Comprehensive pipeline collision detection method and system

Abstract

The invention relates to a comprehensive pipeline collision detection method and system, and the method comprises the steps: obtaining a three-dimensional model of a pipeline, and carrying out the self-adaption segmentation according to the bending degree if the pipeline is a bent pipe; extracting the central axis of the pipeline, determining the density of the pipeline according to the pipeline distribution and complexity, if the pipeline distribution is sparse, establishing a capsule body by using the central axis, and screening out the pipeline which may collide through coarse collision detection according to the capsule body; if the pipelines are densely distributed, screening out the pipelines which may collide by combining a bounding box based on a spatial index method; a certain number of points are sampled on the surfaces of the two possibly collided pipelines according to the curvature and complexity of the pipelines to obtain two point sets, whether collision points exist or not is determined according to distribution of elements in the two point sets, and if the collision points exist, the collision points are displayed in the three-dimensional model of the pipelines.

Description

Technical Field

[0001] The present invention relates to the field of pipelines, and in particular to a comprehensive pipeline collision detection method and system. Background Art

[0002] Building Information Modeling (BIM) plays an important role in improving design quality, reducing construction rework, and reducing project costs. Pipeline collision detection, as an important link, is a key technology to ensure the quality of design and construction and avoid construction conflicts and errors. Traditional collision detection methods are mainly based on static analysis of geometric models, and usually use simple geometric bodies for collision detection. However, this method often suffers from false detection and missed detection when faced with complex pipeline layouts and changing design requirements. Moreover, with the continuous increase in building scale and the increase in design complexity, traditional collision detection methods have huge computational complexity and low efficiency when processing large-scale data, and cannot meet the needs of real-time detection and collaborative design. Summary of the invention

[0003] In view of the problem of complex calculation process in current pipeline network collision detection, the present invention provides a comprehensive pipeline collision detection method in a first aspect, the method comprising: Obtain the 3D model of the pipeline. If the pipeline is a curved pipe, adaptively segment it according to the degree of curvature. Extract the central axis of the pipeline and determine the density of the pipeline according to the distribution and complexity of the pipeline. If the pipeline is sparsely distributed, use the central axis to establish a capsule body, and use the capsule body to screen out the pipelines that may collide through rough collision detection. If the pipeline is densely distributed, use the spatial index method combined with the bounding box to screen out the pipelines that may collide. A certain number of points are sampled on the surfaces of two pipelines that may collide according to the curvature and complexity of the pipelines to obtain two point sets. Whether there is a collision point is determined based on the distribution of elements in the two point sets. If there is a collision point, the collision point is displayed in the three-dimensional model of the pipeline.

[0004] Preferably, the determining whether there is a collision point according to the distribution of elements in the two point sets is specifically: Take one of the two point sets as the target point set and the other as the source point set, and record the pipelines corresponding to the target point set and the pipelines corresponding to the source point set; Subtract the points selected from the source point set from all elements in the target point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the source point set and repeat the above operation to obtain the collision point set of the source point set. Subtract the points selected from the target point set from all elements in the source point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the target point set and repeat the above operation to obtain the collision point set of the target point set. If the collision point set of the source point set and / or the collision point set of the target point set is not empty, then there is a collision point.

[0005] Preferably, the adaptive segmentation according to the bending degree is specifically: Obtain the central axis of the pipeline, discretize the central axis of the pipeline into a series of ordered points, and calculate the curvature of each point on the central axis; Initialize the first point of the ordered points in the pipeline as the starting point; If the curvature of the current point is greater than the threshold and the distance between the current point and the starting point is greater than the preset value, the part between the initial point and the previous point of the current point is taken as a segment, and the current point is taken as the starting point, and the segmentation judgment process is repeated; After the traversal is completed, the area between the last starting point and the end point of the pipeline is added to the segmentation result as a segment segment.

