Pipeline fracture three-dimensional reconstruction method and device, electronic equipment and storage medium

Abstract

This application provides a method, apparatus, electronic device, and storage medium for three-dimensional reconstruction of pipeline fractures, relating to the field of pipeline safety. The method includes: acquiring three-dimensional data of an oil and gas pipeline fracture, an image of the oil and gas pipeline fracture, and material property data of the oil and gas pipeline fracture, wherein the material property data indicates the material property data corresponding to the boundary of the oil and gas pipeline fracture; constructing a visual shell model of the oil and gas pipeline fracture based on the three-dimensional data and the image of the oil and gas pipeline fracture; obtaining a triangular mesh model based on the visual shell model and the material property data using the Delaunay triangulation algorithm; and correcting the vertices of the triangular mesh model to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture, wherein the three-dimensional reconstruction model is used to characterize the shape of the oil and gas pipeline fracture and the material properties corresponding to each location within the oil and gas pipeline fracture. This application can improve the accuracy of the three-dimensional reconstruction model of oil and gas pipeline fractures.

Description

Technical Field

[0001] This application relates to the field of pipeline safety, and in particular to a method, apparatus, electronic device and storage medium for three-dimensional reconstruction of pipeline fractures. Background Technology

[0002] In response to oil and gas pipeline rupture failure accidents, how to conduct scientific and objective analysis of the causes of failure has become a focus of attention in the oil and gas pipeline field. Constructing a three-dimensional model of the oil and gas pipeline fracture surface can provide a basis for the analysis of these accidents. However, the accuracy of current three-dimensional models of oil and gas pipeline fracture surfaces is relatively low. Summary of the Invention

[0003] This application provides a method, apparatus, electronic device, and storage medium for three-dimensional reconstruction of pipeline fractures, which can improve the accuracy of three-dimensional reconstruction models of oil and gas pipeline fractures.

[0004] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application provides a method for three-dimensional reconstruction of pipeline fractures. The method includes: acquiring three-dimensional data of the oil and gas pipeline fracture, an image of the oil and gas pipeline fracture, and material property data of the oil and gas pipeline fracture, wherein the material property data is used to indicate the material property data corresponding to the boundary of the oil and gas pipeline fracture; constructing a visual shell model of the oil and gas pipeline fracture based on the three-dimensional data and the image of the oil and gas pipeline fracture; obtaining a triangular mesh model based on the visual shell model and the material property data using the Delaunay triangulation algorithm; and correcting the vertices of the triangular mesh model to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture, wherein the three-dimensional reconstruction model is used to characterize the shape of the oil and gas pipeline fracture and the material properties corresponding to each location within the oil and gas pipeline fracture.

[0005] In conjunction with the first aspect mentioned above, in one possible implementation, the vertices of the triangular mesh model are modified to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture. This includes: projecting each vertex in the triangular mesh model to obtain multiple vertex projection positions; determining the cross-correlation coefficient of each vertex based on its grayscale value and the grayscale value of the neighborhood window corresponding to its projection position, wherein the neighborhood window corresponding to each vertex's projection position includes the vertex's projection position, and the cross-correlation coefficient is used to characterize whether the grayscale value of the vertex is consistent with the grayscale value of the neighborhood window; identifying the vertex as a distortion point if the cross-correlation coefficient is less than a cross-correlation threshold; and adjusting the position of the distortion point to obtain the three-dimensional reconstruction model of the oil and gas pipeline fracture.

[0006] In conjunction with the first aspect mentioned above, in one possible implementation, the position of the distortion point is adjusted to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture. This includes: determining the target vertex among the non-distortion points with the distortion point as the center; performing a weighted average of the position of the target vertex and the cross-correlation coefficient of the target vertex to obtain the adjusted position, which is used to correct the distortion point; and constructing a three-dimensional reconstruction model of the oil and gas pipeline fracture based on the adjusted position and the positions of the non-distortion points.

[0007] In conjunction with the first aspect above, in one possible implementation, the method further includes: readjusting the adjustment positions when adjustment conditions are met; wherein the adjustment conditions satisfy at least one of the following: the cross-correlation coefficient of the adjustment positions is less than the cross-correlation threshold; the ratio of the number of adjustment positions with cross-correlation coefficients less than the cross-correlation threshold to the total number of vertices in the 3D reconstruction model is greater than the ratio threshold; the mean of the cross-correlation coefficients of all vertices in the 3D reconstruction model is less than the mean threshold; and the number of adjustments to the distortion points is less than or equal to the number of adjustments threshold.

[0008] In conjunction with the first aspect mentioned above, in one possible implementation, a visual shell model of an oil and gas pipeline fracture is constructed based on the 3D data and image of the fracture. This includes: projecting the 3D data and corresponding 2D data of the oil and gas pipeline fracture image onto multiple projection planes to obtain point cloud data of the oil and gas pipeline fracture; constructing a bounding box based on the point cloud data of the oil and gas pipeline fracture, the bounding box being used to enclose the point cloud data of the oil and gas pipeline fracture in 3D space; performing voxelization processing on the bounding box according to a preset voxel resolution to obtain multiple voxels; projecting each voxel onto multiple projection planes to obtain a projected image of the voxel; determining the voxel as a target voxel in response to the overlap between the projected image of the voxel and the region formed by the fracture contour of the oil and gas pipeline fracture; constructing a voxel set based on the target voxels; and performing morphological closing operations on the voxel set to obtain the visual shell model.

