Stress monitoring system for self-weight sinking of oil and gas pipeline

Abstract

The invention discloses a stress monitoring system for self-weight sinking of an oil and gas pipeline. The stress monitoring system comprises an unmanned aerial vehicle loaded with a camera, the oil and gas pipeline provided with a visual identification target, a reference target group and a computer. Horizontal and vertical targets are arranged on the oil and gas pipeline in the length direction of the oil and gas pipeline and used for measuring the space displacement of the pipeline in the sinking process. The reference target group is fixed on the ground and serves as a space positioning reference. The unmanned aerial vehicle shoots data containing target images in the sinking construction process and transmits the data to the computer for image recognition and coordinate reconstruction, the real-time three-dimensional space displacement of each target is extracted, and stress distribution of the pipeline is calculated through a mechanical model. When the maximum stress exceeds a preset threshold value, the system sends out an alarm signal to prompt constructors to take control measures. The system has non-contact, high-flexibility and wide-area coverage capabilities, can realize real-time dynamic monitoring of pipeline stress under the condition of not influencing on-site construction, and has the advantages of simplicity and convenience in installation, lower cost and strong anti-interference capability.

Description

Technical Field

[0001] The present invention uses a camera mounted on a drone to measure the displacement of an oil and gas pipeline when it sinks under its own weight, thereby calculating the stress of the oil and gas pipeline in real time, and belongs to the field of structural health monitoring. Background Art

[0002] The typical method for installing oil and gas pipelines is to first dig a trench, use crane equipment to lower the pipeline into the trench, and then make connections at the bottom of the trench. A newer installation method eliminates trenching altogether and instead connects the pipelines on the ground. The soil beneath the pipelines is then gradually excavated, allowing the pipelines to sink under their own weight. This new installation method offers two advantages: it eliminates the need for cranes, and it facilitates construction by making connections between the pipelines on the surface rather than at the bottom of the trench.

[0003] In the installation method of sinking oil and gas pipelines by their own weight, as the underlying soil is gradually excavated, the pipeline slowly sinks under its own weight and eventually falls into the predetermined position. While this method simplifies the construction process, reduces reliance on lifting equipment, and improves the convenience of ground connection operations, it also introduces new structural safety issues. Due to the inherent rigidity of the pipeline, its support state constantly changes during the sinking process, which can easily form overhanging sections or unevenly stressed areas in certain locations, causing localized bending, deformation, and even damage to the pipeline.

[0004] Existing stress monitoring methods typically rely on strain gauges, fiber optic sensors, or distributed sensing technologies such as BOTDA installed on pipelines. While these methods can achieve highly accurate stress or strain monitoring, they suffer from complex installation, high costs, and poor adaptability to construction sites. This is particularly challenging in large, long-distance construction sites, where sensor cables are difficult to lay. Furthermore, these methods are easily affected by construction activities, leading to distortion or interruption of monitoring data.

[0005] Therefore, a new, non-contact monitoring method with wide coverage, flexible deployment, and dynamic acquisition of pipeline stress information is urgently needed to meet the technical requirements of the self-sinking installation process. Drones equipped with camera systems and combined with image processing technology can efficiently capture spatial displacement data of oil and gas pipelines during construction, making it possible to calculate pipeline stress based on geometric changes, offering a new approach to solving this problem. Summary of the Invention

[0006] The technical problem to be solved by the present invention is that in projects where oil and gas pipelines are installed using the deadweight sinking technology, there is a lack of means for real-time, economical and accurate monitoring of the stress of the oil and gas pipelines.

[0007] To achieve the above-mentioned object, the present invention adopts the following technical solution: a stress monitoring system for the self-weight sinking of an oil and gas pipeline, comprising a drone equipped with a camera, an oil and gas pipeline provided with a visual recognition target, a reference target group, and a computer;

[0008] The oil and gas pipeline is provided with a visual recognition target for measuring horizontal displacement at the 12 o'clock direction of the cross section at regular intervals, referred to as a horizontal target for short, and a visual recognition target for measuring vertical displacement at the 3 o'clock or 9 o'clock direction of the cross section, referred to as a vertical target for short; the 12 o'clock direction corresponds to the top end of the pipeline cross section, the 6 o'clock direction corresponds to the bottom end of the pipeline cross section, and the 3 o'clock and 9 o'clock directions are located exactly in the middle of the 12 o'clock and 6 o'clock directions on the outer surface of the pipeline;

[0009] The reference target group is set at a fixed position next to the oil and gas pipeline and remains stationary during the sinking process of the oil and gas pipeline. The reference target group is composed of equal to or more than three visual recognition targets to determine a stable spatial reference plane, thereby improving the system's measurement accuracy of the spatial displacement changes of the oil and gas pipeline;

[0010] The drone's camera collects image data of horizontal targets, vertical targets, and a reference target group in real time, and transmits it to a computer via Wi-Fi for processing. This data provides the real-time horizontal and vertical displacements of the oil and gas pipeline, which are then further calculated to determine the stress distribution of the pipeline. When the stress exceeds a threshold, an alarm is triggered, prompting on-site construction personnel to take emergency measures such as slowing down the sinking speed or temporarily suspending work.

