A method and system for detecting exposed pipe segments of submarine cables based on point cloud data

Abstract

The present invention discloses a method and system for detecting exposed pipe sections of submarine cables based on point cloud data, which relates to a method for detecting submarine cables. At present, the detection method for exposed pipe sections of submarine cables lacks efficient automated quantitative analysis means, relies on manual analysis, and has a complex processing process, making it difficult to achieve real-time monitoring and accurate assessment. The present invention first separates the submarine cable part and the seabed part from the submarine point cloud data; performs profile processing on the point cloud; for the submarine cable part, extracts the centers of continuous submarine cable pipe sections, calculates the cable orientation, and simultaneously extracts the cable height; for the seabed part, extracts the seabed height after seabed reconstruction, compares it with the cable height, and quantitatively calculates the occurrence status. This technical solution provides a method for processing submarine cable point cloud data, a method for fitting the submarine cable profile, and a method for quantitatively calculating the occurrence status, and can detect abnormal states such as cable exposure, suspension, and displacement, providing key technical support for the automation and intelligence of submarine cable detection.

Description

Technical Field

[0001] The present invention relates to a method for detecting submarine cables, and more particularly to a method for detecting exposed pipe sections of submarine cables based on point cloud data. Background Art

[0002] As an important part of the power transmission of offshore wind farms, the safe and reliable operation of submarine cables is crucial for ensuring the stability of offshore wind farm systems. Submarine cables are usually buried or laid deep under the sea floor, directly undertaking the task of transmitting electrical energy from offshore wind turbines to the land. Due to the complex working environment of submarine cables, which is full of unforeseen factors, such as submarine geological changes, seawater flow, and submarine animal activities, submarine cables are extremely vulnerable to damage, exposure, or displacement. These problems may directly lead to cable damage or power transmission interruption, thus affecting the stable operation of the entire wind farm. Therefore, how to effectively monitor the operation of submarine cables, especially when cable exposure or abnormal conditions occur, and timely detect and take measures is the key to ensuring the safe operation of submarine cables.

[0003] Currently, underwater three-dimensional sonar, multi-beam bathymetric sonar and other devices are generally used for detecting the state of exposed pipe sections of submarine cables. These devices can obtain three-dimensional point cloud data of the sea floor and the submarine cable by scanning the sea floor area. These point cloud data provide basic information for detecting submarine cables. Based on these point cloud data, traditional submarine cable detection methods usually identify the exposed pipe sections of the cable through manual analysis or simple qualitative evaluation. However, this method has many problems, mainly reflected in the following aspects:

[0004] 1. Mainly qualitative detection, lack of quantitative analysis: Most of the existing methods adopt qualitative evaluation based on point clouds, which can only provide a rough judgment on the occurrence state of submarine cables (such as whether they are exposed, suspended, etc.), lacking accurate quantitative calculation, which makes the detection of submarine cable states often inaccurate.

[0005] 2. Strong dependence on manual analysis: Many current detection methods based on point cloud data rely on manual analysis of data section by section, with a large workload, low efficiency and prone to human errors. Especially in complex submarine environments, the accuracy and real-time performance of manual analysis are difficult to guarantee.

[0006] 3. Low automation level: Although some automated detection technologies have been proposed, most of them still remain in the initial stage and cannot efficiently and accurately process a large amount of point cloud data. Especially in a dynamically changing submarine environment, the existing technologies are difficult to handle complex situations.

[0007] Therefore, with the gradual increase in the application of submarine cables and the increasing complexity of the seabed environment, there is an urgent need for a new method for detecting exposed pipe sections of submarine cables based on point cloud data, which can improve the accuracy and efficiency of automatic detection, quantitatively evaluate the storage state of submarine cables, reduce manual intervention, provide more reliable monitoring results, and provide technical support for the safe and stable operation of offshore wind farms. Summary of the Invention

[0008] The technical problem to be solved and the technical task proposed by the present invention are to improve and refine the existing technical solutions, and provide a method and system for detecting exposed pipe sections of submarine cables based on point cloud data, so as to achieve the purpose of efficient and automatic detection by quantitatively analyzing the storage state of submarine cables. To this end, the present invention adopts the following technical solutions.

[0009] A method for detecting exposed pipe sections of submarine cables based on point cloud data includes the following steps:

[0010] 1) Obtain seabed point cloud data P, and separate submarine cable point cloud data PC and seabed terrain point cloud data PG from the seabed point cloud data by the RANSAC method;

[0011] 2) Slice the submarine cable point cloud data PC and the seabed terrain point cloud data PG to obtain a submarine cable profile set and a terrain profile set;

[0012] 3) Perform elliptical fitting on the submarine cable point cloud profile data in the submarine cable profile set, and extract the center (x c , y c ) and the height h of the submarine cable pipe ; perform polynomial fitting on the seabed terrain point cloud profile data in the terrain profile set to obtain the seabed height h seabed ;

[0013] 4) According to the difference E between the height h of the submarine cable pipe and the seabed height h seabed , quantitatively calculate the storage state of the submarine cable. If E ≤ D, it means that the submarine cable is exposed or completely exposed. If E > D, it means that the submarine cable is suspended, where D is the diameter of the submarine cable.

[0014] This technical solution can quantitatively calculate the occurrence state of the submarine cable by processing the point cloud data of the submarine cable and the seabed through profile slicing, ellipse fitting, polynomial fitting, etc. It overcomes the limitations of traditional qualitative analysis and provides more accurate and reliable detection results. It greatly improves the automation level of submarine cable detection, reduces the dependence on manual analysis, can quickly and efficiently process large-scale point cloud data, and improves the efficiency and accuracy of detection. By fitting the profile data of the submarine cable with an ellipse and the seabed terrain data with a polynomial, the geometric features of the submarine cable and the height information of the seabed can be accurately extracted. Especially when dealing with curved or complex submarine cables, it has excellent fitting accuracy. It can accurately identify abnormal states such as exposure, suspension, or displacement of the submarine cable, timely discover potential safety hazards, and ensure the safety and stability of the submarine cable. This method can adapt to complex seabed environments and can effectively handle different seabed terrains and submarine cable configurations in the monitoring of submarine cables, with a wide range of application scenarios.

