Submarine pipeline burial depth acquisition method and electronic equipment

Abstract

The invention provides a method for acquiring the burial depth of a subsea pipeline. The method comprises the following steps: acquiring point cloud data of the pipeline; determining the position and height of the pipe top elevation according to the point cloud data; determining the height of a natural mud surface according to the position of the pipe top elevation; and determining the burial depth of the pipeline according to the height of the pipe top elevation and the height of the natural mud surface. According to the scheme provided by the invention, manual intervention is not needed, the burial depth change of the pipeline can be reflected comprehensively in real time through automatic calculation and optimization, the measurement efficiency and precision are remarkably improved, personal errors are reduced, and more reliable technical support is provided for monitoring and maintenance of the submarine pipeline.

Description

Technical Field

[0001] The present invention relates to the field of ocean surveying and mapping, and in particular to a method for acquiring the buried depth of a submarine pipeline and electronic equipment. Background Art

[0002] During the laying of submarine pipelines, the submarine pipelines must first be sunk to the designed position, and the trenches that meet the design specifications must be flushed out under the pipelines using the high-pressure water flushing of the trencher. The pipelines then sink into the trenches by their own gravity. During the pipeline laying process, it is crucial to know whether the buried depth of the pipelines meets the design requirements. Traditionally, the buried depth is obtained by the cross-section method, which calculates the buried depth of the pipeline based on the positional relationship between the pipe top elevation and the natural mud surface. This method usually requires manual judgment of the pipe top elevation and extraction one by one, followed by finding and comparing the natural mud surface height at the corresponding position for calculation.

[0003] However, the traditional cross-section method is cumbersome and inefficient, and is limited by manual judgment, which may result in large measurement errors. More importantly, this method can only reflect the burial depth of a small section of the pipeline, and cannot accurately and comprehensively reflect the burial depth of the entire pipeline. Therefore, in a complex seabed environment, such as large changes in water depth, strong flow velocity, uneven bottom quality and other factors, the accuracy and efficiency of the traditional method are difficult to be effectively guaranteed.

[0004] The existing technology lacks a solution that can quickly, accurately and fully monitor the buried depth of submarine pipelines. Especially in complex environments, the existing technology generally faces problems such as complex operation, incomplete data, and unstable measurement accuracy. Therefore, a new method is urgently needed to effectively overcome the above limitations and improve the accuracy and efficiency of submarine pipeline buried depth measurement. Summary of the invention

[0005] The embodiments of the present application provide a method and electronic equipment for obtaining the buried depth of a submarine pipeline, which solves the problem of quickly finding and obtaining the elevation of the top of the submarine pipeline, and the problem of quickly finding and comparing the elevation of the top of the pipeline and the natural mud surface point at the corresponding position, and finally quickly obtains the buried depth of the submarine pipeline.

[0006] An embodiment of the present application provides a method for obtaining the buried depth of a submarine pipeline, comprising the following steps: obtaining point cloud data of the pipeline; determining the position and height of the pipe top elevation based on the point cloud data; determining the height of the natural mud surface based on the position of the pipe top elevation; and determining the buried depth of the pipeline based on the height of the pipe top elevation and the height of the natural mud surface.

[0007] In one embodiment, the point cloud data includes pipeline upper point cloud data; determining the position and height of the pipe top elevation based on the point cloud data includes: screening the pipeline upper point cloud data that meets the first preset condition as denoised pipeline upper point cloud data by automatically adjusting the weight; determining the pipeline lower point cloud data based on the size of the pipeline and the denoised pipeline upper point cloud data; determining the pipeline three-dimensional model based on the pipeline lower point cloud data and the denoised pipeline upper point cloud data; and slicing the pipeline three-dimensional model to determine the position and height of the pipe top elevation.

[0008] In one embodiment, the step of obtaining the point cloud data of the pipeline includes: obtaining a three-dimensional image of the pipeline using three-dimensional sonar equipment; converting the three-dimensional image into initial point cloud data; and selecting initial point cloud data that meets a second preset condition as the point cloud data according to the reflection intensity of the pipeline. In one embodiment, the step of determining the point cloud data of the lower part of the pipeline according to the size of the pipeline and the denoised point cloud data of the upper part of the pipeline includes: determining an interpolation coefficient according to the size of the pipeline and the denoised point cloud data of the upper part of the pipeline; and determining the point cloud data of the lower part of the pipeline according to the interpolation coefficient by using a spline interpolation method.

[0009] In one embodiment, determining the pipeline three-dimensional model based on the pipeline lower point cloud data and the denoised pipeline upper point cloud data includes: using the least squares method to match the pipeline lower point cloud data and the denoised pipeline upper point cloud data with a white model to obtain the best matching pipeline lower point cloud data and the denoised pipeline upper point cloud data; determining the pipeline three-dimensional model based on the best matching pipeline lower point cloud data and the denoised pipeline upper point cloud data; wherein the white model is a standard pipeline three-dimensional model constructed based on the size of the pipeline.

[0010] In one embodiment, slicing the pipeline three-dimensional model to determine the position and height of the pipe top elevation includes: slicing the pipeline three-dimensional model to obtain multiple nearly circular slices; for each nearly circular slice, performing the following operations: making multiple tangents to the nearly circular slice to obtain multiple tangent points; extracting the position and height of each tangent point, and selecting the top three tangent points in height; calculating the curvature of the arc formed by the three tangent points; if the curvature is less than a preset curvature, selecting the position and height of the tangent point with the highest height among the three tangent points as the position and height of the pipe top elevation.