[0009] In conjunction with the first aspect mentioned above, in one possible implementation, a triangular mesh model is obtained based on the visual shell model and material property data using the Delaunay triangulation algorithm. This includes: constructing a set of points to be interpolated based on the surface point cloud and material property data of the visual shell model. The set of points to be interpolated includes multiple points, which are used to characterize each point cloud on the surface of the visual shell model and its corresponding material properties; filling the set of points to be interpolated using the Delaunay triangulation algorithm to obtain multiple triangular planes, each of which represents a portion of the fracture surface of an oil and gas pipeline; and constructing a triangular mesh model based on the multiple triangular planes.

[0010] Secondly, this application provides a three-dimensional reconstruction device for pipeline fractures. The device includes: an acquisition unit for acquiring three-dimensional data of an oil and gas pipeline fracture, an image of the oil and gas pipeline fracture, and material property data of the oil and gas pipeline fracture, wherein the material property data is used to indicate the material property data corresponding to the boundary of the oil and gas pipeline fracture; a construction unit for constructing a visual shell model of the oil and gas pipeline fracture based on the three-dimensional data and the image of the oil and gas pipeline fracture; an interpolation unit for obtaining a triangular mesh model based on the visual shell model and the material property data using the Delaunay triangulation algorithm; and a correction unit for correcting the vertices of the triangular mesh model to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture, wherein the three-dimensional reconstruction model is used to characterize the shape of the oil and gas pipeline fracture and the material properties corresponding to each position in the oil and gas pipeline fracture.

[0011] In conjunction with the second aspect above, in one possible implementation, the correction unit is used to: project each vertex in the triangular mesh model to obtain multiple vertex projection positions; for each vertex projection position among the multiple vertex projection positions, based on the grayscale of each vertex and the grayscale of the neighborhood window corresponding to the projection position of each vertex, the neighborhood window corresponding to the projection position of each vertex includes the projection position of the vertex, and the cross-correlation number is used to characterize whether the grayscale of the vertex is consistent with the grayscale of the neighborhood window; in response to the cross-correlation number being less than the cross-correlation threshold, the vertex is identified as a distortion point; the position of the distortion point is adjusted to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture.

[0012] In conjunction with the second aspect above, in one possible implementation, the correction unit is used to: determine the target vertex among the non-distortion points with the distortion point as the center; perform a weighted average of the position of the target vertex and the cross-correlation coefficient of the target vertex to obtain the adjusted position, which is used to correct the distortion point; and construct a three-dimensional reconstruction model of the oil and gas pipeline fracture based on the adjusted position and the positions of the non-distortion points.

[0013] In conjunction with the second aspect above, in one possible implementation, the device further includes: an adjustment unit, configured to readjust the adjustment positions when adjustment conditions are met; wherein the adjustment conditions satisfy at least one of the following: the cross-correlation coefficient of the adjustment positions is less than a cross-correlation threshold; the ratio of the number of adjustment positions with cross-correlation coefficients less than the cross-correlation threshold to the total number of vertices in the 3D reconstruction model is greater than a ratio threshold; the mean cross-correlation coefficient of all vertices in the 3D reconstruction model is less than a mean threshold; and the number of adjustments to the distortion points is less than or equal to a number threshold.

[0014] In conjunction with the second aspect above, in one possible implementation, the construction unit is used to: project the three-dimensional data of the oil and gas pipeline fracture and the corresponding two-dimensional data of the oil and gas pipeline fracture image onto multiple projection planes to obtain point cloud data of the oil and gas pipeline fracture; construct a bounding box based on the point cloud data of the oil and gas pipeline fracture, the bounding box being used to enclose the point cloud data of the oil and gas pipeline fracture in three-dimensional space; perform voxelization processing on the bounding box according to a preset voxel resolution to obtain multiple voxels; project each voxel onto multiple projection planes to obtain a projected image of the voxel; in response to the overlap between the projected image of the voxel and the region formed by the fracture contour of the oil and gas pipeline fracture, determine the voxel as the target voxel; construct a voxel set based on the target voxels, and perform morphological closing operations on the voxel set to obtain a visual shell model.

[0015] In conjunction with the second aspect above, in one possible implementation, the interpolation unit is used to: construct a set of points to be interpolated based on the surface point cloud and material property data of the visual shell model. The set of points to be interpolated includes multiple points to be interpolated, which are used to characterize each point cloud on the surface of the visual shell model and its corresponding material properties; fill the set of points to be interpolated using the Delaunay triangulation algorithm to obtain multiple triangular planes, each of which is a partial surface of the oil and gas pipeline fracture; and construct a triangular mesh model based on the multiple triangular planes.

[0016] Thirdly, this application provides an electronic device, including: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run computer programs or instructions to implement the three-dimensional reconstruction method of pipe fracture as described in the first aspect and any possible implementation of the first aspect.

[0017] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the pipe fracture three-dimensional reconstruction method as described in the first aspect and any possible implementation thereof.

[0018] Fifthly, this application provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the pipe fracture three-dimensional reconstruction method as described in the first aspect and any possible implementation thereof.

[0019] In a sixth aspect, this application provides a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run computer programs or instructions to implement the pipe fracture three-dimensional reconstruction method as described in the first aspect and any possible implementation thereof.

[0020] Specifically, the chip provided in this application also includes a memory for storing computer programs or instructions.

[0021] It should be noted that the aforementioned computer instructions may be stored, in whole or in part, on a computer-readable storage medium. This computer-readable storage medium may be packaged together with the processor of the device, or it may be packaged separately from the processor of the device; this application does not impose any limitation on this.

[0022] The descriptions of the second to sixth aspects in this application can be referenced to the detailed description of the first aspect; and the beneficial effects of the descriptions of the second to sixth aspects can be referenced to the analysis of the beneficial effects of the first aspect, which will not be repeated here.