[0015] As a preferred technical means: in step 2), by setting a slicing plane and an auxiliary plane, the intersection of the point cloud and the slicing plane is used to obtain a set of profile point clouds, and the profile point clouds are projected to obtain a set of profile data points corresponding to the slicing plane.

[0016] This technical solution can effectively increase the point cloud density of each slice by setting an auxiliary plane and adjusting the slice thickness, avoiding incomplete or large-error profile data caused by sparse point clouds, and thus improving the accuracy and reliability of the profile point cloud data. Compared with traditional methods, the combination of the slicing plane and the auxiliary plane can more accurately obtain a set of profile point clouds, avoiding data omission or error that may be caused by a single slicing plane, and ensuring that the profile data more conforms to the actual submarine cable and seabed structure. Through projection processing, the error of the profile data in three-dimensional space can be reduced, making the profile data smoother and more consistent, avoiding interference caused by factors such as seabed terrain undulation and submarine cable shape changes, and improving the stability and reliability of detection. This method can more accurately express different seabed terrains and submarine cable configurations through the projection processing of the profile point cloud, can adapt to different environmental changes, and has stronger flexibility and universality. This technical solution uses the strategy of the slicing plane and the auxiliary plane to make the slicing and processing process of the point cloud data more efficient, reduces a large amount of unnecessary data calculations, improves the overall data processing efficiency, and has obvious advantages especially in the processing of large-scale point cloud data.

[0017] As a preferred technical means: the slicing process of step 2) includes the following contents:

[0018] 2.1) Given point cloud data P{P i |i = 1, 2, 3,..., n} and a set of slicing planes {S i|i = 1, 2, 3,..., m}, for each slice plane S i Generate two symmetric auxiliary planes S i ’ and S i ”, the distance between the two auxiliary planes is the slice thickness σ, and take the points between S i ’ and S i ” as the contour point cloud set corresponding to the slice plane S i ;

[0019] 2.2) According to the normal vector and plane equation of the slice plane S i , traverse each point in the point cloud data P to determine the point set located on the slice plane S i ;

[0020] 2.3) Project the point set on the slice plane S i into the slice plane to obtain the profile data point set corresponding to the slice plane S i ;

[0021] By generating two symmetric auxiliary planes S i for each slice plane S i ’ and S i", and select the point cloud data between them as the contour point cloud set, which can effectively improve the resolution of the point cloud data. The use of the auxiliary plane ensures the controllability of the slice thickness σ, making the capture of details more accurate, thus providing higher-quality data for subsequent fitting and analysis. The double-layer screening strategy of the slice plane and the auxiliary plane can ensure that each slice can obtain richer and more accurate point cloud data, avoiding potential data loss or errors generated by only a single slice plane, and ensuring that each profile can comprehensively represent the actual submarine cable or seabed terrain features. In step 2.1), by controlling the slice thickness σ and the distance between the auxiliary planes, it can be flexibly adjusted according to different seabed terrains, submarine cable structures and environmental changes to meet different actual needs, enabling this scheme to widely adapt to different detection scenarios. Whether in flat seabeds or complex seabed terrains, it can be stably and effectively executed. The slice plane and point cloud projection methods in steps 2.2) and 2.3) simplify the process of point cloud processing, avoiding the complex three-dimensional space calculations that may be required in traditional methods. While ensuring data accuracy, it can significantly reduce the computational burden, improve the processing efficiency, especially when dealing with large-scale point cloud data, it can effectively save computational resources and time. By projecting the point set on the slice plane, the uncertainties caused by point cloud data noise, seabed terrain irregularities, etc. can be eliminated, improving the stability of the profile data, making the shapes of the submarine cable and seabed terrain more accurately reflected in the profile data, thus ensuring the reliability of the analysis results. Through the projection process, not only can the point cloud be accurately mapped onto the slice plane, but also its structural information in the slice plane can be better retained, enhancing the details of the profile data, making the quantitative analysis of the occurrence status of the submarine cable, seabed morphology, etc. more accurate and comprehensive.

[0022] As a preferred technical means: In step 2.2), according to the normal vector of the slice plane S i of , the plane equation n 1 x + n 2 y + n 3 z + n 0 = 0, traverse each point P i in the point cloud. If it satisfies , it means that this point is on this slice plane, and obtain the point set i on the slice plane S ;

[0023] In step 2.3), project the point set on the slice plane into the slice plane. For any P i,j , let its projection point in the slice plane be . Using and the perpendicular projection relationship with the slice plane S i , through the following formula:

[0024]

[0025] The sliced plane S is calculated i The corresponding set of profile data points {q i,j | j = 1, 2, ..., N}; where refers to the vector from point to its projection point

[0026] In step 2.2), by according to the relationship between the normal vector of the sliced plane S i and each point Pi in the point cloud data, it accurately determines which points are located on the sliced plane. By using the formula to judge whether a point belongs to the sliced plane, it ensures that only the qualified points are selected, effectively filtering out the unqualified noise data, and guaranteeing the accuracy and reliability of the data. By traversing the point cloud data and screening points according to the plane equation, step 2.2) simplifies the point cloud selection process in the traditional method, improves the calculation efficiency, and can quickly locate the set of points on the sliced plane without relying on complex spatial analysis or lengthy calculation processes.

[0027] In step 2.3), by projecting the set of points on the sliced plane onto the sliced plane and adopting the projection relationship perpendicular to the sliced plane to process the point cloud, it ensures the accuracy of the projection result, while avoiding the errors that may be brought by the complexity or noise of the point cloud. It efficiently maps each point accurately into the sliced plane, thereby ensuring the quality of the set of profile data points. By using the projection relationship between the sliced plane and the point cloud points, step 2.3) adopts the geometric projection formula, simplifies the traditional three-dimensional data conversion process, can quickly obtain the projection result of each point, significantly reduces the calculation amount, is particularly suitable for processing large-scale point cloud data, and helps to improve the efficiency of data processing. By using clear mathematical formulas to describe the relationship between the sliced plane and the point cloud points, the projection result of the point cloud data on the sliced plane is more stable and reliable, ensuring that in a complex seabed environment, regardless of the changes in the submarine cable or seabed terrain, step 2.3) can obtain a high-quality set of profile data points, thereby improving the accuracy of subsequent analysis results. This method can flexibly adapt to different types of seabed environments, including the undulations of the seabed terrain, different laying situations of submarine cables, etc. Regardless of how the seabed environment changes, the processing method based on the sliced plane and the projection relationship can ensure data accuracy and has strong adaptability. Through the set of profile data points obtained in step 2.3), subsequent fitting, analysis and detection can be conveniently carried out, such as submarine cable status assessment, seabed terrain analysis, etc.; the accuracy and integrity of the set of profile data points provide a reliable data basis for subsequent quantitative analysis and determination.