[0011] In one embodiment, slicing the pipeline three-dimensional model to obtain a plurality of nearly circular slices includes: determining a slice spacing according to the shape of the pipeline; and slicing the pipeline three-dimensional model according to the slice spacing to obtain a plurality of nearly circular slices.

[0012] In one embodiment, determining the height of the natural mud surface based on the position of the pipe top elevation includes: using a multi-beam depth sounding system to obtain three-dimensional terrain data of the natural mud surface; performing three-dimensional modeling on the three-dimensional terrain data to obtain a three-dimensional model of the mud surface; arranging the pipe top elevation on the three-dimensional model of the mud surface, and circling multiple height data of the three-dimensional model of the mud surface with the position of the pipe top elevation as the center and a preset radius as the radius; and calculating the average value of the multiple height data as the height of the natural mud surface.

[0013] In one embodiment, the buried depth of the pipeline is determined according to the height of the pipe top elevation and the height of the natural mud surface, including: calculating the difference between the height of the pipe top elevation and the height of the natural mud surface as the initial buried depth of the pipeline; and determining the buried depth of the pipeline according to the initial pipeline buried depth and minimizing the error.

[0014] An embodiment of the present application further provides an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the above-mentioned method for obtaining the buried depth of a submarine pipeline.

[0015] The solution provided in the above-mentioned embodiments of the present application can reflect the changes in the buried depth of the pipeline in real time and comprehensively through automated calculation and optimization without the need for human intervention, significantly improve measurement efficiency and accuracy, reduce human errors, and provide more reliable technical support for submarine pipeline monitoring and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the embodiments of the present application, the drawings required for use in the embodiments of the present application are briefly introduced below.

[0017] Figure 1 is a schematic diagram of a submarine pipeline provided in an embodiment of the present application; Figure 2 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application; Figure 3 It is a flow chart of a method for obtaining the buried depth of a submarine pipeline provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0019] Similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0020] Figure 1 Schematic diagram of the submarine pipeline provided in the embodiment of the present application. Figure 1 In the pipeline, the submarine pipeline is buried below the natural mud surface. The pipe top elevation is a point on the submarine pipeline, and there can be multiple pipe top elevations. For example, on the submarine pipeline, a pipe top elevation is determined at each interval. Taking any pipe top elevation A as an example, the position B of the natural mud surface corresponding to the position can be determined according to the position of the pipe top elevation, and the position C of the sea level corresponding to the position can also be determined. The height of the pipe top elevation is the distance from the position of the pipe top elevation to the corresponding sea level position (that is, AC), the height of the natural mud surface is the distance from the position of the corresponding natural mud surface to the position of the corresponding sea level (that is, BC), and the pipeline burial depth is the distance from the position of the pipe top elevation to the corresponding natural mud surface position (that is, AB). Since the natural mud surface is not a smooth plane, and the shape and size of the submarine pipeline at different positions on the seabed may be different, the pipeline burial depth at different positions of the submarine pipeline may be different. Generally, multiple pipe top elevations are required to obtain a more accurate pipeline burial depth.

[0021] In related technologies, the buried depth of pipelines is mostly obtained by the cross-section method, which calculates the buried depth of pipelines based on the positional relationship between the pipe top elevation and the natural mud surface. This method usually requires manual judgment of the pipe top elevation and extraction one by one, and then searching and comparing the natural mud surface height at the corresponding position for calculation. However, the cross-section method is cumbersome and inefficient, and is limited by manual judgment, which may result in large measurement errors. More importantly, this method can only reflect the buried depth of a small section of the pipeline, and cannot accurately and comprehensively reflect the buried depth status of the entire pipeline. Therefore, in a complex seabed environment, under the influence of factors such as large changes in water depth, strong flow velocity, and uneven bottom quality, the accuracy and efficiency of traditional methods are difficult to be effectively guaranteed.

[0022] In order to solve the above problems, the embodiment of the present application provides a method for obtaining the buried depth of a submarine pipeline, including obtaining point cloud data of the pipeline; determining the position and height of the pipe top elevation according to the point cloud data; determining the height of the natural mud surface according to the position of the pipe top elevation; and determining the buried depth of the pipeline according to the height of the pipe top elevation and the height of the natural mud surface. This method does not require human intervention, and through automated calculation and optimization, it can reflect the changes in the buried depth of the pipeline in real time and comprehensively, significantly improve measurement efficiency and accuracy, reduce human errors, and provide more reliable technical support for submarine pipeline monitoring and maintenance.

[0023] Figure 2 1 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 100 can be used to execute the method for obtaining the buried depth of a submarine pipeline provided in an embodiment of the present application. Figure 1As shown, the electronic device 100 includes: one or more processors 102, and one or more memories 104 storing processor executable instructions. The processor 102 is configured to execute the method for obtaining the buried depth of a submarine pipeline provided in the following embodiment of the present application.

[0024] The processor 102 can be a gateway, a smart terminal, or a device including a central processing unit (CPU), a graphics processing unit (GPU), or other forms of processing units with data processing capabilities and / or instruction execution capabilities. It can process data of other components in the electronic device 100 and control other components in the electronic device 100 to perform desired functions.

[0025] The memory 104 may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 102 may run the program instructions to implement the method for obtaining the buried depth of the submarine pipeline described below. Various applications and various data may also be stored in the computer-readable storage medium, such as various data used and / or generated by the application.

