the second layer area;

[0021] If the layered area is less than or equal to the first layered area, and the layered area is greater than zero, then the pipeline layered impact value is the first layered impact value;

[0022] If the layered area is larger than the first layered area and smaller than or equal to the second layered area, the pipeline layered impact value is the second layered impact value;

[0023] If the layered area is larger than the second layered area, the pipeline layered impact value is the third layered impact value;

[0024] Among them, the first layer influence value is smaller than the second layer influence value, and the second layer influence value is smaller than the third layer influence value.

[0025] Furthermore, the calculating of the pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and the calculating of the pipeline thickness impact value based on the pipeline deviation value, include:

[0026] Calculate the pipeline deviation value between the pipeline thickness information and the pipeline standard thickness information, and take the absolute value of the pipeline deviation value to obtain the absolute value of the pipeline deviation;

[0027] Setting a first deviation absolute value and a second deviation absolute value, wherein the first deviation absolute value is smaller than the second deviation absolute value;

[0028] If the absolute value of the pipeline deviation is less than or equal to the absolute value of the first deviation, the pipeline thickness influence value is the first thickness influence value;

[0029] If the absolute value of the pipeline deviation is greater than the absolute value of the first deviation and less than or equal to the absolute value of the second deviation, the pipeline thickness influence value is the second thickness influence value;

[0030] If the absolute value of the pipeline deviation is greater than the absolute value of the second deviation, the pipeline thickness influence value is the third thickness influence value;

[0031] The first thickness influence value is smaller than the second thickness influence value, and the second thickness influence value is smaller than the third thickness influence value.

[0032] Furthermore, the calculation of the pipeline deviation value between the pipeline thickness information and the pipeline standard thickness information includes:

[0033] If the pipeline deviation value is less than zero, it is judged that the pipeline is corroded or worn;

[0034] If the pipeline deviation value is equal to zero, the pipeline is judged to be normal and the pipeline thickness impact value is zero;

[0035] If the pipeline deviation value is greater than zero, it is determined that foreign matter is deposited in the pipeline.

[0036] Furthermore, the determining whether to locate the pipeline defect according to the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value respectively includes:

[0037] The minimum values ​​of the pipeline crack impact value, pipeline delamination impact value and pipeline thickness impact value are set respectively, and recorded as the minimum pipeline crack impact value, the minimum pipeline delamination impact value and the minimum pipeline thickness impact value;

[0038] If any of the pipeline crack impact value, pipeline delamination impact value, and pipeline thickness impact value is greater than or equal to its corresponding minimum value, it is determined that the pipeline defect needs to be located;

[0039] Otherwise, it is determined that there is no need to locate the pipeline defect.

[0040] Furthermore, the calculation of the pipeline comprehensive defect value based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value includes:

[0041] The comprehensive defect value of the pipeline is calculated by the following formula:

[0042] Z=α*S1+β*S2+γ*S3;

[0043] In the above formula, Z represents the comprehensive defect value of the pipeline, S1 represents the influence value of the pipeline crack, S2 represents the influence value of the pipeline delamination, S3 represents the influence value of the pipeline thickness, α represents the pipeline crack weight coefficient, β represents the pipeline delamination weight coefficient, and γ represents the pipeline thickness influence coefficient. The value ranges of α, β, and γ are all [0, 1], and α+β+γ=1.

[0044] Furthermore, when the pipeline is classified into defect levels and a defect classification warning is performed based on the comprehensive defect value of the pipeline, the following steps are included:

[0045] Set a comprehensive defect threshold. If the pipeline comprehensive defect value is less than or equal to the comprehensive defect threshold, the defect level is level one and a level one warning is issued.

[0046] If the pipeline comprehensive defect value is greater than the comprehensive defect threshold and less than or equal to 1.5 times the comprehensive defect threshold, the defect level is level 2 and a level 2 warning is issued;

[0047] If the comprehensive defect value of the pipeline is greater than 1.5 times the comprehensive defect threshold, the defect level is level three and a level three warning is issued.