[0028] As a preferred technical means: Step 3) includes the following content:​

[0029] 3.1) Ellipse fitting of submarine cable point cloud profile data:

[0030] Assume that the submarine cable profile is approximately an ellipse, and the point set of the submarine cable profile {q i (x i , y i ) | i = 1, 2,..., N} is the sliced plane data of the submarine cable point cloud;

[0031] Use the general form of the ellipse equation for fitting, and the equation is as follows:

[0032]

[0033] where A, B, C, D, E, F are fitting parameters, and Δ is the discriminant;

[0034] For each point (x i , y i ), calculate its algebraic distance d(x, y) to the ellipse, and this distance is:

[0035] Use the least squares method to fit the parameters of the ellipse, and the goal is to minimize the sum of the algebraic distances of all points:

[0036]

[0037] where, , is the parameter vector of the ellipse equation; , is the eigenvector of the point (x i , y i );

[0038] Solve the geometric parameters of the ellipse, including the semi-major axis a, the semi-minor axis b, the ellipse center coordinates (x c , y c ), and the angle between the major axis and the minor axis; the calculation formulas of these parameters are as follows:

[0039]

[0040] Calculate the height of the submarine cable , that is, the longitudinal coordinate of the center of the submarine cable profile plus the length of the semi-minor axis;

[0041] 3.2) Polynomial fitting of terrain point cloud profile data:

[0042] Perform polynomial fitting on the terrain profile point cloud data near the submarine cable; select the highest point of the fitting segment from the fitted polynomial as the seabed height h seabed , which is used for the subsequent calculation of the occurrence state of the submarine cable.

[0043] Step 3.1 Assume that the cross-section of the submarine cable is approximately an ellipse and use the ellipse equation for fitting, which can accurately describe the geometric shape of the submarine cable. This assumption is often applicable in practical applications, especially since submarine cables are usually cylindrical and their cross-sections are approximately elliptical; through least-squares fitting, accurate geometric parameters of the submarine cable can be obtained, such as the semi-major axis, semi-minor axis, center coordinates, and the tilt angle of the ellipse. By minimizing the sum of algebraic distances, the fitting accuracy can be effectively improved and errors reduced; this makes the fitting result more consistent with the actual geometric characteristics of the submarine cable and improves the detection accuracy.

[0044] The geometric parameters of the fitted ellipse (such as the semi-major axis, semi-minor axis, ellipse center, included angle, etc.) can accurately describe the geometric shape of the submarine cable; the calculated parameters ensure more accurate calculation of the submarine cable height and provide reliable data for subsequent analysis of the submarine cable's occurrence state. Using the least-squares method to optimize the fitting process can effectively avoid error accumulation, and by optimizing the cost function, the geometric model of the submarine cable is made more consistent with the actual situation, improving the fitting accuracy.

[0045] Step 3.2 Use polynomial fitting to model the seabed topography, which can better reflect the complex undulations of the seabed; polynomial fitting can flexibly adjust parameters to adapt to different types of terrain features and improve the accuracy of the seabed height. By selecting the highest point in the fitting polynomial as the seabed height, it can accurately represent the seabed height at the location of the submarine cable, effectively avoiding interference from factors such as local depressions on the seabed and ensuring a more reliable judgment of the submarine cable's occurrence state.

[0046] This method reduces the need for manual analysis through automated fitting and calculation, improves the detection efficiency, and avoids the possibility of human judgment errors. Especially when faced with a large amount of point cloud data, automated processing can significantly improve the processing speed and accuracy. Regardless of the complexity of the seabed topography, this method can automatically adapt and perform fitting, enabling this solution to work reliably in different sea area environments and adapt to different submarine cable layouts and terrain conditions.

[0047] By using mathematical models and optimization algorithms, large-scale point cloud data can be effectively processed; submarine point cloud data is usually voluminous, and adopting this solution can ensure the accuracy of the processing results while maintaining the calculation efficiency, meeting the processing requirements of large-scale data sets.

[0048] By accurately calculating the difference E between the submarine cable height and the seabed height, the occurrence state of the submarine cable can be quantitatively judged, providing quantitative data with more reference value than traditional qualitative analysis; making the detection results more objective and scientific and providing data support for subsequent maintenance and management.

[0049] The precise submarine cable geometric parameters and seabed height information provided by this solution can provide reliable data support for subsequent intelligent decision-making systems. For example, the system can automatically identify whether the submarine cable needs to be reinforced, repaired, or reinstalled based on the calculated occurrence state data, improving the intelligent level of submarine cable management.

[0050] Another object of the present invention is to provide a submarine cable exposed pipe section detection system based on point cloud data. The system applies the aforementioned method for detecting submarine cable exposed pipe sections based on point cloud data, and the system includes:

[0051] A point cloud data acquisition module for acquiring seabed point cloud data;

[0052] A point cloud separation module for separating submarine cable point cloud data PC and seabed terrain point cloud data PG from the seabed point cloud data by the RANSAC method;

[0053] A slicing module for slicing the submarine cable point cloud data PC and the seabed terrain point cloud data PG to obtain a submarine cable profile set and a terrain profile set;

[0054] A fitting module for:

[0055] Performing ellipse fitting on the submarine cable point cloud profile data in the submarine cable profile set to extract the center (x c , y c ) and the submarine cable height h pipe ;

[0056] Performing polynomial fitting on the seabed terrain point cloud profile data in the terrain profile set to obtain the seabed height h seabed ;

[0057] An occurrence state calculation module for quantitatively calculating the occurrence state of the submarine cable based on the difference E between the submarine cable height h seabed and the seabed height h seabed , and determining whether the submarine cable is exposed or suspended.