[0026] In one embodiment, Figure 1 The electronic device 100 shown may also include an input device 106, an output device 108, and a data acquisition device 110, which are interconnected via a bus system 112 and / or other forms of connection mechanisms (not shown). Figure 1 The components and structures of the electronic device 100 shown are merely exemplary and non-limiting. The electronic device 100 may also have other components and structures as required.

[0027] The input device 106 may be a device for a user to input instructions, and may include one or more of a keyboard, a mouse, a microphone, a touch screen, etc. The output device 108 may output various information (e.g., images or sounds) to the outside (e.g., a user), and may include one or more of a display, a speaker, etc. The data acquisition device 110 may acquire a three-dimensional image of a submarine pipeline, and store the acquired data in the memory 104 for use by other components. Exemplarily, the data acquisition device 110 may be a three-dimensional sonar device.

[0028] In one embodiment, the various components in the example electronic device 100 for implementing the method for obtaining the buried depth of a submarine pipeline of the embodiment of the present application may be integrated or dispersed, such as integrating the processor 102, the memory 104, the input device 106 and the output device 108 into one, while separating the data acquisition device 110.

[0029] In one embodiment, the example electronic device 100 for implementing the method for obtaining the buried depth of a submarine pipeline according to an embodiment of the present application may be implemented as an intelligent terminal such as a smart phone, a tablet computer, a desktop computer, a server, a vehicle-mounted device, or the like.

[0030] Figure 3 FIG. 1 is a flow chart of a method for obtaining the buried depth of a submarine pipeline according to an embodiment of the present application. Figure 3 As shown, the method includes the following steps 210-240.

[0031] Step 210: Acquire point cloud data of the pipeline.

[0032] Point cloud data refers to a set of vectors in a three-dimensional coordinate system. Each point contains at least three coordinate information (X, Y, Z), which is used to accurately describe the geometric shape of the object surface. Three-dimensional sonar equipment can be used to obtain high-definition three-dimensional images of the upper part of the submarine pipeline. High-definition three-dimensional images can be obtained by setting the optimal values ​​of acquisition parameters. The acquisition parameters include operating frequency, beam angle, gain value, sensitivity, noise suppression degree, reflection intensity threshold, etc. There is a mutual gain or mutual inhibition effect between the various parameters, and they have different reflections in different water depths, turbidity, flow rates and other environments. The acquired high-definition three-dimensional images are converted into point cloud data of the pipeline for processing.

[0033] Step 210 may specifically include steps 2101 to 2103 .

[0034] Step 2101: Use three-dimensional sonar equipment to obtain a three-dimensional image of the pipeline.

[0035] Regarding the process of acquiring a three-dimensional image of a pipeline, this application describes how to optimize image quality by using adjusted parameters through a simplified model based on optimization of sound wave propagation and reflection intensity (referred to as the sound wave model).

[0036] Relationship between the acoustic wave propagation model and image quality: The acoustic wave propagation model is used to estimate the signal strength, which is directly related to the clarity of the image. The propagation and reflection strength of the signal are affected by a variety of environmental factors and acquisition parameters. The main influencing factors include: Working frequency 𝑓: The higher the frequency, the higher the resolution, but the poorer the penetration; conversely, the lower the frequency, the stronger the penetration, but the lower the resolution. Beam angle 𝜃: The smaller the beam angle, the more concentrated the signal can be obtained, the higher the image resolution, but the coverage range is reduced. Gain value 𝐺: The gain value affects the intensity of the echo. Too high a gain may increase noise, while too low a gain may result in a weak signal. Sensitivity 𝑆: Sensitivity determines the response of the receiving system to weak signals. Too low a sensitivity will make the image blurred.

[0037] The relationship between acquisition parameters and reflection intensity is described by the formula as follows:

[0038] in, I echo is the reflection intensity, which reflects the quality of the image, P transmit is the power emitted by the sound source, is the acoustic reflection coefficient of the target object, G is the gain value, S is the sensitivity, T is the distance from the target to the receiver, 𝑓(𝜃) is the functional relationship between the beam angle 𝜃 and the operating frequency 𝑓.

[0039] Basic relationship between operating frequency 𝑓 and beam angle 𝜃: Operating frequency 𝑓 and beam angle 𝜃 play different roles in sonar systems. Although they are usually independent control parameters, they have a mutual influence on reflection intensity and image quality during sound wave propagation. High frequency and small beam angle: In the case of high frequencies, since sound waves have a higher energy density, when the beam angle is smaller (narrower beam), the sound waves will be focused on a small area, providing higher resolution and clearer images. Low frequency and large beam angle: In the case of low frequencies, when the beam angle is larger, the sound wave energy is dispersed to a larger area, which results in a larger detection range, but the resolution is reduced due to energy dispersion. Therefore, the relationship between operating frequency and beam angle can be described by some form of function, usually a function that takes into account reflection intensity, signal dispersion, and energy concentration.

[0040] By adjusting the acquisition parameters, it is possible to ensure signal strength while avoiding excessive noise effects, thereby obtaining high-definition three-dimensional images.

[0041] In one embodiment, in order to obtain the best three-dimensional image in a complex seabed environment, an objective function is proposed to comprehensively consider the optimal configuration of various parameters. J Can be reflection intensity I echo With noise level NThis can maximize the image quality and minimize the impact of noise.