[0023] In this application, the name of the aforementioned three-dimensional reconstruction device for pipe fractures does not limit the equipment or functional modules themselves. In actual implementation, these devices or functional modules may appear under other names. As long as the functions of each device or functional module are similar to those in this application, they fall within the scope of the claims of this application and their equivalents.

[0024] These or other aspects of this application will become more readily apparent in the following description.

[0025] The three-dimensional reconstruction method for pipeline fractures provided in this application improves the consistency between the three-dimensional reconstruction model and the actual oil and gas pipeline fracture by constructing a visual shell model, determining a triangular mesh model, and correcting vertices. This enhances the accuracy of the three-dimensional reconstruction model of the oil and gas pipeline fracture, provides a basis for finding key vulnerable points of pipeline fractures, improves the level of oil and gas pipeline failure analysis, enables the digital preservation of accident investigation data, and provides standardized, systematic, and scientific means for accident investigation. Attached Figure Description

[0026] Figure 1 A flowchart of a method for three-dimensional reconstruction of a pipeline fracture provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of a three-dimensional reconstruction device for a pipe fracture provided in an embodiment of this application; Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0029] The terms "first" and "second," etc., used in the specification and drawings of this application are used to distinguish different objects or to distinguish different treatments of the same object, rather than to describe a specific order of objects.

[0030] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0031] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0032] In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0033] Long-distance oil and gas pipelines are vital national energy infrastructure projects. Due to the high pressure and large diameter of these pipelines, their failure can cause severe economic and social impacts. For example, the natural gas leak and explosion in Selangor, Malaysia in April 2025 caused enormous losses. Domestically, with the large-scale construction and commissioning of high-strength, large-diameter pipelines, pipeline cracking and leakage accidents are also increasing.

[0034] In response to oil and gas pipeline rupture failure accidents, how to conduct scientific and objective analysis of the causes of failure has become a focus of attention in the oil and gas pipeline field. Currently, oil and gas pipeline rupture failure analysis mainly relies on traditional analytical testing techniques, such as microstructure analysis, composition analysis, and mechanical property analysis. Tensile testing, impact testing, hardness testing, metallographic analysis, chemical composition analysis, scanning electron microscopy, and transmission electron microscopy are commonly used as auxiliary methods in the analysis of oil and gas pipeline rupture failures.

[0035] However, due to the complex structure of oil and gas pipelines, the diverse failure modes, and the multi-factor coupling of failure mechanisms, current analysis techniques cannot adequately explain the causes of failure, identify the key vulnerabilities in pipeline failure, or solve the quality and safety problems encountered in research and engineering.

[0036] The three-dimensional reconstruction method for pipeline fractures provided in this application improves the consistency between the three-dimensional reconstruction model and the actual oil and gas pipeline fracture by constructing a visual shell model, determining a triangular mesh model, and correcting vertices. This enhances the accuracy of the three-dimensional reconstruction model of the oil and gas pipeline fracture, provides a basis for finding key vulnerable points of pipeline fractures, improves the level of oil and gas pipeline failure analysis, enables the digital preservation of accident investigation data, and provides standardized, systematic, and scientific means for accident investigation.

[0037] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0038] It should be noted that the various embodiments of this application can be referenced or learned from each other. For example, the same or similar steps, method embodiments, system embodiments and device embodiments can be referenced from each other without limitation.

[0039] Figure 1 This is a flowchart illustrating a method for three-dimensional reconstruction of a pipe fracture, as provided in an embodiment of this application. Figure 1 As shown, the three-dimensional reconstruction method for the pipe fracture includes: S101. Obtain three-dimensional data of the oil and gas pipeline fracture, images of the oil and gas pipeline fracture, and material property data of the oil and gas pipeline fracture.

[0040] For example, the three-dimensional data of the oil and gas pipeline fracture includes three-dimensional macroscopic data, three-dimensional mesoscopic data and three-dimensional microscopic data of the oil and gas pipeline fracture.

[0041] For example, a 3D laser scanner can be used to scan the fracture surface of an oil and gas pipeline to obtain 3D macroscopic data of the fracture. The 3D laser scanner has a detection accuracy of ≤0.03mm, a depth of field of ≥200mm, and a measurement rate of 480,000 measurements per second.

[0042] For example, three-dimensional mesoscopic data of oil and gas pipeline fractures can be acquired using a three-dimensional ultra-depth-of-field microscope. The depth of field of the three-dimensional ultra-depth-of-field microscope is ≥50mm.

[0043] For example, laser confocal microscopy is used to acquire three-dimensional microscopic data of fractures in oil and gas pipelines. The resolution of the laser confocal microscope is at the micrometer level.

[0044] For example, images of oil and gas pipeline fractures are acquired using field emission scanning electron microscopy with a tungsten filament. The images of the oil and gas pipeline fractures include morphological features at magnifications of 100x, 200x, 500x, and 800-1500x.

[0045] Material property data is used to indicate the material property data corresponding to the fracture boundary of an oil and gas pipeline.

[0046] For example, material property data of oil and gas pipeline fractures can be obtained using tensile testing machines, pendulum impact testing machines, etc.

[0047] S102. Based on the 3D data and images of the oil and gas pipeline fracture, construct a visual shell model of the oil and gas pipeline fracture.

[0048] S103. Based on the visual shell model and material property data, a triangular mesh model is obtained through the Delaunay triangulation algorithm.

[0049] S104. Correct the vertices of the triangular mesh model to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture.

[0050] Among them, the three-dimensional reconstruction model is used to characterize the shape of the oil and gas pipeline fracture and the material properties corresponding to each location in the oil and gas pipeline fracture.