[0058] This technical solution can efficiently and accurately detect submarine cable exposed pipe sections through automated data processing, precise fitting algorithms, and quantitative occurrence state evaluation. The system has high adaptability, a low error rate, and good scalability, providing reliable technical support for the monitoring and maintenance of submarine cables. Specifically:

[0059] Through the automated cooperation of multiple modules, the system automatically completes all processes from data acquisition to occurrence state calculation, greatly reducing manual intervention; not only improving the detection efficiency, but also avoiding errors that may be caused by human operations. The system can efficiently process a large amount of point cloud data, support the processing of large-scale data sets, and is applicable to submarine cable detection tasks of different scales.

[0060] The RANSAC method is used to accurately separate the submarine cable point cloud data and the seabed terrain point cloud data, ensuring that subsequent analysis only targets relevant data and improving the accuracy of the analysis. The submarine cable profile data can be accurately described by elliptical fitting, especially when the submarine cable is cylindrical. This method can ensure the accuracy of height calculation. Polynomial fitting of the seabed terrain point cloud data can better adapt to the complex and undulating seabed terrain, thereby obtaining a more accurate seabed height hseabed.

[0061] By calculating the difference between the height of the submarine cable and the seabed height, the system can quantitatively evaluate the occurrence state of the submarine cable. Compared with traditional qualitative analysis methods, this quantitative method is more scientific and objective, and can provide reliable data support for subsequent submarine cable maintenance and management. By setting the thresholds of the difference E and the diameter D of the submarine cable, the system can automatically determine whether the submarine cable is exposed or suspended, providing accurate decision-making support.

[0062] The system automatically completes the fitting of the submarine cable and the seabed terrain and the calculation of the occurrence state through algorithms, reducing manual intervention and possible errors in the analysis process, and improving the accuracy and reliability of detection. By optimizing the elliptical fitting and polynomial fitting through the least squares method, the system can obtain more accurate geometric parameters, further improving the accuracy of the occurrence state calculation.

[0063] Regardless of the complexity of the seabed terrain, the system can automatically adapt through different fitting methods and can operate stably in various seabed environments with strong adaptability.

[0064] The data provided by this system can not only be used for detecting the occurrence state of submarine cables, but also for intelligent decision-making support systems. By combining with other monitoring systems, it can realize automatic monitoring, early warning and maintenance of submarine cables. The system can process point cloud data in real time and generate detection results. For the problems of exposed or suspended submarine cables, the system can quickly issue early warnings and provide timely decision-making support for subsequent repair and maintenance.

[0065] Automated detection replaces the traditional manual detection process, greatly reducing labor costs and being able to process a large amount of data in a short time, improving work efficiency. Since the on-site detection of submarine cables by humans is reduced, the safety risks brought by manual intervention are reduced, ensuring the safety of staff.

[0066] The system can process large-scale submarine cable point cloud data, adapt to submarine cable monitoring tasks of different scales, and has high efficiency and accuracy, and can operate stably in complex environments such as large offshore wind farms.

[0067] As an optimal technical means: the slicing module further includes:

[0068] The contour point cloud set generation unit, given point cloud data and a set of slicing planes, generates two symmetric auxiliary planes for each slicing plane, and takes the points between the two auxiliary planes as the contour point cloud set corresponding to the slicing plane;

[0069] The point set determination unit traverses each point in the point cloud data according to the normal vector and plane equation of the slicing plane to determine the point set located on the slicing plane;

[0070] The projection processing unit projects the point set on the slicing plane into the slicing plane to obtain the profile data point set corresponding to the slicing plane.

[0071] Through the refined design of the slicing module, the system has higher precision and efficiency when processing seabed point cloud data. The refined processing of each sub-module ensures the accurate extraction and processing of data, thereby improving the accuracy, robustness and efficiency of the entire detection system, and enhancing the scalability and adaptability of the system. These advantages enable this technical solution to better meet the requirements of detecting exposed pipe sections of submarine cables in complex seabed environments.

[0072] As a preferred technical means: The point set determination unit traverses each point in the point cloud according to the normal vector and plane equation of the slicing plane. If a specific condition is met, it means that the point is on the slicing plane, thereby obtaining the point set on the slicing plane; The projection processing unit uses the vertical projection relationship and calculates the profile data point set corresponding to the slicing plane through a specific formula.

[0073] This technical solution not only improves the accuracy of data processing through point screening and projection processing, but also enhances the efficiency, robustness and scalability of the system. Through this solution, effective information can be efficiently and accurately extracted and processed from point cloud data, improving the accuracy and automation level of detecting exposed pipe sections of submarine cables.

[0074] As a preferred technical means: The fitting module further includes:

[0075] The ellipse fitting unit assumes that the cross-section of the submarine cable is approximately an ellipse, uses the general form of the ellipse equation for fitting, solves the geometric parameters of the ellipse, and calculates the height of the submarine cable;

[0076] The polynomial fitting unit performs polynomial fitting on the seabed terrain point cloud profile data, and selects the highest point of the fitting segment from the fitted polynomial as the seabed height for subsequent calculation of the storage state of the submarine cable.

[0077] Through the combined use of the ellipse fitting unit and the polynomial fitting unit, the system can efficiently and accurately complete the analysis of submarine cables and seabed topography. This technical solution not only improves the calculation accuracy, automation level, and robustness, but also simplifies the data processing process, enhances the adaptability and scalability of the system, and provides strong technical support for the detection of exposed sections of submarine cables.

[0078] As a preferred technical means: it further includes an output module for outputting the visual detection results and displaying the specific positions and relevant parameters of the exposed sections of submarine cables.