[0048] Compared with the existing technology, the beneficial effects of the present invention are as follows: through the multi-sensor fusion of ultrasonic phased array technology, high-definition visual module and infrared temperature measurement module, comprehensive detection of structural defects on the inner wall of the pipeline is achieved, including inner surface cracks, internal cracks, delamination defects and pipeline thickness information, significantly improving the accuracy and comprehensiveness of detection. Secondly, by calculating the pipeline crack impact value, delamination impact value and thickness impact value, the impact of different defects on pipeline safety can be quantified, and combined with the positioning information, it is sent to the remote terminal, realizing the precise positioning and remote monitoring of defects. In addition, by calculating the comprehensive defect value of the pipeline, the pipeline is classified into defect levels and graded warnings are provided, providing a scientific basis for pipeline maintenance and repair, and effectively avoiding pipeline failure or safety accidents caused by defect accumulation. This method is not only applicable to non-metallic PE gas pipelines, but can also be widely used in various scenarios such as water supply and industrial pipelines. It has the advantages of strong environmental adaptability, high detection efficiency and good operational safety. Through intelligent data processing and multi-dimensional defect assessment, the present invention significantly improves the technical level of pipeline detection and provides reliable protection for the safe operation of the pipeline.

[0049] On the other hand, the present application also provides a pipeline inner wall defect detection system based on a pipeline robot, comprising:

[0050] An acquisition module includes a defect detection device, a high-definition vision module, and an infrared temperature measurement module. The defect detection device is fixed to the pipeline robot via a connecting device. The high-definition vision module and the infrared temperature measurement module are both arranged at an end of the pipeline robot away from the defect detection device. The acquisition module is configured to acquire structural defect information of the pipeline; wherein the structural defect information includes inner surface crack information, internal crack information, pipeline layer information, and pipeline thickness information;

[0051] a data processing module configured to calculate a pipeline crack impact value based on the inner surface crack information and the internal crack information, calculate a pipeline stratification impact value based on the pipeline stratification information, calculate a pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and calculate a pipeline thickness impact value based on the pipeline deviation value;

[0052] a positioning module configured to determine whether to locate the pipeline defect based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, and if it is determined that the pipeline defect needs to be located, send positioning information and the pipeline crack impact value to a remote terminal;

[0053] The early warning module is configured to calculate a comprehensive pipeline defect value based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, and to classify the pipeline into defect levels and provide defect classification early warning based on the comprehensive pipeline defect value.

[0054] It can be understood that the pipeline inner wall defect detection method and system based on the pipeline robot provided in this application have the same beneficial effects and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0056] Figure 1 A flow chart of a pipeline inner wall defect detection method based on a pipeline robot provided in an embodiment of the present invention;

[0057] Figure 2 A functional block diagram of a pipeline inner wall defect detection system based on a pipeline robot provided in an embodiment of the present invention;

[0058] Figure 3 A schematic structural diagram of a pipeline robot provided in an embodiment of the present invention.

[0059] In the figure, 10, pipeline robot; 11, fuselage trunk; 12, front connecting arm; 13, rear connecting arm; 14, first ball wheel; 15, second ball wheel; 16, omnidirectional wheel; 20, defect detection device; 30, high-definition vision module; 40, infrared temperature measurement module; 50, connecting device. DETAILED DESCRIPTION

[0060] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0061] In some embodiments of the present application, see Figure 1 As shown, this embodiment provides a pipeline inner wall defect detection method based on a pipeline robot, comprising the following steps:

[0062] S100: Collecting structural defect information of the pipeline; wherein the structural defect information includes inner surface crack information, internal crack information, pipeline layer information, and pipeline thickness information;

[0063] S200, calculating a pipeline crack impact value based on the inner surface crack information and the internal crack information, calculating a pipeline stratification impact value based on the pipeline stratification information, calculating a pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and calculating a pipeline thickness impact value based on the pipeline deviation value;

[0064] S300: Determine whether to locate the pipeline defect based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, and if it is determined that the pipeline defect needs to be located, send the location information and the pipeline crack impact value to the remote terminal;

[0065] S400: Calculate a comprehensive pipeline defect value based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, and classify the pipeline into defect grades and provide defect graded warnings based on the comprehensive pipeline defect value.