[0042] Define an objective function:

[0043] in N The noise level is usually a measure related to environmental factors such as water turbidity and flow rate. Based on the analysis of the underwater acoustic environment and noise sources, the noise level N It can be modeled as the combined effect of environmental factors (such as turbidity, flow rate) and system noise:

[0044] in, N background is the basic noise (including constants such as thermal noise and equipment electronic noise), is the water turbidity (unit: such as NTU or mg / L), reflects the concentration of suspended particles, v Water flow velocity (unit: m / s). The square of the flow velocity reflects the contribution of turbulent noise. α , β is the weight coefficient (needs to be calibrated through experiments or field data). These parameters related to the noise level are noise suppression parameters.

[0045] By optimizing the objective function J , find the best operating frequency 𝑓, beam angle 𝜃, gain value G , Sensitivity S and noise suppression parameters to improve the quality of 3D images.

[0046] Step 2102: Convert the three-dimensional image into initial point cloud data.

[0047] Step 2103: According to the reflection intensity of the pipeline, initial point cloud data that meets the second preset condition is selected as the point cloud data.

[0048] Although the three-dimensional images obtained by the three-dimensional sonar equipment have undergone the above series of optimizations to obtain clear images, it cannot ensure that there is no point cloud data of the mud surface mixed in the three-dimensional images. Therefore, it is necessary to filter out the point cloud output belonging to the mud surface in the initial point cloud data to obtain the point cloud data of the pipeline.

[0049] According to different reflection intensity values, the reflection intensity of the pipeline is greater than the reflection intensity of the surrounding mud surface. The threshold of the pipeline reflection intensity value is set to filter out the point cloud data of the mud surface and only retain the point cloud data of the pipeline.

[0050] The second preset condition may be that the reflection intensity corresponding to the initial point cloud data is greater than or equal to a reflection intensity threshold. The reflection intensity corresponding to each point cloud data can be calculated by the above formula (1), and then compared with the reflection intensity threshold to screen out the initial point cloud data greater than or equal to the threshold. The screened out initial point cloud data is the point cloud data of the pipeline.

[0051] Specifically, regarding the threshold value for distinguishing the reflection intensity value of the mud surface and the pipeline, this application proposes a threshold method for dynamically calculating the reflection intensity. The reflection intensity is obtained by formula (1): I echo Then, a dynamic threshold function based on the parameters in formula (1) is set I threshold , as follows:

[0052] in: c Is a constant coefficient used to adjust the sensitivity of the reflection intensity threshold, which is usually adjusted according to the actual environment and experimental results. I=I max -I min It is the difference in reflection intensity between the pipeline and the mud surface, indicating the difference between the reflection intensity of the pipeline and the reflection intensity of the mud surface. I max and I min They respectively represent the maximum reflection intensity of the pipeline and the minimum reflection intensity of the mud surface. I max During the actual measurement process, the reflection intensity values ​​of the pipeline can be sampled and the maximum value can be selected. I min It is the minimum reflection intensity of the mud surface, and is usually selected from multiple samplings to obtain the minimum reflection intensity of the mud surface area. k It is an adjustment factor used to adjust the threshold of reflection intensity and the factor of reflection intensity difference. Its function is to adjust the sensitivity of the threshold, that is, to control the influence of the difference in pipeline reflection and mud surface reflection intensity on the threshold. k The value of needs to be determined through actual testing and optimization, usually based on experimental data comparing different k value, select the optimal value that makes the threshold more adaptable to different seabed environmental conditions.

[0053] Based on the calculated dynamic threshold I threshold , filter point cloud data. Set point cloud data P i The corresponding reflection intensity is I pointi , and make the following formula judgment:

[0054] in, P i For the i The initial point cloud data is considered to belong to the pipeline only when the reflection intensity corresponding to the initial point cloud data is greater than or equal to the threshold, otherwise it belongs to the mud surface. Through dynamic threshold calculation, this application can accurately determine the reflection intensity distinction threshold between pipelines and mud surfaces under various environmental conditions. This method combines the influence of important parameters such as working frequency, gain, sensitivity, etc., can adapt to different working environments, and effectively filter point cloud data to provide accurate results for submarine pipeline detection.

[0055] Step 220: Determine the position and height of the pipe top elevation based on the point cloud data.

[0056] As mentioned above, due to the complexity of the submarine environment, the top elevations of submarine pipelines at different locations are different. Therefore, multiple top elevations are required to accurately and completely reflect the buried depth of the pipeline. In steps 220-240, the acquisition of a certain top elevation is taken as an example to introduce the buried depth of the pipeline corresponding to the top elevation of the pipeline, and the remaining top elevations can be implemented by reference.

[0057] Regarding the acquisition of pipe top elevation, this application proposes a pipe top elevation extraction method based on adaptive point cloud repair and optimized matching. The first step is pipeline point cloud data preprocessing: the point cloud data obtained in step 210 is filtered and removed for noise. By automatically adjusting the weight, the appropriate noise removal threshold is automatically selected. The second step is pipeline geometric model construction and data filling: based on the known pipeline size, the blind area data is filled using an interpolation algorithm (such as spline interpolation) and geometric modeling, and matched in combination with the point cloud data. The third step is least squares matching optimization: the filled data is matched with the white model by least squares optimization, and external noise is further removed to obtain a high-quality three-dimensional pipeline model. The fourth step is adaptive slicing and pipe top elevation extraction: through the adaptive slicing algorithm, combined with tangent extraction and geometric analysis, the resolution of the slice and the tangent extraction point are automatically determined, and the pipe top elevation is extracted based on the method of constructing an arc with three points. The fifth step is efficient arc screening and elevation optimization: the arc constructed by three points is screened using a dynamic threshold optimization algorithm, the threshold is automatically adjusted, and the pipe top elevation is quickly extracted.