[0051] The three-dimensional reconstruction method for pipeline fractures provided in this application improves the consistency between the three-dimensional reconstruction model and the actual oil and gas pipeline fracture by constructing a visual shell model, determining a triangular mesh model, and correcting vertices. This enhances the accuracy of the three-dimensional reconstruction model of the oil and gas pipeline fracture, provides a basis for finding key vulnerable points of pipeline fractures, improves the level of oil and gas pipeline failure analysis, enables the digital preservation of accident investigation data, and provides standardized, systematic, and scientific means for accident investigation.

[0052] In some embodiments, the above-mentioned correction of the vertices of the triangular mesh model to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture includes: projecting each vertex in the triangular mesh model to obtain multiple vertex projection positions; determining the cross-correlation coefficient of each vertex based on the gray level of each vertex and the gray level of the neighborhood window corresponding to the projection position of each vertex, wherein the neighborhood window corresponding to the projection position of each vertex includes the projection position of the vertex, and the cross-correlation coefficient is used to characterize whether the gray level of the vertex is consistent with the gray level of the neighborhood window; determining the vertex as a distortion point in response to the cross-correlation coefficient being less than the cross-correlation threshold; and adjusting the position of the distortion point to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture.

[0053] For example, taking the projection of one vertex from a set of multiple vertices as an example, the vertices in the triangular mesh model are projected... ( , , Projected onto the k-th projection plane I through projection matrix P. k In the middle, the projected position of the vertex is obtained ( , ). Based on the projected position of the vertex ( , Centered on a vertex, a 5×5 pixel region is selected as the neighborhood window corresponding to the projection position of that vertex.

[0054] The cross-correlation coefficient of this vertex satisfies the following formula 1.

[0055] Formula 1 In the formula, Represents the vertex in the k-th projection plane The cross-correlation coefficient; the cross-correlation coefficient of vertices in a triangular mesh model can be used to measure the performance of the triangular mesh model. Place and No. The consistency of each projection plane in lighting / texture, with a range of values. The closer The better the consistency. Let represent the i-th vertex in the triangular mesh model. u and v represent the x and y coordinates of pixels within the neighborhood window, respectively. W represents the vertex. The neighborhood window corresponding to the projection position. This represents the grayscale value of the k-th projection plane at pixel (u,v). This represents the grayscale value of pixel (u,v) when the triangular mesh model is rendered onto the k-th projection plane, which is the simulated grayscale value of the triangular mesh model after projection. Let represent the average gray level of the k-th projection plane within the neighborhood window W. Where, This represents the average gray value of the triangular mesh model projected onto the neighborhood window W. Wherein, .

[0056] For example, the cross-correlation threshold is 0.75.

[0057] When the cross-correlation coefficient is less than the cross-correlation threshold, the vertex is identified as a distorted point; when the cross-correlation coefficient is greater than or equal to the cross-correlation threshold, the vertex is identified as a non-distorted point.

[0058] By identifying distortion points based on the grayscale values ​​of vertices in the triangular mesh model and adjusting their positions, severely distorted surface areas such as reflections and occlusions can be eliminated. This improves the consistency between the 3D reconstruction model and the actual oil and gas pipeline fracture, reduces errors, and provides a more reliable visualization model for subsequent oil and gas pipeline fracture analysis.

[0059] In some embodiments, adjusting the position of the distortion point to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture includes: determining a target vertex among the non-distortion points with the distortion point as the center; performing a weighted average of the position of the target vertex and the cross-correlation coefficient of the target vertex to obtain an adjusted position, which is used to correct the distortion point; and constructing a three-dimensional reconstruction model of the oil and gas pipeline fracture based on the adjusted position and the positions of the non-distortion points.

[0060] For example, for each distortion point, if the non-distortion points in the neighborhood window are determined as the target vertices with the distortion point as the center, then the position adjustment satisfies the following formula 2.

[0061] Formula 2 In the formula, Indicates distortion point Adjust the position; Indicates the position of the target vertex; Represents the set of vertices consisting of all non-distorted points within the neighborhood window of the distorted point; Represents the target vertex in the k-th projection plane. The cross-correlation coefficient.

[0062] Adjusting the position of distortion points based on non-distortion points allows for adjustments using neighborhood information without significantly disrupting the mesh structure, resulting in more accurate adjustments.

[0063] In some embodiments, the method further includes: readjusting the adjustment position if the adjustment conditions are met.

[0064] The adjustment conditions must meet at least one of the following: The cross-correlation coefficient of the adjusted position is less than the cross-correlation threshold; The ratio of the number of adjustment positions with cross-correlation coefficients less than the cross-correlation threshold to the total number of vertices in the 3D reconstruction model is greater than the ratio threshold. The mean cross-correlation coefficient of all vertices in the 3D reconstruction model is less than the mean threshold. The number of adjustments to the distortion points is less than or equal to the number of adjustments threshold.

[0065] For example, the ratio threshold is 3%. For example, the mean threshold is 0.85. For example, the frequency threshold is 3, 5, etc.

[0066] Clearly defining the adjustment conditions provides a basis for judging the adjustment position. By continuously adjusting the adjustment position, the accuracy of the 3D reconstruction model can be improved.