[0066] It can be understood that the multi-sensor fusion of ultrasonic phased array technology, high-definition vision modules, and infrared temperature measurement modules enables comprehensive detection of structural defects on the inner wall of pipelines, including inner surface cracks, internal cracks, delamination defects, and pipeline thickness information, significantly improving the accuracy and comprehensiveness of detection. Secondly, by calculating the pipeline crack impact value, delamination impact value, and thickness impact value, it is possible to quantify the impact of different defects on pipeline safety. Combined with positioning information, this information is sent to a remote terminal, enabling precise defect positioning and remote monitoring. In addition, by calculating the pipeline's comprehensive defect value, the pipeline is classified into defect levels and graded warnings are issued, providing a scientific basis for pipeline maintenance and repair, effectively avoiding pipeline failures or safety accidents caused by defect accumulation. This method is not only applicable to non-metallic PE gas pipelines, but can also be widely used in various scenarios such as water supply and industrial pipelines. It has the advantages of strong environmental adaptability, high detection efficiency, and good operational safety. Through intelligent data processing and multi-dimensional defect assessment, the present invention significantly improves the technical level of pipeline detection and provides reliable protection for the safe operation of pipelines.

[0067] Specifically, the pipeline robot uses an infrared temperature measurement module to perceive the three-dimensional temperature field inside the pipeline, and combines the vision module and inertial sensor to realize visual SLAM mapping, which facilitates autonomous navigation; the robot can drag defect detection devices to detect defects such as cracks, welds, and corrosion on the pipeline, and can navigate in complex pipeline networks, adapt to straight pipes, right-angle bends, T-shaped tees and other working conditions, and can even climb pipelines vertically, with strong movement capabilities; the robot has its own internal power supply to realize self-driving function, and can drag ultrasonic phased array detection devices, high-precision inertial navigation units or other devices (such as cleaning devices) to complete pipeline mapping and defect detection tasks.

[0068] In some embodiments of the present application, collecting structural defect information of a pipeline includes:

[0069] The ultrasonic phased array probe is used to scan the inner wall of the pipeline, transmit ultrasonic waves and receive reflected signals. By analyzing the amplitude, time and phase changes of the reflected signals, the inner surface crack information, internal crack information, pipeline layer information and pipeline thickness information of the inner wall of the pipeline are identified;

[0070] The image data of the inner wall of the pipeline is collected by a high-definition camera, and the inner surface crack information of the inner wall of the pipeline is identified based on image processing to supplement the inner surface crack information;

[0071] The infrared temperature measurement module collects three-dimensional temperature field data of the inner wall of the pipeline, identifies local temperature abnormality areas, and generates thermal imaging maps to supplement the inner surface crack information and obtain the final structural defect information.

[0072] As can be understood, the ultrasonic phased array probe, by emitting ultrasonic waves and analyzing the amplitude, timing, and phase variations of the reflected signals, can accurately identify inner surface cracks, internal cracks, delamination defects, and thickness information on the inner wall of a pipe, with particularly high sensitivity for minute cracks and delamination defects. Secondly, the high-definition vision module collects image data from the inner wall of the pipe and, using image processing technology, supplements the identification of inner surface crack information, further improving the accuracy and comprehensiveness of crack detection. Furthermore, the infrared temperature measurement module collects three-dimensional temperature field data from the inner wall of the pipe, identifies localized areas of temperature anomalies, and generates thermal imaging maps. This indirectly assists in determining the location and severity of defects such as cracks, providing multi-dimensional data support for defect detection. By fusion of multi-sensor data, this method not only overcomes the limitations of single-technology detection but also significantly improves the accuracy and reliability of defect identification, making it particularly suitable for complex environments such as non-metallic PE pipes. Furthermore, this method avoids the high risks of manual operation, improves detection efficiency and safety, and provides a scientific basis for pipeline maintenance and repair, with significant engineering application value.

[0073] In some embodiments of the present application, calculating the pipeline crack impact value based on the inner surface crack information and the internal crack information includes:

[0074] Obtain the crack length, crack depth, and crack width values ​​of each inner surface crack and internal crack, set the crack length threshold, crack depth threshold, and crack width threshold, and calculate the pipeline crack impact value using the following formula:

[0075]

[0076] In the above formula, S1 represents the impact value of pipeline crack, Li represents the crack length value of the i-th crack, Lmax represents the crack length threshold, Di represents the crack depth value of the i-th crack, Dmax represents the crack depth threshold, Wi represents the crack width value of the i-th crack, Wmax represents the crack width threshold, a represents the crack length value weight coefficient, b represents the crack depth value weight coefficient, c represents the crack width value weight coefficient, di represents the crack position weight coefficient of the i-th crack, and n represents the total number of cracks. Among them, the value ranges of a, b and c are all [0, 1], the value range of di is (0, 1], and a+b+c=1, i=1,2,3,…,n.