[0058] Specifically, step 220 may include steps 2201 to 2204 .

[0059] Step 2201: By automatically adjusting the weight, the pipeline upper point cloud data that meets the first preset condition is selected as the denoised pipeline upper point cloud data.

[0060] In one embodiment, the three-dimensional sonar equipment obtains a high-resolution three-dimensional image of the upper portion of the submarine pipeline, and thus the obtained point cloud data includes point cloud data of the upper portion of the pipeline.

[0061] The first preset condition may be that the weight corresponding to the pipeline upper point cloud data is greater than or equal to the weight threshold. The weight corresponding to each point cloud data can be calculated by the following formula (6), and then compared with the weight threshold to screen out the pipeline upper point cloud data that is greater than or equal to the threshold. The screened pipeline upper point cloud data is the denoised pipeline upper point cloud data.

[0062] The point cloud data of the upper part of the pipeline is denoised to obtain the denoised point cloud data of the upper part of the pipeline. As mentioned above, the point cloud data is P 管线 , the noise is removed by automatically adjusting the weight method, and the weight function is defined as:

[0063] in, d i Point cloud data i The distance from a point to its nearest neighbor. d is the adjustment parameter for controlling the threshold. d threshold It is the distance threshold between noise points and real data. It is a distance threshold used to distinguish normal points from abnormal points, and is determined according to the local density of point cloud data. The weight calculation does not directly rely on known noise points, but judges whether each point is noise based on the relative distance between each point and its neighborhood. Points with low weights are more likely to be noise, and points with high weights are considered to be real. Real data refers to point cloud data that conforms to actual physical meaning, usually objects that have a small distance to surrounding points and exist in the actual environment. By automatically adjusting the weight function w i , the weight of each point will be automatically adjusted according to the distance to remove noise. The weight here refers to the "importance" or "credibility" of each point cloud data, which is used to quantify the influence of the point in the data processing process. For each point cloud data, the meaning of weight is to measure whether the point is valid data or noise.

[0064] Defining the weight function w i The purpose is to assign a weighted value to each point to determine whether it is a noise point. By calculating the weight of each point, we can know which points are close to other points (probably real data) and which points are far away from other points (probably noise). w i The size reflects the point iThe "credibility" of a point is the distance between it and the surrounding points. Points with higher weights are usually "credible" data (possibly points of real objects), while points with lower weights are "abnormal" data, possibly noise. d i is very small, indicating that it may belong to real data, so the weight w i will be close to 1, indicating that it is reliable. i Distance to surrounding points d i When it is large, it means that it may be an outlier (i.e., a noise point), so the weight w i will be close to 0, indicating that it is unreliable. In this way, the weight value can help us determine which points are reasonable and which are noise. By setting a weight threshold w threshold , points with weights lower than this value are regarded as noise, thus achieving noise removal.

[0065] Step 2202: Determine the pipeline lower point cloud data according to the size of the pipeline and the denoised pipeline upper point cloud data.

[0066] Due to the existence of the measurement blind area, the bottom data of the pipeline cannot be obtained. The interpolation coefficient can be determined according to the size of the pipeline and the denoised upper point cloud data of the pipeline; according to the interpolation coefficient, the lower point cloud data of the pipeline is determined by the spline interpolation method. The size of the pipeline is a known data, which is generally expressed by the diameter of the pipeline.

[0067] Specifically, based on the known dimensions of the pipeline D The denoised upper point cloud data of the pipeline is filled using the spline interpolation method. The bottom data of the pipeline can be supplemented by the spline interpolation formula, as follows:

[0068] in, S(x) Indicates at location x Specifically, S(x) It is a height function obtained by spline interpolation, which describes the continuity of the bottom point cloud. x It is the independent variable, usually representing the horizontal position or the coordinate of the pipeline along the pipeline direction. a 0. a 1. a 2. a3 are the interpolation coefficients calculated from the known point cloud data. Usually, spline interpolation calculates these coefficients by using a number of known points (in this case, some known heights of the pipeline). The specific method is to determine these coefficients by solving a system of equations so that the interpolation function can minimize the error at the known data points and remain smooth over the entire interval.

[0069] The interpolation function is used to generate supplementary bottom point cloud data. The bottom point cloud data is a three-dimensional coordinate, that is, each point has (x, y, z) However, the spline interpolation function S(x) It just provides the direction along the pipeline x The height value of z In order to convert it into a complete 3D point cloud data, it is still necessary to combine the horizontal y For example, if the geometric shape of the pipeline at a certain lateral position is known, the final 3D point cloud data can be obtained by x and y Combined with the height values ​​provided by the spline interpolation S(x) To construct the three-dimensional coordinate points: (x, y, S(x)) . Thus, the result of the interpolation function is S(x) Can be compared with the transverse coordinates of the pipeline y Combined, we get complete 3D point cloud data.

[0070] Step 2203: Determine the pipeline three-dimensional model based on the pipeline lower point cloud data and the denoised pipeline upper point cloud data.

[0071] After processing in step 2202, point cloud data of the complete pipeline can be obtained. Therefore, a three-dimensional model of the pipeline can be constructed based on the point cloud data, and then the pipe top elevation can be determined based on the three-dimensional model of the pipeline.