[0067] In some embodiments, the above-mentioned construction of a visual shell model of an oil and gas pipeline fracture based on the three-dimensional data and image of the oil and gas pipeline fracture includes: projecting the three-dimensional data and the corresponding two-dimensional data of the oil and gas pipeline fracture image onto multiple projection planes to obtain point cloud data of the oil and gas pipeline fracture; constructing a bounding box based on the point cloud data of the oil and gas pipeline fracture, the bounding box being used to enclose the point cloud data of the oil and gas pipeline fracture in three-dimensional space; performing voxelization processing on the bounding box according to a preset voxel resolution to obtain multiple voxels; projecting each voxel onto multiple projection planes to obtain a projected image of the voxel; in response to the overlap between the projected image of the voxel and the region formed by the fracture contour of the oil and gas pipeline fracture, determining the voxel as a target voxel; constructing a voxel set based on the target voxels, and performing morphological closing operations on the voxel set to obtain a visual shell model.

[0068] For example, the point cloud data of the oil and gas pipeline fracture is converted to a polar coordinate system. A bounding box is constructed using a point in the point cloud data as the center and the point farthest from the center point as the boundary point. Wherein, the bounding box Ω = [ , ]×[ , ]×[ , ].

[0069] in, , as well as These are the x, y, and z coordinates of the center point in the world coordinate system, respectively. , as well as These are the x, y, and z coordinates of the boundary point in the world coordinate system.

[0070] To avoid losing the break point edge, the boundary length of the bounding box is extended. For example, by 10%.

[0071] The preset voxel resolution can be a fixed value or it can be obtained based on the scanning accuracy. For example, if the voxel side length d = 0.015 mm is set based on the laser scanner accuracy (≤0.03 mm), then the bounding box is divided into N1×N2×N3 voxels.

[0072] Where N1=ceil(( - ) / d); N2=ceil(( - ) / d); N3=ceil(( - ) / d). ceil is the floor function.

[0073] For example, all voxels {v n |n=1,2,…,N1×N2×N3} is labeled as an internal voxel. For each voxel v n Through the projection function (Based on projection matrix M) k The projection is applied to the k-th projection plane. The projection function is based on the projection matrix M. k Construction. If the projected image of the obtained voxel is completely located in the region S formed by the fracture contour. k Externally, it is labeled as an external voxel; if the region S formed by the projected image of the obtained voxel and the fracture contour is... k If overlap exists, it is marked as a target voxel. The voxel set consisting of target voxels is then H = { | ∈Target voxel}.

[0074] Perform morphological closing operations on the voxel set (kernel size 3×3×3 voxels) to fill tiny holes and output a visual shell model.

[0075] For example, when projecting the two-dimensional data corresponding to the image of the oil and gas pipeline fracture, the two-dimensional data can be mapped to a three-dimensional plane first, and then projected to multiple projection planes.

[0076] By constructing a visual shell model, a closed and continuous three-dimensional approximate model can be obtained using two-dimensional information from multiple perspectives, providing a model foundation for subsequent three-dimensional reconstruction.

[0077] In one possible implementation, the above-mentioned projection of the three-dimensional data of the oil and gas pipeline fracture and the corresponding two-dimensional data of the oil and gas pipeline fracture image onto multiple projection planes to obtain the point cloud data of the oil and gas pipeline fracture includes: unifying the three-dimensional data of the oil and gas pipeline fracture and the corresponding two-dimensional data of the oil and gas pipeline fracture image into the same coordinate system to obtain unified three-dimensional data and unified two-dimensional data; removing noise data and performing regularization processing on the unified three-dimensional data and unified two-dimensional data to obtain regularized three-dimensional data and regularized two-dimensional data; and projecting the regularized three-dimensional data and regularized two-dimensional data onto multiple projection planes to obtain the point cloud data of the oil and gas pipeline fracture.

[0078] For example, a unified world coordinate system is constructed. The origin O is set at the center point of the oil and gas pipeline fracture plane, the fracture plane is the XY plane, and the direction perpendicular to the fracture plane is the Z-axis. The coordinate system accuracy is 0.001 mm. The unified 3D data and unified 2D data are obtained by calculating the 3D data and corresponding 2D data of the oil and gas pipeline fracture image using rotation matrices and translation vectors. For example, the unified 3D data and unified 2D data satisfy the following formula 3.

[0079] Pworld=R Pdevice+t formula 3 In the formula, Pworld represents the unified three-dimensional data or the unified two-dimensional data; R represents the rotation matrix; Pdevice represents the three-dimensional data of the oil and gas pipeline fracture or the two-dimensional data corresponding to the image of the oil and gas pipeline fracture; and t represents the translation vector.

[0080] To improve data accuracy, the coordinates can be fine-tuned using the iterative closest point (ICP) algorithm. Based on the overlapping area of ​​multi-view data, the algorithm iterates until the alignment error is ≤0.01mm, ensuring the consistency of the data in spatial location.

[0081] Based on the actual dimensional measurements of oil and gas pipeline fractures, an effective region is defined in a unified world coordinate system. The unified 3D and 2D data are then evaluated point-by-point; points falling outside this effective region are deleted. The effective region is larger than the actual dimensional measurements to avoid accidental deletion of valid points at the fracture edges. Next, noisy data is removed.

[0082] For example, set the neighborhood radius r = 0.05 mm, and calculate the number of neighboring points N within this radius for each data point; based on the point cloud density requirement (≥100 points / mm²), calculate the theoretical average number of neighboring points Navg = πr² × 100 ≈ 1.57, and set the noise judgment threshold Nth = 0.3Navg ≈ 0.47; if the number of neighboring points N < Nth, mark it as noise data and remove it.

[0083] Construct a projection matrix P, traverse all data points, and obtain the image point corresponding to each data point. The relationship between the data point and its corresponding image point satisfies the following formula 4.

[0084] Formula 4 In the formula, X represents the projection scale factor; P represents the data point; and P represents the projection matrix. This represents the image point corresponding to the data point.