[0006] Preferably, the pipeline density is determined according to the pipeline distribution and complexity, specifically: Obtain the central axis of the pipeline and calculate the directional consistency of the central axis of the pipeline; If the directional consistency meets the preset conditions, the pipeline density is marked as sparse; otherwise, the average distance of the central axis of the pipeline is calculated, and whether the pipeline is sparse or dense is determined based on the directional consistency and the average distance.

[0007] Preferably, determining whether the pipeline is sparse according to the directional consistency and the average distance is specifically: The average distance is normalized using the average diameter of the pipeline. If the directional consistency is less than the predetermined directional value and the normalized average distance is greater than the predetermined distance value, the pipeline is identified as sparse; otherwise, the pipeline is identified as dense.

[0008] In a second aspect of the present invention, a comprehensive pipeline collision detection system is provided, the system comprising: The rough collision detection module is used to obtain the three-dimensional model of the pipeline. If the pipeline is a curved pipe, it is segmented adaptively according to the degree of curvature; the central axis of the pipeline is extracted, and the density of the pipeline is determined according to the distribution and complexity of the pipeline. If the pipeline is sparsely distributed, a capsule body is established using the central axis, and the possible collision pipelines are screened out through rough collision detection based on the capsule body; if the pipeline is densely distributed, the spatial index method combined with the bounding box is used to screen out the possible collision pipelines; The fine collision detection module is used to sample a certain number of points on the surfaces of two pipelines that may collide according to the curvature and complexity of the pipelines to obtain two point sets, and determine whether there is a collision point based on the distribution of elements in the two point sets. If there is a collision point, the collision point is displayed in the three-dimensional model of the pipeline.

[0009] Preferably, the determining whether there is a collision point according to the distribution of elements in the two point sets is specifically: Take one of the two point sets as the target point set and the other as the source point set, and record the pipelines corresponding to the target point set and the pipelines corresponding to the source point set; Subtract the points selected from the source point set from all elements in the target point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the source point set and repeat the above operation to obtain the collision point set of the source point set. Subtract the points selected from the target point set from all elements in the source point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the target point set and repeat the above operation to obtain the collision point set of the target point set. If the collision point set of the source point set and / or the collision point set of the target point set is not empty, then there is a collision point.

[0010] Preferably, the adaptive segmentation according to the bending degree is specifically: Obtain the central axis of the pipeline, discretize the central axis of the pipeline into a series of ordered points, and calculate the curvature of each point on the central axis; Initialize the first point of the ordered points in the pipeline as the starting point; If the curvature of the current point is greater than the threshold and the distance between the current point and the starting point is greater than the preset value, the part between the initial point and the previous point of the current point is taken as a segment, and the current point is taken as the starting point, and the segmentation judgment process is repeated; After the traversal is completed, the area between the last starting point and the end point of the pipeline is added to the segmentation result as a segment segment.

[0011] Preferably, the pipeline density is determined according to the pipeline distribution and complexity, specifically: Obtain the central axis of the pipeline and calculate the directional consistency of the central axis of the pipeline; If the directional consistency meets the preset conditions, the pipeline density is marked as sparse; otherwise, the average distance of the central axis of the pipeline is calculated, and whether the pipeline is sparse or dense is determined based on the directional consistency and the average distance.

[0012] Preferably, determining whether the pipeline is sparse according to the directional consistency and the average distance is specifically: The average distance is normalized using the average diameter of the pipeline. If the directional consistency is less than the predetermined directional value and the normalized average distance is greater than the predetermined distance value, the pipeline is identified as sparse; otherwise, the pipeline is identified as dense.