[0072] Specifically, the pipeline lower point cloud data and the denoised pipeline upper point cloud data are matched with the white model using the least squares method to obtain the best matching pipeline lower point cloud data and denoised pipeline upper point cloud data. The pipeline 3D model is determined based on the best matching pipeline lower point cloud data and denoised pipeline upper point cloud data. The white model is a standard pipeline 3D model constructed based on the size of the pipeline.

[0073] The least squares objective function is:

[0074] in, P i It is the point cloud data of the lower part of the pipeline and the denoised point cloud data of the upper part of the pipeline. i These point cloud data are i Point cloud,M model ( i ) is the first i Point cloud data, Q is the total number of these point cloud data.

[0075] The optimal match is obtained by minimizing the objective function M model ( i ), and then according to all M model ( i ) to determine the pipeline three-dimensional model. If it exceeds the set threshold, continue to optimize until the error is lower than the threshold.

[0076] Step 2204: Slice the pipeline three-dimensional model to determine the position and height of the pipe top elevation.

[0077] The pipeline three-dimensional model is sliced ​​to obtain multiple near-circular slices. For each near-circular slice, the following operations are performed: multiple tangents are made to the near-circular slice to obtain multiple tangent points; the position and height of each tangent point are extracted, and the top three tangent points are selected in height order; the curvature of the arc formed by the three tangent points is calculated; if the curvature is less than a preset curvature, the position and height of the tangent point with the highest height among the three tangent points are selected as the position and height of the pipe top elevation.

[0078] Slicing the pipeline three-dimensional model to obtain a plurality of nearly circular slices includes: determining a slice spacing according to the shape of the pipeline; and slicing the pipeline three-dimensional model according to the slice spacing to obtain a plurality of nearly circular slices.

[0079] Specifically, adaptive slicing is performed based on the pipeline 3D model. Slice spacing Δ z It will be adjusted adaptively according to the shape of the pipeline. Smaller slice spacing is used for complex areas of the pipeline, and larger slice spacing is used for straight segments. The calculation method of adaptive slicing is:

[0080] in, L It is the minimum number of points required for slicing, that is, the minimum number of point data required to complete slicing. It can be set according to the specific shape of the pipeline and the required accuracy. L It depends on the following factors: (1) The complexity of the pipeline: For pipelines with complex shapes (such as bends or irregular parts), more point cloud data may be required to ensure accuracy. L It can be increased appropriately. (2) Density of point cloud data: If the density of point cloud data collection is high, L can be relatively small; if the data is sparse, you may need to increaseL To obtain enough points for slicing. (3) Accuracy requirements: If the accuracy requirements for pipe top elevation extraction are high, a smaller slicing interval (i.e., larger L ) to improve the accuracy of the calculation. z max Δ is the maximum slice spacing, which can usually be set based on the following factors: (1) The size and shape of the pipe: A larger pipe diameter may allow for a larger slice spacing, while a smaller pipe diameter requires a smaller slice spacing to ensure the accuracy of the slices. (2) The quality of the point cloud data: If the point cloud data is dense and accurate, a larger Δ can be used. z max , otherwise it is recommended to select a smaller slice spacing to ensure more accurate extraction of the pipe top elevation. (3) Calculation efficiency requirements: A larger slice spacing will reduce the amount of calculation, but may affect the accuracy of the result. Therefore, Δ z max A trade-off between accuracy and efficiency needs to be made based on the needs of the actual application.

[0081] For a slice, make tangents of the slice at regular intervals, extract the positions and heights of the points where the tangents intersect, compare the heights of the extracted tangent points and select the three points with the highest heights. The three highest points are constructed into an arc. When the arc is less than the set threshold, the highest point is selected as the pipe top elevation.

[0082] For an arc formed by three points, its arc can be calculated e , and dynamic threshold e threshold For comparison, the formula is as follows:

[0083] Where 𝑅 is the radius calculated from three points, x 1. x 2. x 3 represents the coordinates of the three points that make up the arc. These points are used to calculate the tangent and angle of the arc, and then determine whether the part is the key part of the pipe top. e < e threshold , the highest point is selected as the pipe top elevation. Dynamic threshold e threshold Adjust according to the complexity of the slice area. Through dynamic optimization, the threshold can be automatically adjusted to improve the accuracy and efficiency of elevation extraction. On the cross section of the pipeline, if it is a relatively smooth arc shape with a relatively small curvature (i.e. e The value is small), indicating that this part of the pipeline is relatively straight or has a low arc, which meets the requirements for extracting the pipe top elevation. At this time, the highest point should be the top of the pipeline, that is, the pipe top elevation. eLess than threshold e threshold , it can be considered that the shape of the pipeline in this area is relatively regular (close to a circle or a smooth arc), so it is reasonable to choose the highest point as the pipe top elevation.

[0084] if e Greater than threshold e threshold , indicating that the pipe shape in this area is relatively complex (may have large curvature or irregular shape), and it is no longer suitable to directly extract the pipe top elevation by fitting three points. In this case, the following methods can be used to re-determine the pipe top elevation: (1) More detailed slicing: divide the area into more slices and reselect a set of suitable points for calculation. (2) Use other geometric models: The pipe top elevation can be found through more accurate fitting methods, such as curve fitting or multi-point matching. (3) Local optimization: Perform local optimization processing on complex areas to improve the accuracy of elevation extraction by adjusting point cloud data or using more data.