[0079] This technical solution provides an intuitive, convenient, and efficient visual means for the detection of exposed sections of submarine cables. It not only enhances the readability of the detection results, improves the timeliness and accuracy of decision-making, but also provides important support for subsequent monitoring, data analysis, and report generation. Combined with other modules, the output module further enhances the comprehensive performance of the system and promotes the automation, intelligence, and precision of submarine cable monitoring. Specifically:

[0080] The output module can display the detection results in a graphical form, making the specific positions and relevant parameters of the exposed sections of submarine cables clear at a glance. Through intuitive charts or 3D views, users can quickly understand the detection results without the need for complex numerical analysis or processing, greatly improving the user experience. The visual interface clearly shows the positions of the exposed sections of submarine cables and other important information (such as submarine cable height, seabed height difference, occurrence state, etc.) through colors, icons, or markings, enabling relevant personnel to quickly identify problem areas and make timely responses.

[0081] The output module helps operators quickly locate potential risk areas by displaying the specific positions of the exposed sections of submarine cables, thereby improving decision-making efficiency. During the inspection, maintenance, and monitoring of submarine cables, it can accurately identify which areas have potential safety hazards, and then formulate more targeted emergency plans. The visual detection results not only help decision-makers identify current problems, but also provide data support for subsequent analysis and reports. By displaying relevant parameters (such as submarine cable height, seabed height, occurrence state, etc.), further monitoring and trend analysis of submarine cables at different positions can be carried out to ensure long-term safety and reliability.

[0082] The output module can automatically generate visual reports, reducing the time for manual processing and analysis. This is particularly important for the regular inspection of submarine cables, as it can complete data analysis, report generation, and visual display in a very short time, greatly improving work efficiency. By displaying the detection results in real time, the output module can provide instant feedback to the monitoring system, enabling staff to take immediate action when the state of the submarine cable is abnormal. For example, if the submarine cable is exposed or suspended, the system can quickly notify the operator and display the specific position to ensure that the problem is dealt with in a timely manner.

[0083] The output module can display multi-dimensional detection results, such as the specific location of the submarine cable, the height change of the seabed, the change of occurrence state, etc. The multi-angle presentation of these data helps to comprehensively evaluate the safety status of the submarine cable. It can help the monitoring personnel to deeply understand the detection results and conduct a more comprehensive risk analysis than a single numerical report. By showing the specific location and relevant parameters of the exposed pipe section of the submarine cable, the output module helps the detection personnel to grasp the state of the submarine cable as a whole, can more effectively discover potential problem areas, and avoid missing possible risk points.

[0084] The output module can also display historical monitoring data and compare it with the current detection results. This function helps to judge whether the state of the submarine cable has changed and whether the detection trend is deteriorating. The comparison of historical data can also help to judge whether there are new potential hazard areas and whether additional maintenance work is needed. The output module can support long-term monitoring. Through the visual display of multiple detection data, a trend chart with a long time span is formed, which helps the management personnel to monitor the overall health status of the submarine cable, discover potential risks and change trends, and take measures in advance.

[0085] The visual detection results are not only convenient for the operators to understand and process, but also suitable for communication with relevant departments or teams. Through charts, marks, data summaries, etc., the detection situation can be reported to decision-makers, management or relevant parties simply and clearly, helping higher-level decision-makers to master information. The visual output module can be used as the basic data for multi-party collaboration, facilitating different teams or departments to share results and conduct subsequent joint analysis and work deployment. For example, the maintenance team of the submarine cable can quickly understand which areas need to be processed first based on the visual data to ensure a quick response.

[0086] The output module can uniformly generate standardized detection reports, reducing manual intervention and ensuring the standardization and consistency of the reports. This is particularly important for long-term and large-scale monitoring, helping to ensure the detection quality and the accuracy of the reports. The automatically generated detection reports are not only convenient for immediate viewing but also can be archived for a long time, facilitating future viewing and management. The digital format of the reports helps to improve the storage and management efficiency of the data and is convenient for retrieving and analyzing historical data in the future.

[0087] Beneficial effects: Through precise quantitative analysis and efficient automated detection, this technical solution significantly improves the detection accuracy and speed of the exposed pipe section of the submarine cable, which is a key technological breakthrough in the field of submarine cable detection. Specifically

[0088] 1. By performing processing such as profile slicing, ellipse fitting, and polynomial fitting on the point cloud data of submarine cables and the seabed, the occurrence state of submarine cables can be quantitatively calculated, overcoming the limitations of traditional qualitative analysis and providing more accurate and reliable detection results.

[0089] 2. This method greatly improves the automation level of submarine cable detection, reduces the dependence on manual analysis, can quickly and efficiently process large-scale point cloud data, and improves the efficiency and accuracy of detection.

[0090] 3. By fitting the cable profile data with an ellipse and the seabed terrain data with a polynomial, the geometric features of the submarine cable and the height information of the seabed can be accurately extracted. Especially when dealing with curved or complex submarine cables, it has excellent fitting accuracy.

[0091] 4. It can accurately identify abnormal states such as the exposure, suspension, or displacement of submarine cables, timely discover potential safety hazards, and ensure the safety and stability of submarine cables.

[0092] 5. This method can adapt to complex seabed environments. In the monitoring of submarine cables, it can effectively handle different seabed terrains and cable configurations and has a wide range of application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] Figure 1 is a flowchart of the present invention;

[0094] Figure 2 is a schematic diagram of the occurrence state of the submarine cable detected by the present invention;

[0095] Figure 3 is a schematic diagram of the suspended section and exposed section of the submarine cable detected by the present invention;

[0096] Figure 4 is a schematic diagram of the principle of the point cloud slice of the submarine cable with thickness in the present invention;

[0097] Figure 5 is the processing effect of the submarine cable point cloud. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0098] The technical solutions of the present invention will be further described in detail below with reference to the accompanying drawings of the specification.

[0099] Example 1:

[0100] As Figure 1 shown, it is a flowchart of a method for detecting the exposed pipe section of a submarine cable based on point cloud data of the present invention. First, on the basis of obtaining the seabed point cloud data P, the seabed point cloud data P in the point cloud data is separated into cable data PC and seabed terrain data PG by the RANSAC method; then, the cable point cloud PC and the terrain point cloud PG are sliced respectively to obtain the cable profile set {qi} and the terrain profile set {gi}; Then, complete the fitting expression of the profile data points to obtain the submarine cable profile geometric parameters and the ground approximation result, and calculate the set {C i} of the submarine cable center, the set {H i} of the submarine cable height, and the set {G i} of the seabed height; Finally, fit the set {C i} of the submarine cable center, which is the submarine cable trend; According to the relationship between the set {H i} of the submarine cable height and the set {G i} of the seabed height, quantitatively detect the occurrence status. Specifically, it includes the following steps:

[0101] S1: On the basis of obtaining the seabed point cloud data P, separate the seabed point cloud data P in the point cloud data into submarine cable data PC and seabed terrain data PG by the RANSAC method.