[0077] It can be understood that by obtaining the crack length value, crack depth value and crack width value of each inner surface crack and internal crack, the size characteristics of the crack can be fully understood. Secondly, setting the crack length threshold, crack depth threshold and crack width threshold can help distinguish which cracks need attention and which may have less impact on pipeline safety. Through a specific calculation formula, the size characteristics of the crack are combined with the corresponding weight coefficient, and the impact of each crack on pipeline safety can be quantitatively evaluated. The introduction of weight coefficients a, b, c and crack location weight coefficient di allows adjustment based on the specific location and importance of the size characteristics of the crack, thereby providing a more accurate assessment. In addition, the sum of the weight coefficients is 1, which ensures the rationality of the calculation results. This comprehensive assessment method not only improves the accuracy of pipeline safety assessment, but also helps to formulate more effective maintenance and repair plans, thereby extending the service life of the pipeline, reducing the risk of accidents, and ensuring the safety and efficiency of industrial production.

[0078] In some embodiments of the present application, calculating the pipeline layering impact value based on the pipeline layering information includes:

[0079] Get the layer area, set the first layer area and the second layer area, and the first layer area is smaller than the second layer area;

[0080] If the layer area is less than or equal to the first layer area, and the layer area is greater than zero, the pipeline layer impact value is the first layer impact value;

[0081] If the layer area is larger than the first layer area and smaller than or equal to the second layer area, the pipeline layer impact value is the second layer impact value;

[0082] If the layer area is larger than the second layer area, the pipeline layer impact value is the third layer impact value;

[0083] Among them, the first layer impact value is smaller than the second layer impact value, and the second layer impact value is smaller than the third layer impact value.

[0084] It can be understood that this method can intuitively reflect the degree of impact of delamination defects on pipeline safety through quantitative assessment of delamination area, and facilitate the rapid judgment of the severity of the defect. Secondly, by setting different delamination area thresholds (first delamination area and second delamination area), the delamination impact value is divided into the first delamination impact value, the second delamination impact value and the third delamination impact value, thereby realizing the hierarchical management of delamination defects and providing a clear decision-making basis for pipeline maintenance. For example, when the delamination area is small, the delamination impact value is low, indicating that the defect has little impact on pipeline safety and may not require immediate treatment; when the delamination area is large, the delamination impact value is high, indicating that the defect has a greater impact on pipeline safety and requires timely repair. This hierarchical assessment method not only improves the scientificity and efficiency of defect management, but also effectively avoids pipeline failure or safety accidents caused by defect accumulation. In addition, this method is simple and easy to implement, applicable to a variety of pipeline types and detection scenarios, and has broad application prospects.

[0085] In some embodiments of the present application, the pipeline deviation value is calculated based on the pipeline thickness information and the pipeline standard thickness information, and the pipeline thickness impact value is calculated based on the pipeline deviation value, including:

[0086] Calculate the pipeline deviation value between the pipeline thickness information and the pipeline standard thickness information, and take the absolute value of the pipeline deviation value to obtain the absolute value of the pipeline deviation;

[0087] Setting a first deviation absolute value and a second deviation absolute value, wherein the first deviation absolute value is smaller than the second deviation absolute value;

[0088] If the absolute value of the pipeline deviation is less than or equal to the absolute value of the first deviation, the pipeline thickness influence value is the first thickness influence value;

[0089] If the absolute value of the pipeline deviation is greater than the absolute value of the first deviation and less than or equal to the absolute value of the second deviation, the pipeline thickness influence value is the second thickness influence value;

[0090] If the absolute value of the pipeline deviation is greater than the absolute value of the second deviation, the pipeline thickness influence value is the third thickness influence value;

[0091] The first thickness influence value is smaller than the second thickness influence value, and the second thickness influence value is smaller than the third thickness influence value.