[0085] During the regularization process, it is necessary to calibrate the viewpoint center point and establish a viewpoint imaging model. This viewpoint imaging model projects a point in a three-dimensional world space onto multiple projection planes to obtain point cloud data. In this model, spatial points are represented by homogeneous coordinates. Points mapped to the plane The '1' indicates the coordinate system. This point cloud data is used to represent connection points. The intersection of the line with the projection center and the plane, the above projection relationship satisfies the following formula 5.

[0086] Formula 5 Where P is a 3 A 4th-order matrix is ​​called a projection matrix, and the projection matrix satisfies the following formula 6.

[0087] Formula 6 Where K is the intrinsic parameter matrix, R represents the rotation matrix, and t represents the translation vector. K satisfies the following formula 7.

[0088] Formula 7 In the formula, f represents the distance between the observation point and the break point of the oil and gas pipeline in the horizontal direction; s represents the tilt factor of the coordinate axis in the world coordinate system; u represents the sum of the coordinates of the observation point on the projection plane; rf represents the distance between the observation point and the break point of the oil and gas pipeline in the direction perpendicular to the horizontal direction; and v represents the sum of the coordinates of the observation point on the projection plane.

[0089] By processing 2D and 3D data, the accuracy of subsequent 3D reconstruction can be guaranteed, invalid, noisy and redundant data can be removed, and standardized preprocessing of multi-source data can be achieved to provide high-quality data input for the next step.

[0090] It should be noted that the projection plane for voxel projection, the projection plane for vertex projection, and the projection plane for 3D data point projection can be the same or different projection planes. This application does not limit this.

[0091] In some embodiments, the above-mentioned method of obtaining a triangular mesh model based on a visual shell model and material property data using the Delaunay triangulation algorithm includes: constructing a set of points to be interpolated based on the surface point cloud and material property data of the visual shell model, the set of points to be interpolated including multiple points to be interpolated, the points to be interpolated being used to characterize each point cloud on the surface of the visual shell model and its corresponding material properties; filling the set of points to be interpolated using the Delaunay triangulation algorithm to obtain multiple triangular planes, each of the multiple triangular planes being a part of the fracture surface of an oil and gas pipeline; and constructing a triangular mesh model based on the multiple triangular planes.

[0092] For example, the set of points to be interpolated is P={ , ,…, The maximum span is calculated using the polar coordinates of all points in the interpolation point set P. This maximum span characterizes the distance between the two farthest points in the interpolation point set. A super triangle T0 is constructed with a side length of 1.5 times the maximum span, such that... Includes all points in P. For each point in the set of points to be interpolated... Determine the circumcircle within the triangular mesh. The influence triangle set { , ,…, }. Delete the common edges between the triangles in the set of triangles that affect them, forming a polygonal region. Then, set p... i Connecting to each vertex of the polygonal region forms a new set of triangles. , ,…, When an edge of a new triangle in the new triangle set coincides with an edge at the edge of a pipeline fracture, that edge is marked as a constraint edge, fixed, and not involved in subsequent optimization processes. For approximately collinear pipeline fracture edge points, the initial boundary is determined using the extreme angle method (minimum included angle ≥ 15°) to avoid mesh distortion. The new triangles in the new triangle set are validated using the Delaunay criterion to obtain multiple triangular planes. During the validation process, if the minimum interior angle of a new triangle is < 30°, the vertex connection method is adjusted until the minimum interior angle is ≥ 30° to improve the minimum interior angle and approach the "maximum minimum angle" characteristic.

[0093] After obtaining multiple triangular planes, super triangles and redundant meshes that exceed the bounding box are deleted to obtain a triangular mesh model.

[0094] The triangular mesh model obtained by the Delaunay triangulation algorithm achieves a mesh continuity rate of ≥99% in the sparse fracture region, which can solve the surface discretization problem of traditional reconstruction and thus improve the accuracy of the 3D reconstruction model.

[0095] In some embodiments, the above-mentioned construction of the interpolation point set based on the surface point cloud and material property data of the visual shell model includes: constructing a mapping relationship based on the material property data, the mapping relationship being used to indicate the correspondence between the coordinates of each point on the oil and gas pipeline fracture and the material properties of each point; and constructing the interpolation point set based on the surface point cloud and mapping relationship of the visual shell model.

[0096] As a concrete example, the 3D reconstruction model format supports STL / PLY to meet the measurement and visualization needs of subsequent failure analysis. The 3D reconstruction model has a dimensional error of ≤0.05mm and a defect detail (≥100μm) restoration accuracy of ≥95%, meeting the failure analysis requirements for identifying microscopic defects.

[0097] This application embodiment can divide the three-dimensional reconstruction device for pipe fractures into functional modules or functional units according to the above method example. For example, each function can be divided into a separate functional module or functional unit, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or in software functional modules or functional units. The module or unit division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0098] Figure 2 This is a schematic diagram of the structure of a three-dimensional reconstruction device 20 for pipeline fractures provided in an embodiment of this application. The three-dimensional reconstruction device 20 for pipeline fractures includes: an acquisition unit 201, used to acquire three-dimensional data of the oil and gas pipeline fracture, an image of the oil and gas pipeline fracture, and material property data of the oil and gas pipeline fracture, wherein the material property data is used to indicate the material property data corresponding to the boundary of the oil and gas pipeline fracture; a construction unit 202, used to construct a visual shell model of the oil and gas pipeline fracture based on the three-dimensional data and the image of the oil and gas pipeline fracture; an interpolation unit 203, used to obtain a triangular mesh model based on the visual shell model and the material property data using the Delaunay triangulation algorithm; and a correction unit 204, used to correct the vertices of the triangular mesh model to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture, wherein the three-dimensional reconstruction model is used to characterize the shape of the oil and gas pipeline fracture and the material properties corresponding to each position in the oil and gas pipeline fracture.