[0013] The present invention determines different rough collision detection methods according to the density of pipelines. In sparse scenes, simple capsule detection is used, and in dense scenes, a spatial index method combined with a bounding box is used, which can avoid unnecessary calculations and improve performance. In the fine collision detection stage, by analyzing the spatial distribution of the difference between two point sets, not only can it be accurately determined whether there is a collision, but also the collision point can be identified, and then the collision point can be marked in the pipeline model, which is convenient for engineers to adjust the pipeline. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the process of embodiment 1; Figure 2 A schematic diagram for segmenting the pipeline; Figure 3 Schematic diagram of AABB bounding box and OBB bounding box; Figure 4 It is a structural diagram of embodiment 2. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] Embodiment 1 provides a comprehensive pipeline collision detection method, such as Figure 1 As shown, the method includes: S1, obtain the three-dimensional model of the pipeline. If the pipeline is a curved pipe, it is segmented adaptively according to the degree of curvature; extract the central axis of the pipeline, determine the density of the pipeline according to the distribution and complexity of the pipeline, if the pipeline is sparsely distributed, use the central axis to establish a capsule body, and use the capsule body to screen out the pipelines that may collide through rough collision detection; if the pipeline is densely distributed, use the spatial index method combined with the bounding box to screen out the pipelines that may collide; In collision detection, first obtain the geometric representation of the pipeline in three-dimensional space, that is, the three-dimensional model of the pipeline. The three-dimensional model contains information such as the shape, size, and position of the pipeline. If the pipeline is curved, divide it into several relatively simple sections. The more severe the bend, the finer the segmentation; the gentler the bend, the coarser the segmentation, thereby avoiding unnecessary computational overhead. For example, if a section of a pipe with a large bend is represented by only one whole section, it is difficult to accurately approximate it with simple geometric bodies (such as straight lines and cylinders). After being divided into multiple sections, each section can be approximately regarded as a straight line or arc, which is convenient for subsequent processing. Compared with other objects, the shape of the pipeline is relatively fixed. The central axis is a line connecting the geometric center of the pipeline, which can simplify the geometric representation of the pipeline. For example, for a straight pipe, the central axis is a straight line; for a curved pipe, the central axis is a curve. The distribution density of pipelines is different, and the rough collision detection method is also different. Specifically, if the number of pipelines is small, the distance between them is far, and the shape is simple, the pipeline distribution is sparse; if the number of pipelines is large, and the distance between them is close, or the shape is very complex and entangled with each other, the pipeline distribution is dense.

[0017] For sparsely distributed pipelines, a capsule is established using the central axis. By detecting whether the capsules intersect, it is possible to quickly determine whether the pipelines may collide. For densely distributed pipelines, a spatial index-based method combined with an AABB bounding box is used; wherein, the spatial index includes but is not limited to an octree, a KD tree, etc., and the AABB bounding box is the smallest axis-aligned bounding box used to quickly determine whether two objects may intersect. For densely distributed pipelines, first use the spatial index to quickly find spatially adjacent pipelines, then use the AABB bounding box for preliminary screening, and finally perform more accurate collision detection.

[0018] In an optional embodiment, the adaptive segmentation according to the bending degree is specifically: Obtain the central axis of the pipeline, discretize the central axis of the pipeline into a series of ordered points, and calculate the curvature of each point on the central axis; Initialize the first point of the ordered points in the pipeline as the starting point; If the curvature of the current point is greater than the threshold and the distance between the current point and the starting point is greater than the preset value, the part between the initial point and the previous point of the current point is taken as a segment, and the current point is taken as the starting point, and the segmentation judgment process is repeated; After the traversal is completed, the area between the last starting point and the end point of the pipeline is added to the segmentation result as a segment.

[0019] Extract the central axis of the pipeline and discretize the continuous central axis into a series of ordered points, such as Figure 2As shown in the figure, for each point, its curvature is calculated, and the distance from the current point to the starting point is calculated. The curvature threshold is used to determine whether the curvature is large enough. If the curvature of the current point is greater than the threshold, it is considered that the curve near the point is more severely curved and needs to be segmented; the distance threshold is used to control the minimum length of the segmentation. Even if the curvature of the current point is large, if it is very close to the starting point, it will not be segmented to avoid too short segment segments. When a segment segment is obtained, the current point is used as the starting point, and the remaining part is re-segmented, that is, whether to segment is re-determined. After traversing all points, the part between the last starting point and the end point of the pipeline is added to the segmentation result as a segment segment. Each segment segment is used as a pipeline for subsequent calculations.