[0085] Through the above-mentioned pipe top elevation extraction algorithm based on adaptive point cloud repair and optimized matching in the present application, the pipe top elevation of the submarine pipeline can be extracted more accurately and automatically, while greatly improving the efficiency.

[0086] Step 230: Determine the height of the natural mud surface according to the position of the pipe top elevation.

[0087] A multi-beam bathymetric system is used to obtain three-dimensional terrain data of the natural mud surface; three-dimensional modeling is performed on the three-dimensional terrain data to obtain a three-dimensional model of the mud surface; the pipe top elevation is arranged on the three-dimensional model of the mud surface, and multiple height data of the three-dimensional model of the mud surface are circled with the position of the pipe top elevation as the center of the circle and a preset radius as the radius; an average value of the multiple height data is calculated as the height of the natural mud surface.

[0088] Regarding arranging the pipe top elevation on the mud surface three-dimensional model, the position and height of the pipe top elevation have been obtained by step 220, and the pipe top elevation can be arranged on the three-dimensional model by using software by displaying points or marking points. Regarding the preset radius, it can generally be set to 5 cm according to empirical values. In theory, one pipe top elevation corresponds to one mud surface point, but considering that the height of the mud surface point is obtained by measuring equipment, there is a certain deviation. In order to reduce this deviation, 5 cm is specified as the radius of the circle with the pipe top elevation feature point as the center. If it is specified as 1-2 cm, the points within this range may be relatively sparse. If it is specified too large, it cannot reflect the actual situation. Based on experience, 5 cm is specified. In this way, there can be multiple pipe top elevations within the range of 5 cm. Therefore, multiple natural mud surfaces corresponding to multiple pipe top elevations can be determined, and the heights of these natural mud surfaces are averaged, and the average value is used as the height of the natural mud surface.

[0089] In view of the non-uniformity of the seabed topography and the measurement error, this application provides an adaptive elevation correction method based on the weighted average of the local area. This method dynamically adjusts the weight according to the distance between the mud surface point and the pipe top elevation. The mud surface points far away from the pipe top elevation have a lower weight, and the mud surface points close to the pipe have a higher weight. In this way, accurate natural mud surface correction can be performed according to the local environment where the pipeline is located. By analyzing the local changes in the seabed topography, the formula for correcting the natural mud surface height using the weighted average is:

[0090] in, l i It is i The weight of a mud surface point is usually related to the measurement accuracy of the point, or the relative distance between the point and the pipe top elevation. h i For the i The height of each mud surface point is obtained through the above steps. K is the total number of mud surface points.

[0091] The weight value can be calculated by the following formula:

[0092] in, u i is the distance between the 𝑖th mud surface point and the pipe top elevation, u pipe It refers to the reference distance from the pipe top elevation to a certain point. u pipeIt is the distance from a specified reference point (usually the center of the pipe top elevation or the closest known elevation point) to a measurement point. This distance can be used to calculate the relative distance between each point and the pipe top elevation, thus providing a basis for weighted averaging. φ is the weighted standard deviation, and different φs are used for correction in different areas. For more complex seabed environments, the correction strategy in the area can be dynamically adjusted to make the correction result more accurate.

[0093] Step 240: Determine the buried depth of the pipeline according to the height of the pipe top elevation and the height of the natural mud surface.

[0094] The difference between the height of the pipe top elevation and the height of the natural mud surface is calculated as the initial pipeline burial depth; and the pipeline burial depth is determined according to the initial pipeline burial depth and the minimized error.

[0095] Specifically, for the calculation of pipeline burial depth, the present application provides a global pipeline burial depth optimization algorithm, which optimizes the burial depth data of the entire pipeline by accurately matching the adaptively corrected natural mud surface height and the pipe top elevation.

[0096] In the measurement of the buried depth of submarine pipelines, due to the complex seabed environment, it is affected by various factors such as water depth and turbidity, which may cause measurement errors. In order to compensate for these errors, traditional buried depth calculation methods are usually based on the natural mud surface and pipe top elevation data at a certain point, but these methods may be inaccurate or inefficient. Therefore, a global pipeline buried depth optimization algorithm based on minimizing errors provides a more accurate calculation method. The core idea of ​​the algorithm is to match the adaptively corrected natural mud surface height and pipe top elevation data by minimizing the global error, and calculate the optimized buried depth value.

[0097] Global pipeline burial depth optimization algorithm steps: (1) Difference between pipe top elevation and natural mud surface: First, calculate the difference between the pipe top elevation and the corresponding corrected natural mud surface. For the point cloud data of a pipeline, calculate the height difference of each point. h 管线 - h 修正自然泥面高度 , the burial depth information of the point can be obtained.

[0098] (2) Error minimization: In order to obtain the globally optimal burial depth data, the algorithm is optimized by minimizing the error. The error function is defined as follows:

[0099] in, O i It is i The actual burial depth of a point, h管线 is the height of the pipe top elevation, h 修正自然泥面高度 is the height of the corrected natural mud surface, or is the total number of points.

[0100] (3) Global optimization: The algorithm adjusts the burial depth of each point O i , in order to minimize the total error. Specifically, the least square method or other optimization methods are used to calculate the optimal burial depth value of each point, so as to obtain the globally optimized pipeline burial depth data.