[0099] In some embodiments, the correction unit 204 is configured to: project each vertex in the triangular mesh model to obtain multiple vertex projection positions; determine the cross-correlation coefficient of each vertex based on the gray level of each vertex and the gray level of the neighborhood window corresponding to the projection position of each vertex, wherein the neighborhood window corresponding to the projection position of each vertex includes the projection position of the vertex, and the cross-correlation coefficient is used to characterize whether the gray level of the vertex is consistent with the gray level of the neighborhood window; determine the vertex as a distortion point in response to the cross-correlation coefficient being less than the cross-correlation threshold; and adjust the position of the distortion point to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture.

[0100] In some embodiments, the correction unit 204 is used to: determine the target vertex in the non-distortion points with the distortion point as the center; perform a weighted average of the position of the target vertex and the cross-correlation coefficient of the target vertex to obtain the adjusted position, which is used to correct the distortion point; and construct a three-dimensional reconstruction model of the oil and gas pipeline fracture based on the adjusted position and the positions of the non-distortion points.

[0101] In some embodiments, the above-described apparatus further includes: an adjustment unit, configured to readjust the adjustment position when adjustment conditions are met; wherein the adjustment conditions satisfy at least one of the following: the cross-correlation coefficient of the adjustment position is less than a cross-correlation threshold; the ratio of the number of adjustment positions with cross-correlation coefficients less than the cross-correlation threshold to the total number of vertices in the 3D reconstruction model is greater than a ratio threshold; the mean of the cross-correlation coefficients of all vertices in the 3D reconstruction model is less than a mean threshold; and the number of adjustments to the distortion points is less than or equal to a number threshold.

[0102] In some embodiments, the construction unit 202 is used to: project the three-dimensional data of the oil and gas pipeline fracture and the two-dimensional data corresponding to the image of the oil and gas pipeline fracture onto multiple projection planes to obtain point cloud data of the oil and gas pipeline fracture; construct a bounding box based on the point cloud data of the oil and gas pipeline fracture, the bounding box being used to enclose the point cloud data of the oil and gas pipeline fracture in three-dimensional space; perform voxelization processing on the bounding box according to a preset voxel resolution to obtain multiple voxels; project each voxel onto multiple projection planes to obtain a projected image of the voxel; in response to the overlap between the projected image of the voxel and the region formed by the fracture contour of the oil and gas pipeline fracture, determine the voxel as a target voxel; construct a voxel set based on the target voxels, and perform morphological closing operation processing on the voxel set to obtain a visual shell model.

[0103] In some embodiments, the interpolation unit 203 is used to: construct a set of points to be interpolated based on the surface point cloud and material property data of the visual shell model, the set of points to be interpolated including multiple points to be interpolated, the points to be interpolated being used to characterize each point cloud on the surface of the visual shell model and its corresponding material properties; fill the set of points to be interpolated using the Delaunay triangulation algorithm to obtain multiple triangular planes, each of the multiple triangular planes being a part of the fracture surface of the oil and gas pipeline; and construct a triangular mesh model based on the multiple triangular planes.

[0104] Through the above description of the embodiments, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0105] When implemented in hardware, the various modules of the pipe fracture 3D reconstruction device can be integrated into, for example... Figure 3 This is implemented in the hardware structure of the electronic device shown. Specifically, as... Figure 3 As shown, the basic hardware structure of electronic devices is introduced.

[0106] Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Figure 3 As shown, the electronic device includes at least one processor 301, a communication line 302, and at least one communication interface 304, and may also include a memory 303. The processor 301, memory 303, and communication interface 304 are connected via the communication line 302.

[0107] The processor 301 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0108] Communication line 302 may include a path for transmitting information between the aforementioned components.

[0109] Communication interface 304 is used to communicate with other devices or communication networks. It can use any transceiver-like device, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0110] The memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of including or storing desired program code having the form of instructions or data structures and capable of being accessed by a computer, but not limited thereto.

[0111] In one possible design, the memory 303 can exist independently of the processor 301, meaning the memory 303 can be an external memory of the processor 301. In this case, the memory 303 can be connected to the processor 301 via a communication line 302 to store execution instructions or application code, and its execution is controlled by the processor 301 to implement the pipe fracture three-dimensional reconstruction method provided in the following embodiments of this application. In another possible design, the memory 303 can also be integrated with the processor 301, meaning the memory 303 can be an internal memory of the processor 301. For example, the memory 303 can be a cache, which can be used to temporarily store some data and instruction information.

[0112] As one possible implementation, processor 301 may include one or more CPUs, for example Figure 3 CPU0 and CPU1 in the example. As another possible implementation, the electronic device may include multiple processors, such as... Figure 3 The processors 301 and 307 are included. As another possible implementation, the electronic device may also include an output device 305 and an input device 306.

[0113] This application provides a computer program product containing instructions that, when run on a computer, cause the computer to execute the three-dimensional reconstruction method of pipe fracture described in the above method embodiments.

[0114] This application also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the pipe fracture three-dimensional reconstruction method in the method flow shown in the above method embodiment.