[0092] In some embodiments of the present application, calculating the pipeline deviation value between the pipeline thickness information and the pipeline standard thickness information includes:

[0093] If the pipeline deviation value is less than zero, it is judged that the pipeline is corroded or worn;

[0094] If the pipeline deviation value is equal to zero, the pipeline is judged to be normal and the pipeline thickness impact value is zero;

[0095] If the pipeline deviation value is greater than zero, it is determined that foreign matter has deposited in the pipeline.

[0096] It is understandable that in some embodiments of the present application, by calculating the deviation value between the pipeline thickness and the standard thickness, it is possible to quickly determine whether the pipeline has problems such as corrosion, wear or foreign matter deposition, providing a scientific basis for the assessment of pipeline health status. Secondly, by dividing the absolute value of the pipeline deviation into different intervals and corresponding to different thickness impact values, a quantitative assessment and hierarchical management of pipeline thickness changes are achieved, which facilitates the rapid identification of potential risks in the pipeline. For example, when the absolute value of the deviation is small, the thickness impact value is low, indicating that the pipeline is in good condition; when the absolute value of the deviation is large, the thickness impact value is high, indicating that the pipeline may have severe corrosion or foreign matter deposition and needs to be dealt with in a timely manner. In addition, this method can further distinguish the type of pipeline problem (such as corrosion, wear or foreign matter deposition) based on the positive and negative values ​​of the deviation value, providing clear guidance for targeted maintenance. This hierarchical assessment method not only improves the efficiency and accuracy of pipeline detection, but also can effectively prevent safety accidents caused by abnormal pipeline thickness, and has broad application prospects.

[0097] In some embodiments of the present application, when determining whether to locate a pipeline defect based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, the following steps are performed:

[0098] The minimum values ​​of the pipeline crack influence value, pipeline delamination influence value and pipeline thickness influence value are set respectively, and recorded as the minimum pipeline crack influence value, the minimum pipeline delamination influence value and the minimum pipeline thickness influence value;

[0099] If any of the pipeline crack impact value, pipeline delamination impact value, and pipeline thickness impact value is greater than or equal to its corresponding minimum value, it is determined that the pipeline defect needs to be located;

[0100] Otherwise, it is determined that there is no need to locate the pipeline defect.

[0101] It is understood that in some embodiments of the present application, when determining whether to locate pipeline defects based on the pipeline crack impact value, pipeline delamination impact value, and pipeline thickness impact value, by setting the pipeline crack impact minimum value, pipeline delamination impact minimum value, and pipeline thickness impact minimum value, intelligent judgment and precise positioning of pipeline defects are achieved, which has significant technical advantages and application value. First, by setting the minimum threshold value of each impact value, the method can quickly screen out defects that have a greater impact on pipeline safety, avoid over-detection of minor defects, and thus improve detection efficiency. Second, when the crack impact value, delamination impact value, or thickness impact value exceeds its corresponding minimum value, the system automatically determines that the defect needs to be located and sends the location information to the remote terminal, realizing the automation and intelligence of defect detection and reducing the need for manual intervention. In addition, the method can perform a comprehensive assessment based on different types of defect impact values ​​(cracks, delamination, thickness) to ensure comprehensive monitoring of the overall safety of the pipeline. This threshold-based judgment mechanism not only improves the accuracy and efficiency of defect location, but also provides a scientific basis for pipeline maintenance, can effectively prevent pipeline failure or safety accidents caused by defect accumulation, and has broad application prospects.

[0102] In some embodiments of the present application, when calculating the comprehensive pipeline defect value based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, the calculation includes:

[0103] The comprehensive defect value of the pipeline is calculated by the following formula:

[0104] Z=α*S1+β*S2+γ*S3;

[0105] In the above formula, Z represents the comprehensive defect value of the pipeline, S1 represents the influence value of the pipeline crack, S2 represents the influence value of the pipeline delamination, S3 represents the influence value of the pipeline thickness, α represents the pipeline crack weight coefficient, β represents the pipeline delamination weight coefficient, and γ represents the pipeline thickness influence coefficient. The value ranges of α, β, and γ are all [0, 1], and α+β+γ=1.

[0106] In some embodiments of the present application, when classifying pipeline defects and performing defect classification warning according to the comprehensive defect value of the pipeline, the process includes:

[0107] Set a comprehensive defect threshold. If the pipeline comprehensive defect value is less than or equal to the comprehensive defect threshold, the defect level is level 1 and a level 1 warning is issued.