[0020] In an optional embodiment, the pipeline density is determined according to the pipeline distribution and complexity, specifically: Obtain the central axis of the pipeline and calculate the directional consistency of the central axis of the pipeline; If the directional consistency meets the preset conditions, the pipeline density is marked as sparse; otherwise, the average distance of the central axis of the pipeline is calculated, and whether the pipeline is sparse or dense is determined based on the directional consistency and the average distance.

[0021] Get the central axis of all pipelines and calculate the directional consistency of these central axis. If all pipelines extend roughly in the same direction, the directional consistency is high; if the pipelines are in a disorderly direction, the directional consistency is low. If the calculated directional consistency meets the preset conditions, such as being less than a certain value, the density of the pipelines is directly marked as sparse. Since they are in the same direction, collision is not likely to occur on the one hand, and on the other hand, the capsule method can be used to roughly determine whether a collision is possible, without the need for complex rough collision detection.

[0022] If the directional consistency does not meet the preset conditions, it is necessary to further calculate the average distance between the central axes of the pipelines. Specifically, even if the directional consistency is not high, if the average distance between the pipelines is large enough, the pipelines can be considered sparse. In one embodiment, the directional consistency is obtained by calculating the angle of the axis. The smaller the angle, the higher the consistency. In one embodiment, the determination of whether the pipeline is sparse based on the directional consistency and the average distance is specifically as follows: the average distance is normalized using the average diameter of the pipeline. If the directional consistency is less than the predetermined value of the direction and the average distance after normalization is greater than the predetermined value of the distance, the pipeline is identified as sparse, otherwise, the pipeline is identified as dense. Calculate the average diameter of all pipelines and perform a normalization operation, that is, divide the calculated average distance by the average diameter to obtain a relative distance value, where the predetermined value of the direction is greater than the value in the preset conditions. Only when the directional consistency is less than the predetermined value of the direction and the average distance after normalization is greater than the predetermined value of the distance, the pipeline will be identified as sparse. In other cases, the pipeline will be identified as dense. In a specific embodiment, the system automatically treats the pipelines in an area as a whole to determine whether the pipelines as a whole are dense or sparse. The average distance of the central axes is obtained by averaging the shortest distance between the central axes of two pipelines.

[0023] In an alternative embodiment, sparse or dense is manually divided by the user in the three-dimensional model, that is, for dense areas, they are manually marked as dense, and a spatial index-based method combined with a bounding box is used to filter out pipelines that may collide; for sparse areas, they are manually marked as sparse, and a capsule is used to filter out pipelines that may collide.

[0024] In one embodiment, a spatial index method combined with a bounding box is used to filter out pipelines that may collide. Specifically, an OBB bounding box is created for all pipelines, wherein the OBB bounding box is similar to the AABB bounding box. The AABB bounding box and the OBB bounding box are as follows: Figure 3 As shown. Then, an octree is constructed, that is, the scene space is recursively divided into eight sub-cubes, and the cube nodes containing the pipeline OBB bounding boxes are stored in the tree; when performing collision detection, for each pipeline, the octree node where its OBB is located is determined, and then other pipelines are searched only in this node and its adjacent nodes, and OBB intersection detection is used for preliminary screening. If the OBBs of two pipelines do not intersect, then the two pipelines have not collided. Only when the OBBs of two pipelines intersect, then the pair of pipelines may collide. In one embodiment, the bounding box area in the area of ​​the octree node is found, and then the OBB areas of other pipelines are searched in this node and its adjacent nodes for rough collision detection. In an alternative embodiment, for dense areas, the k-DOP method is used for rough collision detection.

[0025] S2, a certain number of points are sampled on the surfaces of two pipelines that may collide according to the curvature and complexity of the pipelines to obtain two point sets, and whether there is a collision point is determined according to the distribution of elements in the two point sets. If there is a collision point, the collision point is displayed in the three-dimensional model of the pipeline.