[0101] Through this optimization process, the algorithm can accurately calculate the burial depth of the entire pipeline based on the difference between the adaptively corrected natural mud surface and the pipe top elevation, and reduce local errors through global optimization methods to ensure the accuracy and reliability of the burial depth calculation, thereby obtaining the precise burial depth of the submarine pipeline.

[0102] The embodiment of the present application can efficiently and accurately obtain the buried depth data of the pipeline by introducing multiple optimization schemes, such as adaptive point cloud repair, global buried depth optimization and high-precision three-dimensional modeling. Compared with the prior art, the present application does not require manual intervention. Through automated calculation and optimization, it can reflect the buried depth changes of the pipeline in real time and comprehensively, significantly improve the measurement efficiency and accuracy, reduce human errors, and provide more reliable technical support for submarine pipeline monitoring and maintenance.

[0103] In several embodiments provided in the present application, the disclosed devices and methods can also be implemented in other ways. The device and method embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and a part of a module, a program segment or a code contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of boxes in the block diagram and / or the flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0104] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0105] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

Claims

1. A method for obtaining the buried depth of a submarine pipeline, characterized in that: The following steps are involved: Acquiring point cloud data of the pipeline; Determine the position and height of the pipe top elevation according to the point cloud data; Determine the height of the natural mud surface according to the position of the pipe top elevation; Determining the buried depth of the pipeline according to the height of the pipe top elevation and the height of the natural mud surface; The point cloud data includes point cloud data of the upper part of the pipeline; Determining the position and height of the pipe top elevation according to the point cloud data includes: By automatically adjusting the weight, the pipeline upper point cloud data meeting the first preset condition is selected as the denoised pipeline upper point cloud data; Determine the pipeline lower point cloud data according to the size of the pipeline and the denoised pipeline upper point cloud data; Determine a pipeline three-dimensional model according to the pipeline lower point cloud data and the denoised pipeline upper point cloud data; The pipeline three-dimensional model is sliced ​​to determine the position and height of the pipe top elevation.

2. The method for obtaining the buried depth of a submarine pipeline according to claim 1, characterized in that: The step of obtaining the point cloud data of the pipeline includes: Using three-dimensional sonar equipment to obtain a three-dimensional image of the pipeline; Converting the three-dimensional image into initial point cloud data; According to the reflection intensity of the pipeline, initial point cloud data meeting a second preset condition is selected as the point cloud data.

3. The method for obtaining the buried depth of a submarine pipeline according to claim 1, characterized in that: The step of determining the pipeline lower point cloud data according to the size of the pipeline and the denoised pipeline upper point cloud data comprises: Determining an interpolation coefficient according to the size of the pipeline and the denoised upper point cloud data of the pipeline; According to the interpolation coefficients, the pipeline lower point cloud data is determined by spline interpolation method.

4. The method for obtaining the buried depth of a submarine pipeline according to claim 1, characterized in that: Determining the pipeline three-dimensional model according to the pipeline lower point cloud data and the denoised pipeline upper point cloud data includes: Using the least squares method, matching the pipeline lower point cloud data and the denoised pipeline upper point cloud data with the white model to obtain the best matching pipeline lower point cloud data and denoised pipeline upper point cloud data; Determine the pipeline three-dimensional model according to the optimally matched pipeline lower point cloud data and the denoised pipeline upper point cloud data; The white model is a standard pipeline three-dimensional model constructed based on the size of the pipeline.

5. The method for obtaining the buried depth of a submarine pipeline according to claim 1, characterized in that: The slicing of the pipeline three-dimensional model to determine the position and height of the pipe top elevation includes: Slicing the pipeline three-dimensional model to obtain a plurality of nearly circular slices; For each near-circle slice, do the following: Make multiple tangent lines on the nearly circular slice to obtain multiple tangent points; Extract the position and height of each tangent point, and select the top three tangent points in terms of height; Calculate the arc formed by the three tangent points; If the curvature is smaller than a preset curvature, the position and height of the highest tangent point among the three tangent points are selected as the position and height of the pipe top elevation.

6. The method for obtaining the buried depth of submarine pipeline according to claim 1, characterized in that: The slicing of the pipeline three-dimensional model to obtain a plurality of nearly circular slices includes: Determining the slice spacing according to the shape of the pipeline; The pipeline three-dimensional model is sliced ​​according to the slice spacing to obtain a plurality of nearly circular slices.

7. The method for obtaining the buried depth of a submarine pipeline according to claim 1, characterized in that: Determining the height of the natural mud surface according to the position of the pipe top elevation includes: Using a multi-beam bathymetric system to obtain three-dimensional topographic data of the natural mud surface; Performing three-dimensional modeling on the three-dimensional terrain data to obtain a three-dimensional mud surface model; Arrange the pipe top elevation on the three-dimensional model of the mud surface, take the position of the pipe top elevation as the center of a circle, and circle a plurality of height data of the three-dimensional model of the mud surface with a preset radius as the radius; An average value of the plurality of height data is calculated as the height of the natural mud surface.

8. The method for obtaining the buried depth of a submarine pipeline according to claim 1, characterized in that: Determining the buried depth of the pipeline according to the height of the pipe top elevation and the height of the natural mud surface includes: Calculate the difference between the height of the pipe top elevation and the height of the natural mud surface as the initial pipeline burial depth; The pipeline burial depth is determined according to the initial pipeline burial depth and the minimized error.

9. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to execute the method for obtaining the buried depth of a submarine pipeline according to any one of claims 1-8.

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