[0108] If the pipeline comprehensive defect value is greater than the comprehensive defect threshold and less than or equal to 1.5 times the comprehensive defect threshold, the defect level is level 2 and a level 2 warning is issued;

[0109] If the comprehensive defect value of the pipeline is greater than 1.5 times the comprehensive defect threshold, the defect level is level three and a level three warning is issued.

[0110] It is understandable that by introducing weight coefficients (α, β, γ), the impact of different types of defects (cracks, delamination, thickness) on the comprehensive safety of the pipeline can be flexibly adjusted, making the assessment results more scientific and reasonable. Secondly, by setting a comprehensive defect threshold, the pipeline defect level is divided into level one, level two, and level three, and corresponds to different warning levels, thus realizing quantitative management and graded warning of pipeline defects. For example, when the comprehensive defect value is low, the defect level is level one, indicating that the pipeline is in good condition and only requires level one warning and routine monitoring; when the comprehensive defect value is high, the defect level is level three, indicating that the pipeline has serious defects and requires immediate repair and treatment. This graded warning mechanism not only improves the efficiency and pertinence of pipeline defect management, but also effectively prevents pipeline failure or safety accidents caused by defect accumulation. In addition, this method is simple and easy to implement, applicable to a variety of pipeline types and detection scenarios, provides a scientific basis for pipeline maintenance, and has broad application prospects.

[0111] On the other hand, see Figure 2-3 As shown, the present application also provides a pipeline inner wall defect detection system based on a pipeline robot, which is used to apply the above-mentioned pipeline inner wall defect detection method based on a pipeline robot, including:

[0112] The acquisition module includes a defect detection device 20, a high-definition vision module 30, and an infrared temperature measurement module 40. The defect detection device 20 is fixed to the pipeline robot 10 via a connecting device 50. The high-definition vision module 30 and the infrared temperature measurement module 40 are both located at an end of the pipeline robot 10 away from the defect detection device 20. The acquisition module is configured to collect structural defect information of the pipeline; wherein the structural defect information includes inner surface crack information, internal crack information, pipeline layer information, and pipeline thickness information;

[0113] a data processing module configured to calculate a pipeline crack impact value based on the inner surface crack information and the internal crack information, calculate a pipeline stratification impact value based on the pipeline stratification information, calculate a pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and calculate a pipeline thickness impact value based on the pipeline deviation value;

[0114] a positioning module configured to determine whether to locate the pipeline defect based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, and if it is determined that the pipeline defect needs to be located, send the positioning information and the pipeline crack impact value to the remote terminal;

[0115] The early warning module is configured to calculate the pipeline comprehensive defect value based on the pipeline crack impact value, the pipeline delamination impact value and the pipeline thickness impact value, and classify the pipeline into defect levels and provide defect classification early warning based on the pipeline comprehensive defect value.

[0116] As can be seen, the system integrates ultrasonic phased array technology, a high-definition vision module, and an infrared temperature measurement module through the acquisition module. This allows for comprehensive detection of structural defects on the pipeline's inner wall, including surface cracks, internal cracks, delamination defects, and thickness information, significantly improving detection accuracy and comprehensiveness. Secondly, the data processing module calculates the impact values ​​of pipeline cracks, delamination, and thickness, quantifying the impact of different defect types on pipeline safety and providing a scientific basis for defect assessment. The positioning module determines whether defects need to be located based on the impact values ​​and transmits the location information to a remote terminal, enabling precise defect location and remote monitoring. The early warning module calculates the pipeline's comprehensive defect value, classifies defects, and issues graded early warnings, providing clear decision-making support for pipeline maintenance. This system not only avoids the high risks of manual operation but also improves detection efficiency and safety, making it particularly suitable for complex environments such as non-metallic PE pipelines. Through the collaborative operation of multiple modules, the system achieves intelligent, automated, and efficient pipeline defect detection, providing reliable assurance for safe pipeline operation and possessing significant engineering application value.