[0102] S2: Slice the submarine cable point cloud PC and the terrain point cloud PG respectively to obtain the submarine cable profile set and the terrain profile set.

[0103] The specific point cloud slicing method is as follows:

[0104] S2.1 Given the point cloud data P{P i | i = 1, 2, 3,..., n} and a set of slicing planes {S i | i = 1, 2, 3,..., m}, the distance between the slicing planes is d, as Figure 4 shown; Since the actual points have no size, by the way of intersecting the point cloud with the slicing plane, the point cloud density on the obtained slicing plane is too small. This method introduces the slicing width, and generates two auxiliary planes S i ' and S i " symmetric to S i on both sides of S i . The distance between the two auxiliary planes is the slicing thickness σ w , and the points between S i ' and S i " are used as the contour point cloud set in the cutting plane S i .

[0105] S2.2 Given the normal vector i of the slicing plane S , the plane equation ; Traverse each point P i in the point cloud. If it satisfies , it means that the point is on the slicing plane, and the point set i on the slicing plane S can be obtained.

[0106] S2.3 Project the point set on the slice plane onto the slice plane: For any point P i,j , let its projection point in the slice plane be . Using the perpendicular projection relationship between and the slice plane Si, the solution formula can be obtained:

[0107]

[0108] From this, the profile data point set {q i |j = 1, 2,..., N} corresponding to the slice plane S can be obtained; where, i,j . Here, refers to the vector from point to its projection point .

[0109] S3: Complete the fitting expression of the profile data points: For the profile data of the submarine cable point cloud, perform elliptic curve fitting and obtain the center (x c , y c ) of the submarine cable and the height h pipe of the submarine cable; for the profile data of the ground near the submarine cable, perform polynomial curve fitting to obtain the seabed height h seabed .

[0110] The specific process of processing the profile point cloud in S3 is as follows:

[0111] First, process the slice plane of the submarine cable point cloud. The submarine cable can be approximated as a cylinder, and its slice plane is approximately an ellipse. Therefore, use an ellipse model for fitting. The general form of the ellipse equation is:

[0112]

[0113] Denote the algebraic distance from any point (x, y) to the ellipse as d(x, y), then its expression is

[0114]

[0115] Let

[0116]

[0117]

[0118] Then the ellipse equation can be expressed as ax = 0. Assume the submarine cable profile point set {q i (x i , y i )|i = 1, 2,..., N}, then the best-fitting ellipse should make

[0119]

[0120] To ensure that the obtained result conforms to the ellipse equation, corresponding constraint conditions need to be added when using the least squares method to solve it. . At this time, the general equation of the ellipse is solved. To analyze the submarine cable, it is necessary to solve the geometric parameters of the profile-fitting ellipse, including the semi-major axis a, the semi-minor axis b, the ellipse center coordinates (x c , y c ), and the angle between the major axis and the minor axis. The specific solution formulas are as follows:

[0121]

[0122] where the submarine cable height .

[0123] Secondly, to analyze the occurrence status of the submarine cable, it is necessary to perform fitting analysis on the ground profile data near the submarine cable to predict and estimate the ground height. Here, a polynomial is used for fitting, and the highest point of the fitting segment is selected as the highest point of the seabed h seabed .

[0124] As Figure 5 shown, it is the processing effect of the submarine cable point cloud processed by the present invention, that is, for the profile data of the submarine cable point cloud, elliptic curve fitting is performed; for the ground profile data near the submarine cable, polynomial curve fitting is performed.

[0125] S4: Fit the elliptic center coordinates of each submarine cable profile, which is the submarine cable trend; according to the submarine cable height h pipe , the seabed height h seabed , the occurrence state of the submarine cable can be quantitatively calculated. Define E = h pipe - h seabed . Assume the diameter of the submarine cable is D. When E <= D, it means that part of the submarine cable is exposed or completely exposed. When E i > D, it means that the submarine cable is suspended.

[0126] As Figure 2 , Figure 3 shown, it is a schematic diagram of the occurrence state of the submarine cable detected by the present invention, where the part with a small part of the submarine cable exposed is the exposed pipe section, and the part where the bottom of the submarine cable leaves the ground is the suspended pipe section.

[0127] Embodiment 2:

[0128] Provide a submarine cable exposed pipe section detection system based on point cloud data. The system applies the aforementioned submarine cable exposed pipe section detection method based on point cloud data. The system includes:

[0129] 1. A point cloud data acquisition module, which is used to acquire submarine point cloud data.

[0130] II. Point cloud separation module, which is used to separate the submarine cable point cloud data PC and the seabed terrain point cloud data PG from the seabed point cloud data through the RANSAC method.

[0131] III. Slicing module, which is used to slice the submarine cable point cloud data PC and the seabed terrain point cloud data PG to obtain a set of submarine cable profiles and a set of terrain profiles.

[0132] The slicing module further includes:

[0133] Contour point cloud set generation unit, given point cloud data and a set of slicing planes, generates two symmetric auxiliary planes for each slicing plane, and takes the points between the two auxiliary planes as the contour point cloud set corresponding to the slicing plane;

[0134] Point set determination unit, according to the normal vector and plane equation of the slicing plane, traverses each point in the point cloud data to determine the point set located on the slicing plane; the point set determination unit traverses each point in the point cloud according to the normal vector and plane equation of the slicing plane. If a specific condition is met, it means that the point is on the slicing plane, so as to obtain the point set on the slicing plane; the projection processing unit uses the vertical projection relationship and calculates through a specific formula to obtain the profile data point set corresponding to the slicing plane. Through point screening and projection processing, not only the accuracy of data processing is improved, but also the efficiency, robustness and scalability of the system are enhanced. Through this solution, effective information can be extracted and processed from point cloud data efficiently and accurately, improving the accuracy and automation level of submarine cable exposed pipe section detection.