[0026] In places where the pipeline is relatively curved and complex, it is more complicated to judge the collision. Generally speaking, the greater the curvature of the pipeline and the higher the complexity, the more points are collected. In one possible embodiment, the curvature of the central axis of the pipeline is used as the curvature of the pipeline, and the change of the normal vector of the area on the surface of the pipeline is used as the complexity. If the curvature is greater and the complexity is greater, the density of the collected points is greater. In another possible embodiment, the pipeline surface is first uniformly sampled, and then the density of the points in the local area is increased according to the curvature change rate of the local area.

[0027] After obtaining the point sets of the two pipelines that may collide, further determine whether a collision occurs based on the two point sets. In one embodiment, a GLK collision detection method is used to determine whether a collision point exists. In order to accurately determine the collision point, in another optional embodiment, the determination of whether a collision point exists based on the distribution of elements in the two point sets is specifically: Take one of the two point sets as the target point set and the other as the source point set, and record the pipelines corresponding to the target point set and the pipelines corresponding to the source point set; Subtract the points selected from the source point set from all elements in the target point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the source point set and repeat the above operation to obtain the collision point set of the source point set. Subtract the points selected from the target point set from all elements in the source point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the target point set and repeat the above operation to obtain the collision point set of the target point set. If the collision point set of the source point set and / or the collision point set of the target point set is not empty, then there is a collision point.

[0028] When judging whether two pipelines collide, the point set corresponding to one pipeline is used as the target point set, and the point set corresponding to the other pipeline is used as the source point set. All elements in the target point set are subtracted from the selected point. The subtraction here refers to the subtraction of coordinates or positions. For example, there are 10 points in the target point set, and the coordinates of one point are (2, 5, 12). A point is selected from the source point set and the coordinates are assumed to be (12, 4, 2). After subtraction, it is (-10, 1, 10).

[0029] The three-dimensional space is divided into eight quadrants and six coordinate axes. The points in the calculation results closest to the origin on each quadrant and each coordinate axis are found. It is determined whether the area enclosed by these points contains the origin. If the origin is included, it means that point (12, 4, 2) collides with the pipeline represented by the target point set, so point (12, 4, 2) is marked as a collision point. If the enclosed area does not contain the origin, it means that point (12, 4, 2) does not collide with the pipeline represented by the target point set. The next point is selected from the source point set and the above operation is repeated. In the same way, the collision points in the target point set can be obtained, which will not be repeated here. As long as the collision point set of the source point set or the collision point set of the target point set is not empty, it means that there is a collision point. In other words, as long as the point considered to be a collision is found in one of the point sets, it can be determined that the two pipelines have collided. If both sets are empty, it means that no collision is detected. This method can not only detect whether a collision occurs, but also obtain the collision point, which is convenient for engineers to adjust the pipeline.

[0030] Embodiment 2 provides a comprehensive pipeline collision detection system, such as Figure 4 As shown, the system comprises: The rough collision detection module 201 is used to obtain the three-dimensional model of the pipeline. If the pipeline is a curved pipe, it is segmented adaptively according to the degree of curvature; the central axis of the pipeline is extracted, and the density of the pipeline is determined according to the distribution and complexity of the pipeline. If the pipeline is sparsely distributed, a capsule body is established using the central axis, and the pipelines that may collide are screened out through rough collision detection based on the capsule body; if the pipeline is densely distributed, a spatial index-based method combined with a bounding box is used to screen out the pipelines that may collide; The fine collision detection module 202 is used to sample a certain number of points on the surfaces of two pipelines that may collide according to the curvature and complexity of the pipelines to obtain two point sets, determine whether there is a collision point according to the distribution of elements in the two point sets, and if there is a collision point, display the collision point in the three-dimensional model of the pipeline.