[0117] Specifically, the pipeline robot 10 includes a fuselage trunk 11, a front connecting arm 12, a rear connecting arm 13, a first ball wheel 14, a second ball wheel 15 and an omnidirectional wheel 16, wherein the front connecting arm 12 is arranged at one end of the fuselage trunk, and the front connecting arm 12 is rotatably connected to the fuselage trunk 11, the rear connecting arm 13 is arranged at the end of the fuselage trunk 11 away from the front connecting arm 12, and a connecting device 50 is arranged on the rear connecting arm 13, the end of the front connecting arm 12 away from the fuselage trunk 11 is connected to the first ball wheel 14, the end of the rear connecting arm 13 away from the fuselage trunk 11 is connected to the second ball wheel 15, and at least four omnidirectional wheels 16 are provided, and the omnidirectional wheels 16 are arranged on both sides of the two ends of the fuselage trunk 11.

[0118] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0120] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A pipeline inner wall defect detection method based on a pipeline robot, characterized in that: include: Collecting structural defect information of the pipeline; wherein the structural defect information includes inner surface crack information, internal crack information, pipeline layer information and pipeline thickness information; Calculate the pipeline crack impact value based on the inner surface crack information and the internal crack information: obtain the crack length value, crack depth value, and crack width value of each inner surface crack and internal crack, set the crack length threshold, crack depth threshold, and crack width threshold, and calculate the pipeline crack impact value using the following formula: In the above formula, S1 represents the impact value of pipeline crack, Li represents the crack length value of the i-th crack, Lmax represents the crack length threshold, Di represents the crack depth value of the i-th crack, Dmax represents the crack depth threshold, Wi represents the crack width value of the i-th crack, Wmax represents the crack width threshold, a represents the crack length value weight coefficient, b represents the crack depth value weight coefficient, c represents the crack width value weight coefficient, di represents the crack position weight coefficient of the i-th crack, and n represents the total number of cracks. Among them, the value ranges of a, b and c are all [0, 1], the value range of di is (0, 1], and a+b+c=1, i=1,2,3,…,n; Calculating a pipeline stratification impact value according to the pipeline stratification information: obtaining a stratification area, setting a first stratification area and a second stratification area, wherein the first stratification area is smaller than the second stratification area; if the stratification area is smaller than or equal to the first stratification area and greater than zero, the pipeline stratification impact value is the first stratification impact value; if the stratification area is larger than the first stratification area and smaller than or equal to the second stratification area, the pipeline stratification impact value is the second stratification impact value; if the stratification area is larger than the second stratification area, the pipeline stratification impact value is the third stratification impact value; wherein the first stratification impact value is smaller than the second stratification impact value, and the second stratification impact value is smaller than the third stratification impact value; Calculating a pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and calculating a pipeline thickness impact value based on the pipeline deviation value: calculating the pipeline deviation value between the pipeline thickness information and the pipeline standard thickness information, and taking the absolute value of the pipeline deviation value to obtain the pipeline deviation absolute value; setting a first deviation absolute value and a second deviation absolute value, wherein the first deviation absolute value is less than the second deviation absolute value; if the pipeline deviation absolute value is less than or equal to the first deviation absolute value, the pipeline thickness impact value is the first thickness impact value; if the pipeline deviation absolute value is greater than the first deviation absolute value and less than or equal to the second deviation absolute value, the pipeline thickness impact value is the second thickness impact value; if the pipeline deviation absolute value is greater than the second deviation absolute value, the pipeline thickness impact value is the third thickness impact value; the first thickness impact value is less than the second thickness impact value, and the second thickness impact value is less than the third thickness impact value; wherein, when calculating the pipeline deviation value between the pipeline thickness information and the pipeline standard thickness information, the following steps are included: if the pipeline deviation value is less than zero, determining that the pipeline is corroded or worn; if the pipeline deviation value is equal to zero, determining that the pipeline is normal and the pipeline thickness impact value is zero; if the pipeline deviation value is greater than zero, determining that foreign matter deposition has occurred in the pipeline; determining whether to locate the pipeline defect based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, respectively; and if it is determined that the pipeline defect needs to be located, sending the location information and the pipeline crack impact value to a remote terminal; The pipeline comprehensive defect value is calculated according to the pipeline crack impact value, the pipeline delamination impact value and the pipeline thickness impact value, and the pipeline defect level is classified and the defect classification warning is performed according to the pipeline comprehensive defect value.