[0011] The horizontal target, vertical target, and reference target group are preferably high-contrast QR codes or dot array structures, with patterns that are anti-fouling and anti-reflective, and are sprayed or pasted on the surface of oil and gas pipelines. After special treatment, they can adapt to high temperatures, rain, dust, and other factors in open-air construction environments.

[0012] The computer is equipped with an image processing module, a spatial coordinate reconstruction module and a stress calculation module;

[0013] The oil and gas pipeline that participates in the self-weight sinking part is between 20m and 200m;

[0014] Preferably, the horizontal targets and vertical targets are arranged at intervals of 0.1m to 2m in the length direction of the oil and gas pipeline;

[0015] Preferably, the drone has a four-rotor structure, has autonomous flight control capabilities and image stabilization functions, and can hover stably and take clear images in a field construction environment with a wind speed not exceeding level 5;

[0016] Preferably, the camera is an industrial-grade camera with a wide-angle lens and high resolution (not less than 4K), which can be combined with an image enhancement algorithm to improve recognition accuracy under complex lighting conditions.

[0017] The beneficial effects of the present invention are: non-contact, real-time monitoring of the stress distribution of oil and gas pipelines during their self-weight sinking process is achieved through drones equipped with cameras, with the advantages of flexible deployment, wide coverage, and low cost; the system uses high-precision visual recognition targets and image processing technology to promptly alarm when stress exceeds the standard, thereby ensuring construction safety and pipeline structural integrity. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of the system of the present invention when the oil and gas pipeline is not sunk at the beginning;

[0019] Figure 2 A schematic diagram of the system during the sinking process of the oil and gas pipeline of the present invention;

[0020] Figure 3 Schematic diagram of the cross section of the oil and gas pipeline.

[0021] The meanings of the marks in the accompanying drawings are as follows: 1. Oil and gas pipeline, 2. Horizontal target, 3. Vertical target, 4. Reference target group, 5. UAV, 6. Computer. Specific implementation plan

[0022] The present invention will be described in further detail below with reference to the accompanying drawings.

[0023] Figure 1 This is a schematic diagram of the system with the oil and gas pipeline initially unsunk. Oil and gas pipeline 1 is placed on the ground, and the soil has not yet been excavated. Horizontal targets 2 are set at the 12 o'clock direction of the oil and gas pipeline, and vertical targets 3 are set at the 3 o'clock direction. Horizontal targets 2 and vertical targets 3 are aligned in pairs on the same cross-section of the oil and gas pipeline, with a constant distance Δx along the length. A reference target group 4 is placed at a fixed position next to the oil and gas pipeline, containing three or more visual recognition targets. Drone 5 captures aerial images of horizontal targets 2, vertical targets 3, and reference target group 4, and transmits them to computer 6 via Wi-Fi. The image processing module and spatial coordinate reconstruction module in computer 6 calculate the initial spatial coordinates of the n horizontal targets 2 and n vertical targets 3.

[0024] Figure 2 The diagram below is a schematic diagram of the system during the sinking of the oil and gas pipeline. The ground soil is gradually excavated, and the oil and gas pipeline 1 sinks due to its own weight. Due to the influence of on-site construction, the oil and gas pipeline 1 not only has vertical displacement but also horizontal displacement, so it is necessary to measure the displacement of the vertical target 3 and the horizontal target 2 at the same time. At a certain moment, the real-time spatial coordinates of n horizontal targets 2 and n vertical targets 3 are obtained by the image captured by the drone 5 and processed by the computer 6. After processing by the spatial coordinate reconstruction module in the computer 6, the horizontal displacement of the i-th (i=1,2,3,...,n) horizontal target 2 is obtained as u i, the vertical displacement of the i-th vertical target 3 is v i . byu i 、v i Calculate the horizontal curvature and vertical curvature, respectively denoted as κ 1i and κ 2i . Under small deformation, κ 1i and κ 2i It can be calculated approximately by Matlab's gradient function. 1i ]=[κ 11 ,κ 12 ,...κ 1n ],[κ 2i ]=[κ 21 ,κ 22 ,...κ 2n ],[u i ]=[u1,u2,...u n ],[v i ]=[v1,v2,...v n ],[x i ]=[0,Δx,2Δx,...(n-1)Δx]. byu i Calculate κ 1i The method is [κ 1i ]=gradient(gradient([u i ],[x i ]),[x i ]); by v i Calculate κ 2i The method is [κ 2i ]=gradient(gradient([v i ],[x i ]),[x i ]). The bending stresses of the oil and gas pipeline 1 in the horizontal and vertical directions are:

[0025] σ 1i =E Y Rκ 1i Formula (1)

[0026] σ 2i =E Y Rκ 2i Formula (2)

[0027] In formula (1) and formula (2), σ 1i is the horizontal bending stress at the i-th horizontal target 2, σ 2i is the vertical bending stress at the i-th vertical target 3, E Yand R are the Young's modulus and external radius of the oil and gas pipeline 1, respectively. Ignoring the uniform axial stretching of the oil and gas pipeline 1 and only considering the stress caused by bending, the total stress of the oil and gas pipeline 1 during the sinking process is:

[0028]

[0029] When σ i When the maximum value exceeds the threshold, an alarm is issued and on-site construction personnel take emergency measures such as slowing down the sinking speed or temporarily stopping work.

[0030] The image processing module in computer 6 is primarily responsible for identifying and extracting the positions of individual targets from images captured by drone 5. Because targets have high-contrast structures (such as QR codes or dot arrays), the image processing module can accurately identify horizontal, vertical, and reference targets in the image through computer vision algorithms such as template matching, edge detection, or feature point recognition. This module also integrates image preprocessing processes, such as brightness equalization, denoising, and perspective correction, to improve recognition accuracy under varying lighting and angle conditions. After completing target recognition, computer 6 inputs the two-dimensional image coordinates into the spatial coordinate reconstruction module. This module first establishes a stable three-dimensional coordinate reference system based on the reference targets. By applying known distance constraints to the spatial geometric relationships between three or more reference targets, the system can calculate the transformation matrix between image coordinates and world coordinates. Furthermore, using the camera's intrinsic parameters (such as focal length, principal point position, and distortion parameters) and extrinsic parameters (position and attitude relative to the reference coordinate system), the spatial coordinate reconstruction module performs three-dimensional positioning of each horizontal and vertical target, obtaining its real-time spatial coordinates in the world coordinate system.

[0031] To minimize the impact of errors, Computer 6 also incorporates an image verification mechanism that automatically removes frames with blur, target obstruction, or low recognition confidence, ensuring the continuity and reliability of displacement data. Furthermore, the system features data caching and playback capabilities, enabling visual analysis of historical displacement trajectories and stress evolution trends during pipeline sinking.

[0032] The above describes the specific embodiments of the present invention, but the present invention is not limited to the specific embodiments described above. Those skilled in the art may make various changes in form and details within the scope of the claims, which will not affect the essence of the present invention.

Claims

1. A stress monitoring system for oil and gas pipeline sinking due to its own weight, characterized in that: include: An oil and gas pipeline equipped with visual identification targets, wherein the oil and gas pipeline is provided with horizontal targets for measuring horizontal displacement at regular intervals at the 12 o'clock direction of the cross section, and vertical targets for measuring vertical displacement at the 3 o'clock or 9 o'clock direction of the cross section; A reference target set located at a fixed position, comprising at least three visual recognition targets; A drone equipped with a camera, wherein the camera is used to capture and identify horizontal targets, vertical targets, and reference target groups; A computer that communicates with the drone includes an image processing module, a spatial coordinate reconstruction module, and a stress calculation module. The computer is used to process image data from the camera, calculate the stress distribution of the oil and gas pipeline during its sinking process, and issue an alarm when the stress exceeds a threshold.

2. The system according to claim 1, wherein: The horizontal target, vertical target, and reference target group are preferably high-contrast two-dimensional codes or dot array structures, have anti-fouling and anti-reflective properties, and are fixed on the surface of the pipeline.

3. The system according to claim 1, wherein: The reference target group is located on stable ground at a certain distance from the pipeline and remains stationary during the sinking process to serve as a reference benchmark for image space coordinate reconstruction.

4. The system according to claim 1, wherein: The image processing module includes edge detection, feature extraction, template matching and other algorithms, which are used to accurately identify the position of the visual target in the image.

5. The system according to claim 1, wherein: The spatial coordinate reconstruction module calculates the three-dimensional coordinates of each target on the oil and gas pipeline in the world coordinate system based on the geometric relationship between multiple reference targets, camera internal parameters and external parameters.

6. The system according to claim 1, wherein: The stress calculation module processes the displacement data to calculate the bending stress in the horizontal and vertical directions.

7. The system according to claim 1, wherein: The drone is a four-rotor aircraft with image stabilization control and automatic hovering functions, and is suitable for outdoor environments with wind speeds not exceeding level 5.

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