[0031] Preferably, the determining whether there is a collision point according to the distribution of elements in the two point sets is specifically: Take one of the two point sets as the target point set and the other as the source point set, and record the pipelines corresponding to the target point set and the pipelines corresponding to the source point set; Subtract the points selected from the source point set from all elements in the target point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the source point set and repeat the above operation to obtain the collision point set of the source point set. Subtract the points selected from the target point set from all elements in the source point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the target point set and repeat the above operation to obtain the collision point set of the target point set. If the collision point set of the source point set and / or the collision point set of the target point set is not empty, then there is a collision point.

[0032] Preferably, the adaptive segmentation according to the bending degree is specifically: Obtain the central axis of the pipeline, discretize the central axis of the pipeline into a series of ordered points, and calculate the curvature of each point on the central axis; Initialize the first point of the ordered points in the pipeline as the starting point; If the curvature of the current point is greater than the threshold and the distance between the current point and the starting point is greater than the preset value, the part between the initial point and the previous point of the current point is taken as a segment, and the current point is taken as the starting point, and the segmentation judgment process is repeated; After the traversal is completed, the area between the last starting point and the end point of the pipeline is added to the segmentation result as a segment segment.

[0033] Preferably, the pipeline density is determined according to the pipeline distribution and complexity, specifically: Obtain the central axis of the pipeline and calculate the directional consistency of the central axis of the pipeline; If the directional consistency meets the preset conditions, the pipeline density is marked as sparse; otherwise, the average distance of the central axis of the pipeline is calculated, and whether the pipeline is sparse or dense is determined based on the directional consistency and the average distance.

[0034] Preferably, determining whether the pipeline is sparse according to the directional consistency and the average distance is specifically: The average distance is normalized using the average diameter of the pipeline. If the directional consistency is less than the predetermined directional value and the normalized average distance is greater than the predetermined distance value, the pipeline is identified as sparse; otherwise, the pipeline is identified as dense.

[0035] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

Claims

1. A comprehensive pipeline collision detection method, characterized in that: The method comprises: Obtain the 3D model of the pipeline. If the pipeline is a curved pipe, adaptively segment it according to the degree of curvature. Extract the central axis of the pipeline and determine the density of the pipeline according to the distribution and complexity of the pipeline. If the pipeline is sparsely distributed, use the central axis to establish a capsule body, and use the capsule body to screen out the pipelines that may collide through rough collision detection. If the pipeline is densely distributed, use the spatial index method combined with the bounding box to screen out the pipelines that may collide. A certain number of points are sampled on the surfaces of two pipelines that may collide according to the curvature and complexity of the pipelines to obtain two point sets. Whether there is a collision point is determined based on the distribution of elements in the two point sets. If there is a collision point, the collision point is displayed in the three-dimensional model of the pipeline.

2. The method according to claim 1, characterized in that The determination of whether there is a collision point according to the distribution of elements in the two point sets is specifically as follows: Take one of the two point sets as the target point set and the other as the source point set, and record the pipelines corresponding to the target point set and the pipelines corresponding to the source point set; Subtract the points selected from the source point set from all elements in the target point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the source point set and repeat the above operation to obtain the collision point set of the source point set. Subtract the points selected from the target point set from all elements in the source point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the target point set and repeat the above operation to obtain the collision point set of the target point set. If the collision point set of the source point set and / or the collision point set of the target point set is not empty, then there is a collision point.

3. The method according to claim 1, characterized in that The adaptive segmentation according to the bending degree is specifically as follows: Obtain the central axis of the pipeline, discretize the central axis of the pipeline into a series of ordered points, and calculate the curvature of each point on the central axis; Initialize the first point of the ordered points in the pipeline as the starting point; If the curvature of the current point is greater than the threshold and the distance between the current point and the starting point is greater than the preset value, the part between the initial point and the previous point of the current point is taken as a segment, and the current point is taken as the starting point, and the segmentation judgment process is repeated; After the traversal is completed, the area between the last starting point and the end point of the pipeline is added to the segmentation result as a segment segment.