[0135] Projection processing unit, projects the point set on the slicing plane into the slicing plane to obtain the profile data point set corresponding to the slicing plane.

[0136] Through the refined design of the slicing module, the system has higher accuracy and efficiency in processing seabed point cloud data. The refined processing of each sub-module ensures the accurate extraction and processing of data, thus improving the accuracy, robustness and efficiency of the entire detection system, and enhancing the scalability and adaptability of the system. These advantages enable this technical solution to better meet the requirements of submarine cable exposed pipe section detection in complex seabed environments.

[0137] IV. Fitting module, which is used for:

[0138] Performing ellipse fitting on the submarine cable point cloud profile data in the submarine cable profile set to extract the center (x c , y c ) and the height h of the submarine cable pipe ;

[0139] Performing polynomial fitting on the seabed terrain point cloud profile data in the terrain profile set to obtain the seabed height h seabed ;

[0140] The fitting module correspondingly includes:

[0141] An ellipse fitting unit, assuming that the submarine cable profile is approximately an ellipse, uses the general form of the ellipse equation for fitting, solves the geometric parameters of the ellipse, and calculates the height of the submarine cable;

[0142] A polynomial fitting unit performs polynomial fitting on the seabed terrain point cloud profile data, and selects the highest point of the fitting segment from the fitted polynomial as the seabed height for subsequent calculation of the storage state of the submarine cable.

[0143] By using the ellipse fitting unit and the polynomial fitting unit in combination, the system can efficiently and accurately complete the analysis of the submarine cable and the seabed terrain. This technical solution not only improves the calculation accuracy, automation level and robustness, but also simplifies the data processing process, enhances the adaptability and scalability of the system, and provides strong technical support for the detection of exposed sections of submarine cables.

[0144] V. A storage state calculation module, used to quantitatively calculate the storage state of the submarine cable according to the difference E between the submarine cable height h seabed and the seabed height h seabed and determine whether the submarine cable is exposed or suspended.

[0145] VI. An output module, used to output the visual detection result, display the specific position and relevant parameters of the exposed section of the submarine cable. It provides an intuitive, convenient and efficient visual means for the detection of exposed sections of submarine cables. It not only enhances the readability of the detection result, improves the timeliness and accuracy of decision-making, but also provides important support for subsequent monitoring, data analysis and report generation. Combined with other modules, the output module further enhances the comprehensive performance of the system and promotes the automation, intelligence and precision of submarine cable monitoring.

[0146] Through automated data processing, accurate fitting algorithms, and quantitative assessment of the storage state, this embodiment can efficiently and accurately detect exposed sections of submarine cables. The system has high adaptability, low error rate and good scalability, providing reliable technical guarantee for the monitoring and maintenance of submarine cables.

[0147] It can be understood that the detailed function implementation of each of the above modules can refer to the introduction in the foregoing method embodiment, and no other elaboration will be made here.

[0148] Embodiment III:

[0149] All functions that can be achieved by a submarine cable exposed pipe section detection system based on point cloud data can be completed by a computer device. The computer device includes one or more processors and one or more memories. At least one program code is stored in the one or more memories, and the program code is loaded and executed by the one or more processors to implement the wireless signal processing method.

[0150] The processor fetches instructions one by one from the memory, analyzes the instructions, and then completes corresponding operations according to the requirements of the instructions, generating a series of control commands to make all parts of the computer act automatically, continuously and coordinately, becoming an organic whole, realizing the input of the program, the input of data, and the operation and output of results. All arithmetic operations or logical operations generated in this process are completed by the arithmetic unit; the memory includes a read-only memory (ROM), and the read-only memory is used to store computer programs. A protection device is provided outside the memory.

[0151] Exemplarily, the computer program can be divided into one or more modules. One or more modules are stored in the memory and executed by the processor to complete the present invention. One or more modules can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0152] Those skilled in the art can understand that the description of the above service device is only an example and does not constitute a limitation on the terminal device. It may include more or fewer components than the above description, or combine some components, or different components. For example, it may include input / output devices, network access devices, buses, etc.

[0153] The so-called processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The above processor is the control center of the above terminal device, and uses various interfaces and lines to connect all parts of the entire user terminal.

[0154] The above-mentioned memory can be used to store computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory, the above-mentioned terminal device can realize various functions. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as information collection template display function, product information release function, etc.); the data storage area can store data created according to the use of the berth status display system (such as product information collection templates corresponding to different product categories, product information to be released by different product providers, etc.). In addition, the memory can include high-speed random access memory and can also include non-volatile memory, such as hard disks, memory, plug-in hard disks, smart media cards (SMC), secure digital (SD) cards, flash cards, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices.

[0155] If the modules / units integrated in the terminal device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable medium. Based on this understanding, to implement all or part of the modules / units in the above-mentioned embodiment system of the present invention, it can also be completed by instructing relevant hardware through a computer program. The above-mentioned computer program can be stored in a computer-readable medium. When the computer program is executed by a processor, it can realize the functions of the above-mentioned various system embodiments. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The storage medium can be a computer-readable medium, and the computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0156] The above-described method and system for detecting exposed pipe sections of submarine cables based on point cloud data are specific embodiments of the present invention, which have already reflected the substantial features and progress of the present invention. According to actual usage needs, under the inspiration of the present invention, equivalent modifications can be made to its shape, structure, etc., and all are within the protection scope of this solution.