2. The pipeline inner wall defect detection method based on the pipeline robot according to claim 1 is characterized in that: The collecting of structural defect information of the pipeline includes: The ultrasonic phased array probe is used to scan the inner wall of the pipeline, transmit ultrasonic waves and receive reflected signals. By analyzing the amplitude, time and phase changes of the reflected signals, the inner surface crack information, internal crack information, pipeline layer information and pipeline thickness information of the inner wall of the pipeline are identified; The image data of the inner wall of the pipeline is collected by a high-definition camera, and the inner surface crack information of the inner wall of the pipeline is identified based on image processing to supplement the inner surface crack information; The infrared temperature measurement module collects three-dimensional temperature field data of the inner wall of the pipeline, identifies local temperature abnormality areas, and generates thermal imaging maps to supplement the inner surface crack information and obtain the final structural defect information.

3. The pipeline inner wall defect detection method based on the pipeline robot according to claim 2 is characterized in that: The determining whether to locate the pipeline defect according to the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value respectively includes: The minimum values ​​of the pipeline crack impact value, pipeline delamination impact value and pipeline thickness impact value are set respectively, and recorded as the minimum pipeline crack impact value, the minimum pipeline delamination impact value and the minimum pipeline thickness impact value; If any of the pipeline crack impact value, pipeline delamination impact value, and pipeline thickness impact value is greater than or equal to its corresponding minimum value, it is determined that the pipeline defect needs to be located; Otherwise, it is determined that there is no need to locate the pipeline defect.

4. The pipeline inner wall defect detection method based on the pipeline robot according to claim 3 is characterized in that: The calculation of the pipeline comprehensive defect value based on the pipeline crack impact value, the pipeline delamination impact value and the pipeline thickness impact value includes: The comprehensive defect value of the pipeline is calculated by the following formula: Z=α*S1+β*S2+γ*S3; In the above formula, Z represents the comprehensive defect value of the pipeline, S1 represents the influence value of the pipeline crack, S2 represents the influence value of the pipeline delamination, S3 represents the influence value of the pipeline thickness, α represents the pipeline crack weight coefficient, β represents the pipeline delamination weight coefficient, and γ represents the pipeline thickness influence coefficient. The value ranges of α, β, and γ are all [0, 1], and α+β+γ=1.

5. The pipeline inner wall defect detection method based on the pipeline robot according to claim 4 is characterized in that: The defect classification and defect classification warning of the pipeline according to the comprehensive defect value of the pipeline include: Set a comprehensive defect threshold. If the pipeline comprehensive defect value is less than or equal to the comprehensive defect threshold, the defect level is level one and a level one warning is issued. If the pipeline comprehensive defect value is greater than the comprehensive defect threshold and less than or equal to 1.5 times the comprehensive defect threshold, the defect level is level 2 and a level 2 warning is issued; If the comprehensive defect value of the pipeline is greater than 1.5 times the comprehensive defect threshold, the defect level is level three and a level three warning is issued.

6. A pipeline inner wall defect detection system based on a pipeline robot, used for applying the pipeline inner wall defect detection method based on a pipeline robot according to any one of claims 1 to 5, characterized in that: include: An acquisition module includes a defect detection device, a high-definition vision module, and an infrared temperature measurement module. The defect detection device is fixed to the pipeline robot via a connecting device. The high-definition vision module and the infrared temperature measurement module are both arranged at an end of the pipeline robot away from the defect detection device. The acquisition module is configured to acquire structural defect information of the pipeline; wherein the structural defect information includes inner surface crack information, internal crack information, pipeline layer information, and pipeline thickness information; a data processing module configured to calculate a pipeline crack impact value based on the inner surface crack information and the internal crack information, calculate a pipeline stratification impact value based on the pipeline stratification information, calculate a pipeline deviation value based on the pipeline thickness information and the pipeline standard thickness information, and calculate a pipeline thickness impact value based on the pipeline deviation value; a positioning module configured to determine whether to locate the pipeline defect based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, and if it is determined that the pipeline defect needs to be located, send positioning information and the pipeline crack impact value to a remote terminal; The early warning module is configured to calculate a comprehensive pipeline defect value based on the pipeline crack impact value, the pipeline delamination impact value, and the pipeline thickness impact value, and to classify the pipeline into defect levels and provide defect classification early warning based on the comprehensive pipeline defect value.

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