4. The method according to claim 1, characterized in that The pipeline density is determined according to the pipeline distribution and complexity, specifically: Obtain the central axis of the pipeline and calculate the directional consistency of the central axis of the pipeline; If the directional consistency meets the preset conditions, the pipeline density is marked as sparse; Otherwise, the average distance of the central axis of the pipeline is calculated, and whether the pipeline is sparse or dense is determined according to the directional consistency and the average distance.

5. The method according to claim 4, characterized in that The determining whether the pipeline is sparse according to the directional consistency and the average distance is specifically as follows: The average distance is normalized using the average diameter of the pipeline. If the directional consistency is less than the predetermined directional value and the normalized average distance is greater than the predetermined distance value, the pipeline is identified as sparse; otherwise, the pipeline is identified as dense.

6. A comprehensive pipeline collision detection system, characterized in that: The system comprises: The rough collision detection module is used to obtain the three-dimensional model of the pipeline. If the pipeline is a curved pipe, it is segmented adaptively according to the degree of curvature; the central axis of the pipeline is extracted, and the density of the pipeline is determined according to the distribution and complexity of the pipeline. If the pipeline is sparsely distributed, a capsule body is established using the central axis, and the possible collision pipelines are screened out through rough collision detection based on the capsule body; if the pipeline is densely distributed, the spatial index method combined with the bounding box is used to screen out the possible collision pipelines; The fine collision detection module is used to sample a certain number of points on the surfaces of two pipelines that may collide according to the curvature and complexity of the pipelines to obtain two point sets, and determine whether there is a collision point based on the distribution of elements in the two point sets. If there is a collision point, the collision point is displayed in the three-dimensional model of the pipeline.

7. The system according to claim 6, characterized in that The determination of whether there is a collision point according to the distribution of elements in the two point sets is specifically as follows: Take one of the two point sets as the target point set and the other as the source point set, and record the pipelines corresponding to the target point set and the pipelines corresponding to the source point set; Subtract the points selected from the source point set from all elements in the target point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the source point set and repeat the above operation to obtain the collision point set of the source point set. Subtract the points selected from the target point set from all elements in the source point set. If the area enclosed by each quadrant and the point closest to the origin on the coordinate axis in the calculation result covers the origin, the selected point is marked as the collision point. Otherwise, continue to select points from the target point set and repeat the above operation to obtain the collision point set of the target point set. If the collision point set of the source point set and / or the collision point set of the target point set is not empty, then there is a collision point.

8. The system according to claim 6, characterized in that The adaptive segmentation according to the bending degree is specifically as follows: Obtain the central axis of the pipeline, discretize the central axis of the pipeline into a series of ordered points, and calculate the curvature of each point on the central axis; Initialize the first point of the ordered points in the pipeline as the starting point; If the curvature of the current point is greater than the threshold and the distance between the current point and the starting point is greater than the preset value, the part between the initial point and the previous point of the current point is taken as a segment, and the current point is taken as the starting point, and the segmentation judgment process is repeated; After the traversal is completed, the area between the last starting point and the end point of the pipeline is added to the segmentation result as a segment segment.

9. The system according to claim 6, characterized in that The pipeline density is determined according to the pipeline distribution and complexity, specifically: Obtain the central axis of the pipeline and calculate the directional consistency of the central axis of the pipeline; If the directional consistency meets the preset conditions, the pipeline density is marked as sparse; Otherwise, the average distance of the central axis of the pipeline is calculated, and whether the pipeline is sparse or dense is determined according to the directional consistency and the average distance.

10. The system according to claim 9, characterized in that The determining whether the pipeline is sparse according to the directional consistency and the average distance is specifically as follows: The average distance is normalized using the average diameter of the pipeline. If the directional consistency is less than the predetermined directional value and the normalized average distance is greater than the predetermined distance value, the pipeline is identified as sparse; otherwise, the pipeline is identified as dense.

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