Claims

1. A method for detecting exposed sections of submarine cables based on point cloud data, characterized in that The following steps are involved: 1) Obtain seabed point cloud data P, and separate submarine cable point cloud data PC and seabed terrain point cloud data PG from the seabed point cloud data using the RANSAC method; 2) Slice the submarine cable point cloud data PC and the seabed terrain point cloud data PG to obtain the submarine cable profile set and the terrain profile set; 3) Perform ellipse fitting on the submarine cable point cloud profile data in the submarine cable profile set to extract the center of the submarine cable (x c ,y c ) and the cable height h pipe ; Perform polynomial fitting on the seafloor topography point cloud profile data in the topographic profile set to obtain the seafloor height h seabed ; 4) According to the height h of the submarine cable pipe and seafloor height h seabed The difference E of the cable is used to quantitatively calculate the cable's state of existence. If E≤d, it means the cable is exposed or completely exposed. If E>d, it means the cable is suspended in the air, where d is the cable's diameter. Step 3) Include: 3.1) Ellipse fitting of submarine cable point cloud profile data: Assuming that the cross section of the submarine cable is approximately an ellipse, the cross section point set of the submarine cable {q i (x i ,y i )|i=1,2,...,N} is the slice plane data of the submarine cable point cloud; The fit is done using the general form of the equation of an ellipse, which is as follows: Among them, A, B, C, D, E, and F are fitting parameters, and Δ is the discriminant; For each point (x i ,y i ), calculate its algebraic distance d(x,y) to the ellipse, which is: Use the least squares method to fit the parameters of the ellipse, with the goal of minimizing the sum of the algebraic distances of all points: in, , is the parameter vector of the ellipse equation; , for the point (x i ,y i )’s feature vector; Solve the geometric parameters of the ellipse, including the semi-major axis a, the semi-minor axis b, the coordinates of the center of the ellipse (x c ,y c ), the angle between the major axis and the minor axis; the calculation formulas for these parameters are as follows: Calculating the height of a submarine cable , which is the longitudinal coordinate of the center of the cable section plus the length of the semi-minor axis; 3.2) Polynomial fitting of terrain point cloud profile data: Perform polynomial fitting on the terrain profile point cloud data near the submarine cable; select the highest point of the fitting segment from the fitted polynomial as the seabed height h seabed , which is used for the subsequent calculation of the submarine cable existence status.

2. The method for detecting exposed submarine cable sections based on point cloud data according to claim 1, characterized in that: In step 2), by setting the slice plane and the auxiliary plane, the cross-section point cloud set is obtained by intersecting the point cloud with the slice plane, and the cross-section point cloud is projected to obtain the cross-section data point set corresponding to the slice plane; The slicing process in step 2) includes the following: 2.1) Given point cloud data P{P i |i=1,2,3,...,n} and a set of slice planes {S i |i=1,2,3,...,m}, for each slice plane S i Generate two symmetrical auxiliary planes S i ' and S i ", the distance between the two auxiliary planes is the slice thickness σ, and S i ' and S i The point between them is taken as the slice plane S i The corresponding contour point cloud set; 2.2) According to the slice plane S i The normal vector and plane equation are used to traverse each point in the point cloud data P and determine the point set corresponding to the slice plane Si; 2.3) Set the slice plane S i The point set on the slice plane is projected onto the slice plane to obtain the slice plane S i The corresponding profile data point set.

3. The method for detecting exposed submarine cable sections based on point cloud data according to claim 2, characterized in that: In step 2.2), according to the slice plane S i The normal vector , plane equation n1x+n2y+n3z+n0=0, traverse each point P in the point cloud i , if satisfied , which means that the point is on the slice plane, and the slice plane S is obtained. i The point set on ; In step 2.3), the point set on the slice plane is projected into the slice plane. For any P i,j , let its projection point in the slice plane be ,use With the slice plane S i The vertical projection relationship is given by the following formula: Calculate the slice plane S i The corresponding profile data point set {q i,j |j=1,2,...,N}; where It is a pointer To its projection point Vector.

4. A submarine cable exposed pipe section detection system based on point cloud data, characterized in that: A method for detecting exposed pipe sections of submarine cables based on point cloud data as described in any one of claims 1 to 3 is applied, wherein the system comprises: Point cloud data acquisition module, used to acquire seabed point cloud data; A point cloud separation module is used to separate the submarine cable point cloud data PC and the seabed terrain point cloud data PG from the seabed point cloud data by using the RANSAC method; The slicing module is used to slice the submarine cable point cloud data PC and the seabed terrain point cloud data PG to obtain the submarine cable profile set and the terrain profile set; Fitting module for: Perform ellipse fitting on the submarine cable point cloud profile data in the submarine cable profile set to extract the center of the submarine cable (x c ,y c ) and the cable height h pipe ; Perform polynomial fitting on the seafloor topography point cloud profile data in the topographic profile set to obtain the seafloor height h seabed ; The existence state calculation module is used to calculate the cable height h seabed and seafloor height h seabed The difference E is used to quantitatively calculate the existence status of the submarine cable and determine whether the submarine cable is exposed or suspended.

5. The submarine cable exposed pipe section detection system based on point cloud data according to claim 1 is characterized in that: The slicing module further comprises: The contour point cloud set generating unit, given the point cloud data and a set of slice planes, generates two symmetrical auxiliary planes for each slice plane, and uses the points between the two auxiliary planes as the contour point cloud set corresponding to the slice plane; A point set determination unit, which traverses each point in the point cloud data according to the normal vector and plane equation of the slice plane, and determines the point set located on the slice plane; The projection processing unit projects the point set on the slice plane into the slice plane to obtain the section data point set corresponding to the slice plane.

6. The submarine cable exposed pipe section detection system based on point cloud data according to claim 5 is characterized by: The point set determination unit traverses each point in the point cloud according to the normal vector and the plane equation of the slice plane, thereby obtaining a point set on the slice plane; The projection processing unit uses the vertical projection relationship through the formula: Calculate and obtain the cross-section data point set corresponding to the slice plane; Among them, the point set on the slice plane is: ; For any , and its projection point in the slice plane is: ; The normal vector of the slice plane is: ;The plane equation is: n1x+n2y+n3z+n0=0.

7. The submarine cable exposed pipe section detection system based on point cloud data according to claim 4 is characterized by: The fitting module further comprises: The ellipse fitting unit assumes that the cross section of the submarine cable is approximately an ellipse, uses the general form of the ellipse equation to fit, solves the geometric parameters of the ellipse, and calculates the height of the submarine cable; The polynomial fitting unit performs polynomial fitting on the seabed topography point cloud profile data, and selects the highest point of the fitting segment from the fitted polynomial as the seabed height for the subsequent calculation of the submarine cable existence status.

8. The submarine cable exposed pipe section detection system based on point cloud data according to claim 4 is characterized by: It also includes an output module for outputting visual detection results to display the specific location and relevant parameters of the exposed pipe section of the submarine cable.

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