[0115] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires; a portable computer disk drive; a hard disk drive; random access memory (RAM); read-only memory (ROM); erasable programmable read-only memory (EPROM); a register; a hard disk drive; an optical fiber; a compact disc read-only memory (CD-ROM); an optical storage device; a magnetic storage device; or any suitable combination thereof; or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may reside in an application-specific integrated circuit (ASIC). In the embodiments of this application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0116] Since the pipe fracture three-dimensional reconstruction device, electronic device, computer-readable storage medium, and computer program product in the embodiments of this application can be applied to the above method, the technical effects that can be obtained can also be referred to the above method embodiments. The embodiments of this application will not be repeated here.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0118] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0119] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0120] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for three-dimensional reconstruction of a pipe break, characterized in that, The method includes: The three-dimensional data of the oil and gas pipeline fracture, the image of the oil and gas pipeline fracture, and the material property data of the oil and gas pipeline fracture are obtained. The material property data is used to indicate the material property data corresponding to the boundary of the oil and gas pipeline fracture. Based on the three-dimensional data and images of the oil and gas pipeline fracture, a visual shell model of the oil and gas pipeline fracture is constructed. Based on the visual shell model and the material property data, a triangular mesh model is obtained using the Delaunay triangulation algorithm. The vertices of the triangular mesh model are corrected to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture. The three-dimensional reconstruction model is used to characterize the shape of the oil and gas pipeline fracture and the material properties corresponding to each position in the oil and gas pipeline fracture.

2. The method of claim 1, wherein, The process of correcting the vertices of the triangular mesh model to obtain the three-dimensional reconstruction model of the oil and gas pipeline fracture includes: Projecting each vertex in the triangular mesh model yields the projected positions of multiple vertices; For each vertex in the projection positions of the plurality of vertices, based on the gray level of each vertex and the gray level of the neighborhood window corresponding to the projection position of each vertex, a cross-correlation number is determined for each vertex. The neighborhood window corresponding to the projection position of each vertex includes the projection position of the vertex. The cross-correlation number is used to characterize whether the gray level of the vertex is consistent with the gray level of the neighborhood window. In response to the cross-correlation coefficient being less than the cross-correlation threshold, the vertex is identified as a distortion point; The positions of the distortion points are adjusted to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture.

3. The method of claim 2, wherein, The process of adjusting the position of the distortion points to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture includes: Using the distortion point as the center, determine the target vertex among the non-distortion points; The adjusted position is obtained by weighted averaging the position of the target vertex and the cross-correlation coefficient of the target vertex, and the adjusted position is used to correct the distortion point; Based on the adjusted position and the position of the non-distortion point, a three-dimensional reconstruction model of the oil and gas pipeline fracture is constructed.

4. The method of claim 3, wherein, The method further includes: If the adjustment conditions are met, the adjustment position is readjusted. Wherein, the adjustment condition satisfies at least one of the following: The cross-correlation coefficient of the adjusted position is less than the cross-correlation threshold; The ratio of the number of adjustment positions with cross-correlation coefficients less than the cross-correlation threshold to the total number of vertices in the 3D reconstruction model is greater than the ratio threshold. The mean cross-correlation coefficient of all vertices in the three-dimensional reconstruction model is less than the mean threshold. The number of adjustments to the distortion point is less than or equal to the number threshold.

5. The method of claim 1, wherein, The construction of a visual shell model of the oil and gas pipeline fracture based on the 3D data and image of the fracture includes: The three-dimensional data of the oil and gas pipeline fracture and the two-dimensional data corresponding to the image of the oil and gas pipeline fracture are projected onto multiple projection planes to obtain the point cloud data of the oil and gas pipeline fracture. A bounding box is constructed based on the point cloud data of the oil and gas pipeline break, and the bounding box is used to enclose the point cloud data of the oil and gas pipeline break in three-dimensional space. The bounding box is voxelized according to a preset voxel resolution to obtain multiple voxels; In the plurality of voxels, each voxel is projected onto the plurality of projection planes to obtain a projected image of the voxel; In response to the overlap between the projected image of the voxel and the area formed by the fracture outline of the oil and gas pipeline fracture, the voxel is identified as the target voxel. A voxel set is constructed based on the target voxel, and morphological closing operations are performed on the voxel set to obtain the visual shell model.

6. The method of claim 1, wherein, The process of obtaining a triangular mesh model based on the visual shell model and the material property data using the Delaunay triangulation algorithm includes: Based on the surface point cloud of the visual shell model and the material property data, a set of interpolation points is constructed. The set of interpolation points includes multiple interpolation points, which are used to characterize each point cloud on the surface of the visual shell model and its corresponding material properties. The set of points to be interpolated is filled by the Delaunay triangulation algorithm to obtain multiple triangular planes, each of which is a part of the surface of the oil and gas pipeline fracture. The triangular mesh model is constructed based on the multiple triangular planes.

7. A pipeline break three-dimensional reconstruction device, characterized in that, The device includes: The acquisition unit is used to acquire three-dimensional data of the oil and gas pipeline fracture, an image of the oil and gas pipeline fracture, and material property data of the oil and gas pipeline fracture. The material property data is used to indicate the material property data corresponding to the boundary of the oil and gas pipeline fracture. A construction unit is used to construct a visual shell model of the oil and gas pipeline fracture based on the three-dimensional data and the image of the oil and gas pipeline fracture. An interpolation unit is used to obtain a triangular mesh model based on the visual shell model and the material property data using the Delaunay triangulation algorithm. The correction unit is used to correct the vertices of the triangular mesh model to obtain a three-dimensional reconstruction model of the oil and gas pipeline fracture. The three-dimensional reconstruction model is used to characterize the shape of the oil and gas pipeline fracture and the material properties corresponding to each position in the oil and gas pipeline fracture.

8. An electronic device, comprising: include: A processor and a communication interface; the communication interface is coupled to the processor, the processor being configured to run computer programs or instructions to implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed by a computer, perform the method as described in any one of claims 1-6.

10. A computer program product, characterised in that, The computer program product includes computer instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1-6.

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